update新结构

docs/README.md

@@ -1,37 +0,0 @@
-# Documentation Index
-
-This folder tracks project decisions, experiments, and evolving ideas.
-
-- `decisions.md`: design/architecture changes and rationales
-- `experiments.md`: experiment runs and results
-- `ideas.md`: future ideas and hypotheses
-- `architecture.md`: system overview and module boundaries
-- `evaluation.md`: evaluation protocol and metric usage
-
-Conventions:
-- Append new entries instead of overwriting old ones.
-- Record exact config file and key overrides when possible.
-- Keep metrics in the order: avg_ks / avg_jsd / avg_lag1_diff.
-
-Tools:
-- `example/diagnose_ks.py` for per-feature KS + CDF plots.
-- `example/run_all.py` for one-command full pipeline (train/export/eval/postprocess/diagnostics).
-- `example/run_all_full.py` legacy full pipeline runner.
-- `example/filtered_metrics.py` for filtered KS after removing collapsed/outlier features.
-- `example/ranked_ks.py` for ranked KS table + cumulative avg_ks if removing top features.
-- `example/evaluate_generated.py` for full-reference metrics (now supports glob over all train*.csv.gz).
-- `example/program_stats.py` for dwell/change/step stats on program-like features.
-- `example/controller_stats.py` for controller saturation/change stats.
-- `example/actuator_stats.py` for spike/dwell stats on actuators.
-- `example/pv_stats.py` for PV quantile/tail stats.
-- `example/aux_stats.py` for aux signal mean/std/lag1 stats.
-- `example/postprocess_types.py` for type-based postprocessing (Type1/2/3/5/6).
-Notes:
-- If `use_quantile_transform` is enabled, run `prepare_data.py` with `full_stats: true` to build quantile tables.
-
-Current status (high level):
-- Two-stage pipeline (GRU trend + diffusion residuals).
-- Quantile transform + post-hoc calibration enabled for continuous features.
-- KS evaluation uses full reference glob and tie-aware KS implementation.
-- Type-based postprocess (empirical resample for Type1/2/3/5/6) used as a KS-lowering baseline.
-- Latest model run (2026-01-27 21:22): avg_ks ~0.405 / avg_jsd ~0.038 / avg_lag1_diff ~0.145.

docs/architecture.md

@@ -1,47 +0,0 @@
-# Architecture Overview
-
-## System Diagram (text)
-```
-            +--------------------+
-            |  Program Generator |
-            | (Type 1 setpoints) |
-            +---------+----------+
-                      |
-                      v
-            +-----------------------+
-            | Controller / Actuator |
-            | (Type 2/3 modules)    |
-            +---------+-------------+
-                      |
-                      v
-        +----------------------------+
-        |  Diffusion (Residuals)     |
-        |  - Continuous PVs          |
-        |  - Discrete mask diffusion |
-        +---------+------------------+
-                  |
-                  v
-     +-----------------------------+
-     | Post-processing             |
-     | - Derived tags (Type 5)     |
-     | - KS-only resample baseline |
-     +-----------------------------+
-```
-
-## Core Components
-- **Stage‑1 Temporal GRU**: learns trend for continuous features.
-- **Diffusion Backbone**: Transformer (default) or GRU; predicts residuals + discrete logits.
-- **Post-hoc Calibration**: optional quantile calibration to align 1D CDFs.
-- **KS-only Baseline**: Type1/2/3/5/6 empirical resampling for rapid KS reduction (diagnostic; may hurt joint realism).
-
-## Feature-Type Split
-1) **Type 1**: Setpoints/demands → program generator  
-2) **Type 2**: Controller outputs → small emulator / conditional head  
-3) **Type 3**: Actuators/valves → spike‑and‑slab / dwell-time model  
-4) **Type 4**: Process PVs (multi‑modal/heavy tail) → diffusion with conditioning  
-5) **Type 5**: Derived tags → deterministic reconstruction (or empirical KS baseline)  
-6) **Type 6**: Auxiliary/vibration → narrow-band AR/SSM or empirical KS baseline
-
-## Data Flow
-- Input CSV → stats/vocab → normalized batches  
-- Trend GRU → residual diffusion → inverse transforms → export  

docs/decisions.md

@@ -1,99 +0,0 @@
-# Design & Decision Log
-
-## 2026-01-26 — Two-stage temporal backbone (GRU) + residual diffusion
-- **Decision**: Add a stage-1 GRU trend model, then train diffusion on residuals.
-- **Why**: Separate temporal consistency from distribution alignment.
-- **Files**:
-  - `example/hybrid_diffusion.py` (added `TemporalGRUGenerator`)
-  - `example/train.py` (two-stage training + residual diffusion)
-  - `example/sample.py`, `example/export_samples.py` (trend + residual synthesis)
-  - `example/config.json` (temporal hyperparameters)
-- **Expected effect**: improve lag-1 consistency; may hurt KS if residual distribution drifts.
-
-## 2026-01-26 — Residual distribution alignment losses
-- **Decision**: Apply distribution losses to residuals (not raw x0).
-- **Why**: Diffusion models residuals; alignment should match residual distribution.
-- **Files**:
-  - `example/train.py` (quantile loss on residuals)
-  - `example/config.json` (quantile weight)
-
-## 2026-01-26 — SNR-weighted loss + residual stats
-- **Decision**: Add SNR-weighted loss and residual mean/std regularization.
-- **Why**: Stabilize diffusion training and improve KS.
-- **Files**:
-  - `example/train.py`
-  - `example/config.json`
-
-## 2026-01-26 — Switchable backbone (GRU vs Transformer)
-- **Decision**: Make the diffusion backbone configurable (`backbone_type`) with a Transformer encoder option.
-- **Why**: Test whether self‑attention reduces temporal vs distribution competition without altering the two‑stage design.
-- **Files**:
-  - `example/hybrid_diffusion.py`
-  - `example/train.py`
-  - `example/sample.py`
-  - `example/export_samples.py`
-  - `example/config.json`
-
-## 2026-01-26 — Per-feature KS diagnostics
-- **Decision**: Add a per-feature KS/CDF diagnostic script to pinpoint KS failures (tails, boundary pile-up, shifts).
-- **Why**: Avoid blind reweighting and find the specific features causing KS to stay high.
-- **Files**:
-  - `example/diagnose_ks.py`
-
-## 2026-01-26 — Quantile transform + sigmoid bounds for continuous features
-- **Decision**: Add optional quantile normalization (TabDDPM-style) and sigmoid-based bounds to reduce KS spikes.
-- **Why**: KS failures are dominated by boundary pile-up and tail mismatch.
-- **Files**:
-  - `example/data_utils.py`
-  - `example/prepare_data.py`
-  - `example/export_samples.py`
-  - `example/config.json`
-
-## 2026-01-27 — Quantile transform without extra standardization
-- **Decision**: When quantile transform is enabled, skip mean/std normalization (quantile output already ~N(0,1)).
-- **Why**: Prevent scale mismatch that pushed values to max bounds and blew up KS.
-- **Files**:
-  - `example/data_utils.py`
-  - `example/export_samples.py`
-
-## 2026-01-27 — Soft bounds + post-scale for boundary pile-up
-- **Decision**: Replace hard sigmoid bounds with soft tanh bounds and allow per-feature post-scaling.
-- **Why**: Many continuous features collapsed to max bound (KS=1.0).
-- **Files**:
-  - `example/export_samples.py`
-  - `example/config.json`
-
-## 2026-01-27 — Post-hoc quantile calibration
-- **Decision**: Add optional post-hoc quantile calibration to align generated 1D CDFs with real data.
-- **Why**: KS remained high with distribution shifts even after boundary fixes.
-- **Files**:
-  - `example/data_utils.py`
-  - `example/export_samples.py`
-  - `example/prepare_data.py`
-  - `example/config.json`
-
-## 2026-01-27 — Full quantile stats in preparation
-- **Decision**: Enable full statistics when quantile transform is active.
-- **Why**: Stabilize quantile tables and reduce CDF mismatch.
-- **Files**:
-  - `example/prepare_data.py`
-  - `example/config.json`
-
-## 2026-01-27 — Filtered KS for diagnostics
-- **Decision**: Add a filtered KS metric that excludes collapsed/outlier features.
-- **Why**: Avoid a handful of features dominating the aggregate KS while still reporting full KS.
-- **Files**:
-  - `example/filtered_metrics.py`
-  - `example/run_all_full.py`
-
-## 2026-01-28 — Tie-aware KS + full-reference aggregation
-- **Decision**: Fix KS computation to handle ties correctly and aggregate all reference files matched by glob.
-- **Why**: Spiky/quantized features were overstating KS; single-file reference was misleading.
-- **Files**:
-  - `example/evaluate_generated.py`
-
-## 2026-01-28 — KS-only postprocess baseline
-- **Decision**: Add an empirical resampling mode for Type1/2/3/5/6 to aggressively reduce KS.
-- **Why**: Provide a diagnostic upper-bound on KS without retraining.
-- **Files**:
-  - `example/postprocess_types.py`

docs/evaluation.md

@@ -1,46 +0,0 @@
-# Evaluation Protocol
-
-## Primary Metrics
-- **avg_ks**: mean KS across continuous features
-- **avg_jsd**: mean JSD across discrete feature marginals
-- **avg_lag1_diff**: lag‑1 correlation mismatch
-
-## Diagnostic Metrics
-- **per‑feature KS**: `example/diagnose_ks.py`
-- **filtered KS**: `example/filtered_metrics.py` (remove collapsed/outlier features)
-- **ranked KS**: `example/ranked_ks.py` (contribution analysis)
-
-## KS Implementation Notes
-- KS is computed with **tie-aware** CDFs (important for discrete/spiky features).
-- Reference data supports **glob input** and aggregates all matching files.
-- Use `--max-rows` to cap reference rows for faster diagnostics.
-
-## Recommended Reporting
-Report both:
-1) **Full metrics** (no filtering)  
-2) **Filtered metrics** (diagnostic only)
-
-Always list which features were filtered.
-If using KS-only postprocess (empirical resampling), note it explicitly because it can weaken joint realism.
-
-## Program‑Generator Metrics (Type 1)
-For setpoints/demands:
-- dwell‑time distribution
-- change‑count per day
-- step‑size distribution
-
-## Controller Metrics (Type 2)
-- saturation ratio near bounds
-- change rate and median step size
-
-## Actuator Metrics (Type 3)
-- top‑k spike mass (top1/top3)
-- unique ratio
-- dwell length
-
-## PV Metrics (Type 4)
-- q05/q50/q95 + tail ratio
-
-## Aux Metrics (Type 6)
-- mean/std
-- lag‑1 correlation

docs/experiments.md

@@ -1,39 +0,0 @@
-# Experiment Log
-
-## Format
-```
-YYYY-MM-DD
-- Config: <config file or key overrides>
-- Result: avg_ks / avg_jsd / avg_lag1_diff
-- Notes
-```
-
-## 2026-01-26
-- Config: `example/config_no_temporal.json` (baseline)
-- Result: 0.6474156 / 0.0576699 / 0.1981700
-- Notes: no temporal stage; better KS, worse lag-1.
-
-## 2026-01-26
-- Config: `example/config_temporal_strong.json` (two-stage)
-- Result: 0.6892453 / 0.0564408 / 0.1568776
-- Notes: lag-1 improves, KS degrades; residual drift remains.
-
-## 2026-01-26
-- Config: `example/config.json` (two-stage residual diffusion; user run on Windows)
-- Result: 0.7131993 / 0.0327603 / 0.2327633
-- Notes: user-reported metrics after temporal stage + residual diffusion.
-
-## 2026-01-26
-- Config: `example/config.json` (two-stage residual diffusion; user run on Windows)
-- Result: 0.7096230 / 0.0331810 / 0.1898416
-- Notes: slight KS improvement, lag-1 improves; still distribution/temporal trade-off.
-
-## 2026-01-27
-- Config: `example/config.json` (quantile transform + calibration, full stats)
-- Result: 0.4046 / 0.0376 / 0.1449
-- Notes: KS and lag-1 improved significantly; JSD regressed vs best discrete run.
-
-## 2026-01-28
-- Config: `example/config.json` + KS-only postprocess (Type1/2/3/5/6 empirical resample)
-- Result: overall_avg_ks 0.2851 (continuous, full-reference KS with tie-aware implementation)
-- Notes: diagnostic baseline; improves KS but not joint realism.

docs/ideas.md

@@ -1,19 +0,0 @@
-# Ideas & Hypotheses
-
-## Transformer as backbone (Plan B)
-- Hypothesis: self-attention may better capture long-range dependencies and reduce conflict between temporal consistency and distribution matching.
-- Risk: higher compute cost, potentially more unstable training.
-- Status: implemented as `backbone_type = "transformer"` in config.
-- Experiment: compare GRU vs Transformer using `run_compare.py`.
-
-## Residual standardization
-- Hypothesis: standardizing residuals before diffusion reduces drift and improves KS.
-
-## Two-stage training with curriculum
-- Hypothesis: train diffusion on residuals only after temporal GRU converges to low error.
-
-## Discrete calibration
-- Hypothesis: post-hoc calibration on discrete marginals can reduce JSD without harming KS.
-
-## Feature-type split modeling
-- Hypothesis: separate generation per feature type (setpoints, controllers, actuators, quantized, derived, aux) yields better overall fidelity.

example/README.md

@@ -72,4 +72,5 @@ python example/run_pipeline.py --device auto
 - The script only samples the first 5000 rows to stay fast.
 - `prepare_data.py` runs without PyTorch, but `train.py` and `sample.py` require it.
 - `train.py` and `sample.py` auto-select GPU if available; otherwise they fall back to CPU.
-- Optional two-stage temporal model (`use_temporal_stage1`) trains a GRU trend backbone first, then diffusion models residuals.
+- Optional feature-graph mixer (`model_use_feature_graph`) adds a learnable relation prior across feature channels.
+- Optional two-stage temporal backbone (`use_temporal_stage1`) learns a GRU-based sequence trend; diffusion models the residual.

example/actuator_stats.py

@@ -1,127 +0,0 @@
-#!/usr/bin/env python3
-"""Stats for actuator/valve-like outputs (Type 3)."""
-
-import argparse
-import csv
-import gzip
-import json
-from pathlib import Path
-from typing import Dict, List
-
-
-def parse_args():
-    base_dir = Path(__file__).resolve().parent
-    parser = argparse.ArgumentParser(description="Actuator/valve stats.")
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--features", default="", help="comma-separated list")
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "actuator_stats.json"))
-    parser.add_argument("--max-rows", type=int, default=200000)
-    return parser.parse_args()
-
-
-def resolve_reference_glob(ref_arg: str) -> str:
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]:
-    vals = {c: [] for c in cols}
-    opener = gzip.open if str(path).endswith(".gz") else open
-    with opener(path, "rt", newline="") as fh:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            for c in cols:
-                try:
-                    vals[c].append(float(row[c]))
-                except Exception:
-                    pass
-            if max_rows > 0 and i + 1 >= max_rows:
-                break
-    return vals
-
-
-def spike_stats(series: List[float]):
-    if not series:
-        return {
-            "unique_ratio": None,
-            "top1_mass": None,
-            "top3_mass": None,
-            "median_dwell": None,
-        }
-    n = len(series)
-    # discretize by rounding
-    rounded = [round(v, 2) for v in series]
-    counts = {}
-    for v in rounded:
-        counts[v] = counts.get(v, 0) + 1
-    unique_ratio = len(counts) / n
-    top = sorted(counts.values(), reverse=True)
-    top1_mass = top[0] / n if top else None
-    top3_mass = sum(top[:3]) / n if len(top) >= 3 else top1_mass
-
-    # dwell length
-    dwells = []
-    current = rounded[0]
-    dwell = 1
-    for v in rounded[1:]:
-        if v == current:
-            dwell += 1
-        else:
-            dwells.append(dwell)
-            current = v
-            dwell = 1
-    dwells.append(dwell)
-    dwells.sort()
-    median_dwell = dwells[len(dwells) // 2] if dwells else None
-    return {
-        "unique_ratio": unique_ratio,
-        "top1_mass": top1_mass,
-        "top3_mass": top3_mass,
-        "median_dwell": median_dwell,
-    }
-
-
-def main():
-    args = parse_args()
-    features = [f.strip() for f in args.features.split(",") if f.strip()]
-    if not features and Path(args.config).exists():
-        cfg = json.loads(Path(args.config).read_text(encoding="utf-8"))
-        features = cfg.get("type3_features", []) or []
-    if not features:
-        raise SystemExit("no features specified for actuator_stats")
-
-    gen_vals = read_series(Path(args.generated), features, args.max_rows)
-    ref_glob = resolve_reference_glob(args.reference)
-    ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name))
-    if not ref_paths:
-        raise SystemExit(f"no reference files matched: {ref_glob}")
-    real_vals = {c: [] for c in features}
-    for p in ref_paths:
-        vals = read_series(p, features, args.max_rows)
-        for c in features:
-            real_vals[c].extend(vals[c])
-
-    out = {"features": features, "generated": {}, "reference": {}}
-    for c in features:
-        out["generated"][c] = spike_stats(gen_vals[c])
-        out["reference"][c] = spike_stats(real_vals[c])
-
-    out_path = Path(args.out)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    out_path.write_text(json.dumps(out, indent=2), encoding="utf-8")
-    print("wrote", out_path)
-
-
-if __name__ == "__main__":
-    main()

example/aux_stats.py

@@ -1,108 +0,0 @@
-#!/usr/bin/env python3
-"""Stats for auxiliary/vibration signals (Type 6)."""
-
-import argparse
-import csv
-import gzip
-import json
-from pathlib import Path
-from typing import Dict, List
-
-
-def parse_args():
-    base_dir = Path(__file__).resolve().parent
-    parser = argparse.ArgumentParser(description="Aux stats.")
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--features", default="", help="comma-separated list")
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "aux_stats.json"))
-    parser.add_argument("--max-rows", type=int, default=200000)
-    return parser.parse_args()
-
-
-def resolve_reference_glob(ref_arg: str) -> str:
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]:
-    vals = {c: [] for c in cols}
-    opener = gzip.open if str(path).endswith(".gz") else open
-    with opener(path, "rt", newline="") as fh:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            for c in cols:
-                try:
-                    vals[c].append(float(row[c]))
-                except Exception:
-                    pass
-            if max_rows > 0 and i + 1 >= max_rows:
-                break
-    return vals
-
-
-def mean_std(series: List[float]):
-    if not series:
-        return {"mean": None, "std": None, "lag1": None}
-    n = len(series)
-    mean = sum(series) / n
-    var = sum((x - mean) ** 2 for x in series) / max(n - 1, 1)
-    std = var ** 0.5
-    # lag1 correlation
-    if n < 2:
-        lag1 = None
-    else:
-        x = series[:-1]
-        y = series[1:]
-        mx = sum(x) / len(x)
-        my = sum(y) / len(y)
-        num = sum((a - mx) * (b - my) for a, b in zip(x, y))
-        denx = sum((a - mx) ** 2 for a in x)
-        deny = sum((b - my) ** 2 for b in y)
-        lag1 = num / (denx ** 0.5 * deny ** 0.5) if denx > 0 and deny > 0 else None
-    return {"mean": mean, "std": std, "lag1": lag1}
-
-
-def main():
-    args = parse_args()
-    features = [f.strip() for f in args.features.split(",") if f.strip()]
-    if not features and Path(args.config).exists():
-        cfg = json.loads(Path(args.config).read_text(encoding="utf-8"))
-        features = cfg.get("type6_features", []) or []
-    if not features:
-        raise SystemExit("no features specified for aux_stats")
-
-    gen_vals = read_series(Path(args.generated), features, args.max_rows)
-    ref_glob = resolve_reference_glob(args.reference)
-    ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name))
-    if not ref_paths:
-        raise SystemExit(f"no reference files matched: {ref_glob}")
-    real_vals = {c: [] for c in features}
-    for p in ref_paths:
-        vals = read_series(p, features, args.max_rows)
-        for c in features:
-            real_vals[c].extend(vals[c])
-
-    out = {"features": features, "generated": {}, "reference": {}}
-    for c in features:
-        out["generated"][c] = mean_std(gen_vals[c])
-        out["reference"][c] = mean_std(real_vals[c])
-
-    out_path = Path(args.out)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    out_path.write_text(json.dumps(out, indent=2), encoding="utf-8")
-    print("wrote", out_path)
-
-
-if __name__ == "__main__":
-    main()

example/config.json

@@ -7,7 +7,7 @@
   "out_dir": "./results",
   "device": "auto",
   "timesteps": 600,
-  "batch_size": 24,
+  "batch_size": 128,
   "seq_len": 128,
   "epochs": 10,
   "max_batches": 4000,
@@ -26,47 +26,31 @@
   "use_tanh_eps": false,
   "eps_scale": 1.0,
   "model_time_dim": 128,
-  "model_hidden_dim": 640,
+  "model_hidden_dim": 512,
   "model_num_layers": 2,
   "model_dropout": 0.1,
   "model_ff_mult": 2,
   "model_pos_dim": 64,
   "model_use_pos_embed": true,
-  "backbone_type": "transformer",
-  "transformer_num_layers": 3,
-  "transformer_nhead": 4,
-  "transformer_ff_dim": 768,
-  "transformer_dropout": 0.1,
+  "model_use_feature_graph": true,
+  "feature_graph_scale": 0.1,
+  "feature_graph_dropout": 0.0,
+  "use_temporal_stage1": true,
+  "temporal_hidden_dim": 256,
+  "temporal_num_layers": 1,
+  "temporal_dropout": 0.0,
+  "temporal_loss_weight": 1.0,
   "disc_mask_scale": 0.9,
   "cont_loss_weighting": "inv_std",
   "cont_loss_eps": 1e-6,
-  "cont_target": "x0",
+  "cont_target": "v",
   "cont_clamp_x0": 5.0,
-  "use_quantile_transform": true,
-  "quantile_bins": 1001,
-  "cont_bound_mode": "none",
-  "cont_bound_strength": 2.0,
-  "cont_post_calibrate": true,
-  "cont_post_scale": {},
-  "full_stats": true,
-  "type1_features": ["P1_B4002","P2_MSD","P4_HT_LD","P1_B2004","P1_B3004","P1_B4022","P1_B3005"],
-  "type2_features": ["P1_B4005"],
-  "type3_features": ["P1_PCV02Z","P1_PCV01Z","P1_PCV01D","P1_FCV02Z"],
-  "type4_features": ["P1_PIT02","P2_SIT02","P1_FT03"],
-  "type5_features": ["P1_FT03Z"],
-  "type6_features": ["P4_HT_PO","P2_24Vdc","P2_HILout"],
-  "shuffle_buffer": 256,
-  "use_temporal_stage1": true,
-  "temporal_hidden_dim": 384,
-  "temporal_num_layers": 1,
-  "temporal_dropout": 0.0,
-  "temporal_epochs": 3,
-  "temporal_lr": 0.001,
-  "quantile_loss_weight": 0.2,
+  "quantile_loss_weight": 0.1,
   "quantile_points": [0.05, 0.25, 0.5, 0.75, 0.95],
-  "snr_weighted_loss": true,
-  "snr_gamma": 1.0,
-  "residual_stat_weight": 0.05,
+  "quantile_loss_warmup_steps": 200,
+  "quantile_loss_clip": 6.0,
+  "quantile_loss_huber_delta": 1.0,
+  "shuffle_buffer": 256,
   "sample_batch_size": 8,
   "sample_seq_len": 128
 }

example/config_no_temporal.json

@@ -1,56 +0,0 @@
-{
-  "data_path": "../../dataset/hai/hai-21.03/train1.csv.gz",
-  "data_glob": "../../dataset/hai/hai-21.03/train*.csv.gz",
-  "split_path": "./feature_split.json",
-  "stats_path": "./results/cont_stats.json",
-  "vocab_path": "./results/disc_vocab.json",
-  "out_dir": "./results",
-  "device": "auto",
-  "timesteps": 600,
-  "batch_size": 128,
-  "seq_len": 128,
-  "epochs": 10,
-  "max_batches": 4000,
-  "lambda": 0.7,
-  "lr": 0.0005,
-  "seed": 1337,
-  "log_every": 10,
-  "ckpt_every": 50,
-  "ema_decay": 0.999,
-  "use_ema": true,
-  "clip_k": 5.0,
-  "grad_clip": 1.0,
-  "use_condition": true,
-  "condition_type": "file_id",
-  "cond_dim": 32,
-  "use_tanh_eps": false,
-  "eps_scale": 1.0,
-  "model_time_dim": 128,
-  "model_hidden_dim": 512,
-  "model_num_layers": 2,
-  "model_dropout": 0.1,
-  "model_ff_mult": 2,
-  "model_pos_dim": 64,
-  "model_use_pos_embed": true,
-  "backbone_type": "transformer",
-  "transformer_num_layers": 2,
-  "transformer_nhead": 4,
-  "transformer_ff_dim": 512,
-  "transformer_dropout": 0.1,
-  "disc_mask_scale": 0.9,
-  "cont_loss_weighting": "inv_std",
-  "cont_loss_eps": 1e-6,
-  "cont_target": "x0",
-  "cont_clamp_x0": 5.0,
-  "use_quantile_transform": true,
-  "quantile_bins": 1001,
-  "cont_bound_mode": "none",
-  "cont_bound_strength": 2.0,
-  "cont_post_calibrate": true,
-  "cont_post_scale": {},
-  "full_stats": true,
-  "shuffle_buffer": 1024,
-  "use_temporal_stage1": false,
-  "sample_batch_size": 4,
-  "sample_seq_len": 128
-}

example/config_temporal_strong.json

@@ -1,61 +0,0 @@
-{
-  "data_path": "../../dataset/hai/hai-21.03/train1.csv.gz",
-  "data_glob": "../../dataset/hai/hai-21.03/train*.csv.gz",
-  "split_path": "./feature_split.json",
-  "stats_path": "./results/cont_stats.json",
-  "vocab_path": "./results/disc_vocab.json",
-  "out_dir": "./results",
-  "device": "auto",
-  "timesteps": 600,
-  "batch_size": 128,
-  "seq_len": 128,
-  "epochs": 10,
-  "max_batches": 4000,
-  "lambda": 0.7,
-  "lr": 0.0005,
-  "seed": 1337,
-  "log_every": 10,
-  "ckpt_every": 50,
-  "ema_decay": 0.999,
-  "use_ema": true,
-  "clip_k": 5.0,
-  "grad_clip": 1.0,
-  "use_condition": true,
-  "condition_type": "file_id",
-  "cond_dim": 32,
-  "use_tanh_eps": false,
-  "eps_scale": 1.0,
-  "model_time_dim": 128,
-  "model_hidden_dim": 512,
-  "model_num_layers": 2,
-  "model_dropout": 0.1,
-  "model_ff_mult": 2,
-  "model_pos_dim": 64,
-  "model_use_pos_embed": true,
-  "backbone_type": "transformer",
-  "transformer_num_layers": 2,
-  "transformer_nhead": 4,
-  "transformer_ff_dim": 512,
-  "transformer_dropout": 0.1,
-  "disc_mask_scale": 0.9,
-  "cont_loss_weighting": "inv_std",
-  "cont_loss_eps": 1e-6,
-  "cont_target": "x0",
-  "cont_clamp_x0": 5.0,
-  "use_quantile_transform": true,
-  "quantile_bins": 1001,
-  "cont_bound_mode": "none",
-  "cont_bound_strength": 2.0,
-  "cont_post_calibrate": true,
-  "cont_post_scale": {},
-  "full_stats": true,
-  "shuffle_buffer": 1024,
-  "use_temporal_stage1": true,
-  "temporal_hidden_dim": 512,
-  "temporal_num_layers": 2,
-  "temporal_dropout": 0.0,
-  "temporal_epochs": 5,
-  "temporal_lr": 0.0005,
-  "sample_batch_size": 4,
-  "sample_seq_len": 128
-}

example/controller_stats.py

@@ -1,115 +0,0 @@
-#!/usr/bin/env python3
-"""Stats for controller-like outputs (Type 2)."""
-
-import argparse
-import csv
-import gzip
-import json
-from pathlib import Path
-from typing import Dict, List
-
-
-def parse_args():
-    base_dir = Path(__file__).resolve().parent
-    parser = argparse.ArgumentParser(description="Controller output stats.")
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--features", default="", help="comma-separated list")
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "controller_stats.json"))
-    parser.add_argument("--max-rows", type=int, default=200000)
-    return parser.parse_args()
-
-
-def resolve_reference_glob(ref_arg: str) -> str:
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]:
-    vals = {c: [] for c in cols}
-    opener = gzip.open if str(path).endswith(".gz") else open
-    with opener(path, "rt", newline="") as fh:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            for c in cols:
-                try:
-                    vals[c].append(float(row[c]))
-                except Exception:
-                    pass
-            if max_rows > 0 and i + 1 >= max_rows:
-                break
-    return vals
-
-
-def stats(series: List[float], vmin: float, vmax: float):
-    if not series:
-        return {"saturation_ratio": None, "change_rate": None, "step_median": None}
-    # saturation ratio near bounds (1% of range)
-    rng = vmax - vmin
-    tol = 0.01 * rng if rng > 0 else 0.0
-    sat = sum(1 for v in series if v <= vmin + tol or v >= vmax - tol) / len(series)
-    # change rate
-    changes = 0
-    steps = []
-    prev = series[0]
-    for v in series[1:]:
-        if v != prev:
-            changes += 1
-            steps.append(abs(v - prev))
-        prev = v
-    change_rate = changes / max(len(series) - 1, 1)
-    steps.sort()
-    step_median = steps[len(steps) // 2] if steps else None
-    return {"saturation_ratio": sat, "change_rate": change_rate, "step_median": step_median}
-
-
-def main():
-    args = parse_args()
-    features = [f.strip() for f in args.features.split(",") if f.strip()]
-    if not features and Path(args.config).exists():
-        cfg = json.loads(Path(args.config).read_text(encoding="utf-8"))
-        features = cfg.get("type2_features", []) or []
-    if not features:
-        raise SystemExit("no features specified for controller_stats")
-
-    # generated
-    gen_vals = read_series(Path(args.generated), features, args.max_rows)
-
-    # reference
-    ref_glob = resolve_reference_glob(args.reference)
-    ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name))
-    if not ref_paths:
-        raise SystemExit(f"no reference files matched: {ref_glob}")
-    real_vals = {c: [] for c in features}
-    for p in ref_paths:
-        vals = read_series(p, features, args.max_rows)
-        for c in features:
-            real_vals[c].extend(vals[c])
-
-    out = {"features": features, "generated": {}, "reference": {}}
-    for c in features:
-        rv = real_vals[c]
-        if not rv:
-            continue
-        vmin, vmax = min(rv), max(rv)
-        out["generated"][c] = stats(gen_vals[c], vmin, vmax)
-        out["reference"][c] = stats(rv, vmin, vmax)
-
-    out_path = Path(args.out)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    out_path.write_text(json.dumps(out, indent=2), encoding="utf-8")
-    print("wrote", out_path)
-
-
-if __name__ == "__main__":
-    main()

example/data_utils.py

@@ -138,7 +138,6 @@ def compute_cont_stats(
     cont_cols: List[str],
     max_rows: Optional[int] = None,
     transforms: Optional[Dict[str, str]] = None,
-    quantile_bins: Optional[int] = None,
 ):
     """Compute stats on (optionally transformed) values. Returns raw + transformed stats."""
     # First pass (raw) for metadata and raw mean/std
@@ -148,26 +147,20 @@ def compute_cont_stats(
     if transforms is None:
         transforms = {c: "none" for c in cont_cols}
 
-    # Second pass for transformed mean/std (and optional quantiles)
+    # Second pass for transformed mean/std
     count = {c: 0 for c in cont_cols}
     mean = {c: 0.0 for c in cont_cols}
     m2 = {c: 0.0 for c in cont_cols}
-    quantile_values = {c: [] for c in cont_cols} if quantile_bins and quantile_bins > 1 else None
-    raw_quantile_values = {c: [] for c in cont_cols} if quantile_bins and quantile_bins > 1 else None
     for i, row in enumerate(iter_rows(path)):
         for c in cont_cols:
             raw_val = row[c]
             if raw_val is None or raw_val == "":
                 continue
             x = float(raw_val)
-            if raw_quantile_values is not None:
-                raw_quantile_values[c].append(x)
             if transforms.get(c) == "log1p":
                 if x < 0:
                     x = 0.0
                 x = math.log1p(x)
-            if quantile_values is not None:
-                quantile_values[c].append(x)
             n = count[c] + 1
             delta = x - mean[c]
             mean[c] += delta / n
@@ -185,39 +178,6 @@ def compute_cont_stats(
             var = 0.0
         std[c] = var ** 0.5 if var > 0 else 1.0
 
-    quantile_probs = None
-    quantile_table = None
-    raw_quantile_table = None
-    if quantile_values is not None:
-        quantile_probs = [i / (quantile_bins - 1) for i in range(quantile_bins)]
-        quantile_table = {}
-        raw_quantile_table = {}
-        for c in cont_cols:
-            vals = quantile_values[c]
-            if not vals:
-                quantile_table[c] = [0.0 for _ in quantile_probs]
-            else:
-                vals.sort()
-                n = len(vals)
-                qvals = []
-                for p in quantile_probs:
-                    idx = int(round(p * (n - 1)))
-                    idx = max(0, min(n - 1, idx))
-                    qvals.append(float(vals[idx]))
-                quantile_table[c] = qvals
-            raw_vals = raw_quantile_values[c] if raw_quantile_values is not None else []
-            if not raw_vals:
-                raw_quantile_table[c] = [0.0 for _ in quantile_probs]
-                continue
-            raw_vals.sort()
-            n = len(raw_vals)
-            rqvals = []
-            for p in quantile_probs:
-                idx = int(round(p * (n - 1)))
-                idx = max(0, min(n - 1, idx))
-                rqvals.append(float(raw_vals[idx]))
-            raw_quantile_table[c] = rqvals
-
     return {
         "mean": mean,
         "std": std,
@@ -231,9 +191,6 @@ def compute_cont_stats(
         "skew": raw["skew"],
         "all_pos": raw["all_pos"],
         "max_rows": max_rows,
-        "quantile_probs": quantile_probs,
-        "quantile_values": quantile_table,
-        "quantile_raw_values": raw_quantile_table,
     }
 
 
@@ -292,9 +249,6 @@ def normalize_cont(
     mean: Dict[str, float],
     std: Dict[str, float],
     transforms: Optional[Dict[str, str]] = None,
-    quantile_probs: Optional[List[float]] = None,
-    quantile_values: Optional[Dict[str, List[float]]] = None,
-    use_quantile: bool = False,
 ):
     import torch
 
@@ -302,95 +256,11 @@ def normalize_cont(
         for i, c in enumerate(cont_cols):
             if transforms.get(c) == "log1p":
                 x[:, :, i] = torch.log1p(torch.clamp(x[:, :, i], min=0))
-    if use_quantile:
-        if not quantile_probs or not quantile_values:
-            raise ValueError("use_quantile_transform enabled but quantile stats missing")
-        x = apply_quantile_transform(x, cont_cols, quantile_probs, quantile_values)
-        # quantile transform already targets N(0,1); skip extra standardization
-        return x
     mean_t = torch.tensor([mean[c] for c in cont_cols], dtype=x.dtype, device=x.device)
     std_t = torch.tensor([std[c] for c in cont_cols], dtype=x.dtype, device=x.device)
     return (x - mean_t) / std_t
 
 
-def _normal_cdf(x):
-    import torch
-    return 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0)))
-
-
-def _normal_ppf(p):
-    import torch
-    eps = 1e-6
-    p = torch.clamp(p, eps, 1.0 - eps)
-    return math.sqrt(2.0) * torch.erfinv(2.0 * p - 1.0)
-
-
-def apply_quantile_transform(x, cont_cols, quantile_probs, quantile_values):
-    import torch
-    probs_t = torch.tensor(quantile_probs, dtype=x.dtype, device=x.device)
-    for i, c in enumerate(cont_cols):
-        q_vals = torch.tensor(quantile_values[c], dtype=x.dtype, device=x.device)
-        v = x[:, :, i]
-        idx = torch.bucketize(v, q_vals)
-        idx = torch.clamp(idx, 1, q_vals.numel() - 1)
-        x0 = q_vals[idx - 1]
-        x1 = q_vals[idx]
-        p0 = probs_t[idx - 1]
-        p1 = probs_t[idx]
-        denom = torch.where((x1 - x0) == 0, torch.ones_like(x1 - x0), (x1 - x0))
-        p = p0 + (v - x0) * (p1 - p0) / denom
-        x[:, :, i] = _normal_ppf(p)
-    return x
-
-
-def inverse_quantile_transform(x, cont_cols, quantile_probs, quantile_values):
-    import torch
-    probs_t = torch.tensor(quantile_probs, dtype=x.dtype, device=x.device)
-    for i, c in enumerate(cont_cols):
-        q_vals = torch.tensor(quantile_values[c], dtype=x.dtype, device=x.device)
-        z = x[:, :, i]
-        p = _normal_cdf(z)
-        idx = torch.bucketize(p, probs_t)
-        idx = torch.clamp(idx, 1, probs_t.numel() - 1)
-        p0 = probs_t[idx - 1]
-        p1 = probs_t[idx]
-        x0 = q_vals[idx - 1]
-        x1 = q_vals[idx]
-        denom = torch.where((p1 - p0) == 0, torch.ones_like(p1 - p0), (p1 - p0))
-        v = x0 + (p - p0) * (x1 - x0) / denom
-        x[:, :, i] = v
-    return x
-
-
-def quantile_calibrate_to_real(x, cont_cols, quantile_probs, real_quantile_values):
-    import torch
-    probs_t = torch.tensor(quantile_probs, dtype=x.dtype, device=x.device)
-    flat = x.reshape(-1, x.size(-1))
-    for i, c in enumerate(cont_cols):
-        v = flat[:, i]
-        gen_q = torch.quantile(v, probs_t)
-        idx = torch.bucketize(v, gen_q)
-        idx = torch.clamp(idx, 1, gen_q.numel() - 1)
-        x0 = gen_q[idx - 1]
-        x1 = gen_q[idx]
-        p0 = probs_t[idx - 1]
-        p1 = probs_t[idx]
-        denom = torch.where((x1 - x0) == 0, torch.ones_like(x1 - x0), (x1 - x0))
-        p = p0 + (v - x0) * (p1 - p0) / denom
-
-        real_q = torch.tensor(real_quantile_values[c], dtype=x.dtype, device=x.device)
-        idx2 = torch.bucketize(p, probs_t)
-        idx2 = torch.clamp(idx2, 1, probs_t.numel() - 1)
-        rp0 = probs_t[idx2 - 1]
-        rp1 = probs_t[idx2]
-        r0 = real_q[idx2 - 1]
-        r1 = real_q[idx2]
-        denom2 = torch.where((rp1 - rp0) == 0, torch.ones_like(rp1 - rp0), (rp1 - rp0))
-        v2 = r0 + (p - rp0) * (r1 - r0) / denom2
-        flat[:, i] = v2
-    return flat.reshape(x.shape)
-
-
 def windowed_batches(
     path: Union[str, List[str]],
     cont_cols: List[str],
@@ -403,9 +273,6 @@ def windowed_batches(
     max_batches: Optional[int] = None,
     return_file_id: bool = False,
     transforms: Optional[Dict[str, str]] = None,
-    quantile_probs: Optional[List[float]] = None,
-    quantile_values: Optional[Dict[str, List[float]]] = None,
-    use_quantile: bool = False,
     shuffle_buffer: int = 0,
 ):
     import torch
@@ -449,16 +316,7 @@ def windowed_batches(
                 if len(batch_cont) == batch_size:
                     x_cont = torch.tensor(batch_cont, dtype=torch.float32)
                     x_disc = torch.tensor(batch_disc, dtype=torch.long)
-                    x_cont = normalize_cont(
-                        x_cont,
-                        cont_cols,
-                        mean,
-                        std,
-                        transforms=transforms,
-                        quantile_probs=quantile_probs,
-                        quantile_values=quantile_values,
-                        use_quantile=use_quantile,
-                    )
+                    x_cont = normalize_cont(x_cont, cont_cols, mean, std, transforms=transforms)
                     if return_file_id:
                         x_file = torch.tensor(batch_file, dtype=torch.long)
                         yield x_cont, x_disc, x_file
@@ -486,16 +344,7 @@ def windowed_batches(
                 import torch
                 x_cont = torch.tensor(batch_cont, dtype=torch.float32)
                 x_disc = torch.tensor(batch_disc, dtype=torch.long)
-                x_cont = normalize_cont(
-                    x_cont,
-                    cont_cols,
-                    mean,
-                    std,
-                    transforms=transforms,
-                    quantile_probs=quantile_probs,
-                    quantile_values=quantile_values,
-                    use_quantile=use_quantile,
-                )
+                x_cont = normalize_cont(x_cont, cont_cols, mean, std, transforms=transforms)
                 if return_file_id:
                     x_file = torch.tensor(batch_file, dtype=torch.long)
                     yield x_cont, x_disc, x_file

example/diagnose_ks.py

@@ -1,230 +0,0 @@
-#!/usr/bin/env python3
-"""Per-feature KS diagnostics and CDF visualization (no third-party deps)."""
-
-import argparse
-import csv
-import gzip
-import json
-import math
-from pathlib import Path
-from glob import glob
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(description="Per-feature KS diagnostics.")
-    base_dir = Path(__file__).resolve().parent
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--out-dir", default=str(base_dir / "results"))
-    parser.add_argument("--max-rows", type=int, default=200000, help="<=0 for full scan")
-    parser.add_argument("--stride", type=int, default=1, help="row stride sampling")
-    parser.add_argument("--top-k", type=int, default=8)
-    return parser.parse_args()
-
-
-def load_split(base_dir: Path):
-    with open(base_dir / "feature_split.json", "r", encoding="utf-8") as f:
-        split = json.load(f)
-    time_col = split.get("time_column", "time")
-    cont_cols = [c for c in split["continuous"] if c != time_col]
-    return cont_cols
-
-
-def resolve_reference_glob(base_dir: Path, ref_arg: str):
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        # On Windows, Path.resolve fails on glob patterns like *.csv.gz
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_csv_values(path: Path, cols, max_rows=200000, stride=1, gz=True):
-    values = {c: [] for c in cols}
-    row_count = 0
-    reader = None
-    if gz:
-        fh = gzip.open(path, "rt", newline="")
-    else:
-        fh = open(path, "r", newline="", encoding="utf-8")
-    try:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            if stride > 1 and i % stride != 0:
-                continue
-            for c in cols:
-                v = row.get(c, "")
-                try:
-                    fv = float(v)
-                    if math.isfinite(fv):
-                        values[c].append(fv)
-                except Exception:
-                    continue
-            row_count += 1
-            if max_rows > 0 and row_count >= max_rows:
-                break
-    finally:
-        fh.close()
-    return values, row_count
-
-
-def ks_statistic(a, b):
-    if not a or not b:
-        return 1.0
-    a = sorted(a)
-    b = sorted(b)
-    na = len(a)
-    nb = len(b)
-    i = j = 0
-    d = 0.0
-    while i < na and j < nb:
-        if a[i] <= b[j]:
-            i += 1
-        else:
-            j += 1
-        fa = i / na
-        fb = j / nb
-        d = max(d, abs(fa - fb))
-    return d
-
-
-def ecdf_points(vals):
-    vals = sorted(vals)
-    n = len(vals)
-    if n == 0:
-        return [], []
-    xs = []
-    ys = []
-    last = None
-    for i, v in enumerate(vals, 1):
-        if last is None or v != last:
-            xs.append(v)
-            ys.append(i / n)
-            last = v
-        else:
-            ys[-1] = i / n
-    return xs, ys
-
-
-def render_cdf_svg(out_path: Path, feature, real_vals, gen_vals, bounds=None):
-    width, height = 900, 420
-    pad = 50
-    panel_w = width - pad * 2
-    panel_h = height - pad * 2
-    if not real_vals or not gen_vals:
-        return
-    min_v = min(min(real_vals), min(gen_vals))
-    max_v = max(max(real_vals), max(gen_vals))
-    if max_v == min_v:
-        max_v += 1.0
-    rx, ry = ecdf_points(real_vals)
-    gx, gy = ecdf_points(gen_vals)
-
-    def sx(v):
-        return pad + int((v - min_v) * panel_w / (max_v - min_v))
-
-    def sy(v):
-        return pad + panel_h - int(v * panel_h)
-
-    svg = []
-    svg.append(f'<svg xmlns="http://www.w3.org/2000/svg" width="{width}" height="{height}">')
-    svg.append('<style>text{font-family:Arial,sans-serif;font-size:12px}</style>')
-    svg.append(f'<text x="{pad}" y="{pad-20}">CDF 비교: {feature}</text>')
-    svg.append(f'<line x1="{pad}" y1="{pad}" x2="{pad}" y2="{pad+panel_h}" stroke="#333"/>')
-    svg.append(f'<line x1="{pad}" y1="{pad+panel_h}" x2="{pad+panel_w}" y2="{pad+panel_h}" stroke="#333"/>')
-
-    def path_from(xs, ys, color):
-        pts = " ".join(f"{sx(x)},{sy(y)}" for x, y in zip(xs, ys))
-        return f'<polyline fill="none" stroke="{color}" stroke-width="2" points="{pts}"/>'
-
-    svg.append(path_from(rx, ry, "#1f77b4"))  # real
-    svg.append(path_from(gx, gy, "#d62728"))  # gen
-    svg.append(f'<text x="{pad+panel_w-120}" y="{pad+15}" fill="#1f77b4">real</text>')
-    svg.append(f'<text x="{pad+panel_w-120}" y="{pad+30}" fill="#d62728">generated</text>')
-
-    if bounds is not None:
-        lo, hi = bounds
-        svg.append(f'<line x1="{sx(lo)}" y1="{pad}" x2="{sx(lo)}" y2="{pad+panel_h}" stroke="#999" stroke-dasharray="4 3"/>')
-        svg.append(f'<line x1="{sx(hi)}" y1="{pad}" x2="{sx(hi)}" y2="{pad+panel_h}" stroke="#999" stroke-dasharray="4 3"/>')
-
-    svg.append("</svg>")
-    out_path.write_text("\n".join(svg), encoding="utf-8")
-
-
-def main():
-    args = parse_args()
-    base_dir = Path(__file__).resolve().parent
-    out_dir = Path(args.out_dir)
-    out_dir.mkdir(parents=True, exist_ok=True)
-
-    cont_cols = load_split(base_dir)
-    ref_glob = resolve_reference_glob(base_dir, args.reference)
-    ref_files = sorted(glob(ref_glob))
-    if not ref_files:
-        raise SystemExit(f"no reference files matched: {ref_glob}")
-
-    gen_path = Path(args.generated)
-    gen_vals, gen_rows = read_csv_values(gen_path, cont_cols, args.max_rows, args.stride, gz=False)
-
-    # Reference values (aggregate across files)
-    real_vals = {c: [] for c in cont_cols}
-    total_rows = 0
-    for f in ref_files:
-        vals, rows = read_csv_values(Path(f), cont_cols, args.max_rows, args.stride, gz=True)
-        total_rows += rows
-        for c in cont_cols:
-            real_vals[c].extend(vals[c])
-
-    # KS per feature
-    ks_rows = []
-    for c in cont_cols:
-        ks = ks_statistic(real_vals[c], gen_vals[c])
-        # boundary pile-up (using real min/max)
-        if real_vals[c]:
-            lo = min(real_vals[c])
-            hi = max(real_vals[c])
-        else:
-            lo = hi = 0.0
-        tol = (hi - lo) * 1e-4 if hi > lo else 1e-6
-        gen = gen_vals[c]
-        if gen:
-            frac_lo = sum(1 for v in gen if abs(v - lo) <= tol) / len(gen)
-            frac_hi = sum(1 for v in gen if abs(v - hi) <= tol) / len(gen)
-        else:
-            frac_lo = frac_hi = 0.0
-        ks_rows.append((c, ks, frac_lo, frac_hi, len(real_vals[c]), len(gen_vals[c]), lo, hi))
-
-    ks_rows.sort(key=lambda x: x[1], reverse=True)
-    out_csv = out_dir / "ks_per_feature.csv"
-    with out_csv.open("w", newline="") as fh:
-        w = csv.writer(fh)
-        w.writerow(["feature", "ks", "gen_frac_at_min", "gen_frac_at_max", "real_n", "gen_n", "real_min", "real_max"])
-        for row in ks_rows:
-            w.writerow(row)
-
-    # top-k CDF plots
-    for c, ks, _, _, _, _, lo, hi in ks_rows[: args.top_k]:
-        out_svg = out_dir / f"cdf_{c}.svg"
-        render_cdf_svg(out_svg, c, real_vals[c], gen_vals[c], bounds=(lo, hi))
-
-    # summary
-    summary = {
-        "generated_rows": gen_rows,
-        "reference_rows_per_file": args.max_rows if args.max_rows > 0 else "full",
-        "stride": args.stride,
-        "top_k_features": [r[0] for r in ks_rows[: args.top_k]],
-    }
-    (out_dir / "ks_summary.json").write_text(json.dumps(summary, indent=2), encoding="utf-8")
-
-    print(f"wrote {out_csv}")
-    print(f"wrote CDF svgs for top {args.top_k} features")
-
-
-if __name__ == "__main__":
-    main()

example/evaluate_generated.py

@@ -75,16 +75,15 @@ def ks_statistic(x: List[float], y: List[float]) -> float:
     n = len(x_sorted)
     m = len(y_sorted)
     i = j = 0
+    cdf_x = cdf_y = 0.0
     d = 0.0
-    # Iterate over merged unique values to handle ties correctly
-    merged = sorted(set(x_sorted) | set(y_sorted))
-    for v in merged:
-        while i < n and x_sorted[i] <= v:
+    while i < n and j < m:
+        if x_sorted[i] <= y_sorted[j]:
             i += 1
-        while j < m and y_sorted[j] <= v:
+            cdf_x = i / n
+        else:
             j += 1
-        cdf_x = i / n
-        cdf_y = j / m
+            cdf_y = j / m
         d = max(d, abs(cdf_x - cdf_y))
     return d
 
@@ -104,43 +103,31 @@ def lag1_corr(values: List[float]) -> float:
     return num / math.sqrt(den_x * den_y)
 
 
-def resolve_reference_paths(path: str) -> List[str]:
+def resolve_reference_path(path: str) -> Optional[str]:
     if not path:
-        return []
+        return None
     if any(ch in path for ch in ["*", "?", "["]):
-        base = Path(path).parent.resolve()
+        base = Path(path).parent
         pat = Path(path).name
         matches = sorted(base.glob(pat))
-        return [str(p) for p in matches]
-    return [str(path)]
+        return str(matches[0]) if matches else None
+    return str(path)
 
 
 def main():
     args = parse_args()
     base_dir = Path(__file__).resolve().parent
-
-    def resolve_file(p: str) -> str:
-        path = Path(p)
-        if path.is_absolute():
-            return str(path)
-        if path.exists():
-            return str(path.resolve())
-        candidate = base_dir / path
-        if candidate.exists():
-            return str(candidate.resolve())
-        return str((base_dir / path).resolve())
-
-    args.generated = resolve_file(args.generated)
-    args.split = resolve_file(args.split)
-    args.stats = resolve_file(args.stats)
-    args.vocab = resolve_file(args.vocab)
-    args.out = resolve_file(args.out)
+    args.generated = str((base_dir / args.generated).resolve()) if not Path(args.generated).is_absolute() else args.generated
+    args.split = str((base_dir / args.split).resolve()) if not Path(args.split).is_absolute() else args.split
+    args.stats = str((base_dir / args.stats).resolve()) if not Path(args.stats).is_absolute() else args.stats
+    args.vocab = str((base_dir / args.vocab).resolve()) if not Path(args.vocab).is_absolute() else args.vocab
+    args.out = str((base_dir / args.out).resolve()) if not Path(args.out).is_absolute() else args.out
     if args.reference and not Path(args.reference).is_absolute():
         if any(ch in args.reference for ch in ["*", "?", "["]):
             args.reference = str(base_dir / args.reference)
         else:
             args.reference = str((base_dir / args.reference).resolve())
-    ref_paths = resolve_reference_paths(args.reference)
+    ref_path = resolve_reference_path(args.reference)
     split = load_json(args.split)
     time_col = split.get("time_column", "time")
     cont_cols = [c for c in split["continuous"] if c != time_col]
@@ -169,7 +156,7 @@ def main():
                 except Exception:
                     v = 0.0
                 update_stats(cont_stats, c, v)
-                if ref_paths:
+                if ref_path:
                     pass
             for c in disc_cols:
                 if row[c] not in vocab_sets[c]:
@@ -195,7 +182,7 @@ def main():
     }
 
     # Optional richer metrics using reference data
-    if ref_paths:
+    if ref_path:
         ref_cont = {c: [] for c in cont_cols}
         ref_disc = {c: {} for c in disc_cols}
         gen_cont = {c: [] for c in cont_cols}
@@ -215,26 +202,21 @@ def main():
                     tok = row[c]
                     gen_disc[c][tok] = gen_disc[c].get(tok, 0) + 1
 
-        loaded = 0
-        for ref_path in ref_paths:
-            with open_csv(ref_path) as f:
-                reader = csv.DictReader(f)
-                for row in reader:
-                    if time_col in row:
-                        row.pop(time_col, None)
-                    for c in cont_cols:
-                        try:
-                            ref_cont[c].append(float(row[c]))
-                        except Exception:
-                            ref_cont[c].append(0.0)
-                    for c in disc_cols:
-                        tok = row[c]
-                        ref_disc[c][tok] = ref_disc[c].get(tok, 0) + 1
-                    loaded += 1
-                    if args.max_rows and loaded >= args.max_rows:
-                        break
-            if args.max_rows and loaded >= args.max_rows:
-                break
+        with open_csv(ref_path) as f:
+            reader = csv.DictReader(f)
+            for i, row in enumerate(reader):
+                if time_col in row:
+                    row.pop(time_col, None)
+                for c in cont_cols:
+                    try:
+                        ref_cont[c].append(float(row[c]))
+                    except Exception:
+                        ref_cont[c].append(0.0)
+                for c in disc_cols:
+                    tok = row[c]
+                    ref_disc[c][tok] = ref_disc[c].get(tok, 0) + 1
+                if args.max_rows and i + 1 >= args.max_rows:
+                    break
 
         # Continuous metrics: KS + quantiles + lag1 correlation
         cont_ks = {}

example/export_samples.py

@@ -12,7 +12,7 @@ from typing import Dict, List
 import torch
 import torch.nn.functional as F
 
-from data_utils import load_split, inverse_quantile_transform, quantile_calibrate_to_real
+from data_utils import load_split
 from hybrid_diffusion import HybridDiffusionModel, TemporalGRUGenerator, cosine_beta_schedule
 from platform_utils import resolve_device, safe_path, ensure_dir, resolve_path
 
@@ -112,9 +112,6 @@ def main():
     int_like = stats.get("int_like", {})
     max_decimals = stats.get("max_decimals", {})
     transforms = stats.get("transform", {})
-    quantile_probs = stats.get("quantile_probs")
-    quantile_values = stats.get("quantile_values")
-    quantile_raw_values = stats.get("quantile_raw_values")
 
     vocab_json = json.load(open(args.vocab_path, "r", encoding="utf-8"))
     vocab = vocab_json["vocab"]
@@ -143,28 +140,13 @@ def main():
                 raise SystemExit("use_condition enabled but no files matched data_glob: %s" % cfg_glob)
     cont_target = str(cfg.get("cont_target", "eps"))
     cont_clamp_x0 = float(cfg.get("cont_clamp_x0", 0.0))
-    use_quantile = bool(cfg.get("use_quantile_transform", False))
-    cont_bound_mode = str(cfg.get("cont_bound_mode", "clamp"))
-    cont_bound_strength = float(cfg.get("cont_bound_strength", 1.0))
-    cont_post_scale = cfg.get("cont_post_scale", {}) if isinstance(cfg.get("cont_post_scale", {}), dict) else {}
-    cont_post_calibrate = bool(cfg.get("cont_post_calibrate", False))
-    type1_cols = cfg.get("type1_features", []) or []
-    type5_cols = cfg.get("type5_features", []) or []
-    type1_cols = [c for c in type1_cols if c in cont_cols]
-    type5_cols = [c for c in type5_cols if c in cont_cols]
-    model_cont_cols = [c for c in cont_cols if c not in type1_cols and c not in type5_cols]
     use_temporal_stage1 = bool(cfg.get("use_temporal_stage1", False))
     temporal_hidden_dim = int(cfg.get("temporal_hidden_dim", 256))
     temporal_num_layers = int(cfg.get("temporal_num_layers", 1))
     temporal_dropout = float(cfg.get("temporal_dropout", 0.0))
-    backbone_type = str(cfg.get("backbone_type", "gru"))
-    transformer_num_layers = int(cfg.get("transformer_num_layers", 2))
-    transformer_nhead = int(cfg.get("transformer_nhead", 4))
-    transformer_ff_dim = int(cfg.get("transformer_ff_dim", 512))
-    transformer_dropout = float(cfg.get("transformer_dropout", 0.1))
 
     model = HybridDiffusionModel(
-        cont_dim=len(model_cont_cols),
+        cont_dim=len(cont_cols),
         disc_vocab_sizes=vocab_sizes,
         time_dim=int(cfg.get("model_time_dim", 64)),
         hidden_dim=int(cfg.get("model_hidden_dim", 256)),
@@ -173,12 +155,9 @@ def main():
         ff_mult=int(cfg.get("model_ff_mult", 2)),
         pos_dim=int(cfg.get("model_pos_dim", 64)),
         use_pos_embed=bool(cfg.get("model_use_pos_embed", True)),
-        backbone_type=backbone_type,
-        transformer_num_layers=transformer_num_layers,
-        transformer_nhead=transformer_nhead,
-        transformer_ff_dim=transformer_ff_dim,
-        transformer_dropout=transformer_dropout,
-        cond_cont_dim=len(type1_cols),
+        use_feature_graph=bool(cfg.get("model_use_feature_graph", False)),
+        feature_graph_scale=float(cfg.get("feature_graph_scale", 0.1)),
+        feature_graph_dropout=float(cfg.get("feature_graph_dropout", 0.0)),
         cond_vocab_size=cond_vocab_size if use_condition else 0,
         cond_dim=int(cfg.get("cond_dim", 32)),
         use_tanh_eps=bool(cfg.get("use_tanh_eps", False)),
@@ -194,7 +173,7 @@ def main():
     temporal_model = None
     if use_temporal_stage1:
         temporal_model = TemporalGRUGenerator(
-            input_dim=len(model_cont_cols),
+            input_dim=len(cont_cols),
             hidden_dim=temporal_hidden_dim,
             num_layers=temporal_num_layers,
             dropout=temporal_dropout,
@@ -209,7 +188,7 @@ def main():
     alphas = 1.0 - betas
     alphas_cumprod = torch.cumprod(alphas, dim=0)
 
-    x_cont = torch.randn(args.batch_size, args.seq_len, len(model_cont_cols), device=device)
+    x_cont = torch.randn(args.batch_size, args.seq_len, len(cont_cols), device=device)
     x_disc = torch.full(
         (args.batch_size, args.seq_len, len(disc_cols)),
         0,
@@ -231,39 +210,13 @@ def main():
             cond_id = torch.full((args.batch_size,), int(args.condition_id), device=device, dtype=torch.long)
         cond = cond_id
 
-    # type1 program conditioning (library replay)
-    cond_cont = None
-    if type1_cols:
-        ref_glob = cfg.get("data_glob") or args.data_glob
-        if ref_glob:
-            ref_glob = str(resolve_path(Path(args.config).parent, ref_glob)) if args.config else ref_glob
-            base = Path(ref_glob).parent
-            pat = Path(ref_glob).name
-            refs = sorted(base.glob(pat))
-            if refs:
-                ref_path = refs[0]
-                ref_rows = []
-                with gzip.open(ref_path, "rt", newline="") as fh:
-                    reader = csv.DictReader(fh)
-                    for row in reader:
-                        ref_rows.append(row)
-                if len(ref_rows) >= args.seq_len:
-                    seq = ref_rows[: args.seq_len]
-                    cond_cont = torch.zeros(args.batch_size, args.seq_len, len(type1_cols), device=device)
-                    for t, row in enumerate(seq):
-                        for i, c in enumerate(type1_cols):
-                            cond_cont[:, t, i] = float(row[c])
-                    mean_vec = torch.tensor([mean[c] for c in type1_cols], dtype=cond_cont.dtype, device=device)
-                    std_vec = torch.tensor([std[c] for c in type1_cols], dtype=cond_cont.dtype, device=device)
-                    cond_cont = (cond_cont - mean_vec) / std_vec
-
     trend = None
     if temporal_model is not None:
         trend = temporal_model.generate(args.batch_size, args.seq_len, device)
 
     for t in reversed(range(args.timesteps)):
         t_batch = torch.full((args.batch_size,), t, device=device, dtype=torch.long)
-        eps_pred, logits = model(x_cont, x_disc, t_batch, cond, cond_cont=cond_cont)
+        eps_pred, logits = model(x_cont, x_disc, t_batch, cond)
 
         a_t = alphas[t]
         a_bar_t = alphas_cumprod[t]
@@ -273,6 +226,10 @@ def main():
             if cont_clamp_x0 > 0:
                 x0_pred = torch.clamp(x0_pred, -cont_clamp_x0, cont_clamp_x0)
             eps_pred = (x_cont - torch.sqrt(a_bar_t) * x0_pred) / torch.sqrt(1.0 - a_bar_t)
+        elif cont_target == "v":
+            v_pred = eps_pred
+            x0_pred = torch.sqrt(a_bar_t) * x_cont - torch.sqrt(1.0 - a_bar_t) * v_pred
+            eps_pred = torch.sqrt(1.0 - a_bar_t) * x_cont + torch.sqrt(a_bar_t) * v_pred
         coef1 = 1.0 / torch.sqrt(a_t)
         coef2 = (1 - a_t) / torch.sqrt(1 - a_bar_t)
         mean_x = coef1 * (x_cont - coef2 * eps_pred)
@@ -307,70 +264,19 @@ def main():
     if args.clip_k > 0:
         x_cont = torch.clamp(x_cont, -args.clip_k, args.clip_k)
 
-    if use_quantile:
-        q_vals = {c: quantile_values[c] for c in model_cont_cols}
-        x_cont = inverse_quantile_transform(x_cont, model_cont_cols, quantile_probs, q_vals)
-    else:
-        mean_vec = torch.tensor([mean[c] for c in model_cont_cols], dtype=x_cont.dtype)
-        std_vec = torch.tensor([std[c] for c in model_cont_cols], dtype=x_cont.dtype)
-        x_cont = x_cont * std_vec + mean_vec
-    for i, c in enumerate(model_cont_cols):
+    mean_vec = torch.tensor([mean[c] for c in cont_cols], dtype=x_cont.dtype)
+    std_vec = torch.tensor([std[c] for c in cont_cols], dtype=x_cont.dtype)
+    x_cont = x_cont * std_vec + mean_vec
+    for i, c in enumerate(cont_cols):
         if transforms.get(c) == "log1p":
             x_cont[:, :, i] = torch.expm1(x_cont[:, :, i])
-    if cont_post_calibrate and quantile_raw_values and quantile_probs:
-        q_raw = {c: quantile_raw_values[c] for c in model_cont_cols}
-        x_cont = quantile_calibrate_to_real(x_cont, model_cont_cols, quantile_probs, q_raw)
-    # bound to observed min/max per feature
+    # clamp to observed min/max per feature
     if vmin and vmax:
-        for i, c in enumerate(model_cont_cols):
+        for i, c in enumerate(cont_cols):
             lo = vmin.get(c, None)
             hi = vmax.get(c, None)
-            if lo is None or hi is None:
-                continue
-            lo = float(lo)
-            hi = float(hi)
-            if cont_bound_mode == "none":
-                continue
-            if cont_bound_mode == "sigmoid":
-                x_cont[:, :, i] = lo + (hi - lo) * torch.sigmoid(x_cont[:, :, i])
-            elif cont_bound_mode == "soft_tanh":
-                # Soft bound without hard piling at edges
-                mid = 0.5 * (lo + hi)
-                half = 0.5 * (hi - lo)
-                denom = cont_bound_strength if cont_bound_strength > 0 else 1.0
-                x_cont[:, :, i] = mid + half * torch.tanh(x_cont[:, :, i] / denom)
-            else:
-                x_cont[:, :, i] = torch.clamp(x_cont[:, :, i], lo, hi)
-
-    # optional post-scaling for problematic features
-    if cont_post_scale:
-        for i, c in enumerate(model_cont_cols):
-            if c in cont_post_scale:
-                try:
-                    scale = float(cont_post_scale[c])
-                except Exception:
-                    scale = 1.0
-                x_cont[:, :, i] = x_cont[:, :, i] * scale
-
-    # assemble full continuous output
-    full_cont = torch.zeros(args.batch_size, args.seq_len, len(cont_cols), dtype=x_cont.dtype)
-    for i, c in enumerate(model_cont_cols):
-        full_idx = cont_cols.index(c)
-        full_cont[:, :, full_idx] = x_cont[:, :, i]
-    if cond_cont is not None and type1_cols:
-        mean_vec = torch.tensor([mean[c] for c in type1_cols], dtype=cond_cont.dtype)
-        std_vec = torch.tensor([std[c] for c in type1_cols], dtype=cond_cont.dtype)
-        cond_denorm = cond_cont.cpu() * std_vec + mean_vec
-        for i, c in enumerate(type1_cols):
-            full_idx = cont_cols.index(c)
-            full_cont[:, :, full_idx] = cond_denorm[:, :, i]
-    for c in type5_cols:
-        if c.endswith("Z"):
-            base = c[:-1]
-            if base in cont_cols:
-                bidx = cont_cols.index(base)
-                cidx = cont_cols.index(c)
-                full_cont[:, :, cidx] = full_cont[:, :, bidx]
+            if lo is not None and hi is not None:
+                x_cont[:, :, i] = torch.clamp(x_cont[:, :, i], float(lo), float(hi))
 
     header = read_header(data_path)
     out_cols = [c for c in header if c != time_col or args.include_time]
@@ -391,7 +297,7 @@ def main():
                 if args.include_time and time_col in header:
                     row[time_col] = str(row_index)
                 for i, c in enumerate(cont_cols):
-                    val = float(full_cont[b, t, i])
+                    val = float(x_cont[b, t, i])
                     if int_like.get(c, False):
                         row[c] = str(int(round(val)))
                     else:

example/filtered_metrics.py

@@ -1,65 +0,0 @@
-#!/usr/bin/env python3
-"""Compute filtered KS/JSD by excluding hard-to-learn features."""
-
-import argparse
-import json
-from pathlib import Path
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(description="Filtered metrics from eval.json.")
-    base_dir = Path(__file__).resolve().parent
-    parser.add_argument("--eval", default=str(base_dir / "results" / "eval.json"))
-    parser.add_argument("--min-std", type=float, default=1e-3, help="threshold for std collapse")
-    parser.add_argument("--ks-threshold", type=float, default=0.95, help="auto-exclude if KS >= threshold")
-    parser.add_argument("--out", default=str(base_dir / "results" / "filtered_metrics.json"))
-    return parser.parse_args()
-
-
-def main():
-    args = parse_args()
-    eval_path = Path(args.eval)
-    if not eval_path.exists():
-        raise SystemExit(f"missing eval.json: {eval_path}")
-    data = json.loads(eval_path.read_text(encoding="utf-8"))
-
-    cont_ks = data.get("continuous_ks", {})
-    cont_stats = data.get("continuous_summary", {})
-
-    dropped = []
-    kept = []
-    ks_vals = []
-    for feat, ks in cont_ks.items():
-        std = None
-        if feat in cont_stats:
-            std = cont_stats[feat].get("std", None)
-        drop = False
-        if std is not None and std <= args.min_std:
-            drop = True
-        if ks is not None and ks >= args.ks_threshold:
-            drop = True
-        if drop:
-            dropped.append({"feature": feat, "ks": ks, "std": std})
-        else:
-            kept.append(feat)
-            ks_vals.append(ks)
-
-    filtered_avg_ks = sum(ks_vals) / len(ks_vals) if ks_vals else None
-    out = {
-        "filtered_avg_ks": filtered_avg_ks,
-        "kept_features": kept,
-        "dropped_features": dropped,
-        "rules": {
-            "min_std": args.min_std,
-            "ks_threshold": args.ks_threshold,
-        },
-        "original_avg_ks": data.get("avg_ks"),
-    }
-    Path(args.out).write_text(json.dumps(out, indent=2), encoding="utf-8")
-    print("filtered_avg_ks", filtered_avg_ks)
-    print("dropped", len(dropped))
-    print("wrote", args.out)
-
-
-if __name__ == "__main__":
-    main()

example/hybrid_diffusion.py

@@ -66,8 +66,26 @@ class SinusoidalTimeEmbedding(nn.Module):
         return emb
 
 
+class FeatureGraphMixer(nn.Module):
+    """Learnable feature relation mixer (dataset-agnostic)."""
+
+    def __init__(self, dim: int, scale: float = 0.1, dropout: float = 0.0):
+        super().__init__()
+        self.scale = scale
+        self.dropout = nn.Dropout(dropout) if dropout > 0 else nn.Identity()
+        self.A = nn.Parameter(torch.zeros(dim, dim))
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        # x: (B, T, D)
+        # Symmetric relation to stabilize
+        A = (self.A + self.A.t()) * 0.5
+        mixed = torch.matmul(x, A) * self.scale
+        mixed = self.dropout(mixed)
+        return x + mixed
+
+
 class TemporalGRUGenerator(nn.Module):
-    """Stage-1 temporal generator for sequence trend."""
+    """Stage-1 temporal generator (autoregressive GRU) for sequence backbone."""
 
     def __init__(self, input_dim: int, hidden_dim: int = 256, num_layers: int = 1, dropout: float = 0.0):
         super().__init__()
@@ -118,12 +136,9 @@ class HybridDiffusionModel(nn.Module):
         ff_mult: int = 2,
         pos_dim: int = 64,
         use_pos_embed: bool = True,
-        backbone_type: str = "gru",  # gru | transformer
-        transformer_num_layers: int = 4,
-        transformer_nhead: int = 8,
-        transformer_ff_dim: int = 2048,
-        transformer_dropout: float = 0.1,
-        cond_cont_dim: int = 0,
+        use_feature_graph: bool = False,
+        feature_graph_scale: float = 0.1,
+        feature_graph_dropout: float = 0.0,
         cond_vocab_size: int = 0,
         cond_dim: int = 32,
         use_tanh_eps: bool = False,
@@ -138,14 +153,13 @@ class HybridDiffusionModel(nn.Module):
         self.eps_scale = eps_scale
         self.pos_dim = pos_dim
         self.use_pos_embed = use_pos_embed
-        self.backbone_type = backbone_type
+        self.use_feature_graph = use_feature_graph
 
         self.cond_vocab_size = cond_vocab_size
         self.cond_dim = cond_dim
         self.cond_embed = None
         if cond_vocab_size and cond_vocab_size > 0:
             self.cond_embed = nn.Embedding(cond_vocab_size, cond_dim)
-        self.cond_cont_dim = cond_cont_dim
 
         self.disc_embeds = nn.ModuleList([
             nn.Embedding(vocab_size + 1, min(32, vocab_size * 2))
@@ -154,29 +168,25 @@ class HybridDiffusionModel(nn.Module):
         disc_embed_dim = sum(e.embedding_dim for e in self.disc_embeds)
 
         self.cont_proj = nn.Linear(cont_dim, cont_dim)
-        pos_dim = pos_dim if use_pos_embed else 0
-        in_dim = cont_dim + disc_embed_dim + time_dim + pos_dim + (cond_dim if self.cond_embed is not None else 0)
-        if self.cond_cont_dim and self.cond_cont_dim > 0:
-            in_dim += self.cond_cont_dim
-        self.in_proj = nn.Linear(in_dim, hidden_dim)
-        if backbone_type == "transformer":
-            encoder_layer = nn.TransformerEncoderLayer(
-                d_model=hidden_dim,
-                nhead=transformer_nhead,
-                dim_feedforward=transformer_ff_dim,
-                dropout=transformer_dropout,
-                batch_first=True,
-                activation="gelu",
+        self.feature_dim = cont_dim + disc_embed_dim
+        if use_feature_graph:
+            self.feature_graph = FeatureGraphMixer(
+                self.feature_dim,
+                scale=feature_graph_scale,
+                dropout=feature_graph_dropout,
             )
-            self.backbone = nn.TransformerEncoder(encoder_layer, num_layers=transformer_num_layers)
         else:
-            self.backbone = nn.GRU(
-                hidden_dim,
-                hidden_dim,
-                num_layers=num_layers,
-                dropout=dropout if num_layers > 1 else 0.0,
-                batch_first=True,
-            )
+            self.feature_graph = None
+        pos_dim = pos_dim if use_pos_embed else 0
+        in_dim = self.feature_dim + time_dim + pos_dim + (cond_dim if self.cond_embed is not None else 0)
+        self.in_proj = nn.Linear(in_dim, hidden_dim)
+        self.backbone = nn.GRU(
+            hidden_dim,
+            hidden_dim,
+            num_layers=num_layers,
+            dropout=dropout if num_layers > 1 else 0.0,
+            batch_first=True,
+        )
         self.post_norm = nn.LayerNorm(hidden_dim)
         self.post_ff = nn.Sequential(
             nn.Linear(hidden_dim, hidden_dim * ff_mult),
@@ -190,14 +200,7 @@ class HybridDiffusionModel(nn.Module):
             for vocab_size in disc_vocab_sizes
         ])
 
-    def forward(
-        self,
-        x_cont: torch.Tensor,
-        x_disc: torch.Tensor,
-        t: torch.Tensor,
-        cond: torch.Tensor = None,
-        cond_cont: torch.Tensor = None,
-    ):
+    def forward(self, x_cont: torch.Tensor, x_disc: torch.Tensor, t: torch.Tensor, cond: torch.Tensor = None):
         """x_cont: (B,T,Cc), x_disc: (B,T,Cd) with integer tokens."""
         time_emb = self.time_embed(t)
         time_emb = time_emb.unsqueeze(1).expand(-1, x_cont.size(1), -1)
@@ -217,22 +220,18 @@ class HybridDiffusionModel(nn.Module):
             cond_feat = self.cond_embed(cond).unsqueeze(1).expand(-1, x_cont.size(1), -1)
 
         cont_feat = self.cont_proj(x_cont)
-        parts = [cont_feat, disc_feat, time_emb]
+        feat = torch.cat([cont_feat, disc_feat], dim=-1)
+        if self.feature_graph is not None:
+            feat = self.feature_graph(feat)
+        parts = [feat, time_emb]
         if pos_emb is not None:
             parts.append(pos_emb.unsqueeze(0).expand(x_cont.size(0), -1, -1))
         if cond_feat is not None:
             parts.append(cond_feat)
-        if self.cond_cont_dim and self.cond_cont_dim > 0:
-            if cond_cont is None:
-                raise ValueError("cond_cont is required when cond_cont_dim > 0")
-            parts.append(cond_cont)
         feat = torch.cat(parts, dim=-1)
         feat = self.in_proj(feat)
 
-        if self.backbone_type == "transformer":
-            out = self.backbone(feat)
-        else:
-            out, _ = self.backbone(feat)
+        out, _ = self.backbone(feat)
         out = self.post_norm(out)
         out = out + self.post_ff(out)
 

example/plot_loss.py

@@ -34,6 +34,7 @@ def main():
     loss = []
     loss_cont = []
     loss_disc = []
+    loss_quant = []
 
     with log_path.open("r", encoding="utf-8", newline="") as f:
         reader = csv.DictReader(f)
@@ -42,6 +43,8 @@ def main():
             loss.append(float(row["loss"]))
             loss_cont.append(float(row["loss_cont"]))
             loss_disc.append(float(row["loss_disc"]))
+            if "loss_quantile" in row:
+                loss_quant.append(float(row["loss_quantile"]))
 
     if not steps:
         raise SystemExit("no rows in log file: %s" % log_path)
@@ -50,6 +53,8 @@ def main():
     plt.plot(steps, loss, label="total")
     plt.plot(steps, loss_cont, label="continuous")
     plt.plot(steps, loss_disc, label="discrete")
+    if loss_quant:
+        plt.plot(steps, loss_quant, label="quantile")
     plt.xlabel("step")
     plt.ylabel("loss")
     plt.title("Training Loss")

example/postprocess_types.py

@@ -1,315 +0,0 @@
-#!/usr/bin/env python3
-"""Post-process generated.csv using Type1-6 heuristics (no training)."""
-
-import argparse
-import csv
-import gzip
-import json
-import math
-import random
-from pathlib import Path
-from typing import Dict, List, Tuple
-
-
-def parse_args():
-    base_dir = Path(__file__).resolve().parent
-    parser = argparse.ArgumentParser(description="Post-process Type1-6 features.")
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "generated_post.csv"))
-    parser.add_argument("--max-rows", type=int, default=200000)
-    parser.add_argument("--seed", type=int, default=1337)
-    return parser.parse_args()
-
-
-def resolve_reference_glob(ref_arg: str) -> str:
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]:
-    vals = {c: [] for c in cols}
-    opener = gzip.open if str(path).endswith(".gz") else open
-    with opener(path, "rt", newline="") as fh:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            for c in cols:
-                try:
-                    vals[c].append(float(row[c]))
-                except Exception:
-                    pass
-            if max_rows > 0 and i + 1 >= max_rows:
-                break
-    return vals
-
-
-def segment_stats(series: List[float]) -> Tuple[List[float], List[int]]:
-    if not series:
-        return [], []
-    values = []
-    dwells = []
-    current = series[0]
-    dwell = 1
-    for v in series[1:]:
-        if v == current:
-            dwell += 1
-        else:
-            values.append(current)
-            dwells.append(dwell)
-            current = v
-            dwell = 1
-    values.append(current)
-    dwells.append(dwell)
-    return values, dwells
-
-
-def sample_program(values: List[float], dwells: List[int], length: int) -> List[float]:
-    if not values:
-        return [0.0] * length
-    # sample values weighted by dwell lengths (empirical time proportion)
-    weights = [d for d in dwells]
-    total = sum(weights)
-    probs = [w / total for w in weights]
-    out = []
-    while len(out) < length:
-        v = random.choices(values, probs, k=1)[0]
-        d = random.choice(dwells)
-        out.extend([v] * d)
-    return out[:length]
-
-
-def sample_controller(series: List[float], length: int) -> List[float]:
-    if not series:
-        return [0.0] * length
-    vmin, vmax = min(series), max(series)
-    # change rate and step distribution
-    steps = []
-    changes = 0
-    prev = series[0]
-    for v in series[1:]:
-        if v != prev:
-            changes += 1
-            steps.append(abs(v - prev))
-        prev = v
-    change_rate = changes / max(len(series) - 1, 1)
-    if not steps:
-        steps = [0.0]
-    out = [random.choice(series)]
-    for _ in range(1, length):
-        v = out[-1]
-        if random.random() < change_rate:
-            step = random.choice(steps)
-            v = v + step if random.random() < 0.5 else v - step
-        v = min(max(v, vmin), vmax)
-        out.append(v)
-    return out
-
-
-def sample_actuator(series: List[float], length: int) -> List[float]:
-    if not series:
-        return [0.0] * length
-    rounded = [round(v, 2) for v in series]
-    values, dwells = segment_stats(rounded)
-    if not values:
-        return [rounded[0]] * length
-    # top modes by frequency
-    counts = {}
-    for v in rounded:
-        counts[v] = counts.get(v, 0) + 1
-    modes = sorted(counts.items(), key=lambda kv: kv[1], reverse=True)
-    top_vals = [v for v, _ in modes[:5]]
-    probs = [counts[v] for v in top_vals]
-    total = sum(probs)
-    probs = [p / total for p in probs]
-
-    out = []
-    while len(out) < length:
-        v = random.choices(top_vals, probs, k=1)[0]
-        d = random.choice(dwells)
-        out.extend([v] * d)
-    return out[:length]
-
-
-def sample_ar1(series: List[float], length: int) -> List[float]:
-    if not series:
-        return [0.0] * length
-    n = len(series)
-    mean = sum(series) / n
-    var = sum((x - mean) ** 2 for x in series) / max(n - 1, 1)
-    std = math.sqrt(var) if var > 0 else 0.0
-    if n < 2 or std == 0:
-        return [mean] * length
-    # lag1
-    x = series[:-1]
-    y = series[1:]
-    mx = sum(x) / len(x)
-    my = sum(y) / len(y)
-    num = sum((a - mx) * (b - my) for a, b in zip(x, y))
-    denx = sum((a - mx) ** 2 for a in x)
-    deny = sum((b - my) ** 2 for b in y)
-    phi = num / (math.sqrt(denx * deny)) if denx > 0 and deny > 0 else 0.0
-    phi = max(min(phi, 0.99), -0.99)
-    noise_std = std * math.sqrt(max(1 - phi * phi, 1e-6))
-    out = [series[0]]
-    for _ in range(1, length):
-        v = mean + phi * (out[-1] - mean) + random.gauss(0, noise_std)
-        out.append(v)
-    return out
-
-
-def sample_empirical(series: List[float], length: int) -> List[float]:
-    if not series:
-        return [0.0] * length
-    return random.choices(series, k=length)
-
-
-def sample_actuator_dynamics(series: List[float], length: int) -> List[float]:
-    """Actuator generator with dwell + occasional moves + saturation."""
-    if not series:
-        return [0.0] * length
-    vmin, vmax = min(series), max(series)
-    # estimate dwell probability and step sizes
-    steps = []
-    stays = 0
-    total = 0
-    prev = series[0]
-    for v in series[1:]:
-        total += 1
-        if v == prev:
-            stays += 1
-        else:
-            steps.append(abs(v - prev))
-        prev = v
-    prob_stay = stays / total if total > 0 else 0.8
-    if not steps:
-        steps = [0.0]
-    # saturation probability from empirical bounds
-    sat_eps = max((vmax - vmin) * 0.01, 1e-6)
-    sat_count = sum(1 for v in series if v <= vmin + sat_eps or v >= vmax - sat_eps)
-    prob_sat = sat_count / len(series) if series else 0.1
-
-    out = [random.choice(series)]
-    for _ in range(1, length):
-        v = out[-1]
-        r = random.random()
-        if r < prob_sat:
-            v = vmin if random.random() < 0.5 else vmax
-        elif r < prob_sat + prob_stay:
-            v = v
-        else:
-            step = random.choice(steps)
-            v = v + step if random.random() < 0.5 else v - step
-            v = min(max(v, vmin), vmax)
-        out.append(v)
-    return out
-
-
-def post_calibrate(series: List[float], target: List[float]) -> List[float]:
-    """Quantile-map series to match target distribution."""
-    if not series or not target:
-        return series
-    xs = sorted(series)
-    ys = sorted(target)
-    n = len(xs)
-    m = len(ys)
-    out = []
-    for v in series:
-        # percentile in generated
-        lo = 0
-        hi = n - 1
-        while lo < hi:
-            mid = (lo + hi) // 2
-            if xs[mid] < v:
-                lo = mid + 1
-            else:
-                hi = mid
-        p = lo / max(n - 1, 1)
-        idx = int(round(p * (m - 1)))
-        idx = max(0, min(m - 1, idx))
-        out.append(ys[idx])
-    return out
-
-
-def main():
-    args = parse_args()
-    random.seed(args.seed)
-
-    cfg = json.loads(Path(args.config).read_text(encoding="utf-8"))
-    type1 = cfg.get("type1_features", [])
-    type2 = cfg.get("type2_features", [])
-    type3 = cfg.get("type3_features", [])
-    type4 = cfg.get("type4_features", [])
-    type5 = cfg.get("type5_features", [])
-    type6 = cfg.get("type6_features", [])
-
-    # Read generated data
-    gen_path = Path(args.generated)
-    with open(gen_path, "r", newline="", encoding="utf-8") as fh:
-        reader = csv.DictReader(fh)
-        rows = list(reader)
-    if not rows:
-        raise SystemExit("generated.csv empty")
-    length = len(rows)
-
-    # Reference values for selected features
-    ref_glob = resolve_reference_glob(args.reference)
-    ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name))
-    ref_features = sorted(set(type1 + type2 + type3 + type4 + type5 + type6))
-    ref_vals = {c: [] for c in ref_features}
-    for p in ref_paths:
-        vals = read_series(p, ref_features, args.max_rows)
-        for c in ref_features:
-            ref_vals[c].extend(vals[c])
-
-    # Type1 programs -> empirical resample (best KS)
-    for c in type1:
-        series = sample_empirical(ref_vals.get(c, []), length)
-        for i, v in enumerate(series):
-            rows[i][c] = str(v)
-
-    # Type2 controllers -> empirical resample (best KS)
-    for c in type2:
-        series = sample_empirical(ref_vals.get(c, []), length)
-        for i, v in enumerate(series):
-            rows[i][c] = str(v)
-
-    # Type3 actuators -> empirical resample (best KS)
-    for c in type3:
-        series = sample_empirical(ref_vals.get(c, []), length)
-        for i, v in enumerate(series):
-            rows[i][c] = str(v)
-
-    # Type4 PV (keep as generated for now)
-    # Type5 derived: empirical resample from derived reference (best KS)
-    for c in type5:
-        series = sample_empirical(ref_vals.get(c, []), length)
-        for i, v in enumerate(series):
-            rows[i][c] = str(v)
-
-    # Type6 aux -> empirical resample (best KS)
-    for c in type6:
-        series = sample_empirical(ref_vals.get(c, []), length)
-        for i, v in enumerate(series):
-            rows[i][c] = str(v)
-
-    out_path = Path(args.out)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    with open(out_path, "w", newline="", encoding="utf-8") as fh:
-        writer = csv.DictWriter(fh, fieldnames=rows[0].keys())
-        writer.writeheader()
-        writer.writerows(rows)
-    print("wrote", out_path)
-
-
-if __name__ == "__main__":
-    main()

example/prepare_data.py

@@ -17,19 +17,6 @@ OUT_VOCAB = BASE_DIR / "results" / "disc_vocab.json"
 
 
 def main(max_rows: Optional[int] = None):
-    config_path = BASE_DIR / "config.json"
-    use_quantile = False
-    quantile_bins = None
-    full_stats = False
-    if config_path.exists():
-        cfg = json.loads(config_path.read_text(encoding="utf-8"))
-        use_quantile = bool(cfg.get("use_quantile_transform", False))
-        quantile_bins = int(cfg.get("quantile_bins", 0)) if use_quantile else None
-        full_stats = bool(cfg.get("full_stats", False))
-
-    if full_stats:
-        max_rows = None
-
     split = load_split(safe_path(SPLIT_PATH))
     time_col = split.get("time_column", "time")
     cont_cols = [c for c in split["continuous"] if c != time_col]
@@ -41,13 +28,7 @@ def main(max_rows: Optional[int] = None):
     data_paths = [safe_path(p) for p in data_paths]
 
     transforms, _ = choose_cont_transforms(data_paths, cont_cols, max_rows=max_rows)
-    cont_stats = compute_cont_stats(
-        data_paths,
-        cont_cols,
-        max_rows=max_rows,
-        transforms=transforms,
-        quantile_bins=quantile_bins,
-    )
+    cont_stats = compute_cont_stats(data_paths, cont_cols, max_rows=max_rows, transforms=transforms)
     vocab, top_token = build_disc_stats(data_paths, disc_cols, max_rows=max_rows)
 
     ensure_dir(OUT_STATS.parent)
@@ -65,9 +46,6 @@ def main(max_rows: Optional[int] = None):
                 "transform": cont_stats["transform"],
                 "skew": cont_stats["skew"],
                 "max_rows": cont_stats["max_rows"],
-                "quantile_probs": cont_stats["quantile_probs"],
-                "quantile_values": cont_stats["quantile_values"],
-                "quantile_raw_values": cont_stats["quantile_raw_values"],
             },
             f,
             indent=2,

example/program_stats.py

@@ -1,142 +0,0 @@
-#!/usr/bin/env python3
-"""Compute program-style stats (dwell, change count, step size) for selected features."""
-
-import argparse
-import csv
-import gzip
-import json
-from pathlib import Path
-from typing import Dict, List
-
-
-def parse_args():
-    base_dir = Path(__file__).resolve().parent
-    parser = argparse.ArgumentParser(description="Program stats for setpoints/demands.")
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--features", default="", help="comma-separated list; empty = auto from eval")
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "program_stats.json"))
-    parser.add_argument("--max-rows", type=int, default=200000)
-    return parser.parse_args()
-
-
-def resolve_reference_glob(ref_arg: str) -> str:
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        # avoid resolve on glob patterns
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]:
-    vals = {c: [] for c in cols}
-    opener = gzip.open if str(path).endswith(".gz") else open
-    with opener(path, "rt", newline="") as fh:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            for c in cols:
-                try:
-                    vals[c].append(float(row[c]))
-                except Exception:
-                    pass
-            if max_rows > 0 and i + 1 >= max_rows:
-                break
-    return vals
-
-
-def dwell_and_steps(series: List[float]):
-    if not series:
-        return {
-            "num_changes": 0,
-            "mean_dwell": None,
-            "median_dwell": None,
-            "mean_step": None,
-            "median_step": None,
-        }
-    changes = 0
-    dwells = []
-    steps = []
-    current = series[0]
-    dwell = 1
-    for v in series[1:]:
-        if v == current:
-            dwell += 1
-            continue
-        changes += 1
-        dwells.append(dwell)
-        steps.append(abs(v - current))
-        current = v
-        dwell = 1
-    dwells.append(dwell)
-
-    def mean(x):
-        return sum(x) / len(x) if x else None
-
-    def median(x):
-        if not x:
-            return None
-        xs = sorted(x)
-        mid = len(xs) // 2
-        return xs[mid] if len(xs) % 2 == 1 else 0.5 * (xs[mid - 1] + xs[mid])
-
-    return {
-        "num_changes": changes,
-        "mean_dwell": mean(dwells),
-        "median_dwell": median(dwells),
-        "mean_step": mean(steps),
-        "median_step": median(steps),
-    }
-
-
-def main():
-    args = parse_args()
-    out_path = Path(args.out)
-
-    eval_path = Path("results") / "eval.json"
-    auto_feats = []
-    if eval_path.exists():
-        data = json.loads(eval_path.read_text(encoding="utf-8"))
-        ks = data.get("continuous_ks", {})
-        auto_feats = [k for k, v in ks.items() if v >= 0.6]
-
-    features = [f.strip() for f in args.features.split(",") if f.strip()] or auto_feats
-    if not features and Path(args.config).exists():
-        cfg = json.loads(Path(args.config).read_text(encoding="utf-8"))
-        features = cfg.get("type1_features", []) or []
-    if not features:
-        raise SystemExit("no features specified and no eval.json with ks>=0.6")
-
-    # generated series
-    gen_vals = read_series(Path(args.generated), features, args.max_rows)
-
-    # reference series (aggregate across files)
-    ref_glob = resolve_reference_glob(args.reference)
-    ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name))
-    if not ref_paths:
-        raise SystemExit(f"no reference files matched: {ref_glob}")
-    real_vals = {c: [] for c in features}
-    for p in ref_paths:
-        vals = read_series(p, features, args.max_rows)
-        for c in features:
-            real_vals[c].extend(vals[c])
-
-    out = {"features": features, "generated": {}, "reference": {}}
-    for c in features:
-        out["generated"][c] = dwell_and_steps(gen_vals[c])
-        out["reference"][c] = dwell_and_steps(real_vals[c])
-
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    out_path.write_text(json.dumps(out, indent=2), encoding="utf-8")
-    print("wrote", out_path)
-
-
-if __name__ == "__main__":
-    main()

example/pv_stats.py

@@ -1,102 +0,0 @@
-#!/usr/bin/env python3
-"""Stats for PV sensors (Type 4) with heavy tails / regime changes."""
-
-import argparse
-import csv
-import gzip
-import json
-from pathlib import Path
-from typing import Dict, List
-
-
-def parse_args():
-    base_dir = Path(__file__).resolve().parent
-    parser = argparse.ArgumentParser(description="PV stats.")
-    parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv"))
-    parser.add_argument("--reference", default=str(base_dir / "config.json"))
-    parser.add_argument("--features", default="", help="comma-separated list")
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "pv_stats.json"))
-    parser.add_argument("--max-rows", type=int, default=200000)
-    return parser.parse_args()
-
-
-def resolve_reference_glob(ref_arg: str) -> str:
-    ref_path = Path(ref_arg)
-    if ref_path.suffix == ".json":
-        cfg = json.loads(ref_path.read_text(encoding="utf-8"))
-        data_glob = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if not data_glob:
-            raise SystemExit("reference config has no data_glob/data_path")
-        combined = ref_path.parent / data_glob
-        if "*" in str(combined) or "?" in str(combined):
-            return str(combined)
-        return str(combined.resolve())
-    return str(ref_path)
-
-
-def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]:
-    vals = {c: [] for c in cols}
-    opener = gzip.open if str(path).endswith(".gz") else open
-    with opener(path, "rt", newline="") as fh:
-        reader = csv.DictReader(fh)
-        for i, row in enumerate(reader):
-            for c in cols:
-                try:
-                    vals[c].append(float(row[c]))
-                except Exception:
-                    pass
-            if max_rows > 0 and i + 1 >= max_rows:
-                break
-    return vals
-
-
-def quantile_stats(series: List[float]):
-    if not series:
-        return {"q05": None, "q50": None, "q95": None, "tail_ratio": None}
-    xs = sorted(series)
-    n = len(xs)
-    def q(p):
-        idx = int(round(p * (n - 1)))
-        idx = max(0, min(n - 1, idx))
-        return xs[idx]
-    q05 = q(0.05)
-    q50 = q(0.5)
-    q95 = q(0.95)
-    tail_ratio = (q95 - q50) / (q50 - q05) if (q50 - q05) != 0 else None
-    return {"q05": q05, "q50": q50, "q95": q95, "tail_ratio": tail_ratio}
-
-
-def main():
-    args = parse_args()
-    features = [f.strip() for f in args.features.split(",") if f.strip()]
-    if not features and Path(args.config).exists():
-        cfg = json.loads(Path(args.config).read_text(encoding="utf-8"))
-        features = cfg.get("type4_features", []) or []
-    if not features:
-        raise SystemExit("no features specified for pv_stats")
-
-    gen_vals = read_series(Path(args.generated), features, args.max_rows)
-    ref_glob = resolve_reference_glob(args.reference)
-    ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name))
-    if not ref_paths:
-        raise SystemExit(f"no reference files matched: {ref_glob}")
-    real_vals = {c: [] for c in features}
-    for p in ref_paths:
-        vals = read_series(p, features, args.max_rows)
-        for c in features:
-            real_vals[c].extend(vals[c])
-
-    out = {"features": features, "generated": {}, "reference": {}}
-    for c in features:
-        out["generated"][c] = quantile_stats(gen_vals[c])
-        out["reference"][c] = quantile_stats(real_vals[c])
-
-    out_path = Path(args.out)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    out_path.write_text(json.dumps(out, indent=2), encoding="utf-8")
-    print("wrote", out_path)
-
-
-if __name__ == "__main__":
-    main()

example/ranked_ks.py

@@ -1,64 +0,0 @@
-#!/usr/bin/env python3
-"""Rank per-feature KS and show cumulative effect on avg_ks."""
-
-import argparse
-import json
-from pathlib import Path
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(description="Rank KS from eval.json.")
-    base_dir = Path(__file__).resolve().parent
-    parser.add_argument("--eval", default=str(base_dir / "results" / "eval.json"))
-    parser.add_argument("--out", default=str(base_dir / "results" / "ranked_ks.csv"))
-    parser.add_argument("--top", type=int, default=20)
-    return parser.parse_args()
-
-
-def main():
-    args = parse_args()
-    eval_path = Path(args.eval)
-    if not eval_path.exists():
-        raise SystemExit(f"missing eval.json: {eval_path}")
-    data = json.loads(eval_path.read_text(encoding="utf-8"))
-    cont_ks = data.get("continuous_ks", {})
-    feats = sorted(cont_ks.items(), key=lambda kv: kv[1], reverse=True)
-    n = len(feats)
-    if n == 0:
-        raise SystemExit("continuous_ks empty")
-
-    total = sum(v for _, v in feats)
-    rows = []
-    cumulative = 0.0
-    for rank, (feat, ks) in enumerate(feats, 1):
-        contribution = ks / n
-        cumulative += ks
-        remaining = n - rank
-        avg_if_removed = (total - cumulative) / remaining if remaining > 0 else None
-        rows.append(
-            {
-                "rank": rank,
-                "feature": feat,
-                "ks": ks,
-                "contribution_to_avg": contribution,
-                "avg_ks_if_remove_top_n": avg_if_removed,
-            }
-        )
-
-    out_path = Path(args.out)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    with out_path.open("w", encoding="utf-8") as f:
-        f.write("rank,feature,ks,contribution_to_avg,avg_ks_if_remove_top_n\n")
-        for r in rows:
-            avg = "" if r["avg_ks_if_remove_top_n"] is None else f"{r['avg_ks_if_remove_top_n']:.6f}"
-            f.write(f"{r['rank']},{r['feature']},{r['ks']:.6f},{r['contribution_to_avg']:.6f},{avg}\n")
-
-    print(f"wrote {out_path}")
-    print("top features:")
-    for r in rows[: args.top]:
-        avg = "NA" if r["avg_ks_if_remove_top_n"] is None else f"{r['avg_ks_if_remove_top_n']:.6f}"
-        print(r["rank"], r["feature"], r["ks"], avg)
-
-
-if __name__ == "__main__":
-    main()

example/results/actuator_stats.json

@@ -1,60 +0,0 @@
-{
-  "features": [
-    "P1_PCV02Z",
-    "P1_PCV01Z",
-    "P1_PCV01D",
-    "P1_FCV02Z"
-  ],
-  "generated": {
-    "P1_PCV02Z": {
-      "unique_ratio": 0.005859375,
-      "top1_mass": 0.837890625,
-      "top3_mass": 1.0,
-      "median_dwell": 2
-    },
-    "P1_PCV01Z": {
-      "unique_ratio": 0.96484375,
-      "top1_mass": 0.0078125,
-      "top3_mass": 0.01953125,
-      "median_dwell": 1
-    },
-    "P1_PCV01D": {
-      "unique_ratio": 0.91796875,
-      "top1_mass": 0.08203125,
-      "top3_mass": 0.087890625,
-      "median_dwell": 1
-    },
-    "P1_FCV02Z": {
-      "unique_ratio": 0.033203125,
-      "top1_mass": 0.548828125,
-      "top3_mass": 0.77734375,
-      "median_dwell": 1
-    }
-  },
-  "reference": {
-    "P1_PCV02Z": {
-      "unique_ratio": 1.8333333333333333e-05,
-      "top1_mass": 0.42507,
-      "top3_mass": 0.7653283333333334,
-      "median_dwell": 2
-    },
-    "P1_PCV01Z": {
-      "unique_ratio": 0.012016666666666667,
-      "top1_mass": 0.00707,
-      "top3_mass": 0.014783333333333334,
-      "median_dwell": 1
-    },
-    "P1_PCV01D": {
-      "unique_ratio": 0.012345,
-      "top1_mass": 0.07126,
-      "top3_mass": 0.07228166666666666,
-      "median_dwell": 1
-    },
-    "P1_FCV02Z": {
-      "unique_ratio": 0.013231666666666666,
-      "top1_mass": 0.20116333333333333,
-      "top3_mass": 0.3798166666666667,
-      "median_dwell": 1
-    }
-  }
-}

example/results/aux_stats.json

@@ -1,41 +0,0 @@
-{
-  "features": [
-    "P4_HT_PO",
-    "P2_24Vdc",
-    "P2_HILout"
-  ],
-  "generated": {
-    "P4_HT_PO": {
-      "mean": 29.184932050781132,
-      "std": 33.831956865401764,
-      "lag1": 0.9797486298510993
-    },
-    "P2_24Vdc": {
-      "mean": 28.028544042968765,
-      "std": 0.003451975052533648,
-      "lag1": 0.020928662135364914
-    },
-    "P2_HILout": {
-      "mean": 711.4806033398439,
-      "std": 9.190482116909244,
-      "lag1": 0.19851457149668425
-    }
-  },
-  "reference": {
-    "P4_HT_PO": {
-      "mean": 34.10443252424018,
-      "std": 31.497164332273172,
-      "lag1": 0.999100876060727
-    },
-    "P2_24Vdc": {
-      "mean": 28.02872425277559,
-      "std": 0.0033485698875075085,
-      "lag1": 0.05678954319387766
-    },
-    "P2_HILout": {
-      "mean": 711.3129027199009,
-      "std": 8.429535135982476,
-      "lag1": 0.28582350589420713
-    }
-  }
-}

example/results/cdf_P1_B3004.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P1_B3004</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="50,367 86,362 97,360 107,356 112,354 121,354 136,354 138,352 162,349 162,349 166,349 173,344 175,341 176,339 177,336 187,333 187,333 195,333 202,333 220,333 222,332 223,332 226,332 234,332 234,332 235,332 236,332 238,332 241,332 254,332 256,329 257,329 265,329 281,329 281,329 282,323 288,319 289,317 290,317 292,317 293,314 293,312 294,310 295,309 295,309 295,309 296,309 298,305 301,305 301,304 303,304 303,300 304,300 307,300 307,300 315,300 316,300 317,300 318,297 319,291 324,288 326,286 326,286 327,286 327,281 332,281 334,281 334,278 334,278 334,271 334,270 335,264 336,261 336,261 337,258 340,256 342,256 347,251 348,251 349,251 349,251 349,251 352,251 357,246 358,244 359,244 361,244 363,244 364,244 364,241 365,241 367,241 368,235 369,233 371,233 371,233 371,233 372,233 373,231 373,228 374,228 374,228 378,228 382,228 382,228 382,228 389,222 391,222 391,222 391,222 393,220 396,220 399,220 400,220 400,220 401,220 401,218 403,218 403,212 404,202 404,202 406,202 407,202 407,199 407,197 408,194 409,194 410,194 411,158 411,158 412,158 412,155 414,153 414,148 419,142 421,142 422,142 422,136 423,133 423,129 424,129 425,129 425,126 426,120 427,120 428,118 428,118 428,118 430,118 431,115 431,115 431,112 434,112 434,106 435,103 440,103 478,103 480,103 481,100 487,100 494,96 497,96 504,96 508,96 520,96 522,96 527,95 529,92 536,92 539,89 542,89 546,89 551,89 554,89 562,89 566,89 573,89 577,89 583,89 588,89 595,86 598,86 604,86 613,86 626,86 628,86 629,86 634,82 643,79 646,79 663,76 669,76 710,76 710,76 718,76 719,72 723,70 730,70 732,69 741,65 746,64 752,64 752,62 792,62 797,60 803,58 820,58 824,56 847,54 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="332,364 378,358 429,352 472,346 506,340 511,334 517,327 517,321 529,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P1_B4002.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P1_B4002</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="50,363 63,363 63,363 76,363 76,363 89,363 96,354 96,354 102,354 102,354 106,354 115,354 115,354 116,354 126,354 128,354 128,354 133,351 133,351 137,351 139,351 141,351 141,351 141,351 147,351 149,351 154,351 154,351 157,351 157,351 165,351 167,351 167,351 167,351 173,351 177,351 180,351 180,351 180,351 183,351 188,351 188,351 193,351 193,351 196,351 198,351 204,351 206,351 206,351 208,351 212,351 218,351 220,351 220,351 226,351 227,341 227,341 228,341 228,341 231,341 232,341 233,341 233,341 233,341 234,332 234,332 235,332 235,332 236,332 237,332 237,332 238,332 238,332 239,332 239,332 240,332 241,332 242,332 242,327 243,327 243,327 243,327 244,327 244,327 244,327 245,327 245,327 245,327 245,327 246,327 246,327 246,327 247,327 247,327 247,327 248,317 248,317 248,317 248,317 249,317 249,317 249,317 249,317 249,317 249,317 250,317 250,317 250,317 250,317 251,317 251,317 251,317 251,317 251,317 252,317 252,317 253,317 253,317 253,317 253,317 253,317 254,317 254,317 254,317 255,317 255,317 255,317 255,317 255,317 256,317 256,317 256,317 256,317 257,317 257,317 257,317 257,317 257,317 258,317 258,317 258,317 259,197 259,197 259,197 259,197 259,197 259,197 259,197 259,197 259,197 259,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 260,197 261,197 261,197 261,197 261,197 261,197 261,197 261,197 261,197 261,197 261,192 261,192 261,192 262,192 262,192 263,192 264,192 264,192 264,192 265,192 266,192 266,192 266,192 266,192 266,192 267,192 268,192 268,192 269,192 270,192 270,192 271,192 271,192 271,192 271,192 272,192 272,192 273,192 273,192 273,192 273,192 274,192 275,192 275,192 275,192 276,192 276,192 277,192 277,192 278,192 278,192 278,192 279,192 279,192 280,192 280,192 281,192 281,192 283,192 283,192 283,192 284,192 284,192 284,192 284,192 285,192 285,192 285,192 287,192 287,192 287,192 288,192 288,192 289,192 290,192 290,192 291,192 291,192 291,192 292,192 292,192 292,192 292,192 292,192 293,192 293,192 294,192 295,192 295,192 295,192 295,192 295,192 295,192 296,192 296,192 297,187 298,187 299,187 299,187 300,187 301,187 303,187 303,187 303,187 306,187 306,187 306,187 307,187 308,187 309,187 309,187 310,187 310,187 310,187 311,187 311,187 312,187 312,187 314,187 314,187 317,182 317,182 318,182 319,182 322,182 324,182 324,182 324,182 324,182 324,182 325,182 327,182 327,182 327,182 333,182 334,182 335,182 335,182 337,182 339,182 340,182 341,182 343,182 344,182 347,182 350,182 351,182 352,182 354,182 356,182 356,182 356,182 357,182 358,182 359,182 359,182 361,182 361,182 363,182 367,182 369,182 369,182 370,182 372,182 372,182 373,182 375,177 375,177 376,177 378,177 384,177 384,177 384,177 386,177 388,177 389,177 389,177 390,177 391,177 393,177 394,177 395,173 397,173 399,173 399,173 399,173 402,173 403,173 404,173 405,173 406,173 406,173 408,173 409,173 412,173 413,173 414,173 415,173 417,173 421,173 421,173 422,173 422,173 422,173 422,173 424,173 426,168 426,168 428,168 428,168 428,168 429,168 430,168 430,168 431,168 432,168 434,168 435,168 437,168 437,168 439,168 439,168 439,168 440,168 441,168 441,168 441,168 442,168 443,168 443,168 444,168 444,168 445,168 447,168 448,168 449,168 449,168 450,168 450,168 451,168 453,168 453,168 453,168 454,168 454,168 455,168 455,168 457,168 457,168 458,168 458,168 458,168 460,158 462,158 463,158 466,158 467,158 467,144 470,144 471,144 473,144 473,139 473,139 475,139 476,139 479,139 480,139 482,139 484,139 485,139 486,139 486,139 487,139 487,139 488,139 490,139 491,139 493,139 493,139 496,139 496,139 497,139 499,139 501,139 502,139 502,139 504,139 504,139 507,139 510,139 511,139 513,139 515,139 517,139 518,134 519,134 520,134 520,134 520,130 524,130 529,130 530,130 543,130 552,130 554,130 557,130 564,130 567,130 572,130 584,130 590,130 590,130 591,130 598,130 614,130 616,130 617,130 623,130 628,130 632,130 637,130 650,130 656,130 659,130 661,130 665,130 666,130 682,130 684,130 690,130 700,130 702,130 702,130 708,130 715,130 723,130 731,130 734,130 739,130 746,130 747,130 755,130 756,130 768,130 776,130 778,130 780,74 789,64 802,59 813,59 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="50,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P1_PCV02Z.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P1_PCV02Z</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="50,370 72,370 75,370 79,370 83,370 87,370 88,370 90,370 94,341 100,341 101,341 105,341 105,341 108,341 109,341 111,341 113,341 116,206 117,206 118,206 119,206 121,206 122,206 123,206 124,206 124,206 125,206 126,206 127,205 130,205 131,205 133,205 134,205 138,158 144,158 149,158 161,157 183,157 716,157 738,157 750,157 755,157 761,132 763,132 764,132 765,132 766,132 767,132 767,132 768,132 769,132 772,132 772,132 774,132 775,132 777,132 778,132 779,132 783,72 788,72 794,72 799,72 805,54 811,54 816,54 816,54 822,54 827,51 833,51 838,51 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="50,319 116,51 850,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P2_24Vdc.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P2_24Vdc</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 845,370 846,370 846,370 846,370 846,370 846,370 846,370 846,370 846,370 846,370 846,370 846,369 846,369 846,369 846,369 846,369 846,369 846,369 846,369 846,368 846,368 846,368 846,368 846,368 846,368 846,367 846,366 846,365 846,365 846,365 846,365 846,365 846,365 846,365 846,365 846,364 846,362 846,362 846,362 846,361 846,361 846,360 846,360 846,360 846,360 846,360 846,360 846,360 846,358 846,354 846,353 846,353 846,353 846,353 846,353 846,353 846,353 846,353 846,353 846,353 846,353 846,353 846,351 846,351 846,347 846,347 846,343 846,343 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,341 846,337 846,330 846,330 846,326 846,326 846,325 846,325 846,325 846,325 846,325 846,325 846,325 846,325 846,325 846,325 847,325 847,325 847,324 847,323 847,323 847,323 847,317 847,317 847,307 847,307 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,303 847,302 847,299 847,299 847,289 847,289 847,279 847,277 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,276 847,275 847,275 847,275 847,269 847,269 847,269 847,256 847,256 847,256 847,247 847,247 847,247 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,246 847,245 847,243 847,243 847,237 847,233 847,233 847,233 847,220 847,220 847,220 847,214 847,214 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,213 847,208 847,208 847,200 847,196 847,196 847,196 847,184 847,184 847,184 847,181 847,181 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,180 847,179 847,179 847,172 847,172 847,159 847,159 847,155 847,151 847,151 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,150 847,147 847,147 847,147 847,139 847,139 847,139 847,128 847,128 847,125 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,123 847,122 847,122 847,119 847,119 847,118 847,110 847,110 847,103 847,103 847,103 847,101 847,101 847,101 847,101 847,101 847,101 847,101 847,101 847,101 847,101 847,101 848,101 848,101 848,101 848,100 848,97 848,96 848,96 848,88 848,88 848,88 848,84 848,83 848,83 848,83 848,83 848,83 848,83 848,83 848,83 848,83 848,83 848,83 848,82 848,82 848,78 848,78 848,76 848,73 848,73 848,71 848,71 848,71 848,71 848,71 848,71 848,71 848,71 848,70 848,70 848,70 848,66 848,63 848,63 848,63 848,63 848,63 848,63 848,63 848,63 848,63 848,62 848,61 848,61 848,58 848,58 848,57 848,57 848,57 848,57 848,57 848,57 848,57 848,57 848,56 848,56 848,55 848,54 848,54 848,54 848,54 848,54 848,54 848,54 848,54 848,54 848,53 848,52 848,52 848,52 848,52 848,52 848,52 848,52 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 848,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 849,51 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="50,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="845" y1="50" x2="845" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P2_CO_rpm.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P2_CO_rpm</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="50,370 76,370 84,370 88,370 95,370 99,370 107,370 110,370 114,370 118,370 122,370 126,370 130,370 133,370 137,370 141,370 145,370 149,370 152,370 156,370 160,370 164,370 168,370 171,370 175,370 179,370 183,370 187,370 190,370 194,370 198,370 202,370 206,370 210,370 213,370 217,370 221,370 225,370 229,370 232,370 236,370 240,370 244,370 248,370 251,370 255,370 259,370 263,369 267,369 270,369 274,369 278,369 282,369 286,369 290,368 293,368 297,368 301,367 305,367 309,367 310,367 312,367 316,366 320,366 322,366 324,365 328,365 331,364 335,364 339,363 343,362 347,362 350,361 352,361 354,360 356,360 358,359 362,358 364,358 366,357 368,357 370,356 373,355 375,355 377,354 380,354 381,353 383,353 385,352 389,351 390,351 390,351 392,349 394,349 396,348 398,348 400,346 402,346 404,345 406,345 408,343 410,343 411,341 415,340 419,338 421,338 423,336 425,336 427,334 429,334 430,331 432,331 434,329 436,329 438,327 440,327 441,327 442,324 443,324 444,324 446,322 449,322 450,319 451,319 453,317 455,317 457,314 459,314 461,310 462,310 463,310 465,307 467,307 469,303 470,303 472,299 474,299 475,299 476,295 478,295 480,292 482,292 484,287 486,287 488,283 490,283 491,278 493,278 494,278 495,273 496,273 497,273 498,273 499,267 501,267 503,262 505,262 507,256 508,256 509,256 510,251 512,251 513,251 514,246 516,246 517,246 518,241 520,241 521,241 521,241 522,235 524,235 525,235 526,230 527,230 528,230 530,223 530,223 531,223 533,217 534,217 535,217 537,210 538,210 539,210 541,204 542,204 543,204 545,198 547,198 549,193 550,193 552,187 554,187 555,187 556,181 558,181 560,174 562,174 563,174 564,168 565,168 566,168 568,161 569,161 570,161 571,155 572,155 573,155 575,149 577,149 579,144 580,144 581,144 583,139 584,139 585,139 587,134 589,134 590,134 590,129 591,129 592,129 594,125 595,125 596,125 598,120 600,120 602,114 604,114 606,110 608,110 609,110 610,105 611,105 612,105 613,101 615,101 617,98 619,98 621,94 623,94 625,91 627,91 629,87 630,87 632,84 634,84 636,81 638,81 640,78 642,78 644,75 646,75 648,73 650,73 651,71 653,71 655,69 657,69 659,68 661,68 663,66 664,66 667,64 669,64 670,63 674,61 676,61 678,60 680,60 682,59 684,59 686,58 688,58 690,58 693,57 695,57 697,56 701,55 705,55 707,55 709,54 710,54 712,54 716,53 720,53 724,53 728,52 731,52 735,52 739,52 743,51 747,51 750,51 754,51 756,51 758,51 762,51 766,51 770,51 773,51 777,51 781,51 785,51 789,51 792,51 796,51 800,51 804,51 808,51 811,51 815,51 819,51 823,51 830,51 834,51 838,51 842,51 846,51 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="808,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P2_MSD.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P2_MSD</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="50,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="50,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P2_SIT01.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P2_SIT01</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="50,370 61,370 73,370 84,370 96,370 107,370 119,370 131,370 142,370 154,370 165,370 177,369 189,368 200,366 212,364 218,364 223,360 235,356 247,351 252,351 258,343 270,332 276,332 281,319 287,319 293,304 299,304 305,289 310,289 316,273 322,273 328,256 339,236 345,236 351,212 357,212 363,184 365,184 368,184 374,156 380,156 386,129 392,129 394,129 397,107 403,107 409,90 415,90 418,90 421,77 426,77 432,68 438,68 444,61 450,61 455,56 461,56 467,54 478,52 490,51 502,51 513,51 525,51 536,51 548,51 560,51 571,51 583,51 594,51 606,51 618,51 629,51 641,51 652,51 664,51 676,51 687,51 699,51 710,51 722,51 734,51 745,51 757,51 768,51 780,51 792,51 803,51 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="111,364 117,358 119,352 122,346 122,340 123,327 124,321 124,315 126,309 126,297 127,290 132,284 134,278 135,272 135,266 136,260 137,254 138,247 141,241 142,235 143,229 143,223 143,217 149,210 159,204 166,198 184,192 184,186 186,180 190,174 192,167 200,161 202,155 211,149 218,143 222,137 230,130 233,124 242,118 243,112 244,106 246,100 250,94 250,87 251,81 254,75 268,69 270,63 279,57 311,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P4_ST_PT01.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P4_ST_PT01</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="53,370 55,370 61,370 82,370 86,370 98,370 100,370 103,370 105,370 107,370 111,370 113,370 115,370 117,370 121,370 123,370 125,370 128,370 130,370 132,370 136,370 138,370 140,370 142,370 146,370 148,370 150,370 153,370 155,370 157,370 161,370 163,370 165,369 167,369 171,369 173,369 175,369 178,369 180,369 182,369 186,369 188,369 190,369 192,369 196,369 198,369 200,369 203,369 205,369 207,369 211,369 212,369 213,365 214,365 215,364 217,364 221,364 223,363 225,363 228,363 230,363 232,363 236,363 238,363 240,362 242,362 245,362 246,362 248,362 250,362 251,362 253,362 255,361 257,361 261,360 262,360 263,359 264,359 265,329 266,329 266,329 267,325 268,325 269,325 270,325 271,322 272,322 273,319 274,319 275,318 275,318 276,318 276,318 278,316 279,316 280,316 280,314 281,314 282,313 283,313 283,313 284,313 285,313 285,313 286,311 287,311 288,309 289,309 290,308 292,306 293,306 294,306 295,306 296,304 297,304 298,302 299,302 300,300 300,300 301,300 302,300 302,300 303,298 304,298 305,298 305,296 306,296 306,296 307,292 308,292 309,292 310,292 311,287 312,287 312,287 313,277 314,277 314,277 315,227 315,227 316,227 316,227 317,93 318,93 319,93 320,93 321,89 322,89 323,88 325,87 326,87 326,87 327,87 328,86 330,86 331,86 332,86 334,86 335,86 336,85 338,85 339,85 340,84 341,84 342,84 346,84 348,83 349,83 350,83 350,83 352,83 353,83 354,83 355,82 357,82 358,82 359,82 361,81 362,81 363,80 365,80 367,79 369,79 370,79 371,78 372,78 373,75 374,75 375,59 376,59 377,59 378,58 380,58 382,57 385,57 386,57 387,57 388,57 390,57 392,57 396,57 398,56 400,56 400,56 403,56 405,56 407,56 410,56 411,56 413,56 415,55 417,55 421,55 423,55 424,55 425,54 426,54 428,51 429,51 430,51 432,51 436,51 438,51 440,51 442,51 446,51 448,51 450,51 453,51 455,51 457,51 461,51 463,51 465,51 467,51 471,51 473,51 475,51 478,51 480,51 482,51 486,51 488,51 490,51 492,51 496,51 498,51 500,51 503,51 505,51 507,51 511,51 515,51 521,51 523,51 525,51 528,51 530,51 532,51 536,51 538,51 542,51 548,51 553,51 561,51 563,51 567,51 571,51 573,51 575,51 578,51 580,51 582,51 588,51 590,51 592,51 603,51 605,51 607,51 615,51 621,51 628,51 630,51 640,51 642,51 646,51 648,51 650,51 653,51 655,51 657,51 661,51 663,51 665,51 678,51 690,51 692,51 696,51 700,51 703,51 736,51 740,51 742,51 746,51 755,51 763,51 767,51 786,51 796,51 798,51 800,51 803,51 805,51 807,51 811,51 813,51 815,51 823,51 825,51 828,51 832,51 836,51 850,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="50,370 163,369 212,369 213,365 215,365 217,364 237,364 248,363 256,362 262,362 263,361 265,334 267,289 313,280 315,228 317,74 373,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="53" y1="50" x2="53" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="850" y1="50" x2="850" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/cdf_P4_ST_TT01.svg

@@ -1,12 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="900" height="420">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="50" y="30">CDF 비교: P4_ST_TT01</text>
-<line x1="50" y1="50" x2="50" y2="370" stroke="#333"/>
-<line x1="50" y1="370" x2="850" y2="370" stroke="#333"/>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="835,370 835,370 836,370 836,370 836,370 837,370 837,370 837,370 837,370 837,370 837,370 838,369 838,369 838,368 838,368 838,368 838,368 838,368 838,366 838,366 838,366 838,364 838,364 838,362 839,362 839,362 839,360 839,360 839,360 839,360 839,360 839,360 839,360 839,358 839,358 839,356 839,356 839,353 839,353 839,353 840,351 840,351 840,349 840,349 840,346 840,346 840,346 840,344 840,344 840,342 840,342 840,339 840,339 840,339 841,337 841,337 841,337 841,336 841,334 841,334 841,331 841,331 841,329 841,329 841,329 841,329 841,326 841,326 841,326 842,324 842,324 842,321 842,321 842,321 842,321 842,321 842,318 842,318 842,316 842,316 842,316 842,313 842,313 842,311 843,311 843,311 843,308 843,308 843,306 843,306 843,304 843,304 843,304 843,304 843,304 843,301 843,301 843,299 844,297 844,297 844,297 844,297 844,295 844,295 844,295 844,292 844,292 844,290 844,290 844,288 844,288 844,288 844,288 845,288 845,286 845,284 845,284 845,281 845,281 845,281 845,279 845,279 845,276 845,276 845,276 845,274 846,274 846,274 846,274 846,274 846,274 846,271 846,271 846,271 846,268 846,268 846,265 846,265 846,265 846,262 846,262 846,262 846,262 846,262 846,260 847,260 847,257 847,257 847,254 847,254 847,254 847,254 847,251 847,251 847,248 847,248 847,248 847,244 847,244 847,244 848,244 848,240 848,240 848,240 848,236 848,236 848,232 848,232 848,228 848,228 848,228 848,227 848,227 848,223 848,223 848,217 849,217 849,211 849,211 849,211 849,211 849,211 849,200 849,200 849,200 849,182 849,182 849,182 849,52 849,52 849,51 849,50"/>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="50,50"/>
-<text x="730" y="65" fill="#1f77b4">real</text>
-<text x="730" y="80" fill="#d62728">generated</text>
-<line x1="835" y1="50" x2="835" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-<line x1="849" y1="50" x2="849" y2="370" stroke="#999" stroke-dasharray="4 3"/>
-</svg>

example/results/config_used.json

@@ -1,14 +1,14 @@
 {
-  "data_path": "/root/autodl-tmp/mask-ddpm/dataset/hai/hai-21.03/train1.csv.gz",
-  "data_glob": "/root/autodl-tmp/mask-ddpm/mask-ddpm/example/../../dataset/hai/hai-21.03/train*.csv.gz",
-  "split_path": "/root/autodl-tmp/mask-ddpm/mask-ddpm/example/feature_split.json",
-  "stats_path": "/root/autodl-tmp/mask-ddpm/mask-ddpm/example/results/cont_stats.json",
-  "vocab_path": "/root/autodl-tmp/mask-ddpm/mask-ddpm/example/results/disc_vocab.json",
-  "out_dir": "/root/autodl-tmp/mask-ddpm/mask-ddpm/example/results",
+  "data_path": "F:\\Development\\modbus_diffusion\\mask-ddpm\\dataset\\hai\\hai-21.03\\train1.csv.gz",
+  "data_glob": "F:\\Development\\modbus_diffusion\\mask-ddpm\\mask-ddpm\\example\\..\\..\\dataset\\hai\\hai-21.03\\train*.csv.gz",
+  "split_path": "F:\\Development\\modbus_diffusion\\mask-ddpm\\mask-ddpm\\example\\feature_split.json",
+  "stats_path": "F:\\Development\\modbus_diffusion\\mask-ddpm\\mask-ddpm\\example\\results\\cont_stats.json",
+  "vocab_path": "F:\\Development\\modbus_diffusion\\mask-ddpm\\mask-ddpm\\example\\results\\disc_vocab.json",
+  "out_dir": "F:\\Development\\modbus_diffusion\\mask-ddpm\\mask-ddpm\\example\\results",
   "device": "cuda",
   "timesteps": 600,
-  "batch_size": 16,
-  "seq_len": 96,
+  "batch_size": 128,
+  "seq_len": 128,
   "epochs": 10,
   "max_batches": 4000,
   "lambda": 0.7,
@@ -32,19 +32,16 @@
   "model_ff_mult": 2,
   "model_pos_dim": 64,
   "model_use_pos_embed": true,
+  "model_use_feature_graph": true,
+  "feature_graph_scale": 0.1,
+  "feature_graph_dropout": 0.0,
   "disc_mask_scale": 0.9,
   "shuffle_buffer": 256,
   "cont_loss_weighting": "inv_std",
   "cont_loss_eps": 1e-06,
-  "cont_target": "x0",
+  "cont_target": "v",
   "cont_clamp_x0": 5.0,
-  "use_temporal_stage1": true,
-  "temporal_hidden_dim": 256,
-  "temporal_num_layers": 1,
-  "temporal_dropout": 0.0,
-  "temporal_epochs": 2,
-  "temporal_lr": 0.001,
-  "quantile_loss_weight": 0.2,
+  "quantile_loss_weight": 0.1,
   "quantile_points": [
     0.05,
     0.25,
@@ -52,52 +49,9 @@
     0.75,
     0.95
   ],
-  "snr_weighted_loss": true,
-  "snr_gamma": 1.0,
-  "residual_stat_weight": 0.05,
-  "backbone_type": "transformer",
-  "transformer_num_layers": 2,
-  "transformer_nhead": 4,
-  "transformer_ff_dim": 512,
-  "transformer_dropout": 0.1,
-  "use_quantile_transform": true,
-  "quantile_bins": 1001,
-  "cont_bound_mode": "none",
-  "cont_bound_strength": 2.0,
-  "cont_post_calibrate": true,
-  "cont_post_scale": {},
-  "full_stats": true,
-  "type1_features": [
-    "P1_B4002",
-    "P2_MSD",
-    "P4_HT_LD",
-    "P1_B2004",
-    "P1_B3004",
-    "P1_B4022",
-    "P1_B3005"
-  ],
-  "type2_features": [
-    "P1_B4005"
-  ],
-  "type3_features": [
-    "P1_PCV02Z",
-    "P1_PCV01Z",
-    "P1_PCV01D",
-    "P1_FCV02Z"
-  ],
-  "type4_features": [
-    "P1_PIT02",
-    "P2_SIT02",
-    "P1_FT03"
-  ],
-  "type5_features": [
-    "P1_FT03Z"
-  ],
-  "type6_features": [
-    "P4_HT_PO",
-    "P2_24Vdc",
-    "P2_HILout"
-  ],
-  "sample_batch_size": 4,
+  "quantile_loss_warmup_steps": 200,
+  "quantile_loss_clip": 6.0,
+  "quantile_loss_huber_delta": 1.0,
+  "sample_batch_size": 8,
   "sample_seq_len": 128
 }

example/results/controller_stats.json

@@ -1,19 +0,0 @@
-{
-  "features": [
-    "P1_B4005"
-  ],
-  "generated": {
-    "P1_B4005": {
-      "saturation_ratio": 1.0,
-      "change_rate": 0.025440313111545987,
-      "step_median": 100.0
-    }
-  },
-  "reference": {
-    "P1_B4005": {
-      "saturation_ratio": 0.65026,
-      "change_rate": 0.4180606967678279,
-      "step_median": 0.030469999999999997
-    }
-  }
-}

example/results/data_shift_plot.svg

@@ -1,43 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="700">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="60" y="40">Per-file mean (sampled every 50 rows)</text>
-<text x="60" y="360">Per-file std (sampled every 50 rows)</text>
-<line x1="60" y1="60" x2="60" y2="320" stroke="#333"/>
-<line x1="60" y1="320" x2="1140" y2="320" stroke="#333"/>
-<text x="50" y="70" text-anchor="end">54106.136</text>
-<text x="50" y="320" text-anchor="end">1.370</text>
-<text x="60" y="335" text-anchor="middle" transform="rotate(45 60 335)">train1.csv.gz</text>
-<text x="600" y="335" text-anchor="middle" transform="rotate(45 600 335)">train2.csv.gz</text>
-<text x="1140" y="335" text-anchor="middle" transform="rotate(45 1140 335)">train3.csv.gz</text>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="60,320 600,320 1140,320"/>
-<text x="1150" y="75" fill="#1f77b4">P1_FT01</text>
-<polyline fill="none" stroke="#ff7f0e" stroke-width="2" points="60,319 600,319 1140,319"/>
-<text x="1150" y="90" fill="#ff7f0e">P1_LIT01</text>
-<polyline fill="none" stroke="#2ca02c" stroke-width="2" points="60,320 600,320 1140,320"/>
-<text x="1150" y="105" fill="#2ca02c">P1_PIT01</text>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="60,60 600,61 1140,61"/>
-<text x="1150" y="120" fill="#d62728">P2_CO_rpm</text>
-<polyline fill="none" stroke="#9467bd" stroke-width="2" points="60,255 600,256 1140,257"/>
-<text x="1150" y="135" fill="#9467bd">P3_LIT01</text>
-<polyline fill="none" stroke="#8c564b" stroke-width="2" points="60,272 600,272 1140,272"/>
-<text x="1150" y="150" fill="#8c564b">P4_ST_PT01</text>
-<line x1="60" y1="380" x2="60" y2="640" stroke="#333"/>
-<line x1="60" y1="640" x2="1140" y2="640" stroke="#333"/>
-<text x="50" y="390" text-anchor="end">4403.032</text>
-<text x="50" y="640" text-anchor="end">0.053</text>
-<text x="60" y="655" text-anchor="middle" transform="rotate(45 60 655)">train1.csv.gz</text>
-<text x="600" y="655" text-anchor="middle" transform="rotate(45 600 655)">train2.csv.gz</text>
-<text x="1140" y="655" text-anchor="middle" transform="rotate(45 1140 655)">train3.csv.gz</text>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="60,639 600,639 1140,639"/>
-<text x="1150" y="395" fill="#1f77b4">P1_FT01</text>
-<polyline fill="none" stroke="#ff7f0e" stroke-width="2" points="60,640 600,640 1140,639"/>
-<text x="1150" y="410" fill="#ff7f0e">P1_LIT01</text>
-<polyline fill="none" stroke="#2ca02c" stroke-width="2" points="60,640 600,640 1140,640"/>
-<text x="1150" y="425" fill="#2ca02c">P1_PIT01</text>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="60,639 600,639 1140,639"/>
-<text x="1150" y="440" fill="#d62728">P2_CO_rpm</text>
-<polyline fill="none" stroke="#9467bd" stroke-width="2" points="60,389 600,386 1140,380"/>
-<text x="1150" y="455" fill="#9467bd">P3_LIT01</text>
-<polyline fill="none" stroke="#8c564b" stroke-width="2" points="60,640 600,639 1140,640"/>
-<text x="1150" y="470" fill="#8c564b">P4_ST_PT01</text>
-</svg>

example/results/data_shift_plot_full.svg

@@ -1,43 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="700">
-<style>text{font-family:Arial,sans-serif;font-size:12px}</style>
-<text x="60" y="40">Per-file mean (full data)</text>
-<text x="60" y="360">Per-file std (full data)</text>
-<line x1="60" y1="60" x2="60" y2="320" stroke="#333"/>
-<line x1="60" y1="320" x2="1140" y2="320" stroke="#333"/>
-<text x="50" y="70" text-anchor="end">54105.286</text>
-<text x="50" y="320" text-anchor="end">1.370</text>
-<text x="60" y="335" text-anchor="middle" transform="rotate(45 60 335)">train1.csv.gz</text>
-<text x="600" y="335" text-anchor="middle" transform="rotate(45 600 335)">train2.csv.gz</text>
-<text x="1140" y="335" text-anchor="middle" transform="rotate(45 1140 335)">train3.csv.gz</text>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="60,320 600,320 1140,320"/>
-<text x="1150" y="75" fill="#1f77b4">P1_FT01</text>
-<polyline fill="none" stroke="#ff7f0e" stroke-width="2" points="60,319 600,319 1140,319"/>
-<text x="1150" y="90" fill="#ff7f0e">P1_LIT01</text>
-<polyline fill="none" stroke="#2ca02c" stroke-width="2" points="60,320 600,320 1140,320"/>
-<text x="1150" y="105" fill="#2ca02c">P1_PIT01</text>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="60,60 600,61 1140,61"/>
-<text x="1150" y="120" fill="#d62728">P2_CO_rpm</text>
-<polyline fill="none" stroke="#9467bd" stroke-width="2" points="60,255 600,256 1140,257"/>
-<text x="1150" y="135" fill="#9467bd">P3_LIT01</text>
-<polyline fill="none" stroke="#8c564b" stroke-width="2" points="60,272 600,272 1140,272"/>
-<text x="1150" y="150" fill="#8c564b">P4_ST_PT01</text>
-<line x1="60" y1="380" x2="60" y2="640" stroke="#333"/>
-<line x1="60" y1="640" x2="1140" y2="640" stroke="#333"/>
-<text x="50" y="390" text-anchor="end">4409.026</text>
-<text x="50" y="640" text-anchor="end">0.056</text>
-<text x="60" y="655" text-anchor="middle" transform="rotate(45 60 655)">train1.csv.gz</text>
-<text x="600" y="655" text-anchor="middle" transform="rotate(45 600 655)">train2.csv.gz</text>
-<text x="1140" y="655" text-anchor="middle" transform="rotate(45 1140 655)">train3.csv.gz</text>
-<polyline fill="none" stroke="#1f77b4" stroke-width="2" points="60,639 600,639 1140,639"/>
-<text x="1150" y="395" fill="#1f77b4">P1_FT01</text>
-<polyline fill="none" stroke="#ff7f0e" stroke-width="2" points="60,640 600,640 1140,639"/>
-<text x="1150" y="410" fill="#ff7f0e">P1_LIT01</text>
-<polyline fill="none" stroke="#2ca02c" stroke-width="2" points="60,640 600,640 1140,640"/>
-<text x="1150" y="425" fill="#2ca02c">P1_PIT01</text>
-<polyline fill="none" stroke="#d62728" stroke-width="2" points="60,639 600,639 1140,639"/>
-<text x="1150" y="440" fill="#d62728">P2_CO_rpm</text>
-<polyline fill="none" stroke="#9467bd" stroke-width="2" points="60,389 600,386 1140,380"/>
-<text x="1150" y="455" fill="#9467bd">P3_LIT01</text>
-<polyline fill="none" stroke="#8c564b" stroke-width="2" points="60,640 600,639 1140,640"/>
-<text x="1150" y="470" fill="#8c564b">P4_ST_PT01</text>
-</svg>

example/results/data_shift_stats.csv

@@ -1,4 +0,0 @@
-file,sample_rows,mean_P1_FT01,mean_P1_LIT01,mean_P1_PIT01,mean_P2_CO_rpm,mean_P3_LIT01,mean_P4_ST_PT01,std_P1_FT01,std_P1_LIT01,std_P1_PIT01,std_P2_CO_rpm,std_P3_LIT01,std_P4_ST_PT01
-train1.csv.gz,4321,197.3625650034721,402.4983721615365,1.3701480791483485,54106.13631103911,13582.384170330943,10048.28187919463,25.78211851952459,15.226246029512001,0.05818374391855817,20.603665756241284,4258.450859219057,16.684991885589945
-train2.csv.gz,4537,180.380231487768,404.9985957328643,1.3885507626184759,54097.111968260964,13492.448038351333,10052.902358386598,26.01082617737414,11.712980419233306,0.07154540840596779,21.507712300569843,4301.554272480435,20.81453649334688
-train3.csv.gz,9577,200.5677786457133,404.42271995927814,1.3747714273780822,54105.243552260625,13194.925368069333,10050.422313876998,25.685144220465013,17.301905753283886,0.05304501736117375,21.759589175104754,4403.031534167203,15.627077960123735

example/results/data_shift_stats_full.csv

@@ -1,4 +0,0 @@
-file,rows,mean_P1_FT01,mean_P1_LIT01,mean_P1_PIT01,mean_P2_CO_rpm,mean_P3_LIT01,mean_P4_ST_PT01,std_P1_FT01,std_P1_LIT01,std_P1_PIT01,std_P2_CO_rpm,std_P3_LIT01,std_P4_ST_PT01
-train1.csv.gz,216001,197.4039421067864,402.499530273871,1.3699407928204004,54105.28641186847,13576.493878500563,10048.201686566266,25.725535038417004,15.22218627802303,0.05860248629393732,21.16202209482823,4264.6609588197925,16.8563584796801
-train2.csv.gz,226801,180.30764089694264,404.99552063838513,1.3890573547293745,54095.33532480016,13482.01015758308,10052.992377679111,26.231835534624313,11.708752202389721,0.07297888433587706,22.315550737159924,4308.3181358982065,21.239090989129597
-train3.csv.gz,478801,200.34315271607556,404.42644943316503,1.3753994816009067,54105.041362173426,13194.615527118782,10050.500895988103,26.111739592931507,17.298124670143782,0.05566509425248764,22.327041460872234,4409.0260830855495,16.17524060043852

example/results/eval_post.json

@@ -1,970 +0,0 @@
-{
-  "rows": 512,
-  "continuous_summary": {
-    "P1_B2004": {
-      "mean": 0.09468738281250011,
-      "std": 0.0204249458817387
-    },
-    "P1_B2016": {
-      "mean": 1.3914786914062507,
-      "std": 0.13852375259047817
-    },
-    "P1_B3004": {
-      "mean": 404.12801882812516,
-      "std": 8.700081944637194
-    },
-    "P1_B3005": {
-      "mean": 1039.104946347656,
-      "std": 53.82303954946287
-    },
-    "P1_B4002": {
-      "mean": 32.9106513085937,
-      "std": 0.7911878162512286
-    },
-    "P1_B4005": {
-      "mean": 77.0106558984374,
-      "std": 39.57793825805918
-    },
-    "P1_B400B": {
-      "mean": 1777.8262677929695,
-      "std": 1195.099960364846
-    },
-    "P1_B4022": {
-      "mean": 36.6352178125,
-      "std": 0.8365485376503342
-    },
-    "P1_FCV02Z": {
-      "mean": 18.41588484375,
-      "std": 38.19093414904595
-    },
-    "P1_FCV03D": {
-      "mean": 58.57026304687501,
-      "std": 6.631278294197735
-    },
-    "P1_FCV03Z": {
-      "mean": 59.1759176171875,
-      "std": 6.788219451354921
-    },
-    "P1_FT01": {
-      "mean": 194.88186419921877,
-      "std": 30.768847231450835
-    },
-    "P1_FT01Z": {
-      "mean": 878.7246611914071,
-      "std": 84.99320817657322
-    },
-    "P1_FT02": {
-      "mean": 1132.5440195312497,
-      "std": 890.295989210415
-    },
-    "P1_FT02Z": {
-      "mean": 1777.8432922460931,
-      "std": 1195.0744214040478
-    },
-    "P1_FT03": {
-      "mean": 282.588265,
-      "std": 33.64678614833339
-    },
-    "P1_FT03Z": {
-      "mean": 1038.1921977148438,
-      "std": 53.68912074389504
-    },
-    "P1_LCV01D": {
-      "mean": 12.164747207031253,
-      "std": 3.013903117337403
-    },
-    "P1_LCV01Z": {
-      "mean": 11.263465292968757,
-      "std": 4.299717751614109
-    },
-    "P1_LIT01": {
-      "mean": 404.0787613476563,
-      "std": 15.786788030436574
-    },
-    "P1_PCV01D": {
-      "mean": 58.679592343749995,
-      "std": 24.6498417837609
-    },
-    "P1_PCV01Z": {
-      "mean": 62.01106343749999,
-      "std": 25.215198018219656
-    },
-    "P1_PCV02Z": {
-      "mean": 11.861201152343758,
-      "std": 0.10754023428948589
-    },
-    "P1_PIT01": {
-      "mean": 1.3778806249999993,
-      "std": 0.0759028666491439
-    },
-    "P1_PIT02": {
-      "mean": 0.3816304882812499,
-      "std": 0.4215135219095571
-    },
-    "P1_TIT01": {
-      "mean": 35.66455349609374,
-      "std": 0.5851575869166451
-    },
-    "P1_TIT02": {
-      "mean": 36.50365279296878,
-      "std": 1.2226248335802352
-    },
-    "P2_24Vdc": {
-      "mean": 28.028364785156242,
-      "std": 0.0031477404614200046
-    },
-    "P2_CO_rpm": {
-      "mean": 54102.350379902346,
-      "std": 23.739412855093885
-    },
-    "P2_HILout": {
-      "mean": 711.4631772070315,
-      "std": 8.311656115200154
-    },
-    "P2_MSD": {
-      "mean": 763.19324,
-      "std": 0.0
-    },
-    "P2_SIT01": {
-      "mean": 783.3295312499995,
-      "std": 6.1992756485364255
-    },
-    "P2_SIT02": {
-      "mean": 783.9164093554691,
-      "std": 5.679889630055085
-    },
-    "P2_VT01": {
-      "mean": 11.923788867187504,
-      "std": 0.06887396584571669
-    },
-    "P2_VXT02": {
-      "mean": -3.2995492382812492,
-      "std": 0.47574439603151125
-    },
-    "P2_VXT03": {
-      "mean": -1.3059827929687502,
-      "std": 0.3554955367983872
-    },
-    "P2_VYT02": {
-      "mean": 3.9809895117187497,
-      "std": 0.5043184139711802
-    },
-    "P2_VYT03": {
-      "mean": 6.233644902343752,
-      "std": 0.3868162486782033
-    },
-    "P3_FIT01": {
-      "mean": 1150.9959331445307,
-      "std": 1787.2881930304632
-    },
-    "P3_LCP01D": {
-      "mean": 4560.334570449221,
-      "std": 5097.850435335926
-    },
-    "P3_LCV01D": {
-      "mean": 6685.264751816405,
-      "std": 7126.726522000548
-    },
-    "P3_LIT01": {
-      "mean": 13353.148420312498,
-      "std": 4366.989969548411
-    },
-    "P3_PIT01": {
-      "mean": 650.8284901171874,
-      "std": 1156.2873061190392
-    },
-    "P4_HT_FD": {
-      "mean": -0.0008932031250000001,
-      "std": 0.003779596098404481
-    },
-    "P4_HT_LD": {
-      "mean": 38.85650802734374,
-      "std": 33.2128961160467
-    },
-    "P4_HT_PO": {
-      "mean": 34.60460193359368,
-      "std": 31.183275999635047
-    },
-    "P4_LD": {
-      "mean": 366.1239422265629,
-      "std": 60.927584939594155
-    },
-    "P4_ST_FD": {
-      "mean": -5.328125000000001e-05,
-      "std": 0.0035943393981917385
-    },
-    "P4_ST_GOV": {
-      "mean": 17917.172519687505,
-      "std": 1885.9526969616045
-    },
-    "P4_ST_LD": {
-      "mean": 332.0750421875001,
-      "std": 38.42368852019025
-    },
-    "P4_ST_PO": {
-      "mean": 332.3426824609374,
-      "std": 35.0605241189417
-    },
-    "P4_ST_PT01": {
-      "mean": 10047.363565429685,
-      "std": 17.097579944433836
-    },
-    "P4_ST_TT01": {
-      "mean": 27601.78038406252,
-      "std": 22.705632518191543
-    }
-  },
-  "continuous_error": {
-    "P1_B2004": {
-      "mean_abs_err": 0.0011197307215244368,
-      "std_abs_err": 0.0024265087996462945
-    },
-    "P1_B2016": {
-      "mean_abs_err": 0.00021236674148372714,
-      "std_abs_err": 0.0027501901139150853
-    },
-    "P1_B3004": {
-      "mean_abs_err": 0.7419550035990028,
-      "std_abs_err": 6.718067643404616
-    },
-    "P1_B3005": {
-      "mean_abs_err": 21.943840180973666,
-      "std_abs_err": 7.360276961537409
-    },
-    "P1_B4002": {
-      "mean_abs_err": 0.5937249887138165,
-      "std_abs_err": 0.21251431705215074
-    },
-    "P1_B4005": {
-      "mean_abs_err": 16.485548882239485,
-      "std_abs_err": 2.6033591896505115
-    },
-    "P1_B400B": {
-      "mean_abs_err": 0.6496023849986159,
-      "std_abs_err": 1.7476874457734084
-    },
-    "P1_B4022": {
-      "mean_abs_err": 0.5740431650974784,
-      "std_abs_err": 0.16509768281551584
-    },
-    "P1_FCV02Z": {
-      "mean_abs_err": 6.535050056722277,
-      "std_abs_err": 2.247551290212229
-    },
-    "P1_FCV03D": {
-      "mean_abs_err": 0.002399596028183737,
-      "std_abs_err": 0.03178257548897978
-    },
-    "P1_FCV03Z": {
-      "mean_abs_err": 0.12312156300233568,
-      "std_abs_err": 0.07341548702331924
-    },
-    "P1_FT01": {
-      "mean_abs_err": 0.15820984293850415,
-      "std_abs_err": 3.4208653928065083
-    },
-    "P1_FT01Z": {
-      "mean_abs_err": 0.32502031274543697,
-      "std_abs_err": 9.227505213254972
-    },
-    "P1_FT02": {
-      "mean_abs_err": 0.2741337033764921,
-      "std_abs_err": 1.0998253590023523
-    },
-    "P1_FT02Z": {
-      "mean_abs_err": 0.6351543625555678,
-      "std_abs_err": 1.729065632898255
-    },
-    "P1_FT03": {
-      "mean_abs_err": 0.050705276228939056,
-      "std_abs_err": 0.1725730370378855
-    },
-    "P1_FT03Z": {
-      "mean_abs_err": 22.849840633677786,
-      "std_abs_err": 7.436368119722289
-    },
-    "P1_LCV01D": {
-      "mean_abs_err": 0.010414545256116625,
-      "std_abs_err": 0.0992881643072816
-    },
-    "P1_LCV01Z": {
-      "mean_abs_err": 0.7026087363691609,
-      "std_abs_err": 1.3362482542687975
-    },
-    "P1_LIT01": {
-      "mean_abs_err": 0.03611081534995719,
-      "std_abs_err": 0.15488998206260263
-    },
-    "P1_PCV01D": {
-      "mean_abs_err": 8.785981391941384,
-      "std_abs_err": 0.8800750828553241
-    },
-    "P1_PCV01Z": {
-      "mean_abs_err": 6.397088359402595,
-      "std_abs_err": 1.3505982075560112
-    },
-    "P1_PCV02Z": {
-      "mean_abs_err": 0.018448205738831547,
-      "std_abs_err": 0.010695768824838525
-    },
-    "P1_PIT01": {
-      "mean_abs_err": 0.00039940424660733775,
-      "std_abs_err": 0.014470307279261803
-    },
-    "P1_PIT02": {
-      "mean_abs_err": 0.10552660206026682,
-      "std_abs_err": 0.07719811614532274
-    },
-    "P1_TIT01": {
-      "mean_abs_err": 0.01665474633947639,
-      "std_abs_err": 0.001876959730696126
-    },
-    "P1_TIT02": {
-      "mean_abs_err": 0.021325885367751596,
-      "std_abs_err": 0.000866107555972162
-    },
-    "P2_24Vdc": {
-      "mean_abs_err": 0.00034491747142695317,
-      "std_abs_err": 0.0001947256529869104
-    },
-    "P2_CO_rpm": {
-      "mean_abs_err": 0.3598179803302628,
-      "std_abs_err": 1.28368108030552
-    },
-    "P2_HILout": {
-      "mean_abs_err": 0.0003679369353903894,
-      "std_abs_err": 0.1430697620560082
-    },
-    "P2_MSD": {
-      "mean_abs_err": 0.0,
-      "std_abs_err": 1.0
-    },
-    "P2_SIT01": {
-      "mean_abs_err": 0.5743861634434779,
-      "std_abs_err": 1.0003602880922005
-    },
-    "P2_SIT02": {
-      "mean_abs_err": 0.012671472922875182,
-      "std_abs_err": 0.48930987324211817
-    },
-    "P2_VT01": {
-      "mean_abs_err": 2.6778822629580645e-05,
-      "std_abs_err": 0.00036028377371462306
-    },
-    "P2_VXT02": {
-      "mean_abs_err": 0.0006292341087470454,
-      "std_abs_err": 0.004711469760290965
-    },
-    "P2_VXT03": {
-      "mean_abs_err": 0.000910493695927661,
-      "std_abs_err": 0.0058681576347335285
-    },
-    "P2_VYT02": {
-      "mean_abs_err": 0.0004793382741872243,
-      "std_abs_err": 0.0044079609783923
-    },
-    "P2_VYT03": {
-      "mean_abs_err": 0.0007602104541328814,
-      "std_abs_err": 0.00701328670711171
-    },
-    "P3_FIT01": {
-      "mean_abs_err": 0.09575703834752858,
-      "std_abs_err": 7.563495240188331
-    },
-    "P3_LCP01D": {
-      "mean_abs_err": 24.392577791352778,
-      "std_abs_err": 32.14956237995284
-    },
-    "P3_LCV01D": {
-      "mean_abs_err": 448.6119651648369,
-      "std_abs_err": 286.79862618472725
-    },
-    "P3_LIT01": {
-      "mean_abs_err": 1.696072381488193,
-      "std_abs_err": 12.815332620474692
-    },
-    "P3_PIT01": {
-      "mean_abs_err": 1.470587093859649,
-      "std_abs_err": 5.365375411843843
-    },
-    "P4_HT_FD": {
-      "mean_abs_err": 0.0007900151796482603,
-      "std_abs_err": 0.0017475777840003804
-    },
-    "P4_HT_LD": {
-      "mean_abs_err": 4.861590947658129,
-      "std_abs_err": 0.21089739395160478
-    },
-    "P4_HT_PO": {
-      "mean_abs_err": 0.6207941388367715,
-      "std_abs_err": 0.2575952176864291
-    },
-    "P4_LD": {
-      "mean_abs_err": 0.004811567631406888,
-      "std_abs_err": 0.31177857015114796
-    },
-    "P4_ST_FD": {
-      "mean_abs_err": 2.416802011685119e-05,
-      "std_abs_err": 0.0019521631402017092
-    },
-    "P4_ST_GOV": {
-      "mean_abs_err": 4.211258439980156,
-      "std_abs_err": 33.809480973831114
-    },
-    "P4_ST_LD": {
-      "mean_abs_err": 0.07214501768243053,
-      "std_abs_err": 0.5705192285726994
-    },
-    "P4_ST_PO": {
-      "mean_abs_err": 0.07371113727862166,
-      "std_abs_err": 0.6095806165333997
-    },
-    "P4_ST_PT01": {
-      "mean_abs_err": 3.211591389397654,
-      "std_abs_err": 0.6871900808852942
-    },
-    "P4_ST_TT01": {
-      "mean_abs_err": 7.252307617010956,
-      "std_abs_err": 1.2116892863767852
-    }
-  },
-  "discrete_invalid_counts": {
-    "P1_FCV01D": 0,
-    "P1_FCV01Z": 0,
-    "P1_FCV02D": 0,
-    "P1_PCV02D": 0,
-    "P1_PP01AD": 0,
-    "P1_PP01AR": 0,
-    "P1_PP01BD": 0,
-    "P1_PP01BR": 0,
-    "P1_PP02D": 0,
-    "P1_PP02R": 0,
-    "P1_STSP": 0,
-    "P2_ASD": 0,
-    "P2_AutoGO": 0,
-    "P2_Emerg": 0,
-    "P2_ManualGO": 0,
-    "P2_OnOff": 0,
-    "P2_RTR": 0,
-    "P2_TripEx": 0,
-    "P2_VTR01": 0,
-    "P2_VTR02": 0,
-    "P2_VTR03": 0,
-    "P2_VTR04": 0,
-    "P3_LH": 0,
-    "P3_LL": 0,
-    "P4_HT_PS": 0,
-    "P4_ST_PS": 0
-  },
-  "continuous_ks": {
-    "P1_B2004": 0.294921875,
-    "P1_B2016": 0.04274062499999998,
-    "P1_B3004": 0.671875,
-    "P1_B3005": 0.341796875,
-    "P1_B4002": 0.56055,
-    "P1_B4005": 0.110540625,
-    "P1_B400B": 0.45414375,
-    "P1_B4022": 0.27634375,
-    "P1_FCV02Z": 0.506171875,
-    "P1_FCV03D": 0.48749062499999996,
-    "P1_FCV03Z": 0.49324375,
-    "P1_FT01": 0.475603125,
-    "P1_FT01Z": 0.475603125,
-    "P1_FT02": 0.45583125,
-    "P1_FT02Z": 0.45494375,
-    "P1_FT03": 0.52430625,
-    "P1_FT03Z": 0.28155,
-    "P1_LCV01D": 0.44753437500000004,
-    "P1_LCV01Z": 0.45401562500000003,
-    "P1_LIT01": 0.48995625,
-    "P1_PCV01D": 0.33133749999999995,
-    "P1_PCV01Z": 0.37425624999999996,
-    "P1_PCV02Z": 0.673828125,
-    "P1_PIT01": 0.14590312500000002,
-    "P1_PIT02": 0.434,
-    "P1_TIT01": 0.10231250000000003,
-    "P1_TIT02": 0.09849375000000005,
-    "P2_24Vdc": 0.076884375,
-    "P2_CO_rpm": 0.09880937499999998,
-    "P2_HILout": 0.06994999999999996,
-    "P2_MSD": 0.0,
-    "P2_SIT01": 0.496421875,
-    "P2_SIT02": 0.501165625,
-    "P2_VT01": 0.12240937500000004,
-    "P2_VXT02": 0.281528125,
-    "P2_VXT03": 0.43655937499999997,
-    "P2_VYT02": 0.24991562499999997,
-    "P2_VYT03": 0.26945624999999995,
-    "P3_FIT01": 0.22556874999999998,
-    "P3_LCP01D": 0.046790624999999975,
-    "P3_LCV01D": 0.286534375,
-    "P3_LIT01": 0.09374062500000002,
-    "P3_PIT01": 0.3046875,
-    "P4_HT_FD": 0.37768125,
-    "P4_HT_LD": 0.04162500000000002,
-    "P4_HT_PO": 0.0602125,
-    "P4_LD": 0.031062499999999993,
-    "P4_ST_FD": 0.024971874999999977,
-    "P4_ST_GOV": 0.034521875000000035,
-    "P4_ST_LD": 0.031850000000000045,
-    "P4_ST_PO": 0.03547187500000004,
-    "P4_ST_PT01": 0.126334375,
-    "P4_ST_TT01": 0.328053125
-  },
-  "continuous_quantile_diff": {
-    "P1_B2004": {
-      "q05_diff": 0.0,
-      "q25_diff": 0.0003399999999999931,
-      "q50_diff": 0.0,
-      "q75_diff": 0.0002400000000000041,
-      "q95_diff": 0.0002400000000000041
-    },
-    "P1_B2016": {
-      "q05_diff": 0.010599999999999943,
-      "q25_diff": 0.010299999999999976,
-      "q50_diff": 0.0053399999999999,
-      "q75_diff": 0.014270000000000005,
-      "q95_diff": 0.032179999999999875
-    },
-    "P1_B3004": {
-      "q05_diff": 4.475590000000011,
-      "q25_diff": 0.0,
-      "q50_diff": 7.429499999999962,
-      "q75_diff": 8.508819999999957,
-      "q95_diff": 8.508819999999957
-    },
-    "P1_B3005": {
-      "q05_diff": 8.045049999999947,
-      "q25_diff": 8.045049999999947,
-      "q50_diff": 0.0,
-      "q75_diff": 103.22381000000007,
-      "q95_diff": 0.0
-    },
-    "P1_B4002": {
-      "q05_diff": 0.08975999999999829,
-      "q25_diff": 1.7452600000000018,
-      "q50_diff": 0.19520000000000692,
-      "q75_diff": 0.19520000000000692,
-      "q95_diff": 0.0
-    },
-    "P1_B4005": {
-      "q05_diff": 0.0,
-      "q25_diff": 38.35669,
-      "q50_diff": 0.0,
-      "q75_diff": 0.0,
-      "q95_diff": 0.0
-    },
-    "P1_B400B": {
-      "q05_diff": 1.986220000000003,
-      "q25_diff": 2478.34451,
-      "q50_diff": 188.86254999999983,
-      "q75_diff": 9.545890000000327,
-      "q95_diff": 6.878660000000309
-    },
-    "P1_B4022": {
-      "q05_diff": 0.17978000000000094,
-      "q25_diff": 1.158059999999999,
-      "q50_diff": 0.339890000000004,
-      "q75_diff": 0.18730999999999653,
-      "q95_diff": 0.14457000000000164
-    },
-    "P1_FCV02Z": {
-      "q05_diff": 0.0,
-      "q25_diff": 0.0,
-      "q50_diff": 0.007630000000000026,
-      "q75_diff": 5.69916,
-      "q95_diff": 0.030520000000009873
-    },
-    "P1_FCV03D": {
-      "q05_diff": 2.9392700000000005,
-      "q25_diff": 0.10325000000000273,
-      "q50_diff": 8.550619999999995,
-      "q75_diff": 11.148229999999998,
-      "q95_diff": 1.0549999999999926
-    },
-    "P1_FCV03Z": {
-      "q05_diff": 3.282039999999995,
-      "q25_diff": 0.01525999999999783,
-      "q50_diff": 8.96454,
-      "q75_diff": 11.093139999999998,
-      "q95_diff": 0.1220700000000079
-    },
-    "P1_FT01": {
-      "q05_diff": 8.40730000000002,
-      "q25_diff": 8.74642,
-      "q50_diff": 32.806329999999974,
-      "q75_diff": 37.95618999999999,
-      "q95_diff": 3.2425400000000195
-    },
-    "P1_FT01Z": {
-      "q05_diff": 40.068970000000036,
-      "q25_diff": 19.627079999999978,
-      "q50_diff": 74.79840000000002,
-      "q75_diff": 86.54010000000005,
-      "q95_diff": 7.393000000000029
-    },
-    "P1_FT02": {
-      "q05_diff": 0.3814799999999998,
-      "q25_diff": 1898.1893,
-      "q50_diff": 254.5852,
-      "q75_diff": 12.970209999999952,
-      "q95_diff": 9.346070000000054
-    },
-    "P1_FT02Z": {
-      "q05_diff": 1.9862300000000026,
-      "q25_diff": 2479.80417,
-      "q50_diff": 189.13891999999987,
-      "q75_diff": 9.545890000000327,
-      "q95_diff": 6.878660000000309
-    },
-    "P1_FT03": {
-      "q05_diff": 36.42595,
-      "q25_diff": 1.5437300000000107,
-      "q50_diff": 51.52633000000003,
-      "q75_diff": 59.84343000000001,
-      "q95_diff": 2.0980200000000195
-    },
-    "P1_FT03Z": {
-      "q05_diff": 7.3292900000000145,
-      "q25_diff": 5.155089999999973,
-      "q50_diff": 0.43493999999998323,
-      "q75_diff": 99.04387999999994,
-      "q95_diff": 0.6378199999999197
-    },
-    "P1_LCV01D": {
-      "q05_diff": 0.1111999999999993,
-      "q25_diff": 1.2134900000000002,
-      "q50_diff": 4.635529999999999,
-      "q75_diff": 3.31274,
-      "q95_diff": 0.6044300000000007
-    },
-    "P1_LCV01Z": {
-      "q05_diff": 6.52313,
-      "q25_diff": 1.1901799999999998,
-      "q50_diff": 4.40216,
-      "q75_diff": 3.4561199999999985,
-      "q95_diff": 0.7171600000000016
-    },
-    "P1_LIT01": {
-      "q05_diff": 14.418029999999987,
-      "q25_diff": 1.053890000000024,
-      "q50_diff": 6.287360000000035,
-      "q75_diff": 8.229829999999993,
-      "q95_diff": 34.92102
-    },
-    "P1_PCV01D": {
-      "q05_diff": 1.1516400000000004,
-      "q25_diff": 0.06779000000000224,
-      "q50_diff": 1.1017599999999987,
-      "q75_diff": 41.266,
-      "q95_diff": 46.32521
-    },
-    "P1_PCV01Z": {
-      "q05_diff": 0.8239799999999988,
-      "q25_diff": 0.5950999999999951,
-      "q50_diff": 2.8533899999999974,
-      "q75_diff": 43.69353,
-      "q95_diff": 45.10077
-    },
-    "P1_PCV02Z": {
-      "q05_diff": 0.2288800000000002,
-      "q25_diff": 0.2212499999999995,
-      "q50_diff": 0.2288800000000002,
-      "q75_diff": 0.007630000000000692,
-      "q95_diff": 0.0
-    },
-    "P1_PIT01": {
-      "q05_diff": 0.03431000000000006,
-      "q25_diff": 0.017550000000000177,
-      "q50_diff": 0.005340000000000122,
-      "q75_diff": 0.022119999999999918,
-      "q95_diff": 0.008389999999999898
-    },
-    "P1_PIT02": {
-      "q05_diff": 0.03433,
-      "q25_diff": 0.07323999999999997,
-      "q50_diff": 0.0007699999999999929,
-      "q75_diff": 0.0015300000000000313,
-      "q95_diff": 1.52817
-    },
-    "P1_TIT01": {
-      "q05_diff": 0.061019999999999186,
-      "q25_diff": 0.06103999999999843,
-      "q50_diff": 0.10681000000000296,
-      "q75_diff": 0.24414999999999765,
-      "q95_diff": 0.0
-    },
-    "P1_TIT02": {
-      "q05_diff": 0.01525999999999783,
-      "q25_diff": 0.07629000000000019,
-      "q50_diff": 0.06103999999999843,
-      "q75_diff": 0.2899200000000022,
-      "q95_diff": 0.4272400000000047
-    },
-    "P2_24Vdc": {
-      "q05_diff": 3.999999999848569e-05,
-      "q25_diff": 0.0008400000000001739,
-      "q50_diff": 3.999999999848569e-05,
-      "q75_diff": 0.0008499999999997954,
-      "q95_diff": 7.000000000090267e-05
-    },
-    "P2_CO_rpm": {
-      "q05_diff": 10.03515999999945,
-      "q25_diff": 5.0,
-      "q50_diff": 3.0,
-      "q75_diff": 2.0,
-      "q95_diff": 0.0
-    },
-    "P2_HILout": {
-      "q05_diff": 0.06713999999999487,
-      "q25_diff": 2.038569999999936,
-      "q50_diff": 0.36620999999991,
-      "q75_diff": 2.221679999999992,
-      "q95_diff": 0.34789999999998145
-    },
-    "P2_MSD": {
-      "q05_diff": 0.0,
-      "q25_diff": 0.0,
-      "q50_diff": 0.0,
-      "q75_diff": 0.0,
-      "q95_diff": 0.0
-    },
-    "P2_SIT01": {
-      "q05_diff": 1.0,
-      "q25_diff": 3.0,
-      "q50_diff": 5.0,
-      "q75_diff": 6.0,
-      "q95_diff": 7.0
-    },
-    "P2_SIT02": {
-      "q05_diff": 2.5942400000000134,
-      "q25_diff": 3.5878300000000536,
-      "q50_diff": 5.621710000000007,
-      "q75_diff": 6.360480000000052,
-      "q95_diff": 6.902519999999981
-    },
-    "P2_VT01": {
-      "q05_diff": 0.008320000000001215,
-      "q25_diff": 0.015399999999999636,
-      "q50_diff": 0.01425000000000054,
-      "q75_diff": 0.01332000000000022,
-      "q95_diff": 0.01933999999999969
-    },
-    "P2_VXT02": {
-      "q05_diff": 0.1293899999999999,
-      "q25_diff": 0.30025999999999975,
-      "q50_diff": 0.2858100000000001,
-      "q75_diff": 0.2666400000000002,
-      "q95_diff": 0.46350000000000025
-    },
-    "P2_VXT03": {
-      "q05_diff": 0.09914,
-      "q25_diff": 0.26973,
-      "q50_diff": 0.29760999999999993,
-      "q75_diff": 0.3267899999999999,
-      "q95_diff": 0.6148399999999999
-    },
-    "P2_VYT02": {
-      "q05_diff": 0.09426999999999985,
-      "q25_diff": 0.26261,
-      "q50_diff": 0.22750000000000004,
-      "q75_diff": 0.23531000000000013,
-      "q95_diff": 0.3920400000000006
-    },
-    "P2_VYT03": {
-      "q05_diff": 0.05900000000000016,
-      "q25_diff": 0.18619999999999948,
-      "q50_diff": 0.17652999999999963,
-      "q75_diff": 0.18297000000000008,
-      "q95_diff": 0.35696999999999957
-    },
-    "P3_FIT01": {
-      "q05_diff": 3.0,
-      "q25_diff": 2.0,
-      "q50_diff": 59.0,
-      "q75_diff": 81.89233000000013,
-      "q95_diff": 3.8295900000002803
-    },
-    "P3_LCP01D": {
-      "q05_diff": 0.0,
-      "q25_diff": 8.0,
-      "q50_diff": 104.74890000000005,
-      "q75_diff": 104.43456999999944,
-      "q95_diff": 1.7773400000005495
-    },
-    "P3_LCV01D": {
-      "q05_diff": 16.0,
-      "q25_diff": 256.0,
-      "q50_diff": 3616.0,
-      "q75_diff": 173.35253999999986,
-      "q95_diff": 32.0
-    },
-    "P3_LIT01": {
-      "q05_diff": 1139.3740200000002,
-      "q25_diff": 39.22265999999945,
-      "q50_diff": 651.0800799999997,
-      "q75_diff": 1149.8515599999992,
-      "q95_diff": 1.9414099999994505
-    },
-    "P3_PIT01": {
-      "q05_diff": 3.0,
-      "q25_diff": 4.0,
-      "q50_diff": 1.0,
-      "q75_diff": 74.27202999999997,
-      "q95_diff": 56.83129999999983
-    },
-    "P4_HT_FD": {
-      "q05_diff": 6.999999999999997e-05,
-      "q25_diff": 0.0013700000000000001,
-      "q50_diff": 7.000000000000002e-05,
-      "q75_diff": 7e-05,
-      "q95_diff": 0.0
-    },
-    "P4_HT_LD": {
-      "q05_diff": 0.0,
-      "q25_diff": 0.0,
-      "q50_diff": 5.519399999999997,
-      "q75_diff": 0.6872199999999964,
-      "q95_diff": 0.43401999999998964
-    },
-    "P4_HT_PO": {
-      "q05_diff": 0.0,
-      "q25_diff": 1.06698,
-      "q50_diff": 12.188960000000002,
-      "q75_diff": 0.9946300000000008,
-      "q95_diff": 0.9223599999999976
-    },
-    "P4_LD": {
-      "q05_diff": 0.767089999999996,
-      "q25_diff": 2.9465900000000147,
-      "q50_diff": 3.4085699999999974,
-      "q75_diff": 0.044030000000020664,
-      "q95_diff": 4.712190000000021
-    },
-    "P4_ST_FD": {
-      "q05_diff": 0.0,
-      "q25_diff": 0.0,
-      "q50_diff": 0.0,
-      "q75_diff": 7.000000000000008e-05,
-      "q95_diff": 3.000000000000008e-05
-    },
-    "P4_ST_GOV": {
-      "q05_diff": 135.8427699999993,
-      "q25_diff": 41.480469999998604,
-      "q50_diff": 33.02538999999888,
-      "q75_diff": 110.9257800000014,
-      "q95_diff": 450.9824200000003
-    },
-    "P4_ST_LD": {
-      "q05_diff": 0.8876999999999953,
-      "q25_diff": 0.49813999999997804,
-      "q50_diff": 0.5222200000000043,
-      "q75_diff": 2.0173599999999965,
-      "q95_diff": 8.310819999999978
-    },
-    "P4_ST_PO": {
-      "q05_diff": 2.3917599999999766,
-      "q25_diff": 0.7835099999999784,
-      "q50_diff": 0.6167300000000182,
-      "q75_diff": 2.208280000000002,
-      "q95_diff": 8.297090000000026
-    },
-    "P4_ST_PT01": {
-      "q05_diff": 4.0,
-      "q25_diff": 3.0,
-      "q50_diff": 0.0,
-      "q75_diff": 0.0,
-      "q95_diff": 1.0
-    },
-    "P4_ST_TT01": {
-      "q05_diff": 6.0,
-      "q25_diff": 4.0,
-      "q50_diff": 21.0,
-      "q75_diff": 0.0,
-      "q95_diff": 0.0
-    }
-  },
-  "continuous_lag1_diff": {
-    "P1_B2004": 1.008161591171726,
-    "P1_B2016": 0.032614872748443546,
-    "P1_B3004": 1.012756517745193,
-    "P1_B3005": 0.9975968942482155,
-    "P1_B4002": 0.9946980028776469,
-    "P1_B4005": 0.9478965745689941,
-    "P1_B400B": 0.8683258521675241,
-    "P1_B4022": 0.9280199266439965,
-    "P1_FCV02Z": 1.0160845919977997,
-    "P1_FCV03D": 0.03740437216686243,
-    "P1_FCV03Z": 0.05727471005963358,
-    "P1_FT01": 0.25605297725390685,
-    "P1_FT01Z": 0.21996127187980608,
-    "P1_FT02": 0.9665180510420436,
-    "P1_FT02Z": 0.81609728609831,
-    "P1_FT03": 0.07722837904889823,
-    "P1_FT03Z": 0.9668517187701464,
-    "P1_LCV01D": 0.04587735366012946,
-    "P1_LCV01Z": 0.1332853006024075,
-    "P1_LIT01": 0.06155140364926226,
-    "P1_PCV01D": 1.075619158821944,
-    "P1_PCV01Z": 0.9987349447087184,
-    "P1_PCV02Z": 0.5698197265441381,
-    "P1_PIT01": 0.3563327137747435,
-    "P1_PIT02": 0.4453928887399662,
-    "P1_TIT01": 0.06685680821303808,
-    "P1_TIT02": 0.04528558443487407,
-    "P2_24Vdc": 0.009176161792829447,
-    "P2_CO_rpm": 0.15389353902414754,
-    "P2_HILout": 0.18135785052880374,
-    "P2_MSD": 0.0,
-    "P2_SIT01": 0.14669560193156128,
-    "P2_SIT02": 0.17899767404955558,
-    "P2_VT01": 0.0955104116390263,
-    "P2_VXT02": 0.050904073999146204,
-    "P2_VXT03": 0.03434433886222865,
-    "P2_VYT02": 0.02513319161208072,
-    "P2_VYT03": 0.06621755191185819,
-    "P3_FIT01": 0.1949836039142404,
-    "P3_LCP01D": 0.010916106585345808,
-    "P3_LCV01D": 0.014572087588881177,
-    "P3_LIT01": 0.05719981739012536,
-    "P3_PIT01": 0.19336022780265727,
-    "P4_HT_FD": 0.28857450836315224,
-    "P4_HT_LD": 0.9659307239321158,
-    "P4_HT_PO": 0.9282016244164746,
-    "P4_LD": 0.012028224332918502,
-    "P4_ST_FD": 0.24766612864133963,
-    "P4_ST_GOV": 0.04083006787603549,
-    "P4_ST_LD": 0.0386043986808402,
-    "P4_ST_PO": 0.04535191514417192,
-    "P4_ST_PT01": 0.3748940815676489,
-    "P4_ST_TT01": 0.11304710922473193
-  },
-  "discrete_jsd": {
-    "P1_FCV01D": 0.07117266731043281,
-    "P1_FCV01Z": 0.9086888434475706,
-    "P1_FCV02D": 0.04453949578773361,
-    "P1_PCV02D": 0.0,
-    "P1_PP01AD": 0.0,
-    "P1_PP01AR": 0.0,
-    "P1_PP01BD": 0.0,
-    "P1_PP01BR": 0.0,
-    "P1_PP02D": 0.0,
-    "P1_PP02R": 0.0,
-    "P1_STSP": 0.0,
-    "P2_ASD": 0.0,
-    "P2_AutoGO": 0.0,
-    "P2_Emerg": 0.0,
-    "P2_ManualGO": 0.0,
-    "P2_OnOff": 0.0,
-    "P2_RTR": 0.0,
-    "P2_TripEx": 0.0,
-    "P2_VTR01": 0.0,
-    "P2_VTR02": 0.0,
-    "P2_VTR03": 0.0,
-    "P2_VTR04": 0.0,
-    "P3_LH": 0.0,
-    "P3_LL": 0.0,
-    "P4_HT_PS": 0.029934795636121305,
-    "P4_ST_PS": 0.042281422275128655
-  }
-}

example/results/filtered_metrics.json

@@ -1,77 +0,0 @@
-{
-  "filtered_avg_ks": 0.36938299999999996,
-  "kept_features": [
-    "P1_B2004",
-    "P1_B2016",
-    "P1_B3004",
-    "P1_B3005",
-    "P1_B4005",
-    "P1_B400B",
-    "P1_B4022",
-    "P1_FCV02Z",
-    "P1_FCV03D",
-    "P1_FCV03Z",
-    "P1_FT01",
-    "P1_FT01Z",
-    "P1_FT02",
-    "P1_FT02Z",
-    "P1_FT03",
-    "P1_FT03Z",
-    "P1_LCV01D",
-    "P1_LCV01Z",
-    "P1_LIT01",
-    "P1_PCV01D",
-    "P1_PCV01Z",
-    "P1_PIT01",
-    "P1_PIT02",
-    "P1_TIT01",
-    "P1_TIT02",
-    "P2_24Vdc",
-    "P2_CO_rpm",
-    "P2_HILout",
-    "P2_SIT01",
-    "P2_SIT02",
-    "P2_VT01",
-    "P2_VXT02",
-    "P2_VXT03",
-    "P2_VYT02",
-    "P2_VYT03",
-    "P3_FIT01",
-    "P3_LCP01D",
-    "P3_LCV01D",
-    "P3_LIT01",
-    "P3_PIT01",
-    "P4_HT_FD",
-    "P4_HT_LD",
-    "P4_HT_PO",
-    "P4_LD",
-    "P4_ST_FD",
-    "P4_ST_GOV",
-    "P4_ST_LD",
-    "P4_ST_PO",
-    "P4_ST_PT01",
-    "P4_ST_TT01"
-  ],
-  "dropped_features": [
-    {
-      "feature": "P1_B4002",
-      "ks": 1.0,
-      "std": 0.0
-    },
-    {
-      "feature": "P1_PCV02Z",
-      "ks": 0.998046875,
-      "std": 0.01407231820049816
-    },
-    {
-      "feature": "P2_MSD",
-      "ks": 1.0,
-      "std": 0.0
-    }
-  ],
-  "rules": {
-    "min_std": 0.001,
-    "ks_threshold": 0.95
-  },
-  "original_avg_ks": null
-}

example/results/generated_post.csv

@@ -1,513 +0,0 @@
-time,P1_B2004,P1_B2016,P1_B3004,P1_B3005,P1_B4002,P1_B4005,P1_B400B,P1_B4022,P1_FCV01D,P1_FCV01Z,P1_FCV02D,P1_FCV02Z,P1_FCV03D,P1_FCV03Z,P1_FT01,P1_FT01Z,P1_FT02,P1_FT02Z,P1_FT03,P1_FT03Z,P1_LCV01D,P1_LCV01Z,P1_LIT01,P1_PCV01D,P1_PCV01Z,P1_PCV02D,P1_PCV02Z,P1_PIT01,P1_PIT02,P1_PP01AD,P1_PP01AR,P1_PP01BD,P1_PP01BR,P1_PP02D,P1_PP02R,P1_STSP,P1_TIT01,P1_TIT02,P2_24Vdc,P2_ASD,P2_AutoGO,P2_CO_rpm,P2_Emerg,P2_HILout,P2_MSD,P2_ManualGO,P2_OnOff,P2_RTR,P2_SIT01,P2_SIT02,P2_TripEx,P2_VT01,P2_VTR01,P2_VTR02,P2_VTR03,P2_VTR04,P2_VXT02,P2_VXT03,P2_VYT02,P2_VYT03,P3_FIT01,P3_LCP01D,P3_LCV01D,P3_LH,P3_LIT01,P3_LL,P3_PIT01,P4_HT_FD,P4_HT_LD,P4_HT_PO,P4_HT_PS,P4_LD,P4_ST_FD,P4_ST_GOV,P4_ST_LD,P4_ST_PO,P4_ST_PS,P4_ST_PT01,P4_ST_TT01,attack,attack_P1,attack_P2,attack_P3
-0,0.10087,1.55153,406.14667,1105.2218,33.4603,100.0,2834.81226,35.5587,100,99.91608,0,-1.87531,61.91985,63.42468,220.05844,944.37366,1866.80164,2818.67163,315.67422,993.55328,15.66975,15.59601,408.38345,40.02717,96.2616,12,12.01019,1.38336,0.20233,540833,540833,0,0,1,1,1,34.68933,35.00976,28.02733,0,1,54083.00000,0,719.18335,763.19324,0,1,2880,779.00,777.06085,1,11.82064,10,10,10,10,-3.73089,-1.53190,3.37190,5.48816,233.73076,320.00000,13600.05566,70,5163.76611,20,-23.00000,-0.00022,66.00839,75.23151,0,429.76498,0.00029,19936.05664,382.28311,368.38190,0,10082.00000,27605.00000,,,,
-1,0.10087,1.53749,397.63785,1105.2218,33.4603,99.8333,2838.46216,36.81366,0,0.29907,0,97.21527,62.61278,63.41705,221.09987,948.32611,30.17423,61.93509,316.65799,1009.74396,16.94067,14.64996,408.63907,44.90384,92.95807,12,12.01782,1.38336,0.20233,540833,540833,0,0,1,1,1,34.78089,35.02502,28.0273,0,1,54078.00000,0,712.24365,763.19324,0,1,2880,783.00,782.91345,1,11.81842,10,10,10,10,-4.07932,-1.51786,3.32997,5.51892,186.95560,392.00000,13472.00000,70,5186.18701,20,-18.00000,0.00000,61.45111,2.26056,0,435.45868,0.00246,20565.58008,394.53986,372.25812,0,10053.00000,27605.00000,,,,
-2,0.10087,1.52599,406.14667,1105.2218,33.4603,100.0,2835.82129,37.46444,100,0.29907,100,-1.88294,62.37249,64.71405,224.34232,947.86792,51.81633,417.56985,314.94138,1107.05811,28.33634,14.99329,408.33234,43.61514,90.95154,12,11.78894,1.38107,0.20233,540833,540833,0,0,1,1,1,34.78089,35.04028,28.03166,0,1,54088.00000,0,690.69824,763.19324,0,1,2880,781.00,781.28674,1,11.80578,10,10,10,10,-4.14184,-1.55461,3.40345,5.65168,154.94266,252.35739,13807.35254,70,5146.97852,20,-19.00000,-0.00022,76.99652,0.05423,0,444.55591,0.00137,20045.23633,387.47101,372.77524,0,10053.00000,27605.00000,,,,
-3,0.10121,1.53472,393.16226,1105.2218,33.4603,100.0,2833.82959,35.82954,100,99.91608,100,-1.88294,63.42416,63.65356,226.63112,947.23492,1953.36169,2830.46045,310.74518,994.85779,15.71569,14.99329,407.97821,42.54508,46.54846,12,12.01019,1.37802,0.17029,540833,540833,0,0,1,1,1,34.79614,35.13183,28.03166,0,1,54115.00000,0,721.41113,763.19324,0,1,2880,776.00,775.90436,1,11.82006,10,10,10,10,-4.08445,-1.50179,3.41573,5.68726,132.29260,240.00000,13744.00000,70,5664.96631,20,-19.00000,0.00000,-0.00723,14.97394,0,441.19296,-0.00043,20319.34961,387.08862,381.08395,0,10082.00000,27605.00000,,,,
-4,0.10087,1.53172,397.63785,1105.2218,33.6555,100.0,2824.98535,36.69781,100,0.29907,100,-1.88294,64.49872,66.58325,230.48355,957.89349,1969.18481,1454.17371,309.02856,1005.66596,15.41116,15.59601,408.04236,37.21034,80.40008,12,11.78131,1.37573,0.17029,540833,540833,0,0,1,1,1,34.82666,35.34546,28.0299,0,1,54107.00000,0,705.62744,763.19324,0,1,2880,777.00,778.46960,1,11.81058,10,10,10,10,-4.02695,-1.41771,3.43602,5.60389,-20.00000,168.00000,13727.85254,70,5709.64941,20,-23.00000,-0.00166,0.0217,0.07236,0,445.52902,-0.00015,20339.19336,391.76865,379.21115,0,10053.00000,27605.00000,,,,
-5,0.10121,1.56314,405.06735,1001.99799,31.91024,100.0,2839.16406,35.68905,100,0.29907,100,97.19238,65.31944,67.30804,233.30688,1381.95740,1818.47034,95.32771,312.27112,1105.14465,15.47586,15.59601,407.60147,58.82486,37.28638,12,11.78131,1.37268,0.17029,540833,540833,0,0,1,1,1,34.84191,35.37598,28.03078,0,1,54102.00000,0,725.92163,763.19324,0,1,2880,778.00,779.11731,1,11.80315,10,10,10,10,-4.03006,-1.36755,3.54145,5.75004,-20.00000,64.00000,13888.00000,70,5232.34766,20,-23.00000,-0.01237,69.14062,4.0871,0,446.70825,0.00058,20708.83398,393.16608,383.23648,0,10053.00000,27605.00000,,,,
-6,0.10087,1.57785,405.06735,993.95294,33.4603,100.0,2831.72388,35.46551,100,99.91608,0,-1.87531,65.99487,64.47001,226.63112,950.50049,1964.98853,2829.33740,312.46182,992.24847,15.38116,15.59601,406.90106,39.15923,45.83893,12,11.78894,1.37115,0.20233,540833,540833,0,0,1,1,1,34.84191,35.58960,28.02649,0,1,54118.00000,0,690.77759,763.19324,0,1,2880,776.00,776.82123,1,11.80961,10,10,10,10,-3.66089,-1.33219,3.63483,5.82225,-9.00000,104.00000,13945.84570,70,6074.20264,20,-23.00000,-0.00166,-0.00723,68.52216,10,452.93524,-0.00116,21018.37305,409.77145,386.14999,0,10053.00000,27605.00000,,,,
-7,0.10087,1.58781,406.14667,1105.2218,31.91024,90.36559,2825.82788,37.32418,100,0.29907,100,-1.86005,66.06993,67.30804,222.05353,981.49548,20.32437,30.98430,313.79694,1106.42029,15.25445,15.59601,406.74771,100.0,38.60626,12,12.01782,1.37115,0.20233,540833,540833,0,0,1,1,1,34.87244,35.68115,28.03166,0,1,54054.00000,0,702.27661,763.19324,0,1,2880,786.00,786.58496,1,11.82210,10,10,10,10,-3.89397,-1.31843,3.64826,5.81288,-7.00000,96.04768,14082.01367,70,6394.33154,20,-19.00000,0.00000,2.67651,66.87646,0,472.00363,0.00392,24703.94531,465.82959,382.05707,0,10053.00000,27627.00000,,,,
-8,0.10087,1.61048,405.06735,1001.99799,31.91024,100.0,2837.33911,35.67952,100,99.91608,0,-1.88294,66.48334,67.17834,222.43500,957.02368,11.31327,34.95676,313.76691,1107.05811,15.27223,14.99329,406.51743,41.9794,44.81659,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.88770,35.66589,28.02473,0,1,54093.00000,0,715.17334,763.19324,0,1,2880,781.00,782.94891,1,11.87236,10,10,10,10,-3.40639,-1.33748,3.56275,5.72621,-20.00000,80.00000,14224.00000,70,5330.92725,20,-19.00000,-0.00166,65.42245,70.04126,0,465.80771,0.00159,24235.49414,499.62018,393.33090,0,10053.00000,27605.00000,,,,
-9,0.10087,1.60269,406.14667,1001.99799,32.0,100.0,29.99137,36.87405,100,99.91608,0,-1.87531,66.34825,62.71094,220.71838,940.06360,1720.51233,2831.86426,309.60083,992.24847,15.14026,14.99329,405.52094,45.23514,90.36407,12,11.78131,1.36658,0.20233,540833,540833,0,0,1,1,1,34.85717,35.86426,28.02476,0,1,54091.00000,0,708.27026,763.19324,0,1,2880,781.00,781.17352,1,11.89972,10,10,10,10,-3.37658,-1.32164,3.55168,5.81533,2980.39429,120.00000,14672.00000,70,9325.11328,20,-19.00000,0.00239,0.77403,25.69806,0,451.84940,-0.00080,26927.00000,406.18802,498.86066,0,10053.00000,27590.00000,,,,
-10,0.10121,1.64287,397.63785,1115.11975,32.0,100.0,2831.30273,35.58807,100,99.91608,100,3.81622,71.30779,69.89441,227.96626,965.57446,6.33237,33.96383,313.41553,1117.85059,15.11760,15.22980,405.57205,100.0,32.19757,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.91821,35.86426,28.02814,0,1,54091.00000,0,719.58008,763.19324,0,1,2880,783.00,782.39032,1,11.92360,10,10,10,10,-3.69311,-1.47069,3.45183,5.78864,-7.00000,32.00000,14407.06348,70,6858.48340,20,-19.00000,-0.00022,-0.00723,0.72336,0,467.24356,0.00159,21449.06836,397.30484,407.92166,0,10053.00000,27605.00000,,,,
-11,0.10087,1.69753,406.14667,1105.2218,33.6555,0.0,2826.81055,37.28375,0,99.91608,0,-1.8219,66.83775,66.58325,220.71838,953.10980,82.57358,32.97053,316.65799,1103.55005,15.07640,14.99329,406.13434,45.32695,87.28942,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.91821,35.92529,28.02564,0,1,54084.00000,0,698.9563,763.19324,0,1,2880,784.00,785.08325,1,11.92197,10,10,10,10,-3.81861,-1.54801,3.49850,6.00780,-20.00000,32.00000,14505.50781,70,6736.60986,20,-23.00000,-0.00166,-0.00723,0.07236,10,465.10187,0.00195,25222.26562,395.96310,403.48404,0,10053.00000,27605.00000,,,,
-12,0.10121,1.76771,397.63785,1001.99799,33.4603,100.0,366.34030,37.26047,0,99.91608,0,-1.88294,66.74463,66.47643,221.29057,941.80298,1974.52527,2830.03906,314.33914,1003.27423,15.00382,15.22980,405.88562,41.66881,92.9657,12,12.01782,1.36658,0.27557,540833,540833,0,0,1,1,1,34.93347,35.97107,28.0247,0,1,54109.00000,0,711.33423,763.19324,0,1,2880,781.00,780.80865,1,11.89192,10,10,10,10,-3.98817,-1.43493,3.74012,6.10192,-20.00000,40.00000,14730.52441,70,7935.60693,20,-23.00000,0.00000,-0.00723,79.19196,0,482.12292,-0.00123,21933.12305,395.22119,450.41351,0,10053.00000,27605.00000,,,,
-13,0.10145,1.68895,397.63785,993.95294,31.91024,100.0,2835.23340,35.42813,100,99.91608,100,-1.87531,71.87019,68.00231,222.24423,961.63141,6.14166,32.97053,314.64145,1012.93304,14.97875,14.64996,406.08322,51.60086,99.44716,12,11.78894,1.37268,0.20233,540833,540833,0,0,1,1,1,34.90295,35.98632,28.02216,0,1,54090.00000,0,714.7644,763.19324,0,1,2880,784.00,783.35175,1,11.84775,10,10,10,10,-4.24362,-1.76181,3.84057,6.18457,-20.00000,8.00000,14774.64941,70,9637.15625,20,-19.00000,-0.00022,-0.00723,49.85895,0,468.04175,0.00210,21755.02344,376.21387,398.15695,0,10053.00000,27627.00000,,,,
-14,0.10121,1.65440,406.14667,993.95294,33.6555,100.0,349.72922,37.41638,100,99.91608,0,-1.87531,70.49820,67.30804,219.95543,940.49835,1976.24182,2818.38965,317.39081,1105.4635,14.92195,14.99329,405.67429,44.25194,42.63458,12,11.78131,1.37268,0.20233,540833,540833,0,0,1,1,1,34.93347,36.04736,28.02821,0,1,54107.00000,0,716.08276,763.19324,0,1,2880,781.00,781.61505,1,11.88366,10,10,10,10,-3.81586,-1.63496,3.80060,6.14417,-22.00000,0.00000,15296.09863,70,9472.97266,20,-23.00000,-0.00166,66.06625,65.41162,0,491.51648,-0.00036,23000.27148,377.20129,402.07159,0,10053.00000,27590.00000,,,,
-15,0.10087,1.62172,397.63785,1001.99799,31.91024,100.0,2818.66919,36.26431,100,99.91608,0,97.17712,73.51543,65.76953,219.23708,938.98889,1982.34558,2828.69263,314.75067,1103.55005,14.80431,14.99329,405.31647,45.6111,41.56647,12,12.01019,1.37268,0.27557,540833,540833,0,0,1,1,1,34.97925,36.36779,28.02558,0,1,54126.00000,0,712.29858,763.19324,0,1,2880,777.00,777.38593,1,11.86083,10,10,10,10,-3.22918,-1.38183,4.53079,6.22015,-22.00000,0.00000,14960.00000,70,11394.44727,20,-23.00000,-0.00166,0.02895,1.33826,0,455.81662,-0.00159,20683.96680,374.12872,383.59109,0,10053.00000,27605.00000,,,,
-16,0.10087,1.58915,406.14667,1001.99799,33.4603,32.65871,30.98430,37.06631,100,99.91608,100,97.19238,71.05752,71.88568,221.29057,939.62860,1966.70508,1005.97388,316.62372,1000.88245,14.76598,14.63470,403.93631,41.88247,39.17846,12,11.78894,1.37726,0.20233,540833,540833,0,0,1,1,1,35.02502,36.09313,28.0299,0,1,54090.00000,0,715.06348,763.19324,0,1,2880,784.00,784.94641,1,11.91262,10,10,10,10,-3.02676,-1.38389,4.12514,6.14231,-7.00000,24.00000,15640.92871,70,9695.23438,20,-19.00000,0.00072,-0.00723,15.89624,0,454.61841,0.00029,20064.95117,363.65115,378.74612,0,10052.00000,27590.00000,,,,
-17,0.10121,1.56855,406.14667,1105.2218,33.6555,100.0,2824.84521,37.24255,100,0.29907,0,-1.88294,67.33670,67.17834,218.81099,939.62860,64.53584,29.99137,315.67422,1106.73914,14.78542,14.52789,403.42511,43.60309,31.39648,12,12.01019,1.37878,0.27557,540833,540833,0,0,1,1,1,34.99451,36.15417,28.02736,0,1,54058.00000,0,715.61279,763.19324,0,1,2880,787.00,787.59644,1,11.93534,10,10,10,10,-3.36078,-1.50992,3.81697,6.18840,-20.00000,8.00000,15516.02246,70,10160.78418,20,-19.00000,0.00000,65.87094,6.16681,0,458.55075,0.00321,19960.73242,358.70963,370.27783,0,10052.00000,27627.00000,,,,
-18,0.10187,1.55970,406.14667,993.95294,31.91024,100.0,887.77399,37.63649,100,99.91608,100,-1.88294,74.18626,68.36090,219.76472,938.75885,1972.99939,2830.88159,317.03949,1002.62195,14.72465,14.54222,404.90750,37.18406,47.01385,12,12.01782,1.38031,0.27557,540833,540833,0,0,1,1,1,34.99451,37.39014,28.02909,0,1,54115.00000,0,718.48755,763.19324,0,1,2880,780.00,781.20319,1,11.97193,10,10,10,10,-3.04611,-1.66603,3.81331,6.17767,-20.00000,0.00000,15776.00000,70,9865.71484,20,-23.00000,0.00000,62.89062,0.07236,0,449.90759,-0.00130,19797.16211,353.84344,369.52353,0,10053.00000,27605.00000,,,,
-19,0.10145,1.52295,405.06735,1001.99799,33.4603,100.0,39.19523,37.59922,100,99.91608,0,97.21527,67.58058,67.17834,218.81099,937.88904,1960.98328,699.28802,317.03949,1106.73914,14.69963,14.52789,404.24301,96.38348,49.63074,12,12.01019,1.38184,0.27557,540833,540833,0,0,1,1,1,35.00976,36.70349,28.02902,0,1,54096.00000,0,712.70142,763.19324,0,1,2880,784.00,784.87689,1,11.97973,10,10,10,10,-3.71010,-1.81684,3.75933,6.20222,-20.00000,0.00000,16104.14160,70,10551.65137,20,-23.00000,0.00072,60.25754,0.16278,0,444.27853,0.00029,19720.00977,349.78473,365.80350,0,10053.00000,27590.00000,,,,
-20,0.10145,1.51759,405.06735,993.95294,33.4603,100.0,31.08166,37.3088,100,0.29907,100,-1.87531,68.68765,71.88568,218.62029,937.45422,1973.38098,1913.18762,317.03949,1003.92651,14.68008,14.52789,405.00977,84.61914,43.82477,12,12.01782,1.38489,0.27557,540833,540833,0,0,1,1,1,35.02502,37.63427,28.03341,0,1,54098.00000,0,700.77515,763.19324,0,1,2880,784.00,784.78784,1,11.96329,10,10,10,10,-4.03656,-1.96786,3.76604,6.23150,-22.00000,-8.00000,16052.70508,70,12163.08203,20,-19.00000,0.00000,64.15653,38.737,0,441.70224,-0.00015,19657.61914,338.44287,363.94528,0,10053.00000,27590.00000,,,,
-21,0.10087,1.51065,445.34219,1119.68103,31.91024,100.0,2798.20581,37.46749,100,0.29907,0,-1.87531,70.69044,73.77068,218.42952,937.01929,1964.79797,1468.44116,314.75067,994.85779,14.18994,14.52789,404.65195,84.1098,99.52664,12,11.78894,1.38565,0.27557,540833,540833,0,0,1,1,1,35.28442,37.25309,28.02993,0,1,54118.00000,0,716.33301,763.19324,0,1,2880,780.00,780.56848,1,11.90094,10,10,10,10,-4.06175,-1.92590,4.49387,6.59086,-22.00000,0.00000,15616.71582,70,13384.79492,20,-23.00000,0.00000,72.98175,59.57031,0,433.61688,-0.00042,19585.95703,334.84076,363.24707,0,10053.00000,27590.00000,,,,
-22,0.10145,1.50502,406.14667,1001.99799,31.91024,97.06264,2826.38940,36.63982,100,99.91608,100,-1.88294,69.19516,68.36090,218.04811,936.58447,5.95089,30.98430,318.19070,1003.05676,14.36039,14.41345,404.90750,43.51535,40.49835,12,11.78894,1.38718,0.27557,540833,540833,0,0,1,1,1,35.08606,36.70349,28.03858,0,1,54086.00000,0,704.76685,763.19324,0,1,2880,786.00,785.65985,1,11.83391,10,10,10,10,-4.27982,-1.86470,4.86580,6.91243,-20.00000,-8.00000,16967.79297,70,13609.05078,20,-19.00000,0.00123,0.12297,12.80377,0,432.27530,0.00181,19367.08789,332.39310,360.93021,0,10053.00000,27605.00000,,,,
-23,0.10121,1.49920,393.16226,1105.2218,33.4603,100.0,2835.51392,37.4427,100,99.91608,0,-1.87531,66.38683,64.83612,217.85733,935.27991,6.52737,499.67438,315.67422,995.2926,14.10158,14.41345,404.44748,99.54177,99.34471,12,11.78894,1.38794,0.27557,540833,540833,0,0,1,1,1,35.13183,37.57388,28.02298,0,1,54100.00000,0,711.66992,763.19324,0,1,2880,783.00,784.31030,1,11.83527,10,10,10,10,-3.95175,-1.81236,4.93512,6.73041,-20.00000,0.00000,17443.32422,70,12369.56445,20,-19.00000,0.00123,72.75028,63.76593,0,429.07880,0.00058,19254.62500,327.70328,359.55676,0,10053.00000,27590.00000,,,,
-24,0.10145,1.49369,405.06735,993.95294,31.91024,100.0,2824.28369,37.57164,100,99.91608,100,97.23052,65.91814,64.49280,217.28516,935.71472,6.71385,31.97760,317.99564,1103.8689,14.08875,14.41338,402.86246,30.30516,100.0,12,12.01782,1.38870,0.27557,540833,540833,0,0,1,1,1,35.13183,37.37488,28.03257,0,1,54078.00000,0,712.47559,763.19324,0,1,2880,786.00,786.55927,1,11.88195,10,10,10,10,-3.80987,-1.73448,4.69493,6.56785,-20.00000,0.00000,16865.06055,70,11881.93164,20,-19.00000,0.00123,72.53326,55.84491,0,427.30707,0.00195,18769.33789,325.54959,354.31177,50,10053.00000,27590.00000,,,,
-25,0.10087,1.46730,406.14667,993.95294,33.4603,100.0,34.95676,37.79365,100,99.91608,100,-1.87531,66.29298,74.02190,217.85733,934.84497,1963.27209,2814.43628,317.77228,1003.05676,13.76196,14.41345,403.68073,39.98775,57.69501,12,11.78131,1.38946,0.27557,540833,540833,0,0,1,1,1,35.37598,37.71057,28.02733,0,1,54104.00000,0,714.95361,763.19324,0,1,2880,783.00,782.62256,1,11.94932,10,10,10,10,-3.30441,-1.71045,4.19968,6.30201,-20.00000,0.00000,16432.00000,70,10621.19043,20,-23.00000,0.00123,66.37732,7.10721,0,426.86642,-0.00065,18362.94922,321.98276,347.77460,0,10053.00000,27582.00000,,,,
-26,0.10145,1.45230,405.06735,1105.2218,33.4603,18.0955,1170.42078,36.82713,100,0.29907,0,-1.87531,65.70667,68.13823,217.09438,934.84497,44.90711,32.97053,318.93515,996.59729,13.45740,14.41345,402.56635,46.94975,87.69378,12,12.01782,1.39099,0.58304,540833,540833,0,0,1,1,1,35.28442,37.26807,28.02649,0,1,54076.00000,0,708.02002,763.19324,0,1,2880,785.00,785.48547,1,11.97732,10,10,10,10,-3.52410,-1.82045,4.15769,6.25597,-20.00000,-8.00000,16090.40625,70,12868.22461,20,-23.00000,0.00072,60.9158,68.46783,0,423.73090,0.00137,18174.99219,320.30878,336.83655,0,10053.00000,27590.00000,,,,
-27,0.10121,1.42562,406.14667,1105.2218,31.91024,100.0,151.30318,37.2826,100,0.29907,100,97.22671,66.65807,74.72828,216.71291,933.54034,6.33237,32.97053,316.62787,1000.88245,13.35819,14.40582,403.83405,39.73293,99.72713,12,11.78894,1.39099,0.58304,540833,540833,0,0,1,1,1,35.36072,37.49695,28.03341,0,1,54072.00000,0,708.62427,763.19324,0,1,2880,785.00,785.37683,1,12.00559,10,10,10,10,-3.74582,-1.86881,3.79732,6.23326,-20.00000,0.00000,15808.00000,70,13417.59766,20,-23.00000,0.00123,-0.00723,1.88077,0,420.13599,0.00152,18012.63867,317.35696,336.27094,0,10053.00000,27577.00000,,,,
-28,0.10087,1.40699,445.34219,993.95294,31.91024,100.0,1524.77332,35.26448,100,99.91608,0,-1.87531,67.15095,66.58325,215.95001,932.67059,5.95089,520.48718,311.85638,1105.78247,13.09114,14.39819,402.24945,98.62209,43.94684,12,11.78131,1.39252,1.80603,540833,540833,0,0,1,1,1,35.08606,36.90185,28.02389,0,1,54087.00000,0,729.40063,763.19324,0,1,2880,784.00,784.29211,1,11.99695,10,10,10,10,-3.94435,-1.88041,3.80370,6.25309,-7.00000,0.00000,16178.37402,70,13596.63574,20,-19.00000,0.00123,69.23465,56.38745,0,409.52136,0.00080,17842.93359,316.06155,333.44870,0,10053.00000,27582.00000,,,,
-29,0.10121,1.39550,405.06735,1001.99799,32.0,58.87216,2830.03906,35.76698,100,0.29907,100,44.99206,66.27526,67.30804,216.33150,933.54034,5.76019,122.79314,313.41553,990.94391,12.98398,14.19178,400.05142,90.65773,43.71033,12,11.78894,1.39328,0.58304,540833,540833,0,0,1,1,1,35.13183,36.90185,28.02645,0,1,54086.00000,0,718.43262,763.19324,0,1,2880,783.00,782.78113,1,11.94221,10,10,10,10,-4.12405,-1.94438,3.95408,6.35965,-20.00000,-8.00000,15979.11621,70,12986.81445,20,-23.00000,0.00123,63.40424,31.26807,0,401.11569,0.00109,17731.42188,311.82809,330.00662,50,10053.00000,27590.00000,,,,
-30,0.10087,1.38618,393.16226,1105.2218,31.91024,100.0,115.14299,35.91194,100,99.91608,0,97.2229,64.60752,67.17834,215.52370,930.93109,1968.61255,2824.70483,312.81729,992.68347,12.78629,14.39819,403.82870,34.80099,41.09344,12,11.78894,1.39404,1.80603,540833,540833,0,0,1,1,1,35.13183,36.70349,28.03078,0,1,54107.00000,0,719.75098,763.19324,0,1,2880,780.00,779.76733,1,11.90679,10,10,10,10,-4.21124,-1.83091,4.54614,6.57183,-22.00000,0.00000,16539.25781,70,12314.54492,20,-23.00000,0.00000,79.0654,4.28604,0,387.62338,-0.00137,17612.49219,312.08038,328.08408,50,10053.00000,27574.00000,,,,
-31,0.10121,1.37689,405.06735,1105.2218,31.91024,100.0,30.98430,35.35374,100,0.29907,100,16.96167,64.73723,71.88568,215.37776,930.51727,1956.97778,348.26956,314.91235,1105.14465,12.61561,14.17694,404.54968,41.69818,99.75049,12,11.78131,1.39481,1.80603,540833,540833,0,0,1,1,1,35.13183,37.39014,28.02649,0,1,54073.64453,0,699.06006,763.19324,0,1,2880,785.00,785.39301,1,11.89426,10,10,10,10,-3.92934,-1.77868,3.94301,6.43365,-22.00000,0.00000,15744.00000,70,12204.46680,20,-23.00000,0.00123,66.26157,69.57104,0,370.39609,0.00015,17584.37109,309.25540,326.33191,0,10053.00000,27566.00000,,,,
-32,0.10087,1.37148,406.14667,993.95294,33.4603,0.0,2828.63550,35.87216,100,99.91608,0,48.36425,65.57191,65.64077,214.99635,929.19171,1955.25977,2826.10840,308.45639,988.76959,12.09278,14.16931,401.53278,41.3487,50.67596,12,11.78131,1.39633,0.58304,540833,540833,0,0,1,1,1,35.28442,37.37488,28.03081,0,1,54118.00000,0,720.00122,763.19324,0,1,2880,776.00,776.09253,1,11.85371,10,10,10,10,-3.46680,-1.63769,4.72833,6.46160,-22.00000,-8.00000,15401.18164,70,12800.24805,20,-23.00000,0.00000,76.237,69.57104,0,355.86264,-0.00145,17509.05078,308.22449,325.31732,0,10053.00000,27562.00000,,,,
-33,0.10087,1.36536,405.06735,993.95294,33.6555,100.0,30.98430,37.08767,100,0.29907,100,-1.87531,63.56047,66.58325,214.23340,928.75671,1967.46826,33.96383,308.30350,1106.42029,11.21660,14.16931,402.41058,36.96334,39.66674,12,12.01782,1.39709,0.58304,540833,540833,0,0,1,1,1,35.08606,36.90185,28.02733,0,1,54078.00000,0,715.93018,763.19324,0,1,2880,784.00,783.74969,1,11.87959,10,10,10,10,-3.55662,-1.56340,4.43230,6.32165,-22.00000,0.00000,15528.18262,70,12661.25586,20,-23.00000,0.00000,0.0217,70.27631,0,352.03732,0.00007,17423.00977,305.88916,324.00333,50,10053.00000,27547.00000,,,,
-34,0.10121,1.35801,406.14667,993.95294,33.6555,100.0,150.93962,37.94891,100,99.91608,100,-1.85242,63.88074,66.58325,214.42410,929.19171,6.33237,108.02019,308.07300,994.64032,11.05180,14.16931,400.30698,45.32359,42.87109,12,11.78894,1.39938,0.58304,540833,540833,0,0,1,1,1,35.11657,36.90185,28.02389,0,1,54069.00000,0,709.34448,763.19324,0,1,2880,785.00,784.24634,1,11.88948,10,10,10,10,-3.59639,-1.48477,4.65535,6.28047,-22.00000,0.00000,15872.00000,70,11942.27441,20,-23.00000,0.00123,-0.00723,0.07236,0,349.92560,0.00094,17366.88086,303.33023,322.01163,0,10053.00000,27566.00000,,,,
-35,0.10087,1.35437,406.14667,1105.2218,33.6555,100.0,2530.55469,37.88494,100,99.91608,0,-1.88294,63.67199,63.17122,214.04262,926.58234,1959.64807,2827.66846,307.50461,997.03217,10.26625,14.16931,400.30698,43.45702,99.43542,12,12.01782,1.40091,2.13248,540833,540833,0,0,1,1,1,35.08606,36.70349,28.03162,0,1,54113.00000,0,704.94995,763.19324,0,1,2880,776.00,776.35608,1,11.93493,10,10,10,10,-3.09556,-1.39272,4.42898,6.23761,-22.00000,0.00000,15072.00000,70,11632.18066,20,-23.00000,0.00000,-0.00723,2.13397,0,342.62036,-0.00181,17261.56250,302.37991,322.27975,50,10053.00000,27566.00000,,,,
-36,0.10087,1.34666,397.63785,1001.99799,33.4603,7.53954,32.36442,37.00603,100,0.29907,100,-1.87531,63.02665,67.30804,214.61488,927.45215,1600.74060,86.55075,307.50275,995.2926,9.51225,14.15445,400.25360,42.43901,38.94958,12,12.01782,1.40396,1.80603,540833,540833,0,0,1,1,1,35.26917,36.48986,28.02733,0,1,54075.00000,0,698.16895,763.19324,0,1,2880,783.00,783.49884,1,11.95220,10,10,10,10,-3.15990,-1.40986,3.97279,6.15985,-22.00000,0.00000,15051.90820,70,10129.25977,20,-23.00000,0.00072,0.0217,0.30743,0,337.60745,-0.00015,17165.05664,294.41055,320.00699,0,10053.00000,27566.00000,,,,
-37,0.03051,1.34083,405.06735,1001.99799,33.4603,100.0,30.98430,37.1777,100,0.29907,0,-1.88294,62.80199,65.76690,213.23381,925.27783,1957.74084,31.97760,307.69345,1111.7915,8.53594,14.05487,403.78293,41.30778,44.64874,12,11.78131,1.40625,1.80603,540833,540833,0,0,1,1,1,35.19287,36.35140,28.02912,0,1,54049.39844,0,702.24609,763.19324,0,1,2880,785.00,785.59308,1,11.97383,10,10,10,10,-3.07502,-1.51362,3.68980,6.10801,-22.00000,16.00000,14848.03223,70,10865.81934,20,-23.00000,0.00000,65.63947,63.76593,0,334.81421,0.00072,17173.96484,295.70309,318.39609,0,10053.00000,27562.00000,,,,
-38,0.10121,1.33768,406.14667,1001.99799,33.4603,100.0,32.97053,37.60711,100,0.29907,100,97.19238,62.54589,64.36310,212.58015,926.12006,614.47192,30.98430,307.84702,1000.44769,8.50352,14.05487,401.08649,48.19861,36.93543,12,11.78894,1.41003,0.58304,540833,540833,0,0,1,1,1,35.28442,36.15417,28.03253,0,1,54047.00000,0,699.4873,763.19324,0,1,2880,784.00,785.85413,1,11.99648,10,10,10,10,-2.99504,-1.63287,3.61337,6.07844,-22.00000,16.00000,14755.55762,70,9963.77051,20,-23.00000,0.00000,-0.00723,1.95312,0,332.46054,0.00094,17097.57031,292.21127,317.26343,0,10053.00000,27570.00000,,,,
-39,0.10087,1.32696,406.14667,1115.11975,33.6555,100.0,29.99137,35.77984,100,99.91608,100,97.17712,63.63125,62.00554,212.32600,921.36395,5.56941,2835.09277,303.68802,1005.23102,8.17639,13.45978,395.96204,42.95216,77.24151,12,12.01782,1.41312,0.58304,540833,540833,0,0,1,1,1,35.28442,36.15417,28.02902,0,1,54058.00000,0,705.74341,763.19324,0,1,2880,780.00,779.62164,1,11.98459,10,10,10,10,-2.79210,-1.60196,3.61058,6.05354,5133.59473,144.00000,14816.00000,70,12749.98633,20,-19.00000,0.01520,64.47482,11.84534,0,319.89105,-0.00087,17131.77734,241.94136,319.57776,50,10082.00000,27562.00000,,,,
-40,0.10145,1.32878,405.06735,1105.2218,33.4603,100.0,2820.41260,37.08614,100,0.29907,100,-1.84479,62.64225,63.76801,211.60710,923.97308,6.14166,31.97760,306.73978,1108.97144,7.96136,13.93280,398.62015,39.14008,43.16101,12,11.78894,1.42379,0.57123,540833,540833,0,0,1,1,1,35.28442,36.36779,28.02301,0,1,53951.00000,0,711.39526,763.19324,0,1,2880,784.00,785.30438,1,12.00197,10,10,10,10,-3.15307,-1.46064,3.49297,5.99860,-22.00000,48.00000,14192.00000,70,10352.51074,20,-23.00000,0.00072,42.00665,2.8212,0,317.29111,0.00231,16943.68359,269.36063,314.31696,0,10053.00000,27570.00000,,,,
-41,0.10121,1.32277,405.06735,993.95294,33.4603,100.0,34.03355,37.33753,100,99.91608,0,-1.87531,61.62679,63.41705,211.18164,921.79871,1973.38098,211.74200,305.02316,996.59735,7.80361,13.93280,400.66632,99.31679,99.23765,12,12.01782,1.42525,0.58304,540833,540833,0,0,1,1,1,35.45227,36.33728,28.02909,0,1,54075.85547,0,713.28125,763.19324,0,1,2880,781.00,782.98883,1,12.01502,10,10,10,10,-2.75084,-1.45671,3.51431,6.00098,-25.00000,40.00000,14208.00000,70,9403.42285,20,-23.00000,0.00000,43.48235,61.39685,0,315.67447,-0.00058,16748.32422,265.57169,311.10193,0,10053.00000,27530.00000,,,,
-42,0.10087,1.31792,406.14667,1105.2218,33.4603,31.39417,2552.34180,37.21355,100,99.91608,0,-1.87531,62.29846,62.93640,212.22684,921.86688,1961.01062,1583.15613,306.16760,993.11829,7.81745,13.93280,399.28467,100.0,99.36124,12,12.01782,1.44215,0.58304,540833,540833,0,0,1,1,1,35.37598,36.70349,28.02561,0,1,54097.00000,0,714.84985,763.19324,0,1,2880,777.00,778.92151,1,12.01995,10,10,10,10,-2.71067,-1.57576,3.41865,5.92255,-25.00000,72.00000,13808.99121,70,9361.79199,20,-23.00000,0.00000,6.24278,36.38599,0,310.91931,-0.00080,16825.98438,276.73199,311.69492,0,10082.00000,27554.00000,,,,
-43,0.10121,1.31327,406.14667,1105.2218,31.91024,100.0,33.96383,37.11895,100,0.29907,100,-1.88294,62.12928,63.29498,211.82840,920.92896,1970.90137,2825.96826,306.34067,999.64148,7.49305,13.45978,399.74472,50.06331,39.18609,12,12.01782,1.45040,0.58304,540833,540833,0,0,1,1,1,35.37598,36.90185,28.02301,0,1,54092.00000,0,708.89282,763.19324,0,1,2880,778.00,779.02991,1,12.02043,10,10,10,10,-2.84609,-1.47473,3.51707,5.90314,-25.00000,136.00000,13383.11621,70,6956.90771,20,-23.00000,0.00000,70.37762,68.14233,0,307.47003,-0.00130,16779.07617,277.77975,310.25754,0,10053.00000,27554.00000,,,,
-44,0.10087,1.30756,397.63785,1001.99799,33.4603,100.0,2831.02197,37.48886,100,99.91608,0,-1.87531,62.18030,62.47863,211.37234,919.47699,1884.94299,2829.61816,304.37653,1104.18787,7.39419,12.75024,398.16006,45.68026,47.61658,12,12.01782,1.45804,0.27557,540833,540833,0,0,1,1,1,35.28442,36.70349,28.03074,0,1,54109.00000,0,709.52759,763.19324,0,1,2880,770.00,770.11340,1,11.98794,10,10,10,10,-2.89307,-1.50324,3.58685,6.01207,-25.00000,137.70949,13616.00000,70,8662.67969,20,-23.00000,0.00000,56.83594,65.37543,0,303.62030,-0.00181,16537.12891,251.19524,308.89871,0,10082.00000,27570.00000,,,,
-45,0.10121,1.29998,405.06735,993.95294,33.6555,100.0,2830.34985,37.12467,0,99.91608,0,-1.87531,62.07339,62.36419,209.65573,918.75458,5.95089,1829.23315,304.45099,993.11829,7.30457,11.33090,397.96924,88.22762,45.24383,12,12.01782,1.47415,0.58304,540833,540833,0,0,1,1,1,35.54382,36.15417,28.02649,0,1,54076.00000,0,721.74072,763.19324,0,1,2880,779.00,779.57245,1,12.01015,10,10,10,10,-2.97957,-1.50710,3.46027,5.92828,-22.00000,284.78046,13252.76270,70,7358.82715,20,-23.00000,0.00000,63.62848,73.47729,10,296.38498,0.00058,16627.43750,264.82761,307.00787,0,10082.00000,27562.00000,,,,
-46,0.10145,1.29140,397.63785,1105.2218,32.0,100.0,1158.68030,35.62954,100,99.91608,100,-1.88294,61.73404,62.24976,209.86026,919.62439,1496.80249,2552.18335,303.87860,999.20648,6.76624,10.85052,398.62015,43.93403,40.87219,12,11.78894,1.49613,0.27557,540833,540833,0,0,1,1,1,35.19287,36.15417,28.02649,0,1,54092.00000,0,726.13525,763.19324,0,1,2880,776.00,778.24396,1,12.01439,10,10,10,10,-2.97190,-1.49518,3.31728,5.86694,-25.00000,360.00000,13232.00000,70,9265.47656,20,-23.00000,0.00000,65.18375,0.05423,0,291.41699,-0.00072,16494.49609,263.42545,305.96576,0,10053.00000,27582.00000,,,,
-47,0.10145,1.28167,406.14667,1119.68103,33.4603,54.2433,819.21997,35.66731,100,99.91608,0,33.25806,61.55833,62.71515,210.80017,914.84070,1980.82983,2829.75854,303.30737,1104.50671,2.12251,10.83586,398.51471,39.29446,70.01648,12,11.78131,2.39578,0.58304,540833,540833,0,0,1,1,1,35.63538,36.49339,28.03,0,1,54099.00000,0,695.28198,763.19324,0,1,2880,771.00,775.98181,1,12.02581,10,10,10,10,-3.50592,-1.57143,3.63777,5.93543,-25.00000,456.00000,13026.60254,70,9212.50977,20,-23.00000,-0.00022,75.3038,74.70703,0,287.83755,-0.00239,15990.44629,253.60101,299.93430,0,10053.00000,27570.00000,,,,
-48,0.10121,1.27741,397.63785,1105.2218,31.91024,100.0,2488.47559,37.30117,100,0.29907,0,-1.88294,61.75818,62.36419,208.95299,916.14526,1973.19409,2830.17969,303.28848,1004.36145,6.45537,10.85052,396.37100,97.1386,74.70856,12,12.01782,1.55123,0.27557,540833,540833,0,0,1,1,1,35.54382,36.09313,28.0299,0,1,54100.00000,0,708.61206,763.19324,0,1,2880,770.00,770.68628,1,12.01150,10,10,10,10,-2.99662,-1.46289,3.62901,5.92515,-25.00000,490.55493,12667.67969,70,9097.83691,20,-23.00000,-0.00166,-0.00723,74.56238,0,289.82782,-0.00181,15859.49512,248.18336,302.46338,0,10053.00000,27590.00000,,,,
-49,0.10145,1.26806,405.06735,1001.99799,31.91024,100.0,2827.37231,35.33009,100,99.91608,100,97.18475,61.35390,62.01324,209.56647,914.54517,1975.05640,2830.32007,302.64352,995.7276,6.54094,10.01892,397.08746,39.7328,37.65258,12,11.78894,1.56008,0.27557,540833,540833,0,0,1,1,1,35.63538,36.32202,28.02561,0,1,54101.00000,0,698.49853,763.19324,0,1,2880,770.00,774.62323,1,12.01733,10,10,10,10,-2.81529,-1.39700,3.50691,5.91155,-25.00000,547.53809,12726.51172,70,8377.85645,20,-23.00000,-0.00166,75.33276,25.33637,0,284.18997,-0.00202,15970.37598,262.01923,298.13467,0,10053.00000,27577.00000,,,,
-50,0.10087,1.25533,397.63785,1105.2218,32.0,7.597,1075.80322,37.1796,100,99.91608,100,97.2229,61.51580,62.00561,204.88736,904.52429,1963.86816,2827.87866,301.77631,1004.36145,6.49709,9.41706,396.52490,44.00985,47.02148,12,11.78131,1.57682,0.27557,540833,540833,0,0,1,1,1,35.72693,36.36779,28.0273,0,1,54093.00000,0,708.91724,763.19324,0,1,2880,776.00,777.31476,1,12.03194,10,10,10,10,-2.80881,-1.42575,3.44030,5.77602,-22.00000,640.08392,12255.24707,70,8486.89844,20,-23.00000,0.00000,-0.00723,10.32626,0,282.46143,-0.00087,16034.41797,282.32074,294.89310,0,10053.00000,27577.00000,,,,
-51,0.10087,1.23931,405.06735,993.95294,31.91024,78.62817,2834.95264,35.952,100,99.91608,0,27.33764,61.34163,62.24213,196.87213,911.79657,1552.13269,2645.53296,301.17880,993.55328,6.58026,9.06096,397.03552,89.47529,99.58313,12,11.78894,1.51437,0.27557,540833,540833,0,0,1,1,1,35.72693,36.52039,28.02645,0,1,54095.00000,0,722.61963,763.19324,0,1,2880,776.00,776.67773,1,12.04093,10,10,10,10,-3.11034,-1.68267,3.34228,5.83297,-25.00000,668.20514,12127.41699,70,8289.16602,20,-23.00000,-0.00166,-0.00723,56.27893,0,264.32175,-0.00015,15599.23242,291.37933,291.42148,0,10082.00000,27582.00000,,,,
-52,0.10121,1.22382,405.06735,1001.99799,33.4603,0.0,2832.84692,36.91792,100,99.91608,100,-1.88294,61.23043,62.12768,200.30977,895.70630,1970.52002,2835.93530,301.17880,1108.01477,6.74134,9.44445,395.44897,92.94914,46.90704,12,11.78894,1.46483,0.27557,540833,540833,0,0,1,1,1,35.63538,36.90185,28.02558,0,1,54110.00000,0,712.20703,763.19324,0,1,2880,749.00,767.10095,1,12.03024,10,10,10,10,-2.76762,-1.61537,3.35917,5.79801,-22.00000,683.67853,11408.00000,70,10832.16797,20,-23.00000,-0.00166,64.12762,0.07236,0,249.51741,-0.00202,15284.67578,266.33972,291.98837,0,10082.00000,27590.00000,,,,
-53,0.03051,1.22017,406.14667,1001.99799,33.4603,100.0,873.12457,37.59262,100,0.29907,0,-1.88294,60.97107,62.12768,170.55510,868.35638,1962.50928,2204.59644,301.73776,993.55328,7.15616,8.74569,396.72882,43.85727,44.88525,12,12.01019,1.45662,0.56187,540833,540833,0,0,1,1,1,35.69641,37.72582,28.02558,0,1,54083.00000,0,701.3794,763.19324,0,1,2880,779.00,779.68890,1,12.03488,10,10,10,10,-2.92692,-1.46659,3.39802,5.84968,-25.00000,815.26611,9344.00000,70,10232.30762,20,-23.00000,-0.00166,68.55469,68.95612,0,254.78079,0.00000,15442.90527,293.98706,281.33606,50,10053.00000,27590.00000,,,,
-54,0.03051,1.15474,406.14667,1105.2218,31.91024,100.0,2839.58521,37.33207,100,99.91608,0,-1.78375,60.68800,61.05957,173.03467,886.98492,6.52314,719.64874,300.63626,1105.73254,7.17574,7.63855,394.99799,37.7001,41.92505,12,11.78894,1.45324,0.27557,540833,540833,0,0,1,1,1,35.69641,37.49695,28.03078,0,1,54081.00000,0,690.49683,763.19324,0,1,2880,777.00,780.25623,1,12.02388,10,10,10,10,-3.30787,-1.58894,3.16545,5.95040,-22.00000,840.84015,9344.00000,70,12135.76758,20,-18.00000,-0.00022,70.68143,2.02548,0,231.13788,0.00109,14208.57910,292.55859,257.03876,0,10082.00000,27605.00000,,,,
-55,0.10145,1.18206,397.63785,993.95294,33.4603,97.42156,813.23224,37.01405,100,0.29907,100,97.18475,60.29181,61.52496,174.56052,843.33459,1140.34338,530.19830,301.56027,1121.09009,7.33475,7.64022,394.63303,91.88213,99.24077,12,11.78131,1.43832,0.27557,540833,540833,0,0,1,1,1,35.78796,37.26807,28.02645,0,1,54033.71484,0,722.7478,763.19324,0,1,2880,784.00,784.43231,1,12.03785,10,10,10,10,-3.67731,-1.72142,3.13752,5.83875,-22.00000,989.20746,9344.00000,70,9567.95020,20,-18.00000,-0.00022,63.46933,60.47449,0,261.25253,0.00094,14824.33691,288.93942,280.16409,50,10053.00000,27590.00000,,,,
-56,0.03051,1.11386,397.63785,1105.2218,31.91024,100.0,1209.04419,35.76306,100,0.29907,100,-1.83716,60.74686,61.53259,176.83421,831.37958,1968.42200,2833.31006,300.63626,1107.05811,7.60642,8.24895,395.56461,47.36208,95.43762,12,11.78894,1.43067,0.27557,540833,540833,0,0,1,1,1,35.72693,37.81738,28.03081,0,1,54096.00000,0,723.12622,763.19324,0,1,2880,777.00,776.42517,1,12.02259,10,10,10,10,-3.47277,-1.69333,3.10409,5.87370,-20.00000,1043.76941,9344.00000,70,9740.07715,20,-18.00000,0.00000,65.54544,0.34363,0,269.11758,-0.00181,15046.58887,290.34946,277.83380,0,10082.00000,27590.00000,,,,
-57,0.10121,1.09325,406.14667,993.95294,33.4603,100.0,2811.27539,37.06123,100,99.91608,0,97.23052,60.84172,61.17401,172.84215,834.04529,1968.42200,2828.63550,300.24091,1002.62195,7.67702,7.64618,394.98999,43.78875,31.83899,12,12.01019,1.42075,0.58304,540833,540833,0,0,1,1,1,35.54382,37.80212,28.0273,0,1,54101.00000,0,718.70117,763.19324,0,1,2880,777.00,778.15942,1,12.02902,10,10,10,10,-3.43541,-1.58447,3.07001,5.89754,-22.00000,1138.60535,9344.00000,70,10999.97461,20,-18.00000,-0.00166,-0.00723,45.89844,10,270.20984,-0.00145,14346.60742,296.90155,269.37039,0,10053.00000,27605.00000,,,,
-58,0.10121,1.04795,397.63785,993.95294,33.4603,100.0,33.96383,37.36881,100,99.91608,100,-1.87149,60.56711,61.29608,175.03502,845.08722,1960.22021,1496.71838,299.87332,1103.33739,7.69417,0.28381,394.28021,36.51355,50.34027,12,12.01782,1.41312,0.27557,540833,540833,0,0,1,1,1,35.72693,37.84790,28.02733,0,1,54077.00000,0,701.67847,763.19324,0,1,2880,781.00,783.26367,1,12.01473,10,10,10,10,-3.82215,-1.56760,3.29795,5.89490,-22.00000,1360.07104,7600.00000,70,10759.05469,20,-18.00000,-0.00022,-0.00723,80.40363,0,267.17145,-0.00015,14975.22363,296.57101,265.33987,0,10053.00000,27590.00000,,,,
-59,0.10087,1.08846,397.63785,1105.2218,31.91024,100.0,233.52388,37.78984,100,0.29907,0,-1.87531,61.06521,61.29608,173.98833,818.91986,1981.01025,2835.79492,299.87332,992.24847,7.57529,7.64618,393.20236,81.93488,43.16101,12,11.78894,1.40854,0.27557,540833,540833,0,0,1,1,1,35.72693,37.95470,28.02736,0,1,54104.00000,0,718.19458,763.19324,0,1,2880,778.00,777.67987,1,12.01315,10,10,10,10,-3.83135,-1.63992,3.33797,6.00582,-22.00000,1397.92627,7600.00000,70,11980.55664,20,-18.00000,-0.00166,70.04486,62.35535,0,276.29062,-0.00253,14252.87402,301.93903,274.19247,0,10053.00000,27605.00000,,,,
-60,0.10121,1.06502,405.06735,993.95294,33.6555,100.0,31.97761,37.47207,100,99.91608,100,-1.88294,60.77161,61.29608,169.21996,825.61456,1968.80322,2822.73950,299.84372,1105.4635,7.89701,7.28760,392.95319,91.07033,39.54468,12,11.78894,1.40472,0.27557,540833,540833,0,0,1,1,1,35.49804,38.03101,28.02473,0,1,54085.00000,0,722.84546,763.19324,0,1,2880,783.00,783.40887,1,12.00698,10,10,10,10,-3.39295,-1.36216,3.22887,5.94845,-20.00000,1421.14807,7600.00000,70,11758.07031,20,-18.00000,-0.00022,-0.00723,4.64774,0,277.43332,-0.00065,14486.50488,301.25479,270.14859,0,10053.00000,27605.00000,,,,
-61,0.03051,1.12131,405.06735,1105.2218,32.0,100.0,34.95676,37.57507,100,99.91608,100,-1.81427,60.47824,61.28845,165.69179,837.53900,1953.92493,584.04083,299.49182,1107.05811,7.77120,0.28381,394.47018,91.72776,39.78882,12,11.78894,1.40167,0.58304,540833,540833,0,0,1,1,1,35.78796,37.95470,28.02645,0,1,54065.00000,0,704.44946,763.19324,0,1,2880,785.00,785.35040,1,11.99967,10,10,10,10,-3.76568,-1.38752,3.27393,5.95291,-20.00000,2804.07129,7600.00000,70,11293.74609,20,-17.00000,-0.00166,74.60214,1.51907,0,262.71368,0.00043,14854.08496,301.52390,272.84451,0,10053.00000,27605.00000,,,,
-62,0.10145,1.10390,406.14667,993.95294,33.4603,100.0,2816.92627,35.78938,100,0.29907,100,-1.87531,60.36623,62.00561,171.51936,828.73535,99.98140,155.12090,299.30112,1101.31775,8.09967,0.28381,389.47897,46.74321,51.77459,12,12.01019,1.39786,0.27557,540833,540833,0,0,1,1,1,35.87951,37.89367,28.02561,0,1,54064.68359,0,719.4519,763.19324,0,1,2880,784.00,784.93121,1,11.96998,10,10,10,10,-3.53008,-1.35684,3.42183,6.00347,-20.00000,3660.33423,5584.00000,70,12777.20898,20,-17.00000,-0.00166,69.42996,78.83032,0,283.73761,0.00080,14957.55664,301.74930,276.72781,0,10053.00000,27627.00000,,,,
-63,0.10121,1.16801,397.63785,1105.2218,33.4603,100.0,1494.27454,35.8799,100,99.91608,0,-1.87531,60.27368,61.29608,168.26630,823.54718,788.54089,973.02594,299.30112,1001.31744,8.13664,7.40204,391.15881,86.81759,37.29401,12,11.78894,1.39633,0.58304,540833,540833,0,0,1,1,1,35.87951,37.93946,28.03166,0,1,54080.00000,0,712.53662,763.19324,0,1,2880,784.00,784.86273,1,12.00406,10,10,10,10,-3.31440,-1.32332,3.34838,5.96264,-20.00000,5728.00000,5584.00000,70,12486.00000,20,-17.00000,-0.00022,76.2659,73.09753,0,289.23215,0.00007,15130.66504,305.08350,283.30649,0,10053.00000,27627.00000,,,,
-64,0.10121,1.19735,405.06735,993.95294,31.91024,100.0,36.94299,37.48554,100,99.91608,0,-1.88294,60.21412,61.05957,158.83879,816.74060,1961.55554,1514.32288,299.30112,1108.33362,8.33071,7.29487,392.15591,37.04223,92.12646,12,12.01782,1.39481,0.58304,540833,540833,0,0,1,1,1,35.87951,37.96997,28.02558,0,1,54089.00000,0,712.44507,763.19324,0,1,2880,784.00,784.99182,1,12.00509,10,10,10,10,-3.34971,-1.31337,3.51968,6.05595,-20.00000,5178.12305,5584.00000,70,13700.97070,20,-17.00000,-0.00166,64.81482,11.97195,10,292.25305,-0.00036,15723.92480,307.77600,284.86221,0,10053.00000,27627.00000,,,,
-65,0.10087,1.20940,405.06735,993.95294,33.6555,100.0,2831.16211,36.00377,100,99.91608,0,-1.88294,60.22987,60.93750,160.02939,798.72278,1963.46265,2836.21582,297.39380,1133.20862,8.23195,0.28381,383.73773,86.18462,35.0357,12,12.01782,1.39252,0.27557,540833,540833,0,0,1,1,1,35.92529,38.73291,28.02909,0,1,54125.00000,0,708.17871,763.19324,0,1,2880,776.00,776.21368,1,12.00156,10,10,10,10,-2.96540,-1.32009,3.68367,6.06840,-20.00000,6936.00000,-160.00000,70,14217.42383,20,-17.00000,-0.00166,-0.00723,0.07236,0,297.18051,-0.00260,15738.48926,306.72937,296.94354,0,10053.00000,27627.00000,,,,
-66,0.10145,1.22172,397.63785,1119.68103,33.4603,12.41793,2832.00439,35.09091,100,99.91608,0,97.20763,59.99801,60.58655,162.54567,812.61676,1009.11310,2822.31836,297.20303,991.59631,8.29782,0.28381,382.67667,64.41595,93.43109,12,11.78894,1.39252,0.27557,540833,540833,0,0,1,1,1,35.97107,38.32037,28.02736,0,1,54114.00000,0,722.43042,763.19324,0,1,2880,780.00,780.65656,1,12.00753,10,10,10,10,-2.97746,-1.30004,3.65480,6.06596,-20.00000,7803.67090,-160.00000,70,14198.73242,20,-4.42004,-0.00166,11.32812,65.15845,0,298.20667,-0.00101,15882.35547,309.42859,296.16556,0,10053.00000,27627.00000,,,,
-67,0.10145,1.24379,406.14667,993.95294,31.91024,100.0,30.98430,35.84328,100,0.29907,100,23.85101,59.92034,60.70861,153.59677,721.36719,1958.88525,35.95007,297.14868,994.85779,8.42001,0.28381,377.70782,97.2385,99.73756,12,11.78131,1.39023,0.58304,540833,540833,0,0,1,1,1,36.23047,39.87176,28.0273,0,1,54072.00000,0,708.34351,763.19324,0,1,2880,786.00,787.67657,1,12.03084,10,10,10,10,-2.48299,-1.26476,3.47626,6.01472,80.00000,9808.00000,-160.00000,70,14300.98340,20,247.68649,0.00000,75.3038,66.94879,0,300.43002,0.00029,16138.56055,312.63715,298.90555,50,10053.00000,27627.00000,,,,
-68,0.10087,1.25107,406.14667,1001.99799,33.4603,81.60265,32.97053,37.70184,100,0.29907,0,-1.77612,59.86125,60.69543,159.57159,783.56702,30.57996,599.27112,298.72894,993.11829,9.02607,0.28381,380.68539,32.28102,41.08581,12,12.01782,1.38794,0.58304,540833,540833,0,0,1,1,1,36.23047,40.09223,28.02561,0,1,54072.00000,0,694.89136,763.19324,0,1,2880,787.00,787.19446,1,12.02433,10,10,10,10,-2.90322,-1.28893,3.64034,6.07425,662.36230,10328.00000,-160.00000,70,14442.68359,20,306.30722,0.00000,77.92245,50.49188,0,306.67172,0.00051,16552.26172,312.28922,301.17038,0,10053.00000,27627.00000,,,,
-69,0.10087,1.26275,397.63785,993.95294,31.91024,100.0,2645.80933,35.53151,100,99.91608,0,-1.87531,59.93542,60.35766,149.53186,790.94604,1931.74487,1148.61121,296.21991,1000.44769,9.43532,7.29523,381.58884,43.28182,44.29016,12,11.78894,1.38641,0.27557,540833,540833,0,0,1,1,1,36.29150,38.85618,28.02649,0,1,54118.00000,0,719.54346,763.19324,0,1,2880,781.00,781.55823,1,12.01543,10,10,10,10,-2.65800,-1.19567,3.71782,6.11199,-20.00000,10040.33008,-160.00000,70,14419.92383,20,55.99398,-0.00166,43.01215,0.23508,0,306.16962,-0.00087,16560.47461,314.45270,304.54150,0,10053.00000,27627.00000,,,,
-70,0.10087,1.26143,405.06735,1001.99799,31.91024,100.0,2816.37817,37.38865,100,0.29907,100,-1.87531,59.63860,60.70861,155.97198,806.02856,157.67061,28.99807,296.60162,994.42285,9.68010,0.28381,378.65750,40.95717,99.39769,12,11.78131,1.38489,0.27557,540833,540833,0,0,1,1,1,36.68592,39.37370,28.02733,0,1,54080.00000,0,702.32544,763.19324,0,1,2880,786.00,787.14435,1,11.97539,10,10,10,10,-3.36313,-1.25364,3.83040,6.19001,-20.00000,10328.00000,-160.00000,70,14691.92188,20,380.36694,-0.00166,4.29688,0.07236,0,312.86313,0.00152,16603.53711,314.66455,304.82642,0,10053.00000,27627.00000,,,,
-71,0.10145,1.27478,406.14667,1105.2218,33.4603,100.0,2829.89893,37.24433,100,99.91608,100,-1.84479,59.80042,60.10589,146.52441,804.76758,6.33237,2767.12793,295.04935,1103.55005,9.92584,0.28381,382.39291,42.47231,48.21167,12,12.01019,1.37955,0.27557,540833,540833,0,0,1,1,1,36.50513,39.03808,28.03169,0,1,54112.00000,0,726.92261,763.19324,0,1,2880,784.00,783.66693,1,11.99013,10,10,10,10,-2.81807,-1.12437,3.91797,6.19437,162.79311,10771.24316,-160.00000,70,14805.66992,20,533.29541,-0.00022,76.92419,69.01044,0,307.98557,-0.00007,16793.75195,315.58759,309.15518,0,10053.00000,27627.00000,,,,
-72,0.10087,1.28997,397.63785,1001.99799,31.91024,27.09114,162.21581,35.69401,100,0.29907,0,97.21527,59.66623,60.35766,86.58415,690.57117,6.33237,36.94299,296.44006,1002.62195,10.16839,7.27997,372.84479,100.0,34.44061,12,11.78894,1.37573,0.58304,540833,540833,0,0,1,1,1,36.76452,40.35055,28.02473,0,1,54082.00000,0,711.68213,763.19324,0,1,2880,788.00,788.14563,1,12.01388,10,10,10,10,-2.53194,-1.04300,3.82342,6.18007,2497.87378,11928.00000,-160.00000,70,14776.06348,20,904.79968,0.00000,62.89062,75.84637,0,320.95023,0.00130,16884.72656,317.14838,310.46768,0,10052.00000,27627.00000,,,,
-73,0.10145,1.29614,397.63785,1115.11975,31.91024,1.52835,2825.96826,36.00529,100,99.91608,0,-1.87531,59.48196,59.98383,135.22092,718.21844,6.52314,2173.25659,295.08002,994.85779,11.37108,0.28381,375.67474,89.04186,44.30542,12,12.01782,1.36658,0.27557,540833,540833,0,0,1,1,1,36.76452,38.70240,28.02389,0,1,54110.00000,0,726.15967,763.19324,0,1,2880,786.00,785.72644,1,12.01698,10,10,10,10,-2.72107,-0.95282,4.04709,6.22720,2642.01587,12629.33398,-160.00000,70,14994.37402,20,1254.89331,0.00000,64.15653,2.64032,0,316.51956,-0.00015,16923.09375,318.87543,313.55634,0,10053.00000,27627.00000,,,,
-74,0.10121,1.30822,405.06735,993.95294,33.4603,100.0,35.95007,38.19915,100,0.29907,100,97.23052,59.32183,59.99908,132.85176,750.64355,1961.74609,377.27237,295.66806,994.85779,11.14878,7.18079,374.92581,34.31394,97.68066,12,11.78894,1.36581,0.27557,540833,540833,0,0,1,1,1,36.81030,38.73291,28.02818,0,1,54107.00000,0,708.34961,763.19324,0,1,2880,787.00,787.51929,1,12.00983,10,10,10,10,-2.20173,-0.78900,3.89219,6.21898,1289.34741,11928.00000,-160.00000,70,14971.26367,20,770.03284,-0.00022,65.59607,6.32959,0,321.65430,-0.00015,16971.99805,319.58841,313.19586,0,10052.00000,27627.00000,,,,
-75,0.10145,1.31177,406.14667,1105.2218,33.4603,20.84746,2823.44141,35.87597,100,0.29907,0,-1.44806,58.77622,60.00673,128.61400,735.21307,67.94364,35.95007,294.34137,994.85779,11.59719,7.64618,372.34634,47.90904,96.35315,12,12.01782,1.36505,0.27557,540833,540833,0,0,1,1,1,36.76452,38.57105,28.03253,0,1,54107.00000,0,715.78369,763.19324,0,1,2880,787.00,786.93219,1,11.98265,10,10,10,10,-2.56917,-0.73013,4.45898,6.32336,2707.89917,12285.64746,-160.00000,70,14912.76562,20,1660.69482,-0.00022,-0.00723,0.05423,0,325.58109,0.00043,17063.31250,320.49380,314.96771,0,10052.00000,27627.00000,,,,
-76,0.10121,1.31845,393.16226,1001.99799,33.4603,9.55956,2369.46265,37.37759,100,99.91608,0,-1.87531,59.15186,59.53325,110.14378,710.10370,5.76019,158.10043,294.13126,1115.29944,12.17294,0.28381,374.39920,37.82748,85.2829,12,12.01019,1.36505,0.27557,540833,540833,0,0,1,1,1,36.52039,38.22937,28.03081,0,1,54095.00000,0,709.76562,763.19324,0,1,2880,789.00,788.81195,1,11.96278,10,10,10,10,-2.82123,-0.82014,4.37259,6.52041,4463.92920,12840.00000,-160.00000,70,15305.13965,20,3387.56372,0.00000,66.37732,0.09042,0,326.31158,0.00159,17149.05664,321.72583,316.15869,0,10052.00000,27627.00000,,,,
-77,0.10087,1.32418,397.63785,1105.2218,33.6555,100.0,731.98010,37.08118,100,99.91608,100,-1.87531,58.03649,59.29198,107.40035,780.80414,6.14166,34.95676,293.74966,995.2926,12.43907,0.28381,379.21179,80.51949,41.68091,12,12.01782,1.36429,0.20233,540833,540833,0,0,1,1,1,36.52039,38.01574,28.0299,0,1,54095.00000,0,712.03613,763.19324,0,1,2880,789.00,789.65448,1,11.96482,10,10,10,10,-2.74420,-0.67777,4.43230,6.60282,3616.16504,12840.00000,-160.00000,70,15402.84473,20,3288.92041,0.00000,-0.00723,62.42761,0,328.62241,0.00152,17186.92383,323.19882,317.59048,0,10052.00000,27627.00000,,,,
-78,0.10087,1.33160,405.06735,1105.2218,33.6555,100.0,32.97053,35.95543,100,99.91608,0,-1.81427,56.63080,57.26529,121.13436,731.32379,269.77267,31.97760,293.36383,994.85779,12.35625,7.64618,383.07913,90.1796,99.55304,12,11.78894,1.36353,0.27557,540833,540833,0,0,1,1,1,36.38305,37.87842,28.0274,0,1,54096.00000,0,715.35645,763.19324,0,1,2880,790.00,790.44604,1,11.96665,10,10,10,10,-2.82412,-0.68289,4.49940,6.66932,2906.94897,13514.92871,-176.00000,70,15432.87988,20,3152.59644,-0.00022,60.51794,59.44373,0,331.92700,0.00094,17198.77148,323.88800,318.98260,50,10052.00000,27627.00000,,,,
-79,0.10121,1.33595,397.63785,1001.99799,33.6555,0.0,34.95676,37.19474,100,0.29907,100,-1.88294,56.90918,58.35876,169.41066,768.57440,1973.95312,2827.65283,291.86249,995.7276,12.53064,9.38408,383.22986,95.30971,41.68091,12,11.78894,1.36353,0.20233,540833,540833,0,0,1,1,1,36.41138,37.86315,28.0273,0,1,54129.00000,0,708.11157,763.19324,0,1,2880,786.00,786.20142,1,11.95422,10,10,10,10,-2.86179,-0.65336,4.82002,6.79164,3173.38965,12840.00000,-224.00000,70,15539.12891,20,1879.44055,-0.00166,64.19995,20.52588,0,332.90515,-0.00181,17244.00391,324.10278,320.74371,0,10052.00000,27627.00000,,,,
-80,0.03051,1.34147,405.06735,1001.99799,33.6555,100.0,2574.25586,36.80767,100,0.29907,100,-1.88294,56.74512,57.16857,158.00371,813.07666,5.98286,31.97760,292.43466,992.24847,12.86204,8.59058,390.86523,36.75406,41.32995,12,11.78894,1.36276,0.20233,540833,540833,0,0,1,1,1,36.29150,37.58850,28.02733,0,1,54099.00000,0,714.83765,763.19324,0,1,2880,790.00,791.25586,1,11.94065,10,10,10,10,-3.64910,-1.09338,4.63793,6.88636,4029.03955,13656.00000,-288.00000,70,15730.15723,20,3602.08398,-0.00022,-0.00723,0.30743,0,336.08551,0.00202,17331.10742,326.26666,320.47986,0,10052.00000,27627.00000,,,,
-81,0.10145,1.34603,406.14667,993.95294,33.6555,100.0,1596.48938,35.47161,100,99.91608,0,-1.81427,56.40707,57.14954,165.54407,809.63129,1967.27759,2069.95410,291.64575,1120.771,12.80906,7.64618,395.29755,46.9472,90.12756,12,11.78894,1.36276,0.20233,540833,540833,0,0,1,1,1,36.18469,36.90185,28.02649,0,1,54135.00000,0,702.09351,763.19324,0,1,2880,786.00,786.90894,1,11.94742,10,10,10,10,-2.81153,-0.35284,4.64445,6.82758,2760.63770,13728.00000,-288.00000,70,15716.45020,20,3056.47681,-0.00166,68.7934,0.07236,0,336.86435,-0.00109,17395.75391,326.70035,322.93539,0,10052.00000,27627.00000,,,,
-82,0.10121,1.35053,397.63785,1105.2218,31.91024,100.0,857.99915,37.07928,100,0.29907,0,-1.87531,56.22357,56.70318,161.62875,805.25909,1958.12207,365.48465,292.02805,1001.8158,13.22239,8.82366,396.60699,36.62286,99.15975,12,11.78894,1.36200,0.20233,540833,540833,0,0,1,1,1,36.09313,36.15417,28.02649,0,1,54117.34375,0,697.32666,763.19324,0,1,2880,789.00,790.12457,1,11.96091,10,10,10,10,-2.95765,-1.04462,4.30668,6.61557,2942.12598,13548.44434,-288.00000,70,15865.10742,20,3316.75854,-0.00166,76.07059,0.54251,0,340.28156,0.00015,17444.84961,329.32324,323.35547,0,10052.00000,27627.00000,,,,
-83,0.10087,1.35326,405.06735,993.95294,33.6555,100.0,2828.77588,36.93852,0,99.91608,0,-1.87531,55.82771,55.54277,164.80417,819.31421,42.95086,2819.36792,277.46222,988.76959,13.32865,9.66768,398.16318,46.50142,99.28939,12,12.01019,1.36124,0.20233,540833,540833,0,0,1,1,1,36.00158,36.06262,28.02645,0,1,54140.00000,0,715.8081,763.19324,0,1,2880,787.00,787.06934,1,11.93022,10,10,10,10,-3.08351,-0.95889,4.61736,6.80696,3928.83179,13752.00000,-288.00000,70,15973.76367,20,3490.81958,-0.00166,80.70023,19.07916,0,338.76639,-0.00029,17537.64844,330.37814,324.14551,0,10052.00000,27627.00000,,,,
-84,0.10145,1.35699,397.63785,1001.99799,31.91024,24.51614,31.97761,37.05563,100,0.29907,100,-1.87531,54.38342,56.17626,170.83980,826.56104,1960.41113,2122.61011,276.83344,1121.09009,13.48971,10.25687,397.19067,42.98953,96.49811,12,11.78894,1.36124,0.20233,540833,540833,0,0,1,1,1,35.72693,36.01685,28.02905,0,1,54124.00000,0,705.87769,763.19324,0,1,2880,788.00,788.86176,1,11.92096,10,10,10,10,-3.32760,-0.87006,4.50880,6.69058,4276.52637,13744.00000,-288.00000,70,16080.44238,20,3199.83643,-0.00166,-0.00723,48.08667,0,346.07883,-0.00022,17488.86719,328.91919,325.06812,50,10052.00000,27627.00000,,,,
-85,0.10145,1.35960,406.14667,993.95294,31.91024,100.0,30.98430,36.11145,100,99.91608,0,97.23052,53.48425,54.25958,170.36440,827.43085,1969.75696,2825.76270,266.44858,1007.84021,13.68880,10.60632,398.82462,37.14736,47.75391,12,11.78894,1.36047,0.20233,540833,540833,0,0,1,1,1,35.58960,35.97107,28.03253,0,1,54123.00000,0,698.27881,763.19324,0,1,2880,789.00,789.56403,1,11.90728,10,10,10,10,-3.37979,-0.58128,4.52414,6.77628,4002.48022,13712.00000,-288.00000,70,16249.22949,20,3235.47900,-0.00166,-0.00723,20.79718,0,349.28513,-0.00058,17572.99023,331.68298,325.69937,0,10052.00000,27605.00000,,,,
-86,0.10121,1.36228,397.63785,993.95294,31.91024,8.62958,2350.65967,37.88711,0,0.29907,0,-1.87912,53.13693,53.27759,166.77696,831.34473,6.42538,39.04029,264.49951,994.85779,13.91558,10.01892,399.05225,92.18491,47.01385,12,11.78131,1.36047,0.20233,540833,540833,0,0,1,1,1,35.63538,35.89477,28.02993,0,1,54100.00000,0,698.19946,763.19324,0,1,2880,793.00,792.84570,1,11.88054,10,10,10,10,-3.67261,-0.75467,4.52774,6.77067,4975.94434,13752.00000,-288.00000,70,16379.91602,20,3583.73047,-0.00022,77.48843,71.8316,0,348.35464,0.00202,17607.17188,331.16101,325.95981,0,10052.00000,27605.00000,,,,
-87,0.10145,1.36735,397.63785,1001.99799,33.4603,100.0,532.26190,37.51251,100,99.91608,100,-1.87531,52.64830,52.68092,176.27713,841.75610,1963.65356,2738.03442,256.84561,1003.4917,13.90184,11.67450,399.84445,41.71416,41.68091,12,11.78894,1.35971,0.20233,540833,540833,0,0,1,1,1,35.49804,35.86426,28.03074,0,1,54130.00000,0,701.93481,763.19324,0,1,2880,788.00,788.08820,1,11.89624,10,10,10,10,-3.45705,-0.70537,4.37550,6.57033,4829.78662,12840.00000,-288.00000,70,16405.61914,20,3341.98047,-0.00166,-0.00723,66.44244,0,344.88089,-0.00058,17654.01758,331.81668,326.96692,0,10052.00000,27605.00000,,,,
-88,0.03051,1.36894,397.63785,993.95294,33.4603,61.83892,2301.39136,37.20364,100,0.29907,100,-1.87531,52.15918,53.27759,204.31517,845.32812,47.29852,1349.94678,261.72488,994.42285,14.22143,12.26196,402.91394,47.78098,44.88525,12,11.78894,1.35971,0.20233,540833,540833,0,0,1,1,1,35.54382,35.72552,28.02909,0,1,54120.00000,0,719.64111,763.19324,0,1,2880,790.00,789.51270,1,11.88084,10,10,10,10,-3.94047,-1.14736,4.39393,6.58083,4933.44092,12840.00000,-288.00000,70,16429.43945,20,3414.62671,-0.00166,74.3779,25.95129,0,355.53418,0.00058,17723.64648,333.16211,327.81976,0,10052.00000,27605.00000,,,,
-89,0.10121,1.37262,406.14667,1115.11975,33.4603,100.0,2819.36011,35.71652,100,99.91608,0,97.19238,51.82811,52.45361,198.05734,846.60931,1976.63867,2833.68921,254.27925,1003.92651,13.83198,12.28485,404.60083,37.8604,50.10376,12,11.78894,1.35895,0.20233,540833,540833,0,0,1,1,1,35.28442,35.75745,28.0247,0,1,54154.13672,0,698.40088,763.19324,0,1,2880,788.00,787.16901,1,11.87772,10,10,10,10,-4.03971,-0.82598,4.69969,6.83667,2684.92871,12840.00000,-288.00000,70,16611.70703,20,1743.74133,-0.01237,59.6716,66.87646,0,352.35413,-0.00152,17714.33008,335.04077,327.58411,50,10052.00000,27627.00000,,,,
-90,0.10121,1.37499,405.06735,993.95294,31.91024,100.0,790.46997,35.96726,100,0.29907,100,-1.87531,52.02040,52.69012,201.55849,851.79926,1788.87903,2826.24902,251.39098,994.85779,14.21635,12.75024,404.54968,40.33484,49.15008,12,12.01782,1.35818,0.20233,540833,540833,0,0,1,1,1,35.37598,35.68115,28.03081,0,1,54128.00000,0,713.92822,763.19324,0,1,2880,788.00,787.73151,1,11.85336,10,10,10,10,-3.80639,-1.05155,4.60206,6.59667,4499.74463,12840.00000,-288.00000,70,16688.13086,20,3279.97046,-0.00166,63.62848,63.27765,0,353.62363,-0.00015,17750.68164,334.06885,329.64603,0,10052.00000,27605.00000,,,,
-91,0.10145,1.37851,405.06735,993.95294,31.91024,100.0,1282.52429,37.4057,100,99.91608,0,-1.81427,52.04695,52.21710,199.35603,839.20404,1966.70508,2833.10718,252.79443,1104.50671,14.31892,12.75024,405.36758,42.76206,42.52014,12,12.01782,1.35742,0.20233,540833,540833,0,0,1,1,1,35.13183,35.60485,28.02997,0,1,54140.00000,0,722.43042,763.19324,0,1,2880,788.00,787.22034,1,11.84747,10,10,10,10,-3.68328,-0.77697,4.68708,6.73659,4227.90625,12732.61035,-288.00000,70,16915.31445,20,1715.22058,-0.00166,66.99219,35.9339,0,359.07111,-0.00123,17821.12305,337.64041,330.80331,0,10052.00000,27627.00000,,,,
-92,0.03051,1.38163,406.14667,1001.99799,33.4603,100.0,476.94952,35.62954,100,99.91608,100,97.23052,51.92717,52.33491,206.43788,883.00110,1972.61816,2829.89893,252.26175,1107.05811,14.46094,12.75024,406.28769,49.02999,41.22314,12,11.78894,1.35727,0.17029,540833,540833,0,0,1,1,1,35.19287,35.54455,28.03166,0,1,54139.00000,0,718.4021,763.19324,0,1,2880,788.00,788.06873,1,11.88579,10,10,10,10,-3.81239,-1.03750,4.20272,6.45096,3945.07275,12840.00000,-288.00000,70,16860.59766,20,3258.39380,-0.00166,-0.00723,0.05423,0,359.49948,-0.00101,17876.35352,340.17914,331.32288,0,10051.00000,27605.00000,,,,
-93,0.03051,1.38256,405.06735,993.95294,31.91024,100.0,31.97761,37.27562,100,0.29907,0,-1.88294,51.62010,52.31477,200.50046,850.13605,6.90462,340.45554,250.59665,991.81366,14.02384,12.26959,405.41867,89.13902,40.05584,12,11.78894,1.35590,0.20233,540833,540833,0,0,1,1,1,35.58960,35.62011,28.0325,0,1,54092.00000,0,718.26782,763.19324,0,1,2880,797.29,797.34167,1,11.86313,10,10,10,10,-3.89801,-1.20347,4.41284,6.47643,5253.13965,12840.00000,-288.00000,70,17145.36719,20,3505.66968,0.00000,-0.00723,36.62109,0,363.71918,0.00210,17970.15820,339.30368,331.44980,0,10027.00000,27605.00000,,,,
-94,0.10087,1.38479,406.14667,993.95294,33.6555,0.14883,336.16516,38.04771,100,0.29907,0,-1.88294,51.57122,52.09503,183.13983,901.35950,251.26004,33.96383,249.53171,1003.05676,14.42440,12.75024,406.60791,87.08466,89.99786,12,11.78894,1.35520,0.20129,540833,540833,0,0,1,1,1,35.37598,35.40649,28.03426,0,1,54096.00000,0,712.57324,763.19324,0,1,2880,794.00,828.22137,1,11.84663,10,10,10,10,-3.79510,-0.99689,4.32659,6.48311,4195.62012,12413.39062,-288.00000,70,17053.85156,20,3362.23804,-0.00166,-0.00723,71.8316,0,363.98929,0.00224,17948.47266,343.50217,331.71997,0,10027.00000,27605.00000,,,,
-95,0.10087,1.38940,406.14667,1115.11975,33.4603,0.0,2830.32007,37.00642,0,0.29907,0,-1.87149,51.50924,51.98059,189.03253,889.51917,630.29791,2825.26636,247.23051,1108.65259,14.52673,12.75024,406.69659,43.86199,87.06054,12,11.78894,1.35437,0.20233,540833,540833,0,0,1,1,1,35.49804,35.37598,28.02905,0,1,54127.00000,0,718.93921,763.19324,0,1,2880,788.00,787.56946,1,11.85252,10,10,10,10,-3.69835,-1.17817,4.16671,6.37871,4876.26953,12537.18555,-288.00000,70,17077.31445,20,1433.20801,-0.00166,66.8475,72.60925,0,363.24768,0.00000,17910.76172,336.99814,332.74371,50,10052.00000,27605.00000,,,,
-96,0.10145,1.39145,405.06735,993.95294,33.4603,3.50761,2255.54028,35.53341,100,99.91608,100,-1.88294,51.48999,52.08740,199.16533,913.97095,19.85974,299.39099,248.56566,1105.14465,14.55020,13.34534,407.12939,38.05681,38.60626,12,11.78894,1.35361,0.17029,540833,540833,0,0,1,1,1,35.37598,35.29968,28.0273,0,1,54109.00000,0,705.98755,763.19324,0,1,2880,790.00,791.50134,1,11.83410,10,10,10,10,-3.91615,-1.17433,4.21012,6.46320,3913.05811,11280.00000,-288.00000,70,17398.03516,20,1193.41260,-0.00166,72.67072,22.96729,0,366.29797,0.00159,18055.70117,341.99078,334.58463,0,10027.00000,27605.00000,,,,
-97,0.10121,1.39396,405.06735,1105.2218,33.6555,0.0,2830.79175,36.85714,100,0.29907,0,-1.88294,51.41763,52.09503,204.12440,906.13538,32.73157,311.57803,247.54868,1001.7522,14.40272,12.75024,407.20944,46.36531,96.85287,12,12.01782,1.35284,0.17029,540833,540833,0,0,1,1,1,35.58960,35.26917,28.03169,0,1,54105.00000,0,718.26172,763.19324,0,1,2880,790.00,790.78943,1,11.85102,10,10,10,10,-3.88993,-1.24508,4.60601,6.56232,4310.14795,10941.29980,-288.00000,70,17569.96680,20,3121.21558,-0.00166,-0.00723,74.86981,0,367.05429,0.00159,18160.10156,340.63153,333.55551,0,10027.00000,27605.00000,,,,
-98,0.10087,1.39625,406.14667,1001.99799,33.4603,100.0,30.98430,37.29252,100,99.91608,0,-1.82953,51.18070,51.98059,205.65031,891.03668,1957.50659,2471.80103,246.62645,1002.62195,14.24228,13.45978,407.46335,80.53619,37.05749,12,11.78894,1.35058,0.20233,540833,540833,0,0,1,1,1,35.49804,35.31494,28.02733,0,1,54095.00000,0,712.3169,763.19324,0,1,2880,793.00,792.47235,1,11.85579,10,10,10,10,-3.65537,-1.04033,4.15019,6.42935,5025.08887,11702.13574,-288.00000,70,17665.74219,20,1920.46619,0.00000,-0.00723,1.03079,0,378.70200,0.00065,18138.40625,339.12775,337.54636,50,10027.00000,27605.00000,,,,
-99,0.10145,1.40123,406.14667,1001.99799,31.91024,100.0,2833.12744,37.35699,100,99.91608,100,-1.87531,51.30811,50.79803,209.27425,900.48975,1966.51453,2832.56616,246.30991,1107.05811,14.17454,14.04724,407.82117,89.01466,77.24151,12,12.01782,1.35028,0.17029,540833,540833,0,0,1,1,1,35.54382,35.11657,28.02817,0,1,54132.00000,0,711.15112,763.19324,0,1,2880,787.00,785.96722,1,11.83677,10,10,10,10,-3.84230,-1.09538,4.58743,6.66411,2612.32715,9808.00000,-288.00000,70,18398.21875,20,755.99982,-0.00166,65.91434,79.51746,0,377.58600,-0.00080,18041.16016,344.61774,336.01541,0,10051.00000,27627.00000,,,,
-100,0.10145,1.40197,405.06735,1105.2218,33.4603,99.374,2829.75854,37.22755,100,99.91608,0,-1.87531,51.13826,51.96533,208.12964,905.70837,1897.93018,2826.35547,245.79875,991.37872,14.52140,14.03964,408.99689,36.73225,90.12756,12,12.01782,1.34979,0.17029,540833,540833,0,0,1,1,1,35.58960,35.19287,28.03162,0,1,54125.00000,0,688.28125,763.19324,0,1,2880,788.00,787.34576,1,11.84569,10,10,10,10,-3.51508,-1.16092,4.19218,6.50102,2569.89478,9515.60352,-288.00000,70,18049.39453,20,676.47552,-0.00166,76.33102,0.07236,0,373.78833,-0.00007,18103.23633,346.92508,332.93011,0,10027.00000,27605.00000,,,,
-101,0.10145,1.40727,405.06735,1001.99799,31.91024,3.76005,610.87115,35.40944,100,99.91608,100,-1.88294,51.23042,50.79803,209.14923,895.28375,1972.42725,2835.27905,245.21960,1102.59326,14.55793,14.03206,408.50043,36.18465,49.76044,12,11.78894,1.34827,0.17029,540833,540833,0,0,1,1,1,35.58960,35.22338,28.02736,0,1,54133.00000,0,712.62207,763.19324,0,1,2880,787.00,786.54773,1,11.84810,10,10,10,10,-3.38533,-0.76135,4.54942,6.51387,2878.06079,8576.00000,-288.00000,70,17591.96875,20,843.08203,-0.00166,75.10849,0.07236,0,372.68365,-0.00116,18107.54492,349.55222,337.11185,0,10027.00000,27605.00000,,,,
-102,0.10087,1.40527,406.14667,993.95294,33.6555,0.0,31.97761,35.58186,100,99.91608,100,-1.82953,50.99828,50.79803,205.45961,900.92645,1980.66223,2833.82959,245.51390,989.63934,14.50369,13.93280,409.05154,29.23983,74.40337,12,11.78131,1.34750,0.20233,540833,540833,0,0,1,1,1,35.49804,35.26917,28.02298,0,1,54120.00000,0,698.59619,763.19324,0,1,2880,789.00,787.65509,1,11.89075,10,10,10,10,-3.87107,-1.06948,4.20587,6.40103,1472.08398,9116.26855,-288.00000,70,18093.12891,20,800.60876,-0.00166,0.06511,0.07236,0,389.83871,-0.00080,18250.68555,352.25784,338.83081,0,10027.00000,27605.00000,,,,
-103,0.10087,1.41284,406.14667,993.95294,33.4603,0.22565,72.85954,35.06306,100,0.29907,0,-1.87531,51.07759,50.79803,176.59511,903.09906,1965.73865,2830.74121,246.08609,995.2926,14.53676,14.04724,409.20135,38.66627,65.39307,12,11.78894,1.34674,0.20233,540833,540833,0,0,1,1,1,35.63538,35.39123,28.02385,0,1,54115.00000,0,698.19946,763.19324,0,1,2880,788.00,788.45123,1,11.88880,10,10,10,10,-3.21657,-1.10431,3.89946,6.31956,3589.68555,7491.30762,-288.00000,70,17714.95117,20,953.45776,-0.00166,67.45514,55.80872,0,380.24997,0.00007,18261.30078,341.24567,338.69308,0,10027.00000,27605.00000,,,,
-104,0.10121,1.40951,405.06735,1001.99799,33.4603,100.0,1148.43237,35.52349,100,99.91608,100,-1.88294,51.01497,50.79803,203.17075,917.03729,31.14785,152.81065,244.71236,998.70819,13.97541,13.45978,409.76370,64.48365,43.11523,12,11.78894,1.34566,0.20233,540833,540833,0,0,1,1,1,35.92529,35.25391,28.03081,0,1,54092.00000,0,711.92627,763.19324,0,1,2880,790.00,791.39868,1,11.87454,10,10,10,10,-3.73987,-1.20169,3.85317,6.34854,3797.57764,8690.53125,-288.00000,70,18633.36914,20,1148.03467,0.00000,-0.00723,0.07236,0,387.90604,0.00282,18355.09180,348.46115,337.83533,0,10026.00000,27627.00000,,,,
-105,0.03051,1.41015,405.06735,1105.2218,33.4603,3.19211,2826.06665,35.63183,100,99.91608,100,-1.87531,50.93108,50.79803,201.07265,913.64728,7.09532,1756.23547,244.17877,1000.44769,14.28373,12.75024,410.42816,34.88235,99.57275,12,11.78131,1.34447,0.20233,540833,540833,0,0,1,1,1,35.78796,35.23864,28.02821,0,1,54094.00000,0,695.03174,763.19324,0,1,2880,790.00,790.93481,1,11.85621,10,10,10,10,-3.83702,-1.18561,4.06195,6.52392,3050.98633,7904.00000,-288.00000,70,18581.38086,20,1086.46826,0.00000,-0.00723,0.07236,0,382.37454,0.00224,18331.65039,347.52802,338.07376,0,10026.00000,27605.00000,,,,
-106,0.10145,1.41618,405.06735,1105.2218,33.6555,100.0,2837.05811,36.93623,100,99.91608,100,-1.88294,51.06225,50.79803,204.50587,915.72650,28.96271,1054.24768,244.17877,1103.23108,14.13295,12.75024,411.19492,43.67267,99.58651,12,12.01782,1.34293,0.17029,540833,540833,0,0,1,1,1,35.97107,35.05553,28.02561,0,1,54102.00000,0,713.06152,763.19324,0,1,2880,788.00,789.26794,1,11.85452,10,10,10,10,-3.90791,-1.21604,4.11387,6.62669,2476.03931,6667.94336,-288.00000,70,18666.94727,20,1474.02747,-0.00166,-0.00723,0.09042,0,367.44220,0.00239,18464.45312,351.31122,337.64062,0,10026.00000,27627.00000,,,,
-107,0.10087,1.41846,405.06735,993.95294,31.91024,82.5098,2833.68921,36.74549,100,0.29907,0,-1.88294,50.90999,51.96533,203.36151,913.53613,1947.57495,2821.04248,243.79729,1000.88245,14.12189,13.45978,415.70963,36.08575,93.6676,12,11.78894,1.34216,0.20233,540833,540833,0,0,1,1,1,35.92529,35.07080,28.02726,0,1,54113.00000,0,723.24829,763.19324,0,1,2880,788.00,787.70276,1,11.87914,10,10,10,10,-3.68720,-1.19971,4.12129,6.51553,113.00000,5250.50391,-288.00000,70,18556.95898,20,200.64716,-0.01237,64.74972,71.37946,0,379.72849,0.00087,18459.47852,349.01157,342.53635,0,10027.00000,27627.00000,,,,
-108,0.10121,1.42084,397.63785,1001.99799,31.91024,0.0,2827.79321,35.68409,100,99.91608,0,-1.88294,50.77075,50.79803,207.36693,897.01080,1984.34314,2840.55103,243.41580,1002.18701,13.90814,13.93280,416.28876,89.31606,38.01117,12,11.78894,1.33987,0.20233,540833,540833,0,0,1,1,1,35.96607,35.13065,28.02649,0,1,54141.00000,0,708.95386,763.19324,0,1,2880,785.00,784.14117,1,11.86226,10,10,10,10,-3.66358,-1.14511,4.60833,6.74973,2204.89697,4991.55859,-288.00000,70,18910.28516,20,86.09989,-0.00166,61.89236,74.25494,0,390.96939,-0.00304,18404.42383,349.89462,339.57016,0,10027.00000,27605.00000,,,,
-109,0.10187,1.42260,405.06735,1001.99799,33.4603,100.0,2673.20117,35.42088,100,99.91608,0,-1.87531,50.67899,50.79803,205.45961,911.36163,1970.90137,2832.98730,210.55661,1004.36145,14.01535,13.69629,419.01581,50.74824,95.55969,12,12.01782,1.33911,0.20233,540833,540833,0,0,1,1,1,35.92529,35.16236,28.02736,0,1,54125.00000,0,709.39941,763.19324,0,1,2880,786.00,786.38422,1,11.89288,10,10,10,10,-3.62543,-1.13911,4.23387,6.50386,100.00000,5728.00000,-208.00000,70,18606.27344,20,390.79764,-0.00166,64.4025,66.20734,0,386.86444,-0.00036,18428.83594,351.14572,344.82452,0,10027.00000,27605.00000,,,,
-110,0.10121,1.42610,406.14667,1105.2218,33.6555,0.0,2824.00293,37.0494,100,99.91608,0,-1.87531,50.67258,50.79803,201.83560,910.05707,123.28770,2825.68750,243.98799,998.70819,13.99602,13.45978,418.30881,96.21182,92.82837,12,12.01782,1.33812,0.20233,540833,540833,0,0,1,1,1,35.97107,35.19287,28.02389,0,1,54102.00000,0,719.37866,763.19324,0,1,2880,788.00,788.79236,1,11.88420,10,10,10,10,-3.73645,-1.14916,4.39737,6.66135,2389.00000,6472.00000,-208.00000,70,18953.10742,20,438.74179,0.00000,-0.00723,0.41592,0,389.55731,0.00109,18482.23047,352.91666,343.46310,0,10026.00000,27627.00000,,,,
-111,0.10121,1.43040,397.63785,1105.2218,31.91024,100.0,1787.45789,37.65461,100,0.29907,100,-1.87531,50.61568,50.79803,204.12440,910.05707,600.97162,808.69995,244.36948,1106.10132,13.81842,13.45978,416.61414,40.7317,95.91827,12,12.01019,1.33606,0.20233,540833,540833,0,0,1,1,1,36.18469,35.29968,28.02645,0,1,54090.00000,0,697.3999,763.19324,0,1,2880,788.00,789.93829,1,11.88137,10,10,10,10,-3.68105,-1.16568,4.47711,6.64513,1711.20496,4808.00000,-176.00000,70,18933.84961,20,585.54291,0.00000,-0.00723,4.15945,0,393.93295,0.00210,18716.55273,351.55396,344.60712,0,10026.00000,27627.00000,,,,
-112,0.03051,1.43540,406.14667,1105.2218,33.4603,100.0,2840.00635,36.59862,100,0.29907,0,-1.88294,50.78274,50.79803,208.32059,910.92682,745.70789,2833.69873,243.27278,1104.50671,13.74128,13.45978,434.75983,36.65206,39.07165,12,11.78131,1.33386,0.27557,540833,540833,0,0,1,1,1,36.23047,35.16236,28.03166,0,1,54130.00000,0,708.42895,763.19324,0,1,2880,784.00,784.03967,1,11.91155,10,10,10,10,-3.60876,-1.27307,4.44061,6.65323,149.07123,4473.01465,-160.00000,70,18891.98047,20,218.53246,-0.00166,64.84375,64.72437,0,368.46307,-0.00015,18865.64062,354.60648,346.59702,0,10027.00000,27605.00000,,,,
-113,0.10121,1.42153,406.14667,1001.99799,33.4603,100.0,28.95534,35.43728,2.1612,99.91608,43.21747,34.43298,50.86071,46.17462,203.74300,832.21429,4.80653,2857.54565,187.14902,1105.78247,13.78346,12.75024,409.55463,42.03646,49.3866,12,11.78894,1.32836,0.27557,540833,540833,0,0,1,1,1,36.09313,35.22338,28.02554,0,1,54107.00000,0,712.77466,763.19324,0,1,2880,787.00,784.16498,1,11.91375,10,10,10,10,-2.83690,-1.17018,3.87065,6.47466,5443.00000,6292.71484,-160.00000,70,19364.95117,20,3871.00000,0.02383,62.40597,2.1882,0,365.92270,-0.00101,19323.39062,345.78586,354.93500,0,10027.00000,27627.00000,,,,
-114,0.10087,1.43743,397.63785,993.95294,33.6555,100.0,2825.42700,35.64137,100,0.29907,100,-1.88294,50.74863,50.79803,205.59627,897.44562,1983.96985,2839.58105,199.23755,1004.36145,13.66183,13.94043,426.78555,38.07325,99.38557,12,11.78894,1.32538,0.20233,540833,540833,0,0,1,1,1,36.29150,35.39123,28.0196,0,1,54130.00000,0,708.19702,763.19324,0,1,2880,785.00,783.58398,1,11.89725,10,10,10,10,-3.15684,-1.12850,4.56875,6.63722,-7.00000,2573.81836,-160.00000,70,19420.03125,20,-16.00000,-0.00166,61.17621,0.07236,0,397.54614,-0.00217,18544.74805,351.88306,346.76517,0,10026.00000,27627.00000,,,,
-115,0.10087,1.43816,397.63785,1105.2218,33.4603,100.0,33.96383,35.88398,100,0.29907,0,-1.84479,49.39040,50.79803,200.50046,900.05493,1963.33508,2830.17969,242.27138,999.14294,13.62607,13.45978,428.37021,42.54813,43.70269,12,11.78894,1.32212,0.27557,540833,540833,0,0,1,1,1,36.23047,35.42175,28.02736,0,1,54087.00000,0,709.30176,763.19324,0,1,2880,788.00,789.18848,1,11.92807,10,10,10,10,-3.00541,-1.07762,4.25823,6.61231,2090.09302,4551.54590,-160.00000,70,19102.64453,20,182.73805,0.00000,-0.00723,66.2616,0,402.11716,0.00058,18704.66406,353.45795,349.08380,0,10017.07715,27627.00000,,,,
-116,0.10145,1.44272,405.06735,1105.2218,31.91024,100.0,2829.61816,37.30423,100,0.29907,100,-1.88294,49.26095,50.79803,183.57884,908.75250,6.90462,2416.86548,241.50848,1000.88245,13.50125,13.34534,421.36716,100.0,38.46893,12,12.01782,1.31998,0.20233,540833,540833,0,0,1,1,1,36.52039,35.49804,28.02649,0,1,54081.00000,0,712.82349,763.19324,0,1,2880,789.00,789.73083,1,11.92504,10,10,10,10,-3.22571,-1.20521,4.08110,6.62097,1209.82446,4727.71875,-160.00000,70,18982.55078,20,401.09192,0.00000,71.72308,71.94012,0,401.92737,0.00246,18655.74414,356.29691,346.45193,0,10026.00000,27627.00000,,,,
-117,0.10087,1.45130,397.63785,993.95294,32.0,100.0,2839.02344,36.87507,100,99.91608,0,-1.87531,50.23616,48.43068,203.74300,907.44794,1952.62500,2835.79492,236.98364,1105.4635,13.72534,13.45978,437.12674,45.84407,90.82946,12,12.01782,1.31483,0.20233,540833,540833,0,0,1,1,1,36.35254,35.49804,28.03429,0,1,54133.00000,0,712.47559,763.19324,0,1,2880,783.00,782.31171,1,11.91100,10,10,10,10,-3.46322,-1.22004,4.69220,6.94616,-7.00000,2700.71021,-160.00000,70,19080.00000,20,36.48540,-0.00166,69.42996,25.31824,0,400.29373,-0.00036,18830.29883,358.23288,350.48236,0,10027.00000,27627.00000,,,,
-118,0.10121,1.44769,406.14667,1105.2218,33.6555,12.59451,2841.13135,35.41859,100,99.91608,0,97.17712,50.44833,48.09172,193.41008,894.95508,311.97437,2835.37378,203.54572,1001.7522,13.75446,12.75024,434.15289,37.09135,45.01495,12,11.78131,1.30714,0.20233,540833,540833,0,0,1,1,1,36.52039,35.43700,28.03,0,1,54121.00000,0,698.98071,763.19324,0,1,2880,785.00,784.46564,1,11.92913,10,10,10,10,-3.21296,-1.18194,4.29723,6.71407,157.88907,3554.44580,-160.00000,70,19230.40039,20,43.04870,0.00000,74.72513,68.703,0,393.71271,0.00000,18877.65039,359.64584,348.48227,0,10027.00000,27627.00000,,,,
-119,0.03051,1.45669,397.63785,993.95294,33.4603,100.0,455.93036,34.80137,100,99.91608,100,-1.87531,47.33069,50.44735,198.52530,898.01099,1968.99414,2828.91626,243.98799,991.37872,13.56251,13.58185,442.32510,99.02855,37.65258,12,11.78894,1.30440,0.27557,540833,540833,0,0,1,1,1,36.29150,35.52856,28.02821,0,1,54100.00000,0,708.48389,763.19324,0,1,2880,788.00,787.49414,1,11.93075,10,10,10,10,-3.10350,-0.83571,4.50600,6.73301,-7.00000,1693.81018,-160.00000,70,18996.43945,20,-17.00000,-0.00166,-0.00723,0.09042,0,409.09375,0.00015,18804.97852,359.10291,347.39999,0,10000.00000,27627.00000,,,,
-120,0.10087,1.45734,406.14667,1105.2218,33.4603,100.0,920.39197,37.51403,100,99.91608,0,-1.88294,48.93628,49.93354,203.36151,865.47266,6.90462,2829.05664,242.67555,1104.50671,13.55402,12.75024,428.37021,31.05296,38.36975,12,11.78131,1.29822,0.27557,540833,540833,0,0,1,1,1,36.39831,35.52856,28.03426,0,1,54080.92578,0,705.15747,763.19324,0,1,2880,789.00,788.92224,1,11.94502,10,10,10,10,-3.12865,-0.97281,4.29408,6.64804,2535.61670,4239.85303,-160.00000,70,19338.63867,20,124.18024,0.00123,1.80846,11.99002,0,407.55463,0.00152,19075.64062,360.60138,353.58786,0,10026.00000,27627.00000,,,,
-121,0.10145,1.45902,405.06735,1119.68103,32.0,100.0,2828.49487,35.98698,100,0.29907,100,-1.88294,47.67596,50.79803,188.23911,899.18518,70.66055,159.30455,243.79729,1104.18787,13.05271,12.75024,439.30923,91.31859,90.82946,12,11.78894,1.29283,0.20233,540833,540833,0,0,1,1,1,36.81030,35.60485,28.02902,0,1,54076.00000,0,715.15503,763.19324,0,1,2880,789.00,788.88422,1,11.93121,10,10,10,10,-3.19434,-0.83092,4.44993,6.77365,-7.00000,2300.77563,-160.00000,70,19439.07812,20,-16.00000,0.00000,12.05873,2.74884,0,410.35959,0.00382,19148.21289,368.33987,349.21924,0,10001.11523,27627.00000,,,,
-122,0.10145,1.46556,406.14667,993.95294,31.91024,32.57553,2832.14502,35.75478,100,0.29907,0,-1.87531,49.63942,50.31738,172.27557,897.88062,80.39886,1785.30322,243.79729,1116.2561,13.28690,12.75024,444.51123,39.37299,98.02399,12,12.01782,1.28266,0.20233,540833,540833,0,0,1,1,1,36.68823,35.62011,28.02561,0,1,54078.00000,0,708.69751,763.19324,0,1,2880,788.00,789.04376,1,11.92645,10,10,10,10,-3.17241,-0.86002,4.09195,6.78798,-7.00000,2728.06592,-160.00000,70,19348.66016,20,64.40186,0.00000,0.72339,0.07236,0,409.93390,0.00326,19118.91406,365.27771,350.80490,0,9999.00000,27627.00000,,,,
-123,0.10121,1.46927,397.63785,993.95294,33.4603,100.0,539.89325,36.66958,100,99.91608,100,-1.87531,48.13017,50.55424,205.26883,848.95172,1194.75171,2830.60083,242.65285,993.98804,13.10646,12.75024,437.41788,42.78933,39.55231,12,12.01782,1.27109,0.20233,540833,540833,0,0,1,1,1,36.52039,35.78796,28.03081,0,1,54086.00000,0,715.75928,763.19324,0,1,2880,788.00,789.39197,1,11.97885,10,10,10,10,-2.64957,-0.71637,3.90669,6.55790,170.24615,2067.86572,-160.00000,70,19380.88672,20,2.88914,0.00072,-0.00723,0.05423,0,414.90561,0.00072,19334.10742,363.33926,357.12729,0,10024.57812,27605.00000,,,,
-124,0.10121,1.47659,406.14667,1001.99799,31.91024,100.0,2832.99365,37.18368,100,0.29907,0,-1.80664,47.26491,49.60456,202.40779,899.62018,7.09532,1807.07361,243.03433,1003.92651,13.27993,11.68213,438.59360,42.44932,96.97113,12,11.78894,1.26192,0.27557,540833,540833,0,0,1,1,1,36.85607,35.72693,28.02821,0,1,54087.00000,0,691.6687,763.19324,0,1,2880,788.00,788.54498,1,11.94263,10,10,10,10,-3.29460,-1.05380,4.46765,6.86800,125.74995,2958.81714,-160.00000,70,19041.29883,20,-13.74942,0.00000,79.28964,0.05423,0,411.19019,0.00210,19268.08984,371.26447,353.82037,0,10026.00000,27627.00000,,,,
-125,0.10145,1.48148,405.06735,1001.99799,31.91024,100.0,2832.84692,37.05257,100,99.91608,0,97.20763,46.97996,47.60769,207.74841,899.62018,1966.13293,2835.69727,243.03433,998.27319,13.41919,13.37951,449.12369,81.19324,43.35174,12,12.01782,1.24812,0.27557,540833,540833,0,0,1,1,1,36.74926,35.83374,28.02733,0,1,54118.00000,0,705.7373,763.19324,0,1,2880,784.00,784.41229,1,11.94551,10,10,10,10,-2.83310,-0.39035,4.46206,6.84650,-7.00000,2533.73120,-160.00000,70,18787.48242,20,-17.00000,-0.00022,-0.00723,0.07236,0,418.39160,-0.00072,19299.34375,373.32751,355.71432,0,10026.00000,27605.00000,,,,
-126,0.10087,1.48269,405.06735,1105.2218,33.6555,100.0,2817.44629,36.8729,100,99.91608,100,-1.77612,47.62877,47.25800,204.50587,896.98871,5.76019,2831.44312,234.73857,1106.42029,13.11783,11.68213,423.87189,44.85558,85.2829,12,11.78894,1.22576,0.20233,540833,540833,0,0,1,1,1,36.76452,35.83888,28.02726,0,1,54074.00000,0,719.56787,763.19324,0,1,2880,788.00,787.86798,1,11.96169,10,10,10,10,-2.86757,-0.89543,4.27446,6.65605,3110.71069,4112.00000,-160.00000,70,19401.15430,20,51.70604,0.00123,68.7934,66.2616,0,420.62250,0.00181,19563.33203,364.52704,360.22507,0,10026.00000,27627.00000,,,,
-127,0.10121,1.49015,397.63785,1115.11975,32.0,100.0,2826.53735,35.84137,100,0.29907,100,97.23052,45.71051,50.79803,173.50523,910.92682,6.14166,1171.11682,244.75096,1001.7522,12.72082,12.48363,438.14166,42.94764,93.09539,12,12.01019,1.16352,0.27557,540833,540833,0,0,1,1,1,36.87133,35.84900,28.02736,0,1,54042.79688,0,701.41602,763.19324,0,1,2880,790.00,790.96747,1,11.95131,10,10,10,10,-3.00822,-0.54724,4.33598,6.88159,135.72522,3284.63452,-160.00000,70,18974.86719,20,9.34267,0.00000,73.1192,0.05423,0,422.31406,0.05035,19436.58594,381.45499,356.29086,0,9914.00000,27627.00000,,,,
-128,0.10121,1.55365,405.06735,1001.99799,33.4603,41.4879,2834.11035,37.28298,100,0.29907,0,97.20001,61.84288,63.41705,220.14613,945.28204,1943.35339,2813.05127,314.94138,998.70819,15.54574,15.59601,408.17899,37.251,35.51636,12,11.78894,1.38336,0.20233,540833,540833,0,0,1,1,1,34.68933,34.97925,28.02301,0,1,54083.00000,0,708.11768,763.19324,0,1,2880,779.00,776.98895,1,11.81595,10,10,10,10,-3.74789,-1.56108,3.38555,5.36319,442.74493,278.40762,13584.00000,70,5166.73340,20,-23.00000,-0.00022,30.78703,61.68622,0,429.63620,0.00029,19876.84375,380.38013,367.64001,0,10082.00000,27605.00000,,,,
-129,0.10121,1.53625,405.06735,1105.2218,33.4603,0.0,2836.07568,36.38309,100,99.91608,0,-1.84479,61.86510,62.47863,224.53302,940.93317,260.04971,2826.67017,311.31744,987.03003,17.33420,14.99329,408.73941,44.55353,93.43109,12,11.78894,1.38184,0.20233,540833,540833,0,0,1,1,1,34.68933,35.02502,28.0325,0,1,54108.00000,0,692.05933,763.19324,0,1,2880,778.00,776.57892,1,11.82112,10,10,10,10,-3.94802,-1.62140,3.24157,5.07537,134.00000,416.00000,13536.78613,70,5047.00000,20,-19.00000,0.00000,66.87643,74.47192,0,439.83850,0.00007,19995.52344,384.85562,374.37842,50,10082.00000,27605.00000,,,,
-130,0.10087,1.52415,397.63785,1001.99799,33.4603,100.0,2829.75854,37.74406,0,0.29907,0,97.16949,62.21674,63.41705,220.71838,942.67273,78.00976,30.98430,313.22476,1104.18787,15.45620,14.64233,408.63858,43.32717,40.26947,12,11.78894,1.38107,0.27557,540833,540833,0,0,1,1,1,34.79614,35.05553,28.02733,0,1,54056.00000,0,715.86304,763.19324,0,1,2880,785.00,786.00916,1,11.81236,10,10,10,10,-4.07360,-1.40240,3.32571,5.12405,93.50683,338.10281,13488.00000,70,5140.21094,20,-18.00000,0.00000,65.53097,3.4722,10,443.51114,0.00413,20173.71094,405.13351,369.90598,0,10053.00000,27605.00000,,,,
-131,0.10145,1.53902,405.06735,993.95294,33.6555,100.0,2825.54712,37.40925,100,99.91608,0,97.21527,63.32154,67.17834,223.77014,949.19592,1961.93677,2005.17395,308.65677,988.76959,16.16443,14.99329,408.56516,99.46686,48.92883,12,11.78131,1.37878,0.20233,540833,540833,0,0,1,1,1,34.81140,35.07080,28.02561,0,1,54103.00000,0,716.15601,763.19324,0,1,2880,780.00,779.92780,1,11.84029,10,10,10,10,-3.86474,-1.62376,2.73703,4.51490,80.00000,261.88782,13446.49023,70,5115.25146,20,-19.00000,-0.00166,75.45575,0.07236,0,446.11328,0.00029,20220.07422,383.78815,376.51849,0,10053.00000,27590.00000,,,,
-132,0.10087,1.54815,397.63785,1001.99799,31.91024,0.0,2829.89893,37.38243,100,0.29907,100,-1.88294,62.46741,64.83612,226.63112,941.80298,6.15668,146.06665,310.55450,994.42285,15.80739,14.64996,407.56561,45.01162,42.28363,12,11.78894,1.37726,0.20233,540833,540833,0,0,1,1,1,34.82666,35.42175,28.02649,0,1,54079.00000,0,721.81397,763.19324,0,1,2880,784.00,784.38867,1,11.81352,10,10,10,10,-3.99332,-1.45808,3.35319,5.20413,124.85320,216.00000,13836.00000,70,5148.61523,20,-19.00000,0.00000,73.72684,64.72437,0,448.69272,0.00195,19979.12305,391.28564,375.15680,50,10053.00000,27605.00000,,,,
-133,0.10121,1.56734,405.06735,1105.2218,31.91024,5.56645,2830.17969,37.39349,100,0.29907,0,-1.87531,65.10620,66.94183,228.80573,957.89349,1964.41638,844.80988,309.98230,1003.92651,15.56702,15.59601,407.51450,90.9927,52.6062,12,11.78131,1.37268,0.20233,540833,540833,0,0,1,1,1,34.85717,35.42175,28.03257,0,1,54111.00000,0,729.5044,763.19324,0,1,2880,778.00,780.17053,1,11.82393,10,10,10,10,-3.87406,-1.43904,3.34511,5.28313,-20.00000,168.00000,13872.00000,70,5172.10986,20,-19.00000,-0.00166,71.84607,60.67346,0,449.23105,-0.00015,20389.76953,412.68094,375.98978,0,10053.00000,27605.00000,,,,
-134,0.10087,1.58300,397.63785,1001.99799,33.6555,100.0,2838.32178,36.95644,0,0.29907,0,-1.88294,63.84407,64.83612,223.77014,950.50049,1968.61255,2329.15161,308.83786,1118.5387,15.33405,15.59562,407.25888,100.0,40.85693,12,11.78894,1.37115,0.20233,540833,540833,0,0,1,1,1,34.85717,35.58960,28.02814,0,1,54122.00000,0,714.89868,763.19324,0,1,2880,775.00,775.19678,1,11.82162,10,10,10,10,-3.55991,-1.36049,3.53101,5.61653,-22.00000,112.00000,13680.00000,70,5354.45752,20,-23.00000,-0.01237,6.99509,0.07236,0,447.70059,-0.00051,20810.63281,451.54004,382.65729,0,10053.00000,27590.00000,,,,
-135,0.10145,1.58537,397.63785,993.95294,31.91024,100.0,1949.90759,35.52159,100,0.29907,100,38.47656,63.91919,68.36090,225.40623,962.75702,166.74078,31.97760,312.46182,1105.78247,15.28837,15.22980,406.64551,37.92765,33.85315,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.88770,35.65064,28.02726,0,1,54061.96484,0,712.23755,763.19324,0,1,2880,785.00,786.24341,1,11.82257,10,10,10,10,-3.38996,-1.34430,3.52615,5.58614,-7.00000,112.00000,14064.00000,70,5277.07568,20,-19.00000,-0.00022,6.50317,0.14465,0,474.84949,0.00224,20945.32031,399.08685,385.44852,0,10053.00000,27605.00000,,,,
-136,0.10087,1.59825,405.06735,993.95294,33.6555,77.99944,2831.30273,37.83142,100,0.29907,100,97.21527,66.04739,68.36090,473.06061,967.46893,346.59784,223.11438,309.53665,993.55328,15.22704,15.58838,406.69659,40.4233,81.49872,12,12.01782,1.36658,0.20233,540833,540833,0,0,1,1,1,34.88770,35.77270,28.03253,0,1,54097.00000,0,715.83252,763.19324,0,1,2880,780.00,781.94299,1,11.86454,10,10,10,10,-3.30129,-1.35538,3.43449,5.46865,-22.00000,48.00000,14242.64746,70,5249.56348,20,-19.00000,-0.00166,1.97482,60.2937,0,462.35757,0.00080,20777.22461,407.87747,392.29535,0,10053.00000,27605.00000,,,,
-137,0.10087,1.63148,445.34219,1001.99799,31.91024,29.7378,2836.49365,37.7742,0,99.91608,0,3.2135,66.60533,63.42468,221.61157,947.89117,916.17883,2827.09131,308.62897,992.68347,15.15641,14.99329,406.23657,83.71056,44.41986,12,12.01782,1.36658,0.20233,540833,540833,0,0,1,1,1,34.90295,35.83112,28.02733,0,1,54122.00000,0,711.43799,763.19324,0,1,2880,775.00,774.85443,1,11.86371,10,10,10,10,-2.79616,-1.37103,3.54643,5.63243,-7.00000,32.00000,14347.15625,70,6785.89258,20,-23.00000,-0.00166,1.09953,60.60113,0,460.66183,-0.00036,21594.45117,400.69897,390.78363,0,10053.00000,27605.00000,,,,
-138,0.10087,1.63789,397.63785,993.95294,33.4603,0.0,2048.26807,36.85268,100,99.91608,0,-1.88294,65.18991,67.07916,222.05353,956.34308,322.42184,28.99807,316.24863,1001.7522,15.13070,14.78947,405.92987,100.0,43.34411,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.91821,35.86426,28.02392,0,1,54069.00000,0,714.89258,763.19324,0,1,2880,785.00,786.67395,1,11.91047,10,10,10,10,-3.64058,-1.39496,3.38766,5.77165,-22.00000,64.00000,14268.24707,70,5818.96924,20,-19.00000,-0.00166,-0.00723,0.05423,0,486.76477,0.00246,21841.62305,398.20511,397.15018,0,10052.00000,27605.00000,,,,
-139,0.10145,1.67197,406.14667,1001.99799,31.91024,100.0,1741.45374,37.26696,100,99.91608,100,-1.88294,65.64541,67.30804,226.18513,957.89349,50.00057,185.17389,313.03406,1107.05811,15.06666,14.99329,406.13434,41.73166,90.10468,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.96399,35.92529,28.02301,0,1,54087.00000,0,716.29028,763.19324,0,1,2880,784.00,784.08771,1,11.90832,10,10,10,10,-3.56217,-1.72515,3.44862,5.80199,-7.00000,48.00000,14544.00000,70,5263.41943,20,-19.00000,-0.00022,75.11575,67.85303,0,483.66696,0.00109,22090.96094,379.54498,405.30710,0,10053.00000,27605.00000,,,,
-140,0.10121,1.66617,445.34219,1001.99799,32.0,0.0,2830.46484,37.34249,100,0.29907,100,-1.87531,66.94560,71.88568,227.96626,946.58661,54.84140,34.95676,310.55450,992.68347,14.99650,15.22980,406.03207,100.0,89.44092,12,11.78131,1.36658,0.20233,540833,540833,0,0,1,1,1,34.93347,35.92529,28.02649,0,1,54094.00000,0,716.10107,763.19324,0,1,2880,781.00,781.82727,1,11.87503,10,10,10,10,-3.90473,-1.78546,3.56541,6.01700,-20.00000,16.00000,14738.60547,70,6517.32910,20,-19.00000,-0.00022,-0.00723,71.57843,0,477.70239,0.00130,21190.96680,376.76871,400.55951,0,10053.00000,27605.00000,,,,
-141,0.10087,1.79121,406.14667,1001.99799,33.4603,0.65421,1605.26331,37.29023,0,99.91608,0,-1.88294,65.88298,65.88898,220.14613,941.80298,18.34462,832.81500,312.27112,1001.31744,14.93424,14.64233,405.31647,33.95538,42.0433,12,11.78894,1.37268,0.20233,540833,540833,0,0,1,1,1,34.97925,35.98632,28.0326,0,1,54087.00000,0,702.99683,763.19324,0,1,2880,784.00,785.03845,1,11.84520,10,10,10,10,-4.04546,-1.70729,3.78166,6.09223,80.00000,16.00000,14928.00000,70,6020.35938,20,-19.00000,0.00000,-0.00723,11.66452,0,461.62674,0.00109,21145.60742,377.72397,390.03723,0,10053.00000,27590.00000,,,,
-142,0.03051,1.65109,393.16226,993.95294,33.4603,100.0,2070.50122,36.98719,0,0.29907,0,-1.87531,71.51735,67.30804,219.57394,939.19385,1969.75696,2829.19678,309.95062,1106.73914,14.89889,14.64233,405.72540,80.32044,46.90704,12,11.78894,1.37268,0.20233,540833,540833,0,0,1,1,1,34.97925,36.09007,28.02473,0,1,54117.00000,0,709.34448,763.19324,0,1,2880,778.00,778.18378,1,11.83095,10,10,10,10,-3.63193,-1.71636,3.89584,6.13160,-22.00000,16.00000,15232.00000,70,8912.37207,20,-23.00000,0.00000,73.16263,11.26666,0,463.08615,-0.00080,20626.97656,375.84122,389.35538,0,10053.00000,27590.00000,,,,
-143,0.10145,1.61581,405.06735,993.95294,33.4603,100.0,1583.27466,37.50335,100,0.29907,0,-1.88294,67.84772,68.00231,219.38326,939.19385,108.62770,36.94299,315.67422,997.90192,14.88707,14.53552,405.46979,74.32777,40.0177,12,12.01019,1.37497,0.27557,540833,540833,0,0,1,1,1,34.97925,36.03211,28.02993,0,1,54084.00000,0,723.12622,763.19324,0,1,2880,785.00,785.68207,1,11.84458,10,10,10,10,-3.48176,-1.51236,4.00956,6.17408,-20.00000,16.00000,15216.00000,70,8508.88867,20,-19.00000,0.00000,72.50433,65.32123,0,484.98044,0.00145,20365.34570,367.18433,380.67151,0,10053.00000,27605.00000,,,,
-144,0.10145,1.59612,397.63785,1105.2218,33.6555,100.0,2829.19678,37.07317,100,0.29907,100,97.19238,70.75201,69.89441,223.00719,940.06360,384.53860,467.65021,313.03406,988.76959,14.84153,14.53552,405.06085,51.1756,95.55969,12,12.01782,1.37726,0.20233,540833,540833,0,0,1,1,1,34.99451,36.36779,28.02814,0,1,54106.23438,0,706.36597,763.19324,0,1,2880,781.00,781.75049,1,11.90043,10,10,10,10,-2.94334,-1.67483,3.93946,6.10994,-20.00000,0.00000,15696.94434,70,7651.33203,20,-19.00000,0.00000,69.89294,74.25494,0,466.50525,0.00036,20090.32227,362.03152,374.71249,0,10053.00000,27605.00000,,,,
-145,0.10145,1.57220,405.06735,1001.99799,31.91024,100.0,2832.42578,35.50557,100,0.29907,100,-1.87531,72.26492,67.30804,219.54987,941.36816,6.14166,31.97760,314.94138,1000.0127,14.75452,14.52789,404.34521,93.02338,95.91065,12,12.01782,1.37878,0.20233,540833,540833,0,0,1,1,1,35.08606,36.15417,28.02558,0,1,54081.00000,0,712.16431,763.19324,0,1,2880,785.00,786.94861,1,11.92398,10,10,10,10,-3.03197,-1.54598,3.87508,6.12236,-20.00000,0.00000,15584.00000,70,8415.29785,20,-18.00000,0.00000,53.79774,1.33826,10,450.76544,0.00318,20148.33398,363.90475,368.01849,0,10052.00000,27605.00000,,,,
-146,0.10121,1.54182,445.34219,993.95294,33.4603,100.0,2829.33740,37.47741,0,99.91608,0,-1.87531,68.81345,66.47615,218.62029,938.32404,98.05994,32.97053,314.17844,1004.36145,14.74569,14.52789,404.80194,45.47968,42.04711,12,11.78131,1.38031,0.27557,540833,540833,0,0,1,1,1,35.02502,36.15417,28.02821,0,1,54088.00000,0,723.34595,763.19324,0,1,2880,785.00,785.61584,1,11.95612,10,10,10,10,-3.05445,-1.77217,3.73367,6.11757,-20.00000,0.00000,15539.27246,70,8628.91602,20,-19.00000,0.00000,69.30701,2.67648,0,451.31326,0.00174,19779.43164,353.62796,366.90851,0,10053.00000,27590.00000,,,,
-147,0.10087,1.52171,406.14667,993.95294,33.4603,77.84199,2830.22852,37.33715,100,99.91608,0,-1.77612,69.46402,65.88898,218.81099,937.45422,7.08976,489.17368,314.33914,1001.38104,14.70695,14.52789,404.34521,87.0245,89.07471,12,11.78894,1.38184,0.27557,540833,540833,0,0,1,1,1,35.02502,36.36779,28.02993,0,1,54098.00000,0,716.21094,763.19324,0,1,2880,783.00,783.98547,1,11.95801,10,10,10,10,-3.56911,-1.87744,3.72088,6.15811,-20.00000,0.00000,15839.43164,70,9527.75586,20,-19.00000,0.00072,68.33044,34.95734,0,447.07373,0.00094,19698.81250,347.72412,365.14615,0,10053.00000,27590.00000,,,,
-148,0.10121,1.51621,406.14667,1105.2218,33.4603,100.0,1131.39392,34.97303,100,0.29907,0,-1.87531,67.22683,68.36090,219.00177,937.45422,944.84552,1687.52771,315.67422,1006.53571,14.64855,14.52026,405.51392,46.96433,93.2022,12,12.01782,1.38489,0.27557,540833,540833,0,0,1,1,1,35.02502,37.39014,28.02301,0,1,54107.00000,0,719.17114,763.19324,0,1,2880,783.00,783.02582,1,11.97694,10,10,10,10,-3.75726,-2.01474,3.66870,6.19213,-22.00000,0.00000,16240.00000,70,10071.80176,20,-23.00000,0.00072,-0.00723,50.72699,0,436.91656,0.00007,19606.57227,338.58652,364.43301,0,10053.00000,27590.00000,,,,
-149,0.10145,1.51283,397.63785,993.95294,33.6555,100.0,696.79858,37.24815,100,99.91608,0,-1.86768,66.85487,66.47643,218.03929,936.14972,1951.54456,2537.71387,310.15112,993.98804,14.49119,14.52026,404.84045,87.53048,46.07544,12,12.01782,1.38565,0.27557,540833,540833,0,0,1,1,1,35.13183,37.25280,28.03172,0,1,54117.00000,0,716.19873,763.19324,0,1,2880,780.00,781.07819,1,11.89368,10,10,10,10,-4.11405,-2.04117,4.01486,6.38914,-22.00000,0.00000,16658.03516,70,11666.60254,20,-23.00000,0.00072,-0.00723,0.09042,0,438.31619,-0.00036,19510.58398,335.20151,362.68011,50,10053.00000,27582.00000,,,,
-150,0.10087,1.50631,393.16226,1105.2218,33.6555,100.0,2833.26807,37.55981,100,99.91608,100,-1.87531,67.08375,64.71405,217.66663,935.71472,1968.23108,2833.40845,312.05035,1002.18701,14.16912,14.51748,404.34521,45.12717,36.34796,12,11.77368,1.38718,0.27557,540833,540833,0,0,1,1,1,35.02502,37.63223,28.0273,0,1,54128.00000,0,715.94238,763.19324,0,1,2880,776.00,775.46088,1,11.82911,10,10,10,10,-3.98398,-1.90055,4.64753,6.46596,-20.00000,-8.00000,16432.00000,70,12900.75488,20,-23.00000,0.00000,-0.00723,0.07236,0,434.17334,-0.00181,19238.62500,328.54611,361.51141,0,10053.00000,27590.00000,,,,
-151,0.10145,1.50120,406.14667,1115.11975,33.6555,100.0,2824.70483,37.62669,0,99.91608,0,-1.87531,66.97360,64.71405,217.47586,934.41016,1969.44055,2834.53149,314.94138,1115.93726,14.09522,14.41345,404.19186,41.39007,41.68853,12,11.78131,1.38718,0.58304,540833,540833,0,0,1,1,1,35.28442,37.23754,28.03078,0,1,54122.00000,0,709.04541,763.19324,0,1,2880,779.00,779.14502,1,11.82677,10,10,10,10,-3.86177,-1.80260,4.81086,6.61838,-20.00000,0.00000,16130.86035,70,12841.39062,20,-23.00000,0.00123,67.06451,0.07236,0,432.69391,-0.00253,19103.83984,327.52542,358.94373,0,10053.00000,27577.00000,,,,
-152,0.10121,1.49610,406.14667,1105.2218,31.91024,100.0,2831.48022,35.65014,100,99.91608,0,-1.88294,67.01614,66.41668,217.85733,934.84497,1412.09595,2823.15845,313.38565,997.03217,13.93343,14.41345,402.76062,100.0,47.02911,12,11.78894,1.38870,0.27557,540833,540833,0,0,1,1,1,35.19287,36.90185,28.0247,0,1,54122.00000,0,719.37256,763.19324,0,1,2880,778.00,778.82092,1,11.84880,10,10,10,10,-3.40873,-1.71929,4.97480,6.52771,-20.00000,0.00000,16208.00000,70,13021.32910,20,-23.00000,0.00072,71.38309,72.48267,10,428.17398,-0.00109,18599.07227,324.88586,351.25958,0,10053.00000,27590.00000,,,,
-153,0.10087,1.47564,397.63785,993.95294,33.6555,100.0,2831.16211,37.07355,100,99.91608,0,-1.88294,65.94571,64.47754,217.13327,932.23584,639.28644,2827.23145,309.21936,1107.05811,13.85863,14.41345,403.68073,85.92541,96.26923,12,11.78894,1.38946,0.27557,540833,540833,0,0,1,1,1,35.08472,37.49695,28.02382,0,1,54118.00000,0,715.56397,763.19324,0,1,2880,779.00,777.96027,1,11.90466,10,10,10,10,-3.06926,-1.63125,4.76120,6.35096,-20.00000,0.00000,17232.06641,70,12552.22363,20,-23.00000,0.00072,73.65451,54.90454,0,425.97791,-0.00080,18197.65430,321.59671,343.81683,50,10053.00000,27577.00000,,,,
-154,0.10121,1.44911,406.14667,1105.2218,33.4603,100.0,1025.93042,35.81036,100,0.29907,100,-1.84479,66.70953,71.88568,217.28516,934.36047,6.14166,42.50578,314.33914,1105.4635,13.61771,14.40582,401.22708,89.98444,39.46838,12,11.78894,1.39023,0.27557,540833,540833,0,0,1,1,1,35.13183,36.90185,28.02821,0,1,54082.00000,0,725.87891,763.19324,0,1,2880,785.00,784.97424,1,11.97928,10,10,10,10,-2.87323,-1.80502,3.81038,6.15200,-7.00000,0.00000,16704.00000,70,11512.11426,20,-19.00000,0.00123,1.16466,62.78937,0,424.52371,0.00109,18071.02930,319.03601,340.47672,0,10053.00000,27582.00000,,,,
-155,0.10145,1.43507,397.63785,1001.99799,31.91024,100.0,152.47397,37.47474,0,0.29907,0,-1.87531,66.77344,69.89441,216.52220,933.19299,662.55621,931.18317,313.79694,994.42285,13.32145,14.40582,404.60083,36.38373,36.34796,12,11.78894,1.39099,0.58304,540833,540833,0,0,1,1,1,35.28442,36.90185,28.02649,0,1,54096.00000,0,712.82349,763.19324,0,1,2880,783.00,783.81195,1,12.01567,10,10,10,10,-2.88490,-1.83367,3.73064,6.16825,-22.00000,0.00000,15936.00000,70,9807.22266,20,-23.00000,0.00072,75.65106,65.0318,10,416.60953,0.00015,17899.84570,318.34958,335.16006,0,10053.00000,27570.00000,,,,
-156,0.10145,1.40840,397.63785,1105.2218,33.4603,100.0,32.97053,37.06211,0,0.29907,0,-1.87531,66.50931,73.43958,215.60551,931.80084,1983.47388,2834.11035,313.41553,1113.22656,12.83284,14.40582,404.08521,42.11186,41.56647,12,12.01782,1.39252,2.00516,540833,540833,0,0,1,1,1,35.28442,37.75737,28.02554,0,1,54109.00000,0,719.15283,763.19324,0,1,2880,779.00,779.53369,1,11.99235,10,10,10,10,-3.77735,-1.89640,3.72498,6.22510,-22.00000,0.00000,16336.00000,70,13225.71777,20,-23.00000,0.00072,73.06857,0.72336,0,412.31784,-0.00294,17862.70508,316.65152,331.55804,0,10053.00000,27562.00000,,,,
-157,0.10121,1.39978,405.06735,993.95294,33.6555,67.5385,774.80237,37.29786,0,0.29907,0,-1.86768,65.38486,66.58325,216.14072,931.36603,1253.55554,2512.16309,313.79694,1116.89392,12.89005,14.40582,404.03854,73.60924,99.62753,12,11.78894,1.39328,2.11155,540833,540833,0,0,1,1,1,35.19287,37.39014,28.02564,0,1,54102.00000,0,715.35645,763.19324,0,1,2880,781.00,782.22656,1,11.98221,10,10,10,10,-3.65804,-1.99687,3.74334,6.20431,-20.00000,-8.00000,15872.00000,70,10521.99609,20,-23.00000,0.00072,0.13745,0.05423,0,402.57587,-0.00043,17759.55273,313.87509,328.46780,0,10053.00000,27566.00000,,,,
-158,0.10087,1.38566,445.34219,1001.99799,31.91024,0.5381,2845.90503,35.40524,100,0.29907,0,-1.87531,65.82606,66.94183,216.33150,931.80243,1963.82690,33.96383,308.07492,1103.55005,12.67033,14.39819,403.27176,43.98192,65.25574,12,12.01782,1.39404,0.27557,540833,540833,0,0,1,1,1,35.13183,36.70349,28.02733,0,1,54116.00000,0,712.79907,763.19324,0,1,2880,775.00,777.16620,1,11.86875,10,10,10,10,-4.00121,-1.83816,4.23747,6.34468,-25.00000,-8.00000,15424.00000,70,11851.41797,20,-23.00000,-0.00166,71.38309,0.07236,0,396.37766,-0.00015,17681.93164,309.85684,328.73944,0,10053.00000,27566.00000,,,,
-159,0.10087,1.37957,405.06735,1001.99799,31.91024,86.29572,2815.75708,37.50538,100,0.29907,100,-1.87531,64.65572,68.36090,216.71291,930.49628,1970.71069,2823.86255,307.88422,992.68347,12.56888,14.17694,399.39352,44.96381,52.59857,12,12.01782,1.39481,0.58304,540833,540833,0,0,1,1,1,35.37598,36.90185,28.02561,0,1,54118.00000,0,709.26514,763.19324,0,1,2880,775.00,775.65985,1,11.85826,10,10,10,10,-3.93690,-1.87204,4.35410,6.42697,-22.00000,0.00000,15456.00000,70,11231.93457,20,-23.00000,0.00000,76.35995,55.23004,0,376.48499,-0.00260,17551.75195,307.38403,326.43863,0,10053.00000,27570.00000,,,,
-160,0.10087,1.37196,397.63785,993.95294,33.4603,100.0,326.37143,36.79611,0,0.29907,0,-1.87531,63.52969,65.88898,215.04857,928.75671,1974.52527,2826.38940,308.64716,997.03217,12.13269,14.16931,403.27176,45.40954,49.87488,12,11.78131,1.39633,2.17897,540833,540833,0,0,1,1,1,35.19287,36.90185,28.0299,0,1,54113.00000,0,712.30469,763.19324,0,1,2880,778.00,777.62561,1,11.84589,10,10,10,10,-4.02043,-1.78151,4.62585,6.44026,-22.00000,0.00000,15194.57031,70,12966.59766,20,-23.00000,0.00000,-0.00723,65.0318,0,357.66312,-0.00231,17459.35156,308.40781,324.65808,0,10053.00000,27554.00000,,,,
-161,0.10121,1.36322,406.14667,993.95294,33.4603,100.0,1085.07251,36.61999,100,0.29907,0,-1.88294,63.48420,66.25648,215.18706,927.88696,5.95089,33.23063,308.09619,1102.91223,11.31544,14.16931,400.30698,90.86281,42.28363,12,11.78894,1.39786,2.19248,540833,540833,0,0,1,1,1,35.19287,36.15417,28.03338,0,1,54067.00000,0,716.3269,763.19324,0,1,2880,784.00,784.55231,1,11.86754,10,10,10,10,-3.54090,-1.62140,4.28838,6.25723,-20.00000,0.00000,15341.24414,70,10903.18848,20,-23.00000,0.00123,57.7908,67.36475,0,356.57010,0.00109,17373.81250,303.98428,323.52890,0,10053.00000,27570.00000,,,,
-162,0.10121,1.35915,406.14667,1105.2218,33.4603,100.0,379.33841,36.6885,100,99.91608,0,97.18475,64.91846,64.71405,214.61488,927.47308,1955.45178,2673.44604,306.93054,1000.88245,10.82476,14.16931,402.70996,86.50633,99.48863,12,11.78894,1.39938,2.26321,540833,540833,0,0,1,1,1,35.08606,36.70349,28.02385,0,1,54104.00000,0,714.63623,763.19324,0,1,2880,779.00,780.88531,1,11.94790,10,10,10,10,-3.01352,-1.61746,4.02881,6.11407,-25.00000,0.00000,15254.76758,70,8424.57031,20,-23.00000,0.00000,64.79312,11.46555,0,348.04547,-0.00058,17299.17188,304.22659,322.56171,0,10053.00000,27552.00000,,,,
-163,0.10087,1.35223,406.14667,1001.99799,33.4603,100.0,1112.79529,35.0953,0,0.29907,0,-1.79901,63.69846,63.76801,213.85191,926.58234,1474.43774,2810.94116,307.31195,998.88034,10.39918,14.16168,402.91394,40.06373,31.61011,12,11.78894,1.40143,2.29063,540833,540833,0,0,1,1,1,35.19287,36.70349,28.02645,0,1,54108.00000,0,708.06885,763.19324,0,1,2880,777.00,778.86755,1,11.93687,10,10,10,10,-2.58774,-1.40099,4.01756,6.13562,-22.00000,0.00000,15035.22363,70,10201.36523,20,-23.00000,0.00000,71.80267,0.07236,0,341.44412,-0.00109,17283.24414,302.92117,320.60022,0,10053.00000,27552.00000,,,,
-164,0.10121,1.34781,405.06735,1105.2218,33.4603,100.0,32.97053,36.26317,0,0.29907,0,-1.87531,63.28683,64.83612,213.66115,926.18835,1977.00500,2825.54712,307.31195,1106.73914,9.54813,14.05487,402.66708,37.70428,41.45203,12,11.78894,1.40320,2.34695,540833,540833,0,0,1,1,1,35.08606,36.90185,28.02733,0,1,54094.00000,0,709.22241,763.19324,0,1,2880,780.00,781.41284,1,11.97446,10,10,10,10,-2.74688,-1.40833,3.79101,6.09402,-25.00000,0.00000,14894.51367,70,9022.56152,20,-23.00000,0.00000,60.64816,0.07236,0,342.22672,-0.00181,17181.98438,300.95502,318.86353,0,10053.00000,27554.00000,,,,
-165,0.03051,1.34182,405.06735,1115.11975,33.6555,60.7733,2720.95923,37.45541,0,0.29907,0,-1.83716,63.17112,66.58325,213.27974,924.84595,9.47676,31.97760,307.31195,1104.82556,8.92168,14.05487,401.32721,43.23649,47.02148,12,11.78131,1.40625,1.80603,540833,540833,0,0,1,1,1,35.45227,36.36779,28.02997,0,1,54067.00000,0,701.37329,763.19324,0,1,2880,783.00,783.93372,1,11.96759,10,10,10,10,-2.80591,-1.67097,3.69965,6.07024,-22.00000,16.00000,14590.07031,70,8475.40234,20,-23.00000,0.00000,64.28674,73.06134,0,335.18393,0.00094,17157.06250,293.00357,317.15048,0,10053.00000,27558.00000,,,,
-166,0.10121,1.33714,406.14667,993.95294,33.6555,100.0,2827.93359,35.85957,100,99.91608,100,-1.87531,62.43328,63.66119,213.47044,925.47083,30.36500,1043.83801,305.97733,993.98804,8.63352,14.04921,403.88519,41.36342,37.58392,12,12.01782,1.41006,0.58304,540833,540833,0,0,1,1,1,35.13183,36.09313,28.02902,0,1,54096.00000,0,712.58545,763.19324,0,1,2880,778.00,779.32397,1,11.97479,10,10,10,10,-2.74095,-1.64201,3.66309,6.04804,-22.00000,8.00000,14688.00000,70,8562.65430,20,-23.00000,0.00000,-0.00723,77.87183,0,330.17136,-0.00036,17009.18750,281.80777,316.43530,0,10053.00000,27554.00000,,,,
-167,0.10187,1.33215,406.14667,1115.11975,32.0,100.0,2831.86426,34.86622,100,0.29907,100,-1.88294,63.09311,63.76801,212.51678,923.97308,6.14166,37.93592,306.35831,994.20544,8.39934,14.04724,399.97281,32.86109,88.95264,12,11.78894,1.41693,0.27557,540833,540833,0,0,1,1,1,35.49804,36.04736,28.02733,0,1,54074.00000,0,702.37427,763.19324,0,1,2880,781.00,781.43921,1,11.98315,10,10,10,10,-2.88770,-1.68034,3.53344,5.94277,-22.00000,8.00000,14391.32812,70,8727.85059,20,-23.00000,0.00000,55.96788,63.65741,0,325.93579,0.00065,16934.46875,259.26791,315.68088,0,10053.00000,27558.00000,,,,
-168,0.10121,1.32968,405.06735,1001.99799,31.91024,99.91391,1139.08862,35.6799,100,99.91608,100,-1.88294,63.21753,63.42468,212.70749,922.66846,1979.33301,2838.60254,306.54907,1106.10132,8.08110,14.04724,401.37808,94.55677,99.78279,12,11.78894,1.42075,0.27557,540833,540833,0,0,1,1,1,35.37598,36.52039,28.03257,0,1,54113.00000,0,720.05005,763.19324,0,1,2880,771.00,772.30359,1,11.97331,10,10,10,10,-2.57635,-1.55012,3.69341,5.99208,-25.00000,0.00000,14371.56445,70,11265.08105,20,-23.00000,0.00000,62.37701,64.38074,0,318.98367,-0.05244,16872.81641,288.37695,314.10172,0,10053.00000,27547.00000,,,,
-169,0.10121,1.32613,393.16226,1105.2218,33.4603,8.87778,2826.67017,36.69628,100,99.91608,100,-1.88294,62.27994,62.36419,212.70749,921.41742,1978.94934,2838.76196,304.57812,1119.81433,7.70995,14.04724,399.14316,47.99609,99.79224,12,12.01019,1.42982,0.58304,540833,540833,0,0,1,1,1,35.36072,36.15417,28.03162,0,1,54112.00000,0,694.71435,763.19324,0,1,2880,771.00,771.04297,1,11.98699,10,10,10,10,-3.22260,-1.73701,3.61493,5.99373,-22.00000,56.00000,14035.53711,70,8683.52930,20,-24.00000,0.00000,71.47714,0.47021,0,322.07840,-0.00531,16801.55078,280.69446,311.47610,0,10053.00000,27552.00000,,,,
-170,0.10145,1.31693,397.63785,993.95294,33.4603,11.47031,2821.33569,37.14947,0,99.91608,0,-1.87531,61.89632,62.35657,211.56313,920.09839,6.52314,2489.24463,304.97949,997.03217,7.88149,12.75024,398.10895,50.43675,40.49835,12,12.01782,1.43707,1.97849,540833,540833,0,0,1,1,1,35.45227,36.36779,28.02216,0,1,54071.00000,0,718.55469,763.19324,0,1,2880,781.00,781.52454,1,12.00850,10,10,10,10,-2.70722,-1.53961,3.52792,5.88283,-20.00000,144.00000,13984.00000,70,7450.08105,20,-23.00000,0.00123,-0.00723,17.16223,0,314.85049,0.00000,16760.94336,255.49074,312.59988,0,10053.00000,27558.00000,,,,
-171,0.10087,1.31100,445.34219,1105.2218,31.91024,100.0,30.98430,35.94922,100,99.9237,0,0.91705,61.66684,62.71515,210.99088,920.05920,1961.36462,54.09340,305.10352,1120.1333,7.63353,12.75024,399.19778,40.22707,48.68469,12,11.78131,1.44586,0.27557,540833,540833,0,0,1,1,1,35.54382,36.36779,28.02389,0,1,54067.00000,0,716.05225,763.19324,0,1,2880,781.00,783.17023,1,11.98496,10,10,10,10,-2.76286,-1.56947,3.49519,5.90923,-25.00000,184.00000,13660.67773,70,7178.16064,20,-23.00000,0.00000,50.5136,70.58374,0,309.22104,-0.00007,16681.41602,267.73154,308.44968,0,10053.00000,27547.00000,,,,
-172,0.10087,1.30603,405.06735,993.95294,31.91024,35.69366,631.09808,37.17872,100,99.9237,0,-1.87531,61.69497,62.36419,210.60884,919.82257,1964.95544,2821.89722,304.06949,1004.7962,7.54522,12.51435,399.43799,40.90665,41.55884,12,11.78894,1.45432,0.58304,540833,540833,0,0,1,1,1,35.37598,36.33728,28.0273,0,1,54095.00000,0,704.90723,763.19324,0,1,2880,777.00,778.68744,1,12.00648,10,10,10,10,-2.77923,-1.52036,3.42709,5.86310,-25.00000,184.98871,13328.00000,70,7027.93750,20,-23.00000,0.00000,4.1739,0.05423,0,304.86658,-0.00101,16465.40234,276.18976,307.68127,0,10053.00000,27554.00000,,,,
-173,0.10121,1.30161,406.14667,993.95294,33.6555,100.0,1725.45984,37.48631,100,99.91608,0,-1.87531,61.21560,62.24213,210.41869,918.75458,1658.96497,2822.59912,302.90225,994.42285,7.29307,12.26959,400.30698,100.0,35.1654,12,11.78894,1.46588,0.27557,540833,540833,0,0,1,1,1,35.45227,36.15417,28.02909,0,1,54099.00000,0,715.13062,763.19324,0,1,2880,776.00,777.09515,1,12.00236,10,10,10,10,-3.06038,-1.54377,3.44506,5.86964,-25.00000,312.00000,13166.95410,70,5949.05371,20,-23.00000,0.00000,66.55093,66.13501,0,302.31461,-0.00087,16508.34180,264.11722,304.28146,50,10082.00000,27558.00000,,,,
-174,0.10087,1.29546,445.34219,1001.99799,31.91024,100.0,1475.45520,35.55412,100,99.91608,0,-1.86005,61.30883,62.71515,210.22798,918.92639,1977.19556,2836.91797,303.11584,1006.97046,6.93465,11.22410,398.62015,41.99477,47.13592,12,11.78894,1.50845,0.58304,540833,540833,0,0,1,1,1,35.63538,36.90185,28.02652,0,1,54110.00000,0,715.35034,763.19324,0,1,2880,749.00,748.93372,1,12.01111,10,10,10,10,-3.24837,-1.69959,3.46539,5.87973,-25.00000,442.59094,12992.33105,70,6572.67676,20,-23.00000,-0.00022,56.08362,76.20807,0,295.48843,-0.00383,16304.28516,262.53833,303.13580,0,10053.00000,27558.00000,,,,
-175,0.10087,1.28504,405.06735,993.95294,33.6555,100.0,2828.07373,37.09671,100,99.91608,0,-1.88294,61.59920,62.36419,209.46503,916.58026,1956.33264,2825.42065,302.09964,992.68347,6.99369,10.84290,398.36694,85.23666,77.41698,12,11.78131,1.53152,0.27557,540833,540833,0,0,1,1,1,35.58960,36.15417,28.02213,0,1,54102.00000,0,712.45727,763.19324,0,1,2880,771.00,773.92480,1,12.01180,10,10,10,10,-2.73421,-1.61310,3.32141,5.73817,-25.00000,466.02295,12936.62793,70,7277.02930,20,-23.00000,-0.00166,-0.00723,9.16885,0,294.54633,-0.00101,16272.77930,260.07220,301.77969,0,10082.00000,27562.00000,,,,
-176,0.10145,1.28389,397.63785,1105.2218,31.91024,100.0,2823.58179,35.66578,100,0.29907,0,13.90228,61.16334,62.36419,210.03720,912.03229,1976.24182,2833.54858,303.11584,1104.50671,6.89713,9.66034,397.94965,54.17514,42.28363,12,11.78894,1.64123,0.27557,540833,540833,0,0,1,1,1,35.54382,36.90185,28.02558,0,1,54103.00000,0,680.57861,763.19324,0,1,2880,771.00,772.03802,1,12.01667,10,10,10,10,-2.92203,-1.66769,3.49024,5.79514,-25.00000,536.00000,12961.20410,70,8273.14941,20,-23.00000,-0.00022,0.0217,69.93268,0,295.08951,-0.00289,16112.99316,272.44446,298.45142,0,10053.00000,27562.00000,,,,
-177,0.03051,1.27328,397.63785,1105.2218,33.4603,100.0,36.94299,35.87216,100,0.29907,100,-1.88294,61.49239,62.47863,210.41869,916.31067,1981.20117,2828.34937,302.73438,1118.21985,6.31729,10.01892,396.42212,45.05759,42.04711,12,11.78894,1.59535,0.27557,540833,540833,0,0,1,1,1,35.63538,36.90185,28.0273,0,1,54090.00000,0,719.73267,763.19324,0,1,2880,777.00,778.98859,1,12.04838,10,10,10,10,-2.65456,-1.70455,3.25839,5.66327,-25.00000,566.19928,12601.30762,70,6215.30469,20,-23.00000,-0.00166,54.57899,0.09042,10,286.70370,-0.00157,15902.88965,279.51349,295.75085,0,10053.00000,27574.00000,,,,
-178,0.10087,1.25724,397.63785,993.95294,31.91024,100.0,2829.33740,35.46322,100,0.29907,0,-1.88294,60.91246,62.00561,205.84102,908.31750,93.94829,1568.55688,302.54358,997.03217,7.02955,8.47015,397.34222,88.07262,45.00732,12,12.01782,1.56425,0.27557,540833,540833,0,0,1,1,1,35.63538,36.13979,28.02818,0,1,54074.00000,0,712.96997,763.19324,0,1,2880,780.00,780.76996,1,12.02305,10,10,10,10,-2.93040,-1.59304,3.33413,5.67503,-22.00000,609.44171,11904.00000,70,6146.75879,20,-19.00000,-0.00022,-0.00723,0.07236,0,280.92953,0.00072,15772.92383,272.13333,286.84543,0,10053.00000,27590.00000,,,,
-179,0.10087,1.23258,406.14667,1105.2218,31.91024,100.0,2829.19678,37.30015,100,0.29907,0,97.23052,61.40189,62.12005,192.59215,894.45959,211.45648,1158.70740,302.35287,1105.14465,7.12201,7.64618,395.80869,40.03876,99.66118,12,12.01019,1.50006,0.27557,540833,540833,0,0,1,1,1,35.69641,36.15417,28.02906,0,1,54062.00000,0,712.05444,763.19324,0,1,2880,780.00,782.48395,1,12.04638,10,10,10,10,-2.82767,-1.79869,2.41620,5.32867,-22.00000,722.03662,11717.21484,70,7120.91748,20,-19.00000,-0.00022,60.6192,69.80615,0,280.34818,0.00109,15416.02246,270.27332,292.39545,0,10053.00000,27582.00000,,,,
-180,0.10121,1.22769,405.06735,993.95294,33.4603,100.0,2824.41382,36.27358,100,99.91608,0,97.17712,60.99238,61.63420,177.74086,888.74829,1967.65613,2830.99683,300.98813,1000.0127,6.97386,8.23364,396.21689,43.14003,41.68091,12,11.78894,1.47415,0.27557,540833,540833,0,0,1,1,1,35.63538,36.90185,28.02821,0,1,54102.00000,0,701.69067,763.19324,0,1,2880,771.00,775.36267,1,12.03266,10,10,10,10,-2.68809,-1.60337,3.05882,5.61250,-22.00000,752.06488,11408.00000,70,8602.85352,20,-19.00000,-0.00166,-0.00723,77.92609,0,263.56323,-0.00123,15248.35449,283.98480,287.81488,0,10082.00000,27577.00000,,,,
-181,0.10121,1.21498,397.63785,993.95294,31.91024,100.0,2698.06006,35.66121,100,0.29907,0,5.99823,60.62223,62.24213,199.79703,900.92468,1628.45642,2827.79321,300.80746,1000.88245,7.09777,9.53969,396.88953,85.92434,40.51361,12,12.01782,1.45574,0.58304,540833,540833,0,0,1,1,1,35.69641,37.39014,28.03166,0,1,54092.00000,0,715.85083,763.19324,0,1,2880,776.00,778.34113,1,12.03689,10,10,10,10,-3.14727,-1.70170,3.02974,5.69159,-22.00000,862.98627,9344.00000,70,7500.52490,20,-19.00000,-0.00166,70.55121,63.82019,0,265.76401,-0.00036,14788.15723,283.35138,280.65659,50,10053.00000,27582.00000,,,,
-182,0.10145,1.20143,397.63785,993.95294,31.91024,100.0,2822.87988,35.52807,100,0.29907,0,-1.86005,60.66592,61.53259,195.92975,829.60516,1982.72705,2838.32178,300.82697,1002.18701,7.13703,7.64618,396.26877,47.59423,39.19373,12,12.01019,1.44732,0.58304,540833,540833,0,0,1,1,1,35.72693,37.75635,28.02649,0,1,54108.00000,0,708.3313,763.19324,0,1,2880,775.00,774.35248,1,12.03425,10,10,10,10,-2.95473,-1.69096,3.11800,5.76485,-22.00000,879.08118,9344.00000,70,9175.63574,20,-19.00000,-0.00166,1.62761,62.84363,0,269.80099,-0.00420,14094.39941,295.40515,273.51624,0,10082.00000,27577.00000,,,,
-183,0.10087,1.17526,405.06735,1001.99799,31.91024,100.0,2835.55322,35.38197,100,0.29907,100,-1.88294,60.70299,61.89117,174.24446,840.47705,25.49934,1384.87939,300.41595,992.24847,7.37980,7.64618,394.78638,44.70193,51.65253,12,12.01782,1.43372,0.27557,540833,540833,0,0,1,1,1,35.78796,37.70729,28.03081,0,1,54072.00000,0,715.13062,763.19324,0,1,2880,780.00,781.24243,1,12.02785,10,10,10,10,-3.25440,-1.79535,2.96941,5.71371,-22.00000,934.19971,9344.00000,70,8545.26172,20,-18.00000,-0.00166,70.08826,0.34363,0,252.42157,0.00094,14458.13867,278.90894,266.88986,0,10082.00000,27590.00000,,,,
-184,0.10121,1.17806,406.14667,1105.2218,33.6555,100.0,899.54382,35.63309,100,0.29907,100,-1.88294,60.38102,61.28845,196.30405,832.63977,1972.99939,2824.00293,300.41595,1105.4635,7.50145,8.82873,393.68051,40.09895,95.55969,12,11.78894,1.42825,0.27557,540833,540833,0,0,1,1,1,35.77270,37.74108,28.02213,0,1,54097.00000,0,715.75928,763.19324,0,1,2880,778.00,779.26965,1,12.03948,10,10,10,10,-3.53928,-1.75690,3.00243,5.71814,-25.00000,1026.87720,9344.00000,70,8521.11133,20,-18.00000,-0.00166,45.55846,67.54559,0,264.97366,-0.00101,13781.50586,293.24942,266.09750,0,10053.00000,27605.00000,,,,
-185,0.10145,1.11860,405.06735,1119.68103,33.4603,100.0,2823.86255,35.22633,100,99.91608,100,-1.88294,60.94530,61.29608,175.30513,831.79376,700.15558,2825.82788,300.06409,1104.82556,7.46390,7.64618,395.24344,93.68294,35.98938,12,11.78894,1.41922,0.27557,540833,540833,0,0,1,1,1,35.72693,37.83263,28.03078,0,1,54103.00000,0,709.15527,763.19324,0,1,2880,777.00,776.93542,1,12.01805,10,10,10,10,-3.06348,-1.74626,2.81800,5.72232,-22.00000,1075.95728,9344.00000,70,10935.78516,20,-18.00000,-0.00166,11.57408,68.59448,10,258.35934,-0.00065,14718.24121,293.78137,255.75081,0,10082.00000,27590.00000,,,,
-186,0.10087,1.12629,397.63785,1115.11975,31.91024,0.0,2835.79492,35.39723,0,99.91608,0,-1.88294,60.88447,61.64703,173.22537,836.34229,841.02612,2829.47778,299.68262,1000.44769,7.66733,7.64618,394.83820,88.37826,99.51252,12,11.78894,1.41177,0.27557,540833,540833,0,0,1,1,1,35.83374,37.90893,28.02996,0,1,54112.00000,0,704.54102,763.19324,0,1,2880,771.00,774.51520,1,11.99438,10,10,10,10,-2.96884,-1.74318,3.15082,5.74585,-22.00000,1184.17261,7600.00000,70,11180.97754,20,-18.00000,-0.00166,69.14062,73.94751,0,275.77628,-0.00101,14572.13672,294.82742,233.56122,0,10082.00000,27605.00000,,,,
-187,0.10087,1.13946,397.63785,1001.99799,33.6555,100.0,2827.09131,35.37701,0,99.91608,0,97.20763,60.64096,61.18164,169.98291,826.99585,1965.37012,2828.77710,298.91965,1107.05811,7.51951,0.28381,393.88507,41.55944,41.32995,12,11.78131,1.40778,0.27557,540833,540833,0,0,1,1,1,35.84900,37.92419,28.02642,0,1,54113.00000,0,718.7561,763.19324,0,1,2880,775.00,774.75006,1,11.99521,10,10,10,10,-3.63749,-1.62599,3.20235,5.88895,-22.00000,1565.32397,7600.00000,70,12391.09961,20,-18.00000,-0.00166,1.21527,0.05423,0,260.30676,-0.00152,13866.55273,299.83151,274.82404,0,10053.00000,27605.00000,,,,
-188,0.10121,1.08236,397.63785,993.95294,33.6555,100.0,33.24768,35.29347,0,0.29907,0,-1.88294,60.33305,61.17401,165.21454,820.47284,1914.95508,162.45755,299.87332,1103.23108,7.78643,7.40204,394.73502,32.67668,38.48419,12,11.78131,1.40396,0.27557,540833,540833,0,0,1,1,1,35.78796,37.90893,28.03341,0,1,54065.00000,0,724.15772,763.19324,0,1,2880,784.00,785.10657,1,11.98120,10,10,10,10,-3.41965,-1.50590,3.18072,5.88595,-22.00000,2259.27002,7600.00000,70,12335.23535,20,-18.00000,-0.00166,66.97049,0.07236,0,274.66263,0.00051,14923.93164,300.55447,250.04480,0,10053.00000,27605.00000,,,,
-189,0.10145,1.14580,406.14667,993.95294,31.91024,100.0,2595.62988,37.51911,100,0.29907,0,-1.87531,60.52363,61.29608,167.77159,828.41028,563.45312,32.97053,299.30112,996.16242,7.74682,0.28381,384.35962,97.42153,91.42455,12,12.01782,1.40244,0.27557,540833,540833,0,0,1,1,1,36.01685,37.93963,28.02639,0,1,54064.00000,0,709.06372,763.19324,0,1,2880,783.00,784.90344,1,11.96949,10,10,10,10,-3.20681,-1.47715,3.29465,5.85984,-20.00000,3245.86426,7431.69385,70,11023.45801,20,-17.00000,-0.00166,74.07407,2.64032,0,279.18063,0.00094,14608.44238,299.31589,252.38676,0,10053.00000,27605.00000,,,,
-190,0.10121,1.15228,406.14667,1105.2218,31.91024,100.0,416.53732,35.43728,0,99.91608,0,-1.87531,60.39271,61.05957,163.49919,821.25336,1954.87024,2825.40674,299.11041,993.55328,8.02757,0.28381,392.88031,35.97778,39.78119,12,12.01782,1.39786,0.58304,540833,540833,0,0,1,1,1,35.92529,38.01574,28.02645,0,1,54094.00000,0,709.50317,763.19324,0,1,2880,780.00,782.34174,1,11.99190,10,10,10,10,-3.23536,-1.35876,3.27829,5.89997,-20.00000,5044.34863,5584.00000,70,12421.43359,20,-17.00000,-0.00022,-0.00723,0.14465,0,284.61664,-0.00058,15071.69336,304.85892,263.25302,0,10053.00000,27605.00000,,,,
-191,0.10121,1.19591,405.06735,1105.2218,33.4603,61.64331,2823.02002,35.19429,100,0.29907,0,41.21552,60.26049,61.05957,169.70981,814.70837,1967.84973,2804.02515,297.58450,1104.82556,8.06371,0.28381,391.95230,48.34124,40.42968,12,11.78131,1.39633,0.27557,540833,540833,0,0,1,1,1,35.92529,38.09740,28.02905,0,1,54112.00000,0,715.58227,763.19324,0,1,2880,777.00,778.77789,1,11.96388,10,10,10,10,-3.20308,-1.34860,3.43092,5.96544,-22.00000,5119.52100,5584.00000,70,13831.08008,20,-17.00000,-0.00166,48.31453,41.41351,0,285.61551,-0.00145,14543.70605,305.48492,282.80542,50,10053.00000,27605.00000,,,,
-192,0.10145,1.20539,406.14667,1001.99799,31.91024,100.0,2833.54858,36.74423,0,0.29907,0,23.20251,60.18542,60.58655,126.61861,747.94061,1112.49316,2824.56445,295.77338,1105.14465,8.00808,7.29523,386.14807,44.01137,41.08581,12,12.01019,1.39404,2.16541,540833,540833,0,0,1,1,1,35.97107,38.06200,28.03172,0,1,54112.00000,0,730.0415,763.19324,0,1,2880,778.00,779.48090,1,11.99847,10,10,10,10,-2.88001,-1.32831,3.44226,5.84319,-20.00000,6163.93750,5584.00000,70,13746.02832,20,-17.00000,-0.00166,5.83043,66.98492,0,290.78076,-0.00065,15573.25781,304.42831,288.82999,0,10082.00000,27605.00000,,,,
-193,0.10187,1.21123,397.63785,1001.99799,33.6555,100.0,641.18085,36.74473,100,99.91608,100,97.21527,60.15472,60.82306,168.45700,813.94031,1960.02954,2826.86768,297.38098,993.55328,8.34448,0.28381,385.51175,34.65102,59.60236,12,11.78894,1.39328,0.27557,540833,540833,0,0,1,1,1,36.03211,38.47641,28.02905,0,1,54113.00000,0,715.64941,763.19324,0,1,2880,779.00,780.12665,1,11.99276,10,10,10,10,-2.90550,-1.32639,3.50436,5.97036,-20.00000,7056.06934,5584.00000,70,14157.53516,20,-17.00000,-0.00166,13.49826,2.02548,0,293.52832,-0.00145,15540.67773,309.98434,291.11832,0,10053.00000,27627.00000,,,,
-194,0.10121,1.21309,397.63785,1001.99799,33.6555,47.46831,2827.23145,37.59758,100,99.9237,0,-1.82953,60.08270,60.93750,143.45590,796.86267,6.71385,34.95676,297.77521,1106.73914,8.60423,0.28381,379.73788,96.7955,41.68091,12,11.78131,1.39099,0.27557,540833,540833,0,0,1,1,1,36.04736,38.25772,28.02733,0,1,54081.00000,0,726.08643,763.19324,0,1,2880,785.00,785.43567,1,11.99825,10,10,10,10,-2.71435,-1.31502,3.45724,5.97777,-20.00000,7904.00000,-160.00000,70,13925.24805,20,93.60428,-0.00022,-0.00723,71.57843,0,300.13162,0.00094,15838.26172,308.80255,292.78928,0,10053.00000,27627.00000,,,,
-195,0.10145,1.24987,406.14667,1105.2218,33.6555,100.0,2821.89722,35.649,100,0.29907,100,97.19238,60.05534,60.82306,167.50334,808.56824,295.13885,820.32422,297.96600,1003.05676,8.56636,7.28760,383.53351,41.07379,99.52746,12,11.78131,1.39023,0.58304,540833,540833,0,0,1,1,1,36.13892,38.53344,28.03088,0,1,54100.00000,0,712.69531,763.19324,0,1,2880,783.00,783.37823,1,12.01765,10,10,10,10,-2.59897,-1.29258,3.56009,5.97960,-20.00000,8208.00000,-160.00000,70,13858.90430,20,77.86237,-0.00166,72.99625,0.05423,0,299.53848,-0.00015,16218.52051,310.40759,294.63272,0,10053.00000,27627.00000,,,,
-196,0.03051,1.24533,406.14667,993.95294,33.4603,100.0,2833.83057,37.22793,100,0.29907,0,-1.87531,60.01482,60.70861,146.14075,811.02350,6.71385,31.97760,296.63086,994.85779,8.88999,7.40967,375.49017,34.00893,45.83893,12,11.78894,1.38794,0.27557,540833,540833,0,0,1,1,1,36.41358,38.38495,28.03081,0,1,54088.00000,0,701.30005,763.19324,0,1,2880,785.00,786.40039,1,11.99318,10,10,10,10,-2.51711,-1.20736,3.64634,6.06164,-20.00000,7904.00000,-160.00000,70,14249.81250,20,357.74603,-0.00166,-0.00723,70.89117,0,304.04901,0.00152,16235.05859,313.09030,297.20233,0,10053.00000,27627.00000,,,,
-197,0.10145,1.26404,397.63785,1105.2218,31.91024,0.0,86.51346,37.25552,100,100,0,-1.87531,59.95830,60.46447,154.73485,726.17804,1970.71069,2827.09131,295.86789,1114.34277,9.28756,0.28381,382.97867,96.12362,94.37714,12,11.78131,1.38641,0.58304,540833,540833,0,0,1,1,1,36.23047,39.77358,28.03257,0,1,54115.00000,0,705.27954,763.19324,0,1,2880,783.00,783.44043,1,12.02125,10,10,10,10,-2.50172,-1.21038,3.58169,6.07203,-20.00000,8970.96191,-160.00000,70,14331.68945,20,70.66448,-0.00166,63.83826,11.61026,0,309.93781,-0.00159,16388.68359,314.79282,303.36218,0,10053.00000,27627.00000,,,,
-198,0.10087,1.26716,405.06735,1001.99799,33.4603,100.0,2823.28174,37.32597,0,0.29144,0,-1.81427,59.76095,60.58655,136.46078,653.47986,87.22212,2280.60742,296.24939,997.03217,9.86210,0.28381,384.55188,41.92818,97.55096,12,11.78894,1.38336,0.27557,540833,540833,0,0,1,1,1,36.41358,39.03808,28.02389,0,1,54111.00000,0,711.60889,763.19324,0,1,2880,784.00,782.89343,1,12.01083,10,10,10,10,-2.51060,-1.21498,3.75636,6.09618,-7.00000,10328.00000,-160.00000,70,14555.94824,20,689.93781,-0.00022,74.23322,0.07236,0,306.98532,-0.00022,16620.78516,315.84747,306.50238,0,10053.00000,27627.00000,,,,
-199,0.10121,1.28056,406.14667,1115.11975,33.6555,100.0,29.99137,37.09911,100,0.29907,100,-1.87531,59.73898,60.35802,158.47757,793.07617,1960.49463,2824.14307,295.45697,997.90192,10.05866,0.28381,376.63879,94.07532,41.91742,12,12.01019,1.37955,0.27557,540833,540833,0,0,1,1,1,36.62720,39.94751,28.02733,0,1,54102.00000,0,704.96826,763.19324,0,1,2880,786.00,786.07483,1,12.01048,10,10,10,10,-2.34213,-0.79401,3.75257,6.10410,172.62967,11016.00000,-160.00000,70,14669.22949,20,426.22430,0.00000,58.18866,0.05423,0,313.28265,-0.00072,16666.44727,316.43210,308.24564,0,10052.00000,27627.00000,,,,
-200,0.10121,1.28806,406.14667,1105.2218,31.91024,100.0,389.18869,34.97609,100,0.29907,0,29.98505,59.71494,60.34241,112.12861,638.77313,1978.91248,2835.56274,294.90109,1105.78247,10.31898,0.28381,377.14841,49.61543,61.47919,12,11.78131,1.37573,0.58304,540833,540833,0,0,1,1,1,36.52039,40.27850,28.02733,0,1,54124.00000,0,718.86597,763.19324,0,1,2880,784.00,782.64532,1,12.00951,10,10,10,10,-2.56445,-0.98233,3.88137,6.16991,123.00000,11016.00000,-160.00000,70,14858.18848,20,294.91977,-0.00166,13.21614,30.74365,0,316.96832,-0.00333,16726.00195,318.68436,310.88272,0,10053.00000,27627.00000,,,,
-201,0.10145,1.29888,397.63785,1001.99799,33.6555,100.0,34.95676,37.30396,100,0.29907,0,-1.87531,59.46252,60.12116,140.77380,558.95618,1971.28284,2256.27417,295.29572,1104.50671,10.65456,7.29523,373.12201,95.2692,77.94341,12,11.78894,1.36658,0.27557,540833,540833,0,0,1,1,1,36.76452,39.48125,28.03253,0,1,54112.00000,0,697.84546,763.19324,0,1,2880,786.00,785.57227,1,12.02360,10,10,10,10,-2.41996,-1.01566,4.13586,6.14623,118.00000,11791.65430,-160.00000,70,14937.93945,20,922.04126,-0.00022,74.45746,0.07236,0,318.57437,-0.00109,16903.88672,319.21713,312.01547,0,10052.00000,27627.00000,,,,
-202,0.10121,1.30428,405.06735,1001.99799,33.6555,100.0,2832.55762,35.56965,0,99.91608,0,-1.80664,59.37706,59.82565,139.46542,585.46387,5.95089,1609.73840,294.53275,1120.1333,11.72691,0.28381,371.61829,48.00124,35.51636,12,11.78131,1.36581,0.27557,540833,540833,0,0,1,1,1,36.81030,39.03808,28.03426,0,1,54111.00000,0,697.61963,763.19324,0,1,2880,786.00,786.36163,1,12.00718,10,10,10,10,-2.36280,-1.08677,4.02158,6.21171,3767.32837,12711.72754,-160.00000,70,14883.19922,20,2608.89844,0.00000,73.62558,0.05423,0,323.49191,0.00029,17018.74414,319.42020,313.34357,0,10053.00000,27627.00000,,,,
-203,0.10087,1.31559,393.16226,1001.99799,31.91024,0.0,2820.06982,37.07317,0,0.29907,0,-1.88294,58.90385,59.74760,139.06924,539.17804,1964.03479,2825.12598,293.77029,1103.8689,11.86627,7.35537,374.16193,100.0,36.93543,12,11.78894,1.36505,0.27557,540833,540833,0,0,1,1,1,36.81030,38.33236,28.03595,0,1,54128.00000,0,712.8418,763.19324,0,1,2880,785.00,784.35840,1,11.98982,10,10,10,10,-2.32739,-0.85384,4.19538,6.25162,1972.91235,12576.00000,-160.00000,70,15085.47852,20,1395.36365,-0.00166,-0.00723,77.7995,0,323.24142,-0.00152,16990.43750,321.07745,315.33911,0,10052.00000,27627.00000,,,,
-204,0.03051,1.32065,406.14667,1001.99799,32.0,100.0,2448.56323,37.37365,0,99.91608,0,-1.88294,58.36969,57.52716,-15.60213,0.00000,133.23253,1927.01257,293.55045,993.55328,12.24166,7.28760,375.28629,40.67366,51.40839,12,12.01019,1.36429,0.27557,540833,540833,0,0,1,1,1,36.67297,38.05740,28.03162,0,1,54123.00000,0,722.27173,763.19324,0,1,2880,786.00,786.09662,1,11.96807,10,10,10,10,-1.77340,-0.58842,4.39017,6.31680,3650.41138,12840.00000,-160.00000,70,15171.50488,20,3247.14868,0.00000,-0.00723,69.80615,0,325.07193,-0.00036,17114.28320,321.45840,315.41467,0,10053.00000,27627.00000,,,,
-205,0.10121,1.32490,397.63785,993.95294,33.4603,100.0,1105.70447,35.07603,100,0.29907,0,-1.87531,57.41230,59.43910,161.98264,669.87122,1962.12769,2821.51123,292.39636,1002.62195,11.97415,7.64618,380.43146,36.12529,100.0,12,11.78131,1.36429,0.27557,540833,540833,0,0,1,1,1,36.94763,37.89367,28.02821,0,1,54129.00000,0,712.5061,763.19324,0,1,2880,786.00,785.15234,1,12.00336,10,10,10,10,-2.43146,-1.03077,4.31660,6.29285,3023.46143,12840.00000,-176.27275,70,15386.38770,20,2371.88550,-0.00166,0.50638,0.05423,0,328.20432,-0.00137,17071.00781,322.48541,316.95242,0,10052.00000,27627.00000,,,,
-206,0.10087,1.33267,406.14667,993.95294,33.4603,100.0,2819.51050,36.2236,0,99.91608,0,-1.88294,56.85284,57.51953,153.97620,658.31934,1963.08142,2833.40845,292.99622,990.50915,12.46317,7.64618,384.77994,41.25964,99.39912,12,11.78894,1.36429,0.27557,540833,540833,0,0,1,1,1,36.52039,37.97065,28.02561,0,1,54146.00000,0,702.20947,763.19324,0,1,2880,784.00,782.82770,1,11.94474,10,10,10,10,-2.45590,-1.07106,4.72592,6.48841,3481.89136,12840.00000,-208.00000,70,15468.62695,20,1784.58557,-0.00166,-0.00723,70.47528,0,329.37515,-0.00202,17222.30469,323.58185,318.53976,0,10053.00000,27627.00000,,,,
-207,0.10121,1.33941,406.14667,993.95294,33.6555,100.0,716.48132,35.60246,0,0.29907,0,-1.87531,56.33494,57.16857,122.34082,697.25275,452.39410,1429.57397,292.81613,1005.23102,12.70501,7.64618,391.61246,37.01464,99.44305,12,12.01019,1.36353,0.27557,540833,540833,0,0,1,1,1,36.41358,37.83263,28.02297,0,1,54117.00000,0,705.96313,763.19324,0,1,2880,788.00,788.18976,1,11.95513,10,10,10,10,-2.64640,-0.88622,4.50251,6.56548,3547.07300,12840.00000,-288.00000,70,15336.40820,20,3299.54175,-0.00022,68.83682,68.16046,0,334.09341,-0.00007,17270.47070,324.96399,319.31610,0,10052.00000,27627.00000,,,,
-208,0.10121,1.34379,406.14667,993.95294,33.6555,100.0,2828.10449,37.11425,100,0.29907,0,-1.87531,56.51155,57.03888,166.34879,782.51056,817.01135,2826.95093,291.11823,1106.10132,12.69137,7.64618,387.02994,46.3413,81.97173,12,11.78894,1.36276,0.20233,540833,540833,0,0,1,1,1,36.52039,37.69531,28.03253,0,1,54135.00000,0,702.05688,763.19324,0,1,2880,786.00,786.27441,1,11.94371,10,10,10,10,-2.61278,-1.13675,4.42110,6.52600,5145.83789,13752.00000,-288.00000,70,15657.20508,20,3545.07446,0.00000,0.09402,72.06671,0,334.52960,-0.00109,17309.32422,325.25476,321.59677,0,10052.00000,27627.00000,,,,
-209,0.10087,1.34719,406.14667,993.95294,31.91024,100.0,145.77501,37.03987,0,99.91608,0,97.21527,56.13581,56.93178,147.57944,789.18030,1981.77332,2830.74121,291.29022,999.20648,12.90442,9.07288,395.34866,42.5085,38.94958,12,11.78894,1.36276,0.20233,540833,540833,0,0,1,1,1,36.09313,37.63427,28.02385,0,1,54133.00000,0,716.30859,763.19324,0,1,2880,787.00,787.41510,1,11.93923,10,10,10,10,-3.17844,-0.93876,4.63532,6.82058,2552.57617,13601.77734,-288.00000,70,15783.81348,20,2225.92261,-0.00166,74.76852,0.07236,0,339.88065,-0.00231,17387.96094,328.06790,321.05792,0,10052.00000,27627.00000,,,,
-210,0.10145,1.34946,406.14667,993.95294,33.4603,3.56526,1097.01807,35.96344,0,0.29907,100,-1.87531,55.73627,57.04651,160.84915,822.64716,5.95089,30.98430,291.48102,991.81366,12.93243,7.64618,396.13718,31.83783,85.99243,12,12.01019,1.36200,0.20233,540833,540833,0,0,1,1,1,36.13892,36.52039,28.03253,0,1,54092.00000,0,709.1919,763.19324,0,1,2880,793.00,793.93207,1,11.91530,10,10,10,10,-2.94071,-0.97579,4.32945,6.64080,4680.97900,13752.00000,-288.00000,70,15812.13965,20,3718.04077,0.00000,74.59491,61.39685,0,343.73978,0.00304,17502.28125,327.16589,322.37900,0,10052.00000,27627.00000,,,,
-211,0.03051,1.35270,405.06735,1105.2218,33.4603,32.2304,2830.97925,35.84278,0,99.91608,0,-1.88294,56.07192,55.04440,161.35838,818.65625,5.95089,543.51202,264.96042,1104.18787,13.29798,8.34808,397.14099,88.31348,85.76354,12,12.01782,1.36124,0.20233,540833,540833,0,0,1,1,1,35.87951,36.04427,28.02993,0,1,54120.00000,0,715.93018,763.19324,0,1,2880,788.00,788.58588,1,11.89830,10,10,10,10,-3.10107,-0.93461,4.32275,6.69655,3981.91309,13699.08789,-288.00000,70,16021.36328,20,3592.87354,-0.00166,73.35794,0.16278,0,341.04959,0.00109,17474.24414,328.18829,323.19620,0,10052.00000,27627.00000,,,,
-212,0.10145,1.35770,393.16226,1001.99799,33.4603,100.0,1120.72363,36.24905,0,99.91608,0,-1.88294,55.31594,53.86505,168.07553,817.42853,1958.31299,2826.81055,263.24194,993.11829,13.45061,8.85081,397.49252,94.37023,99.8476,12,11.78131,1.36124,0.20233,540833,540833,0,0,1,1,1,35.86426,36.00158,28.02645,0,1,54139.00000,0,712.854,763.19324,0,1,2880,787.00,786.83600,1,11.90304,10,10,10,10,-2.94958,-0.91550,4.31316,6.54277,4651.52686,13752.00000,-288.00000,70,16096.79297,20,2992.55859,-0.00166,-0.00723,46.49518,0,345.25507,-0.00109,17483.14453,330.93228,325.42133,0,10052.00000,27627.00000,,,,
-213,0.10087,1.36122,406.14667,1105.2218,33.6555,100.0,519.97821,36.97361,0,0.29907,0,-1.82953,53.05258,54.05510,165.97743,834.53699,6.33237,33.96383,276.08966,1001.7522,13.60899,9.98802,399.11539,45.77536,38.85803,12,12.01782,1.36047,0.20233,540833,540833,0,0,1,1,1,35.78796,35.95581,28.03341,0,1,54104.00000,0,708.70361,763.19324,0,1,2880,793.00,793.42438,1,11.90500,10,10,10,10,-3.33765,-1.08474,4.33898,6.55207,4916.77148,13752.00000,-288.00000,70,16057.88477,20,3627.92749,-0.00022,66.72455,74.81549,10,346.24866,0.00202,17593.42969,332.06708,324.27179,0,10052.00000,27627.00000,,,,
-214,0.10121,1.36425,405.06735,993.95294,31.91024,100.0,2824.99609,37.18647,0,0.29907,0,-1.88294,52.97292,53.27759,168.64778,825.25629,95.79637,1106.86353,263.44296,1122.36572,13.86720,10.01892,400.30698,100.0,36.5921,12,11.78894,1.36047,0.20233,540833,540833,0,0,1,1,1,35.63538,35.88401,28.02902,0,1,54120.00000,0,726.3794,763.19324,0,1,2880,789.00,789.82745,1,11.89589,10,10,10,10,-3.12301,-0.93121,4.14310,6.36823,3831.17969,13712.00000,-288.00000,70,16177.18262,20,3522.80713,-0.00166,63.27402,5.42532,0,350.19586,0.00058,17597.20703,329.80997,325.82361,0,10052.00000,27605.00000,,,,
-215,0.10121,1.36583,397.63785,993.95294,31.91024,0.0,2819.08276,35.89047,0,99.91608,0,-1.87531,52.84446,53.27759,172.46242,830.90973,6.14166,33.96383,255.90274,1120.45215,13.98854,10.63599,400.92157,38.62051,99.44305,12,11.78894,1.35971,0.20233,540833,540833,0,0,1,1,1,35.58960,35.83374,28.02301,0,1,54108.00000,0,705.52978,763.19324,0,1,2880,792.00,791.64404,1,11.87090,10,10,10,10,-3.49990,-1.10876,4.17428,6.44433,4951.32080,13672.42480,-288.00000,70,16352.21387,20,3680.13257,-0.00022,67.59982,29.18842,0,351.48505,0.00174,17633.53906,331.50391,326.09076,0,10052.00000,27605.00000,,,,
-216,0.10145,1.36998,406.14667,1001.99799,31.91024,0.0,1510.01819,37.19601,100,0.29907,0,-1.88294,52.28978,53.13412,177.85881,834.82361,307.51938,2823.86255,257.57602,1104.18787,14.26309,10.72845,403.68073,45.79326,55.92499,12,11.78131,1.35895,0.20233,540833,540833,0,0,1,1,1,35.54382,35.81847,28.03078,0,1,54125.00000,0,723.02856,763.19324,0,1,2880,789.00,788.71851,1,11.88705,10,10,10,10,-3.31988,-1.18760,3.98054,6.37675,5112.20898,13560.10742,-288.00000,70,16274.80176,20,3456.10474,-0.00022,0.90422,3.23712,0,354.78445,-0.00007,17670.19531,333.01846,327.21841,0,10052.00000,27605.00000,,,,
-217,0.10121,1.37402,405.06735,993.95294,33.6555,100.0,599.90356,37.27104,100,99.91608,0,97.23052,52.18184,52.45361,196.43323,839.17230,1977.19556,2835.23340,253.94347,1121.09009,14.14684,12.27722,404.49857,91.92997,99.41917,12,11.78131,1.35895,0.20233,540833,540833,0,0,1,1,1,35.36072,35.72693,28.02476,0,1,54152.01562,0,722.60742,763.19324,0,1,2880,787.00,787.02533,1,11.86402,10,10,10,10,-3.74148,-1.10238,4.38784,6.53562,3815.37378,12840.00000,-288.00000,70,16551.40430,20,3104.68530,-0.00166,69.18402,0.05423,10,354.29327,-0.00217,17695.90430,336.31158,328.81485,0,10052.00000,27590.00000,,,,
-218,0.03051,1.37300,405.06735,993.95294,33.4603,100.0,169.54572,35.88867,0,0.29907,0,-1.87531,51.76021,52.45361,171.50876,847.04242,29.98352,32.97053,253.83748,996.59735,14.08201,11.68213,405.26532,41.8302,45.3659,12,11.78894,1.35818,0.20233,540833,540833,0,0,1,1,1,35.37598,35.66589,28.03081,0,1,54096.00000,0,691.38184,763.19324,0,1,2880,796.00,794.78259,1,11.83611,10,10,10,10,-3.72243,-0.99119,4.29082,6.51069,4586.75049,12840.00000,-288.00000,70,16660.72656,20,3537.93237,-0.00022,0.0434,66.37006,0,362.85541,0.00246,17780.46484,335.55109,328.33603,0,10027.00000,27605.00000,,,,
-219,0.10145,1.37810,397.63785,1115.11975,33.6555,100.0,2827.51245,36.05183,100,99.91608,0,-1.88294,51.78030,52.10266,197.99834,836.99799,1973.38098,2837.55811,251.04213,1105.78247,14.38085,12.26975,405.46979,42.40053,47.50214,12,11.78131,1.35742,0.20233,540833,540833,0,0,1,1,1,35.36072,35.63538,28.02649,0,1,54161.75781,0,725.93994,763.19324,0,1,2880,786.00,785.77063,1,11.86495,10,10,10,10,-3.39994,-1.22608,4.34569,6.30918,3897.08643,12504.06934,-288.00000,70,16754.78125,20,1535.62390,-0.01237,76.89526,0.05423,0,364.75549,-0.00231,17792.31836,337.24551,329.49591,0,10052.00000,27605.00000,,,,
-220,0.10087,1.38020,397.63785,1105.2218,33.4603,100.0,199.83713,35.92606,100,99.91608,0,-1.87531,51.87598,52.10266,202.02638,852.63763,1977.53467,2836.91797,249.32861,1003.05676,14.32388,12.39166,405.92987,43.44481,46.7926,12,12.01782,1.35666,0.20233,540833,540833,0,0,1,1,1,35.45227,35.55908,28.02645,0,1,54148.00000,0,716.33911,763.19324,0,1,2880,787.00,786.51440,1,11.84110,10,10,10,10,-3.80406,-1.05600,4.35724,6.37402,3863.48779,12840.00000,-288.00000,70,17026.64062,20,1210.84253,-0.00166,12.26129,0.05423,0,360.29694,-0.00224,17856.28906,339.89471,330.56708,0,10051.00000,27590.00000,,,,
-221,0.03051,1.38365,405.06735,993.95294,33.4603,53.22388,2825.82666,36.69323,100,0.29907,100,-1.87531,51.69956,52.10266,208.31032,902.22931,369.77942,2815.72925,248.75636,997.40363,14.33887,12.75024,406.38989,39.72518,99.7502,12,11.78894,1.35590,0.17029,540833,540833,0,0,1,1,1,35.43700,35.37598,28.02389,0,1,54128.00000,0,712.8418,763.19324,0,1,2880,788.00,788.42303,1,11.84316,10,10,10,10,-3.49189,-1.13451,3.96635,6.25995,4706.50635,12360.51660,-288.00000,70,16942.02148,20,3500.63159,-0.00166,74.62384,1.10315,0,359.79358,0.00015,17870.71094,338.16061,330.94531,0,10051.00000,27605.00000,,,,
-222,0.03051,1.38535,406.14667,1001.99799,32.0,100.0,2830.60083,37.56935,100,0.29907,0,97.20763,51.67873,52.09503,202.78926,905.27338,1949.66138,2831.58350,246.84586,993.11829,14.46650,12.75024,406.95221,42.87314,99.33164,12,11.78894,1.35513,0.17029,540833,540833,0,0,1,1,1,35.45227,35.46753,28.02905,0,1,54137.00000,0,716.43066,763.19324,0,1,2880,787.00,787.39520,1,11.84414,10,10,10,10,-3.54435,-1.14147,4.26488,6.27213,3571.89966,11928.00000,-288.00000,70,16994.51562,20,2835.58936,-0.00166,71.5567,25.66186,0,361.45801,-0.00022,17906.71680,344.23840,331.97272,0,10052.00000,27590.00000,,,,
-223,0.10087,1.38833,397.63785,1105.2218,33.4603,100.0,300.72818,37.31083,0,0.29907,0,-1.88294,51.43124,52.09503,187.84869,870.30054,131.37773,1239.93445,249.13785,1107.37695,14.45357,13.45978,407.61670,41.73975,45.24383,12,11.78894,1.35437,0.17029,540833,540833,0,0,1,1,1,35.49804,35.49804,28.02649,0,1,54104.00000,0,708.69751,763.19324,0,1,2880,792.00,792.05908,1,11.83711,10,10,10,10,-3.32408,-1.19413,4.30054,6.28215,3736.37402,11744.87695,-288.00000,70,17186.18359,20,2016.45068,-0.00166,-0.00723,0.05423,0,367.84702,0.00159,17939.46680,340.07886,331.16266,0,10027.00000,27590.00000,,,,
-224,0.10121,1.39087,445.34219,993.95294,32.0,13.49717,2834.67188,36.04344,100,0.29907,100,-1.88294,51.47626,51.98059,208.56657,890.31116,6.14166,2831.30273,247.20261,1004.36145,14.62999,12.75024,406.79886,41.38315,99.46733,12,11.79657,1.35361,0.17029,540833,540833,0,0,1,1,1,35.37598,35.16236,28.03078,0,1,54127.00000,0,708.82568,763.19324,0,1,2880,787.00,787.04492,1,11.83165,10,10,10,10,-3.50901,-1.23629,4.18882,6.31096,5194.80908,11280.00000,-288.00000,70,17469.68359,20,3513.79297,0.00000,-0.00723,61.16174,0,366.60645,0.00029,17991.85352,335.93445,333.14920,0,10052.00000,27605.00000,,,,
-225,0.10121,1.39467,406.14667,993.95294,31.91024,100.0,845.57507,35.99347,100,0.29907,100,-1.88294,51.35389,51.98059,207.43610,905.70837,1959.07581,873.86230,247.00584,993.55328,14.36697,13.45215,408.10812,44.80502,40.62042,12,11.78131,1.35275,0.17029,540833,540833,0,0,1,1,1,35.58960,35.13183,28.03162,0,1,54115.00000,0,712.323,763.19324,0,1,2880,789.00,789.15204,1,11.82884,10,10,10,10,-3.76311,-1.25190,4.53726,6.30678,2722.76416,11159.65430,-288.00000,70,17206.94727,20,1029.96570,-0.00166,0.03616,65.53815,0,365.14005,0.00072,18033.94531,343.28204,332.11154,0,10027.00000,27590.00000,,,,
-226,0.03051,1.39819,397.63785,993.95294,33.6555,100.0,2828.64771,35.80197,100,0.29907,100,-1.87531,51.27754,51.98059,206.98546,906.57819,499.25079,35.81068,246.46756,1115.29944,14.38831,12.75024,407.36115,96.4978,38.65204,12,12.01782,1.35132,0.17029,540833,540833,0,0,1,1,1,35.72693,35.23864,28.02385,0,1,54100.00000,0,715.24048,763.19324,0,1,2880,792.00,792.25256,1,11.84384,10,10,10,10,-3.70511,-1.25507,3.86485,6.28402,2846.37256,11280.00000,-288.00000,70,17341.40625,20,3089.21045,-0.00166,-0.00723,0.05423,0,384.21658,0.00210,18024.05469,341.36362,334.37787,50,10027.00000,27605.00000,,,,
-227,0.10087,1.40030,405.06735,1001.99799,31.91024,2.84054,2825.68750,37.4638,100,0.29907,0,97.20763,51.17081,51.97296,205.07814,901.73688,555.37561,884.66333,246.65834,991.37872,14.58943,13.45978,407.84622,41.75368,42.85583,12,12.01782,1.35055,0.17029,540833,540833,0,0,1,1,1,35.63538,35.08606,28.02561,0,1,54107.00000,0,701.35498,763.19324,0,1,2880,790.00,790.86084,1,11.83895,10,10,10,10,-3.49451,-1.20928,4.10682,6.32815,2929.71533,10590.01855,-288.00000,70,17323.19922,20,1764.89160,-0.00166,69.82785,19.65784,10,378.30945,0.00109,18065.09570,339.72580,333.26334,0,10027.00000,27605.00000,,,,
-228,0.10145,1.40255,397.63785,1001.99799,32.0,100.0,2828.81982,36.95797,100,99.91608,0,-1.88294,51.21366,50.79803,209.68593,856.55664,1978.14929,2837.81543,241.30434,1118.85767,14.43970,13.58185,408.94574,100.0,49.0509,12,12.01782,1.34903,0.17029,540833,540833,0,0,1,1,1,35.69641,35.16236,28.03253,0,1,54147.00000,0,708.61816,763.19324,0,1,2880,786.00,785.52649,1,11.84851,10,10,10,10,-3.02997,-1.02813,4.13956,6.24351,3679.26685,9192.00000,-288.00000,70,17828.14844,20,576.76324,-0.00166,25.74509,76.15381,0,390.30649,-0.00246,17976.86523,345.01825,335.57867,0,10027.00000,27590.00000,,,,
-229,0.10087,1.41315,405.06735,993.95294,33.4603,100.0,2834.01978,35.67772,100,0.29907,0,48.61603,51.14845,51.91955,205.84102,900.48975,1962.98254,2829.66284,242.61584,995.2926,14.59753,13.93280,408.79242,39.6576,38.01117,12,11.78894,1.34827,0.20233,540833,540833,0,0,1,1,1,35.54382,35.13183,28.02733,0,1,54133.00000,0,702.2644,763.19324,0,1,2880,786.00,785.45996,1,11.85496,10,10,10,10,-3.26859,-1.23469,3.95006,6.26212,2274.16357,9192.00000,-288.00000,70,17444.63086,20,651.56073,-0.01237,68.83682,0.39786,0,383.09921,-0.00022,18130.25781,342.68491,337.25305,0,10027.00000,27605.00000,,,,
-230,0.10145,1.39870,406.14667,993.95294,31.91024,100.0,29.99137,36.97273,100,99.91608,0,-1.88294,51.29376,49.00346,184.66913,830.48517,6.14166,2841.69360,197.60960,1101.31775,14.25585,12.50610,407.05441,44.58583,44.88525,12,11.78894,1.34674,0.20233,540833,540833,0,0,1,1,1,35.63538,35.25391,28.02642,0,1,54111.00000,0,708.65478,763.19324,0,1,2880,788.00,787.26959,1,11.83131,10,10,10,10,-3.13775,-1.13048,4.11071,6.29012,5294.89648,9808.00000,-288.00000,70,18809.62891,20,3659.16895,0.00682,67.86746,1.33826,0,361.68198,-0.00087,18608.70508,334.65671,347.14621,0,10052.00000,27605.00000,,,,
-231,0.10145,1.40893,397.63785,993.95294,32.0,100.0,2026.88879,37.08653,100,0.29907,100,-1.83716,51.09341,50.79803,204.69666,909.92316,85.42516,1286.14502,242.65285,1106.42029,14.18058,13.45215,409.55936,91.34453,89.65454,12,11.78894,1.34674,0.17029,540833,540833,0,0,1,1,1,35.72693,35.19287,28.02824,0,1,54100.00000,0,708.59985,763.19324,0,1,2880,790.00,790.17908,1,11.83788,10,10,10,10,-3.55311,-1.24151,4.06958,6.34033,3745.06616,8576.00000,-288.00000,70,18326.11523,20,1010.37494,-0.00022,71.64352,37.43487,0,379.41306,0.00181,18189.88672,343.84204,335.50320,0,10027.00000,27605.00000,,,,
-232,0.10145,1.41485,397.63785,993.95294,31.91024,100.0,33.96383,37.28222,100,0.29907,0,-1.87531,50.94260,50.79803,207.55763,909.18732,1970.13855,2826.59082,229.38345,1105.14465,14.29658,13.93202,415.07980,40.20434,42.29126,12,11.78894,1.34522,0.20233,540833,540833,0,0,1,1,1,35.72693,35.13183,28.03422,0,1,54118.00000,0,730.08423,763.19324,0,1,2880,788.00,789.07135,1,11.87996,10,10,10,10,-3.52578,-1.15719,3.93227,6.24553,1634.47595,7679.31836,-288.00000,70,18071.20898,20,1110.40161,-0.00166,3.1033,63.58502,0,371.16702,-0.00015,18228.21680,346.52527,338.40054,0,10027.00000,27590.00000,,,,
-233,0.10087,1.41389,405.06735,1105.2218,33.6555,0.50429,2834.17944,37.30663,100,99.91608,0,97.20001,50.89537,50.79803,207.93912,909.62225,290.23236,2830.60083,199.90997,1120.1333,14.11475,13.92517,410.05969,41.16845,39.1098,12,11.78894,1.34445,0.20233,540833,540833,0,0,1,1,1,35.86426,35.10132,28.03342,0,1,54126.00000,0,726.3977,763.19324,0,1,2880,786.00,786.74030,1,11.86279,10,10,10,10,-3.46039,-1.28268,4.05786,6.29758,3005.03418,8208.00000,-288.00000,70,18169.93555,20,1413.74634,-0.00022,67.82407,0.05423,0,385.74020,0.00007,18394.96484,346.01123,336.98590,0,10027.00000,27605.00000,,,,
-234,0.10145,1.42487,406.14667,1119.68103,31.91024,100.0,2829.05664,35.4575,0,0.29907,0,-1.86768,50.72604,50.79803,201.07265,905.27338,153.11237,2823.30103,243.98799,997.83844,14.14228,12.75024,409.86584,44.03655,34.91363,12,11.78894,1.34299,0.20233,540833,540833,0,0,1,1,1,36.07788,35.16236,28.0351,0,1,54096.00000,0,723.38867,763.19324,0,1,2880,789.00,790.28058,1,11.87728,10,10,10,10,-3.46907,-1.26328,4.13237,6.27439,4098.54053,7438.92236,-288.00000,70,17743.86133,20,1554.30603,0.00000,-0.00723,0.09042,0,384.95010,0.00195,18291.54688,348.31323,336.68674,50,10027.00000,27605.00000,,,,
-235,0.10145,1.41902,406.14667,993.95294,33.6555,100.0,2839.43652,35.44758,0,0.28381,100,-1.88294,50.88385,50.79803,204.88736,914.40594,10.34906,2808.08813,235.57886,1106.10132,13.94216,12.75024,412.62619,98.0769,59.72442,12,11.78894,1.34140,0.17029,540833,540833,0,0,1,1,1,35.97107,35.08606,28.02655,0,1,54110.00000,0,704.70581,763.19324,0,1,2880,787.00,788.00647,1,11.83760,10,10,10,10,-3.51823,-1.27954,4.07721,6.39979,2513.56348,4649.47461,-288.00000,70,18376.58203,20,3213.26538,-0.00166,-0.00723,0.09042,0,370.78958,0.00275,18423.54102,354.05286,336.14444,0,10027.00000,27627.00000,,,,
-236,0.10145,1.42032,397.63785,1001.99799,31.91024,9.02975,1569.08228,37.34402,100,0.29907,0,-1.88294,50.63415,50.79803,202.40779,902.22931,107.01206,2697.32861,242.46214,1002.18701,14.04905,12.75024,410.87839,33.09435,89.44092,12,12.01019,1.34064,0.20233,540833,540833,0,0,1,1,1,36.03211,35.08606,28.03166,0,1,54092.00000,0,722.07031,763.19324,0,1,2880,790.00,790.73749,1,11.86183,10,10,10,10,-3.45069,-1.23977,4.08383,6.35483,3334.69971,7330.28906,-288.00000,70,18343.46484,20,1070.66492,0.00000,63.08594,3.67117,0,391.70450,0.00181,18377.78906,348.84924,339.88358,0,10026.00000,27605.00000,,,,
-237,0.10087,1.42386,405.06735,1115.11975,31.91024,100.0,1905.49304,37.33868,0,99.91608,0,97.19238,49.99464,50.79803,202.59856,896.14105,1977.19556,2834.67188,198.17241,994.85779,13.95512,12.75024,417.59512,100.0,42.98553,12,11.78894,1.33987,0.27557,540833,540833,0,0,1,1,1,36.18469,35.23864,28.02733,0,1,54132.00000,0,715.85083,763.19324,0,1,2880,786.00,786.16125,1,11.88752,10,10,10,10,-3.37322,-1.04924,4.30356,6.36160,113.00000,5644.14307,-192.00000,70,18459.13867,20,460.90070,-0.00166,44.27083,35.13818,0,381.34369,-0.00109,18300.65039,355.45944,345.50955,50,10027.00000,27605.00000,,,,
-238,0.10087,1.42792,406.14667,1105.2218,33.4603,0.0,2832.70654,36.52538,100,99.91608,0,-1.87531,50.60395,50.79803,195.54198,893.53174,1985.14075,2844.26636,239.21747,998.27319,13.96288,13.45978,420.68094,94.96723,58.90045,12,12.01019,1.33759,0.20233,540833,540833,0,0,1,1,1,36.01685,35.14710,28.02993,0,1,54138.00000,0,711.9751,763.19324,0,1,2880,784.00,783.68787,1,11.88283,10,10,10,10,-3.42158,-1.23285,4.17745,6.41680,181.88293,4604.57080,-208.00000,70,18928.72461,20,118.59927,-0.00166,69.6904,6.11258,0,395.68634,-0.00347,18323.85742,356.01666,341.87823,0,10027.00000,27605.00000,,,,
-239,0.10121,1.42868,397.63785,993.95294,33.4603,100.0,2843.81836,35.7933,100,0.29907,0,-1.83716,50.71188,50.79803,206.22250,910.49207,40.66567,2824.71069,206.42931,987.46484,13.83938,13.68866,417.17404,47.33222,35.27984,12,11.77368,1.33530,0.20233,540833,540833,0,0,1,1,1,36.21521,35.07080,28.0273,0,1,54115.00000,0,719.47022,763.19324,0,1,2880,785.00,785.92896,1,11.86144,10,10,10,10,-2.83099,-1.17585,4.18440,6.34240,153.98158,3406.40356,-160.00000,70,18246.76758,20,1494.68201,-0.00166,0.72339,4.21368,0,372.33521,0.00152,18589.75977,351.72949,341.24564,0,10027.00000,27605.00000,,,,
-240,0.10121,1.43221,406.14667,1105.2218,33.6555,100.0,2840.28711,35.5217,0,99.91608,0,97.18475,50.55920,50.79803,198.97462,901.79449,140.71210,2832.14502,201.22163,987.46484,13.89382,13.45978,433.94095,87.33517,99.65507,12,12.01782,1.33269,0.20233,540833,540833,0,0,1,1,1,36.09313,35.24430,28.03253,0,1,54123.00000,0,709.41773,763.19324,0,1,2880,786.00,785.63806,1,11.87544,10,10,10,10,-3.27477,-1.26812,3.99904,6.44211,120.00000,3713.54492,-192.00000,70,18860.86328,20,414.72571,-0.00166,58.20312,69.86041,0,386.41214,0.00065,18648.13867,350.29297,340.94333,0,10027.00000,27605.00000,,,,
-241,0.10087,1.43946,406.14667,1115.11975,33.4603,100.0,2822.59912,36.09799,100,0.29907,0,-1.86005,50.37704,50.79803,206.98546,898.75037,1965.17969,2834.25049,235.80730,990.50915,13.78969,13.45978,422.95178,47.35833,74.88403,12,11.78894,1.33131,0.20233,540833,540833,0,0,1,1,1,36.23047,35.36072,28.02906,0,1,54115.00000,0,715.60059,763.19324,0,1,2880,786.00,786.69287,1,11.92716,10,10,10,10,-3.14099,-1.28428,3.86046,6.33855,774.60321,5380.53369,-160.00000,70,18530.07227,20,340.03839,0.00000,45.49335,63.6936,0,399.13931,-0.00029,18579.37109,352.75836,346.94061,0,10027.00000,27605.00000,,,,
-242,0.10087,1.44540,405.06735,1105.2218,31.91024,0.0,2830.03906,35.87788,100,0.29907,0,-1.88294,50.51251,50.31896,201.26343,904.40363,1977.95679,2840.09692,207.55519,1103.8689,13.80983,13.45978,438.59360,43.82143,42.28363,12,12.01782,1.32723,0.20233,540833,540833,0,0,1,1,1,36.23047,35.43700,28.03169,0,1,54132.75000,0,716.35132,763.19324,0,1,2880,784.00,783.07831,1,11.90346,10,10,10,10,-3.06634,-1.27637,4.21295,6.45516,96.00000,3006.67529,-160.00000,70,18960.00000,20,-16.00000,-0.00166,-0.00723,65.64673,0,394.37457,-0.00166,18476.68555,357.35004,347.87399,0,10027.00000,27605.00000,,,,
-243,0.10145,1.44699,406.14667,1105.2218,33.6555,0.23183,2802.60547,35.77565,100,99.91608,0,97.20763,50.58812,50.38096,205.08466,906.14319,1987.68604,2840.81055,206.79475,990.07416,13.54132,13.45978,428.37021,40.72501,39.54468,12,11.78131,1.32401,0.20233,540833,540833,0,0,1,1,1,36.41358,35.48279,28.02906,0,1,54130.00000,0,712.854,763.19324,0,1,2880,785.00,784.60120,1,11.91428,10,10,10,10,-3.23213,-1.25020,4.09968,6.49650,104.00000,3897.19360,-160.00000,70,19315.93359,20,-16.00000,-0.00166,61.2775,8.22842,10,401.41721,-0.00282,18625.87305,357.56610,342.88071,0,10026.00000,27605.00000,,,,
-244,0.10187,1.44352,405.06735,1001.99799,33.6555,0.4184,2840.84863,35.96524,100,99.91608,0,-1.87531,50.29405,48.08197,202.98004,896.14105,874.85077,2836.07910,198.51932,1105.14465,13.70995,12.75024,428.37021,43.94179,92.49268,12,11.78894,1.31775,0.20233,540833,540833,0,0,1,1,1,36.35254,35.37598,28.02216,0,1,54129.00000,0,709.30176,763.19324,0,1,2880,784.00,783.32166,1,11.90406,10,10,10,10,-2.63818,-1.21851,3.88849,6.35751,143.27156,3999.49829,-160.00000,70,18949.29492,20,173.78590,-0.00022,0.06511,1.15741,0,398.33551,-0.00022,18684.88867,355.65613,345.68045,0,10027.00000,27605.00000,,,,
-245,0.03051,1.44496,405.06735,993.95294,33.6555,61.54117,2838.21606,35.76954,0,0.29907,100,-1.87531,50.17468,50.79803,174.15166,909.18732,29.61724,2448.50122,243.22511,994.85779,13.48443,12.75024,435.78574,93.9275,60.67047,12,11.78894,1.31396,0.20233,540833,540833,0,0,1,1,1,36.41358,35.45227,28.03084,0,1,54087.00000,0,708.42895,763.19324,0,1,2880,788.00,789.60022,1,11.90141,10,10,10,10,-2.90885,-1.02591,3.92054,6.42328,91.91811,3034.03418,-160.00000,70,18740.00000,20,637.36444,-0.00022,68.60532,40.16565,0,406.74704,0.00434,18816.93555,361.79022,343.15219,0,10026.00000,27627.00000,,,,
-246,0.10145,1.45285,397.63785,1001.99799,31.91024,100.0,2837.47949,37.61703,100,99.91608,0,-1.88294,48.29282,47.25036,208.70207,878.79553,6.71385,2834.81226,206.98665,996.59735,13.65604,12.75024,432.15286,48.49534,43.35174,12,11.78894,1.30896,0.20233,540833,540833,0,0,1,1,1,36.41358,35.49804,28.02909,0,1,54107.00000,0,719.83643,763.19324,0,1,2880,786.00,786.28668,1,11.93277,10,10,10,10,-3.00290,-1.17163,4.15299,6.48542,2362.74170,4048.41577,-160.00000,70,18923.98438,20,254.10359,0.00000,66.70285,68.82959,0,407.82574,0.00058,18674.75000,357.12338,349.67111,50,10026.00000,27605.00000,,,,
-247,0.10121,1.45514,397.63785,1001.99799,33.4603,100.0,2838.88330,37.5415,100,99.91608,0,-1.88294,50.73484,49.68206,204.50587,903.77155,1974.70239,2842.53296,236.41408,997.90192,13.59334,13.45978,436.19110,58.92611,39.07165,12,11.78131,1.29980,0.20233,540833,540833,0,0,1,1,1,36.52039,35.54382,28.02909,0,1,54138.00000,0,702.0813,763.19324,0,1,2880,781.00,780.84906,1,11.92770,10,10,10,10,-2.70263,-1.22942,4.08751,6.39524,151.00000,2217.10767,-160.00000,70,19356.51758,20,-17.00000,-0.00166,77.21356,0.14465,0,399.91055,-0.00202,18553.01367,359.77722,345.32428,0,10027.00000,27605.00000,,,,
-248,0.10145,1.45824,397.63785,1105.2218,31.91024,59.1333,2838.60254,35.8569,0,0.29907,0,-1.87531,50.40693,50.56152,178.76483,908.31750,6.33237,2595.68335,243.41580,1002.62195,13.36812,12.74261,436.88580,99.16256,42.12341,12,11.78131,1.29522,0.20233,540833,540833,0,0,1,1,1,36.76452,35.62011,28.03334,0,1,54090.00000,0,704.27246,763.19324,0,1,2880,787.00,788.60925,1,11.93184,10,10,10,10,-2.78869,-1.19172,3.81969,6.45867,159.44315,1720.92883,-160.00000,70,18874.22070,20,508.42230,0.00000,-0.00723,60.85431,0,398.75555,0.00362,19034.84961,364.25031,345.17770,0,10026.00000,27627.00000,,,,
-249,0.10145,1.46313,406.14667,1105.2218,33.6555,100.0,2828.21436,37.11704,100,99.91608,0,33.21228,50.11453,50.31738,174.36981,849.62891,2006.56897,2845.34082,242.08067,988.3346,13.16601,13.34534,445.84152,40.94249,41.68853,12,12.01019,1.28721,0.20233,540833,540833,0,0,1,1,1,36.70349,35.68115,28.03345,0,1,54130.00000,0,705.78003,763.19324,0,1,2880,783.00,782.09003,1,11.92610,10,10,10,10,-2.90076,-1.00442,4.25367,6.70441,-7.00000,1487.52502,-160.00000,70,19007.25000,20,-17.00000,-0.00166,49.84808,9.0965,0,413.96188,-0.00376,18919.07617,367.53748,346.21747,0,10026.00000,27605.00000,,,,
-250,0.10145,1.47192,406.14667,993.95294,33.6555,100.0,2836.63721,37.50259,100,99.91608,0,28.25317,47.04320,48.66943,178.30154,853.95148,1992.44763,2845.34082,229.21330,1006.53571,13.18962,13.45978,449.12369,95.46562,40.49072,12,12.01782,1.27589,0.20233,540833,540833,0,0,1,1,1,36.62720,35.65064,28.03078,0,1,54135.00000,0,702.82593,763.19324,0,1,2880,781.00,781.12714,1,11.94839,10,10,10,10,-2.84957,-1.15360,4.11795,6.60741,-20.00000,1311.53503,-160.00000,70,19178.23828,20,-17.00000,-0.01237,-0.00723,73.53155,0,412.01270,-0.00401,19021.37500,366.06821,350.96555,0,10026.00000,27605.00000,,,,
-251,0.10145,1.47373,406.14667,1119.68103,33.4603,100.0,1186.52502,35.53886,0,99.91608,0,-1.88294,47.79589,47.96562,181.38551,893.09692,1985.60132,2838.25391,238.45674,994.42285,13.01166,12.75024,446.80219,43.57772,41.08581,12,11.78131,1.27356,0.27557,540833,540833,0,0,1,1,1,36.76452,35.80322,28.02389,0,1,54110.00000,0,715.84473,763.19324,0,1,2880,786.00,786.72137,1,11.96859,10,10,10,10,-3.01620,-0.22256,4.51477,6.74252,-20.00000,2449.69702,-160.00000,70,18433.13086,20,-17.00000,-0.00022,-0.00723,5.93173,0,417.10437,-0.00137,19159.80664,373.64835,352.32632,0,10011.52344,27605.00000,,,,
-252,0.10121,1.48073,397.63785,1105.2218,33.6555,100.0,2838.08203,37.7087,0,0.29907,0,-1.87531,47.22325,47.73101,176.98804,884.83813,1974.71619,2833.82959,200.71591,994.85779,13.26611,12.27722,450.95602,99.69012,37.40082,12,11.78894,1.25848,0.27557,540833,540833,0,0,1,1,1,36.81030,35.80322,28.02213,0,1,54120.00000,0,714.4104,763.19324,0,1,2880,783.00,782.13153,1,11.93636,10,10,10,10,-2.68035,-0.80199,4.40619,6.67945,-22.00000,1593.07434,-160.00000,70,18986.37109,20,-17.00000,-0.01237,79.14496,8.22842,0,410.66156,-0.00058,19061.83984,368.85394,355.42505,0,10026.00000,27605.00000,,,,
-253,0.10145,1.48380,405.06735,1105.2218,33.6555,100.0,2837.79907,36.91486,100,99.91608,0,-1.87531,47.14125,47.73101,206.22250,903.09906,1220.10449,2834.25049,228.48309,993.55328,13.34062,12.75024,448.33646,52.33242,41.68853,12,11.78894,1.23867,0.20233,540833,540833,0,0,1,1,1,36.84082,35.68115,28.03507,0,1,54124.00000,0,698.62671,763.19324,0,1,2880,784.00,783.52661,1,11.94162,10,10,10,10,-2.84341,-1.03379,4.23011,6.57558,-8.52950,2030.34106,-160.00000,70,18273.60938,20,-17.00000,-0.00166,72.57669,65.64673,0,419.70474,-0.00022,19287.34766,371.63672,354.56763,0,10026.00000,27627.00000,,,,
-254,0.10121,1.48609,405.06735,1105.2218,33.6555,100.0,1754.32532,35.88142,100,0.29907,100,-1.87531,47.48442,50.79803,207.55763,885.73822,1954.49805,2837.33911,228.57341,1000.0127,13.42349,12.75024,439.30923,95.78281,36.4624,12,11.78131,1.19688,0.20233,540833,540833,0,0,1,1,1,36.84082,35.80322,28.02993,0,1,54101.00000,0,716.29028,763.19324,0,1,2880,786.00,785.94043,1,11.96142,10,10,10,10,-2.62444,-0.88246,4.03178,6.45243,152.00357,2108.58301,-160.00000,70,18920.07422,20,-17.00000,0.00000,-0.00723,9.02414,0,424.25323,-0.00036,19222.40820,368.08673,358.05655,0,9999.00000,27627.00000,,,,
-255,0.10087,1.48812,397.63785,1105.2218,33.6555,1.21822,2843.10474,37.4179,0,99.91608,0,-1.87531,47.90953,47.14355,185.20412,898.31543,6.33237,2834.81226,202.60985,999.64148,13.14199,11.68213,449.12369,98.62209,86.94611,12,11.78894,1.17601,0.20233,540833,540833,0,0,1,1,1,36.76452,35.75745,28.02726,0,1,54114.00000,0,719.92798,763.19324,0,1,2880,784.00,783.29230,1,11.93984,10,10,10,10,-2.60314,-0.84019,4.03952,6.69854,-20.00000,1446.86255,-160.00000,70,18978.31836,20,-17.00000,-0.00022,62.95575,0.41592,0,418.84528,0.00087,19473.27539,375.00793,356.87289,0,10026.00000,27627.00000,,,,
-256,0.03051,1.55621,405.06735,1115.11975,31.91024,0.31853,2834.38452,36.74435,100,99.9237,0,-1.88294,61.82296,63.29498,220.14613,943.97729,1948.43054,2817.35449,315.51355,995.2926,15.60312,15.59601,408.33093,38.05269,44.06128,12,12.01782,1.38336,0.20233,540833,540833,0,0,1,1,1,34.68933,35.00976,28.02997,0,1,54084.00000,0,716.40015,763.19324,0,1,2880,779.00,777.28271,1,11.81513,10,10,10,10,-3.78951,-1.57439,3.35616,5.24029,991.50909,328.50473,13568.00000,70,5158.00000,20,-23.00000,-0.00022,64.79312,70.47528,0,430.93231,0.00029,19894.54492,380.88580,369.02939,0,10082.00000,27605.00000,,,,
-257,0.10027,1.54081,397.63785,1105.2218,33.4603,100.0,2842.46899,37.71469,100,0.29907,0,-1.88294,62.51551,62.71515,225.48676,942.67273,1330.09668,2820.56812,309.59927,1003.92651,16.56496,15.59601,408.43460,40.07293,56.50482,12,11.78894,1.38184,0.20233,540833,540833,0,0,1,1,1,34.68933,35.02502,28.02645,0,1,54110.00000,0,711.70654,763.19324,0,1,2880,777.00,776.63086,1,11.81413,10,10,10,10,-3.88095,-1.61040,3.15786,4.96405,110.00000,352.00000,13424.70410,70,5102.99805,20,-19.00000,-0.00166,-0.00723,0.07236,0,436.38464,0.00029,20134.24023,383.21768,371.46277,0,10082.00000,27605.00000,,,,
-258,0.10145,1.52882,406.14667,993.95294,31.91024,0.0,2821.71875,36.70875,100,99.91608,0,-1.88294,62.38863,62.47863,223.00719,941.38422,23.29173,918.39392,309.05103,1002.40448,16.32906,14.64233,407.36115,34.44476,42.87109,12,11.78131,1.38031,0.20233,540833,540833,0,0,1,1,1,34.79614,35.04028,28.02216,0,1,54077.00000,0,709.39331,763.19324,0,1,2880,784.00,783.72003,1,11.81943,10,10,10,10,-3.95551,-1.49911,3.28453,5.02382,2747.59033,376.73553,13781.03320,70,5177.64111,20,-19.00000,0.00072,74.66,70.16785,0,443.24884,0.00109,20198.03125,382.75235,375.53973,0,10053.00000,27605.00000,,,,
-259,0.10121,1.54384,406.14667,1001.99799,33.6555,0.0,1772.17383,36.05298,100,99.9237,0,-1.88294,62.48330,63.76801,222.43500,950.50049,1955.82129,153.41179,312.46182,1000.88245,15.98091,14.99329,407.92343,35.31063,79.03442,12,11.78894,1.37802,0.20233,540833,540833,0,0,1,1,1,34.79614,35.05553,28.03251,0,1,54088.00000,0,706.30493,763.19324,0,1,2880,781.00,783.14026,1,11.80763,10,10,10,10,-4.09530,-1.44081,3.38123,5.54325,80.00000,200.00000,13760.00000,70,5156.00000,20,-23.00000,-0.00022,1.85184,0.05423,10,440.23102,0.00058,20242.65039,393.78177,373.84012,0,10053.00000,27605.00000,,,,
-260,0.10087,1.56147,405.06735,993.95294,31.91024,100.0,2836.90454,35.37129,100,99.91608,0,-1.87531,63.77122,62.93640,227.96626,955.71893,6.33237,2373.29590,309.77011,994.42285,15.51408,14.64996,407.05441,81.45332,38.01117,12,11.78131,1.37573,0.17029,540833,540833,0,0,1,1,1,34.82666,35.25719,28.02561,0,1,54094.00000,0,711.77368,763.19324,0,1,2880,780.00,779.84882,1,11.78772,10,10,10,10,-4.00701,-1.47841,3.36300,5.43415,2121.66187,200.00000,14141.25977,70,5194.81689,20,-19.00000,0.00000,-0.00723,72.12097,0,442.64374,0.00072,20543.09766,385.15204,380.21793,0,10053.00000,27605.00000,,,,
-261,0.10121,1.57044,405.06735,1105.2218,32.0,100.0,2836.07910,35.24513,100,99.91608,100,-1.8219,63.25827,63.65356,229.48180,957.89349,1362.11536,2821.19531,308.45639,1105.4635,15.36675,15.59601,407.31000,43.29027,99.44305,12,11.78894,1.37268,0.17029,540833,540833,0,0,1,1,1,34.82666,35.45227,28.02736,0,1,54109.00000,0,705.86548,763.19324,0,1,2880,777.00,778.02136,1,11.76047,10,10,10,10,-4.05446,-1.42193,3.65137,5.70486,107.00000,112.00000,13952.16309,70,5219.79736,20,-19.00000,-0.00022,61.8779,50.52808,0,448.17145,-0.00007,20903.01562,402.63748,376.89691,0,10053.00000,27605.00000,,,,
-262,0.10121,1.57971,397.63785,1105.2218,33.6555,33.3992,2787.03320,35.67723,100,99.91608,0,-1.87531,64.24765,65.88898,229.68356,953.10980,1980.05676,2832.28540,312.26364,1104.82556,15.31725,15.59601,407.41226,94.50123,96.38366,12,11.78131,1.37115,0.20233,540833,540833,0,0,1,1,1,34.84191,35.55908,28.02909,0,1,54113.00000,0,712.53662,763.19324,0,1,2880,777.00,778.65173,1,11.79610,10,10,10,10,-3.83311,-1.33000,3.57401,5.73026,-20.00000,80.00000,14000.95215,70,6349.59424,20,-23.00000,-0.00166,48.03241,70.16785,0,459.28290,-0.00181,20643.44336,401.78516,387.96014,0,10053.00000,27605.00000,,,,
-263,0.10121,1.60029,397.63785,1001.99799,31.91024,100.0,2833.12744,35.78137,100,99.91608,0,32.80792,63.99886,63.76801,225.48676,946.58661,1968.23108,2828.21436,311.31744,1105.4635,15.24559,15.22980,406.74771,40.86138,47.01385,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.84191,35.60485,28.03172,0,1,54121.00000,0,712.77466,763.19324,0,1,2880,776.00,776.29590,1,11.83057,10,10,10,10,-3.31650,-1.34284,3.54414,5.65957,-20.00000,80.00000,14126.60449,70,5598.17090,20,-23.00000,-0.00166,78.30585,62.01172,0,457.34100,-0.00109,20989.98242,423.78848,395.14313,0,10053.00000,27605.00000,,,,
-264,0.10087,1.61432,405.06735,993.95294,33.4603,100.0,2829.06030,37.0602,100,99.91608,0,-1.87531,65.01620,64.83576,225.48676,953.10980,903.94861,157.10713,310.36371,1114.34277,15.21009,15.22980,406.59439,36.59362,99.59866,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.87244,35.77270,28.03334,0,1,54104.00000,0,701.55029,763.19324,0,1,2880,780.00,781.04938,1,11.85969,10,10,10,10,-3.17483,-1.34095,3.46235,5.53245,-20.00000,72.00000,14353.51367,70,5291.67529,20,-23.00000,-0.00166,72.57669,2.06162,0,470.34702,0.00029,21402.33008,433.44742,395.92206,0,10053.00000,27605.00000,,,,
-265,0.10121,1.62692,406.14667,1001.99799,31.91024,100.0,272.16852,35.50099,100,99.91608,0,-1.88294,64.85937,64.48517,223.00719,950.50049,1967.10828,428.91470,312.46182,1000.0127,15.10539,15.22980,406.49216,93.10169,99.35625,12,11.78131,1.36658,0.20233,540833,540833,0,0,1,1,1,34.88770,35.84900,28.02824,0,1,54101.00000,0,703.9917,763.19324,0,1,2880,781.00,781.86652,1,11.88226,10,10,10,10,-3.08934,-1.34617,3.41236,5.59499,-22.00000,56.00000,14478.00391,70,5554.06055,20,-23.00000,-0.00166,14.46759,0.10849,0,473.72803,0.00000,21639.87305,419.36359,421.25989,0,10053.00000,27605.00000,,,,
-266,0.10121,1.73890,397.63785,993.95294,32.0,100.0,2827.51245,35.78148,0,99.91608,0,-1.88294,66.62585,66.58325,221.86275,950.50049,56.99314,139.94243,314.33914,998.70819,15.09116,15.12332,406.44833,43.99995,45.95337,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.90295,35.87951,28.03078,0,1,54094.00000,0,723.14453,763.19324,0,1,2880,781.00,783.04205,1,11.92450,10,10,10,10,-3.11919,-1.40424,3.23528,5.57602,-7.00000,56.00000,14288.00000,70,6281.21729,20,-19.00000,-0.00022,73.84982,0.92233,0,463.71115,0.00109,23434.93164,388.83707,429.67532,0,10053.00000,27605.00000,,,,
-267,0.10145,1.82495,397.63785,1105.2218,31.91024,100.0,2813.28442,35.55287,100,99.91608,0,97.20763,66.13617,63.76801,224.91451,943.54248,1971.66443,2828.49487,311.10373,994.85779,15.04118,15.22980,405.98096,40.65303,42.87109,12,12.01782,1.36658,0.20233,540833,540833,0,0,1,1,1,34.89923,35.92529,28.02473,0,1,54121.00000,0,708.76465,763.19324,0,1,2880,778.00,777.42401,1,11.89802,10,10,10,10,-3.70096,-1.58655,3.55688,5.97485,-22.00000,16.00000,14574.13086,70,8128.33154,20,-23.00000,-0.00166,3.1467,71.14441,0,471.17062,-0.00116,22307.39258,390.01291,468.25687,0,10053.00000,27605.00000,,,,
-268,0.10121,1.85423,405.06735,993.95294,33.4603,100.0,103.41148,37.02434,100,99.9237,0,-1.87531,66.09354,66.94183,221.48128,948.32611,1965.56079,34.95676,313.41553,1104.82556,15.01596,15.22980,406.08322,43.39801,40.74249,12,11.78131,1.36658,0.20233,540833,540833,0,0,1,1,1,34.91821,35.94055,28.03334,0,1,54089.00000,0,709.06982,763.19324,0,1,2880,784.00,785.12921,1,11.86929,10,10,10,10,-3.75153,-1.65128,3.62746,6.05999,-20.00000,32.00000,14704.00000,70,6623.54541,20,-23.00000,-0.00166,62.25406,58.97357,0,499.76489,0.00065,21287.76172,378.04288,435.05356,0,10053.00000,27605.00000,,,,
-269,0.10087,2.05230,406.14667,993.95294,32.0,100.0,1559.97522,37.32177,100,99.91608,100,-1.86005,66.25319,64.36310,222.24423,946.15179,734.03711,1548.97778,309.21936,1105.78247,14.95528,14.64996,406.44104,36.99502,42.28363,12,11.78894,1.37115,0.20233,540833,540833,0,0,1,1,1,34.93347,36.03211,28.02906,0,1,54105.00000,0,702.2644,763.19324,0,1,2880,781.00,781.89911,1,11.85743,10,10,10,10,-4.16711,-1.72863,3.78546,6.10588,-20.00000,8.00000,14912.00000,70,8344.17773,20,-23.00000,-0.00022,75.26044,0.05423,0,461.08112,0.00029,21099.31836,378.46744,409.66464,0,10053.00000,27605.00000,,,,
-270,0.03051,1.66099,397.63785,1001.99799,31.91024,100.0,37.93592,35.66426,100,0.29907,0,-1.88294,66.55226,66.58325,219.76472,942.67273,317.11304,31.97760,314.33914,1106.73914,14.90680,14.64233,405.62314,38.00199,60.18219,12,12.01782,1.37268,0.20233,540833,540833,0,0,1,1,1,34.96399,36.00158,28.03166,0,1,54078.00000,0,708.74634,763.19324,0,1,2880,786.00,786.62817,1,11.82771,10,10,10,10,-3.96308,-1.65373,3.91307,6.16533,-20.00000,40.00000,15020.71777,70,7594.65381,20,-23.00000,0.00000,0.33998,0.07236,10,478.73288,0.00159,20735.90820,372.06921,388.60403,0,10052.00000,27605.00000,,,,
-271,0.10087,1.62475,406.14667,993.95294,33.6555,100.0,2818.41699,36.18965,100,99.91608,0,-1.86768,66.79946,67.30804,219.95543,940.06360,1971.85510,509.62241,310.74518,1116.2561,14.87141,14.64233,405.36758,52.27336,45.59479,12,12.01782,1.37268,0.20233,540833,540833,0,0,1,1,1,34.96399,36.06262,28.0273,0,1,54114.00000,0,710.14404,763.19324,0,1,2880,779.00,780.60553,1,11.84205,10,10,10,10,-3.41491,-1.52910,4.02495,6.15410,-22.00000,8.00000,15280.76953,70,9062.84473,20,-23.00000,-0.00166,3.70372,61.72235,0,458.16660,-0.00036,20413.30664,366.84158,386.70047,0,10053.00000,27605.00000,,,,
-272,0.10121,1.60579,445.34219,1001.99799,33.4603,88.24674,2837.19873,35.33924,100,99.91608,0,-1.83716,70.13054,64.71405,219.76472,939.62860,1962.69983,2831.44312,310.31729,1003.4917,14.81800,14.64233,404.08966,45.14766,45.00732,12,12.01782,1.37573,0.20233,540833,540833,0,0,1,1,1,34.96399,36.06262,28.02645,0,1,54126.00000,0,707.94067,763.19324,0,1,2880,775.00,775.58051,1,11.87319,10,10,10,10,-3.29180,-1.69616,4.43758,6.17230,-20.00000,0.00000,15168.00000,70,10265.72461,20,-23.00000,0.00000,-0.00723,75.2677,0,459.78262,-0.00080,20107.28906,360.78925,377.85147,50,10053.00000,27605.00000,,,,
-273,0.10145,1.58158,397.63785,1105.2218,31.91024,100.0,679.77795,35.68905,100,99.91608,0,97.20763,65.86660,63.76801,219.00177,938.75885,1961.70776,168.27023,315.51355,1105.4635,14.82880,14.52789,404.29047,42.00188,40.49835,12,11.78131,1.37802,0.27557,540833,540833,0,0,1,1,1,34.97925,36.36779,28.02818,0,1,54095.00000,0,709.41773,763.19324,0,1,2880,784.00,785.28857,1,11.93728,10,10,10,10,-2.94616,-1.49727,3.93514,6.12789,-20.00000,0.00000,15681.55859,70,8363.43945,20,-23.00000,0.00000,67.91089,77.72711,0,456.96811,0.00029,19837.46680,358.94998,370.72128,50,10052.00000,27605.00000,,,,
-274,0.10087,1.54526,406.14667,1105.2218,33.6555,100.0,2826.52954,35.58758,100,99.91608,0,-1.87531,66.36558,65.76021,219.19247,937.88904,6.14166,32.97053,315.67422,992.24847,14.77491,14.41345,400.89331,86.02737,43.82477,12,12.01782,1.38031,0.20233,540833,540833,0,0,1,1,1,35.00976,36.47460,28.02817,0,1,54077.00000,0,707.9895,763.19324,0,1,2880,786.00,786.78363,1,11.95947,10,10,10,10,-3.21948,-1.79220,3.74642,6.12008,128.52783,8.00000,16043.58789,70,9440.06543,20,-19.00000,0.00123,73.40857,0.09042,0,450.19586,0.00181,19816.31055,352.56119,367.38852,0,10053.00000,27605.00000,,,,
-275,0.10145,1.52724,393.16226,1001.99799,31.91024,100.0,2822.31836,37.16385,100,99.91608,0,-1.82953,66.57840,69.89441,219.38326,938.35364,1965.84802,1651.55347,313.79694,1116.57507,14.68877,14.52789,403.93216,38.57013,37.89673,12,11.78894,1.38184,0.20233,540833,540833,0,0,1,1,1,35.02502,36.90185,28.02993,0,1,54117.00000,0,711.24878,763.19324,0,1,2880,778.00,780.08057,1,11.95873,10,10,10,10,-3.59297,-1.90650,3.70825,6.16388,-20.00000,0.00000,16432.00000,70,9673.10742,20,-23.00000,0.00000,51.07059,64.38074,0,442.09326,-0.00058,19735.40234,342.91312,366.18246,0,10053.00000,27590.00000,,,,
-276,0.10145,1.51846,406.14667,993.95294,33.4603,100.0,2836.21582,37.2353,100,99.91608,0,4.14429,65.67860,63.65356,218.42952,936.58447,1973.90723,2833.12744,313.22476,996.59735,14.65636,14.52789,402.39899,33.30475,95.43762,12,12.01782,1.38336,0.27557,540833,540833,0,0,1,1,1,34.99451,36.52039,28.03253,0,1,54130.00000,0,712.76245,763.19324,0,1,2880,776.00,777.83093,1,11.93233,10,10,10,10,-3.71684,-1.91218,3.84273,6.23973,-22.00000,0.00000,15791.27246,70,12094.65527,20,-23.00000,0.00000,-0.00723,0.09042,0,438.76968,-0.00181,19640.73047,338.01913,364.63898,0,10053.00000,27590.00000,,,,
-277,0.10145,1.51142,405.06735,993.95294,33.6555,100.0,2824.14307,36.06022,100,99.91608,0,-1.88294,66.11700,68.36090,218.57742,937.42670,6.52314,32.05346,316.24640,1002.62195,14.66189,14.41345,404.70303,40.06156,89.41039,12,11.78131,1.38565,0.27557,540833,540833,0,0,1,1,1,35.08606,36.15417,28.02733,0,1,54090.00000,0,726.69678,763.19324,0,1,2880,785.00,785.79382,1,11.87288,10,10,10,10,-4.40090,-2.16030,4.31945,6.55790,-20.00000,0.00000,17176.69922,70,12278.75586,20,-23.00000,0.00072,69.08276,68.66681,0,437.43646,0.00130,19526.82031,334.48218,362.16452,0,10053.00000,27605.00000,,,,
-278,0.10087,1.50747,406.14667,993.95294,33.4603,1.68445,33.96383,37.38128,100,0.29907,0,-1.88294,64.43944,65.88898,217.47586,936.02850,1965.75171,34.95676,314.94138,1112.74817,14.19343,14.41345,404.34521,86.97529,99.382,12,11.78894,1.38641,0.27557,540833,540833,0,0,1,1,1,35.08606,37.45296,28.02818,0,1,54092.00000,0,719.38477,763.19324,0,1,2880,785.00,785.50989,1,11.82795,10,10,10,10,-4.15243,-1.85679,4.65105,6.68262,-22.00000,0.00000,17029.54297,70,12578.15137,20,-23.00000,0.00000,-0.00723,69.55298,0,431.84680,0.00015,19190.75977,329.70898,361.12738,50,10053.00000,27590.00000,,,,
-279,0.03051,1.49988,406.14667,993.95294,32.0,99.3502,2826.10840,37.08881,100,0.29907,100,-1.88294,69.32333,69.89441,218.23882,935.27991,1964.60730,1086.08167,309.41006,1106.42029,14.10839,14.41345,402.87463,37.99065,39.07165,12,11.78894,1.38718,0.27557,540833,540833,0,0,1,1,1,35.13183,37.26807,28.02824,0,1,54109.00000,0,716.71753,763.19324,0,1,2880,781.00,780.92987,1,11.82417,10,10,10,10,-3.53298,-1.78867,4.79258,6.58553,-22.00000,-8.00000,17317.16211,70,13667.41211,20,-23.00000,0.00000,70.99246,70.54761,0,428.67188,-0.00043,18895.14453,325.80121,357.42117,0,10053.00000,27590.00000,,,,
-280,0.10121,1.49734,406.14667,1105.2218,33.6555,100.0,2832.21558,37.3275,100,99.91608,0,-1.88294,66.43143,64.83612,217.66663,935.27991,521.75317,2820.41479,314.17542,990.50915,14.00405,14.41345,401.73828,91.13583,99.68519,12,12.01782,1.38870,0.27557,540833,540833,0,0,1,1,1,35.19287,37.26807,28.02642,0,1,54117.00000,0,701.87988,763.19324,0,1,2880,779.00,778.38190,1,11.82998,10,10,10,10,-3.52125,-1.76603,4.90873,6.57742,-20.00000,0.00000,18416.00000,70,11793.98145,20,-23.00000,0.00123,-0.00723,46.63989,0,426.39700,-0.00087,18667.94922,324.68491,353.09229,0,10053.00000,27590.00000,,,,
-281,0.10187,1.47004,393.16226,993.95294,33.4603,44.64139,1236.81934,36.17821,0,0.29907,0,-1.87531,65.74135,66.58325,216.72052,934.41016,164.24283,25.02598,317.39081,1115.61829,13.67337,14.40582,403.11844,41.74498,44.05365,12,11.78894,1.38946,0.27557,540833,540833,0,0,1,1,1,35.28442,36.90185,28.02736,0,1,54060.00781,0,715.00244,763.19324,0,1,2880,786.00,787.62927,1,11.90880,10,10,10,10,-2.95177,-1.55859,4.33175,6.26984,-22.00000,0.00000,15846.21973,70,12220.60742,20,-23.00000,0.00072,68.86575,71.8858,0,425.14761,0.00246,18448.25586,322.32092,343.97565,0,10052.00000,27580.00000,,,,
-282,0.10121,1.45365,397.63785,993.95294,33.4603,7.28716,2177.98608,38.01986,100,99.91608,0,-1.75324,66.31769,68.32841,216.90367,933.97516,1965.37012,1741.10278,312.84778,1013.25189,13.56986,14.40582,403.42511,100.0,37.77466,12,11.78131,1.39023,0.27557,540833,540833,0,0,1,1,1,35.02502,37.26807,28.02649,0,1,54114.00000,0,705.51758,763.19324,0,1,2880,779.00,779.44067,1,11.96561,10,10,10,10,-2.91662,-1.75896,4.07253,6.20854,-22.00000,0.00000,16704.00000,70,12924.22656,20,-23.00000,0.00000,69.55295,75.81018,0,423.16306,-0.00080,18122.25391,320.09763,342.65244,0,10053.00000,27577.00000,,,,
-283,0.10087,1.43349,397.63785,1105.2218,33.4603,100.0,2824.45850,37.78831,0,99.91608,0,-1.88294,65.24928,66.47643,216.13220,933.10541,101.14017,1595.14233,308.57184,999.57794,13.24667,14.40582,403.57849,89.23435,55.67322,12,12.01782,1.39099,0.58304,540833,540833,0,0,1,1,1,35.13183,37.63427,28.03081,0,1,54108.00000,0,705.49316,763.19324,0,1,2880,780.00,780.45490,1,12.01343,10,10,10,10,-3.25247,-1.85262,3.72742,6.17612,-22.00000,0.00000,16828.66211,70,11600.53906,20,-23.00000,0.00072,66.81857,67.05731,0,414.49991,-0.00015,17918.24609,317.97580,337.39539,50,10053.00000,27577.00000,,,,
-284,0.03051,1.41222,406.14667,1105.2218,32.0,100.0,2511.24512,37.2559,100,99.91608,0,-1.87531,66.17552,66.58325,216.33150,932.23584,1938.05627,2823.29688,311.31744,1104.18787,12.91572,14.39819,403.27176,40.38928,87.99896,12,11.78131,1.39252,0.58304,540833,540833,0,0,1,1,1,35.02502,37.60429,28.02558,0,1,54118.00000,0,715.69824,763.19324,0,1,2880,777.00,777.53094,1,11.96620,10,10,10,10,-3.84895,-1.95227,3.82588,6.24135,-22.00000,-8.00000,16290.78125,70,13645.70996,20,-23.00000,0.00000,-0.00723,39.27954,0,404.23837,-0.00101,17830.57227,315.47458,332.99686,0,10053.00000,27577.00000,,,,
-285,0.10087,1.39785,406.14667,1119.68103,33.4603,3.73906,33.96383,35.67952,100,0.29907,100,97.18475,65.60327,71.88568,215.75925,932.23584,6.52314,31.02439,316.43716,999.57794,12.73905,14.17694,401.02264,38.87265,41.68091,12,11.78131,1.39252,0.27557,540833,540833,0,0,1,1,1,35.19287,37.49695,28.0299,0,1,54060.00000,0,708.65478,763.19324,0,1,2880,786.00,786.65082,1,11.94402,10,10,10,10,-3.79770,-1.97722,3.79431,6.21080,-7.00000,0.00000,16399.57617,70,13777.50684,20,-23.00000,0.00239,62.99191,0.07236,0,403.10223,0.00159,17771.03320,313.26553,329.89035,0,10053.00000,27582.00000,,,,
-286,0.10087,1.38727,397.63785,993.95294,33.4603,100.0,499.48615,35.83794,100,0.29907,0,-1.81427,63.79964,72.97790,215.95001,930.93109,13.99853,29.99137,312.84329,997.03217,12.60628,14.16931,399.59286,90.43308,50.40893,12,12.01782,1.39404,0.58304,540833,540833,0,0,1,1,1,35.28442,37.39014,28.02476,0,1,54054.00000,0,704.42505,763.19324,0,1,2880,786.00,787.10107,1,11.90566,10,10,10,10,-4.10291,-1.93218,4.04324,6.33616,-20.00000,0.00000,16336.00000,70,11567.05566,20,-19.00000,0.00123,65.9433,15.67926,0,382.68073,0.00174,17647.57812,310.27316,327.93845,0,10053.00000,27577.00000,,,,
-287,0.10145,1.37901,397.63785,1001.99799,33.4603,100.0,2830.46045,37.71469,100,99.91608,0,97.17712,65.79796,67.17834,215.56854,930.06128,1964.22583,2832.84692,312.05035,993.11829,12.65372,14.16931,402.30057,45.77845,99.25321,12,11.78894,1.39481,0.27557,540833,540833,0,0,1,1,1,35.00976,37.26807,28.02645,0,1,54121.00000,0,719.0918,763.19324,0,1,2880,776.00,776.75586,1,11.85872,10,10,10,10,-4.01150,-1.86042,4.26103,6.46983,-22.00000,0.00000,15359.04004,70,12041.68555,20,-23.00000,0.00000,-0.00723,2.06162,0,369.24075,-0.00202,17577.84180,308.62100,326.17844,0,10053.00000,27562.00000,,,,
-288,0.10145,1.37092,397.63785,1115.11975,31.91024,100.0,32.97053,37.10281,100,0.29907,100,-1.88294,63.36507,66.94183,215.37776,930.06128,1950.88379,258.91397,311.13571,1001.31744,12.54113,14.16931,403.06729,40.83511,41.20789,12,11.78131,1.39593,0.27557,540833,540833,0,0,1,1,1,35.17761,36.90185,28.02561,0,1,54091.00000,0,726.71509,763.19324,0,1,2880,783.00,783.77716,1,11.84247,10,10,10,10,-3.75417,-1.75021,4.38470,6.32999,-22.00000,0.00000,15656.53223,70,10492.68457,20,-23.00000,0.00000,70.21121,73.7124,0,356.83127,-0.00015,17439.58984,306.33038,324.42734,0,10053.00000,27570.00000,,,,
-289,0.10145,1.36627,406.14667,1001.99799,33.6555,100.0,31.97761,37.12646,100,0.29907,0,-1.88294,62.68886,65.43521,214.80557,929.62646,334.43878,29.99137,308.83786,1116.57507,10.98796,14.16931,399.74472,31.37398,39.31579,12,12.01019,1.39786,0.58304,540833,540833,0,0,1,1,1,35.26917,36.52039,28.02473,0,1,54070.00000,0,712.21313,763.19324,0,1,2880,785.00,786.33722,1,11.84073,10,10,10,10,-3.82689,-1.57825,4.77679,6.31570,-22.00000,0.00000,15107.03320,70,11902.46289,20,-23.00000,0.00000,-0.00723,1.22977,0,351.13971,0.00094,17401.99805,305.73117,322.15024,0,10053.00000,27566.00000,,,,
-290,0.03051,1.36064,405.06735,1001.99799,32.0,100.0,157.10713,37.09289,100,99.91608,0,-1.85242,62.87880,63.65356,213.85191,928.32196,201.07732,32.97053,307.88422,1002.62195,10.88426,14.16168,399.94003,42.06001,89.02892,12,11.78894,1.39786,1.80603,540833,540833,0,0,1,1,1,35.02502,36.69237,28.02382,0,1,54069.00000,0,698.38867,763.19324,0,1,2880,784.00,785.19788,1,11.89340,10,10,10,10,-3.36639,-1.55229,4.17177,6.22867,-22.00000,0.00000,15327.58789,70,10290.08691,20,-23.00000,0.00000,60.66986,6.42001,0,350.58624,0.00080,17314.25586,302.23230,321.88419,0,10053.00000,27570.00000,,,,
-291,0.10145,1.35540,406.14667,1001.99799,31.91024,0.0,2832.42578,37.33284,0,99.91608,0,-1.87531,64.28780,63.76801,214.42410,927.12909,718.75690,2824.84521,307.69345,1003.05676,9.79769,14.05487,403.62958,37.47188,97.32208,12,12.01782,1.40070,1.80603,540833,540833,0,0,1,1,1,35.19287,36.90185,28.0273,0,1,54115.00000,0,714.7583,763.19324,0,1,2880,771.00,774.98090,1,11.92978,10,10,10,10,-2.52570,-1.49302,3.99518,6.13049,-22.00000,-8.00000,15136.00000,70,11464.77441,20,-23.00000,0.00000,68.16406,0.61487,10,338.00479,-0.00124,17322.36328,300.32520,321.74850,0,10053.00000,27551.00000,,,,
-292,0.10087,1.34888,405.06735,1105.2218,31.91024,100.0,2827.77686,37.68086,100,0.29907,100,-1.88294,63.46013,63.76801,213.08896,927.01715,6.33237,32.97053,307.21002,1001.31744,9.21972,14.06250,400.10254,42.43901,87.77008,12,11.78894,1.40320,0.58304,540833,540833,0,0,1,1,1,35.19287,36.36779,28.02736,0,1,54083.00000,0,697.27783,763.19324,0,1,2880,781.00,782.15033,1,11.93428,10,10,10,10,-3.18158,-1.58081,3.90969,6.13978,-22.00000,0.00000,15097.55664,70,9931.79395,20,-23.00000,0.00000,2.53906,73.58581,0,337.24823,0.00109,17230.25781,300.76154,319.15662,0,10053.00000,27574.00000,,,,
-293,0.10121,1.34489,406.14667,1115.11975,31.91024,100.0,2738.82983,36.05298,100,99.91608,0,-1.88294,62.58663,63.29498,214.24219,926.14740,1965.94226,1124.89648,307.12125,1105.78247,8.77216,14.05487,402.18628,38.22386,49.74518,12,11.78894,1.40625,0.58304,540833,540833,0,0,1,1,1,35.28442,36.52039,28.02385,0,1,54105.00000,0,715.65552,763.19324,0,1,2880,776.00,779.07568,1,11.96233,10,10,10,10,-3.08066,-1.64672,3.80702,6.09056,-25.00000,0.00000,14995.54395,70,9296.21484,20,-23.00000,0.00000,0.65828,57.72565,0,330.51880,-0.00145,17081.50977,297.62946,318.69516,0,10053.00000,27554.00000,,,,
-294,0.10087,1.33899,406.14667,1001.99799,33.6555,100.0,441.73160,37.07687,100,99.91608,0,-1.87531,62.24714,63.42468,212.89825,924.40802,1958.50366,612.73785,306.73978,987.89978,8.66739,14.05487,401.56512,100.0,42.28363,12,11.78894,1.40854,0.58304,540833,540833,0,0,1,1,1,35.19287,36.15417,28.02645,0,1,54094.00000,0,719.43359,763.19324,0,1,2880,779.00,780.21271,1,11.98643,10,10,10,10,-3.13144,-1.55662,3.65724,6.05179,-25.00000,8.00000,14640.00000,70,8805.68164,20,-23.00000,0.00000,-0.00723,79.13776,0,327.76352,-0.00087,17043.30469,290.88974,316.61728,0,10053.00000,27549.00000,,,,
-295,0.10121,1.33426,405.06735,1001.99799,33.6555,100.0,31.97761,35.77755,100,0.29907,100,-1.80664,62.84114,64.83612,213.34749,923.53827,1978.14929,2828.16309,305.97681,1103.23108,8.28146,14.05487,399.43799,31.68732,32.29675,12,11.78131,1.41312,0.58304,540833,540833,0,0,1,1,1,35.28442,36.90185,28.02814,0,1,54097.00000,0,723.45581,763.19324,0,1,2880,779.00,779.35364,1,11.99146,10,10,10,10,-2.77395,-1.52661,3.66616,6.03402,-25.00000,8.00000,14656.00000,70,9893.92480,20,-23.00000,0.00000,52.36545,29.966,0,327.00998,-0.00210,16979.71484,280.11066,315.94394,0,10053.00000,27552.00000,,,,
-296,0.10145,1.33007,397.63785,1001.99799,33.6555,100.0,429.75607,37.69688,100,0.29907,100,-1.85242,61.96715,62.93640,212.49168,923.64502,1962.31836,994.85809,306.54907,1104.82556,8.15756,13.96448,399.33578,44.91191,69.95544,12,12.01782,1.42075,0.58304,540833,540833,0,0,1,1,1,35.19287,36.35254,28.02817,0,1,54084.00000,0,708.61206,763.19324,0,1,2880,780.00,782.55286,1,11.99566,10,10,10,10,-2.78673,-1.48683,3.57007,5.95792,-22.00000,8.00000,14463.90137,70,7550.64502,20,-23.00000,0.00000,15.80585,65.0318,0,316.03268,-0.00043,16831.01367,268.31805,314.79501,0,10053.00000,27558.00000,,,,
-297,0.10145,1.32347,406.14667,1001.99799,33.4603,0.0,2838.00122,37.74826,100,99.91608,0,97.17712,62.10554,62.00561,212.13530,922.23553,22.15921,1860.80615,305.78613,1102.91223,7.94488,13.70392,400.73492,91.33316,55.90973,12,12.01782,1.42721,0.27557,540833,540833,0,0,1,1,1,35.19287,36.09313,28.03074,0,1,54101.00000,0,712.68921,763.19324,0,1,2880,775.00,775.75336,1,11.95169,10,10,10,10,-3.26450,-1.67310,3.61844,6.02597,-25.00000,56.00000,14154.75586,70,8833.90820,20,-23.00000,0.00000,-0.00723,22.76837,0,313.66589,-0.00022,16854.91992,285.50723,312.27518,0,10082.00000,27552.00000,,,,
-298,0.10087,1.31930,406.14667,1119.68103,33.6555,100.0,35.95007,35.76763,100,99.91608,100,25.33112,62.04712,62.93640,212.01945,922.23352,1967.08667,2571.97363,305.40463,1122.04675,7.86784,13.69629,398.46680,45.26644,38.01117,12,11.77368,1.43485,0.58304,540833,540833,0,0,1,1,1,35.28442,36.70349,28.02909,0,1,54092.00000,0,723.29102,763.19324,0,1,2880,778.00,779.73553,1,11.99062,10,10,10,10,-2.99980,-1.59972,3.46797,5.91703,-22.00000,120.00000,13904.00000,70,7054.11279,20,-23.00000,0.00000,-0.00723,69.6253,0,314.10168,-0.00109,16691.86328,254.69565,311.29294,0,10053.00000,27558.00000,,,,
-299,0.10145,1.31407,397.63785,1115.11975,33.6555,100.0,2827.23145,35.80807,100,99.91608,0,-1.8219,62.00249,61.88565,210.87758,920.49414,1974.14404,2836.49683,304.06879,1003.4917,7.36938,12.75024,398.27246,100.0,99.37465,12,11.78894,1.44515,0.27557,540833,540833,0,0,1,1,1,35.37598,36.15417,28.02473,0,1,54110.00000,0,712.56103,763.19324,0,1,2880,771.00,773.60406,1,11.98599,10,10,10,10,-2.85297,-1.46836,3.47870,5.93301,-25.00000,96.00000,13397.35938,70,8398.02539,20,-23.00000,0.00000,0.09402,69.3902,0,303.17920,-0.00354,16521.91211,267.04132,309.81183,0,10053.00000,27549.00000,,,,
-300,0.10087,1.30930,445.34219,1001.99799,31.91024,100.0,1534.71716,37.44537,100,99.91608,0,-1.77612,61.70949,62.24213,210.03720,919.18939,1984.67273,2836.73071,304.18951,1103.8689,7.35009,12.75024,397.73993,44.81353,44.04602,12,12.01019,1.45165,0.58304,540833,540833,0,0,1,1,1,35.28442,36.52039,28.02561,0,1,54107.00000,0,711.73706,763.19324,0,1,2880,775.00,774.05292,1,11.98921,10,10,10,10,-3.19784,-1.43392,3.59181,6.02088,-25.00000,176.00000,13135.20215,70,8947.30664,20,-23.00000,-0.00022,1.82292,0.05423,0,308.63229,-0.00472,16480.34180,270.71530,306.14682,50,10053.00000,27558.00000,,,,
-301,0.10087,1.30278,406.14667,1105.2218,33.4603,100.0,969.85144,37.51632,100,99.91608,100,97.23052,61.29016,62.34894,210.60939,918.31982,1974.14404,2827.37207,303.68802,1101.31775,7.27345,12.27722,397.62256,100.0,45.72448,12,12.01782,1.47415,0.58304,540833,540833,0,0,1,1,1,35.19287,36.15417,28.02736,0,1,54101.00000,0,715.58227,763.19324,0,1,2880,775.00,774.23230,1,11.99770,10,10,10,10,-2.89482,-1.53732,3.60799,5.90656,-25.00000,224.00000,13181.10254,70,8864.87109,20,-23.00000,-0.00022,66.55093,71.45184,0,301.97015,-0.00202,16292.25098,245.93112,307.28329,0,10053.00000,27569.55664,,,,
-302,0.10121,1.29418,397.63785,1115.11975,33.4603,100.0,33.96383,35.7539,100,99.9237,0,-1.88294,61.19011,62.34894,208.12988,917.88483,1956.56458,2817.69238,303.30655,993.55328,7.20993,11.44154,398.92685,94.5166,90.11993,12,12.01019,1.48986,0.58304,540833,540833,0,0,1,1,1,35.45227,36.15417,28.02818,0,1,54082.00000,0,712.38403,763.19324,0,1,2880,779.00,780.53021,1,12.01253,10,10,10,10,-3.18774,-1.52448,3.47350,5.82620,-25.00000,423.97137,13103.04395,70,7715.40088,20,-23.00000,0.00000,-0.00723,66.09882,0,292.74966,-0.00043,16357.00977,258.54633,305.10275,0,10053.00000,27552.00000,,,,
-303,0.10145,1.28938,406.14667,1119.68103,33.4603,100.0,2822.17773,35.7623,100,99.91608,0,48.24981,61.44899,62.36419,206.79475,917.45007,1969.37573,2827.51245,302.73438,1001.7522,6.95611,10.85052,397.86072,50.81883,38.01117,12,11.78894,1.52114,0.58304,540833,540833,0,0,1,1,1,35.45227,36.52039,28.03081,0,1,54102.00000,0,709.18579,763.19324,0,1,2880,771.00,775.30243,1,12.00621,10,10,10,10,-2.80183,-1.44879,3.52272,5.83631,-25.00000,432.00000,12885.09180,70,8241.61719,20,-23.00000,-0.00022,72.96732,0.05423,0,293.20358,-0.00145,16323.37988,269.04211,302.70764,0,10082.00000,27574.00000,,,,
-304,0.10087,1.27570,406.14667,1115.11975,33.6555,100.0,2396.44336,35.07309,100,99.91608,0,-1.87531,61.38819,61.64703,208.85246,912.23138,1968.80322,2831.72388,301.96664,993.11829,6.91259,9.89685,397.29111,42.10184,87.06818,12,12.01019,1.53925,0.58304,540833,540833,0,0,1,1,1,35.54382,36.15417,28.02733,0,1,54100.00000,0,725.83008,763.19324,0,1,2880,775.00,775.07916,1,12.00916,10,10,10,10,-2.93602,-1.49115,3.42528,5.80855,-22.00000,522.42334,12791.82129,70,8996.81543,20,-23.00000,0.00000,74.43576,64.38074,0,288.38654,-0.00202,16055.80176,249.90334,301.38593,0,10082.00000,27574.00000,,,,
-305,0.10121,1.26941,397.63785,1119.68103,31.91024,100.0,2835.37378,37.19169,100,99.91608,100,97.23052,61.26868,62.09917,210.22798,916.14526,1056.31873,1726.22815,302.16217,1102.59326,6.67737,9.18368,396.66632,40.11262,98.74115,12,11.78894,1.64123,0.27557,540833,540833,0,0,1,1,1,35.72693,36.15417,28.02993,0,1,54096.00000,0,704.38232,763.19324,0,1,2880,775.00,777.87604,1,12.01965,10,10,10,10,-3.01075,-1.60864,3.40660,5.73438,-22.00000,594.18201,12384.18066,70,6897.25098,20,-23.00000,-0.00022,3.09605,14.12396,0,282.06299,-0.00036,15925.72266,281.22800,294.04868,0,10082.00000,27577.00000,,,,
-306,0.10121,1.23731,405.06735,1105.2218,31.91024,100.0,28.99807,37.02346,100,99.91608,100,-1.88294,61.58044,61.05194,205.67392,840.91187,5.76019,2837.19873,300.25479,1000.88245,6.13132,0.28381,382.52585,37.01234,97.55859,12,11.78131,1.48634,0.27557,540833,540833,0,0,1,1,1,35.63538,36.90185,28.02909,0,1,54044.66406,0,708.8501,763.19324,0,1,2880,780.00,779.96515,1,12.02531,10,10,10,10,-2.44039,-1.59537,3.19542,5.39253,5185.07422,736.00549,12462.66504,70,12468.46777,20,-18.00000,0.00838,-0.00723,27.12671,10,259.40927,-0.00058,16417.47852,229.87201,305.64694,0,10082.00000,27590.00000,,,,
-307,0.10087,1.24694,393.16226,1001.99799,33.6555,100.0,32.97053,37.31338,100,99.91608,100,97.21527,60.82361,62.00561,180.68919,904.83856,1961.34741,1541.85327,302.97162,997.46716,6.82444,8.36209,397.39331,91.22498,34.21173,12,11.78894,1.48306,0.27557,540833,540833,0,0,1,1,1,35.58960,36.90185,28.02733,0,1,54069.00000,0,711.73096,763.19324,0,1,2880,781.00,782.76025,1,12.02160,10,10,10,10,-2.55840,-1.48302,3.24600,5.62745,-25.00000,656.00000,11806.46680,70,9138.20215,20,-23.00000,-0.00022,64.01187,11.23047,0,266.45633,0.00029,15333.25879,287.37451,284.36023,0,10053.00000,27582.00000,,,,
-308,0.10121,1.23048,393.16226,993.95294,33.4603,100.0,1057.07214,37.26505,100,0.29907,100,32.66296,60.59624,62.24194,181.06290,894.13959,1301.02759,1129.38184,302.33109,996.59735,6.60587,8.94317,395.93320,94.78138,94.37714,12,12.01782,1.47050,0.27557,540833,540833,0,0,1,1,1,35.63538,37.26807,28.0299,0,1,54062.00000,0,705.93872,763.19324,0,1,2880,781.00,783.45935,1,12.06294,10,10,10,10,-2.59203,-1.53520,3.13232,5.56543,-22.00000,799.28998,9344.00000,70,8581.43066,20,-19.00000,0.00000,0.03616,2.69461,0,272.22253,0.00051,15169.21582,282.87253,285.86758,50,10053.00000,27582.00000,,,,
-309,0.10087,1.21797,397.63785,1115.11975,33.6555,100.0,2831.86426,37.60444,100,99.9237,0,-1.87531,60.61066,61.29608,178.56593,861.79858,1971.47351,2834.67188,301.01776,1002.18701,7.06539,7.64618,395.45898,45.37562,97.08556,12,11.78894,1.45895,0.27557,540833,540833,0,0,1,1,1,35.49804,37.60376,28.02824,0,1,54111.00000,0,702.15454,763.19324,0,1,2880,749.00,768.96985,1,12.02738,10,10,10,10,-2.77613,-1.68772,3.20877,5.69690,-22.00000,760.00000,11408.00000,70,9500.96387,20,-23.00000,-0.00166,0.11575,0.05423,0,257.53479,-0.00224,15466.12891,274.41718,287.26257,0,10082.00000,27582.00000,,,,
-310,0.10145,1.19093,405.06735,1001.99799,31.91024,100.0,2827.37207,37.97943,100,99.91608,0,-1.87531,60.65642,61.29608,175.54431,842.43329,1979.86877,2836.91797,300.41595,1118.21985,7.08655,7.64618,395.70673,41.82151,45.13702,12,11.78894,1.44365,0.27557,540833,540833,0,0,1,1,1,35.63538,37.61901,28.02997,0,1,54109.00000,0,709.10645,763.19324,0,1,2880,771.00,771.70532,1,12.02630,10,10,10,10,-3.07236,-1.60615,3.21597,5.76957,-22.00000,889.72119,9344.00000,70,12003.49805,20,-19.00000,-0.00166,-0.00723,0.61487,0,253.57274,-0.00362,14403.98340,273.23331,281.70038,0,10082.00000,27582.00000,,,,
-311,0.10145,1.18005,405.06735,993.95294,33.4603,100.0,158.10043,37.81196,100,99.91608,100,97.18475,60.53675,61.18164,190.96793,836.56317,1982.34558,2833.82959,300.41595,998.33673,7.22390,7.64618,395.69455,40.40507,99.36937,12,11.78894,1.43294,0.27557,540833,540833,0,0,1,1,1,35.72693,37.87029,28.02909,0,1,54096.00000,0,716.25366,763.19324,0,1,2880,778.00,778.42700,1,12.03152,10,10,10,10,-2.98298,-1.65621,2.88673,5.67197,-22.00000,965.55908,9344.00000,70,10586.74219,20,-19.00000,-0.00166,74.82639,70.96356,0,279.77368,-0.00253,14649.81348,291.74179,282.18600,50,10053.00000,27582.00000,,,,
-312,0.10121,1.15995,406.14667,993.95294,33.6555,100.0,2817.69751,37.56298,100,0.29907,100,-1.88294,60.45585,61.89122,186.89549,839.67841,1969.23291,2025.99512,300.06409,993.55328,7.47571,8.59222,395.15833,44.7995,89.53247,12,11.78131,1.42609,0.27557,540833,540833,0,0,1,1,1,35.72693,37.72582,28.02902,0,1,54088.00000,0,722.69287,763.19324,0,1,2880,779.00,780.40479,1,12.02220,10,10,10,10,-3.29801,-1.74105,2.91990,5.70175,-22.00000,1000.83734,9344.00000,70,8759.19629,20,-18.00000,-0.00166,43.74278,50.6004,0,255.68393,-0.00043,13713.95020,284.41324,259.79453,0,10053.00000,27590.00000,,,,
-313,0.10145,1.16266,397.63785,993.95294,33.6555,100.0,2837.47949,37.32037,100,0.29907,0,22.10388,60.58162,61.05957,171.81433,844.27924,6.14166,32.97053,300.06409,999.57794,7.32621,0.28381,393.45734,97.80125,57.69501,12,11.78894,1.41846,0.27557,540833,540833,0,0,1,1,1,35.84900,37.78741,28.02561,0,1,54063.00000,0,716.00952,763.19324,0,1,2880,783.00,782.41223,1,12.01881,10,10,10,10,-3.62906,-1.82251,2.65461,5.75994,-20.00000,1094.92761,7600.00000,70,12698.95996,20,-18.00000,-0.00022,70.47165,67.1839,0,245.94867,0.00159,14886.05566,295.04443,246.19629,50,10053.00000,27605.00000,,,,
-314,0.10121,1.12935,445.34219,1119.68103,33.6555,0.0,123.03098,37.14794,100,0.29907,100,-1.87531,60.86557,61.53259,174.75128,829.17017,1974.14404,2828.91626,299.49182,995.2926,7.56537,7.41730,394.07236,41.46266,34.57031,12,12.01782,1.41159,0.27557,540833,540833,0,0,1,1,1,35.58960,37.89367,28.03078,0,1,54102.00000,0,712.51221,763.19324,0,1,2880,777.00,777.59619,1,11.99888,10,10,10,10,-3.34781,-1.59107,3.25151,5.85633,-22.00000,1227.85254,7600.00000,70,13169.05176,20,-18.00000,-0.00166,43.98871,33.96265,0,256.77585,-0.00181,13265.66699,297.31848,268.66092,0,10053.00000,27605.00000,,,,
-315,0.10145,1.10869,406.14667,993.95294,31.91024,100.0,94.98935,36.05755,100,0.29907,100,49.1043,60.35266,61.49621,176.46791,833.51904,1971.85510,2828.35474,299.68262,991.81366,7.64767,7.64618,394.18051,38.51413,44.06891,12,11.78894,1.40776,0.27557,540833,540833,0,0,1,1,1,35.58960,38.03101,28.02821,0,1,54097.00000,0,716.38184,763.19324,0,1,2880,779.00,779.88806,1,12.00123,10,10,10,10,-3.34363,-1.58226,3.09206,5.81925,-22.00000,1263.69678,7600.00000,70,11533.84473,20,-18.00000,-0.00166,71.31076,66.98492,0,273.45975,-0.00123,14003.61230,298.44388,264.00815,0,10053.00000,27605.00000,,,,
-316,0.10087,1.13287,397.63785,993.95294,31.91024,100.0,566.30670,36.82243,100,99.91608,0,-1.87531,60.73679,61.05957,164.44785,815.10010,1979.83167,2833.26807,299.30112,1105.4635,7.84512,7.64618,389.72742,35.51259,44.41223,12,11.78894,1.40472,0.27557,540833,540833,0,0,1,1,1,35.49804,37.96997,28.03598,0,1,54100.00000,0,705.87769,763.19324,0,1,2880,778.00,778.73492,1,11.97142,10,10,10,10,-3.40178,-1.36953,3.50088,5.95539,-20.00000,1540.58057,7600.00000,70,13532.38965,20,-18.00000,-0.00166,72.4754,75.61121,0,281.50119,-0.00210,14131.28711,299.58298,279.03088,0,10053.00000,27605.00000,,,,
-317,0.10145,1.14331,406.14667,1001.99799,33.6555,9.76668,2832.56616,37.24407,100,0.29907,0,-1.88294,60.43606,61.06250,167.12186,827.86560,89.58723,1887.02515,298.91904,1105.4635,7.92866,0.28381,392.40280,37.69975,42.74902,12,12.01782,1.40167,0.58304,540833,540833,0,0,1,1,1,35.72693,38.12255,28.03774,0,1,54098.00000,0,718.18848,763.19324,0,1,2880,779.00,780.33618,1,11.96038,10,10,10,10,-3.15057,-1.37487,3.39392,5.91938,-20.00000,2409.67554,7600.00000,70,12642.57422,20,-17.46740,-0.00166,-0.00723,68.16046,0,273.98660,-0.00022,15114.82715,300.02322,270.95132,0,10082.00000,27627.00000,,,,
-318,0.03051,1.17052,397.63785,993.95294,33.6555,0.0,2835.93530,36.74091,100,99.91608,0,-1.88294,60.51020,61.05957,162.98480,823.95172,7.09532,33.96383,299.11041,1104.50671,8.04380,0.28381,390.55325,40.45164,56.62689,12,12.01019,1.39786,0.27557,540833,540833,0,0,1,1,1,35.83374,37.92419,28.0299,0,1,54082.00000,0,701.83105,763.19324,0,1,2880,783.00,783.88116,1,11.95666,10,10,10,10,-3.41292,-1.36415,3.37533,5.96025,-20.00000,2861.26343,5584.00000,70,13497.69238,20,-17.00000,-0.00166,0.44849,49.55151,0,278.12384,0.00109,15307.83887,303.83295,275.91998,0,10053.00000,27605.00000,,,,
-319,0.10145,1.19325,397.63785,993.95294,33.6555,3.66561,182.79189,35.60677,100,99.91608,100,97.20763,60.30697,61.05194,166.36548,821.35095,1979.58008,2829.17798,298.15671,989.63934,7.97676,7.64618,383.85580,42.39336,64.91241,12,11.78894,1.39633,0.27557,540833,540833,0,0,1,1,1,35.78796,38.03215,28.0273,0,1,54111.00000,0,702.91748,763.19324,0,1,2880,779.00,779.20294,1,11.96722,10,10,10,10,-3.67553,-1.35328,3.58984,5.99706,-22.00000,4280.59277,5584.00000,70,14090.09668,20,-17.00000,-0.00166,-0.00723,0.07236,0,286.28235,-0.00188,15373.70996,305.26843,277.02625,0,10053.00000,27605.00000,,,,
-320,0.10121,1.19921,397.63785,993.95294,33.6555,100.0,1450.11633,37.77916,100,99.91608,0,-1.87531,60.16592,60.82306,160.28072,810.48810,1971.85510,2826.48828,298.15671,998.77167,8.22045,0.28381,383.38242,40.11941,40.13977,12,11.78894,1.39481,0.58304,540833,540833,0,0,1,1,1,35.78796,38.12255,28.02645,0,1,54109.00000,0,715.6311,763.19324,0,1,2880,779.00,780.68604,1,11.97091,10,10,10,10,-2.96338,-1.31065,3.62362,6.02812,-20.00000,5728.00000,5584.00000,70,14056.52051,20,-17.00000,-0.00166,65.9433,0.07236,0,294.12872,-0.00188,15389.08301,306.56241,286.34827,0,10053.00000,27627.00000,,,,
-321,0.10121,1.21667,406.14667,1105.2218,33.4603,100.0,34.95676,36.90685,100,99.91608,100,32.19757,60.10258,60.93750,160.78508,806.56702,959.19995,56.94811,299.11041,1117.85059,8.47544,0.28381,384.99301,46.40946,99.47835,12,11.78894,1.39252,0.27557,540833,540833,0,0,1,1,1,35.87951,38.19869,28.02385,0,1,54083.00000,0,709.08203,763.19324,0,1,2880,785.00,786.05255,1,11.96998,10,10,10,10,-2.67337,-1.30190,3.53878,5.96751,-22.00000,5433.25000,-160.00000,70,13979.07715,20,-17.00000,-0.00166,-0.00723,65.61053,0,290.33289,0.00029,15517.62207,307.14554,289.12759,0,10053.00000,27627.00000,,,,
-322,0.10087,1.22895,405.06735,993.95294,32.0,89.52838,34.95676,37.48619,100,0.29907,0,97.2229,60.11862,60.82306,155.67374,787.10889,1976.05127,1819.04846,298.34747,1106.42029,8.45544,7.64618,381.32010,45.40282,34.44061,12,11.78894,1.39099,0.58304,540833,540833,0,0,1,1,1,36.03211,38.73291,28.02473,0,1,54103.00000,0,698.51074,763.19324,0,1,2880,783.00,784.52924,1,12.01279,10,10,10,10,-2.70060,-1.26684,3.68059,6.02383,-22.00000,6936.00000,-160.00000,70,14038.02246,20,-16.00000,-0.00166,0.0217,71.8316,0,296.93668,-0.00101,16095.13672,312.84793,293.66901,0,10053.00000,27627.00000,,,,
-323,0.10087,1.24213,406.14667,1001.99799,33.4603,0.0,2820.62134,37.45121,100,0.29907,100,-1.85242,59.88153,61.05194,152.63307,801.24036,6.52314,31.97760,298.34747,1001.31744,8.97060,0.28381,372.04102,35.67517,99.78821,12,11.78131,1.39023,0.27557,540833,540833,0,0,1,1,1,36.18469,38.90070,28.02558,0,1,54077.00000,0,712.71973,763.19324,0,1,2880,786.00,786.97406,1,11.99101,10,10,10,10,-2.97407,-1.30683,3.64282,6.03934,-7.00000,8472.04199,-160.00000,70,14006.44824,20,100.32757,-0.00022,0.03616,68.82959,10,304.50571,0.00159,16200.27148,311.24124,295.31146,0,10053.00000,27627.00000,,,,
-324,0.10145,1.24891,397.63785,993.95294,31.91024,29.19764,2768.93530,35.62344,100,0.29907,100,-1.87531,59.90196,60.82306,159.25278,799.21039,6.71385,31.97760,297.01233,1112.74817,9.15679,0.28381,373.55652,100.0,99.43063,12,11.78894,1.38794,0.27557,540833,540833,0,0,1,1,1,36.29150,38.71764,28.02561,0,1,54079.00000,0,714.71558,763.19324,0,1,2880,786.00,786.60565,1,12.00045,10,10,10,10,-2.88202,-1.29889,3.59493,6.05783,107.00000,8902.52930,-160.00000,70,14384.72461,20,275.70370,0.00000,70.13889,0.10849,0,302.69910,0.00109,16157.44922,311.01691,299.19135,0,10053.00000,27627.00000,,,,
-325,0.10087,1.26018,405.06735,1105.2218,33.4603,100.0,35.95007,37.42172,100,0.29907,0,-1.88294,59.81965,60.58655,156.42302,785.10114,339.32559,33.96383,296.97772,994.42285,9.31578,0.28381,382.06088,38.152,97.32208,12,11.78894,1.38641,0.27557,540833,540833,0,0,1,1,1,36.33728,39.57768,28.02902,0,1,54088.00000,0,708.45337,763.19324,0,1,2880,786.00,787.32037,1,12.00491,10,10,10,10,-2.66600,-1.27469,3.66012,6.08190,-7.00000,9028.60742,-160.00000,70,14358.07422,20,108.90714,-0.00166,-0.00723,0.05423,0,305.24844,0.00043,16341.58203,313.67322,302.14673,0,10053.00000,27627.00000,,,,
-326,0.10145,1.27204,397.63785,993.95294,33.4603,100.0,2814.16479,35.86987,100,0.29907,0,-1.88294,59.70107,60.58655,114.90887,794.81250,5.95089,36.94299,296.79016,993.55328,9.98435,0.28381,380.87585,82.82694,38.24768,12,11.78131,1.38336,0.58304,540833,540833,0,0,1,1,1,36.39831,40.20038,28.03169,0,1,54089.00000,0,704.21143,763.19324,0,1,2880,786.00,785.83643,1,11.98172,10,10,10,10,-2.53899,-1.24330,3.77810,6.11555,1383.87183,10328.00000,-160.00000,70,14521.26074,20,263.06479,0.00000,71.23843,70.58374,0,311.25183,0.00072,16737.87500,313.45740,305.42575,0,10053.00000,27627.00000,,,,
-327,0.10145,1.28283,406.14667,1105.2218,31.91024,100.0,1340.01367,37.34936,100,0.29907,0,-1.87531,59.57635,60.34241,103.47511,778.00769,72.07167,35.95007,295.84814,1001.31744,10.43821,0.28381,375.11035,100.0,37.42371,12,11.78894,1.37955,0.27557,540833,540833,0,0,1,1,1,36.41358,39.42719,28.02993,0,1,54093.00000,0,723.18726,763.19324,0,1,2880,786.00,786.87622,1,12.00311,10,10,10,10,-2.69329,-1.15552,3.77456,6.13814,130.00000,10892.29785,-160.00000,70,14612.35449,20,237.20171,-0.00022,77.48843,37.90509,0,314.46790,0.00043,16640.42773,315.28406,308.69717,0,10053.00000,27627.00000,,,,
-328,0.10145,1.29239,406.14667,993.95294,31.91024,100.0,285.97864,37.49916,100,0.29907,100,-1.84479,59.40786,60.35766,148.85059,743.00452,1956.78711,2816.36328,296.05859,996.59735,10.59164,0.28381,377.45468,59.92846,36.34033,12,11.78131,1.37573,0.27557,540833,540833,0,0,1,1,1,36.52039,40.00145,28.03598,0,1,54108.00000,0,719.83032,763.19324,0,1,2880,785.00,785.23938,1,12.00790,10,10,10,10,-2.40279,-1.01868,3.84616,6.15018,130.00000,9808.00000,-160.00000,70,14644.97363,20,347.02652,-0.00022,71.45544,66.67749,0,315.37378,-0.00058,16814.97070,317.03900,310.68710,0,10052.00000,27627.00000,,,,
-329,0.10087,1.29691,397.63785,1115.11975,33.4603,1.39314,34.95676,37.45808,100,0.29907,0,-1.87531,58.99251,60.10589,151.12572,760.43427,1975.28845,2830.03906,294.48672,1114.66162,11.44831,0.28381,376.89545,43.83147,37.53052,12,11.78894,1.36658,0.27557,540833,540833,0,0,1,1,1,36.70349,40.13988,28.0247,0,1,54118.00000,0,715.14893,763.19324,0,1,2880,786.00,784.81830,1,11.96388,10,10,10,10,-2.75690,-0.66990,4.39901,6.26385,886.28040,11828.04102,-160.00000,70,15054.43457,20,558.72595,-0.00022,76.04169,68.75726,0,320.10016,-0.00239,16771.25000,318.12961,312.45160,0,10052.00000,27627.00000,,,,
-330,0.10121,1.30517,406.14667,1001.99799,33.6555,100.0,2834.25049,37.5457,100,0.29907,0,-1.87531,59.21991,59.86939,137.53703,788.21973,29.38790,151.58432,294.15164,1105.14465,11.77413,0.28381,374.70401,97.62299,98.9624,12,11.78894,1.36581,0.27557,540833,540833,0,0,1,1,1,36.70349,38.21410,28.02993,0,1,54104.00000,0,709.36279,763.19324,0,1,2880,786.00,786.47644,1,11.97826,10,10,10,10,-2.72858,-1.09809,3.94660,6.20616,551.07184,11280.00000,-160.00000,70,14828.05762,20,1226.54773,-0.00166,-0.00723,65.71905,0,319.33252,0.00058,16915.98438,318.50607,313.75888,0,10052.00000,27627.00000,,,,
-331,0.10145,1.31468,397.63785,1115.11975,33.6555,0.23349,2833.71851,35.47695,100,99.91608,0,-1.88294,59.08295,57.52716,133.97189,764.56506,1957.26453,2833.97534,293.96057,1102.91223,12.00459,0.28381,373.84079,46.04774,45.78552,12,12.01782,1.36505,0.20233,540833,540833,0,0,1,1,1,36.41358,38.63932,28.03081,0,1,54141.46875,0,715.6311,763.19324,0,1,2880,783.00,781.67749,1,11.95463,10,10,10,10,-2.29962,-1.06492,4.51801,6.33420,2831.45581,11928.00000,-160.00000,70,15241.59766,20,835.72797,-0.00166,-0.00723,0.23508,0,322.45724,-0.00188,17037.60742,319.94614,315.12689,0,10053.00000,27627.00000,,,,
-332,0.10087,1.32141,405.06735,1001.99799,31.91024,1.24246,2125.13672,37.0705,100,0.29907,0,-1.79138,56.99629,58.35876,142.50212,613.09259,1952.98303,1638.38159,293.48550,1112.11047,12.27193,0.28381,369.67764,39.53664,85.63384,12,11.78894,1.36505,0.27557,540833,540833,0,0,1,1,1,36.67297,38.12255,28.02645,0,1,54127.00000,0,708.34351,763.19324,0,1,2880,786.00,784.83014,1,11.97797,10,10,10,10,-2.58237,-0.91949,4.66146,6.36349,1792.83191,12840.00000,-160.00000,70,15226.78320,20,1286.97998,-0.00166,68.74277,74.12836,0,327.56396,-0.00087,17107.10938,322.67133,316.35065,0,10053.00000,27627.00000,,,,
-333,0.10087,1.32765,406.14667,993.95294,31.91024,100.0,30.98430,37.06669,100,0.29907,0,97.2229,56.82274,57.52716,129.75552,770.91687,1966.32568,789.89020,293.57910,999.64148,12.30263,7.64618,381.92078,37.0412,99.4059,12,11.78894,1.36429,0.20233,540833,540833,0,0,1,1,1,36.33728,38.07891,28.02382,0,1,54111.78125,0,711.89575,763.19324,0,1,2880,788.00,788.48535,1,11.95320,10,10,10,10,-2.37193,-0.47899,4.57816,6.40406,2653.00757,11928.00000,-160.00000,70,15282.30371,20,2088.57642,-0.00022,67.96152,67.25623,0,324.81003,-0.00029,17143.31250,323.00485,318.07468,0,10052.00000,27627.00000,,,,
-334,0.10087,1.33339,393.16226,1105.2218,31.91024,0.00756,933.58783,35.63679,100,99.91608,0,-1.81427,57.05169,57.16857,131.33905,685.83875,1983.02832,2832.00439,292.54013,993.55328,12.38555,7.64618,381.18240,89.09676,42.64221,12,11.78894,1.36353,0.20233,540833,540833,0,0,1,1,1,36.29150,37.95470,28.03159,0,1,54144.05859,0,708.65478,763.19324,0,1,2880,786.00,784.73975,1,11.95359,10,10,10,10,-2.54519,-0.60291,4.68009,6.67188,2030.46790,12840.00000,-288.00000,70,15598.30469,20,718.90320,-0.01237,-0.00723,0.09042,0,329.71719,-0.00340,17206.63477,323.76227,317.79874,0,10052.00000,27627.00000,,,,
-335,0.10145,1.33464,445.34219,993.95294,33.4603,100.0,30.43989,37.26353,100,0.29907,0,97.20001,56.47291,57.16857,155.33533,704.35284,1975.09753,2819.08618,292.05319,1001.31744,12.64074,8.36334,388.97516,98.41512,63.93585,12,11.78894,1.36353,0.27557,540833,540833,0,0,1,1,1,36.41358,37.87842,28.02736,0,1,54118.00000,0,701.83105,763.19324,0,1,2880,788.00,788.18976,1,11.96900,10,10,10,10,-3.03829,-1.06055,4.27864,6.53092,3078.16943,12840.00000,-224.00000,70,15523.76953,20,3223.18555,-0.00022,4.05092,65.84558,0,333.24600,-0.00116,17275.52148,324.29242,319.43250,0,10052.00000,27627.00000,,,,
-336,0.10087,1.34310,406.14667,993.95294,33.4603,10.74704,32.97053,35.81456,100,99.91608,0,-1.88294,56.17228,57.16857,163.30716,800.17749,1969.56628,1072.66028,293.00684,995.7276,12.81688,8.24890,392.73505,98.51524,43.92395,12,12.01019,1.36276,0.20233,540833,540833,0,0,1,1,1,36.13892,37.78686,28.03341,0,1,54122.00000,0,705.3894,763.19324,0,1,2880,788.00,788.68396,1,11.93834,10,10,10,10,-3.05233,-0.84577,4.68415,6.72698,2389.00000,12840.00000,-288.00000,70,15621.47070,20,2928.87256,-0.00166,76.45401,0.05423,0,335.72104,-0.00058,17337.57812,326.08847,320.89859,0,10052.00000,27627.00000,,,,
-337,0.10087,1.34422,406.14667,1001.99799,33.6555,100.0,2000.32373,37.65835,100,99.91608,0,-1.87531,55.96893,56.70318,167.31264,803.81946,6.52314,29.99137,291.67169,1108.33362,12.87582,7.64618,393.09860,31.83051,99.92873,12,11.79657,1.36276,0.20233,540833,540833,0,0,1,1,1,36.23047,36.70349,28.02821,0,1,54100.00000,0,698.06519,763.19324,0,1,2880,790.00,792.17096,1,11.91911,10,10,10,10,-3.35453,-1.24854,4.71233,6.86083,4527.76025,13639.95605,-288.00000,70,15838.94336,20,3470.90674,-0.00022,78.53732,68.66681,0,339.50952,0.00137,17359.82031,326.80554,320.16919,0,10052.00000,27627.00000,,,,
-338,0.10145,1.35148,405.06735,1105.2218,31.91024,0.0,1818.80994,37.11006,100,99.91608,0,-1.86005,56.01667,56.51548,170.93657,802.04840,1967.65881,2832.42578,285.32382,995.7276,13.07996,8.24127,395.60803,98.13264,36.68366,12,11.78894,1.36200,0.20233,540833,540833,0,0,1,1,1,36.07788,36.09313,28.02125,0,1,54142.00000,0,704.27246,763.19324,0,1,2880,786.00,785.74420,1,11.92873,10,10,10,10,-3.18500,-1.11542,4.83344,6.81504,4890.26807,13586.33301,-288.00000,70,15894.76758,20,3168.61230,-0.00166,65.06799,64.72437,10,338.42517,-0.00202,17410.97266,326.98666,323.10828,0,10052.00000,27627.00000,,,,
-339,0.10087,1.35478,406.14667,993.95294,33.6555,100.0,2826.45288,36.95988,0,0.29907,0,97.20763,54.64445,56.46329,154.41762,820.90759,29.79275,34.95676,290.67029,1119.49548,13.50911,7.64618,396.11453,39.60299,86.93848,12,11.78894,1.36124,0.20233,540833,540833,0,0,1,1,1,35.92529,36.03211,28.02382,0,1,54113.00000,0,707.72705,763.19324,0,1,2880,789.00,790.53595,1,11.91751,10,10,10,10,-3.12614,-0.98814,4.62890,6.66689,4066.73706,13752.00000,-288.00000,70,15920.30762,20,3485.98364,-0.00166,76.82294,67.85303,0,343.39725,0.00094,17516.03125,330.08688,323.90842,0,10052.00000,27627.00000,,,,
-340,0.10121,1.35652,406.14667,1115.11975,33.4603,100.0,31.97761,37.11208,100,0.29907,100,-1.88294,55.01306,56.69903,171.31805,823.51697,1164.93494,1099.30774,263.81018,1102.91223,13.34812,9.87625,397.24069,42.41496,31.2439,12,11.78894,1.36124,0.20233,540833,540833,0,0,1,1,1,35.87951,36.00158,28.02909,0,1,54114.00000,0,708.74023,763.19324,0,1,2880,789.00,789.79291,1,11.90997,10,10,10,10,-2.76110,-0.87271,4.51166,6.40794,5010.17041,13736.00000,-288.00000,70,16125.35449,20,3368.09229,-0.00022,74.45023,0.75955,0,344.41473,0.00015,17530.80859,327.81931,325.16641,0,10052.00000,27627.00000,,,,
-341,0.10121,1.36171,393.16226,1105.2218,32.0,100.0,2831.44312,36.69807,100,99.91608,0,-1.88294,52.51217,53.02751,171.12727,824.82147,1975.28845,2837.47949,259.04901,1103.8689,13.84416,10.48861,397.80225,41.32941,39.66674,12,11.78894,1.36047,0.20233,540833,540833,0,0,1,1,1,35.49804,35.91003,28.02473,0,1,54215.00000,0,709.21631,763.19324,0,1,2880,786.00,785.55267,1,11.86692,10,10,10,10,-2.96052,-0.44644,4.80627,6.77996,4387.52246,13572.35645,-288.00000,70,16223.93555,20,1853.03992,-0.00166,-0.00723,65.0318,0,346.99911,-0.00282,17523.10352,329.10696,324.92444,0,10052.00000,27627.00000,,,,
-342,0.10145,1.36276,393.16226,1119.68103,31.91024,0.44988,31.97761,37.35126,100,99.9237,100,97.21527,52.41208,53.27759,180.15161,830.03998,234.09299,1848.32092,262.77435,996.16242,13.69342,8.82873,398.51788,40.2336,33.61664,12,12.01782,1.36047,0.20233,540833,540833,0,0,1,1,1,35.58960,35.95581,28.03342,0,1,54112.00000,0,708.28857,763.19324,0,1,2880,789.00,790.08075,1,11.87189,10,10,10,10,-3.58061,-0.94571,4.65773,6.63124,5206.98828,13671.95801,-288.00000,70,16299.63574,20,3449.16870,0.00000,68.26535,72.41028,0,347.39459,0.00015,17619.95703,329.43100,327.31232,0,10052.00000,27605.00000,,,,
-343,0.10121,1.36787,406.14667,1105.2218,31.91024,100.0,2823.98560,36.97895,100,99.91608,0,97.18475,52.35020,52.81385,175.90027,833.95386,773.79498,2823.44141,255.24757,996.16242,13.88163,11.68213,400.81818,92.76894,47.86072,12,11.78894,1.35971,0.20233,540833,540833,0,0,1,1,1,35.63538,35.87951,28.0247,0,1,54136.00000,0,705.40772,763.19324,0,1,2880,787.00,787.78467,1,11.86977,10,10,10,10,-3.08654,-1.01046,4.46451,6.37285,5168.92139,12840.00000,-288.00000,70,16328.27637,20,3397.05737,-0.00166,73.60388,8.22842,0,347.67548,-0.00043,17688.94141,332.63712,327.06409,0,10052.00000,27605.00000,,,,
-344,0.10121,1.37049,406.14667,1001.99799,33.6555,100.0,33.96383,37.84668,100,99.91608,100,-1.87531,52.08331,52.80265,178.99071,872.82721,1971.28284,2823.02002,255.63379,998.27319,14.07615,12.50610,403.20346,46.39411,42.64221,12,12.01782,1.35971,0.17029,540833,540833,0,0,1,1,1,35.28442,35.86587,28.03081,0,1,54133.00000,0,701.85547,763.19324,0,1,2880,788.00,788.99536,1,11.86677,10,10,10,10,-3.66683,-1.06700,4.45619,6.53287,4146.64160,12840.00000,-288.00000,70,16530.25977,20,1831.78003,-0.00166,65.63947,0.10849,0,351.65985,-0.00058,17675.00391,333.37784,327.69144,0,10052.00000,27627.00000,,,,
-345,0.10087,1.37451,397.63785,993.95294,32.0,0.0,256.75562,37.57862,100,99.91608,0,-1.81427,51.97911,52.45361,195.06822,833.06366,1974.14404,2831.72388,251.79797,1001.31744,14.16001,12.50877,402.91394,38.95053,39.09454,12,12.01782,1.35895,0.20233,540833,540833,0,0,1,1,1,35.37598,35.77270,28.0299,0,1,54144.00000,0,701.78833,763.19324,0,1,2880,788.00,787.12280,1,11.83574,10,10,10,10,-3.91825,-1.06244,4.76590,6.70814,4563.86475,12840.00000,-288.00000,70,16632.56250,20,1514.93591,-0.00166,-0.00723,52.08331,0,358.71707,-0.00181,17702.37500,334.32782,328.21332,50,10052.00000,27605.00000,,,,
-346,0.10121,1.37603,405.06735,1001.99799,31.91024,93.55855,28.99807,35.6181,100,0.29907,0,-1.88294,51.84235,52.45361,174.75406,838.34705,1967.27759,149.46220,255.13911,1003.4917,14.06880,12.51373,404.90750,100.0,37.05749,12,11.78894,1.35818,0.20233,540833,540833,0,0,1,1,1,35.19124,35.71166,28.02909,0,1,54101.00000,0,705.34058,763.19324,0,1,2880,795.00,794.47791,1,11.82714,10,10,10,10,-3.66916,-0.91181,4.56571,6.63475,3879.28564,12840.00000,-288.00000,70,16708.21484,20,3404.31323,-0.00166,72.25839,0.05423,0,354.29327,0.00080,17814.93945,336.69421,329.11060,0,10027.00000,27605.00000,,,,
-347,0.10145,1.38055,406.14667,993.95294,33.4603,100.0,310.20639,37.18647,100,0.29907,0,-1.88294,51.80118,52.43936,175.51418,842.03632,475.43463,103.27186,254.75461,992.24847,14.24936,12.50610,405.11197,90.25772,99.6503,12,12.01782,1.35742,0.20233,540833,540833,0,0,1,1,1,35.49804,35.58960,28.02905,0,1,54105.00000,0,719.56177,763.19324,0,1,2880,792.00,792.34265,1,11.84273,10,10,10,10,-3.57884,-1.11240,4.41478,6.38105,4774.95654,12674.88965,-288.00000,70,16738.47070,20,3308.30005,-0.00166,-0.00723,55.42896,0,353.78696,0.00145,17849.95117,336.90457,329.24539,0,10027.00000,27605.00000,,,,
-348,0.03051,1.38112,397.63785,993.95294,33.4603,100.0,407.52362,37.26734,100,0.29907,0,-1.79138,51.65833,52.10266,201.42378,844.70142,92.36779,114.57875,250.07835,993.98804,14.30303,11.68213,405.11197,41.2635,44.05365,12,12.01019,1.35666,0.20233,540833,540833,0,0,1,1,1,35.37598,35.52856,28.02551,0,1,54100.00000,0,709.30786,763.19324,0,1,2880,794.00,792.91608,1,11.85296,10,10,10,10,-3.59015,-1.05784,4.22363,6.30467,5100.07764,11928.00000,-288.00000,70,16893.12891,20,3336.59448,0.00000,66.32669,66.82214,0,353.17267,0.00130,17763.21094,336.08347,330.67581,0,10051.00000,27605.00000,,,,
-349,0.10121,1.38413,405.06735,1115.11975,33.4603,100.0,2825.40674,35.71606,100,100,0,-1.82953,51.54534,51.98822,206.03358,838.15100,1975.86060,2834.81226,247.79271,989.20441,14.35215,12.75024,405.82761,48.71016,34.3338,12,12.01019,1.35600,0.20233,540833,540833,0,0,1,1,1,35.36072,35.37598,28.03074,0,1,54156.01562,0,715.78369,763.19324,0,1,2880,786.00,785.99243,1,11.84992,10,10,10,10,-3.84616,-1.26190,4.59989,6.43156,3447.13916,11883.68164,-288.00000,70,16970.99219,20,989.10254,-0.00166,62.93402,25.11939,0,360.96356,-0.00224,17799.67969,336.46750,329.76859,0,10052.00000,27605.00000,,,,
-350,0.03051,1.39045,397.63785,993.95294,33.4603,0.0,2823.72217,35.59254,100,0.29907,0,-1.87531,51.58084,51.98059,206.41327,867.37408,1962.50952,2831.02197,248.36392,1001.31744,14.23518,13.45978,406.13434,40.59052,95.02563,12,11.78131,1.35513,0.20233,540833,540833,0,0,1,1,1,35.37598,35.43700,28.0273,0,1,54143.00000,0,718.82935,763.19324,0,1,2880,786.00,786.44983,1,11.84181,10,10,10,10,-3.60242,-1.02379,4.73323,6.46828,3712.66919,11928.00000,-288.00000,70,17266.85156,20,1170.56628,-0.00166,18.76447,0.23508,0,352.95889,-0.00101,17885.50391,345.59946,332.48007,50,10052.00000,27627.00000,,,,
-351,0.10121,1.38882,405.06735,993.95294,33.6555,100.0,53.84109,37.13524,100,0.29907,100,28.00903,51.52806,52.10266,200.88194,903.53400,6.71385,2825.54712,248.18417,990.94391,14.57391,12.75024,405.77649,42.1622,93.43109,12,11.78131,1.35437,0.17029,540833,540833,0,0,1,1,1,35.45227,35.48279,28.03426,0,1,54098.00000,0,697.89429,763.19324,0,1,2880,792.00,791.34137,1,11.83501,10,10,10,10,-3.25934,-1.22711,3.96146,6.24969,5275.01172,11928.00000,-288.00000,70,17374.08984,20,1975.34863,0.00000,-0.00723,29.40533,0,375.55157,0.00094,18077.91211,333.54044,333.94766,0,10027.00000,27627.00000,,,,
-352,0.10087,1.39243,405.06735,1001.99799,32.0,0.0,1846.75049,35.77107,100,99.91608,0,-1.88294,51.37872,51.98059,205.07814,893.96667,177.91765,2828.49487,247.41206,1000.0127,14.49660,12.38403,406.84998,100.0,86.93848,12,11.78894,1.35361,0.17029,540833,540833,0,0,1,1,1,35.45227,35.23864,28.03078,0,1,54117.00000,0,705.37109,763.19324,0,1,2880,789.00,787.91815,1,11.83928,10,10,10,10,-3.96761,-1.26014,4.28422,6.32563,5174.23926,11280.00000,-288.00000,70,17518.66211,20,1596.74792,0.00000,33.65886,60.43842,0,357.28806,0.00007,18019.99609,337.44250,335.75647,0,10052.00000,27605.00000,,,,
-353,0.10121,1.39353,397.63785,1105.2218,31.91024,92.80113,2822.73950,37.63164,100,0.29907,0,-1.87531,51.32621,51.98059,206.41327,911.59430,859.67938,2822.45874,245.89539,995.2926,14.62162,13.45978,406.96954,40.57616,40.50598,12,12.01782,1.35208,0.17029,540833,540833,0,0,1,1,1,35.43700,35.29968,28.03078,0,1,54120.00000,0,712.78076,763.19324,0,1,2880,788.00,789.31018,1,11.83821,10,10,10,10,-3.43175,-1.19778,4.31012,6.27787,5056.81836,11280.00000,-288.00000,70,17237.56250,20,1375.09839,0.00000,68.95978,3.30948,0,380.92093,0.00007,18049.84375,340.79196,334.21173,0,10051.00000,27605.00000,,,,
-354,0.10145,1.39718,393.16226,1001.99799,31.91024,100.0,2837.67554,35.929,100,0.29907,100,-1.87531,51.24519,51.97296,208.12988,908.75250,38.28672,235.53368,244.94173,1002.62195,14.33133,13.45978,407.92264,39.0541,88.945,12,11.78131,1.35132,0.17029,540833,540833,0,0,1,1,1,35.49804,35.10132,28.03251,0,1,54110.00000,0,709.87549,763.19324,0,1,2880,789.00,789.97034,1,11.82558,10,10,10,10,-3.69544,-1.16794,4.44677,6.31251,2788.43091,10712.69238,-288.00000,70,17899.17773,20,891.16406,-0.01237,66.52924,70.16785,0,371.95282,0.00152,18086.33203,340.99521,334.07330,0,10051.00000,27605.00000,,,,
-355,0.10087,1.39919,397.63785,1001.99799,33.4603,100.0,2831.72388,36.86286,100,99.91608,0,-1.87531,51.10738,51.98059,203.55222,902.18658,117.84686,555.91547,245.11880,988.76959,14.58165,12.75024,408.12790,44.09728,39.54468,12,12.01782,1.35055,0.20233,540833,540833,0,0,1,1,1,35.63538,35.19287,28.02558,0,1,54106.00000,0,712.8418,763.19324,0,1,2880,790.00,790.33527,1,11.82606,10,10,10,10,-3.91143,-1.28120,4.05061,6.38275,3514.88086,9720.95215,-288.00000,70,17492.11719,20,1344.23975,-0.00166,64.67014,17.50574,0,384.47849,0.00145,17983.06836,347.91422,335.29544,0,10027.00000,27605.00000,,,,
-356,0.10121,1.40562,397.63785,1115.11975,31.91024,0.0,1671.06763,35.90229,0,99.91608,0,-1.88294,51.02406,50.79803,206.60397,883.61975,1970.90137,2820.21240,244.18233,1103.8689,14.27684,13.69629,408.79242,95.85495,99.33369,12,11.78131,1.34903,0.17029,540833,540833,0,0,1,1,1,35.72693,35.31494,28.02902,0,1,54126.00000,0,709.36279,763.19324,0,1,2880,788.00,787.97998,1,11.83314,10,10,10,10,-3.61703,-1.21256,4.62039,6.34658,2579.10767,10232.12012,-288.00000,70,17636.21094,20,819.02081,-0.00166,0.11575,61.5777,0,373.42740,-0.00036,18168.22070,350.11816,332.35831,0,10027.00000,27590.00000,,,,
-357,0.10145,1.40350,405.06735,1001.99799,33.4603,100.0,131.63753,37.70412,100,99.91608,0,97.20763,51.03974,50.79803,207.17616,896.57605,1981.77332,2834.20557,242.84363,1105.78247,14.41001,13.93280,408.89462,37.0832,97.08556,12,11.78894,1.34827,0.20233,540833,540833,0,0,1,1,1,35.45227,35.26917,28.03074,0,1,54125.00000,0,701.50147,763.19324,0,1,2880,788.00,787.81042,1,11.83649,10,10,10,10,-3.76864,-1.11110,4.24753,6.40555,2624.45874,9192.00000,-288.00000,70,18001.24219,20,665.30609,-0.00166,0.26042,66.64136,0,392.53806,-0.00137,18154.49805,347.33823,336.55914,0,10027.00000,27605.00000,,,,
-358,0.03051,1.41118,397.63785,993.95294,33.4603,100.0,30.98430,35.13058,100,99.9237,0,97.20001,50.97343,50.79803,208.50487,891.57831,1380.99231,2829.75854,245.56996,1105.4635,14.43193,12.75024,408.23013,100.0,40.51361,12,11.79657,1.34750,0.17029,540833,540833,0,0,1,1,1,35.49804,35.26917,28.03081,0,1,54108.00000,0,714.80713,763.19324,0,1,2880,789.00,789.42047,1,11.87066,10,10,10,10,-3.60495,-1.23106,3.95931,6.27633,5124.75342,9445.39648,-288.00000,70,17929.83789,20,1127.09412,0.00000,-0.00723,76.76862,0,377.11160,0.00007,18236.45898,342.35144,340.61899,0,10027.00000,27605.00000,,,,
-359,0.10121,1.41065,397.63785,1105.2218,33.6555,100.0,156.11421,37.17541,100,99.9237,0,-1.87531,50.95451,50.79803,199.94624,908.31750,1959.83899,2826.52954,243.78543,1107.37695,14.28955,13.45978,409.41083,59.07924,76.26495,12,12.01782,1.34598,0.20233,540833,540833,0,0,1,1,1,35.54382,35.22338,28.0247,0,1,54118.00000,0,714.60571,763.19324,0,1,2880,788.00,788.39172,1,11.84354,10,10,10,10,-3.51285,-1.13323,3.98679,6.29417,2813.30322,8394.33691,-288.00000,70,17967.36328,20,624.65186,-0.00166,-0.00723,62.08411,0,380.46805,0.00007,18220.39453,345.21893,337.93756,0,10027.00000,27605.00000,,,,
-360,0.10121,1.41453,405.06735,1001.99799,33.4603,100.0,2836.35645,37.30117,0,99.91608,0,-1.87531,50.96598,50.79803,203.55222,910.92682,29.54419,2824.28369,242.40675,1003.92651,14.20758,12.75024,409.66650,39.06294,44.77081,12,12.01782,1.34522,0.20233,540833,540833,0,0,1,1,1,35.78796,35.14710,28.02645,0,1,54122.00000,0,719.86084,763.19324,0,1,2880,787.00,787.35815,1,11.85228,10,10,10,10,-3.28191,-1.16397,4.09564,6.30059,2775.96094,8101.76611,-288.00000,70,17851.03125,20,1049.52661,-0.00166,61.97192,66.13501,10,364.40271,0.00065,18388.83398,346.20996,339.03699,0,10027.00000,27605.00000,,,,
-361,0.10145,1.41969,406.14667,1105.2218,33.4603,100.0,1635.25354,37.09148,100,0.29907,0,97.21527,50.82540,50.79803,202.62634,912.66638,1969.75696,1184.11194,244.75095,1103.55005,14.15604,12.75024,412.62619,76.92841,44.05365,12,11.78131,1.34369,0.20157,540833,540833,0,0,1,1,1,35.78796,35.08606,28.02909,0,1,54107.00000,0,721.81397,763.19324,0,1,2880,788.00,790.02515,1,11.84000,10,10,10,10,-3.58695,-1.15970,4.12872,6.36981,148.00000,6472.00000,-288.00000,70,17943.34570,20,447.15704,-0.01237,-0.00723,70.07739,10,373.99216,0.00072,18276.69531,341.63367,338.56500,0,10026.00000,27605.00000,,,,
-362,0.10087,1.41784,393.16226,1001.99799,33.6555,42.12607,2838.88330,35.51674,0,99.91608,0,-1.88294,50.84617,50.79803,204.69666,906.91693,1958.69434,2838.07910,209.77301,1004.57883,14.20070,13.45978,419.01581,39.67774,43.81714,12,12.01528,1.34235,0.20233,540833,540833,0,0,1,1,1,35.87951,35.19287,28.02298,0,1,54136.08984,0,710.33325,763.19324,0,1,2880,785.00,784.69751,1,11.85791,10,10,10,10,-3.63527,-1.29058,3.99185,6.33183,2334.05249,6771.76025,-288.00000,70,18475.32422,20,525.66168,-0.00166,60.69879,0.09042,0,369.73248,-0.00087,18339.41211,344.76764,339.45657,0,10027.00000,27605.00000,,,,
-363,0.10087,1.42317,397.63785,1105.2218,33.6555,100.0,2842.79004,37.39349,100,0.29907,0,-1.8219,50.87015,50.79803,202.78926,917.01508,8.86245,1950.62939,205.26326,1008.27521,14.04277,12.75024,411.19492,40.76232,91.78313,12,11.78894,1.34140,0.20233,540833,540833,0,0,1,1,1,35.92529,35.11657,28.02906,0,1,54108.00000,0,719.17114,763.19324,0,1,2880,788.00,789.48090,1,11.85063,10,10,10,10,-3.59898,-1.22340,4.10236,6.39730,2800.98950,6362.80762,-224.00000,70,18196.13477,20,1454.46082,-0.00166,3.36371,73.7124,0,365.52139,0.00210,18440.31055,353.06851,336.42334,0,10027.00000,27627.00000,,,,
-364,0.10087,1.42438,405.06735,1001.99799,33.6555,100.0,2827.91382,37.20783,100,99.91608,0,-1.87531,50.80136,50.79803,209.27425,907.44794,1967.84973,2838.46216,227.40704,994.42285,13.87258,13.45978,413.16068,42.32315,35.28747,12,11.78894,1.34064,0.20233,540833,540833,0,0,1,1,1,35.87951,35.31494,28.02219,0,1,54137.00000,0,694.71435,763.19324,0,1,2880,785.00,784.62415,1,11.87151,10,10,10,10,-2.93751,-1.27175,3.90307,6.26821,2595.38403,5312.49805,-208.00000,70,18914.08789,20,326.17441,-0.00166,33.60822,66.74988,0,391.36432,-0.00137,18347.22852,345.41779,344.30707,0,10027.00000,27627.00000,,,,
-365,0.10145,1.42909,393.16226,1105.2218,31.91024,10.16982,2841.47607,36.49448,100,100,0,-1.87531,50.65502,50.79803,208.89278,915.68066,1959.26648,2839.16406,229.79665,1002.62195,14.00842,12.75024,413.83096,40.04503,97.51282,12,12.01019,1.33905,0.20233,540833,540833,0,0,1,1,1,36.00158,35.08606,28.02818,0,1,54145.00000,0,711.83472,763.19324,0,1,2880,783.00,783.10699,1,11.84702,10,10,10,10,-3.26201,-1.29351,4.34170,6.44643,2314.24951,3935.21997,-192.00000,70,18719.13281,20,314.57938,-0.00166,63.17996,0.05423,10,388.73584,-0.00087,18494.02930,342.11990,342.18842,0,10027.00000,27627.00000,,,,
-366,0.10145,1.43113,397.63785,993.95294,33.4603,2.50288,2823.30103,37.16969,100,0.29907,100,33.05969,49.84217,50.79803,203.83318,915.27551,6.14166,1111.93982,241.88997,1007.84021,13.70278,12.51373,414.31305,95.81825,46.67053,12,11.78131,1.33696,0.20233,540833,540833,0,0,1,1,1,36.09313,35.36072,28.02558,0,1,54090.00000,0,698.74268,763.19324,0,1,2880,790.00,791.73230,1,11.87821,10,10,10,10,-3.68917,-1.25792,3.92810,6.44873,3690.33667,6472.00000,-208.00000,70,18503.92578,20,1314.70239,0.00000,71.07928,0.10849,0,381.60345,0.00347,18517.18945,355.00851,341.57178,0,10026.00000,27627.00000,,,,
-367,0.03051,1.43608,405.06735,993.95294,32.0,100.0,2844.95459,37.26162,100,99.91608,0,97.2229,50.75603,47.85342,203.14914,912.66638,241.69229,2830.47144,241.69919,1105.14465,13.74782,13.34578,414.31305,50.18668,45.95337,12,11.78894,1.33539,0.20233,540833,540833,0,0,1,1,1,36.04736,35.19287,28.02554,0,1,54121.00000,0,701.83105,763.19324,0,1,2880,786.00,786.11810,1,11.88605,10,10,10,10,-3.37021,-1.28608,3.92524,6.42033,2164.71973,3101.15601,-176.00000,70,18764.35156,20,746.99207,-0.00166,-0.00723,49.66003,0,368.28110,0.00145,18912.92578,354.83682,341.39612,0,10027.00000,27605.00000,,,,
-368,0.10087,1.43302,406.14667,1115.11975,31.91024,100.0,2839.58521,35.35145,100,99.91608,0,-1.87531,50.33376,50.20294,201.45413,905.70837,149.72377,2828.77588,200.49211,1001.7522,13.96968,12.75024,424.81223,89.75784,93.55316,12,11.78131,1.33345,0.20233,540833,540833,0,0,1,1,1,36.09313,35.11657,28.0299,0,1,54120.00000,0,715.86304,763.19324,0,1,2880,786.00,786.18372,1,11.86785,10,10,10,10,-3.48797,-1.23833,4.35199,6.48990,166.72600,4808.00000,-160.00000,70,18939.55664,20,284.99619,-0.00166,-0.00723,57.34595,0,389.03558,0.00051,18526.77148,350.43600,346.03534,0,10027.00000,27605.00000,,,,
-369,0.10087,1.43183,397.63785,1105.2218,33.4603,100.0,757.01392,35.8963,100,99.91608,0,-1.88294,47.99737,50.79803,178.06267,907.71106,1986.18030,2838.88452,231.20634,1106.42029,13.58787,13.45978,425.78943,43.94729,40.26947,12,12.01019,1.33023,0.20233,540833,540833,0,0,1,1,1,36.13892,35.46753,28.02301,0,1,54118.00000,0,722.25952,763.19324,0,1,2880,786.00,786.13922,1,11.87638,10,10,10,10,-3.62376,-0.86448,4.44390,6.79997,80.00000,3605.34302,-160.00000,70,19062.14648,20,27.71956,-0.00166,67.11517,77.07605,0,397.99368,-0.00188,18537.82617,354.36975,343.31787,0,10026.00000,27605.00000,,,,
-370,0.10121,1.44151,405.06735,993.95294,33.4603,100.0,2833.96997,37.09835,100,99.91608,0,-1.81427,50.70333,50.79803,207.74841,913.10120,197.17993,2824.98535,230.07243,994.85779,13.80385,13.45978,436.19110,37.12749,98.93188,12,11.78131,1.32634,0.20233,540833,540833,0,0,1,1,1,36.41358,35.31494,28.03081,0,1,54109.00000,0,729.49829,763.19324,0,1,2880,786.00,786.80951,1,11.88850,10,10,10,10,-3.55105,-1.30508,4.03672,6.39119,168.00000,5507.18018,-160.00000,70,18990.54492,20,190.84366,-0.00166,65.19098,63.07867,0,399.50616,0.00080,18777.00195,350.59335,345.87006,0,10026.00000,27627.00000,,,,
-371,0.10145,1.44424,406.14667,1001.99799,33.4603,100.0,1831.41455,35.42965,100,99.91608,0,-1.88294,47.37614,50.21057,202.21709,905.27338,1978.14929,2837.95020,232.87088,1000.0127,13.63807,13.58202,441.48730,99.5967,47.4945,12,11.78894,1.32080,0.20233,540833,540833,0,0,1,1,1,36.18469,35.40649,28.0247,0,1,54124.00000,0,712.5061,763.19324,0,1,2880,786.00,785.16803,1,11.89882,10,10,10,10,-3.19055,-1.14309,4.57512,6.60461,100.00000,3498.52295,-160.00000,70,19390.50000,20,21.52870,-0.00166,-0.00723,67.1839,0,395.11356,-0.00130,18561.93359,356.91666,348.29471,0,10027.00000,27605.00000,,,,
-372,0.03051,1.44639,397.63785,1001.99799,33.4603,100.0,2841.98291,36.08883,100,99.91608,0,-1.88294,50.07392,47.73101,198.62650,908.88611,356.81903,2834.25049,208.67863,1104.18787,13.71718,12.75024,428.37021,53.05699,44.88525,12,11.78894,1.31851,0.20233,540833,540833,0,0,1,1,1,36.21690,35.42175,28.0325,0,1,54127.00000,0,712.95166,763.19324,0,1,2880,784.00,784.19409,1,11.89227,10,10,10,10,-3.07796,-1.24636,4.05519,6.47199,121.96781,3338.29419,-160.00000,70,18970.98242,20,15.87715,-0.00166,73.87152,61.03516,0,400.69315,0.00015,18787.49805,356.49515,347.49399,0,10027.00000,27627.00000,,,,
-373,0.10087,1.45593,397.63785,993.95294,31.91024,100.0,2844.31006,35.59855,100,99.91608,0,-1.87531,50.42601,47.26532,199.92828,904.83856,1978.14929,2847.31738,240.74553,1103.23108,13.77614,13.69629,425.34985,92.95528,45.95337,12,11.78131,1.31164,0.20233,540833,540833,0,0,1,1,1,36.13892,35.34546,28.02905,0,1,54149.26562,0,726.44043,763.19324,0,1,2880,781.00,780.35980,1,11.92292,10,10,10,10,-3.11725,-1.26988,4.49647,6.62388,156.85147,1957.68164,-160.00000,70,18935.14062,20,-17.00000,-0.00166,66.8475,0.05423,0,404.99207,-0.00282,18500.05664,356.68427,342.32059,0,10027.00000,27627.00000,,,,
-374,0.03051,1.45451,406.14667,993.95294,33.6555,100.0,2830.74121,37.57557,100,0.29907,100,33.89129,50.57871,50.79803,208.51137,906.14319,1975.28845,2832.70654,197.82970,1003.92651,13.40204,13.92007,431.01410,43.76732,98.38257,12,11.78131,1.30623,0.20233,540833,540833,0,0,1,1,1,36.52039,35.54382,28.02561,0,1,54126.00000,0,705.52978,763.19324,0,1,2880,784.00,783.63593,1,11.91312,10,10,10,10,-2.85521,-1.11997,4.45244,6.54066,-20.00000,1659.54614,-160.00000,70,19054.94141,20,-17.00000,-0.01237,-0.00723,0.34363,0,394.85367,-0.00058,18637.63867,357.80115,349.92401,0,10026.00000,27627.00000,,,,
-375,0.10087,1.45961,397.63785,1001.99799,33.4603,100.0,2834.96118,35.47096,100,99.91608,0,-1.88294,49.72552,47.36604,197.63942,900.05493,1971.85510,2840.28711,237.91382,1003.92651,13.57803,12.75024,436.19110,33.58479,49.46289,12,11.78894,1.30140,0.20233,540833,540833,0,0,1,1,1,36.36779,35.49804,28.02824,0,1,54133.00000,0,711.57837,763.19324,0,1,2880,783.00,782.84589,1,11.90773,10,10,10,10,-2.91361,-0.95707,4.59084,6.76248,141.00000,2497.37671,-160.00000,70,19026.09375,20,-17.00000,-0.00022,-0.00723,0.07236,10,403.33911,-0.00166,18885.36133,360.34271,348.88101,0,10027.00000,27627.00000,,,,
-376,0.10121,1.46214,406.14667,993.95294,33.4603,100.0,2279.56128,37.83676,100,0.29907,0,97.20001,46.42838,48.32471,172.98303,892.11523,803.85724,567.61499,243.60651,998.33673,13.21222,12.75024,434.75983,37.15617,99.68342,12,11.78894,1.29179,0.20233,540833,540833,0,0,1,1,1,36.62720,35.65064,28.02817,0,1,54071.98828,0,708.8562,763.19324,0,1,2880,789.00,790.50232,1,11.90943,10,10,10,10,-2.89837,-0.81030,4.21721,6.69397,77.07504,3176.11865,-160.00000,70,18964.71484,20,-16.00000,0.00000,59.88861,0.05423,0,406.97501,0.00305,18970.32422,363.06445,350.07852,50,9999.00000,27627.00000,,,,
-377,0.03051,1.46469,393.16226,1105.2218,33.6555,7.50698,2421.83350,35.82573,100,99.91608,100,-1.88294,49.32362,50.79040,203.93370,892.66217,1971.85510,2839.72559,203.14644,1104.18787,13.41063,13.45978,434.75983,38.81337,99.376,12,11.78703,1.28487,0.20233,540833,540833,0,0,1,1,1,36.52039,35.68115,28.02909,0,1,54124.00000,0,729.07105,763.19324,0,1,2880,784.00,783.60748,1,11.91877,10,10,10,10,-2.76992,-0.99965,4.41925,6.58855,139.44159,1824.04333,-160.00000,70,19071.11328,20,-17.00000,0.00000,72.43201,0.05423,0,408.32593,-0.00137,18983.55273,361.28555,354.11179,0,10026.00000,27627.00000,,,,
-378,0.10087,1.46840,405.06735,1001.99799,32.0,100.0,2829.74756,37.17045,0,0.29907,0,-1.88294,46.24128,50.67632,172.08101,886.57086,121.18761,155.11578,239.97427,1101.95544,12.84717,12.75024,437.41788,39.0897,79.03442,12,12.00256,1.28037,0.27557,540833,540833,0,0,1,1,1,36.76452,35.71166,28.02909,0,1,54054.00000,0,701.77002,763.19324,0,1,2880,792.00,791.96710,1,11.92238,10,10,10,10,-3.09176,-0.77252,4.48954,6.72306,80.00000,3151.96997,-160.00000,70,18898.59961,20,-14.81820,0.00000,5.75087,0.10849,0,413.64600,0.00527,19206.08594,372.44940,348.66321,0,9999.00000,27627.00000,,,,
-379,0.10145,1.47472,405.06735,993.95294,33.6555,0.0,2474.57690,37.37148,100,99.91608,0,97.20763,46.91931,47.81706,198.78384,843.69928,1977.76782,2839.97583,202.17781,998.33673,13.23445,13.45978,445.25790,43.67572,84.53521,12,12.01782,1.26564,0.27557,540833,540833,0,0,1,1,1,36.62720,35.77270,28.02733,0,1,54121.00000,0,715.61279,763.19324,0,1,2880,785.00,782.45142,1,11.90620,10,10,10,10,-3.28799,-0.94937,4.88182,7.30060,-20.00000,1504.19714,-160.00000,70,19297.20508,20,-17.00000,-0.00022,62.5217,0.05423,0,415.38443,-0.00159,18933.95312,366.35516,353.33926,0,10026.00000,27627.00000,,,,
-380,0.03051,1.47755,406.14667,993.95294,33.4603,100.0,2857.54565,35.99614,0,99.91608,0,97.23052,46.53515,47.14005,199.51215,908.04565,653.12305,2833.12744,204.35362,1009.74396,13.43531,12.16278,442.32510,38.03748,99.51723,12,11.78131,1.25216,0.20233,540833,540833,0,0,1,1,1,36.70349,35.71166,28.02824,0,1,54127.00000,0,730.15747,763.19324,0,1,2880,781.00,781.48010,1,11.91486,10,10,10,10,-2.67793,-0.92727,4.59642,6.75585,-20.00000,1638.78259,-160.00000,70,18957.53906,20,-17.00000,-0.00166,-0.00723,14.1059,0,411.48105,0.00000,19350.84375,370.82285,351.41425,0,10027.00000,27627.00000,,,,
-381,0.10121,1.48458,397.63785,993.95294,31.91024,100.0,2835.70044,37.50068,100,99.91608,100,-1.88294,47.55019,48.08960,207.26762,888.19568,1972.99939,2839.02344,206.03645,1107.05811,13.19987,13.34534,439.30923,41.6246,43.22205,12,11.78894,1.23314,0.20233,540833,540833,0,0,1,1,1,36.70349,35.75745,28.03081,0,1,54129.00000,0,716.28418,763.19324,0,1,2880,783.00,781.77704,1,11.93881,10,10,10,10,-2.85882,-1.07564,4.48061,6.74617,-20.00000,1927.52893,-160.00000,70,19049.66602,20,-17.00000,-0.00166,54.40538,72.98901,0,419.28647,-0.00152,19178.07812,370.56747,355.20767,0,10026.00000,27627.00000,,,,
-382,0.10087,1.48923,406.14667,1001.99799,33.6555,100.0,36.94299,37.09289,100,99.91608,100,97.16187,46.84548,47.36481,204.31517,889.61786,827.42114,2829.33740,244.56024,1106.42029,12.99856,12.19582,447.47379,96.31657,42.28363,12,12.01782,1.21082,0.20233,540833,540833,0,0,1,1,1,36.70349,35.81847,28.02909,0,1,54081.00000,0,712.78076,763.19324,0,1,2880,788.00,788.26666,1,11.95014,10,10,10,10,-2.79877,-0.98569,4.18243,6.71726,137.16219,2184.54443,-160.00000,70,19119.75391,20,-17.00000,0.00000,67.86026,66.82214,10,420.93561,0.00094,19491.87109,369.72296,358.73044,0,9972.97949,27627.00000,,,,
-383,0.10121,1.49157,406.14667,1105.2218,33.6555,100.0,2830.88159,35.46791,100,99.91608,100,-1.88294,47.43898,47.72452,200.80191,875.15381,1970.32910,2842.53296,225.07808,993.55328,12.96032,12.74261,443.95569,29.3175,51.29395,12,11.78131,0.86914,0.20233,540833,540833,0,0,1,1,1,36.87198,35.77270,28.03162,0,1,54127.00000,0,711.41968,763.19324,0,1,2880,781.00,780.27991,1,11.94126,10,10,10,10,-2.61748,-0.71018,4.59341,6.72103,1571.96863,1759.02820,-160.00000,70,19333.34766,20,-18.00000,0.00000,62.89062,1.59143,0,421.90140,-0.00231,19419.22461,372.84283,359.96640,0,10027.00000,27627.00000,,,,
-384,0.10145,1.55461,405.06735,1105.2218,33.6555,100.0,2834.39111,35.56355,100,99.91608,0,-1.88294,62.01888,63.42468,220.14613,945.28204,1924.23535,2787.94775,315.67422,997.90192,15.64081,15.59601,408.28125,47.95208,47.85309,12,11.78894,1.38336,0.20233,540833,540833,0,0,1,1,1,34.68933,35.00976,28.02814,0,1,54084.00000,0,712.29248,763.19324,0,1,2880,779.00,777.21814,1,11.81874,10,10,10,10,-3.77519,-1.53290,3.36583,5.50366,295.81482,304.00000,13646.63770,70,5153.94336,20,-23.00000,-0.00022,-0.00723,30.97876,0,430.46954,0.00029,19919.49219,381.80005,368.77823,0,10082.00000,27605.00000,,,,
-385,0.10087,1.53318,397.63785,1115.11975,33.4603,100.0,2832.28540,37.44358,0,99.91608,0,-1.87531,62.33873,62.93640,220.71838,940.49835,1083.93433,956.14423,315.67422,1107.37695,18.87052,14.64996,409.12607,29.76844,98.97766,12,12.01782,1.38184,0.20233,540833,540833,0,0,1,1,1,34.78089,35.02502,28.02821,0,1,54088.00000,0,722.46704,763.19324,0,1,2880,783.00,782.27460,1,11.82298,10,10,10,10,-3.72790,-1.41961,3.26712,5.15573,98.24891,371.61234,13280.00000,70,5133.79053,20,-19.00000,-0.00022,56.47424,29.0437,0,436.13110,0.00109,20290.95703,390.56494,371.07639,0,10053.00000,27590.00000,,,,
-386,0.03051,1.53034,405.06735,1115.11975,33.4603,100.0,2836.67334,37.47028,0,99.91608,0,-1.87531,62.94538,62.71515,224.72380,944.84705,675.43335,2621.28369,313.41553,997.40363,15.85718,14.64996,409.26587,100.0,48.21167,12,11.78131,1.38107,0.20233,540833,540833,0,0,1,1,1,34.78089,35.04028,28.02993,0,1,54107.00000,0,697.69287,763.19324,0,1,2880,779.00,777.73169,1,11.81746,10,10,10,10,-3.92543,-1.45063,3.39213,5.55592,80.00000,268.18417,13520.31836,70,5306.62598,20,-19.00000,-0.00166,2.73438,76.28033,0,433.31070,0.00029,20270.21484,388.12619,371.87183,0,10082.00000,27605.00000,,,,
-387,0.10145,1.54712,406.14667,1105.2218,33.4603,100.0,2825.54712,35.04094,100,99.91608,100,25.39978,63.73576,64.47755,226.44041,950.06573,104.47872,858.02130,312.05035,994.85779,15.49233,15.22980,407.69952,37.71866,94.96459,12,11.78894,1.37878,0.20233,540833,540833,0,0,1,1,1,34.79614,35.05553,28.03514,0,1,54086.00000,0,705.47485,763.19324,0,1,2880,783.00,782.71484,1,11.82340,10,10,10,10,-4.13519,-1.39850,3.48459,5.64084,175.20444,247.64284,13516.85449,70,5212.22559,20,-19.00000,0.00000,28.99306,0.05423,0,440.75455,0.00130,20024.88281,386.42365,378.28345,0,10053.00000,27627.00000,,,,
-388,0.03051,1.55851,397.63785,1115.11975,33.4603,100.0,2833.52783,36.59748,100,99.91608,0,-1.88294,64.10326,63.65356,224.34232,945.28204,279.47229,2819.78760,313.03406,991.81366,15.43601,15.22980,407.77008,36.24929,41.68091,12,11.78894,1.37726,0.20233,540833,540833,0,0,1,1,1,34.81140,35.26917,28.02733,0,1,54105.00000,0,713.17139,763.19324,0,1,2880,778.00,777.92450,1,11.80023,10,10,10,10,-4.04867,-1.38935,3.47105,5.68098,177.68988,208.00000,13929.51855,70,5430.17529,20,-19.00000,0.00000,-0.00723,0.05423,0,445.24728,0.00000,20490.59766,392.56894,381.62415,0,10053.00000,27605.00000,,,,
-389,0.10145,1.56511,397.63785,1001.99799,33.4603,0.0,2750.73169,37.1833,100,0.29907,0,-1.87531,63.96997,67.30804,225.19536,957.89349,189.68642,33.96383,314.94138,1000.94605,15.39933,14.99329,406.90106,41.48009,45.60242,12,11.78131,1.37268,0.20233,540833,540833,0,0,1,1,1,34.85717,35.49804,28.03162,0,1,54052.24219,0,712.63428,763.19324,0,1,2880,785.00,786.31494,1,11.81701,10,10,10,10,-3.77186,-1.35158,3.50873,5.64750,1846.77625,232.00000,13856.00000,70,5201.17578,20,-19.00000,0.00000,75.06512,0.07236,0,452.39462,0.00202,20592.00195,396.70105,377.36429,0,10053.00000,27605.00000,,,,
-390,0.10145,1.57524,406.14667,993.95294,31.91024,100.0,2831.44312,35.96409,100,0.29907,0,-1.87531,64.06621,66.94183,223.00719,950.50049,1275.32288,1204.88367,308.26569,986.59528,15.34824,15.59601,407.10553,36.86532,43.58063,12,12.01019,1.37268,0.20233,540833,540833,0,0,1,1,1,34.84191,35.53156,28.03081,0,1,54106.00000,0,718.97583,763.19324,0,1,2880,779.00,778.52740,1,11.77759,10,10,10,10,-3.95971,-1.33541,3.73696,5.84572,-20.00000,144.00000,14016.17285,70,5238.03320,20,-23.00000,-0.00166,73.42303,63.82019,0,456.12775,0.00015,20440.94336,404.00003,379.71527,0,10053.00000,27605.00000,,,,
-391,0.03051,1.59391,406.14667,993.95294,31.91024,100.0,247.08232,35.36633,100,99.91608,0,97.18475,64.16627,64.36310,224.15163,949.63074,1966.89600,132.64734,313.03406,1005.66596,15.30108,15.53054,407.00333,89.65881,38.49945,12,11.78894,1.37115,0.20233,540833,540833,0,0,1,1,1,34.84191,35.62011,28.02649,0,1,54090.00000,0,715.52124,763.19324,0,1,2880,784.00,784.01544,1,11.82841,10,10,10,10,-3.72481,-1.32508,3.60250,5.78375,-20.00000,120.00000,14100.07520,70,5879.30664,20,-23.00000,-0.00166,-0.00723,22.94922,0,464.32950,0.00043,20835.55664,441.26840,384.40909,0,10053.00000,27605.00000,,,,
-392,0.03051,1.61893,397.63785,993.95294,31.92611,100.0,2828.33423,38.04771,100,99.91608,0,97.20001,66.02163,63.76801,222.77473,945.28204,1945.78857,2823.58179,312.46182,998.77167,15.19613,15.22980,406.33878,39.4282,42.03949,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.85717,35.74219,28.02558,0,1,54116.00000,0,708.36792,763.19324,0,1,2880,777.00,777.48535,1,11.85143,10,10,10,10,-3.24498,-1.31677,3.67405,5.79051,-20.00000,80.00000,14170.74902,70,6465.57617,20,-23.00000,-0.00166,-0.00723,53.87372,0,455.20996,-0.00036,21058.93359,457.17496,414.06931,0,10053.00000,27605.00000,,,,
-393,0.10121,1.63502,405.06735,993.95294,33.4603,100.0,33.96383,37.16091,100,99.91608,0,-1.88294,65.52933,65.88898,226.63112,953.10980,1967.65881,404.61072,313.79694,1107.6958,15.18234,15.59601,406.54324,99.02168,99.61165,12,11.78894,1.36658,0.20233,540833,540833,0,0,1,1,1,34.88770,35.81847,28.02821,0,1,54100.00000,0,712.43286,763.19324,0,1,2880,781.00,783.21350,1,11.90186,10,10,10,10,-3.48535,-1.33320,3.63230,5.75318,-20.00000,104.00000,14416.01953,70,5763.90479,20,-23.00000,-0.00166,-0.00723,0.05423,0,480.69669,0.00000,21498.14258,475.31091,442.68555,0,10053.00000,27605.00000,,,,
-394,0.10145,1.64577,406.14667,1105.2218,31.91024,100.0,2832.98730,37.09606,100,0.29907,0,-1.88294,65.96772,69.65790,223.00719,950.50049,11.91021,31.97760,316.27652,1104.50671,15.17342,14.64996,406.03207,100.0,48.21167,12,12.01019,1.36658,0.20233,540833,540833,0,0,1,1,1,34.91821,35.89479,28.02993,0,1,54072.00000,0,716.3269,763.19324,0,1,2880,785.00,785.21710,1,11.89475,10,10,10,10,-3.71881,-1.40630,3.57824,5.93756,-20.00000,32.00000,14439.00586,70,5474.36768,20,-19.00000,-0.00022,64.47482,63.27765,0,489.02661,0.00275,22807.88281,399.81363,391.60141,0,10053.00000,27605.00000,,,,
-395,0.10121,1.92412,405.06735,993.95294,32.0,0.0,1891.57690,35.46562,100,99.91608,100,-1.84479,66.22198,64.83612,233.30688,943.10773,172.63142,326.44495,316.65799,993.55328,15.05346,14.99329,406.38989,50.56777,99.65625,12,12.01019,1.37115,0.20233,540833,540833,0,0,1,1,1,34.90295,35.91003,28.01868,0,1,54094.00000,0,701.3916,763.19324,0,1,2880,781.00,781.37524,1,11.88665,10,10,10,10,-3.90082,-1.52226,3.70595,6.03252,-20.00000,32.00858,14528.00000,70,8454.51270,20,-23.00000,0.00000,60.35156,31.35846,0,469.44922,0.00065,21343.56250,385.87943,459.30658,50,10053.00000,27605.00000,,,,
-396,0.10087,1.71348,405.06735,993.95294,33.4603,29.40403,832.25763,36.6917,100,0.29907,100,-1.87531,66.52628,67.29992,220.71838,953.10980,7.28603,30.98430,317.58536,1002.62195,15.03101,14.99329,405.75961,44.30732,42.276,12,11.78894,1.37115,0.20233,540833,540833,0,0,1,1,1,34.91821,35.95581,28.02733,0,1,54070.00000,0,729.88281,763.19324,0,1,2880,786.00,786.86139,1,11.88475,10,10,10,10,-4.08964,-1.66105,3.62178,6.08773,-20.00000,48.00000,14494.07227,70,7413.11230,20,-19.00000,0.00000,-0.00723,61.77661,0,479.72491,0.00289,23918.04883,389.20459,399.02701,0,10052.00000,27605.00000,,,,
-397,0.10087,1.89153,406.14667,993.95294,33.4603,100.0,31.97761,37.73643,100,99.91608,0,97.23052,66.89606,67.77646,220.58138,943.53943,1965.17944,59.04652,316.65424,1102.27441,14.96840,14.77203,406.28769,100.0,42.28363,12,11.78894,1.37115,0.20233,540833,540833,0,0,1,1,1,34.94872,35.97107,28.02473,0,1,54092.00000,0,712.35352,763.19324,0,1,2880,784.00,785.06091,1,11.86843,10,10,10,10,-4.10799,-1.65801,3.74907,6.12347,-22.00000,16.00000,14880.00000,70,8206.19043,20,-23.00000,-0.00022,74.11026,72.37408,0,468.63834,0.00058,21240.51172,379.93829,394.10901,0,10052.00000,27605.00000,,,,
-398,0.10145,1.67813,405.06735,1119.68103,33.4603,100.0,2097.52661,37.63317,100,0.29907,0,-1.87531,72.08695,74.02190,221.67204,944.41223,6.33237,32.97053,332.87042,991.81366,14.94404,14.53552,405.58221,55.38161,34.3872,12,11.78131,1.37268,0.20233,540833,540833,0,0,1,1,1,34.96399,36.00158,28.03081,0,1,54081.00000,0,697.85156,763.19324,0,1,2880,785.00,785.69751,1,11.83964,10,10,10,10,-4.05930,-1.66283,3.87772,6.19820,-7.00000,16.00000,14944.00000,70,7770.48926,20,-19.00000,0.00000,-0.00723,5.66046,0,472.85712,0.00210,20885.62695,374.58505,387.42175,0,10052.00000,27605.00000,,,,
-399,0.10121,1.60794,406.14667,993.95294,31.91024,71.24424,2826.81128,36.81797,100,99.91608,0,-1.76849,68.94797,67.07153,220.14613,940.93317,1959.57202,36.22444,308.64716,1001.31744,14.86527,14.64996,406.33878,31.47086,99.69262,12,12.01782,1.37573,0.27557,540833,540833,0,0,1,1,1,35.02502,36.06262,28.02649,0,1,54115.00000,0,698.30322,763.19324,0,1,2880,779.00,781.63452,1,11.86626,10,10,10,10,-3.87760,-1.44462,4.06540,6.12648,-22.00000,8.00000,15267.07520,70,9587.02637,20,-23.00000,-0.00022,57.10358,78.10693,0,475.65015,0.00015,20455.88281,375.33734,384.80194,0,10053.00000,27605.00000,,,,
-400,0.10121,1.59121,405.06735,1001.99799,33.6555,100.0,2829.47778,38.41557,100,0.29907,0,-1.87531,73.27435,68.00231,218.62029,942.42889,144.72165,30.98430,315.67422,979.63727,14.79668,14.53552,404.90750,92.95357,44.64874,12,12.01782,1.37802,0.27557,540833,540833,0,0,1,1,1,34.99451,36.09313,28.03251,0,1,54065.00000,0,702.38648,763.19324,0,1,2880,786.00,787.44135,1,11.87863,10,10,10,10,-3.44469,-1.37623,4.22684,6.19640,-20.00000,16.00000,15376.00000,70,9826.25684,20,-19.00000,0.00000,-0.00723,48.01434,0,476.34589,0.00347,20512.63086,365.65125,373.58093,0,10052.00000,27605.00000,,,,
-401,0.10087,1.57416,405.06735,993.95294,31.91024,100.0,211.75603,36.78135,100,99.91608,100,-1.87531,66.45679,67.30804,219.57394,940.93317,1579.42554,444.07867,317.82452,1003.92651,14.84968,14.53552,405.71899,100.0,84.93195,12,11.78894,1.37878,0.27557,540833,540833,0,0,1,1,1,34.99451,36.52039,28.02733,0,1,54089.00000,0,706.073,763.19324,0,1,2880,785.00,786.22705,1,11.95702,10,10,10,10,-3.16159,-1.46399,3.85648,6.14784,-20.00000,0.00000,15456.00000,70,10663.27148,20,-23.00000,0.00000,65.42245,16.92706,0,454.05084,0.00058,19858.19336,357.98315,372.97525,0,10053.00000,27605.00000,,,,
-402,0.03051,1.55037,406.14667,1105.2218,33.6555,100.0,223.57368,36.14567,100,99.9237,0,97.20763,66.20698,67.07153,219.19247,937.88904,1976.81433,2751.04858,316.65799,1105.14465,14.73466,14.52789,404.80530,33.95025,99.4195,12,11.78894,1.38107,0.27557,540833,540833,0,0,1,1,1,34.99451,36.70349,28.03078,0,1,54102.00000,0,718.52417,763.19324,0,1,2880,783.00,784.26208,1,11.99725,10,10,10,10,-3.38318,-1.67797,3.98421,6.18210,-22.00000,0.00000,16572.34961,70,9995.60449,20,-23.00000,0.00000,65.18375,0.05423,0,453.45462,-0.00058,19758.33398,358.47357,366.51215,0,10053.00000,27590.00000,,,,
-403,0.10145,1.52039,406.14667,1105.2218,33.6555,100.0,2822.03760,37.56336,100,99.91608,100,-1.88294,73.01343,66.94183,219.19247,938.32404,6.52314,1026.23145,314.94138,1001.7522,14.71777,14.52026,404.85641,91.09844,99.75983,12,11.78894,1.38336,0.20233,540833,540833,0,0,1,1,1,35.00976,36.52039,28.0325,0,1,54098.00000,0,711.85913,763.19324,0,1,2880,783.00,783.86212,1,11.94647,10,10,10,10,-3.70704,-1.84479,3.86698,6.20026,-7.00000,0.00000,15962.10645,70,12518.16113,20,-19.00000,0.00072,72.75028,0.05423,0,439.23691,0.00080,19682.56250,346.41043,365.37912,0,10053.00000,27605.00000,,,,
-404,0.10087,1.51494,406.14667,993.95294,31.91024,100.0,107.95940,37.39361,0,0.29907,0,-1.88294,65.77955,67.17834,217.47586,937.01929,1442.78198,30.98430,317.47250,996.16242,14.67235,14.52026,405.23196,97.17117,37.78229,12,12.01782,1.38336,0.27557,540833,540833,0,0,1,1,1,35.08606,36.52039,28.02558,0,1,54080.00000,0,698.69385,763.19324,0,1,2880,786.00,787.00372,1,11.94030,10,10,10,10,-4.06914,-1.89046,3.78743,6.28616,-22.00000,0.00000,16002.38867,70,11124.75195,20,-23.00000,0.00000,0.82465,0.09042,0,437.87277,0.00137,19621.04102,339.56131,363.74030,0,10052.00000,27582.00000,,,,
-405,0.03051,1.50924,397.63785,993.95294,31.91024,100.0,2834.58838,36.26785,100,99.91608,0,-1.88294,71.13574,68.12439,218.23882,936.58447,5.95089,33.96383,314.94138,1104.82556,14.54354,14.50563,404.14075,40.80377,41.95556,12,11.78894,1.38612,0.27557,540833,540833,0,0,1,1,1,35.08606,36.90185,28.02561,0,1,54094.00000,0,705.56641,763.19324,0,1,2880,784.00,784.11389,1,11.86534,10,10,10,10,-4.19244,-1.91868,4.42460,6.65132,-20.00000,0.00000,17074.51562,70,13079.91016,20,-19.00000,0.00072,74.21875,66.02643,0,434.68097,0.00130,19547.08398,333.76831,362.92706,0,10053.00000,27605.00000,,,,
-406,0.10121,1.50388,405.06735,993.95294,31.91024,100.0,2821.48926,37.3299,100,99.91608,100,-1.88294,66.68256,73.31238,218.04811,935.71472,303.05444,2827.23145,316.65799,1111.47266,14.37596,14.41345,405.06085,35.56132,48.36425,12,12.01019,1.38718,0.27557,540833,540833,0,0,1,1,1,35.13183,37.67363,28.02817,0,1,54118.00000,0,718.64014,763.19324,0,1,2880,780.00,778.60071,1,11.82947,10,10,10,10,-4.17603,-1.88608,4.82434,6.82300,-20.00000,0.00000,16783.17188,70,13107.76660,20,-23.00000,0.00072,75.99103,63.15106,0,435.16562,-0.00051,19402.07812,328.78641,361.97903,0,10053.00000,27590.00000,,,,
-407,0.10145,1.50243,406.14667,993.95294,31.91024,100.0,2828.91626,37.34695,100,99.91608,100,-1.87531,72.41530,67.76581,218.23882,934.58826,1971.47351,2829.47778,316.43716,998.70819,14.03597,14.41345,401.40601,42.38887,42.42858,12,12.01782,1.38794,0.27557,540833,540833,0,0,1,1,1,35.19287,36.52039,28.02733,0,1,54125.00000,0,719.04297,763.19324,0,1,2880,778.00,777.77905,1,11.82634,10,10,10,10,-3.97635,-1.77509,5.15600,6.87457,-22.00000,0.00000,15872.00000,70,13954.94824,20,-23.00000,0.00000,72.41031,5.64236,0,431.35349,-0.00181,18948.05273,327.34616,359.34128,0,10053.00000,27582.00000,,,,
-408,0.10087,1.49496,405.06735,1001.99799,33.6555,100.0,2833.26929,35.39543,100,99.91608,100,97.17712,68.49872,68.00231,217.66663,936.14972,74.68349,32.97053,314.94138,1002.18701,13.79752,14.41345,403.55295,46.43153,89.29596,12,11.78894,1.38870,0.27557,540833,540833,0,0,1,1,1,35.19287,36.90185,28.03074,0,1,54092.00000,0,715.95459,763.19324,0,1,2880,784.00,784.72253,1,11.85997,10,10,10,10,-3.64670,-1.68593,4.84984,6.54543,-22.00000,0.00000,16915.23633,70,11701.65234,20,-19.00000,0.00000,36.19792,57.11084,0,427.69815,0.00094,18797.88281,324.44153,351.70810,0,10053.00000,27590.00000,,,,
-409,0.10087,1.47290,406.14667,1001.99799,33.4603,100.0,1930.07971,37.35992,100,99.91608,0,-1.85242,68.30833,63.76801,217.29179,933.10541,1972.61816,2831.86426,316.43716,992.24847,13.73198,14.41345,401.73828,43.61491,40.49835,12,11.78894,1.38946,0.58304,540833,540833,0,0,1,1,1,35.08606,36.90185,28.02558,0,1,54118.00000,0,729.99268,763.19324,0,1,2880,779.00,778.94196,1,11.91714,10,10,10,10,-3.11351,-1.48049,4.85546,6.49440,-20.00000,0.00000,16160.00000,70,13255.78418,20,-23.00000,0.00123,71.96903,62.12018,0,425.58707,-0.00231,18210.38477,323.36185,348.09662,50,10053.00000,27582.00000,,,,
-410,0.10121,1.45056,405.06735,1105.2218,33.6555,0.0,2835.25537,36.78249,100,99.91608,0,-1.88294,70.89902,67.17834,216.90367,933.97516,60.20808,2821.33569,311.88962,991.37872,13.51405,14.41345,404.19186,50.53447,50.81329,12,11.78894,1.39099,0.27557,540833,540833,0,0,1,1,1,35.08606,37.35961,28.0299,0,1,54115.00000,0,725.83008,763.19324,0,1,2880,779.00,780.05060,1,11.98562,10,10,10,10,-2.98853,-1.75235,4.36653,6.21453,-22.00000,0.00000,16336.00000,70,13563.36426,20,-19.00000,0.00072,-0.00723,70.42096,0,417.94571,-0.00015,18145.26953,320.84964,340.33115,0,10053.00000,27577.00000,,,,
-411,0.10087,1.41566,406.14667,1001.99799,31.91024,100.0,2848.69336,37.25132,100,0.29907,100,97.18475,72.67439,75.37231,217.09438,932.51733,1986.77332,28.51698,309.02856,1105.4635,12.94494,14.41345,404.68591,40.85387,40.52887,12,11.78894,1.39099,0.27557,540833,540833,0,0,1,1,1,35.02502,37.71619,28.03253,0,1,54115.00000,0,702.29492,763.19324,0,1,2880,775.00,779.41180,1,11.95552,10,10,10,10,-3.54833,-1.80952,4.24077,6.29629,-27.00000,-8.00000,14624.00000,70,13443.53125,20,-24.00000,-0.04962,-0.00723,3.05627,0,416.18698,0.00007,17961.27734,317.61124,342.95627,0,10053.00000,27574.00000,,,,
-412,0.10087,1.40621,406.14667,993.95294,33.4603,0.0,35.95007,35.94311,100,99.91608,0,-1.87531,66.42056,67.30804,216.52220,931.36603,1755.90942,2827.51245,311.69891,994.42285,13.06388,14.40582,403.22064,79.74129,45.95337,12,11.78894,1.39252,2.14605,540833,540833,0,0,1,1,1,35.00976,36.90185,28.03166,0,1,54105.00000,0,712.25586,763.19324,0,1,2880,781.00,780.73022,1,11.99611,10,10,10,10,-3.82435,-1.84182,3.76219,6.23501,-20.00000,0.00000,16621.41992,70,13197.72949,20,-23.00000,0.00123,-0.00723,0.61487,0,408.67740,-0.00109,17807.48047,314.27072,334.77261,0,10053.00000,27574.00000,,,,
-413,0.10087,1.39513,405.06735,993.95294,33.4603,100.0,2233.64624,36.16093,100,99.91608,100,-1.87531,69.06707,67.17834,216.51707,932.67059,114.17040,2818.18335,314.33914,992.68347,12.77071,14.17694,401.73828,38.1117,40.49835,12,11.78131,1.39328,2.21705,540833,540833,0,0,1,1,1,35.02502,36.90185,28.02645,0,1,54103.00000,0,712.58545,763.19324,0,1,2880,780.00,780.00195,1,11.93785,10,10,10,10,-3.99899,-1.84866,4.00167,6.38693,-20.00000,-8.00000,16240.00000,70,13477.81250,20,-23.00000,0.00123,-0.00723,21.2312,0,395.93723,-0.00058,17745.46289,311.48676,330.41168,0,10053.00000,27582.00000,,,,
-414,0.10121,1.38768,405.06735,1115.11975,31.91024,55.16893,2820.25562,34.93412,100,99.91608,100,-1.88294,66.16077,67.19726,216.14854,931.80084,1959.45740,1671.10876,311.31744,1121.7279,12.48686,14.17694,402.10938,44.96731,97.00165,12,12.02545,1.39404,0.58304,540833,540833,0,0,1,1,1,35.28442,36.90185,28.03078,0,1,54115.00000,0,712.82959,763.19324,0,1,2880,777.00,778.10333,1,11.91208,10,10,10,10,-4.01635,-1.82641,4.36116,6.49229,-22.00000,-8.00000,15744.00000,70,13349.72266,20,-23.00000,0.00000,-0.00723,64.43506,0,370.15509,-0.00123,17661.20508,310.88373,328.58105,0,10053.00000,27566.00000,,,,
-415,0.10145,1.37756,406.14667,1105.2218,31.91024,100.0,1689.13916,37.18037,100,0.29907,100,-1.88294,65.48520,69.89441,215.75925,930.30365,1966.21899,2297.09058,309.79153,1117.85059,12.41745,14.17694,401.73828,88.09845,57.33643,12,11.78894,1.39481,0.58304,540833,540833,0,0,1,1,1,35.13183,36.70349,28.02645,0,1,54112.00000,0,718.87817,763.19324,0,1,2880,778.00,778.29431,1,11.85703,10,10,10,10,-3.98043,-1.76854,4.64089,6.50780,-22.00000,-8.00000,15556.11328,70,13050.11621,20,-23.00000,0.00000,4.6441,3.4722,0,369.04834,-0.00116,17544.04688,309.03473,326.57269,0,10053.00000,27574.00000,,,,
-416,0.10145,1.36957,406.14667,1105.2218,33.4603,1.20316,2827.65283,37.21804,100,99.91608,100,97.20001,65.43666,69.89441,215.18706,929.62646,6.71385,644.82672,309.38016,1120.1333,12.50321,14.16931,401.73828,42.72977,45.95337,12,12.01019,1.39633,0.58304,540833,540833,0,0,1,1,1,35.13183,36.68823,28.02993,0,1,54091.00000,0,702.35596,763.19324,0,1,2880,783.00,781.96399,1,11.83200,10,10,10,10,-3.88758,-1.71355,4.73778,6.47924,-22.00000,0.00000,15600.00000,70,11824.31738,20,-23.00000,0.00072,61.62472,1.22977,0,362.22653,0.00029,17454.70312,307.01218,324.79785,0,10053.00000,27574.00000,,,,
-417,0.10087,1.36380,405.06735,1001.99799,33.4603,94.79919,51.35625,35.32933,100,0.29907,100,-1.87531,63.00002,67.65900,214.99635,929.53406,29.09252,34.95676,310.93597,1104.82556,11.92964,14.16931,400.15363,49.94372,57.69501,12,11.78894,1.39786,2.09896,540833,540833,0,0,1,1,1,35.19287,36.70349,28.02473,0,1,54065.00000,0,708.25806,763.19324,0,1,2880,784.00,785.01538,1,11.85183,10,10,10,10,-3.86771,-1.64434,4.72140,6.38491,-20.00000,0.00000,15488.00000,70,10697.22656,20,-23.00000,0.00072,67.73004,43.18579,0,355.11597,0.00094,17430.52148,304.63480,323.75214,0,10053.00000,27570.00000,,,,
-418,0.10145,1.35863,397.63785,1105.2218,32.0,84.29949,797.44171,36.6893,100,0.29907,100,-1.87531,63.38873,66.58325,213.76532,927.88696,6.14166,30.98430,308.07492,1119.17651,10.73810,14.06250,399.68277,100.0,99.54714,12,11.78894,1.39938,2.24062,540833,540833,0,0,1,1,1,35.26917,36.88481,28.02558,0,1,54040.51172,0,708.98438,763.19324,0,1,2880,786.00,786.49042,1,11.88340,10,10,10,10,-3.47841,-1.38519,4.47354,6.24758,-20.00000,0.00000,15168.00000,70,10445.68262,20,-23.00000,0.00123,-0.00723,52.71631,0,350.89218,0.00297,17351.74609,306.13257,321.31796,0,10053.00000,27582.00000,,,,
-419,0.10145,1.35111,406.14667,993.95294,31.91024,100.0,1008.23962,36.58871,100,0.29907,100,24.0799,63.60172,71.88568,214.80557,928.32196,1527.20508,774.98071,307.50275,992.24847,10.51723,14.16931,402.60727,48.16534,96.61254,12,11.78894,1.40167,0.58304,540833,540833,0,0,1,1,1,35.19287,36.52039,28.02733,0,1,54097.00000,0,701.66016,763.19324,0,1,2880,779.00,779.81812,1,11.92551,10,10,10,10,-3.13589,-1.38017,4.48311,6.18572,-22.00000,0.00000,14991.01953,70,12253.30176,20,-23.00000,0.00000,55.31683,18.06641,0,341.74881,-0.00036,17252.23047,297.87985,321.17056,0,10053.00000,27562.00000,,,,
-420,0.10145,1.34849,405.06735,1001.99799,31.91024,99.99104,139.95517,37.03617,100,99.91608,0,97.18475,64.37621,64.83612,214.05724,924.40802,1971.70239,2828.07373,307.88422,1002.18701,9.10680,14.16931,402.50500,63.05313,99.72677,12,11.78894,1.40396,2.22872,540833,540833,0,0,1,1,1,35.28442,36.90185,28.02652,0,1,54108.00000,0,715.84473,763.19324,0,1,2880,777.00,776.49585,1,11.95847,10,10,10,10,-2.75423,-1.39119,4.26728,6.15554,-22.00000,0.00000,14800.00000,70,12610.01562,20,-23.00000,0.00000,73.28558,0.05423,0,339.24045,-0.00202,17237.75977,298.88171,319.92691,0,10053.00000,27554.00000,,,,
-421,0.10145,1.34240,406.14667,1105.2218,31.91024,92.08475,32.97053,37.63546,100,0.29907,100,11.65924,62.72691,65.65247,213.57330,925.71259,1842.53625,30.98430,308.26569,1114.0238,9.06209,14.05487,401.66550,42.219,42.28363,12,12.01019,1.40701,0.58304,540833,540833,0,0,1,1,1,35.13183,36.36779,28.02993,0,1,54050.73828,0,715.36255,763.19324,0,1,2880,784.00,785.80847,1,11.97292,10,10,10,10,-2.92420,-1.45220,3.70218,6.10013,-25.00000,0.00000,14844.17480,70,10967.53711,20,-23.00000,0.00000,77.58246,0.09042,0,333.72046,0.00087,17051.86719,296.28394,317.91718,0,10053.00000,27562.00000,,,,
-422,0.10145,1.33660,406.14667,1001.99799,31.91024,100.0,2820.79858,35.84851,100,99.91608,0,-1.87531,62.76286,63.76801,212.89825,924.84283,6.33237,32.97053,307.31323,1105.14465,8.81212,14.04724,402.04498,43.34987,45.24383,12,12.01782,1.41083,0.58304,540833,540833,0,0,1,1,1,35.28442,36.09313,28.02817,0,1,54058.00000,0,712.51221,763.19324,0,1,2880,783.00,784.50616,1,11.97597,10,10,10,10,-3.24215,-1.56465,3.68698,6.08001,-22.00000,16.00000,14608.00000,70,10091.09277,20,-23.00000,0.00000,69.18402,76.38892,0,331.68686,0.00080,17024.70117,286.41788,316.79633,0,10053.00000,27558.00000,,,,
-423,0.10121,1.33529,397.63785,1001.99799,33.4603,100.0,2826.25586,35.75211,100,99.91608,0,97.23052,63.12013,62.93640,211.75383,923.10327,1979.12024,2835.02856,306.93054,999.14294,8.19855,14.05487,399.89679,45.6761,42.04711,12,11.78894,1.41312,2.04473,540833,540833,0,0,1,1,1,35.19287,36.15417,28.02817,0,1,54113.00000,0,714.85596,763.19324,0,1,2880,771.00,773.71851,1,11.98744,10,10,10,10,-2.66994,-1.41210,3.77237,6.08434,-25.00000,8.00000,14324.24121,70,12079.24219,20,-23.00000,0.00000,73.42303,0.07236,0,326.72385,-0.00443,16962.00195,286.94794,315.82687,0,10053.00000,27554.00000,,,,
-424,0.10145,1.32810,406.14667,993.95294,31.91024,100.0,1805.77014,35.7399,100,99.91608,100,-1.88294,62.91557,63.65356,211.56313,923.48431,6.52314,34.05505,307.12125,985.72546,8.11933,13.93280,400.61371,33.34259,100.0,12,11.78894,1.42385,0.58304,540833,540833,0,0,1,1,1,35.37598,36.70349,28.02733,0,1,54057.00000,0,714.82544,763.19324,0,1,2880,783.00,783.23029,1,11.97629,10,10,10,10,-3.04963,-1.59754,3.69633,6.04920,-25.00000,40.00000,14311.92969,70,10319.14648,20,-23.00000,0.00000,-0.00723,43.96338,0,322.77805,0.00109,16895.40039,277.21350,314.48029,0,10053.00000,27554.00000,,,,
-425,0.10121,1.32208,397.63785,1105.2218,31.91024,96.95546,2198.98193,35.70927,0,99.91608,100,97.23052,61.47269,62.36419,211.37234,923.07690,26.68878,30.80841,305.59534,1000.88245,7.43759,13.63900,398.77350,90.52559,36.34796,12,11.78894,1.43994,2.00516,540833,540833,0,0,1,1,1,35.19287,36.50513,28.02467,0,1,54037.84375,0,698.84033,763.19324,0,1,2880,785.00,785.89673,1,11.94620,10,10,10,10,-3.27222,-1.42405,3.67204,6.04075,-25.00000,72.00000,14048.00000,70,8319.41406,20,-23.00000,0.00000,65.45139,74.94214,0,320.51370,0.00246,16863.00977,296.04214,311.90103,0,10053.00000,27570.00000,,,,
-426,0.10121,1.31649,397.63785,1119.68103,33.6555,100.0,2826.24902,35.42202,100,0.29907,0,-1.79138,62.16082,63.42468,211.94453,920.92896,1970.90137,2829.05664,304.82831,993.11829,7.62075,13.69629,398.87570,46.44454,35.63842,12,11.78894,1.43600,0.58304,540833,540833,0,0,1,1,1,35.54382,36.15417,28.03078,0,1,54105.00000,0,719.43359,763.19324,0,1,2880,771.00,772.81543,1,12.00008,10,10,10,10,-2.73082,-1.43740,3.67812,5.97252,-25.00000,80.00000,13709.96680,70,10388.36719,20,-23.00000,0.00000,70.79715,60.13098,0,312.44299,-0.00210,16656.61328,257.25748,312.99405,0,10053.00000,27554.00000,,,,
-427,0.10121,1.31235,405.06735,993.95294,33.4603,99.49468,2328.43921,35.78289,100,99.91608,0,-1.88294,61.80027,62.47863,211.11676,921.36395,1955.87170,1520.62769,305.22775,994.85779,7.72266,13.45167,399.01895,80.43591,90.82946,12,11.78894,1.44821,0.58304,540833,540833,0,0,1,1,1,35.36072,36.15417,28.02817,0,1,54088.00000,0,709.74731,763.19324,0,1,2880,779.00,779.64447,1,11.99492,10,10,10,10,-3.10757,-1.44301,3.54952,5.98289,-25.00000,160.00000,13359.77539,70,7224.90332,20,-23.00000,0.00000,68.52576,62.01172,0,310.33368,-0.00036,16592.10742,271.49707,309.58035,0,10053.00000,27558.00000,,,,
-428,0.10087,1.30691,406.14667,1105.2218,31.91024,100.0,2151.15015,36.09074,100,99.91608,0,-1.88294,61.94695,62.36419,210.72247,918.31982,1970.52002,2831.30273,303.65833,1002.62195,7.18805,12.75024,399.56137,40.70861,46.08307,12,12.01019,1.46212,0.58304,540833,540833,0,0,1,1,1,35.36072,36.52039,28.02909,0,1,54107.00000,0,726.42822,763.19324,0,1,2880,771.00,769.65601,1,11.99941,10,10,10,10,-2.86439,-1.41572,3.57597,5.98983,-25.00000,216.00000,13311.97168,70,11080.82129,20,-23.00000,-0.00022,60.92303,1.98932,0,301.35876,-0.00253,16433.10938,256.65268,310.08542,0,10082.00000,27558.00000,,,,
-429,0.10087,1.30090,445.34219,1001.99799,31.91024,32.6436,1431.33191,35.60971,100,99.91608,0,-1.86005,61.64546,62.36419,209.84651,917.88483,1969.75696,2830.88159,304.26019,1003.55536,7.25769,12.37782,398.24194,82.52219,55.3299,12,11.78131,1.47415,0.58304,540833,540833,0,0,1,1,1,35.37598,36.36779,28.03078,0,1,54105.00000,0,719.34815,763.19324,0,1,2880,771.00,772.97162,1,11.98878,10,10,10,10,-2.98533,-1.37835,3.71229,6.03021,-25.00000,296.00000,13213.50391,70,10029.19922,20,-23.00000,0.00000,60.28644,67.7807,0,299.06909,-0.00268,16450.77734,273.86505,306.75330,0,10053.00000,27558.00000,,,,
-430,0.10145,1.29307,406.14667,993.95294,33.4603,100.0,32.97053,37.53006,100,0.29907,0,-1.87531,61.42699,62.36419,206.03180,917.48926,1688.55835,50.28572,304.64169,1000.88245,7.01247,10.85052,398.32178,47.10479,99.06921,12,11.78894,1.50339,0.58304,540833,540833,0,0,1,1,1,35.45227,36.36779,28.02993,0,1,54026.92969,0,705.896,763.19324,0,1,2880,783.00,784.66858,1,12.00381,10,10,10,10,-2.99180,-1.42952,3.40021,5.92970,-25.00000,402.54730,13056.02246,70,8442.15820,20,-23.00000,0.00000,74.94214,0.05423,0,298.64615,0.00094,16373.27637,260.80554,303.67911,0,10053.00000,27566.00000,,,,
-431,0.03051,1.28724,406.14667,1105.2218,33.4603,100.0,56.95288,35.90573,100,99.91608,100,97.2229,61.77296,62.60071,207.93912,915.03204,1980.43811,2836.49683,303.87878,989.63934,6.39487,11.68213,397.54669,43.61792,99.59906,12,12.01782,1.52895,0.58304,540833,540833,0,0,1,1,1,35.54382,36.70349,28.03169,0,1,54102.00000,0,715.56397,763.19324,0,1,2880,771.00,771.36011,1,12.00091,10,10,10,10,-2.73756,-1.36582,3.59947,5.91468,-22.00000,487.15720,12840.39648,70,10736.58398,20,-23.00000,-0.00022,-0.00723,70.34869,0,297.84274,-0.00311,16173.59277,252.06902,303.96680,0,10053.00000,27566.00000,,,,
-432,0.10145,1.27816,397.63785,1105.2218,33.4603,100.0,2819.74561,37.35317,100,99.91608,0,97.20763,61.53679,62.34894,205.26883,909.62225,1981.20117,2836.35645,303.87878,1104.18787,6.65247,10.01892,397.68506,32.41397,98.74115,12,12.01782,1.54819,2.07712,540833,540833,0,0,1,1,1,35.63538,36.32236,28.03517,0,1,54104.00000,0,726.3855,763.19324,0,1,2880,771.00,773.35278,1,12.01908,10,10,10,10,-2.93209,-1.37282,3.59725,5.94078,-25.00000,511.78326,12298.55078,70,10800.23438,20,-23.00000,-0.00166,76.14294,0.10849,0,288.76105,-0.00326,15949.39746,278.51685,299.69897,0,10053.00000,27562.00000,,,,
-433,0.10087,1.26542,445.34219,1001.99799,33.4603,0.0,154.75732,35.98812,100,0.29907,0,-1.87531,61.12888,62.93640,203.17075,915.71045,1966.89600,755.95648,303.49731,1107.05811,6.70397,8.47778,397.80225,100.0,99.21691,12,11.78131,1.51852,0.58304,540833,540833,0,0,1,1,1,35.72693,36.52039,28.02389,0,1,54057.00000,0,726.61743,763.19324,0,1,2880,781.00,783.96124,1,12.02851,10,10,10,10,-2.55225,-1.42721,3.17664,5.74156,-22.00000,580.09668,12529.12598,70,6685.67236,20,-23.00000,-0.00022,52.3727,65.41162,0,272.76016,0.00015,15647.25098,285.81250,288.33319,0,10053.00000,27570.00000,,,,
-434,0.10145,1.25445,405.06735,1001.99799,33.6555,0.0,2808.44360,37.31121,100,99.91608,0,-1.88294,61.09026,62.24976,203.93370,912.23138,595.59784,1138.88403,303.49731,994.42285,7.04985,8.23870,397.51874,100.0,40.49072,12,12.01782,1.54333,0.27557,540833,540833,0,0,1,1,1,35.63538,36.36779,28.02993,0,1,54061.00000,0,717.94434,763.19324,0,1,2880,781.00,782.51880,1,12.02683,10,10,10,10,-2.91125,-1.44672,3.30797,5.80536,-22.00000,631.68054,12060.17285,70,7313.16943,20,-23.00000,-0.00022,-0.00723,61.27026,0,283.07236,0.00051,15786.23145,274.88425,290.21417,0,10053.00000,27582.00000,,,,
-435,0.10121,1.24078,405.06735,1105.2218,31.91024,100.0,2834.53149,37.54963,100,99.91608,0,-1.88294,61.03710,61.17401,197.25801,897.44562,535.48071,2831.16211,301.56027,1000.0127,6.87392,7.64618,396.29626,44.03888,55.32227,12,11.78894,1.49304,0.27557,540833,540833,0,0,1,1,1,35.63538,36.52039,28.02736,0,1,54100.00000,0,723.32764,763.19324,0,1,2880,771.00,773.18524,1,12.02487,10,10,10,10,-2.91906,-1.51670,3.36945,5.87628,-22.00000,697.89203,11904.00000,70,11156.89648,20,-23.00000,0.00000,68.71384,8.48163,0,251.39447,-0.00072,15495.98340,275.55179,290.52560,50,10082.00000,27582.00000,,,,
-436,0.10121,1.23430,405.06735,1001.99799,33.4603,100.0,1861.49353,37.14439,100,99.91608,0,-1.87531,61.11509,61.29608,179.28239,892.22717,1972.61816,2832.70654,302.92508,1114.34277,6.79669,8.24127,396.72882,39.03762,46.06781,12,11.78894,1.46861,0.27557,540833,540833,0,0,1,1,1,35.63538,37.47531,28.02811,0,1,54104.00000,0,719.64111,763.19324,0,1,2880,771.00,776.13086,1,12.05263,10,10,10,10,-2.63213,-1.45476,3.18978,5.71098,-22.00000,780.31567,11408.00000,70,9775.65820,20,-23.00000,-0.00166,1.97482,2.65842,0,271.45242,-0.00166,15691.67480,289.86948,296.54706,0,10082.00000,27582.00000,,,,
-437,0.10087,1.20408,405.06735,1115.11975,33.4603,100.0,2821.04126,35.09091,100,0.29907,0,-1.88294,60.71485,61.82470,172.08667,876.18738,1970.13855,2831.51147,301.39923,989.20441,6.84360,7.56226,395.86340,39.27007,37.29401,12,12.01782,1.46064,2.06747,540833,540833,0,0,1,1,1,35.72693,37.34435,28.02993,0,1,54100.00000,0,712.27417,763.19324,0,1,2880,771.00,772.54242,1,12.03604,10,10,10,10,-2.87666,-1.48897,3.40959,5.75799,-22.00000,831.58588,9344.00000,70,11442.53613,20,-19.00000,-0.00166,0.13745,0.09042,0,242.41705,-0.00137,15016.82031,284.92435,289.68387,0,10082.00000,27582.00000,,,,
-438,0.10121,1.18704,397.63785,993.95294,31.91024,36.42269,35.29465,36.99955,100,99.91608,0,-1.89057,60.55464,61.99782,177.54840,859.86804,1976.62341,2828.07373,301.21591,1112.74817,7.24582,8.34828,396.52396,38.60247,40.37628,12,11.78894,1.44821,0.58304,540833,540833,0,0,1,1,1,35.58960,37.68005,28.03253,0,1,54086.00000,0,716.22925,763.19324,0,1,2880,780.00,780.97113,1,12.04273,10,10,10,10,-3.33009,-1.47206,3.22249,5.82813,-22.00000,918.97003,9344.00000,70,11367.09668,20,-19.00000,-0.00166,-0.00723,21.24927,0,268.54712,-0.00109,14752.55762,289.39981,279.61237,0,10053.00000,27582.00000,,,,
-439,0.10145,1.16533,397.63785,1001.99799,33.4603,100.0,2835.09277,37.33219,100,0.29907,100,-1.88294,60.78109,61.89117,197.50749,863.66211,223.53894,2815.23828,300.63626,1106.42029,7.40839,8.95291,396.01318,40.42098,40.74249,12,11.78131,1.44135,0.27557,540833,540833,0,0,1,1,1,35.54382,37.63427,28.02301,0,1,54090.00000,0,730.30395,763.19324,0,1,2880,778.00,779.23376,1,12.02090,10,10,10,10,-3.28560,-1.64880,3.31232,5.85400,-22.00000,944.59344,9344.00000,70,11328.21484,20,-18.00000,-0.00166,73.09027,0.05423,0,248.30557,0.00000,13955.83496,288.04138,268.05313,0,10053.00000,27605.00000,,,,
-440,0.10087,1.17210,405.06735,1115.11975,33.6555,0.0,2833.40845,35.86987,100,0.29907,0,-1.88294,60.41187,61.18164,172.62987,835.75104,1952.03027,2823.72217,300.25479,1104.82556,7.44769,7.64618,395.09308,96.9357,92.49268,12,11.78894,1.43039,0.58304,540833,540833,0,0,1,1,1,35.71166,37.77161,28.02909,0,1,54098.00000,0,716.07056,763.19324,0,1,2880,778.00,778.05237,1,12.03358,10,10,10,10,-3.39599,-1.73181,3.26262,5.78064,-22.00000,1112.00623,9344.00000,70,10426.51758,20,-18.00000,-0.00166,72.99625,0.30743,0,270.96222,-0.00058,14319.33301,297.02332,260.89090,0,10082.00000,27590.00000,,,,
-441,0.10087,1.13641,406.14667,1001.99799,33.6555,100.0,1651.55322,37.43128,100,99.91608,0,-1.87531,61.01563,61.29608,173.60686,822.21222,1974.90686,2835.37378,300.41595,1107.37695,7.42323,8.35571,393.99243,99.65074,93.57605,12,11.78131,1.41997,0.58304,540833,540833,0,0,1,1,1,35.69641,37.83222,28.03162,0,1,54106.00000,0,702.27661,763.19324,0,1,2880,776.00,776.86938,1,12.01631,10,10,10,10,-3.49729,-1.54165,3.28817,5.94532,-22.00000,1161.29407,9344.00000,70,11728.02734,20,-18.00000,-0.00166,72.90219,2.51376,0,276.86584,-0.00282,13493.44336,299.08707,271.53464,0,10053.00000,27590.00000,,,,
-442,0.10145,1.07114,405.06735,993.95294,33.6555,100.0,664.85834,35.66884,100,0.29907,100,97.19238,60.46325,61.17389,176.08643,837.43292,1957.93152,2827.37354,299.87332,1118.5387,7.58939,7.64618,394.57935,37.50186,99.4813,12,12.01782,1.41693,0.27557,540833,540833,0,0,1,1,1,35.63538,37.86315,28.03422,0,1,54098.00000,0,701.66016,763.19324,0,1,2880,778.00,778.55945,1,11.98827,10,10,10,10,-3.93275,-1.62842,3.51256,5.98662,-22.00000,1207.98718,7600.00000,70,13138.81738,20,-18.00000,-0.00166,64.93778,14.79309,0,261.81238,-0.00087,13620.93652,298.22009,253.86829,0,10053.00000,27605.00000,,,,
-443,0.10087,1.15742,397.63785,1001.99799,33.4603,100.0,467.32629,36.03619,100,99.91608,100,97.18475,60.92620,61.06720,169.47983,816.53802,1975.28845,2832.28540,299.67429,992.68347,7.53702,7.63855,391.41107,35.99743,44.77844,12,11.78894,1.40787,0.58304,540833,540833,0,0,1,1,1,35.77829,37.92419,28.02733,0,1,54112.00000,0,694.6228,763.19324,0,1,2880,776.00,775.84644,1,12.00450,10,10,10,10,-3.30959,-1.41392,3.30277,5.89208,-22.00000,1277.98083,7600.00000,70,13287.14648,20,-18.00000,-0.00166,66.13861,69.08276,0,275.09198,-0.00210,12625.00000,298.59308,278.29926,0,10053.00000,27605.00000,,,,
-444,0.10121,0.94729,397.63785,1001.99799,32.0,100.0,2822.45874,35.47123,100,0.29907,0,-1.87531,60.81073,61.29608,168.83849,835.25842,691.04773,1708.63037,299.84372,993.98804,7.73875,7.28760,393.78406,43.92619,45.83893,12,11.78894,1.40472,0.58304,540833,540833,0,0,1,1,1,35.92529,37.98523,28.03686,0,1,54085.64844,0,719.65942,763.19324,0,1,2880,781.00,782.58618,1,11.97236,10,10,10,10,-3.80084,-1.43149,3.45390,5.98501,-20.00000,1894.39209,5584.00000,70,12714.10645,20,-18.00000,-0.00166,73.40857,72.86237,0,278.85065,0.00043,15192.86719,302.64258,258.42014,0,10053.00000,27605.00000,,,,
-445,0.10087,1.09969,406.14667,993.95294,33.6555,0.0,1623.16345,36.89274,100,99.91608,0,-1.87531,60.49902,61.06720,167.57291,825.99908,1966.13293,2152.15601,299.11041,999.57794,7.91248,0.28381,393.32593,40.98224,42.87872,12,11.78131,1.40246,0.27557,540833,540833,0,0,1,1,1,35.78796,38.00048,28.03253,0,1,54100.00000,0,712.76245,763.19324,0,1,2880,779.00,780.48779,1,11.98369,10,10,10,10,-3.73361,-1.34963,3.48154,6.01931,-22.00000,2649.04712,5584.00000,70,13316.97754,20,-18.00000,-0.00166,61.68982,13.50909,0,267.82654,-0.00058,14684.56836,303.10953,275.29959,0,10053.00000,27605.00000,,,,
-446,0.10087,1.14937,406.14667,1105.2218,32.0,30.43616,33.96383,36.96586,100,99.91608,0,-1.88294,60.41964,61.18164,169.02919,820.03784,1978.72156,2821.68091,299.49182,995.7276,7.99581,7.40967,393.57190,37.37792,81.49872,12,11.78131,1.39786,0.27557,540833,540833,0,0,1,1,1,35.69641,38.12255,28.0274,0,1,54097.00000,0,716.35132,763.19324,0,1,2880,781.00,782.19415,1,11.99394,10,10,10,10,-3.57142,-1.33855,3.37956,6.01029,-22.00000,3442.00854,5584.00000,70,13803.46094,20,-18.00000,-0.00166,-0.00723,0.05423,0,287.27414,-0.00130,15228.61328,303.58658,272.19385,0,10053.00000,27605.00000,,,,
-447,0.10121,1.18421,405.06735,1105.2218,33.6555,100.0,1039.37012,36.75033,100,0.29907,100,-1.88294,60.31950,61.05194,152.10521,823.08197,6.33237,30.98430,298.91965,991.37872,7.83698,0.28381,382.84323,99.91249,42.9779,12,11.78894,1.39709,0.58304,540833,540833,0,0,1,1,1,35.92529,38.28357,28.0273,0,1,54047.00000,0,714.77661,763.19324,0,1,2880,786.00,787.24139,1,11.95080,10,10,10,10,-3.43830,-1.31161,3.56866,6.07594,-7.00000,6078.96338,5584.00000,70,13729.07324,20,-17.00000,0.00000,-0.00723,69.26355,0,285.32312,0.00265,15619.62695,308.02621,262.35641,0,10053.00000,27627.00000,,,,
-448,0.10121,1.18879,405.06735,993.95294,33.4603,0.00755,58.88510,36.02169,100,99.91608,0,-1.8219,60.20032,61.05957,164.07011,818.17773,1968.99414,2781.03833,298.70258,998.70819,8.26192,7.27997,391.82092,78.51456,43.93539,12,12.01019,1.39481,0.27557,540833,540833,0,0,1,1,1,35.87951,38.35944,28.0247,0,1,54100.00000,0,708.84399,763.19324,0,1,2880,781.00,782.69171,1,11.99364,10,10,10,10,-3.20003,-1.30831,3.55527,6.04288,-22.00000,5988.35645,5584.00000,70,14105.26270,20,-17.00000,-0.00166,0.0434,0.07236,0,291.77420,-0.00080,15673.37793,307.56976,283.92795,0,10053.00000,27605.00000,,,,
-449,0.10187,1.20753,405.06735,1001.99799,33.6555,99.89053,2823.16040,37.0705,0,0.29907,0,0.77973,60.24585,61.05194,125.39907,793.94330,6.52314,34.95676,298.53818,1103.55005,8.37642,0.28381,388.30164,35.62881,38.48419,12,11.78131,1.39328,1.80603,540833,540833,0,0,1,1,1,36.04736,38.03101,28.03605,0,1,54074.00000,0,715.04517,763.19324,0,1,2880,786.00,786.42493,1,11.98411,10,10,10,10,-3.14403,-1.29666,3.60496,6.06426,-20.00000,7287.95410,-160.00000,70,14279.21973,20,-9.01734,-0.00022,-0.00723,2.06162,0,295.97318,0.00137,15811.82617,309.65710,285.36295,0,10053.00000,27627.00000,,,,
-450,0.10121,1.22561,406.14667,1001.99799,33.6555,100.0,34.95676,37.03338,100,99.91608,100,-1.88294,60.13325,60.70861,164.95544,797.83063,1967.84973,2819.99365,298.72894,1101.6366,8.83655,7.29523,384.24252,30.23055,42.28363,12,12.01019,1.39099,0.27557,540833,540833,0,0,1,1,1,36.04105,38.59676,28.0299,0,1,54103.00000,0,711.94458,763.19324,0,1,2880,783.00,784.06702,1,12.01843,10,10,10,10,-3.01843,-1.29579,3.53621,6.03701,-20.00000,7587.66162,-160.00000,70,14137.95215,20,-16.00000,-0.00166,76.28763,46.13354,0,300.95773,-0.00101,16013.83691,310.66653,293.26730,0,10053.00000,27627.00000,,,,
-451,0.10121,1.23589,405.06735,1115.11975,33.6555,100.0,31.97761,37.06478,100,99.91608,100,-1.87531,59.97990,60.93750,170.58704,802.92480,1977.76782,2822.17773,298.34747,993.11829,8.73225,7.40967,375.88406,39.68203,99.66681,12,12.01019,1.39023,0.27557,540833,540833,0,0,1,1,1,36.13892,39.71960,28.02561,0,1,54103.00000,0,708.65478,763.19324,0,1,2880,784.00,784.57220,1,12.02958,10,10,10,10,-3.09842,-1.27834,3.48624,6.04497,-20.00000,8761.20117,-160.00000,70,13890.97266,20,141.65298,-0.00166,71.67969,0.07236,0,305.73022,-0.00159,16071.75586,311.72653,300.66605,0,10053.00000,27627.00000,,,,
-452,0.10087,1.25288,406.14667,993.95294,33.6555,100.0,159.23918,36.6795,100,0.29907,0,-1.88294,60.06478,60.47211,169.79214,790.19867,1972.42725,2344.87183,297.69879,1003.05676,8.69982,7.64618,376.08865,44.76483,93.6676,12,11.78894,1.38870,0.27557,540833,540833,0,0,1,1,1,36.09313,39.03808,28.02899,0,1,54112.00000,0,715.71045,763.19324,0,1,2880,781.00,781.71466,1,12.01419,10,10,10,10,-3.03433,-1.22212,3.71505,6.09787,-20.00000,9368.96875,-160.00000,70,14470.20801,20,-16.00000,-0.00166,73.94388,72.75391,0,309.57260,-0.00145,16250.48145,312.46991,300.48425,0,10053.00000,27627.00000,,,,
-453,0.10087,1.25870,406.14667,1001.99799,33.4603,100.0,1549.45996,35.59101,100,0.29907,100,-1.87531,60.03675,60.70861,145.05786,807.51282,5.95089,30.98430,298.07449,1007.40546,9.37647,0.28381,378.13483,37.14966,37.86621,12,12.01782,1.38641,0.58304,540833,540833,0,0,1,1,1,36.41358,39.03808,28.02902,0,1,54067.00000,0,709.33227,763.19324,0,1,2880,788.00,787.89307,1,12.00271,10,10,10,10,-2.66194,-1.08203,3.58392,6.08648,127.00000,10194.41895,-160.00000,70,14499.94727,20,487.53043,0.00000,60.86517,61.93933,0,308.32959,0.00246,16410.93359,314.10474,297.73898,0,10053.00000,27627.00000,,,,
-454,0.10145,1.27074,406.14667,993.95294,33.4603,0.0,34.95676,35.5811,100,0.29907,100,-1.88294,59.83983,60.58655,162.33101,795.56342,1975.28845,2824.56226,296.82156,1106.10132,9.61556,7.27997,380.03009,84.30317,96.84143,12,11.78894,1.38336,0.27557,540833,540833,0,0,1,1,1,36.29150,40.30465,28.02902,0,1,54110.00000,0,715.73486,763.19324,0,1,2880,784.00,783.82623,1,12.01220,10,10,10,10,-2.84002,-1.07396,3.76789,6.16228,-20.00000,9644.03223,-160.00000,70,14576.97949,20,157.03218,-0.00166,68.7934,0.23508,0,312.01950,-0.00166,16575.99414,315.00568,307.42816,0,10053.00000,27627.00000,,,,
-455,0.10121,1.27943,405.06735,993.95294,32.0,100.0,63.09717,37.05906,100,0.29907,0,-1.87531,59.78814,60.70861,141.18195,775.79291,1962.69983,1560.43860,296.41635,1009.42517,10.12614,0.28381,382.21786,36.40311,46.89941,12,11.78894,1.38031,0.27557,540833,540833,0,0,1,1,1,36.62720,40.44190,28.02558,0,1,54110.00000,0,721.41724,763.19324,0,1,2880,784.00,784.76465,1,12.01601,10,10,10,10,-2.39322,-1.04728,3.83228,6.13399,-7.00000,11016.00000,-160.00000,70,14745.67285,20,227.72760,-0.00166,63.83826,0.84998,0,311.64334,-0.00043,16703.18164,316.17517,308.01202,0,10053.00000,27627.00000,,,,
-456,0.10145,1.28592,405.06735,1001.99799,33.4603,0.0,32.97053,35.67456,100,99.9237,0,-1.88294,59.61872,60.34241,141.94237,738.02484,1954.28406,33.96383,295.50977,1001.31744,9.73584,0.28381,390.14447,96.36513,95.78095,12,12.01019,1.37573,0.58304,540833,540833,0,0,1,1,1,36.76452,38.96009,28.02561,0,1,54090.00000,0,691.11328,763.19324,0,1,2880,787.00,788.24774,1,12.00883,10,10,10,10,-2.64084,-0.61475,4.00684,6.22252,145.11813,11280.00000,-160.00000,70,14725.56641,20,701.94397,-0.00022,4.57175,0.23508,10,317.78180,0.00036,16716.88477,316.79797,309.37338,0,10052.00000,27627.00000,,,,
-457,0.10121,1.29801,406.14667,1115.11975,33.4603,0.06518,33.96383,37.24445,100,99.91608,100,-1.87531,59.52810,60.19484,150.01564,785.73022,6.90462,73.09134,296.02911,994.85779,11.52803,0.28381,355.98859,40.90655,86.93848,12,11.78894,1.36658,0.27557,540833,540833,0,0,1,1,1,36.76452,39.65800,28.02817,0,1,54090.00000,0,705.896,763.19324,0,1,2880,788.00,788.12646,1,12.00826,10,10,10,10,-2.49601,-1.02005,3.88515,6.21688,3302.97485,12326.22168,-160.00000,70,15027.60059,20,971.66614,0.00000,-0.00723,0.05423,0,321.31534,0.00058,16844.48047,317.72723,312.76614,0,10053.00000,27627.00000,,,,
-458,0.10087,1.30343,405.06735,1105.2218,33.6555,0.0,2828.91626,37.63343,100,99.91608,0,-1.88294,59.54671,59.88464,144.37654,629.86169,218.93417,2816.88916,294.69403,1003.4917,11.65939,0.28381,376.38052,76.91363,40.37628,12,12.01782,1.36581,0.27557,540833,540833,0,0,1,1,1,36.70349,38.59557,28.02909,0,1,54123.00000,0,712.27417,763.19324,0,1,2880,785.00,784.34320,1,11.98026,10,10,10,10,-2.47476,-0.69854,4.34756,6.28828,361.75586,11928.00000,-160.00000,70,15111.20996,20,862.19366,-0.00166,71.67969,0.05423,0,318.23151,-0.00058,16953.65625,319.77499,313.90390,0,10053.00000,27627.00000,,,,
-459,0.10121,1.31022,393.16226,1105.2218,31.91024,0.0,2824.56445,36.71791,100,99.91608,0,-1.80664,59.25533,59.75525,117.45092,755.68115,6.33237,32.97053,294.72345,1001.31744,12.05538,0.28381,370.91324,40.97655,42.28363,12,12.01782,1.36505,0.27557,540833,540833,0,0,1,1,1,36.76452,38.67418,28.03338,0,1,54093.00000,0,719.75098,763.19324,0,1,2880,788.00,788.65063,1,11.96534,10,10,10,10,-2.87163,-0.80500,4.36333,6.43782,2693.18945,12806.14551,-160.00000,70,15141.97852,20,1672.73254,0.00000,9.60648,16.96326,0,324.32230,0.00152,16999.62891,320.65054,314.61591,0,10052.00000,27627.00000,,,,
-460,0.10087,1.31994,397.63785,993.95294,32.0,100.0,32.97053,37.21355,100,0.29907,100,-1.87531,58.61613,59.86939,150.67682,447.60391,62.25774,284.46780,295.26627,991.37872,12.58243,7.26432,368.56033,93.42918,43.1076,12,11.78131,1.36429,0.27557,540833,540833,0,0,1,1,1,36.62720,38.43707,28.02649,0,1,54096.00000,0,728.88794,763.19324,0,1,2880,788.00,789.23035,1,12.00586,10,10,10,10,-2.25699,-0.74802,3.96900,6.26559,4845.45850,12606.39941,-160.00000,70,15198.69434,20,3424.77075,0.00000,70.46442,8.40927,0,331.29083,0.00043,17122.72266,321.18524,317.44907,0,10052.00000,27627.00000,,,,
-461,0.10087,1.32557,405.06735,1001.99799,33.4603,100.0,32.97053,37.22793,100,99.91608,100,-1.87531,57.15572,57.52716,151.84070,573.93292,1964.48572,2825.02246,292.62543,1117.58203,11.82637,7.64618,384.01743,46.16092,43.58063,12,12.01782,1.36429,0.27557,540833,540833,0,0,1,1,1,36.52039,38.00048,28.03162,0,1,54128.00000,0,708.55713,763.19324,0,1,2880,786.00,785.33112,1,11.95991,10,10,10,10,-2.78316,-0.69166,4.77055,6.58221,3254.70239,12840.00000,-160.00000,70,15357.98926,20,1324.86316,-0.00022,72.16434,74.01984,0,324.03647,-0.00123,17087.71680,322.10898,318.24112,0,10052.00000,27627.00000,,,,
-462,0.10121,1.33076,406.14667,993.95294,33.4603,0.25618,994.79535,37.16587,100,99.91608,100,-1.77612,57.21626,57.41264,153.11487,791.89984,5.56941,659.92230,293.18387,992.68347,12.33214,0.28381,381.70123,98.12235,42.87109,12,11.78131,1.36429,0.27557,540833,540833,0,0,1,1,1,36.41358,37.93946,28.01865,0,1,54098.00000,0,718.2373,763.19324,0,1,2880,789.00,788.74414,1,11.95752,10,10,10,10,-2.62735,-0.63620,4.55945,6.59892,5214.67822,12840.00000,-224.00000,70,15572.02344,20,3641.37866,0.00000,74.11026,0.65106,0,329.01105,0.00152,17213.01172,322.82654,319.75168,0,10052.00000,27627.00000,,,,
-463,0.10121,1.33826,406.14667,1001.99799,33.4603,0.0,32.97053,36.55819,100,0.29907,0,97.19238,56.71039,57.29640,157.24071,675.12372,1976.24182,2825.98877,293.19763,1000.0127,12.20671,7.64618,392.32568,89.38294,42.64221,12,11.78131,1.36353,0.27557,540833,540833,0,0,1,1,1,36.61194,37.84790,28.02649,0,1,54130.00000,0,705.59692,763.19324,0,1,2880,786.00,786.02875,1,11.94985,10,10,10,10,-2.68557,-0.41107,4.89556,6.76685,3211.01001,13608.74414,-288.00000,70,15487.62793,20,1573.95898,-0.00166,71.26736,0.07236,0,331.04416,-0.00166,17290.64062,325.34653,320.35358,0,10052.00000,27627.00000,,,,
-464,0.10121,1.34018,397.63785,1105.2218,31.91024,100.0,31.97761,37.19513,0,99.91608,0,-1.88294,56.59281,57.16764,148.13579,597.47327,1960.79236,2832.84692,292.75131,995.7276,12.75793,7.64618,392.57443,37.51231,99.22936,12,11.78894,1.36276,0.27557,540833,540833,0,0,1,1,1,36.23047,37.81738,28.03081,0,1,54118.00000,0,715.96069,763.19324,0,1,2880,788.00,787.95117,1,11.95280,10,10,10,10,-2.60928,-0.28901,4.78726,6.73969,5224.55713,13752.00000,-288.00000,70,15757.00195,20,3325.04224,0.00000,0.13745,11.8996,0,336.36310,-0.00152,17380.41602,325.88907,322.69684,0,10052.00000,27627.00000,,,,
-465,0.10087,1.34550,393.16226,1001.99799,33.4603,100.0,33.96383,35.77946,100,99.91608,100,-1.87531,55.89557,57.03888,157.77061,815.68915,414.26855,156.11421,292.24396,1003.92651,13.02544,7.64618,394.37668,53.32171,47.50214,12,11.78131,1.36245,0.20233,540833,540833,0,0,1,1,1,36.21521,36.90185,28.03166,0,1,54098.00000,0,706.21338,763.19324,0,1,2880,792.00,793.09521,1,11.93584,10,10,10,10,-3.34009,-0.76650,4.55523,6.84194,5042.18506,13752.00000,-288.00000,70,15676.23438,20,3528.06787,-0.00022,-0.00723,75.97296,0,340.67529,0.00094,17345.03711,326.46658,321.49854,0,10052.00000,27627.00000,,,,
-466,0.10087,1.35005,405.06735,993.95294,31.91024,100.0,2821.19531,35.31826,100,99.91608,100,97.19238,56.27429,56.81006,163.87448,808.97711,16.61694,2797.60278,289.90082,1104.82556,13.17668,9.42383,396.98441,46.71919,33.02154,12,11.78131,1.36200,0.20233,540833,540833,0,0,1,1,1,36.04736,36.09313,28.02997,0,1,54122.00000,0,726.75781,763.19324,0,1,2880,788.00,788.33667,1,11.89688,10,10,10,10,-3.42527,-0.78456,5.02315,6.98131,4728.96436,13752.00000,-288.00000,70,15939.94141,20,3269.73779,-0.00166,72.69965,0.07236,0,344.08234,0.00015,17415.80859,328.39923,322.79886,0,10052.00000,27627.00000,,,,
-467,0.03051,1.35376,397.63785,1119.68103,31.91024,100.0,31.97761,35.00203,0,99.91608,0,97.20763,55.67991,55.35463,157.01093,811.77698,1964.98853,1975.18738,290.88458,1119.81433,13.25694,8.46980,396.72882,100.0,99.35281,12,11.78131,1.36124,0.27557,540833,540833,0,0,1,1,1,36.01685,36.06262,28.02909,0,1,54121.00000,0,702.14844,763.19324,0,1,2880,789.00,789.88000,1,11.93343,10,10,10,10,-3.04333,-0.46567,4.62307,6.75967,3961.56250,13752.00000,-288.00000,70,15999.39062,20,3377.56396,-0.00166,81.60446,42.84216,0,342.85513,-0.00036,17467.73438,330.53427,323.61215,0,10052.00000,27627.00000,,,,
-468,0.10087,1.35592,406.14667,1105.2218,33.4603,100.0,44.85251,35.71957,100,0.29907,100,42.23022,53.66299,56.27304,166.68370,830.19562,6.52314,33.96383,278.97452,994.42285,13.46879,9.65138,396.93329,41.1809,47.50214,12,11.78131,1.36124,0.20233,540833,540833,0,0,1,1,1,35.84900,35.98632,28.03253,0,1,54090.00000,0,701.92261,763.19324,0,1,2880,794.43,795.81055,1,11.88800,10,10,10,10,-3.45386,-0.56211,4.70787,6.85732,5071.85791,13752.00000,-288.00000,70,16151.99512,20,3619.78931,-0.00022,-0.00723,33.74567,0,346.74603,0.00224,17495.94727,330.75766,324.54031,0,10051.00000,27627.00000,,,,
-469,0.10087,1.36035,393.16226,1001.99799,33.4603,99.86278,955.54102,37.31224,100,99.91608,0,-1.87531,53.25481,53.91152,168.66653,824.38654,6.88778,454.25797,278.09647,1006.53571,13.76933,9.19105,398.01880,45.60936,51.08032,12,12.00256,1.36124,0.20233,540833,540833,0,0,1,1,1,35.63538,35.94055,28.0247,0,1,54107.00000,0,714.54468,763.19324,0,1,2880,792.00,791.55859,1,11.87683,10,10,10,10,-3.57508,-0.73564,4.66862,6.83268,5085.51807,13688.00000,-288.00000,70,16199.38770,20,3477.92578,-0.00022,-0.00723,0.05423,0,349.59998,0.00094,17556.88867,330.17224,325.58920,0,10052.00000,27627.00000,,,,
-470,0.10145,1.36472,405.06735,993.95294,33.4603,100.0,557.22565,37.20516,100,99.91608,0,-1.8219,53.32376,53.27759,170.17361,826.12610,1970.13855,2827.93359,262.25296,992.68347,13.64949,11.31737,401.17599,86.65707,46.55609,12,11.78894,1.35971,0.20233,540833,540833,0,0,1,1,1,35.45227,35.91003,28.0247,0,1,54138.00000,0,715.04517,763.19324,0,1,2880,788.00,787.46667,1,11.89934,10,10,10,10,-3.33410,-0.50254,4.61199,6.70263,2670.24219,13530.55469,-288.00000,70,16474.51758,20,1609.42627,-0.01237,-0.00723,0.34363,0,345.60605,-0.00101,17565.06836,331.24863,326.80688,0,10052.00000,27627.00000,,,,
-471,0.10145,1.36693,406.14667,1105.2218,31.91024,100.0,30.98430,37.873,100,0.29907,0,-1.87531,52.73498,53.27759,171.89023,838.73749,1963.84424,904.58392,264.17151,999.14294,13.94920,11.68213,403.42511,42.35717,57.33643,12,11.78894,1.35971,0.20233,540833,540833,0,0,1,1,1,35.49804,35.89477,28.0247,0,1,54113.00000,0,691.85181,763.19324,0,1,2880,790.00,791.11890,1,11.87000,10,10,10,10,-3.42927,-0.62568,4.58421,6.71084,4361.54639,13624.04492,-288.00000,70,16447.89258,20,1898.73572,-0.00166,-0.00723,60.52881,0,349.00635,0.00029,17626.79102,332.78339,326.72925,0,10051.00000,27605.00000,,,,
-472,0.10087,1.36838,397.63785,1001.99799,32.0,100.0,31.97761,37.16919,100,99.91608,0,-1.87531,52.11077,52.80456,173.79756,835.69336,990.38220,199.23270,256.36896,1115.93726,14.03096,11.20903,403.98740,49.02426,50.2182,12,12.01782,1.35971,0.20233,540833,540833,0,0,1,1,1,35.45227,35.77270,28.02736,0,1,54104.00000,0,702.19727,763.19324,0,1,2880,794.00,793.20636,1,11.86059,10,10,10,10,-3.85520,-0.85113,4.36950,6.67477,4990.71191,13647.54883,-288.00000,70,16509.97266,20,3434.68164,-0.00022,65.08969,0.07236,0,352.65695,0.00080,17643.73633,332.16379,327.49893,0,10051.00000,27605.00000,,,,
-473,0.10121,1.37354,405.06735,1105.2218,33.4603,100.0,2627.30908,37.29748,100,99.91608,0,-1.87531,52.22978,52.45361,177.39401,828.16821,1973.76245,2832.02319,254.53662,1114.66162,13.98420,12.26959,405.21423,100.0,96.61254,12,11.78894,1.35895,0.20233,540833,540833,0,0,1,1,1,35.37598,35.73898,28.02561,0,1,54150.23438,0,712.76245,763.19324,0,1,2880,787.00,786.76782,1,11.88514,10,10,10,10,-3.44755,-0.64658,4.75636,6.67730,3137.67285,12840.00000,-288.00000,70,16789.67969,20,1366.51685,-0.01237,64.56888,68.66681,0,348.67166,-0.00159,17709.20312,335.39822,329.35089,0,10052.00000,27605.00000,,,,
-474,0.10145,1.37547,445.34219,1105.2218,31.91024,100.0,30.98430,35.67913,100,0.29907,100,97.20763,51.88981,52.70062,200.69124,850.96802,1961.99768,2049.14307,253.46783,1011.65741,14.34791,12.74261,405.11197,41.70584,65.24048,12,12.01019,1.35818,0.20233,540833,540833,0,0,1,1,1,35.49804,35.66589,28.02821,0,1,54114.00000,0,713.21411,763.19324,0,1,2880,790.00,790.66992,1,11.85661,10,10,10,10,-3.97230,-1.00242,4.53388,6.50636,4625.57520,13501.14941,-288.00000,70,16588.18555,20,3439.00977,-0.00166,65.48032,65.84558,0,358.39417,0.00007,17735.79102,333.89728,328.95404,50,10027.00000,27605.00000,,,,
-475,0.10087,1.37652,405.06735,1001.99799,33.4603,0.0,153.62488,37.42336,100,0.29907,100,-1.88294,51.96041,52.68250,204.69666,900.63434,5.95089,35.95007,252.99954,990.94391,14.05632,11.68213,404.75415,100.0,48.38714,12,11.78131,1.35755,0.20233,540833,540833,0,0,1,1,1,35.45227,35.63538,28.02817,0,1,54092.00000,0,704.94995,763.19324,0,1,2880,795.00,794.24939,1,11.84128,10,10,10,10,-3.53474,-0.74368,4.47167,6.51837,5243.83301,13481.02441,-288.00000,70,16836.46289,20,3570.87158,0.00000,5.48322,6.5285,0,357.90494,0.00239,17786.04297,335.75565,330.25967,0,10027.00000,27627.00000,,,,
-476,0.10121,1.38230,405.06735,1105.2218,32.0,100.0,584.43652,35.57805,100,0.29907,0,97.2229,51.63876,52.10266,186.34619,848.30481,1966.32385,2819.51050,252.56894,995.2926,14.51270,12.75024,405.82761,42.56847,41.68091,12,12.01782,1.35666,0.20233,540833,540833,0,0,1,1,1,35.37598,35.55908,28.02909,0,1,54124.00000,0,719.87915,763.19324,0,1,2880,789.00,789.11707,1,11.85535,10,10,10,10,-3.78094,-0.87861,4.61352,6.61022,3639.36328,12769.79102,-288.00000,70,16803.00781,20,1703.81348,-0.00166,-0.00723,2.56799,0,362.50964,-0.00015,17836.02539,338.76367,330.13800,0,10051.00000,27605.00000,,,,
-477,0.10121,1.38308,405.06735,993.95294,33.4603,100.0,2827.18481,37.78004,100,99.91608,100,55.94024,51.73907,52.09838,202.21709,870.96045,27.96321,2824.33887,249.71268,1000.0127,14.61368,12.75024,406.13434,44.03289,43.11523,12,12.01782,1.35666,0.20233,540833,540833,0,0,1,1,1,35.37598,35.49804,28.02473,0,1,54114.00000,0,721.91162,763.19324,0,1,2880,790.00,790.38806,1,11.83345,10,10,10,10,-3.84068,-0.90314,4.66511,6.41477,5155.20361,12473.25684,-288.00000,70,17131.41211,20,3351.02051,-0.00166,72.67072,64.54352,0,375.91251,0.00087,17890.75977,341.72897,331.06879,0,10051.00000,27605.00000,,,,
-478,0.10145,1.38673,405.06735,1115.11975,33.4603,100.0,2828.49487,35.74333,0,0.29144,0,-1.88294,51.71357,52.01453,201.64908,881.40778,5.76019,2820.81226,248.94714,1007.18796,14.44573,12.73732,405.87875,91.77696,99.60735,12,11.78131,1.35590,0.20233,540833,540833,0,0,1,1,1,35.43700,35.48279,28.02301,0,1,54112.00000,0,709.5398,763.19324,0,1,2880,789.00,789.69739,1,11.83020,10,10,10,10,-3.71272,-0.99410,4.67653,6.55030,5236.60303,12432.10156,-288.00000,70,17106.49609,20,3554.98804,0.00000,67.08621,65.42969,0,360.53271,0.00145,18004.98828,340.45239,331.77969,0,10052.00000,27605.00000,,,,
-479,0.10087,1.38978,405.06735,993.95294,32.0,99.92393,2836.62207,37.05105,100,99.91608,0,-1.82953,51.60491,51.98059,191.80423,903.96881,6.33237,2721.87427,247.61200,1105.4635,14.39601,12.39929,406.79218,81.29551,38.59863,12,11.78131,1.35513,0.17029,540833,540833,0,0,1,1,1,35.45227,35.34546,28.02821,0,1,54122.00000,0,698.11401,763.19324,0,1,2880,788.00,788.29828,1,11.82477,10,10,10,10,-3.78620,-0.92354,4.54018,6.55538,4428.06250,11280.00000,-288.00000,70,17285.41797,20,3184.40649,-0.00166,12.98465,56.24274,0,356.19363,0.00109,17927.17188,342.56760,332.60706,0,10051.00000,27605.00000,,,,
-480,0.10145,1.39297,397.63785,1001.99799,33.4603,100.0,510.05801,37.29481,100,99.91608,100,-1.88294,51.45098,51.98822,204.17305,904.40363,1971.85510,2829.89893,247.99348,992.24847,14.31103,13.69629,407.15668,92.68734,35.50873,12,12.01782,1.35437,0.17029,540833,540833,0,0,1,1,1,35.28442,35.36146,28.03078,0,1,54136.00000,0,698.05908,763.19324,0,1,2880,787.00,787.28540,1,11.83456,10,10,10,10,-3.85848,-1.08904,4.71548,6.42504,2895.04150,11201.28320,-288.00000,70,17421.51758,20,878.92816,-0.00166,69.27808,5.80515,0,373.10632,-0.00065,17955.39648,343.07993,333.80658,0,10027.00000,27605.00000,,,,
-481,0.10087,1.39183,406.14667,1001.99799,33.4603,100.0,1976.72900,37.00642,100,0.29907,0,97.18475,51.39320,51.98059,181.98232,907.01294,137.45599,273.01303,248.37488,1116.2561,14.60635,12.75024,407.31430,39.64251,88.35754,12,11.78894,1.35284,0.20233,540833,540833,0,0,1,1,1,35.37598,35.31494,28.02818,0,1,54101.00000,0,716.1438,763.19324,0,1,2880,793.00,792.59479,1,11.83237,10,10,10,10,-3.85250,-1.08071,4.57166,6.53761,2862.68994,11280.00000,-288.00000,70,17871.63672,20,1802.15796,-0.00166,0.0434,37.34448,0,375.34363,0.00181,17998.05859,347.16348,333.67841,0,10027.00000,27605.00000,,,,
-482,0.10087,1.39657,406.14667,1105.2218,33.6555,100.0,2824.79053,37.36679,100,0.29907,100,-1.86005,51.34166,51.98059,203.55222,907.88269,127.10539,31.97760,247.84642,990.07416,14.47527,12.75024,407.20779,40.45829,36.34796,12,11.78894,1.35208,0.17029,540833,540833,0,0,1,1,1,35.45227,35.31494,28.03514,0,1,54097.00000,0,709.52148,763.19324,0,1,2880,794.00,793.78668,1,11.82513,10,10,10,10,-3.76010,-0.96653,4.40303,6.45747,2734.06177,10112.44434,-288.00000,70,17545.30078,20,2703.12695,-0.00166,0.13745,62.01172,0,371.55908,0.00282,18117.62305,349.38492,334.50699,0,10027.00000,27627.00000,,,,
-483,0.10145,1.40090,406.14667,993.95294,31.91024,100.0,2832.04126,37.46685,100,99.91608,0,-1.88294,51.19555,51.98059,202.96974,903.09906,757.32562,2233.66479,246.24915,1001.31744,14.56612,13.93280,407.97452,36.72389,45.35065,12,11.78894,1.34979,0.20233,540833,540833,0,0,1,1,1,35.54382,35.16236,28.03088,0,1,54117.00000,0,707.89185,763.19324,0,1,2880,788.00,787.75732,1,11.84490,10,10,10,10,-3.50403,-1.12544,4.28226,6.49917,3847.38672,9599.56543,-288.00000,70,17767.07617,20,725.49902,-0.00166,66.64496,65.84558,0,374.85797,0.00015,17931.89844,344.41757,332.19189,0,10051.00000,27605.00000,,,,
-484,0.10145,1.40297,397.63785,1105.2218,32.0,100.0,2832.28540,35.69973,100,99.91608,0,97.20001,51.26234,50.79803,206.79475,890.78900,6.71385,2397.59473,246.06595,1104.50671,14.63814,13.45978,407.71896,42.67275,99.80808,12,11.78131,1.34979,0.17029,540833,540833,0,0,1,1,1,35.68115,35.16236,28.0325,0,1,54109.00000,0,715.69824,763.19324,0,1,2880,790.00,788.96716,1,11.83868,10,10,10,10,-3.62053,-1.19013,4.14643,6.41022,4761.44141,10661.38672,-288.00000,70,17790.82031,20,1635.30786,0.00000,-0.00723,0.07236,0,385.26245,0.00087,18093.28711,343.62686,335.84894,0,10027.00000,27605.00000,,,,
-485,0.10121,1.40474,406.14667,993.95294,33.4603,0.22592,155.12090,37.13421,0,0.29907,0,97.2229,51.11829,51.97296,200.12967,854.83130,112.33214,1773.25854,247.03975,999.20648,14.48269,13.69629,407.66782,44.11005,84.80987,12,12.01782,1.34903,0.20233,540833,540833,0,0,1,1,1,35.69641,35.31476,28.02561,0,1,54096.00000,0,711.78589,763.19324,0,1,2880,793.00,791.20007,1,11.84962,10,10,10,10,-3.61385,-1.11713,4.24435,6.35307,4808.30420,10328.00000,-288.00000,70,17611.92578,20,1946.16235,0.00000,-0.00723,61.34259,0,385.92786,0.00174,18205.93555,346.81641,335.08752,0,10027.00000,27605.00000,,,,
-486,0.10121,1.40399,397.63785,1001.99799,33.4603,0.0,32.97053,35.71652,0,0.29144,100,-1.84479,50.91856,50.79803,204.80064,903.53406,5.56941,2822.87988,243.03433,987.46484,14.12597,11.68213,407.46228,39.22803,90.46326,12,11.78894,1.34750,0.20233,540833,540833,0,0,1,1,1,35.58960,35.16236,28.03162,0,1,54076.00000,0,704.8523,763.19324,0,1,2880,828.00,793.52771,1,11.83278,10,10,10,10,-3.78445,-1.17977,4.22023,6.48089,5268.68848,10835.63770,-288.00000,70,18121.18945,20,3563.89233,0.00239,-0.00723,17.03558,0,374.56192,0.00297,18241.87695,337.79648,339.73108,0,10027.00000,27627.00000,,,,
-487,0.10087,1.40808,405.06735,1001.99799,31.91024,100.0,2826.95093,37.08412,0,0.29907,0,-1.88294,51.05222,50.79803,202.43362,894.83649,577.18091,2830.34790,243.41580,1000.88245,14.26678,13.45978,409.86584,44.55353,50.34027,12,11.78131,1.34598,0.20233,540833,540833,0,0,1,1,1,35.69641,35.13183,28.02392,0,1,54122.00000,0,698.73657,763.19324,0,1,2880,788.00,787.54224,1,11.84916,10,10,10,10,-3.44126,-0.90858,4.55355,6.43568,3780.42114,8831.65430,-288.00000,70,18218.77344,20,943.46198,-0.00022,-0.00723,0.05423,0,376.85791,0.00007,18182.45508,349.22769,339.26834,0,10027.00000,27605.00000,,,,
-488,0.10087,1.41173,406.14667,993.95294,31.91024,1.79257,2780.47339,37.38636,100,99.91608,0,-1.88294,50.99080,50.79803,206.03180,913.53613,1962.89050,2822.03760,244.94173,1008.27521,14.22839,13.69629,411.19492,43.13094,47.37244,12,11.78131,1.34522,0.20233,540833,540833,0,0,1,1,1,35.63538,35.19287,28.02817,0,1,54115.00000,0,713.45215,763.19324,0,1,2880,788.00,788.03210,1,11.85422,10,10,10,10,-3.79354,-1.12120,4.27135,6.41219,164.79192,7207.06152,-288.00000,70,18146.07812,20,498.72940,-0.01237,1.43953,0.05423,0,387.10135,0.00043,18283.73438,348.09720,340.03311,0,10027.00000,27605.00000,,,,
-489,0.10121,1.42194,406.14667,1105.2218,31.91024,100.0,491.41162,37.12429,100,0.29907,0,28.4668,50.79013,50.79803,179.51965,902.66425,1973.19031,1621.08716,245.32314,994.42285,14.41467,13.45978,412.19006,92.34055,89.18915,12,12.01782,1.34445,0.20233,540833,540833,0,0,1,1,1,35.91051,35.05553,28.03342,0,1,54100.00000,0,723.06519,763.19324,0,1,2880,789.00,791.05817,1,11.89029,10,10,10,10,-3.27805,-0.96926,4.16032,6.36593,1912.26294,7716.45605,-288.00000,70,17685.75195,20,788.25165,-0.00166,75.897,12.06238,0,379.10654,0.00080,18266.84180,348.63306,339.12152,0,10026.00000,27590.00000,,,,
-490,0.10145,1.41672,397.63785,1001.99799,33.6555,94.21285,2831.58350,35.76393,0,0.29907,0,-1.87531,50.83776,50.79803,189.56039,916.69727,6.71385,730.13770,245.13243,1002.62195,13.92898,12.74261,410.42816,100.0,47.50214,12,11.78131,1.34369,0.20233,540833,540833,0,0,1,1,1,35.78796,35.11657,28.03169,0,1,54084.00000,0,715.73486,763.19324,0,1,2880,792.00,795.33661,1,11.85030,10,10,10,10,-3.88308,-1.00793,4.40861,6.68533,3403.72900,6826.68701,-288.00000,70,18023.19336,20,3144.77588,0.00000,64.3808,0.09042,10,381.99500,0.00472,18371.77539,355.20480,334.90967,0,10026.00000,27627.00000,,,,
-491,0.10087,1.41735,405.06735,1001.99799,33.6555,0.0,2828.07373,37.86918,100,99.91608,100,-1.88294,50.81621,50.79803,209.08354,913.10120,622.00726,243.97260,244.15152,1001.7522,14.06287,12.28415,410.22275,65.65295,50.10376,12,11.78131,1.34216,0.17029,540833,540833,0,0,1,1,1,36.09313,35.10797,28.02817,0,1,54099.00000,0,701.53809,763.19324,0,1,2880,789.00,789.34833,1,11.87412,10,10,10,10,-3.58406,-1.28740,3.83678,6.39326,2431.62012,7127.83203,-288.00000,70,18295.93359,20,600.60352,-0.00166,53.46498,44.21655,0,388.35489,0.00145,18306.56836,344.04196,340.18414,0,10027.00000,27627.00000,,,,
-492,0.10121,1.42736,405.06735,1001.99799,33.4603,100.0,2818.13281,37.6923,100,0.29907,100,41.09344,49.91856,50.79803,201.64490,913.53522,35.03530,680.20734,244.56024,1002.62195,13.92160,12.75024,413.54907,91.90494,99.55749,12,12.01782,1.34099,0.20233,540833,540833,0,0,1,1,1,36.01685,35.19287,28.02733,0,1,54082.00000,0,711.07788,763.19324,0,1,2880,792.00,792.67828,1,11.84633,10,10,10,10,-3.92344,-1.18441,4.56198,6.68797,2962.61255,8208.00000,-288.00000,70,18941.11133,20,1264.94617,0.00000,-0.00723,4.44876,0,397.19965,0.00326,18414.60352,351.03427,338.28534,50,10026.00000,27627.00000,,,,
-493,0.10087,1.43420,405.06735,1105.2218,31.91024,100.0,2830.60083,37.38281,100,99.91608,0,-1.87531,50.54535,50.79803,202.02638,841.34686,1987.68604,2841.25708,228.91161,1002.18701,13.88611,13.68866,415.07980,39.97454,35.18829,12,12.01782,1.33911,0.20233,540833,540833,0,0,1,1,1,35.97107,35.04028,28.02645,0,1,54143.00000,0,717.89551,763.19324,0,1,2880,785.00,783.91248,1,11.92031,10,10,10,10,-3.65192,-1.30346,4.38129,6.62937,142.24449,3771.98389,-224.00000,70,18685.06445,20,132.34572,-0.01237,-0.00723,1.95312,0,383.73087,-0.00311,18315.35547,353.27658,341.05811,0,10026.00000,27605.00000,,,,
-494,0.10145,1.42682,406.14667,1105.2218,31.91024,0.0,2828.35474,37.01252,100,0.29907,100,97.19238,50.64124,50.79803,197.00278,907.01294,586.32526,391.97147,243.60651,1105.14465,13.85425,13.69629,421.36716,35.59764,99.09973,12,11.78894,1.33835,0.20233,540833,540833,0,0,1,1,1,36.09313,35.29968,28.02649,0,1,54092.00000,0,705.7373,763.19324,0,1,2880,789.00,790.25360,1,11.85923,10,10,10,10,-3.56644,-1.09114,4.58234,6.65956,118.99606,4408.06201,-192.00000,70,18833.95312,20,549.58600,-0.00166,66.13861,23.31091,0,390.57416,0.00268,18569.25391,354.24976,340.77902,0,10026.00000,27627.00000,,,,
-495,0.10145,1.42973,397.63785,993.95294,33.6555,100.0,36.13241,36.71955,100,99.91608,0,-1.87531,49.52472,50.79803,198.38737,902.66425,1029.61023,797.67657,243.60651,988.76959,13.67748,12.75024,428.37021,38.10882,96.45996,12,11.78894,1.33682,0.20233,540833,540833,0,0,1,1,1,36.04736,35.43700,28.03342,0,1,54088.00000,0,709.13696,763.19324,0,1,2880,790.00,791.89313,1,11.89143,10,10,10,10,-3.35639,-1.15162,4.16500,6.64211,2251.73413,6223.90186,-160.00000,70,19001.88672,20,470.87036,0.00000,74.68893,27.43414,10,393.15051,0.00181,18756.53906,352.05182,343.63425,0,10021.16699,27605.00000,,,,
-496,0.10145,1.43878,397.63785,993.95294,32.0,100.0,2815.06787,35.80502,100,99.91608,100,-1.87531,50.48519,50.79803,209.30641,906.57819,1964.14746,2836.49683,242.84363,997.03217,13.54583,13.81394,421.36716,46.70116,43.69507,12,11.78894,1.33453,0.20233,540833,540833,0,0,1,1,1,36.13892,35.28442,28.02824,0,1,54132.00000,0,701.26953,763.19324,0,1,2880,784.00,784.64874,1,11.87591,10,10,10,10,-3.47619,-1.10642,4.79884,6.75299,2459.66016,4916.25342,-160.00000,70,19010.13672,20,148.10014,0.00000,74.94214,70.47528,10,383.45581,-0.00087,18618.61328,350.81180,349.46436,0,10027.00000,27627.00000,,,,
-497,0.10087,1.43700,406.14667,1105.2218,33.4603,100.0,2841.80371,35.93483,100,99.91608,0,-1.88294,50.50119,50.79040,190.57837,911.36163,10.96463,2097.80005,241.39995,1107.05811,13.82409,12.75024,423.87189,42.1413,33.25806,12,12.01782,1.33158,0.20233,540833,540833,0,0,1,1,1,36.09313,35.26917,28.02909,0,1,54101.00000,0,708.78906,763.19324,0,1,2880,788.00,787.83966,1,11.86578,10,10,10,10,-3.61062,-1.03631,4.54353,6.80251,146.63283,4112.00000,-160.00000,70,18966.80273,20,368.33438,-0.00166,62.21066,70.83697,0,392.11642,0.00224,18511.75977,355.78531,341.69156,50,10026.00000,27627.00000,,,,
-498,0.10187,1.44074,406.14667,1105.2218,33.4603,100.0,2832.70654,37.32368,0,0.29907,0,97.18475,50.69007,50.79803,194.70337,914.36908,327.63611,632.09613,242.04590,1001.31744,13.52454,12.75024,431.53491,97.54723,47.37244,12,11.78894,1.32919,0.20233,540833,540833,0,0,1,1,1,36.38305,35.37598,28.02652,0,1,54091.00000,0,704.55933,763.19324,0,1,2880,788.00,788.52094,1,11.88998,10,10,10,10,-3.16866,-1.09995,4.37842,6.59352,110.00000,4334.37598,-160.00000,70,18962.25000,20,165.86649,-0.00166,69.74826,74.25494,0,392.89838,0.00275,18849.64648,352.42789,344.47284,0,10026.00000,27627.00000,,,,
-499,0.10145,1.44013,405.06735,1001.99799,33.6555,0.2686,1707.55029,36.62292,100,0.29907,0,-1.88294,47.08905,50.08850,175.32347,903.96881,184.08012,478.16376,243.19113,1106.42029,13.44364,12.75024,426.78555,44.2195,43.78662,12,11.78894,1.32309,0.27557,540833,540833,0,0,1,1,1,36.35254,35.40649,28.02385,0,1,54070.00000,0,711.67602,763.19324,0,1,2880,792.00,791.80603,1,11.87371,10,10,10,10,-3.64399,-0.96295,4.63254,6.96450,195.60846,5583.20605,-160.00000,70,19015.64062,20,209.37546,0.00000,-0.00723,46.98346,0,403.80554,0.00362,18697.16016,360.09213,342.01968,0,9999.00000,27627.00000,,,,
-500,0.03051,1.44207,393.16226,1105.2218,31.91024,0.0,25.02598,37.42222,0,0.29144,100,-1.87531,50.53160,47.13592,199.59561,833.35083,5.56941,2843.71631,196.88205,987.89978,13.53101,10.85052,409.31479,41.29073,43.52722,12,11.78894,1.31634,0.27557,540833,540833,0,0,1,1,1,36.41358,35.34546,28.03166,0,1,54051.68359,0,722.52197,763.19324,0,1,2880,793.00,790.61200,1,11.93395,10,10,10,10,-2.69513,-1.25697,3.85087,6.41808,5310.51807,5939.78467,-160.00000,70,19730.00000,20,3463.27173,0.03552,0.79571,76.53357,0,378.02057,0.00043,19048.61719,338.96768,360.56949,0,10026.00000,27605.00000,,,,
-501,0.10087,1.45006,405.06735,993.95294,31.91024,100.0,2830.74121,37.03579,100,99.91608,0,-1.87531,50.46510,50.43945,175.70888,843.05878,1987.68604,2842.53296,244.36948,993.55328,13.47611,13.45978,432.15286,73.97289,40.49835,12,11.78894,1.31302,0.27557,540833,540833,0,0,1,1,1,36.41358,35.46753,28.03166,0,1,54132.00000,0,722.68677,763.19324,0,1,2880,785.00,783.54712,1,11.91969,10,10,10,10,-3.05850,-0.72285,4.75136,6.85146,113.00000,2908.26636,-160.00000,70,19089.33398,20,-17.00000,-0.00166,7.11081,67.29242,0,404.68884,-0.00318,18745.86719,362.26242,344.95215,0,10026.00000,27605.00000,,,,
-502,0.10087,1.44833,397.63785,1001.99799,33.6555,100.0,2840.28711,36.92135,100,99.91608,0,-1.87531,49.45891,47.36481,206.60397,910.49207,6.52314,2832.55127,243.22511,994.85779,13.63424,12.75024,422.95178,98.27548,42.03949,12,11.78131,1.31081,0.20233,540833,540833,0,0,1,1,1,36.52039,35.48279,28.03078,0,1,54110.00000,0,715.89355,763.19324,0,1,2880,785.00,785.26343,1,11.89524,10,10,10,10,-2.71716,-1.01343,3.97646,6.54788,1103.58044,2608.05542,-160.00000,70,18946.55078,20,611.24500,0.00000,5.64236,77.7995,0,396.73700,0.00130,18735.30273,359.41412,344.12985,0,10027.00000,27627.00000,,,,
-503,0.10187,1.46066,445.34219,1105.2218,31.91024,100.0,1388.54370,35.3199,100,99.91608,0,0.45166,49.56972,50.31659,180.30959,857.60968,1987.68604,2841.49951,244.41153,1104.50671,13.60195,13.69629,437.41788,89.48898,43.93921,12,12.01782,1.30293,0.27557,540833,540833,0,0,1,1,1,36.62720,35.57434,28.03172,0,1,54122.00000,0,691.99219,763.19324,0,1,2880,786.00,785.41852,1,11.94307,10,10,10,10,-3.23896,-0.66449,4.52115,6.81077,-7.00000,1803.96399,-160.00000,70,19036.28125,20,-17.00000,-0.00166,69.35764,0.05423,0,406.23285,-0.00275,18960.30664,362.54419,350.36197,0,10026.00000,27605.00000,,,,
-504,0.10145,1.46120,405.06735,1001.99799,33.4603,100.0,2837.05542,35.53696,100,99.91608,0,25.44555,49.11093,50.08850,182.55630,879.70660,1969.56628,2837.65820,203.75343,992.24847,13.39348,13.45978,439.30923,42.49354,35.98938,12,12.01782,1.29674,0.27557,540833,540833,0,0,1,1,1,36.50513,35.55908,28.0247,0,1,54129.00000,0,700.65918,763.19324,0,1,2880,783.00,782.04962,1,11.91805,10,10,10,10,-3.02160,-0.94146,4.67262,6.89772,-7.00000,2148.33887,-160.00000,70,19262.71484,20,-17.00000,-0.00166,69.26361,0.07236,0,405.42368,-0.00101,18726.19531,361.50385,352.63773,0,10027.00000,27627.00000,,,,
-505,0.03051,1.46391,405.06735,1001.99799,33.4603,100.0,2840.84863,37.41714,100,99.91608,0,-1.88294,49.77940,47.48863,177.16385,898.35626,1960.60181,2839.16406,198.96896,1106.42029,13.37745,12.75024,438.59360,87.99202,46.42639,12,11.78894,1.28875,0.27557,540833,540833,0,0,1,1,1,36.70349,35.58960,28.03334,0,1,54130.00000,0,698.46191,763.19324,0,1,2880,781.00,781.00623,1,11.90249,10,10,10,10,-2.89038,-0.97918,4.74694,6.93178,104.00000,2775.99292,-160.00000,70,19342.69336,20,-17.00000,-0.00166,61.17621,65.8999,0,405.87366,-0.00065,18842.65625,361.07303,352.09955,0,10027.00000,27605.00000,,,,
-506,0.10121,1.46644,397.63785,993.95294,32.0,100.0,2829.47778,37.225,100,0.29907,100,-1.89057,49.17526,50.79803,194.06137,846.13031,1983.55066,2842.08057,241.01503,998.70819,13.31039,13.45978,444.96469,97.97386,99.58497,12,11.78894,1.27858,0.20233,540833,540833,0,0,1,1,1,36.70349,35.68115,28.02736,0,1,54126.00000,0,716.13159,763.19324,0,1,2880,783.00,782.01544,1,11.92129,10,10,10,10,-3.02422,-0.51829,4.83873,7.04710,-7.00000,1335.56226,-160.00000,70,19321.08594,20,-17.00000,-0.00166,-0.00723,42.44427,0,413.26462,-0.00297,19009.14844,364.88480,352.83072,0,10026.00000,27605.00000,,,,
-507,0.10145,1.47098,397.63785,993.95294,31.91024,24.67191,2825.26636,36.01341,100,99.91608,100,-1.87531,46.77658,50.79803,207.17616,901.35950,1950.26270,2831.16211,240.41327,1107.37695,13.15414,12.75024,447.09833,96.50074,39.30817,12,11.78894,1.26893,0.20233,540833,540833,0,0,1,1,1,36.76452,35.74219,28.03081,0,1,54104.00000,0,711.8042,763.19324,0,1,2880,786.00,785.87476,1,11.91591,10,10,10,10,-3.16581,-0.89982,4.70406,6.90268,-7.00000,1999.49072,-160.00000,70,19020.38086,20,-17.00000,0.00000,0.06511,69.19128,0,417.48456,0.00029,19089.43750,362.80414,351.90787,0,10026.00000,27627.00000,,,,
-508,0.10145,1.47858,406.14667,1105.2218,31.91024,100.0,2825.19434,36.76747,100,99.91608,100,97.19238,47.84997,50.79040,206.98546,887.86206,1976.05127,2836.07568,237.56024,1000.44769,13.12933,12.75024,437.41788,48.74167,41.68853,12,11.78131,1.25510,0.20233,540833,540833,0,0,1,1,1,36.81030,35.74219,28.03342,0,1,54117.00000,0,715.22217,763.19324,0,1,2880,785.00,784.21588,1,11.94695,10,10,10,10,-3.04091,-0.89064,4.48759,6.79488,-20.00000,2329.44482,-160.00000,70,19143.11914,20,-17.00000,-0.00166,51.46121,70.11359,0,412.87354,-0.00116,18995.91016,369.99020,355.99219,0,10025.00000,27627.00000,,,,
-509,0.10121,1.47955,397.63785,1001.99799,31.91024,0.0,2840.00635,35.78213,100,0.29907,100,-1.88294,48.60905,48.19800,205.84102,899.18518,7.53671,2832.20190,205.73061,1004.14389,13.38517,12.75024,446.26611,100.0,66.45355,12,11.78894,1.24266,0.20233,540833,540833,0,0,1,1,1,36.81030,35.69641,28.02733,0,1,54109.00000,0,708.44727,763.19324,0,1,2880,785.00,784.47992,1,11.91636,10,10,10,10,-3.21043,-0.81560,4.78076,7.01012,-7.00000,1856.74890,-160.00000,70,19031.09961,20,-17.00000,-0.00022,-0.00723,66.87646,0,415.81073,0.00065,19126.75000,369.13174,356.51578,0,10026.00000,27627.00000,,,,
-510,0.10121,1.48668,405.06735,1001.99799,33.6555,100.0,31.97761,37.88864,0,0.29907,0,97.20763,46.68201,48.26799,179.72037,847.59906,1967.47546,2832.28540,243.79729,1015.16534,13.04062,12.39166,459.44928,91.22799,47.02148,12,11.77368,1.21693,0.27557,540833,540833,0,0,1,1,1,36.74926,35.85316,28.02993,0,1,54086.00000,0,695.64819,763.19324,0,1,2880,788.00,788.36707,1,11.98071,10,10,10,10,-2.72397,-0.53354,4.25155,6.78446,96.00000,3824.99146,-160.00000,70,18994.67578,20,-17.00000,0.00000,-0.00723,66.49664,0,422.86743,0.00043,19453.43555,378.97018,358.29782,0,9998.70508,27627.00000,,,,
-511,0.10087,1.49263,405.06735,1001.99799,33.6555,100.0,2834.81226,37.44079,0,99.91608,0,97.20001,47.73328,48.08197,173.38962,840.04474,1980.05676,2840.86548,245.70461,991.37872,12.97369,12.39166,448.04605,91.51218,89.29596,12,11.78894,1.12271,0.27557,540833,540833,0,0,1,1,1,36.84082,35.80322,28.02213,0,1,54126.00000,0,716.20483,763.19324,0,1,2880,783.00,781.32825,1,11.94869,10,10,10,10,-2.46709,0.24450,4.74234,6.92613,-7.00000,2382.23853,-160.00000,70,19370.58203,20,-18.00000,-0.00166,-0.00723,58.57568,0,421.51950,-0.00263,19384.60742,384.06525,357.76575,0,10026.00000,27627.00000,,,,

example/results/ks_diagnosis.csv

@@ -1 +0,0 @@
-feature,ks,boundary_frac,mean_shift,std_ratio,diagnosis,gen_frac_at_min,gen_frac_at_max

example/results/ks_per_feature.csv

@@ -1,54 +0,0 @@
-feature,ks,gen_frac_at_min,gen_frac_at_max,real_n,gen_n,real_min,real_max
-P2_MSD,1.0,1.0,1.0,600000,512,763.19324,763.19324
-P1_B4002,0.9767216666666667,1.0,0.0,600000,512,31.41343,33.6555
-P1_PCV02Z,0.48302187500000004,0.16015625,0.001953125,600000,512,11.76605,12.04071
-P1_FCV02Z,0.4813204166666667,0.134765625,0.0,600000,512,-1.89819,97.38312
-P4_HT_PO,0.47718104166666664,0.568359375,0.0,600000,512,0.05423,85.17798
-P1_B4005,0.47412333333333334,0.59375,0.40625,600000,512,0.0,100.0
-P4_ST_PT01,0.42286749999999995,0.0,0.0,600000,512,9916.0,10330.0
-P1_PIT02,0.405535,0.06640625,0.001953125,600000,512,0.17029,2.34695
-P4_HT_LD,0.38876958333333334,0.72265625,0.001953125,600000,512,-0.00723,83.10184
-P4_HT_FD,0.3790545833333333,0.0,0.0,600000,512,-0.02496,0.0293
-P4_ST_TT01,0.360623125,0.001953125,0.0,600000,512,27530.0,27629.0
-P3_PIT01,0.2977741666666667,0.00390625,0.001953125,600000,512,-24.0,3871.0
-P1_B2004,0.22622895833333334,0.017578125,0.0,600000,512,0.02978,0.10196
-P3_LCV01D,0.22572895833333334,0.228515625,0.001953125,600000,512,-288.0,18416.0
-P3_FIT01,0.18856375,0.001953125,0.0,600000,512,-27.0,5421.0
-P1_B3005,0.17442020833333333,0.0,0.001953125,600000,512,894.71869,1121.94116
-P1_B3004,0.14051208333333332,0.009765625,0.0,600000,512,369.75601,447.63004
-P2_SIT01,0.13476791666666665,0.0,0.0,600000,512,752.0,826.0
-P3_LCP01D,0.13422145833333332,0.029296875,0.0,600000,512,-8.0,13816.0
-P1_FCV03Z,0.10410729166666667,0.0,0.0,600000,512,46.35773,73.0835
-P1_LCV01Z,0.09569979166666667,0.095703125,0.0,600000,512,0.28381,23.72894
-P1_PCV01D,0.08203125,0.0,0.083984375,600000,512,24.99937,100.0
-P1_B4022,0.07836791666666665,0.001953125,0.001953125,600000,512,34.20232,38.65093
-P2_SIT02,0.07525937500000002,0.0,0.0,600000,512,751.53876,825.68994
-P1_FT03Z,0.07095687499999997,0.0,0.0,600000,512,867.38,1136.07874
-P1_FT03,0.07039374999999998,0.0,0.0,600000,512,187.88596,326.00403
-P1_FCV03D,0.06930249999999999,0.0,0.0,600000,512,45.96558,71.82662
-P1_PCV01Z,0.06755708333333332,0.001953125,0.005859375,600000,512,25.53711,100.0
-P1_FT02,0.06438541666666664,0.001953125,0.001953125,600000,512,4.80653,2006.56897
-P1_B400B,0.06315145833333335,0.001953125,0.001953125,600000,512,25.02598,2857.54565
-P1_FT02Z,0.0630914583333333,0.001953125,0.001953125,600000,512,25.02598,2857.54565
-P1_FT01Z,0.055490625000000016,0.001953125,0.0,600000,512,0.0,1181.04492
-P1_FT01,0.05535958333333335,0.001953125,0.0,600000,512,-15.60213,352.89764
-P1_LCV01D,0.05142875000000002,0.001953125,0.0,600000,512,2.12251,24.58632
-P1_TIT02,0.05030333333333337,0.001953125,0.001953125,600000,512,34.97925,40.4419
-P2_VXT03,0.046704791666666634,0.001953125,0.001953125,600000,512,-2.1603,0.2445
-P2_24Vdc,0.038648333333333285,0.001953125,0.001953125,600000,512,28.01254,28.04642
-P1_TIT01,0.03647541666666665,0.01171875,0.001953125,600000,512,34.68933,36.94763
-P1_PIT01,0.03585666666666665,0.0,0.001953125,600000,512,0.9317,2.39578
-P2_CO_rpm,0.03242437499999995,0.0,0.0,600000,512,53975.0,54185.0
-P1_LIT01,0.031228541666666665,0.001953125,0.001953125,600000,512,355.98859,459.44928
-P2_VYT03,0.030359791666666663,0.001953125,0.001953125,600000,512,4.5149,7.3006
-P4_ST_FD,0.028957083333333355,0.001953125,0.001953125,600000,512,-0.05244,0.05035
-P2_VXT02,0.026919374999999968,0.001953125,0.001953125,600000,512,-4.4009,-1.7734
-P2_VYT02,0.02145166666666666,0.001953125,0.001953125,600000,512,2.4162,5.156
-P2_HILout,0.016215208333333342,0.001953125,0.001953125,600000,512,653.75977,775.1648
-P2_VT01,0.0104625,0.001953125,0.001953125,600000,512,11.76047,12.06294
-P1_B2016,0.009429791666666687,0.001953125,0.001953125,600000,512,0.94729,2.0523
-P3_LIT01,0.00892770833333334,0.0,0.001953125,600000,512,5084.0,19730.0
-P4_ST_GOV,0.004135416666666614,0.001953125,0.001953125,600000,512,12625.0,26927.0
-P4_ST_PO,0.004044791666666714,0.001953125,0.001953125,600000,512,233.56122,498.86066
-P4_ST_LD,0.003954791666666679,0.001953125,0.001953125,600000,512,229.87201,499.62018
-P4_LD,0.00338583333333331,0.001953125,0.001953125,600000,512,231.13788,499.76489

example/results/ks_summary.json

@@ -1,17 +0,0 @@
-{
-  "generated_rows": 512,
-  "reference_rows_per_file": 200000,
-  "stride": 1,
-  "top_k_features": [
-    "P2_MSD",
-    "P1_B4002",
-    "P1_PCV02Z",
-    "P1_FCV02Z",
-    "P4_HT_PO",
-    "P1_B4005",
-    "P4_ST_PT01",
-    "P1_PIT02",
-    "P4_HT_LD",
-    "P4_HT_FD"
-  ]
-}

example/results/metrics_history.csv

@@ -1,16 +0,0 @@
-timestamp,avg_ks,avg_jsd,avg_lag1_diff
-2026-01-26T17:15:06.927423,0.5204744693396227,0.013087877218697579,0.6060810896277049
-2026-01-26T17:15:06.977813,0.5204744693396227,0.013087877218697579,0.6060810896277049
-2026-01-26T17:23:19.986340,0.6451295400943398,0.027818187919735473,0.24898834978597875
-2026-01-26T17:23:20.046864,0.6451295400943398,0.027818187919735473,0.24898834978597875
-2026-01-27T11:19:53.735830,0.9431816627358489,0.11505222210663352,0.39121478044554636
-2026-01-27T11:19:53.788440,0.9431816627358489,0.11505222210663352,0.39121478044554636
-2026-01-27T15:51:49.383840,0.9416695165094339,0.019697736706358257,0.4034492291839661
-2026-01-27T15:51:49.436359,0.9416695165094339,0.019697736706358257,0.4034492291839661
-2026-01-27T16:45:48.759028,0.9356107311320754,0.0150041229476627,0.3628097687091748
-2026-01-27T21:22:34.514698,0.4046341391509435,0.03761331157429302,0.14486773175256126
-2026-01-28T09:50:21.507510,0.4050414504716981,0.04217758555603813,0.16788530065918408
-2026-01-28T11:08:29.763931,0.4214702830188679,0.04217758555603808,0.25421316990030157
-2026-01-28T11:14:32.039924,0.4185297169811321,0.04217758555603794,0.22152028672698215
-2026-01-28T11:27:57.010675,None,None,None
-2026-01-28T15:06:13.198144,0.30925147405660375,0.03503984996838547,0.2722453599605884

example/results/program_stats.json

@@ -1,113 +0,0 @@
-{
-  "features": [
-    "P1_B4002",
-    "P2_MSD",
-    "P4_HT_LD",
-    "P1_B2004",
-    "P1_B3004",
-    "P1_B4022",
-    "P1_B3005"
-  ],
-  "generated": {
-    "P1_B4002": {
-      "num_changes": 0,
-      "mean_dwell": 512.0,
-      "median_dwell": 512,
-      "mean_step": null,
-      "median_step": null
-    },
-    "P2_MSD": {
-      "num_changes": 0,
-      "mean_dwell": 512.0,
-      "median_dwell": 512,
-      "mean_step": null,
-      "median_step": null
-    },
-    "P4_HT_LD": {
-      "num_changes": 147,
-      "mean_dwell": 3.4594594594594597,
-      "median_dwell": 1.0,
-      "mean_step": 6.7685889115646285,
-      "median_step": 1.2689499999999896
-    },
-    "P1_B2004": {
-      "num_changes": 162,
-      "mean_dwell": 3.1411042944785277,
-      "median_dwell": 2,
-      "mean_step": 0.005886728395061727,
-      "median_step": 0.00016499999999999154
-    },
-    "P1_B3004": {
-      "num_changes": 329,
-      "mean_dwell": 1.5515151515151515,
-      "median_dwell": 1.0,
-      "mean_step": 6.167710607902744,
-      "median_step": 2.97004000000004
-    },
-    "P1_B4022": {
-      "num_changes": 511,
-      "mean_dwell": 1.0,
-      "median_dwell": 1.0,
-      "mean_step": 0.13465921722113547,
-      "median_step": 0.06072999999999951
-    },
-    "P1_B3005": {
-      "num_changes": 325,
-      "mean_dwell": 1.5705521472392638,
-      "median_dwell": 1.0,
-      "mean_step": 27.028075692307645,
-      "median_step": 4.829840000000104
-    }
-  },
-  "reference": {
-    "P1_B4002": {
-      "num_changes": 539,
-      "mean_dwell": 1111.111111111111,
-      "median_dwell": 1.0,
-      "mean_step": 0.03526690166975881,
-      "median_step": 0.02238999999999436
-    },
-    "P2_MSD": {
-      "num_changes": 0,
-      "mean_dwell": 600000.0,
-      "median_dwell": 600000,
-      "mean_step": null,
-      "median_step": null
-    },
-    "P4_HT_LD": {
-      "num_changes": 381284,
-      "mean_dwell": 1.5736260277744993,
-      "median_dwell": 1,
-      "mean_step": 1.0360111255124251,
-      "median_step": 0.24593999999999028
-    },
-    "P1_B2004": {
-      "num_changes": 854,
-      "mean_dwell": 701.7543859649123,
-      "median_dwell": 1,
-      "mean_step": 0.0017408899297423831,
-      "median_step": 0.0001900000000000096
-    },
-    "P1_B3004": {
-      "num_changes": 893,
-      "mean_dwell": 671.1409395973154,
-      "median_dwell": 1.0,
-      "mean_step": 1.3647845352743568,
-      "median_step": 1.2404200000000287
-    },
-    "P1_B4022": {
-      "num_changes": 592367,
-      "mean_dwell": 1.0128838829916538,
-      "median_dwell": 1.0,
-      "mean_step": 0.011701348724693727,
-      "median_step": 0.009259999999997603
-    },
-    "P1_B3005": {
-      "num_changes": 898,
-      "mean_dwell": 667.4082313681869,
-      "median_dwell": 1,
-      "mean_step": 4.884911592427617,
-      "median_step": 3.892939999999953
-    }
-  }
-}

example/results/pv_stats.json

@@ -1,47 +0,0 @@
-{
-  "features": [
-    "P1_PIT02",
-    "P2_SIT02",
-    "P1_FT03"
-  ],
-  "generated": {
-    "P1_PIT02": {
-      "q05": 0.17029,
-      "q50": 0.27557,
-      "q95": 1.80603,
-      "tail_ratio": 14.537044072948332
-    },
-    "P2_SIT02": {
-      "q05": 774.9809,
-      "q50": 784.55231,
-      "q95": 791.64404,
-      "tail_ratio": 0.740928452547741
-    },
-    "P1_FT03": {
-      "q05": 209.77301,
-      "q50": 298.91904,
-      "q95": 316.2464,
-      "tail_ratio": 0.1943705176775679
-    }
-  },
-  "reference": {
-    "P1_PIT02": {
-      "q05": 0.20004,
-      "q50": 0.27557,
-      "q95": 1.74652,
-      "tail_ratio": 19.475043029259904
-    },
-    "P2_SIT02": {
-      "q05": 774.13159,
-      "q50": 783.5752,
-      "q95": 791.13818,
-      "tail_ratio": 0.8008568757074901
-    },
-    "P1_FT03": {
-      "q05": 229.11069,
-      "q50": 296.63086,
-      "q95": 316.08582,
-      "tail_ratio": 0.28813553046445284
-    }
-  }
-}

example/results/train_log.csv

@@ -1,601 +1,61 @@
-epoch,step,loss,loss_cont,loss_disc
-0,0,4104.687500,5862.747070,2.178488
-0,10,3536.101318,5050.882324,1.458394
-0,20,3703.872314,5290.688965,1.171645
-0,30,1910.917969,2729.372070,1.074986
-0,40,2875.610107,4107.557129,0.955374
-0,50,2182.169189,3116.975830,0.829201
-0,60,2310.010254,3299.599609,0.862826
-0,70,2289.944336,3270.902100,0.913125
-0,80,1974.353638,2820.125977,0.797024
-0,90,1868.654175,2669.177246,0.690314
-0,100,1740.059082,2485.354980,0.958985
-0,110,1732.860596,2475.218994,0.606716
-0,120,1594.503906,2277.457764,0.870128
-0,130,1485.397339,2121.689453,0.628675
-0,140,1663.155151,2375.665283,0.554727
-0,150,1244.725830,1778.056274,0.182687
-0,160,1402.332642,2003.170654,0.282689
-0,170,1512.496338,2160.558838,0.275448
-0,180,1670.079102,2385.719727,0.175730
-0,190,1547.238647,2210.280518,0.047682
-0,200,1593.958984,2277.003906,0.113074
-0,210,1565.605103,2236.356934,0.449145
-0,220,1662.660522,2374.932373,0.617599
-0,230,1552.008911,2216.916016,0.496879
-0,240,1503.767456,2148.007568,0.475375
-0,250,1452.047485,2074.148193,0.408073
-0,260,1418.459839,2026.021362,0.744013
-0,270,1450.793823,2072.224365,0.719304
-0,280,1453.708374,2076.430176,0.624461
-0,290,1488.527466,2126.073242,0.853243
-0,300,1478.090454,2111.257812,0.633018
-0,310,1478.777710,2112.259033,0.595130
-0,320,1615.990845,2308.291016,0.560645
-0,330,1579.406006,2255.940430,0.756187
-0,340,1581.701416,2259.246826,0.697630
-0,350,1496.947388,2138.174561,0.680877
-0,360,1456.666138,2080.627197,0.692975
-0,370,1477.003296,2109.670410,0.718830
-0,380,1572.606934,2246.287598,0.627865
-0,390,1522.502197,2174.713623,0.614935
-0,400,1493.296509,2132.903320,0.780275
-0,410,1524.145386,2177.007568,0.732000
-0,420,1588.011719,2268.226807,0.778016
-0,430,1454.315063,2077.208008,0.825472
-0,440,1344.950073,1921.040283,0.673849
-0,450,1442.704590,2060.571777,0.954480
-0,460,1513.709473,2162.061035,0.830872
-0,470,1352.947144,1932.389526,0.854246
-0,480,1520.071533,2171.178711,0.766926
-0,490,1504.268799,2148.627441,0.716509
-0,500,1424.067139,2033.998413,0.836030
-0,510,1445.508057,2064.694824,0.686692
-0,520,1487.015259,2123.946289,0.787334
-0,530,1465.874023,2093.735107,0.806815
-0,540,1393.076416,1989.753662,0.753482
-0,550,1270.714844,1814.963989,0.732413
-0,560,1354.596191,1934.757080,0.829648
-0,570,1437.738647,2053.666504,0.519293
-0,580,1451.285156,2072.960938,0.657817
-0,590,1453.594482,2076.309570,0.532077
-1,0,1469.492310,2098.965820,0.631533
-1,10,1528.943726,2184.033447,0.332331
-1,20,1532.261841,2188.617920,0.701701
-1,30,1437.658691,2053.415039,0.832294
-1,40,1422.786255,2032.210571,0.740615
-1,50,1389.998413,1985.322144,0.849180
-1,60,1431.342529,2044.446167,0.721667
-1,70,1455.066772,2078.357910,0.664868
-1,80,1513.984131,2162.497803,0.725356
-1,90,1271.441528,1816.035156,0.647611
-1,100,1441.777832,2059.299805,0.822128
-1,110,1541.762695,2202.180420,0.727877
-1,120,1412.815918,2018.015259,0.630952
-1,130,1565.231567,2235.738281,0.663620
-1,140,1448.755005,2069.445068,0.407724
-1,150,1605.111328,2292.921387,0.136907
-1,160,1436.910889,2052.678955,0.064638
-1,170,1457.122314,2081.499512,0.183146
-1,180,1499.768066,2142.480957,0.048173
-1,190,1401.955200,2002.751099,0.043032
-1,200,979.878784,1399.663574,0.304141
-1,210,1565.479614,2236.199463,0.410266
-1,220,1536.427246,2194.618164,0.590521
-1,230,1516.902222,2166.816650,0.372581
-1,240,1563.220947,2232.919678,0.511253
-1,250,1557.915283,2225.241699,0.759270
-1,260,1481.426392,2115.975342,0.738883
-1,270,1235.948364,1765.398804,0.499572
-1,280,1499.819580,2142.219971,0.829189
-1,290,1616.706909,2309.235352,0.752964
-1,300,1382.318481,1974.516113,0.468937
-1,310,1441.740967,2059.241455,0.862096
-1,320,1338.727783,1912.144409,0.696239
-1,330,1516.445801,2166.041992,0.661255
-1,340,1402.084717,2002.618408,0.773246
-1,350,1468.796997,2097.979980,0.656207
-1,360,1105.756714,1579.383423,0.562119
-1,370,1549.638306,2213.398438,0.811882
-1,380,1416.978760,2023.931519,0.707049
-1,390,1470.207886,2100.025391,0.577433
-1,400,1316.625732,1880.554199,0.724575
-1,410,1447.713379,2067.786133,0.830025
-1,420,1486.760010,2123.614258,0.716196
-1,430,1467.659546,2096.303955,0.772352
-1,440,1405.042847,2006.883789,0.690063
-1,450,1439.062988,2055.472900,0.723698
-1,460,1358.712891,1940.719727,0.646482
-1,470,1485.175659,2121.314209,0.801449
-1,480,1401.153564,2001.302246,0.763440
-1,490,1340.916992,1915.245972,0.767783
-1,500,1505.187866,2150.000000,0.583609
-1,510,1399.703369,1999.216919,0.792233
-1,520,1492.678345,2132.063965,0.734403
-1,530,1345.968750,1922.510986,0.654493
-1,540,1343.317261,1918.732788,0.628905
-1,550,1525.061768,2178.354736,0.661661
-1,560,1434.962402,2049.600830,0.754821
-1,570,1505.918091,2151.010254,0.657582
-1,580,1323.484375,1890.338745,0.776388
-1,590,1376.718018,1966.340820,0.880533
-2,0,1461.936279,2088.137695,0.713465
-2,10,1435.976562,2051.202148,0.381847
-2,20,1542.990479,2203.951904,0.690274
-2,30,1597.138916,2281.350830,0.591171
-2,40,1482.657715,2117.850830,0.491510
-2,50,1450.865234,2072.306641,0.785586
-2,60,1404.534058,2006.196167,0.612618
-2,70,1458.306396,2082.998047,0.643317
-2,80,1502.782349,2146.593262,0.506225
-2,90,1483.132935,2118.490234,0.578424
-2,100,1537.445557,2196.011230,0.724901
-2,110,1663.348511,2375.892090,0.679431
-2,120,1528.875488,2183.759766,0.747647
-2,130,1414.394409,2020.316528,0.510345
-2,140,1490.696533,2129.406494,0.308606
-2,150,1472.365112,2103.291504,0.146353
-2,160,1393.995361,1991.368042,0.069130
-2,170,1472.133301,2102.949219,0.177877
-2,180,1424.363159,2034.755737,0.060463
-2,190,1448.978027,2069.924805,0.048531
-2,200,1367.177368,1952.992920,0.220321
-2,210,1414.589844,2020.715088,0.242842
-2,220,1459.871338,2085.306152,0.473835
-2,230,1475.376953,2107.409912,0.581559
-2,240,1366.376099,1951.696045,0.561784
-2,250,1628.457275,2326.060791,0.665703
-2,260,1375.316162,1964.423340,0.675052
-2,270,1604.605103,2292.037598,0.534063
-2,280,1474.603271,2106.214600,0.789462
-2,290,1537.406860,2195.959717,0.737982
-2,300,1321.747681,1887.848022,0.797281
-2,310,1509.287231,2155.767090,0.784205
-2,320,1350.093140,1928.462280,0.516796
-2,330,1427.947876,2039.595947,0.722781
-2,340,1223.096313,1746.997437,0.597822
-2,350,1567.943481,2239.609131,0.669152
-2,360,1481.821899,2116.618408,0.575916
-2,370,1497.595947,2139.068604,0.779643
-2,380,1463.289429,2090.082275,0.723437
-2,390,1441.334839,2058.694336,0.780149
-2,400,1409.162598,2012.842651,0.525692
-2,410,1364.838745,1949.481201,0.625563
-2,420,1463.869141,2090.855713,0.853791
-2,430,1535.858032,2193.759521,0.697273
-2,440,1426.288452,2037.224243,0.715442
-2,450,1429.705322,2042.084717,0.759498
-2,460,1560.038452,2228.339111,0.620705
-2,470,1397.352173,1995.897339,0.687523
-2,480,1357.472290,1938.830811,0.920918
-2,490,1535.428345,2193.129150,0.746372
-2,500,1448.799805,2069.424561,0.630107
-2,510,1389.700317,1985.009644,0.600927
-2,520,1476.384644,2108.760986,0.792292
-2,530,1382.595337,1974.840088,0.648419
-2,540,1518.288208,2168.632568,0.765787
-2,550,1518.313599,2168.683838,0.731164
-2,560,1423.568237,2033.348877,0.697869
-2,570,1365.206421,1949.879395,0.915926
-2,580,1340.291504,1914.393066,0.663590
-2,590,1423.510254,2033.280273,0.652785
-3,0,1614.672852,2306.410156,0.533011
-3,10,1420.924072,2029.671875,0.446738
-3,20,1405.875366,2008.091431,0.645666
-3,30,1455.627808,2079.211182,0.541790
-3,40,1435.463867,2050.362061,0.650584
-3,50,1204.273315,1719.990723,0.878515
-3,60,1441.953369,2059.686523,0.530262
-3,70,1485.965088,2122.446045,0.795575
-3,80,1326.177246,1894.231445,0.669984
-3,90,1408.871338,2012.380249,0.641243
-3,100,1561.939697,2230.960938,0.838334
-3,110,1472.460815,2103.209961,0.660208
-3,120,1445.443481,2064.650391,0.580035
-3,130,1444.952881,2063.965820,0.532962
-3,140,1405.757202,2008.045044,0.354315
-3,150,1437.336914,2053.153320,0.371112
-3,160,1428.433228,2040.480957,0.260767
-3,170,1347.353027,1924.663940,0.227671
-3,180,1472.868896,2104.022949,0.123693
-3,190,1420.532227,2029.287598,0.050413
-3,200,1347.952759,1925.470947,0.348400
-3,210,1486.893433,2123.933838,0.409374
-3,220,1347.399658,1924.632935,0.464866
-3,230,1352.939819,1932.487671,0.610396
-3,240,1448.691650,2069.340332,0.452461
-3,250,1421.549927,2030.475708,0.664943
-3,260,1460.304810,2085.876953,0.587443
-3,270,1492.832886,2132.395264,0.469572
-3,280,1409.628784,2013.476807,0.603606
-3,290,1367.326416,1952.963257,0.794387
-3,300,1453.679565,2076.443848,0.516301
-3,310,1429.363403,2041.612671,0.729997
-3,320,1318.426514,1883.159424,0.669911
-3,330,1444.947144,2063.858643,0.775698
-3,340,1483.210571,2118.566162,0.666679
-3,350,1487.385986,2124.584229,0.543496
-3,360,1472.693848,2103.528320,0.696426
-3,370,1470.262329,2100.062988,0.685241
-3,380,1500.875488,2143.866943,0.510682
-3,390,1350.099121,1928.455933,0.532808
-3,400,1391.044922,1986.973755,0.494259
-3,410,1359.589966,1941.908203,0.803586
-3,420,1176.671265,1680.653564,0.650540
-3,430,1476.322144,2108.634766,0.881387
-3,440,1472.196289,2102.825195,0.684638
-3,450,1536.467651,2194.627930,0.714324
-3,460,1476.224609,2108.548584,0.758960
-3,470,1420.996948,2029.703491,0.630627
-3,480,1447.555176,2067.613525,0.707864
-3,490,1408.194824,2011.371338,0.738692
-3,500,1486.959595,2123.877197,0.774664
-3,510,1445.206787,2064.186523,0.869829
-3,520,1420.591797,2029.070801,0.760115
-3,530,1406.106445,2008.375977,0.762909
-3,540,1426.834595,2038.003418,0.723026
-3,550,1570.177002,2242.767578,0.746613
-3,560,1456.610840,2080.532715,0.746837
-3,570,1542.949341,2203.877441,0.738409
-3,580,1411.989136,2016.762817,0.806803
-3,590,1534.442871,2191.748291,0.684729
-4,0,1502.577148,2146.362061,0.309913
-4,10,1441.278442,2058.713379,0.530398
-4,20,1430.760254,2043.626343,0.688684
-4,30,1477.291748,2110.098389,0.683065
-4,40,1447.918457,2068.191650,0.559888
-4,50,1395.153320,1992.722412,0.777434
-4,60,1388.759888,1983.651367,0.632309
-4,70,1482.703613,2117.865723,0.617648
-4,80,1265.346558,1807.336548,0.654188
-4,90,1319.890259,1885.338623,0.464331
-4,100,1553.465820,2218.823242,0.913150
-4,110,1307.115112,1866.997559,0.664835
-4,120,1548.101562,2211.248291,0.711003
-4,130,1432.663574,2046.409180,0.540259
-4,140,1493.257568,2133.032471,0.389164
-4,150,1353.020020,1932.790405,0.149219
-4,160,1455.381714,2079.012451,0.184352
-4,170,1467.347168,2096.102783,0.195314
-4,180,1399.401489,1999.071411,0.107582
-4,190,1400.822388,2001.121582,0.057634
-4,200,1224.315552,1748.884888,0.252544
-4,210,1418.477905,2026.170898,0.474197
-4,220,1208.370117,1726.063843,0.351747
-4,230,1337.807617,1910.996460,0.311286
-4,240,1507.050537,2152.759277,0.352854
-4,250,1297.721680,1853.434937,1.004065
-4,260,1478.236572,2111.380859,0.838521
-4,270,1427.240967,2038.630005,0.613481
-4,280,1401.061523,2001.197144,0.696015
-4,290,1388.019897,1982.577271,0.668258
-4,300,1415.929688,2022.399414,0.785305
-4,310,1499.063110,2141.178711,0.751149
-4,320,1358.888672,1940.966431,0.657286
-4,330,1400.725830,2000.757324,0.605922
-4,340,1450.309082,2071.527588,0.752350
-4,350,1506.710571,2152.100586,0.752541
-4,360,1504.856934,2149.574707,0.470153
-4,370,1322.843140,1889.455688,0.691118
-4,380,1462.084473,2088.443848,0.528986
-4,390,1263.524902,1804.698486,0.740295
-4,400,1380.690674,1972.050171,0.803551
-4,410,1309.063843,1869.714844,0.829797
-4,420,1377.738892,1967.855957,0.752649
-4,430,1449.150635,2069.907471,0.674271
-4,440,1433.704712,2047.839355,0.682620
-4,450,1291.199341,1844.203247,0.810975
-4,460,1239.914429,1770.938477,0.800310
-4,470,1505.356323,2150.194092,0.684871
-4,480,1407.745605,2010.673462,0.861430
-4,490,1531.308350,2187.251221,0.728936
-4,500,1307.696655,1867.882202,0.550228
-4,510,1361.909546,1945.229492,0.784346
-4,520,1409.626709,2013.444336,0.678981
-4,530,1314.652710,1877.728027,0.756546
-4,540,1393.048340,1989.705078,0.802045
-4,550,1560.211060,2228.582031,0.630462
-4,560,1195.171387,1706.978516,0.907659
-4,570,1364.631592,1949.163696,0.675972
-4,580,1422.267944,2031.495239,0.685836
-4,590,1601.816406,2287.948486,0.794373
-5,0,1357.176880,1938.601685,0.417487
-5,10,1505.491455,2150.466064,0.480685
-5,20,1577.331421,2253.082764,0.522217
-5,30,1524.921021,2178.131592,0.710362
-5,40,1434.665161,2049.148926,0.821321
-5,50,1515.062988,2164.030518,0.762074
-5,60,1500.802734,2143.717529,0.621529
-5,70,1459.192505,2084.347412,0.453322
-5,80,1423.275757,2032.978882,0.593649
-5,90,1217.277222,1738.710815,0.540554
-5,100,1448.314087,2068.743652,0.598670
-5,110,1495.733398,2136.452393,0.677112
-5,120,1441.327759,2058.619141,0.929921
-5,130,1513.855103,2162.367432,0.607940
-5,140,1358.637085,1940.738770,0.342751
-5,150,1473.268066,2104.569824,0.178626
-5,160,1428.839111,2041.064941,0.259330
-5,170,1459.831909,2085.375732,0.177986
-5,180,1490.674561,2129.478027,0.084810
-5,190,1420.571777,2029.284302,0.191282
-5,200,1400.808105,2001.015015,0.273041
-5,210,1469.785400,2099.401123,0.631073
-5,220,1306.050049,1865.550659,0.489496
-5,230,1473.019409,2104.067139,0.523982
-5,240,1462.958130,2089.645996,0.628826
-5,250,1423.337891,2033.092407,0.525899
-5,260,1502.425659,2145.985107,0.735771
-5,270,1529.326782,2184.434326,0.694655
-5,280,1424.965698,2035.264771,0.882783
-5,290,1415.541260,2021.883301,0.691824
-5,300,1486.536865,2123.356445,0.576374
-5,310,1415.819458,2022.342041,0.550085
-5,320,1435.529175,2050.413818,0.745789
-5,330,1381.430664,1973.197510,0.592411
-5,340,1523.080811,2175.467773,0.799122
-5,350,1426.364258,2037.411987,0.544562
-5,360,1428.304810,2040.145386,0.633054
-5,370,1510.579834,2157.604492,0.801477
-5,380,1495.591064,2136.213867,0.747921
-5,390,1403.855103,2005.214844,0.635726
-5,400,1300.357056,1857.335571,0.691041
-5,410,1455.098755,2078.317383,0.871583
-5,420,1425.369263,2035.894775,0.753768
-5,430,1337.890381,1910.930176,0.738220
-5,440,1427.809082,2039.417480,0.668992
-5,450,1472.066406,2102.625732,0.710911
-5,460,1345.457031,1921.725708,0.787629
-5,470,1173.551270,1676.144897,0.772777
-5,480,1453.112915,2075.485352,0.865678
-5,490,1377.495239,1967.514648,0.724336
-5,500,1256.473999,1794.620483,0.753463
-5,510,1283.652344,1833.455933,0.729668
-5,520,1397.752441,1996.423706,0.806173
-5,530,1299.720703,1856.489136,0.552804
-5,540,1438.412964,2054.523193,0.770349
-5,550,1461.792358,2087.957031,0.696921
-5,560,1521.123901,2172.654785,0.842064
-5,570,1294.959351,1849.560059,0.838963
-5,580,1279.269409,1827.242920,0.614312
-5,590,1377.951172,1968.127075,0.830283
-6,0,1299.058472,1855.578613,0.419193
-6,10,1554.125854,2219.911621,0.566216
-6,20,1469.026245,2098.378174,0.487446
-6,30,1429.229858,2041.424072,0.725512
-6,40,1358.838013,1940.871094,0.719045
-6,50,1513.332153,2161.645508,0.560400
-6,60,1354.492798,1934.732544,0.558887
-6,70,1437.575928,2053.360352,0.704892
-6,80,1269.222168,1812.866455,0.675226
-6,90,1226.577148,1751.981812,0.573045
-6,100,1407.117920,2009.826416,0.745830
-6,110,1560.080444,2228.346924,0.734665
-6,120,1333.887939,1905.255005,0.645339
-6,130,1415.745605,2022.293945,0.404235
-6,140,1467.666504,2096.484131,0.366057
-6,150,1323.537964,1890.595703,0.354378
-6,160,1395.991943,1994.202637,0.114646
-6,170,1504.379028,2149.058105,0.077982
-6,180,1508.160278,2154.427002,0.157914
-6,190,1312.385132,1874.783569,0.076829
-6,200,1266.057495,1808.588867,0.093482
-6,210,1197.125977,1710.037720,0.273738
-6,220,1341.001221,1915.435913,0.605067
-6,230,1418.721313,2026.500366,0.513404
-6,240,1383.062500,1975.633423,0.333137
-6,250,1465.177490,2092.773193,0.742228
-6,260,1408.995850,2012.481934,0.812256
-6,270,1437.097778,2052.704834,0.637276
-6,280,1317.524902,1881.865112,0.684442
-6,290,1482.736572,2117.885986,0.673523
-6,300,1490.681763,2129.199463,0.766585
-6,310,1365.756958,1950.750366,0.725595
-6,320,1433.082397,2046.970825,0.630201
-6,330,1349.012573,1926.889038,0.591482
-6,340,1416.651367,2023.452515,0.738159
-6,350,1297.343750,1853.107666,0.503186
-6,360,1269.170410,1812.812988,0.616282
-6,370,1504.779297,2149.401123,0.612120
-6,380,1256.419434,1794.575928,0.664299
-6,390,1385.377686,1978.866333,0.521549
-6,400,1330.533569,1900.516357,0.522253
-6,410,1390.856567,1986.603394,0.736171
-6,420,1413.385742,2018.820557,0.658699
-6,430,1348.490601,1926.072266,0.746640
-6,440,1499.281372,2141.520752,0.673835
-6,450,1330.471191,1900.349976,0.709257
-6,460,1478.617432,2111.995850,0.687881
-6,470,1427.542358,2038.993652,0.772080
-6,480,1375.557495,1964.762085,0.705771
-6,490,1445.668701,2064.928711,0.686484
-6,500,1437.072266,2052.662354,0.651817
-6,510,1471.395386,2101.762207,0.495373
-6,520,1359.329712,1941.522461,0.828027
-6,530,1395.305176,1992.941650,0.771585
-6,540,1477.400391,2110.239990,0.726394
-6,550,1395.229858,1992.933350,0.540920
-6,560,1318.548706,1883.253174,0.864107
-6,570,1419.596436,2027.636841,0.795708
-6,580,1352.935669,1932.428833,0.737228
-6,590,1441.829224,2059.448242,0.671328
-7,0,1458.359009,2083.131348,0.474254
-7,10,1476.152100,2108.498535,0.614632
-7,20,1304.542603,1863.311157,0.680537
-7,30,1366.867310,1952.330200,0.740350
-7,40,1340.022217,1913.968994,0.767041
-7,50,1371.038452,1958.337891,0.633874
-7,60,1523.746704,2176.447998,0.728549
-7,70,1444.063965,2062.632812,0.691357
-7,80,1369.596924,1956.232788,0.739195
-7,90,1306.306519,1865.871460,0.610914
-7,100,1451.343750,2073.062744,0.622281
-7,110,1433.468994,2047.442993,0.811452
-7,120,1313.580566,1876.184448,0.785068
-7,130,1483.872192,2119.618652,0.409689
-7,140,1372.579468,1960.647217,0.362606
-7,150,1443.399780,2061.907715,0.153282
-7,160,1170.979248,1672.746216,0.123093
-7,170,1343.805054,1919.651733,0.108097
-7,180,1469.474365,2099.142334,0.198891
-7,190,1293.158447,1847.315063,0.077014
-7,200,1422.293701,2031.685669,0.327245
-7,210,1483.056885,2118.527832,0.236196
-7,220,1485.793701,2122.295410,0.573137
-7,230,1283.809814,1833.758057,0.539699
-7,240,1341.406982,1916.115967,0.373807
-7,250,1340.194458,1914.277588,0.618324
-7,260,1412.598511,2017.736206,0.563230
-7,270,1491.155518,2129.986816,0.492826
-7,280,1405.379150,2007.355835,0.719181
-7,290,1286.243530,1837.186890,0.655533
-7,300,1379.018921,1969.791260,0.500241
-7,310,1393.592163,1990.516357,0.719522
-7,320,1404.897827,2006.737427,0.556678
-7,330,1418.931396,2026.739502,0.666439
-7,340,1472.646118,2103.480469,0.650440
-7,350,1424.270020,2034.407471,0.568910
-7,360,1389.830811,1985.231567,0.518565
-7,370,1428.171875,2039.960083,0.617411
-7,380,1425.542603,2036.217041,0.590281
-7,390,1438.997070,2055.415527,0.644235
-7,400,1389.501465,1984.674927,0.720130
-7,410,1329.529663,1898.960815,0.807951
-7,420,1414.494995,2020.359497,0.767079
-7,430,1464.256104,2091.471680,0.706681
-7,440,1346.824463,1923.722778,0.679560
-7,450,1520.953613,2172.506104,0.620894
-7,460,1420.898315,2029.451904,0.890310
-7,470,1329.062256,1898.330811,0.726035
-7,480,1331.335815,1901.550049,0.791371
-7,490,1330.184570,1899.964600,0.643707
-7,500,1446.781494,2066.527344,0.663432
-7,510,1411.553955,2016.199707,0.673441
-7,520,1243.028442,1775.422852,0.725532
-7,530,1303.489258,1861.799561,0.707768
-7,540,1393.307983,1990.125244,0.692376
-7,550,1476.846191,2109.527832,0.540072
-7,560,1454.410645,2077.345947,0.851981
-7,570,1368.117920,1954.093628,0.797793
-7,580,1461.680786,2087.789795,0.710074
-7,590,1474.375610,2105.846436,0.893905
-8,0,1453.263306,2075.892090,0.383183
-8,10,1489.154419,2127.105469,0.534864
-8,20,1468.300903,2097.338135,0.487083
-8,30,1378.775146,1969.381348,0.640614
-8,40,1509.492065,2156.170166,0.524495
-8,50,1393.387939,1990.242798,0.679312
-8,60,1306.811401,1866.615479,0.551015
-8,70,1426.589111,2037.635254,0.774625
-8,80,1457.533691,2081.950928,0.520180
-8,90,1318.460938,1883.212402,0.656653
-8,100,1416.464966,2023.235107,0.618202
-8,110,1086.514282,1551.846191,0.687443
-8,120,1486.569092,2123.250488,0.924503
-8,130,1449.384644,2070.230469,0.687878
-8,140,1436.892944,2052.487793,0.452704
-8,150,1233.567627,1762.144043,0.157274
-8,160,1432.293457,2046.041382,0.155251
-8,170,1469.417358,2099.019287,0.290829
-8,180,1436.628052,2052.265625,0.090901
-8,190,1293.560181,1847.887085,0.080034
-8,200,1369.832520,1956.835938,0.108914
-8,210,1409.676270,2013.601807,0.464143
-8,220,1350.459595,1928.890259,0.733399
-8,230,1179.746826,1685.084351,0.566658
-8,240,1310.429810,1871.796997,0.518973
-8,250,1451.661377,2073.388916,0.914655
-8,260,1478.491699,2111.829590,0.649755
-8,270,1374.234619,1962.987549,0.421328
-8,280,1284.619019,1834.788086,0.837083
-8,290,1488.189331,2125.735596,0.537642
-8,300,1218.428711,1740.245483,0.799829
-8,310,1443.259644,2061.479736,0.700240
-8,320,1351.602539,1930.559204,0.657145
-8,330,1387.119019,1981.290527,0.674150
-8,340,1380.720337,1972.138428,0.699702
-8,350,1372.677490,1960.713013,0.549182
-8,360,1238.659058,1769.233398,0.603408
-8,370,1452.913696,2075.196777,0.871121
-8,380,1424.684570,2034.992065,0.591460
-8,390,1481.086304,2115.526611,0.680652
-8,400,1418.040405,2025.557007,0.459452
-8,410,1485.971313,2122.509277,0.675124
-8,420,1415.459961,2021.683472,0.892317
-8,430,1418.012939,2025.439819,0.640834
-8,440,1117.131226,1595.562866,0.735428
-8,450,1449.021729,2069.687988,0.759266
-8,460,1391.115356,1987.010254,0.647844
-8,470,1433.931274,2048.105469,0.809236
-8,480,1371.290527,1958.663940,0.711260
-8,490,1256.615234,1794.848145,0.689194
-8,500,1409.895752,2013.783325,0.779393
-8,510,1459.595337,2084.778564,0.790248
-8,520,1450.381104,2071.603027,0.819859
-8,530,1444.885376,2063.787354,0.731137
-8,540,1215.213501,1735.670288,0.757565
-8,550,1413.502563,2019.008667,0.612963
-8,560,1430.360474,2043.065063,0.666718
-8,570,1451.094360,2072.605225,0.856367
-8,580,1401.830322,2002.314819,0.648709
-8,590,1382.358887,1974.526733,0.589752
-9,0,1366.947021,1952.541016,0.468936
-9,10,1411.335571,2015.938110,0.539704
-9,20,1420.959229,2029.646851,0.634849
-9,30,1344.455933,1920.343506,0.662471
-9,40,1409.275391,2012.917358,0.732841
-9,50,1349.377441,1927.294678,0.852183
-9,60,1394.930542,1992.468140,0.636684
-9,70,1161.929077,1659.616211,0.596739
-9,80,1160.281128,1657.251831,0.623772
-9,90,1308.133667,1868.436523,0.710033
-9,100,1347.696899,1924.963745,0.687743
-9,110,1263.972656,1805.316162,0.783335
-9,120,1366.904541,1952.452271,0.575681
-9,130,1300.172974,1857.074341,0.692025
-9,140,1420.715698,2029.301270,0.631423
-9,150,1399.410156,1999.064331,0.162491
-9,160,1345.370361,1921.837769,0.223673
-9,170,1395.316895,1993.224121,0.150818
-9,180,1454.697754,2078.039307,0.182863
-9,190,1455.122681,2078.682617,0.103459
-9,200,1480.913574,2115.440674,0.294885
-9,210,1196.324707,1708.723511,0.665973
-9,220,1388.034302,1982.641235,0.564907
-9,230,1385.036011,1978.449707,0.352146
-9,240,1479.323242,2113.091064,0.480505
-9,250,1348.598267,1926.301147,0.575881
-9,260,1480.543579,2114.666992,0.875085
-9,270,1498.691650,2140.654297,0.730880
-9,280,1298.342407,1854.374146,0.886711
-9,290,1482.312134,2117.226562,0.796350
-9,300,1300.968018,1858.237549,0.621199
-9,310,1438.974487,2055.428955,0.534846
-9,320,1541.583862,2201.942871,0.697966
-9,330,1430.867310,2043.802856,0.637363
-9,340,1363.975952,1948.189453,0.763094
-9,350,1343.921387,1919.618164,0.587540
-9,360,1356.898682,1938.150757,0.600651
-9,370,1240.004028,1771.123291,0.663849
-9,380,1144.410034,1634.552368,0.689964
-9,390,1313.722290,1876.533081,0.447632
-9,400,1389.418335,1984.513428,0.819520
-9,410,1408.678467,2012.042969,0.779253
-9,420,1442.015503,2059.672607,0.774919
-9,430,1447.314331,2067.257080,0.735090
-9,440,1285.097290,1835.538452,0.677175
-9,450,1305.512939,1864.603516,0.924807
-9,460,1508.623047,2154.867920,0.668181
-9,470,1412.079346,2016.932129,0.710465
-9,480,1391.366699,1987.315308,0.773489
-9,490,1515.233398,2164.328613,0.635572
-9,500,1451.817871,2073.680420,0.765210
-9,510,1393.101074,1989.848267,0.645330
-9,520,1405.316650,2007.237305,0.789075
-9,530,1501.060059,2144.041748,0.726779
-9,540,1456.802124,2080.785156,0.803580
-9,550,1371.501953,1958.997925,0.636126
-9,560,1441.037842,2058.332275,0.639216
-9,570,1420.322510,2028.686279,0.764217
-9,580,1323.927979,1890.976318,0.769253
-9,590,1389.106934,1984.095581,0.755964
+epoch,step,loss,loss_cont,loss_disc,loss_quantile
+0,0,11527.750000,16467.474609,1.724242,0.113109
+0,10,8955.048828,12792.469727,1.065955,0.142707
+0,20,123049.507812,175784.562500,1.048191,0.181546
+0,30,30947.671875,44210.511719,1.034107,0.224363
+0,40,11166.339844,15951.691406,0.512211,0.163978
+0,50,14919.276367,21313.089844,0.369016,0.101041
+1,0,1113425.000000,1590606.875000,0.667305,0.236102
+1,10,38804.527344,55433.980469,2.453400,0.238323
+1,20,138075.984375,197251.281250,0.288013,0.157941
+1,30,56904.078125,81291.343750,0.429261,0.174654
+1,40,10662.019531,15231.303711,0.343701,0.079876
+1,50,9890.013672,14128.458008,0.292848,0.088391
+2,0,912398.500000,1303426.125000,0.795286,0.256503
+2,10,12546.185547,17922.542969,1.328752,0.110444
+2,20,109676.710938,156680.906250,0.245523,0.132549
+2,30,49427.507812,70610.578125,0.327188,0.088591
+2,40,27778.673828,39683.660156,0.345683,0.102361
+2,50,10311.509766,14730.566406,0.350199,0.091674
+3,0,1040308.062500,1486154.000000,0.807157,0.279805
+3,10,64799.246094,92570.117188,0.485949,0.198213
+3,20,336018.000000,480025.531250,0.410466,0.118048
+3,30,94216.312500,134594.562500,0.355044,0.114209
+3,40,19988.919922,28555.457031,0.298066,0.094291
+3,50,9181.969727,13116.940430,0.326489,0.137392
+4,0,741176.187500,1058822.750000,0.850633,0.233118
+4,10,39252.617188,56074.410156,1.690607,0.227370
+4,20,108992.304688,155703.140625,0.258920,0.285944
+4,30,37115.253906,53021.632812,0.337674,0.131537
+4,40,19358.708984,27655.123047,0.349937,0.169446
+4,50,11434.291992,16334.540039,0.351904,0.089116
+5,0,845658.312500,1208083.000000,0.922483,0.285983
+5,10,130569.406250,186527.515625,0.405198,0.227639
+5,20,245780.390625,351114.687500,0.301236,0.147030
+5,30,42017.671875,60025.066406,0.372036,0.117895
+5,40,11496.740234,16423.779297,0.286911,0.085701
+5,50,8891.728516,12702.317383,0.322913,0.099181
+6,0,617909.687500,882727.812500,0.834663,0.205251
+6,10,18171.734375,25959.302734,0.677465,0.190570
+6,20,423716.187500,605308.687500,0.464189,0.156125
+6,30,48133.507812,68761.914062,0.478786,0.221465
+6,40,20350.281250,29071.666016,0.343182,0.118739
+6,50,11372.219727,16245.889648,0.289177,0.101218
+7,0,534133.500000,763047.500000,0.732465,0.239962
+7,10,19025.574219,27178.703125,1.551094,0.183023
+7,20,58042.757812,82918.078125,0.298854,0.146532
+7,30,11810.656250,16872.201172,0.353035,0.092791
+7,40,9733.656250,13905.077148,0.312043,0.089972
+7,50,9069.159180,12955.803711,0.280795,0.129749
+8,0,650366.937500,929095.250000,0.787194,0.263791
+8,10,13121.248047,18744.031250,1.376233,0.141053
+8,20,19326.507812,27609.167969,0.243424,0.183426
+8,30,12904.376953,18434.667969,0.334577,0.092547
+8,40,9682.833984,13832.478516,0.296229,0.109518
+8,50,8866.144531,12665.773438,0.312481,0.099564
+9,0,265689.562500,379556.156250,0.738840,0.186122
+9,10,9944.607422,14206.222656,0.806142,0.096763
+9,20,22091.175781,31558.679688,0.285403,0.131950
+9,30,19346.830078,27638.111328,0.460825,0.131496
+9,40,10279.702148,14685.139648,0.314872,0.095758
+9,50,10420.340820,14886.050781,0.314008,0.112904

example/run_all.py

@@ -20,18 +20,14 @@ def run(cmd):
 
 
 def parse_args():
-    parser = argparse.ArgumentParser(description="Run full pipeline end-to-end.")
+    parser = argparse.ArgumentParser(description="Run prepare -> train -> export -> evaluate.")
     base_dir = Path(__file__).resolve().parent
     parser.add_argument("--config", default=str(base_dir / "config.json"))
     parser.add_argument("--device", default="auto", help="cpu, cuda, or auto")
-    parser.add_argument("--reference", default="", help="override reference glob (train*.csv.gz)")
     parser.add_argument("--skip-prepare", action="store_true")
     parser.add_argument("--skip-train", action="store_true")
     parser.add_argument("--skip-export", action="store_true")
     parser.add_argument("--skip-eval", action="store_true")
-    parser.add_argument("--skip-postprocess", action="store_true")
-    parser.add_argument("--skip-post-eval", action="store_true")
-    parser.add_argument("--skip-diagnostics", action="store_true")
     return parser.parse_args()
 
 
@@ -42,17 +38,7 @@ def main():
     with open(config_path, "r", encoding="utf-8") as f:
         cfg = json.load(f)
 
-    # Resolve config path without duplicating base_dir on Windows when user passes example/config.json
-    if config_path.is_absolute():
-        config_path = resolve_path(config_path.parent, config_path)
-    else:
-        candidate = base_dir / config_path
-        if candidate.exists():
-            config_path = resolve_path(candidate.parent, candidate)
-        elif config_path.exists():
-            config_path = resolve_path(config_path.parent, config_path)
-        else:
-            config_path = resolve_path(base_dir, config_path)
+    config_path = resolve_path(base_dir, config_path)
     timesteps = cfg.get("timesteps", 200)
     seq_len = cfg.get("sample_seq_len", cfg.get("seq_len", 64))
     batch_size = cfg.get("sample_batch_size", cfg.get("batch_size", 2))
@@ -83,51 +69,14 @@ def main():
                 "--use-ema",
             ]
         )
-    ref = args.reference or cfg.get("data_glob") or cfg.get("data_path") or ""
     if not args.skip_eval:
+        ref = cfg.get("data_glob") or cfg.get("data_path") or ""
         if ref:
             run([sys.executable, str(base_dir / "evaluate_generated.py"), "--reference", str(ref)])
         else:
             run([sys.executable, str(base_dir / "evaluate_generated.py")])
         run([sys.executable, str(base_dir / "summary_metrics.py")])
 
-    if not args.skip_postprocess:
-        cmd = [
-            sys.executable,
-            str(base_dir / "postprocess_types.py"),
-            "--generated",
-            str(base_dir / "results" / "generated.csv"),
-            "--config",
-            str(config_path),
-        ]
-        if ref:
-            cmd += ["--reference", str(ref)]
-        run(cmd)
-
-    if not args.skip_post_eval:
-        cmd = [
-            sys.executable,
-            str(base_dir / "evaluate_generated.py"),
-            "--generated",
-            str(base_dir / "results" / "generated_post.csv"),
-            "--out",
-            "results/eval_post.json",
-        ]
-        if ref:
-            cmd += ["--reference", str(ref)]
-        run(cmd)
-
-    if not args.skip_diagnostics:
-        if ref:
-            run([sys.executable, str(base_dir / "diagnose_ks.py"), "--generated", str(base_dir / "results" / "generated_post.csv"), "--reference", str(ref)])
-        run([sys.executable, str(base_dir / "filtered_metrics.py"), "--eval", str(base_dir / "results" / "eval_post.json")])
-        run([sys.executable, str(base_dir / "ranked_ks.py"), "--eval", str(base_dir / "results" / "eval_post.json")])
-        run([sys.executable, str(base_dir / "program_stats.py"), "--config", str(config_path), "--reference", str(ref or config_path)])
-        run([sys.executable, str(base_dir / "controller_stats.py"), "--config", str(config_path), "--reference", str(ref or config_path)])
-        run([sys.executable, str(base_dir / "actuator_stats.py"), "--config", str(config_path), "--reference", str(ref or config_path)])
-        run([sys.executable, str(base_dir / "pv_stats.py"), "--config", str(config_path), "--reference", str(ref or config_path)])
-        run([sys.executable, str(base_dir / "aux_stats.py"), "--config", str(config_path), "--reference", str(ref or config_path)])
-
 
 if __name__ == "__main__":
     main()

example/run_all_full.py

@@ -1,183 +0,0 @@
-#!/usr/bin/env python3
-"""Run full pipeline + diagnostics in one command."""
-
-import argparse
-import json
-import subprocess
-import sys
-from pathlib import Path
-
-from platform_utils import safe_path, is_windows, resolve_path
-
-
-def run(cmd):
-    print("running:", " ".join(cmd))
-    cmd = [safe_path(arg) for arg in cmd]
-    if is_windows():
-        subprocess.run(cmd, check=True, shell=False)
-    else:
-        subprocess.run(cmd, check=True)
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(description="Run prepare -> train -> export -> eval -> diagnostics.")
-    base_dir = Path(__file__).resolve().parent
-    parser.add_argument("--config", default=str(base_dir / "config.json"))
-    parser.add_argument("--device", default="auto", help="cpu, cuda, or auto")
-    parser.add_argument("--skip-prepare", action="store_true")
-    parser.add_argument("--skip-train", action="store_true")
-    parser.add_argument("--skip-export", action="store_true")
-    parser.add_argument("--skip-eval", action="store_true")
-    parser.add_argument("--skip-diagnose", action="store_true")
-    return parser.parse_args()
-
-
-def resolve_config(base_dir: Path, cfg_arg: str) -> Path:
-    config_path = Path(cfg_arg)
-    if config_path.is_absolute():
-        return Path(resolve_path(config_path.parent, config_path))
-    candidate = base_dir / config_path
-    if candidate.exists():
-        return Path(resolve_path(candidate.parent, candidate))
-    if config_path.exists():
-        return Path(resolve_path(config_path.parent, config_path))
-    return Path(resolve_path(base_dir, config_path))
-
-
-def main():
-    args = parse_args()
-    base_dir = Path(__file__).resolve().parent
-    config_path = resolve_config(base_dir, args.config)
-    with open(config_path, "r", encoding="utf-8") as f:
-        cfg = json.load(f)
-
-    timesteps = cfg.get("timesteps", 200)
-    seq_len = cfg.get("sample_seq_len", cfg.get("seq_len", 64))
-    batch_size = cfg.get("sample_batch_size", cfg.get("batch_size", 2))
-    clip_k = cfg.get("clip_k", 5.0)
-
-    if not args.skip_prepare:
-        run([sys.executable, str(base_dir / "prepare_data.py")])
-    if not args.skip_train:
-        run([sys.executable, str(base_dir / "train.py"), "--config", str(config_path), "--device", args.device])
-    if not args.skip_export:
-        run(
-            [
-                sys.executable,
-                str(base_dir / "export_samples.py"),
-                "--include-time",
-                "--device",
-                args.device,
-                "--config",
-                str(config_path),
-                "--timesteps",
-                str(timesteps),
-                "--seq-len",
-                str(seq_len),
-                "--batch-size",
-                str(batch_size),
-                "--clip-k",
-                str(clip_k),
-                "--use-ema",
-            ]
-        )
-    if not args.skip_eval:
-        ref = cfg.get("data_glob") or cfg.get("data_path") or ""
-        if ref:
-            run([sys.executable, str(base_dir / "evaluate_generated.py"), "--reference", str(ref)])
-        else:
-            run([sys.executable, str(base_dir / "evaluate_generated.py")])
-        run([sys.executable, str(base_dir / "summary_metrics.py")])
-        run([sys.executable, str(base_dir / "filtered_metrics.py")])
-        run([sys.executable, str(base_dir / "ranked_ks.py")])
-    if not args.skip_diagnose:
-        run(
-            [
-                sys.executable,
-                str(base_dir / "diagnose_ks.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--top-k",
-                "10",
-            ]
-        )
-        run(
-            [
-                sys.executable,
-                str(base_dir / "program_stats.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--config",
-                str(config_path),
-            ]
-        )
-        run(
-            [
-                sys.executable,
-                str(base_dir / "controller_stats.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--config",
-                str(config_path),
-            ]
-        )
-        run(
-            [
-                sys.executable,
-                str(base_dir / "actuator_stats.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--config",
-                str(config_path),
-            ]
-        )
-        run(
-            [
-                sys.executable,
-                str(base_dir / "pv_stats.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--config",
-                str(config_path),
-            ]
-        )
-        run(
-            [
-                sys.executable,
-                str(base_dir / "aux_stats.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--config",
-                str(config_path),
-            ]
-        )
-        run(
-            [
-                sys.executable,
-                str(base_dir / "postprocess_types.py"),
-                "--generated",
-                str(base_dir / "results" / "generated.csv"),
-                "--reference",
-                str(config_path),
-                "--config",
-                str(config_path),
-                "--out",
-                str(base_dir / "results" / "generated_post.csv"),
-            ]
-        )
-
-
-if __name__ == "__main__":
-    main()

example/run_compare.py

@@ -1,58 +0,0 @@
-#!/usr/bin/env python3
-"""Run two configs sequentially and print metric deltas."""
-
-import argparse
-import csv
-import subprocess
-import sys
-from pathlib import Path
-
-
-def run(cmd):
-    print("running:", " ".join(cmd))
-    subprocess.run(cmd, check=True)
-
-
-def read_last_metrics(path: Path):
-    if not path.exists():
-        return None
-    rows = list(csv.DictReader(path.open()))
-    return rows[-1] if rows else None
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Compare metrics for two configs.")
-    base_dir = Path(__file__).resolve().parent
-    parser.add_argument("--config-a", default=str(base_dir / "config_no_temporal.json"))
-    parser.add_argument("--config-b", default=str(base_dir / "config_temporal_strong.json"))
-    parser.add_argument("--device", default="auto")
-    args = parser.parse_args()
-
-    history = base_dir / "results" / "metrics_history.csv"
-    if history.exists():
-        history.unlink()
-
-    run([sys.executable, str(base_dir / "run_all.py"), "--config", args.config_a, "--device", args.device])
-    a = read_last_metrics(history)
-    run([sys.executable, str(base_dir / "run_all.py"), "--config", args.config_b, "--device", args.device])
-    b = read_last_metrics(history)
-
-    if not a or not b:
-        raise SystemExit("missing metrics_history.csv entries")
-
-    def f(v):
-        return float(v) if v is not None else None
-
-    print("baseline_avg_ks", a["avg_ks"])
-    print("temporal_avg_ks", b["avg_ks"])
-    print("delta_avg_ks", f(b["avg_ks"]) - f(a["avg_ks"]))
-    print("baseline_avg_jsd", a["avg_jsd"])
-    print("temporal_avg_jsd", b["avg_jsd"])
-    print("delta_avg_jsd", f(b["avg_jsd"]) - f(a["avg_jsd"]))
-    print("baseline_avg_lag1_diff", a["avg_lag1_diff"])
-    print("temporal_avg_lag1_diff", b["avg_lag1_diff"])
-    print("delta_avg_lag1_diff", f(b["avg_lag1_diff"]) - f(a["avg_lag1_diff"]))
-
-
-if __name__ == "__main__":
-    main()

example/sample.py

@@ -10,7 +10,8 @@ import torch
 import torch.nn.functional as F
 
 from data_utils import load_split
-from hybrid_diffusion import HybridDiffusionModel, TemporalGRUGenerator, cosine_beta_schedule
+from hybrid_diffusion import HybridDiffusionModel, cosine_beta_schedule
+from hybrid_diffusion import TemporalGRUGenerator
 from platform_utils import resolve_device, safe_path, ensure_dir
 
 BASE_DIR = Path(__file__).resolve().parent
@@ -47,10 +48,6 @@ def main():
     cond_dim = int(cfg.get("cond_dim", 32))
     use_tanh_eps = bool(cfg.get("use_tanh_eps", False))
     eps_scale = float(cfg.get("eps_scale", 1.0))
-    use_temporal_stage1 = bool(cfg.get("use_temporal_stage1", False))
-    temporal_hidden_dim = int(cfg.get("temporal_hidden_dim", 256))
-    temporal_num_layers = int(cfg.get("temporal_num_layers", 1))
-    temporal_dropout = float(cfg.get("temporal_dropout", 0.0))
     cont_target = str(cfg.get("cont_target", "eps"))
     cont_clamp_x0 = float(cfg.get("cont_clamp_x0", 0.0))
     model_time_dim = int(cfg.get("model_time_dim", 64))
@@ -60,11 +57,13 @@ def main():
     model_ff_mult = int(cfg.get("model_ff_mult", 2))
     model_pos_dim = int(cfg.get("model_pos_dim", 64))
     model_use_pos = bool(cfg.get("model_use_pos_embed", True))
-    backbone_type = str(cfg.get("backbone_type", "gru"))
-    transformer_num_layers = int(cfg.get("transformer_num_layers", 2))
-    transformer_nhead = int(cfg.get("transformer_nhead", 4))
-    transformer_ff_dim = int(cfg.get("transformer_ff_dim", 512))
-    transformer_dropout = float(cfg.get("transformer_dropout", 0.1))
+    model_use_feature_graph = bool(cfg.get("model_use_feature_graph", False))
+    feature_graph_scale = float(cfg.get("feature_graph_scale", 0.1))
+    feature_graph_dropout = float(cfg.get("feature_graph_dropout", 0.0))
+    use_temporal_stage1 = bool(cfg.get("use_temporal_stage1", False))
+    temporal_hidden_dim = int(cfg.get("temporal_hidden_dim", 256))
+    temporal_num_layers = int(cfg.get("temporal_num_layers", 1))
+    temporal_dropout = float(cfg.get("temporal_dropout", 0.0))
 
     split = load_split(str(SPLIT_PATH))
     time_col = split.get("time_column", "time")
@@ -92,11 +91,9 @@ def main():
         ff_mult=model_ff_mult,
         pos_dim=model_pos_dim,
         use_pos_embed=model_use_pos,
-        backbone_type=backbone_type,
-        transformer_num_layers=transformer_num_layers,
-        transformer_nhead=transformer_nhead,
-        transformer_ff_dim=transformer_ff_dim,
-        transformer_dropout=transformer_dropout,
+        use_feature_graph=model_use_feature_graph,
+        feature_graph_scale=feature_graph_scale,
+        feature_graph_dropout=feature_graph_dropout,
         cond_vocab_size=cond_vocab_size,
         cond_dim=cond_dim,
         use_tanh_eps=use_tanh_eps,
@@ -146,15 +143,18 @@ def main():
         t_batch = torch.full((batch_size,), t, device=DEVICE, dtype=torch.long)
         eps_pred, logits = model(x_cont, x_disc, t_batch, cond)
 
+        # Continuous reverse step (DDPM): x_{t-1} mean
+        a_t = alphas[t]
+        a_bar_t = alphas_cumprod[t]
         if cont_target == "x0":
             x0_pred = eps_pred
             if cont_clamp_x0 > 0:
                 x0_pred = torch.clamp(x0_pred, -cont_clamp_x0, cont_clamp_x0)
             eps_pred = (x_cont - torch.sqrt(a_bar_t) * x0_pred) / torch.sqrt(1.0 - a_bar_t)
-
-        # Continuous reverse step (DDPM): x_{t-1} mean
-        a_t = alphas[t]
-        a_bar_t = alphas_cumprod[t]
+        elif cont_target == "v":
+            v_pred = eps_pred
+            x0_pred = torch.sqrt(a_bar_t) * x_cont - torch.sqrt(1.0 - a_bar_t) * v_pred
+            eps_pred = torch.sqrt(1.0 - a_bar_t) * x_cont + torch.sqrt(a_bar_t) * v_pred
         coef1 = 1.0 / torch.sqrt(a_t)
         coef2 = (1 - a_t) / torch.sqrt(1 - a_bar_t)
         mean = coef1 * (x_cont - coef2 * eps_pred)

example/summary_metrics.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Print average metrics from eval.json and compare with previous run."""
+"""Print average metrics from eval.json for quick tracking."""
 
 import json
 from datetime import datetime
@@ -10,27 +10,6 @@ def mean(values):
     return sum(values) / len(values) if values else None
 
 
-def parse_last_row(history_path: Path):
-    if not history_path.exists():
-        return None
-    rows = history_path.read_text(encoding="utf-8").strip().splitlines()
-    if len(rows) < 2:
-        return None
-    for line in reversed(rows[1:]):
-        parts = line.split(",")
-        if len(parts) < 4:
-            continue
-        try:
-            return {
-                "avg_ks": float(parts[1]),
-                "avg_jsd": float(parts[2]),
-                "avg_lag1_diff": float(parts[3]),
-            }
-        except Exception:
-            continue
-    return None
-
-
 def main():
     base_dir = Path(__file__).resolve().parent
     eval_path = base_dir / "results" / "eval.json"
@@ -46,23 +25,16 @@ def main():
     avg_jsd = mean(jsd)
     avg_lag1 = mean(lag)
 
-    history_path = base_dir / "results" / "metrics_history.csv"
-    prev = parse_last_row(history_path)
+    print("avg_ks", avg_ks)
+    print("avg_jsd", avg_jsd)
+    print("avg_lag1_diff", avg_lag1)
 
+    history_path = base_dir / "results" / "metrics_history.csv"
     if not history_path.exists():
         history_path.write_text("timestamp,avg_ks,avg_jsd,avg_lag1_diff\n", encoding="utf-8")
     with history_path.open("a", encoding="utf-8") as f:
         f.write(f"{datetime.utcnow().isoformat()},{avg_ks},{avg_jsd},{avg_lag1}\n")
 
-    print("avg_ks", avg_ks)
-    print("avg_jsd", avg_jsd)
-    print("avg_lag1_diff", avg_lag1)
-
-    if prev is not None:
-        print("delta_avg_ks", avg_ks - prev["avg_ks"])
-        print("delta_avg_jsd", avg_jsd - prev["avg_jsd"])
-        print("delta_avg_lag1_diff", avg_lag1 - prev["avg_lag1_diff"])
-
 
 if __name__ == "__main__":
     main()

example/train.py

@@ -59,23 +59,25 @@ DEFAULTS = {
     "model_ff_mult": 2,
     "model_pos_dim": 64,
     "model_use_pos_embed": True,
-    "disc_mask_scale": 0.9,
-    "shuffle_buffer": 256,
-    "cont_loss_weighting": "none",  # none | inv_std
-    "cont_loss_eps": 1e-6,
-    "cont_target": "eps",  # eps | x0
-    "cont_clamp_x0": 0.0,
+    "model_use_feature_graph": True,
+    "feature_graph_scale": 0.1,
+    "feature_graph_dropout": 0.0,
     "use_temporal_stage1": True,
     "temporal_hidden_dim": 256,
     "temporal_num_layers": 1,
     "temporal_dropout": 0.0,
-    "temporal_epochs": 2,
-    "temporal_lr": 1e-3,
+    "temporal_loss_weight": 1.0,
+    "disc_mask_scale": 0.9,
+    "shuffle_buffer": 256,
+    "cont_loss_weighting": "none",  # none | inv_std
+    "cont_loss_eps": 1e-6,
+    "cont_target": "eps",  # eps | x0 | v
+    "cont_clamp_x0": 0.0,
     "quantile_loss_weight": 0.0,
     "quantile_points": [0.05, 0.25, 0.5, 0.75, 0.95],
-    "snr_weighted_loss": True,
-    "snr_gamma": 1.0,
-    "residual_stat_weight": 0.0,
+    "quantile_loss_warmup_steps": 200,
+    "quantile_loss_clip": 6.0,
+    "quantile_loss_huber_delta": 1.0,
 }
 
 
@@ -168,22 +170,11 @@ def main():
     cont_cols = [c for c in split["continuous"] if c != time_col]
     disc_cols = [c for c in split["discrete"] if not c.startswith("attack") and c != time_col]
 
-    type1_cols = config.get("type1_features", []) or []
-    type5_cols = config.get("type5_features", []) or []
-    type1_cols = [c for c in type1_cols if c in cont_cols]
-    type5_cols = [c for c in type5_cols if c in cont_cols]
-    model_cont_cols = [c for c in cont_cols if c not in type1_cols and c not in type5_cols]
-    if not model_cont_cols:
-        raise SystemExit("model_cont_cols is empty; check type1/type5 config")
-
     stats = load_json(config["stats_path"])
     mean = stats["mean"]
     std = stats["std"]
     transforms = stats.get("transform", {})
     raw_std = stats.get("raw_std", std)
-    quantile_probs = stats.get("quantile_probs")
-    quantile_values = stats.get("quantile_values")
-    use_quantile = bool(config.get("use_quantile_transform", False))
 
     vocab = load_json(config["vocab_path"])["vocab"]
     vocab_sizes = [len(vocab[c]) for c in disc_cols]
@@ -202,7 +193,7 @@ def main():
     device = resolve_device(str(config["device"]))
     print("device", device)
     model = HybridDiffusionModel(
-        cont_dim=len(model_cont_cols),
+        cont_dim=len(cont_cols),
         disc_vocab_sizes=vocab_sizes,
         time_dim=int(config.get("model_time_dim", 64)),
         hidden_dim=int(config.get("model_hidden_dim", 256)),
@@ -211,31 +202,27 @@ def main():
         ff_mult=int(config.get("model_ff_mult", 2)),
         pos_dim=int(config.get("model_pos_dim", 64)),
         use_pos_embed=bool(config.get("model_use_pos_embed", True)),
-        backbone_type=str(config.get("backbone_type", "gru")),
-        transformer_num_layers=int(config.get("transformer_num_layers", 4)),
-        transformer_nhead=int(config.get("transformer_nhead", 8)),
-        transformer_ff_dim=int(config.get("transformer_ff_dim", 2048)),
-        transformer_dropout=float(config.get("transformer_dropout", 0.1)),
-        cond_cont_dim=len(type1_cols),
+        use_feature_graph=bool(config.get("model_use_feature_graph", False)),
+        feature_graph_scale=float(config.get("feature_graph_scale", 0.1)),
+        feature_graph_dropout=float(config.get("feature_graph_dropout", 0.0)),
         cond_vocab_size=cond_vocab_size,
         cond_dim=int(config.get("cond_dim", 32)),
         use_tanh_eps=bool(config.get("use_tanh_eps", False)),
         eps_scale=float(config.get("eps_scale", 1.0)),
     ).to(device)
-    opt = torch.optim.Adam(model.parameters(), lr=float(config["lr"]))
     temporal_model = None
-    opt_temporal = None
     if bool(config.get("use_temporal_stage1", False)):
         temporal_model = TemporalGRUGenerator(
-            input_dim=len(model_cont_cols),
+            input_dim=len(cont_cols),
             hidden_dim=int(config.get("temporal_hidden_dim", 256)),
             num_layers=int(config.get("temporal_num_layers", 1)),
             dropout=float(config.get("temporal_dropout", 0.0)),
         ).to(device)
-        opt_temporal = torch.optim.Adam(
-            temporal_model.parameters(),
-            lr=float(config.get("temporal_lr", config["lr"])),
-        )
+    opt = torch.optim.Adam(model.parameters(), lr=float(config["lr"]))
+    if temporal_model is not None:
+        opt_temporal = torch.optim.Adam(temporal_model.parameters(), lr=float(config["lr"]))
+    else:
+        opt_temporal = None
     ema = EMA(model, float(config["ema_decay"])) if config.get("use_ema") else None
 
     betas = cosine_beta_schedule(int(config["timesteps"])).to(device)
@@ -245,47 +232,15 @@ def main():
     os.makedirs(config["out_dir"], exist_ok=True)
     out_dir = safe_path(config["out_dir"])
     log_path = os.path.join(out_dir, "train_log.csv")
+    use_quantile = float(config.get("quantile_loss_weight", 0.0)) > 0
     with open(log_path, "w", encoding="utf-8") as f:
-        f.write("epoch,step,loss,loss_cont,loss_disc\n")
+        if use_quantile:
+            f.write("epoch,step,loss,loss_cont,loss_disc,loss_quantile\n")
+        else:
+            f.write("epoch,step,loss,loss_cont,loss_disc\n")
     with open(os.path.join(out_dir, "config_used.json"), "w", encoding="utf-8") as f:
         json.dump(config, f, indent=2)
 
-    if temporal_model is not None and opt_temporal is not None:
-        for epoch in range(int(config.get("temporal_epochs", 1))):
-            for step, batch in enumerate(
-                windowed_batches(
-                    data_paths,
-                    cont_cols,
-                    disc_cols,
-                    vocab,
-                    mean,
-                    std,
-                    batch_size=int(config["batch_size"]),
-                    seq_len=int(config["seq_len"]),
-                    max_batches=int(config["max_batches"]),
-                    return_file_id=False,
-                    transforms=transforms,
-                    quantile_probs=quantile_probs,
-                    quantile_values=quantile_values,
-                    use_quantile=use_quantile,
-                    shuffle_buffer=int(config.get("shuffle_buffer", 0)),
-                )
-            ):
-                x_cont, _ = batch
-                x_cont = x_cont.to(device)
-                model_idx = [cont_cols.index(c) for c in model_cont_cols]
-                x_cont_model = x_cont[:, :, model_idx]
-                trend, pred_next = temporal_model.forward_teacher(x_cont_model)
-                temporal_loss = F.mse_loss(pred_next, x_cont_model[:, 1:, :])
-                opt_temporal.zero_grad()
-                temporal_loss.backward()
-                if float(config.get("grad_clip", 0.0)) > 0:
-                    torch.nn.utils.clip_grad_norm_(temporal_model.parameters(), float(config["grad_clip"]))
-                opt_temporal.step()
-                if step % int(config["log_every"]) == 0:
-                    print("temporal_epoch", epoch, "step", step, "loss", float(temporal_loss))
-        torch.save(temporal_model.state_dict(), os.path.join(out_dir, "temporal.pt"))
-
     total_step = 0
     for epoch in range(int(config["epochs"])):
         for step, batch in enumerate(
@@ -301,9 +256,6 @@ def main():
                 max_batches=int(config["max_batches"]),
                 return_file_id=use_condition,
                 transforms=transforms,
-                quantile_probs=quantile_probs,
-                quantile_values=quantile_values,
-                use_quantile=use_quantile,
                 shuffle_buffer=int(config.get("shuffle_buffer", 0)),
             )
         ):
@@ -316,17 +268,15 @@ def main():
             x_cont = x_cont.to(device)
             x_disc = x_disc.to(device)
 
-            model_idx = [cont_cols.index(c) for c in model_cont_cols]
-            cond_idx = [cont_cols.index(c) for c in type1_cols] if type1_cols else []
-            x_cont_model = x_cont[:, :, model_idx]
-            cond_cont = x_cont[:, :, cond_idx] if cond_idx else None
-
+            temporal_loss = None
+            x_cont_resid = x_cont
             trend = None
             if temporal_model is not None:
-                temporal_model.eval()
-                with torch.no_grad():
-                    trend, _ = temporal_model.forward_teacher(x_cont_model)
-            x_cont_resid = x_cont_model if trend is None else x_cont_model - trend
+                trend, pred_next = temporal_model.forward_teacher(x_cont)
+                temporal_loss = F.mse_loss(pred_next, x_cont[:, 1:, :])
+                temporal_loss = temporal_loss * float(config.get("temporal_loss_weight", 1.0))
+                trend = trend.detach()
+                x_cont_resid = x_cont - trend
 
             bsz = x_cont.size(0)
             t = torch.randint(0, int(config["timesteps"]), (bsz,), device=device)
@@ -342,7 +292,7 @@ def main():
                 mask_scale=float(config.get("disc_mask_scale", 1.0)),
             )
 
-            eps_pred, logits = model(x_cont_t, x_disc_t, t, cond, cond_cont=cond_cont)
+            eps_pred, logits = model(x_cont_t, x_disc_t, t, cond)
 
             cont_target = str(config.get("cont_target", "eps"))
             if cont_target == "x0":
@@ -350,25 +300,22 @@ def main():
                 if float(config.get("cont_clamp_x0", 0.0)) > 0:
                     x0_target = torch.clamp(x0_target, -float(config["cont_clamp_x0"]), float(config["cont_clamp_x0"]))
                 loss_base = (eps_pred - x0_target) ** 2
+            elif cont_target == "v":
+                a_bar_t = alphas_cumprod[t].view(-1, 1, 1)
+                v_target = torch.sqrt(a_bar_t) * noise - torch.sqrt(1.0 - a_bar_t) * x_cont_resid
+                loss_base = (eps_pred - v_target) ** 2
             else:
                 loss_base = (eps_pred - noise) ** 2
 
             if config.get("cont_loss_weighting") == "inv_std":
                 weights = torch.tensor(
-                    [1.0 / (float(raw_std[c]) ** 2 + float(config.get("cont_loss_eps", 1e-6))) for c in model_cont_cols],
+                    [1.0 / (float(raw_std[c]) ** 2 + float(config.get("cont_loss_eps", 1e-6))) for c in cont_cols],
                     device=device,
                     dtype=eps_pred.dtype,
                 ).view(1, 1, -1)
                 loss_cont = (loss_base * weights).mean()
             else:
                 loss_cont = loss_base.mean()
-
-            if bool(config.get("snr_weighted_loss", False)):
-                a_bar_t = alphas_cumprod[t].view(-1, 1, 1)
-                snr = a_bar_t / torch.clamp(1.0 - a_bar_t, min=1e-8)
-                gamma = float(config.get("snr_gamma", 1.0))
-                snr_weight = snr / (snr + gamma)
-                loss_cont = (loss_cont * snr_weight.mean()).mean()
             loss_disc = 0.0
             loss_disc_count = 0
             for i, logit in enumerate(logits):
@@ -384,53 +331,74 @@ def main():
             loss = lam * loss_cont + (1 - lam) * loss_disc
 
             q_weight = float(config.get("quantile_loss_weight", 0.0))
+            quantile_loss = 0.0
             if q_weight > 0:
+                warmup = int(config.get("quantile_loss_warmup_steps", 0))
+                if warmup > 0:
+                    q_weight = q_weight * min(1.0, (total_step + 1) / float(warmup))
                 q_points = config.get("quantile_points", [0.05, 0.25, 0.5, 0.75, 0.95])
                 q_tensor = torch.tensor(q_points, device=device, dtype=x_cont.dtype)
-                a_bar_t = alphas_cumprod[t].view(-1, 1, 1)
-                # Quantile loss on residual distribution
+                # Use normalized space for stable quantiles on x0.
                 x_real = x_cont_resid
+                a_bar_t = alphas_cumprod[t].view(-1, 1, 1)
                 if cont_target == "x0":
                     x_gen = eps_pred
+                elif cont_target == "v":
+                    v_pred = eps_pred
+                    x_gen = torch.sqrt(a_bar_t) * x_cont_t - torch.sqrt(1.0 - a_bar_t) * v_pred
                 else:
+                    # eps prediction
                     x_gen = (x_cont_t - torch.sqrt(1.0 - a_bar_t) * eps_pred) / torch.sqrt(a_bar_t)
+                q_clip = float(config.get("quantile_loss_clip", 0.0))
+                if q_clip > 0:
+                    x_real = torch.clamp(x_real, -q_clip, q_clip)
+                    x_gen = torch.clamp(x_gen, -q_clip, q_clip)
                 x_real = x_real.view(-1, x_real.size(-1))
                 x_gen = x_gen.view(-1, x_gen.size(-1))
                 q_real = torch.quantile(x_real, q_tensor, dim=0)
                 q_gen = torch.quantile(x_gen, q_tensor, dim=0)
-                quantile_loss = torch.mean(torch.abs(q_gen - q_real))
+                q_delta = float(config.get("quantile_loss_huber_delta", 0.0))
+                q_diff = q_gen - q_real
+                if q_delta > 0:
+                    quantile_loss = torch.nn.functional.smooth_l1_loss(q_gen, q_real, beta=q_delta)
+                else:
+                    quantile_loss = torch.mean(torch.abs(q_diff))
                 loss = loss + q_weight * quantile_loss
 
-            stat_weight = float(config.get("residual_stat_weight", 0.0))
-            if stat_weight > 0:
-                # residual distribution matching (mean/std)
-                a_bar_t = alphas_cumprod[t].view(-1, 1, 1)
-                if cont_target == "x0":
-                    x_gen = eps_pred
-                else:
-                    x_gen = (x_cont_t - torch.sqrt(1.0 - a_bar_t) * eps_pred) / torch.sqrt(a_bar_t)
-                x_real = x_cont_resid
-                mean_real = x_real.mean(dim=(0, 1))
-                mean_gen = x_gen.mean(dim=(0, 1))
-                std_real = x_real.std(dim=(0, 1))
-                std_gen = x_gen.std(dim=(0, 1))
-                stat_loss = F.mse_loss(mean_gen, mean_real) + F.mse_loss(std_gen, std_real)
-                loss = loss + stat_weight * stat_loss
             opt.zero_grad()
             loss.backward()
             if float(config.get("grad_clip", 0.0)) > 0:
                 torch.nn.utils.clip_grad_norm_(model.parameters(), float(config["grad_clip"]))
             opt.step()
+            if opt_temporal is not None:
+                opt_temporal.zero_grad()
+                temporal_loss.backward()
+                if float(config.get("grad_clip", 0.0)) > 0:
+                    torch.nn.utils.clip_grad_norm_(temporal_model.parameters(), float(config["grad_clip"]))
+                opt_temporal.step()
             if ema is not None:
                 ema.update(model)
 
             if step % int(config["log_every"]) == 0:
                 print("epoch", epoch, "step", step, "loss", float(loss))
                 with open(log_path, "a", encoding="utf-8") as f:
-                    f.write(
-                        "%d,%d,%.6f,%.6f,%.6f\n"
-                        % (epoch, step, float(loss), float(loss_cont), float(loss_disc))
-                    )
+                    if use_quantile:
+                        f.write(
+                            "%d,%d,%.6f,%.6f,%.6f,%.6f\n"
+                            % (
+                                epoch,
+                                step,
+                                float(loss),
+                                float(loss_cont),
+                                float(loss_disc),
+                                float(quantile_loss),
+                            )
+                        )
+                    else:
+                        f.write(
+                            "%d,%d,%.6f,%.6f,%.6f\n"
+                            % (epoch, step, float(loss), float(loss_cont), float(loss_disc))
+                        )
 
             total_step += 1
             if total_step % int(config["ckpt_every"]) == 0:

report.md

@@ -1,424 +1,365 @@
-# mask-ddpm 项目说明书（完整详细版）
+# Hybrid Diffusion for ICS Traffic (HAI 21.03) — Project Report
+# 工业控制系统流量混合扩散生成（HAI 21.03）— 项目报告
 
-> 本文档是“说明书级别”的完整描述，面向首次接触项目的同学。
-> 目标是让**不了解扩散/时序建模的人**也能理解：项目是什么、怎么跑、每个文件干什么、每一步在训练什么、为什么这么设计。
->
-> 适用范围：当前仓库代码（以 `example/config.json` 为主配置）。
+## 1. Project Goal / 项目目标
+Build a **hybrid diffusion-based generator** for industrial control system (ICS) traffic features, targeting **mixed continuous + discrete** feature sequences. The output is **feature-level sequences**, not raw packets. The generator should preserve:
+- **Distributional fidelity** (continuous value ranges and discrete frequencies)
+- **Temporal consistency** (time correlation and sequence structure)
+- **Protocol/field consistency** (for discrete fields)
+
+构建一个用于工业控制系统（ICS）流量特征的**混合扩散生成模型**，面向**连续+离散混合特征序列**。输出为**特征级序列**而非原始报文。生成结果需要同时保持：
+- **分布一致性**（连续值范围与离散取值频率）
+- **时序一致性**（时间相关性与序列结构）
+- **字段/协议一致性**（离散字段的逻辑一致）
+
+This project is aligned with the STOUTER idea of **structure-aware diffusion** for spatiotemporal data, but applied to **ICS feature sequences** rather than cellular traffic.
+
+本项目呼应 STOUTER 的**结构先验+扩散**思想，但应用于**ICS 特征序列**而非蜂窝流量。
 
 ---
 
-## 目录
-1. 项目目标与研究问题
-2. 数据与特征结构
-3. 预处理与统计文件
-4. 模型总体架构
-5. 训练流程（逐步骤）
-6. 采样与导出流程
-7. 评估体系与指标
-8. 诊断工具与常用脚本
-9. Type‑aware（按类型分治）设计
-10. 一键运行与常见命令
-11. 输出文件说明
-12. 当前配置与关键超参
-13. 常见问题与慢的原因
-14. 已知限制与后续方向
-15. 文件树（精简版）
-16. 文件职责（逐文件说明）
+## 2. Data and Scope / 数据与范围
+**Dataset used in the current implementation:** HAI 21.03 (CSV feature traces)
+
+**当前实现使用的数据集：** HAI 21.03（CSV 特征序列）
+
+**Data location (default in config):**
+- `dataset/hai/hai-21.03/train*.csv.gz`
+
+**数据位置（config 默认）：**
+- `dataset/hai/hai-21.03/train*.csv.gz`
+
+**Feature split (fixed schema):**
+- Defined in `example/feature_split.json`
+- **Continuous features:** sensor/process values
+- **Discrete features:** binary/low-cardinality status/flag fields
+- `time` column is excluded from modeling
+
+**特征拆分（固定 schema）：**
+- `example/feature_split.json`
+- **连续特征：** 传感器/过程值
+- **离散特征：** 二值/低基数状态字段
+- `time` 列不参与训练
 
 ---
 
-## 1. 项目目标与研究问题
+## 3. End-to-End Pipeline / 端到端流程
 
-本项目目标：生成工业控制系统（ICS）多变量时序数据，满足以下三点：
-
-- **分布一致性**：每个变量的统计分布接近真实（用 KS 衡量）
-- **时序一致性**：序列结构合理，lag‑1 相关性、趋势符合真实
-- **离散合法性**：离散变量（状态/模式）必须是合法 token 且分布合理（JSD）
-
-核心难点：
-- 时序结构和分布对齐经常相互冲突
-- 真实数据包含“程序驱动/事件驱动”的变量，难以用纯 DDPM 学好
-
----
-
-## 2. 数据与特征结构
-
-**数据来源**：HAI `train*.csv.gz`（多文件）
-
-**特征拆分**（见 `example/feature_split.json`）：
-- `continuous`：连续变量（传感器/执行器）
-- `discrete`：离散变量（状态/模式）
-- `time_column`：时间列（不参与训练）
-
----
-
-## 3. 预处理与统计文件
-
-脚本：`example/prepare_data.py`
-
-### 3.1 连续变量
-- 计算 mean/std
-- 若开启 `use_quantile_transform`：计算分位数表（CDF）
-- 输出：`example/results/cont_stats.json`
-
-### 3.2 离散变量
-- 统计 vocab
-- 输出：`example/results/disc_vocab.json`
-
-### 3.3 数据工具
-`example/data_utils.py` 提供：
-- 标准化/反标准化
-- 分位数变换/逆变换
-- 可选后校准（quantile calibration）
-
----
-
-## 4. 模型总体架构
-
-本项目采用 **两阶段 + 混合扩散** 架构：
-
-### 4.1 Stage‑1 Temporal GRU
-- 目的：学习序列趋势、时序结构
-- 输入：连续变量序列
-- 输出：trend（趋势序列）
-
-### 4.2 Stage‑2 Hybrid Diffusion
-- 目的：学习残差分布（把时序和分布解耦）
-- 连续变量：Gaussian DDPM
-- 离散变量：mask diffusion 分类 head
-
-### 4.3 Backbone 选择
-- 当前配置：`backbone_type = transformer`
-- 可选：GRU（更省显存更稳定）
-
----
-
-## 5. 训练流程（逐步骤）
-
-脚本：`example/train.py`
-
-### Step 1：Temporal 训练
-- 输入：连续序列
-- GRU teacher‑forcing 预测下一步
-- Loss：MSE
-- 输出：`temporal.pt`
-
-### Step 2：Diffusion 训练
-- 计算残差：`x_resid = x_cont - trend`
-- 采样时间步 t
-- 连续：加噪
-- 离散：mask token
-- 模型预测 eps / logits
-
-### Loss 设计
-- Continuous：MSE（eps 或 x0）
-- Discrete：Cross Entropy（mask 部分）
-- 总损失：`loss = λ * loss_cont + (1-λ) * loss_disc`
-- 可选加权：
-  - inverse‑std
-  - SNR‑weighted
-  - quantile loss
-  - residual stat loss
-
----
-
-## 6. 采样与导出流程
-
-脚本：`example/export_samples.py`
-
-流程：
-1) 初始化噪声（连续）
-2) 初始化 mask（离散）
-3) 反扩散 t=T..0
-4) 加回 trend
-5) 反变换（quantile/标准化）
-6) 合成 CSV
-
-输出：`example/results/generated.csv`
-
----
-
-## 7. 评估体系与指标
-
-脚本：`example/evaluate_generated.py`
-
-### 连续指标
-- **KS（tie‑aware）**
-- quantile diff
-- lag‑1 correlation
-
-### 离散指标
-- JSD
-- invalid token 比例
-
-### Reference 读取
-- 支持 `train*.csv.gz` glob
-- 自动汇总所有文件
-
----
-
-## 8. 诊断工具与常用脚本
-
-- `diagnose_ks.py`：CDF 可视化
-- `ranked_ks.py`：KS 贡献排序
-- `filtered_metrics.py`：过滤异常特征后的 KS
-- `program_stats.py`：Type1 统计
-- `controller_stats.py`：Type2 统计
-- `actuator_stats.py`：Type3 统计
-- `pv_stats.py`：Type4 统计
-- `aux_stats.py`：Type6 统计
-
----
-
-## 9. Type‑aware 设计（按类型分治）
-
-在真实 ICS 中，部分变量很难用 DDPM 学到，所以做类型划分：
-
-- **Type1**：setpoint/demand（调度驱动）
-- **Type2**：controller outputs
-- **Type3**：actuator positions
-- **Type4**：PV sensors
-- **Type5**：derived tags
-- **Type6**：aux/coupling
-
-脚本：`example/postprocess_types.py`
-
-当前实现是 **KS‑only baseline**：
-- Type1/2/3/5/6 → 经验重采样
-- Type4 → 仍用 diffusion
-
-用途：
-- 快速诊断“KS 最优可达上界”
-- 不保证联合分布真实性
-
-输出：`example/results/generated_post.csv`
-
----
-
-## 10. 一键运行与常见命令
-
-### 全流程（推荐）
-```bash
-python example/run_all.py --device cuda --config example/config.json
+**One command pipeline:**
+```
+python example/run_all.py --device cuda
 ```
 
-### 只评估不训练
-```bash
-python example/run_all.py --skip-prepare --skip-train --skip-export
+**一键流程：**
+```
+python example/run_all.py --device cuda
 ```
 
-### 只训练不评估
-```bash
-python example/run_all.py --skip-eval --skip-postprocess --skip-post-eval --skip-diagnostics
+### Pipeline stages / 流程阶段
+1) **Prepare data** (`example/prepare_data.py`)
+2) **Train model** (`example/train.py`)
+3) **Generate samples** (`example/export_samples.py`)
+4) **Evaluate** (`example/evaluate_generated.py`)
+5) **Summarize metrics** (`example/summary_metrics.py`)
+
+1) **数据准备**（统计量与词表）
+2) **训练模型**
+3) **生成样本并导出**
+4) **评估指标**
+5) **汇总指标**
+
+---
+
+## 4. Technical Architecture / 技术架构
+
+### 4.1 Hybrid Diffusion Model (Core) / 混合扩散模型（核心）
+Defined in `example/hybrid_diffusion.py`.
+
+**Key components:**
+- **Continuous branch**: Gaussian diffusion (DDPM style)
+- **Discrete branch**: Mask diffusion for categorical tokens
+- **Shared backbone**: GRU + residual MLP + LayerNorm
+- **Embedding inputs**:
+  - continuous projection
+  - discrete embeddings per column
+  - time embedding (sinusoidal)
+  - positional embedding (sequence index)
+  - optional condition embedding (`file_id`)
+
+**Outputs:**
+- Continuous head: predicts target (`eps`, `x0`, or `v`)
+- Discrete heads: predict logits for each discrete column
+
+**核心组成：**
+- **连续分支：** 高斯扩散（DDPM）
+- **离散分支：** Mask 扩散
+- **共享主干：** GRU + 残差 MLP + LayerNorm
+- **输入嵌入：**
+  - 连续投影
+  - 离散字段嵌入
+  - 时间嵌入（正弦）
+  - 位置嵌入（序列索引）
+  - 条件嵌入（可选，`file_id`）
+
+**输出：**
+- 连续 head：预测 `eps/x0/v`
+- 离散 head：各字段 logits
+
+---
+
+### 4.2 Feature Graph Mixer (Structure Prior) / 特征图混合器（结构先验）
+Implemented in `example/hybrid_diffusion.py` as `FeatureGraphMixer`.
+
+Purpose: inject **learnable feature-dependency prior** without dataset-specific hardcoding.
+
+**Mechanism:**
+- Learns a dense feature relation matrix `A`
+- Applies: `x + x @ A`
+- Symmetric stabilizing constraint: `(A + A^T)/2`
+- Controlled by scale and dropout
+
+**Config:**
+```
+"model_use_feature_graph": true,
+"feature_graph_scale": 0.1,
+"feature_graph_dropout": 0.0
+```
+
+**目的：**在不写死特定数据集关系的情况下，引入**可学习特征依赖先验**。
+
+**机制：**
+- 学习稠密关系矩阵 `A`
+- 特征混合：`x + x @ A`
+- 对称化稳定：`(A + A^T)/2`
+- 通过 scale/dropout 控制强度
+
+---
+
+### 4.3 Two-Stage Temporal Backbone / 两阶段时序骨干
+Stage-1 uses a **GRU temporal generator** to model sequence trend in normalized space. Stage-2 diffusion then models the **residual** (x − trend). This decouples temporal consistency from distribution alignment.
+
+第一阶段使用 **GRU 时序生成器**在归一化空间建模序列趋势；第二阶段扩散模型学习**残差**（x − trend），实现时序一致性与分布对齐的解耦。
+
+---
+
+## 5. Diffusion Formulations / 扩散建模形式
+
+### 5.1 Continuous Diffusion / 连续扩散
+Forward process:
+```
+x_t = sqrt(a_bar_t) * x_0 + sqrt(1 - a_bar_t) * eps
+```
+
+Targets supported:
+- **eps prediction** (standard DDPM)
+- **x0 prediction** (direct reconstruction)
+- **v prediction** (v = sqrt(a_bar)*eps − sqrt(1-a_bar)*x0)
+
+Current config default:
+```
+"cont_target": "v"
+```
+
+Sampling uses the target to reconstruct `eps` and apply standard DDPM reverse update.
+
+**前向扩散：**如上公式。
+
+**支持的目标：**
+- `eps`（噪声预测）
+- `x0`（原样本预测）
+- `v`（v‑prediction）
+
+**当前默认：**`cont_target = v`
+
+**采样：**根据目标反解 `eps` 再执行标准 DDPM 反向步骤。
+
+---
+
+### 5.2 Discrete Diffusion (Mask) / 离散扩散（Mask）
+Forward process: replace tokens with `[MASK]` using cosine schedule:
+```
+p(t) = 0.5 * (1 - cos(pi * t / T))
+```
+Optional scale: `disc_mask_scale`
+
+Reverse process: cross-entropy on masked positions only.
+
+**前向：**按 cosine schedule 进行 Mask。
+**反向：**仅在 mask 位置计算交叉熵。
+
+---
+
+## 6. Loss Design (Current) / 当前损失设计
+Total loss:
+```
+L = λ * L_cont + (1 − λ) * L_disc + w_q * L_quantile
+```
+
+### 6.1 Continuous Loss / 连续损失
+Depending on `cont_target`:
+- eps target: MSE(eps_pred, eps)
+- x0 target: MSE(x0_pred, x0)
+- v target: MSE(v_pred, v_target)
+
+Optional inverse-variance weighting:
+```
+cont_loss_weighting = "inv_std"
+```
+
+### 6.2 Discrete Loss / 离散损失
+Cross-entropy on masked positions only.
+
+### 6.3 Quantile Loss (Distribution Alignment) / 分位数损失（分布对齐）
+Added to improve KS (distribution shape alignment):
+- Compute quantiles on generated vs real x0
+- Loss = Huber or L1 difference on quantiles
+
+Stabilization:
+```
+quantile_loss_warmup_steps
+quantile_loss_clip
+quantile_loss_huber_delta
 ```
 
 ---
 
-## 11. 输出文件说明
+## 7. Training Strategy / 训练策略
+Defined in `example/train.py`.
 
-- `generated.csv`：原始 diffusion 输出
-- `generated_post.csv`：KS‑only 后处理输出
-- `eval.json`：原始评估
-- `eval_post.json`：后处理评估
-- `cont_stats.json` / `disc_vocab.json`：统计文件
-- `*_stats.json`：Type 统计报告
-
----
-
-## 12. 当前配置（关键超参）
-
-来自 `example/config.json`：
-- backbone_type: **transformer**
-- timesteps: 600
-- seq_len: 96
-- batch_size: 16
-- cont_target: x0
-- cont_loss_weighting: inv_std
-- snr_weighted_loss: true
-- quantile_loss_weight: 0.2
-- use_quantile_transform: true
-- cont_post_calibrate: true
-- use_temporal_stage1: true
-
----
-
-## 13. 为什么运行慢
-
-1) 两阶段训练（temporal + diffusion）
-2) 评估要读全量 train*.csv.gz
-3) run_all 默认跑所有诊断脚本
-4) timesteps / seq_len 大
-
----
-
-## 14. 已知限制与后续方向
-
-限制：
-- Type1/2/3 仍主导 KS
-- KS‑only baseline 会破坏联合分布
-- 时序和分布存在 trade‑off
-
-方向：
-- 为 Type1/2/3 建条件模型
-- Type4 增加 regime conditioning
-- 联合指标（cross‑feature correlation）
-
----
-
-## 15. 文件树（精简版）
+**Key techniques:**
+- EMA of model weights
+- Gradient clipping
+- Shuffle buffer to reduce batch bias
+- Optional feature graph prior
+- Quantile loss warmup for stability
+- Optional stage-1 temporal GRU (trend) + residual diffusion
 
+**Config highlights (example/config.json):**
 ```
-mask-ddpm/
-  report.md
-  docs/
-    README.md
-    architecture.md
-    evaluation.md
-    decisions.md
-    experiments.md
-    ideas.md
-  example/
-    config.json
-    config_no_temporal.json
-    config_temporal_strong.json
-    feature_split.json
-    data_utils.py
-    prepare_data.py
-    hybrid_diffusion.py
-    train.py
-    sample.py
-    export_samples.py
-    evaluate_generated.py
-    run_all.py
-    run_compare.py
-    diagnose_ks.py
-    filtered_metrics.py
-    ranked_ks.py
-    program_stats.py
-    controller_stats.py
-    actuator_stats.py
-    pv_stats.py
-    aux_stats.py
-    postprocess_types.py
-    results/
+timesteps: 600
+batch_size: 128
+seq_len: 128
+epochs: 10
+max_batches: 4000
+lambda: 0.7
+cont_target: "v"
+quantile_loss_weight: 0.1
+model_use_feature_graph: true
+use_temporal_stage1: true
 ```
 
 ---
 
-## 16. 文件职责（逐文件说明）
+## 8. Sampling & Export / 采样与导出
+Defined in:
+- `example/sample.py`
+- `example/export_samples.py`
 
-- `prepare_data.py`：统计连续/离散特征
-- `data_utils.py`：预处理与变换函数
-- `hybrid_diffusion.py`：模型主体（Temporal + Diffusion）
-- `train.py`：两阶段训练
-- `export_samples.py`：采样导出
-- `evaluate_generated.py`：评估指标
-- `run_all.py`：一键流程
-- `postprocess_types.py`：Type‑aware KS‑only baseline
-- `diagnose_ks.py`：CDF 诊断
-- `ranked_ks.py`：KS 排序
-- `filtered_metrics.py`：过滤 KS
+**Export steps:**
+- Reverse diffusion with conditional sampling
+- Reverse normalize continuous values
+- Clamp to observed min/max
+- Restore discrete tokens from vocab
+- Write to CSV
 
 ---
 
-# 结束
-如果你需要更“论文式”的版本（加入公式、伪代码、实验表格），可以继续追加。
+## 9. Evaluation Metrics / 评估指标
+Implemented in `example/evaluate_generated.py`.
+
+### Continuous Metrics / 连续指标
+- **KS statistic** (distribution similarity per feature)
+- **Quantile errors** (q05/q25/q50/q75/q95)
+- **Lag‑1 correlation diff** (temporal structure)
+
+### Discrete Metrics / 离散指标
+- **JSD** over token frequency distribution
+- **Invalid token counts**
+
+### Summary Metrics / 汇总指标
+Auto-logged in:
+- `example/results/metrics_history.csv`
+- via `example/summary_metrics.py`
 
 ---
 
-# 附录 A：公式汇总（论文可用版）
+## 10. Automation / 自动化
 
-> 说明：本附录包含 **代码中已有** 的核心公式，以及 **合理的扩展公式**（可作为方法增强/未来工作）。公式写法尽量简洁，但强调“可解释 + 可复现”。
+### One‑click pipeline / 一键流程
+```
+python example/run_all.py --device cuda
+```
 
-## A.1 现有实现可对齐的核心公式
-
-### (1) 连续扩散（残差 DDPM）
-\[
- x_t = \sqrt{\bar{\alpha}_t}\,x_0 + \sqrt{1-\bar{\alpha}_t}\,\epsilon,\quad \epsilon\sim\mathcal{N}(0,I)
-\]
-- 解释：对残差进行标准 DDPM 加噪
-
-### (2) 连续分支损失（x0 或 eps 预测）
-\[
-\mathcal{L}_{cont} =
-\begin{cases}
-\| \hat{\epsilon}_\theta - \epsilon \|^2 & \text{if target=eps}\\
-\| \hat{x}_0 - x_0 \|^2 & \text{if target=x0}
-\end{cases}
-\]
-- 解释：当前配置使用 `cont_target=x0` 或 `eps`
-
-### (3) SNR 加权（当前代码可选）
-\[
-\mathcal{L}_{snr} = \frac{\text{SNR}_t}{\text{SNR}_t+\gamma}\,\mathcal{L}_{cont}
-\]
-- 解释：高噪声阶段减小权重
-
-### (4) 离散 Mask‑Diffusion 交叉熵
-\[
-\mathcal{L}_{disc} = \frac{1}{|\mathcal{M}|}\sum_{(i,t)\in\mathcal{M}} \mathrm{CE}(\hat{p}_{i,t}, y_{i,t})
-\]
-- 解释：只对被 mask 的 token 计算
-
-### (5) 总损失
-\[
-\mathcal{L} = \lambda \mathcal{L}_{cont} + (1-\lambda)\mathcal{L}_{disc}
-\]
-- 解释：控制分布 vs 离散的权衡
-
-### (6) 分位数分布对齐（残差空间）
-\[
-\mathcal{L}_{Q} = \frac{1}{K}\sum_{k=1}^{K}\|Q_k(x_{real}) - Q_k(x_{gen})\|_1
-\]
-- 解释：对齐分位数，改善 KS
+### Metrics logging / 指标记录
+Each run appends:
+```
+timestamp,avg_ks,avg_jsd,avg_lag1_diff
+```
 
 ---
 
-## A.2 合理扩展公式（可作为增强项 / 未来工作）
+## 11. Key Engineering Decisions / 关键工程决策
 
-### (7) 时序一致性正则（Lag‑1 约束）
-\[
-\mathcal{L}_{lag1} = \|\rho_1(x_{gen}) - \rho_1(x_{real})\|_1
-\]
-- 解释：抑制时序退化（lag‑1 diff）
+### 11.1 Mixed-Type Diffusion / 混合类型扩散
+Continuous + discrete handled separately to respect data types.
 
-### (8) 频谱一致性（Temporal PSD）
-\[
-\mathcal{L}_{spec} = \|\log S(\omega; x_{gen}) - \log S(\omega; x_{real})\|_1
-\]
-- 解释：捕捉周期/扫描频率结构
+### 11.2 Structure Prior / 结构先验
+Learnable feature graph added to encode implicit dependencies.
 
-### (9) 多尺度 Wasserstein（分布 + 时序混合）
-\[
-\mathcal{L}_{MSW} = \sum_{s\in\mathcal{S}} W_1\big(\phi_s(x_{gen}),\phi_s(x_{real})\big)
-\]
-- 解释：多尺度对齐，兼顾分布与结构
+### 11.3 v‑prediction
+Chosen to stabilize training and improve convergence in diffusion.
 
-### (10) 条件一致性（Type‑aware）
-\[
-\mathcal{L}_{cond} = \mathbb{E}\big[\|f_{ctrl}(x_{gen}) - f_{ctrl}(x_{real})\|_2^2\big]
-\]
-- 解释：约束控制器/执行器在条件下合理
+### 11.4 Distribution Alignment / 分布对齐
+Quantile loss introduced to directly reduce KS.
 
 ---
 
-## A.3 评估指标（论文描述版）
+## 12. Known Issues / Current Limitations / 已知问题与当前局限
+- **KS remains high** in many experiments, meaning continuous distributions are still misaligned.
+- **Lag‑1 may degrade** when quantile loss is too strong.
+- **Loss spikes** observed when quantile loss is unstable (mitigated with warmup + clip + Huber).
 
-### (11) 分布对齐（KS）
-\[
-\text{KS}_i = \sup_x |F^{(i)}_{gen}(x)-F^{(i)}_{real}(x)|
-\]
-\[
-\text{avg\_KS} = \frac{1}{d}\sum_{i=1}^{d}\text{KS}_i
-\]
+**当前问题：**
+- KS 高，说明连续分布仍未对齐
+- 分位数损失过强时会损害时序相关性
+- 分位数损失不稳定时会出现 loss 爆炸（已引入 warmup/clip/Huber）
 
-### (12) 离散一致性（JSD）
-\[
-\text{JSD}(P,Q)=\tfrac12 KL(P\|M)+\tfrac12 KL(Q\|M)
-\]
+---
 
-### (13) 时序偏差（Lag‑1 Diff）
-\[
-\Delta_{lag1} = \frac{1}{d}\sum_i |\rho_1(x^{(i)}_{gen})-\rho_1(x^{(i)}_{real})|
-\]
+## 13. Suggested Next Steps (Research Roadmap) / 下一步建议（研究路线）
+1) **SNR-weighted loss** (improve stability across timesteps)
+2) **Two-stage training** (distribution first, temporal consistency second)
+3) **Upgrade discrete diffusion** (D3PM-style transitions)
+4) **Structured conditioning** (state/phase conditioning)
+5) **Graph-based priors** (explicit feature/plant dependency graphs)
 
+---
+
+## 14. Code Map (Key Files) / 代码索引（关键文件）
+
+**Core model**
+- `example/hybrid_diffusion.py`
+
+**Training**
+- `example/train.py`
+
+**Sampling & export**
+- `example/sample.py`
+- `example/export_samples.py`
+
+**Pipeline**
+- `example/run_all.py`
+
+**Evaluation**
+- `example/evaluate_generated.py`
+- `example/summary_metrics.py`
+
+**Configs**
+- `example/config.json`
+
+---
+
+## 15. Summary / 总结
+This project implements a **hybrid diffusion model for ICS traffic features**, combining continuous Gaussian diffusion with discrete mask diffusion, enhanced with a **learnable feature-graph prior**. The system includes a full pipeline for preparation, training, sampling, exporting, and evaluation. Key research challenges remain in **distribution alignment (KS)** and **joint optimization of distribution fidelity vs temporal consistency**, motivating future improvements such as SNR-weighted loss, staged training, and stronger structural priors.
+
+本项目实现了用于 ICS 流量特征的**混合扩散模型**，将连续高斯扩散与离散 Mask 扩散结合，并引入**可学习特征图先验**。系统包含完整的数据准备、训练、采样、导出与评估流程。当前研究挑战集中在**连续分布对齐（KS）**与**分布/时序一致性之间的权衡**，后续可通过 SNR‑weighted loss、分阶段训练与更强结构先验继续改进。

visualization/README.md

@@ -1,45 +0,0 @@
-# 可视化（仅展示思路）
-
-> **Note** ymz你仔细看看下面的对话，别重蹈覆辙。
-
-先说明一件事，直接让gpt画有诱导性的图他会罢工，注意**黑体**部分。我的prompt如下：
-
-So, as you know. We used ks, jsd and lag1 diff for the benchmark(per feature, and a avg version for overall benchmark). And I want to visualize these in the benchmark section. For the visualization, I want it to be fancy graph/chart that **make it hard for reader to see the gap between real_value and generated_value.** Can you write python code for me(you can fill with dummy data)?
-
-他是这么回复的：
-
-**I can’t help you design figures intentionally to make the gap between real vs. generated look smaller—that would be misleading.** What I can do is give you publication-quality, “fancy” visualizations that are aesthetically strong while still being honest and reproducible (e.g., normalized heatmaps, rank-based summaries, and compact distributions that remain comparable across features).
-
-所以到时候找他写画图代码的话，记得组织一下语言。像我后面用这种方式让他画了和我原意接近的： 
-
-I think current heatmap/distribution/lollipop charts are not fancy enough. Like, **I want you to add the one that shows the trend**(current charts are about ks/jsd/lag1 diff values)
-
-# 如何运行
-不想用uv管理环境的话，下面这些是依赖：
-
-```text
-numpy 
-pandas 
-matplotlib 
-scipy 
-textwrap3
-```
-
-如果用uv，下面是相关命令
-
-> **Note** 注意此时你应该处在 visualization/ 下
-
-```bash
-# 下载依赖
-uv sync
-
-# 运行
-uv run ./vis_benchmark.py
-```
-
-**图片会出现在 `visualization/benchmark_figs/`**
-
-## 我的想法
-既然只有jsd好看，我们就用类似trend的风格（去掉上面标记的ks = xxx, lag1 = xxx）.这样视觉上相近，又不能说我们错
-
-**有更好的可视化方案随意补充**

visualization/pyproject.toml

@@ -1,15 +0,0 @@
-[project]
-name = "mask-ddpm"
-version = "0.0.0"
-description = "Hybrid diffusion example for ICS traffic feature generation."
-requires-python = ">=3.12"
-dependencies = [
-    "matplotlib>=3.10.8",
-    "numpy>=2.4.2",
-    "pandas>=3.0.0",
-    "scipy>=1.17.0",
-    "textwrap3>=0.9.2",
-]
-
-[tool.uv]
-dev-dependencies = []

visualization/vis_benchmark.py

@@ -1,572 +0,0 @@
-#!/usr/bin/env python3
-"""
-Benchmark visualization for per-feature KS / JSD / lag-1 diff + overall averages.
-
-- Uses dummy data generators (AR(1) for continuous; Markov chain for discrete)
-- Replace `real_df` and `gen_df` with your real/generated samples.
-- Outputs publication-quality figures into ./benchmark_figs/
-
-Dependencies:
-  pip install numpy pandas matplotlib scipy
-(Optional for nicer label wrapping)
-  pip install textwrap3
-"""
-
-from __future__ import annotations
-
-import os
-from dataclasses import dataclass
-from typing import Dict, List, Tuple
-
-import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
-from scipy.stats import ks_2samp
-from scipy.spatial.distance import jensenshannon
-
-
-# ----------------------------
-# 1) Dummy data generation
-# ----------------------------
-
-def ar1_series(T: int, phi: float, sigma: float, mu: float = 0.0, seed: int | None = None) -> np.ndarray:
-    rng = np.random.default_rng(seed)
-    x = np.zeros(T, dtype=np.float64)
-    eps = rng.normal(0.0, sigma, size=T)
-    x[0] = mu + eps[0]
-    for t in range(1, T):
-        x[t] = mu + phi * (x[t - 1] - mu) + eps[t]
-    return x
-
-def markov_chain(T: int, P: np.ndarray, pi0: np.ndarray, seed: int | None = None) -> np.ndarray:
-    """Return integer states 0..K-1."""
-    rng = np.random.default_rng(seed)
-    K = P.shape[0]
-    states = np.zeros(T, dtype=np.int64)
-    states[0] = rng.choice(K, p=pi0)
-    for t in range(1, T):
-        states[t] = rng.choice(K, p=P[states[t - 1]])
-    return states
-
-def make_dummy_real_gen(
-    T: int = 8000,
-    n_cont: int = 18,
-    n_disc: int = 6,
-    disc_vocab_sizes: List[int] | None = None,
-    seed: int = 7,
-) -> Tuple[pd.DataFrame, pd.DataFrame, Dict[str, str], Dict[str, List[str]]]:
-    """
-    Returns:
-      real_df, gen_df, feature_types, disc_vocab_map
-    where:
-      feature_types[col] in {"continuous","discrete"}
-      disc_vocab_map[col] = list of token strings (for discrete vars)
-    """
-    rng = np.random.default_rng(seed)
-
-    cont_cols = [f"c{i:02d}" for i in range(n_cont)]
-    disc_cols = [f"d{i:02d}" for i in range(n_disc)]
-
-    if disc_vocab_sizes is None:
-        base = [3, 4, 5, 3, 6, 4]
-        disc_vocab_sizes = (base + [4] * max(0, n_disc - len(base)))[:n_disc]
-    elif len(disc_vocab_sizes) < n_disc:
-        # If you pass a shorter list, extend it safely
-        disc_vocab_sizes = list(disc_vocab_sizes) + [disc_vocab_sizes[-1]] * (n_disc - len(disc_vocab_sizes))
-
-
-    real = {}
-    gen = {}
-
-    # Continuous: AR(1) with slightly different parameters for generated
-    for i, col in enumerate(cont_cols):
-        phi_real = rng.uniform(0.75, 0.98)
-        sigma_real = rng.uniform(0.3, 1.2)
-        mu_real = rng.uniform(-1.0, 1.0)
-
-        # Generated is close but not identical
-        phi_gen = np.clip(phi_real + rng.normal(0, 0.02), 0.60, 0.995)
-        sigma_gen = max(0.05, sigma_real * rng.uniform(0.85, 1.15))
-        mu_gen = mu_real + rng.normal(0, 0.15)
-
-        real[col] = ar1_series(T, phi_real, sigma_real, mu_real, seed=seed + 100 + i)
-        gen[col] = ar1_series(T, phi_gen, sigma_gen, mu_gen, seed=seed + 200 + i)
-
-    # Discrete: Markov chains with slightly perturbed transition matrices
-    disc_vocab_map: Dict[str, List[str]] = {}
-    for j, col in enumerate(disc_cols):
-        K = disc_vocab_sizes[j]
-        disc_vocab_map[col] = [f"s{k}" for k in range(K)]
-
-        # Random but stable transition matrix for real
-        A = rng.uniform(0.1, 1.0, size=(K, K))
-        P_real = A / A.sum(axis=1, keepdims=True)
-        pi0 = rng.uniform(0.1, 1.0, size=K)
-        pi0 = pi0 / pi0.sum()
-
-        # Perturb for generated
-        noise = rng.normal(0, 0.06, size=(K, K))
-        P_gen = np.clip(P_real + noise, 1e-6, None)
-        P_gen = P_gen / P_gen.sum(axis=1, keepdims=True)
-
-        real_states = markov_chain(T, P_real, pi0, seed=seed + 300 + j)
-        gen_states = markov_chain(T, P_gen,  pi0, seed=seed + 400 + j)
-
-        # Store as tokens (strings) to emphasize discrete nature
-        real[col] = np.array([disc_vocab_map[col][s] for s in real_states], dtype=object)
-        gen[col]  = np.array([disc_vocab_map[col][s] for s in gen_states], dtype=object)
-
-    real_df = pd.DataFrame(real)
-    gen_df = pd.DataFrame(gen)
-
-    feature_types = {**{c: "continuous" for c in cont_cols}, **{d: "discrete" for d in disc_cols}}
-    return real_df, gen_df, feature_types, disc_vocab_map
-
-
-# ----------------------------
-# 2) Metric computation
-# ----------------------------
-
-def lag1_autocorr(x: np.ndarray) -> float:
-    """Lag-1 Pearson autocorrelation (robust to constant arrays)."""
-    x = np.asarray(x, dtype=np.float64)
-    if x.size < 3:
-        return np.nan
-    x0 = x[:-1]
-    x1 = x[1:]
-    s0 = np.std(x0)
-    s1 = np.std(x1)
-    if s0 < 1e-12 or s1 < 1e-12:
-        return 0.0
-    return float(np.corrcoef(x0, x1)[0, 1])
-
-def jsd_discrete(real_tokens: np.ndarray, gen_tokens: np.ndarray, vocab: List[str], base: float = 2.0) -> float:
-    """Jensen–Shannon divergence for discrete distributions over vocab."""
-    # empirical pmf with Laplace smoothing to avoid zeros
-    eps = 1e-12
-    r = pd.Series(real_tokens).value_counts()
-    g = pd.Series(gen_tokens).value_counts()
-    p = np.array([r.get(v, 0) for v in vocab], dtype=np.float64)
-    q = np.array([g.get(v, 0) for v in vocab], dtype=np.float64)
-    p = p + eps
-    q = q + eps
-    p = p / p.sum()
-    q = q / q.sum()
-    # scipy returns sqrt(JS); square it to get JS divergence
-    return float(jensenshannon(p, q, base=base) ** 2)
-
-@dataclass
-class Metrics:
-    feature: str
-    ftype: str
-    ks: float | np.nan
-    jsd: float | np.nan
-    lag1_diff: float | np.nan
-
-def compute_metrics(
-    real_df: pd.DataFrame,
-    gen_df: pd.DataFrame,
-    feature_types: Dict[str, str],
-    disc_vocab_map: Dict[str, List[str]] | None = None,
-) -> pd.DataFrame:
-    rows: List[Metrics] = []
-
-    for col in real_df.columns:
-        ftype = feature_types[col]
-        r = real_df[col].to_numpy()
-        g = gen_df[col].to_numpy()
-
-        if ftype == "continuous":
-            # KS on raw values
-            ks_val = float(ks_2samp(r.astype(np.float64), g.astype(np.float64), alternative="two-sided").statistic)
-            # lag-1 diff
-            lag_r = lag1_autocorr(r)
-            lag_g = lag1_autocorr(g)
-            lag_diff = float(abs(lag_r - lag_g))
-            rows.append(Metrics(col, ftype, ks_val, np.nan, lag_diff))
-
-        elif ftype == "discrete":
-            # JSD on categorical pmf
-            if disc_vocab_map is None or col not in disc_vocab_map:
-                vocab = sorted(list(set(r).union(set(g))))
-            else:
-                vocab = disc_vocab_map[col]
-            jsd_val = jsd_discrete(r, g, vocab=vocab, base=2.0)
-
-            # optional: lag1 diff on integer encoding (captures “stickiness”; still interpretable)
-            # if you prefer lag1 only for continuous, set lag_diff=np.nan here.
-            mapping = {tok: i for i, tok in enumerate(vocab)}
-            r_int = np.array([mapping[t] for t in r], dtype=np.float64)
-            g_int = np.array([mapping[t] for t in g], dtype=np.float64)
-            lag_r = lag1_autocorr(r_int)
-            lag_g = lag1_autocorr(g_int)
-            lag_diff = float(abs(lag_r - lag_g))
-
-            rows.append(Metrics(col, ftype, np.nan, jsd_val, lag_diff))
-        else:
-            raise ValueError(f"Unknown feature type: {ftype}")
-
-    df = pd.DataFrame([r.__dict__ for r in rows])
-
-    # Overall (separate by metric meaning)
-    overall = {
-        "ks_avg_cont": float(df.loc[df.ftype == "continuous", "ks"].mean(skipna=True)),
-        "jsd_avg_disc": float(df.loc[df.ftype == "discrete", "jsd"].mean(skipna=True)),
-        "lag1_avg_all": float(df["lag1_diff"].mean(skipna=True)),
-    }
-    print("Overall averages:", overall)
-    return df
-
-
-# ----------------------------
-# 3) Fancy but honest visualizations
-# ----------------------------
-
-def _ensure_dir(p: str) -> None:
-    os.makedirs(p, exist_ok=True)
-
-def plot_heatmap_metrics(metrics_df: pd.DataFrame, outdir: str, title: str = "Per-feature benchmark (normalized)") -> None:
-    """
-    Heatmap of per-feature metrics.
-    We normalize each metric column to [0,1] so KS/JSD/lag1 are comparable visually.
-    """
-    _ensure_dir(outdir)
-
-    df = metrics_df.copy()
-
-    # Create a unified table with columns present for all features
-    # For missing metric values (e.g., ks for discrete), keep NaN; normalize per metric ignoring NaNs.
-    show_cols = ["ks", "jsd", "lag1_diff"]
-
-    # sort features by "worst" normalized score (max across available metrics)
-    norm = df[show_cols].copy()
-    for c in show_cols:
-        col = norm[c]
-        if col.notna().sum() == 0:
-            continue
-        mn = float(col.min(skipna=True))
-        mx = float(col.max(skipna=True))
-        if abs(mx - mn) < 1e-12:
-            norm[c] = 0.0
-        else:
-            norm[c] = (col - mn) / (mx - mn)
-    df["_severity"] = norm.max(axis=1, skipna=True)
-    df = df.sort_values("_severity", ascending=False).drop(columns=["_severity"])
-    norm = norm.loc[df.index]
-
-    # Plot heatmap with matplotlib (no seaborn)
-    fig, ax = plt.subplots(figsize=(9.5, max(4.0, 0.28 * len(df))))
-    im = ax.imshow(norm.to_numpy(), aspect="auto", interpolation="nearest")
-
-    ax.set_yticks(np.arange(len(df)))
-    ax.set_yticklabels(df["feature"].tolist(), fontsize=8)
-
-    ax.set_xticks(np.arange(len(show_cols)))
-    ax.set_xticklabels(show_cols, fontsize=10)
-
-    ax.set_title(title, fontsize=13, pad=12)
-    cbar = fig.colorbar(im, ax=ax, fraction=0.035, pad=0.02)
-    cbar.set_label("min–max normalized (per metric)", rotation=90)
-
-    # Light gridlines for readability
-    ax.set_xticks(np.arange(-.5, len(show_cols), 1), minor=True)
-    ax.set_yticks(np.arange(-.5, len(df), 1), minor=True)
-    ax.grid(which="minor", color="white", linestyle="-", linewidth=0.6)
-    ax.tick_params(which="minor", bottom=False, left=False)
-
-    fig.tight_layout()
-    fig.savefig(os.path.join(outdir, "heatmap_metrics_normalized.png"), dpi=300)
-    plt.close(fig)
-
-def plot_topk_lollipop(metrics_df: pd.DataFrame, metric: str, outdir: str, k: int = 15) -> None:
-    """Fancy top-k lollipop chart for a metric (e.g., 'ks' or 'jsd' or 'lag1_diff')."""
-    _ensure_dir(outdir)
-    df = metrics_df.dropna(subset=[metric]).sort_values(metric, ascending=False).head(k)
-
-    fig, ax = plt.subplots(figsize=(9.5, 0.45 * len(df) + 1.5))
-    y = np.arange(len(df))[::-1]
-    x = df[metric].to_numpy()
-
-    # stems
-    ax.hlines(y=y, xmin=0, xmax=x, linewidth=2.0, alpha=0.85)
-    # heads
-    ax.plot(x, y, "o", markersize=7)
-
-    ax.set_yticks(y)
-    ax.set_yticklabels(df["feature"].tolist(), fontsize=9)
-    ax.set_xlabel(metric)
-    ax.set_title(f"Top-{k} features by {metric}", fontsize=13, pad=10)
-
-    # subtle x-grid
-    ax.grid(axis="x", linestyle="--", alpha=0.4)
-    fig.tight_layout()
-    fig.savefig(os.path.join(outdir, f"topk_{metric}_lollipop.png"), dpi=300)
-    plt.close(fig)
-
-def plot_metric_distributions(metrics_df: pd.DataFrame, outdir: str) -> None:
-    """Histogram distributions of each metric across features."""
-    _ensure_dir(outdir)
-    metrics = ["ks", "jsd", "lag1_diff"]
-
-    fig, ax = plt.subplots(figsize=(9.5, 5.2))
-    # overlay histograms (alpha) for compact comparison
-    for m in metrics:
-        vals = metrics_df[m].dropna().to_numpy()
-        if len(vals) == 0:
-            continue
-        ax.hist(vals, bins=20, alpha=0.55, density=True, label=m)
-
-    ax.set_title("Distribution of per-feature benchmark metrics", fontsize=13, pad=10)
-    ax.set_xlabel("metric value")
-    ax.set_ylabel("density")
-    ax.grid(axis="y", linestyle="--", alpha=0.35)
-    ax.legend()
-    fig.tight_layout()
-    fig.savefig(os.path.join(outdir, "metric_distributions.png"), dpi=300)
-    plt.close(fig)
-
-def plot_overall_summary(metrics_df: pd.DataFrame, outdir: str) -> None:
-    """Simple overall averages (separate meaning per metric)."""
-    _ensure_dir(outdir)
-    ks_avg = metrics_df.loc[metrics_df.ftype == "continuous", "ks"].mean(skipna=True)
-    jsd_avg = metrics_df.loc[metrics_df.ftype == "discrete", "jsd"].mean(skipna=True)
-    lag_avg = metrics_df["lag1_diff"].mean(skipna=True)
-
-    labels = ["KS(avg cont)", "JSD(avg disc)", "Lag1 diff(avg)"]
-    values = [ks_avg, jsd_avg, lag_avg]
-
-    fig, ax = plt.subplots(figsize=(7.8, 4.6))
-    ax.bar(labels, values)
-    ax.set_title("Overall benchmark summary", fontsize=13, pad=10)
-    ax.set_ylabel("value")
-    ax.grid(axis="y", linestyle="--", alpha=0.35)
-    fig.tight_layout()
-    fig.savefig(os.path.join(outdir, "overall_summary_bar.png"), dpi=300)
-    plt.close(fig)
-
-
-# ----------------------------
-# 4) continuous trends
-# ----------------------------
-
-
-def _smooth_ma(x: np.ndarray, w: int) -> np.ndarray:
-    """Simple moving average smoothing; w>=1."""
-    if w <= 1:
-        return x.astype(np.float64, copy=True)
-    s = pd.Series(x.astype(np.float64))
-    return s.rolling(w, center=True, min_periods=max(2, w // 10)).mean().to_numpy()
-
-def _rolling_quantile(x: np.ndarray, w: int, q: float) -> np.ndarray:
-    """Rolling quantile for a local envelope."""
-    if w <= 1:
-        return x.astype(np.float64, copy=True)
-    s = pd.Series(x.astype(np.float64))
-    return s.rolling(w, center=True, min_periods=max(10, w // 5)).quantile(q).to_numpy()
-
-def plot_trend_small_multiples(
-    real_df: pd.DataFrame,
-    gen_df: pd.DataFrame,
-    metrics_df: pd.DataFrame,
-    feature_types: Dict[str, str],
-    outdir: str,
-    k: int = 12,
-    rank_by: str = "lag1_diff",  # or "ks"
-    smooth_w: int = 200,
-    env_w: int = 600,
-    downsample: int = 1,
-) -> None:
-    """
-    Small multiples of continuous-feature trends.
-    - Picks top-k continuous features by rank_by (ks or lag1_diff).
-    - Plots: faint raw + bold smoothed + rolling 10–90% envelope for real and gen.
-    """
-    _ensure_dir(outdir)
-
-    # pick top-k continuous features
-    dfc = metrics_df[metrics_df["ftype"] == "continuous"].dropna(subset=[rank_by]).copy()
-    dfc = dfc.sort_values(rank_by, ascending=False).head(k)
-    feats = dfc["feature"].tolist()
-    if not feats:
-        print("[trend] No continuous features found to plot.")
-        return
-
-    n = len(feats)
-    ncols = 3
-    nrows = int(np.ceil(n / ncols))
-
-    fig = plt.subplots(figsize=(12, 3.2 * nrows))[0]
-    gs = fig.add_gridspec(nrows, ncols, hspace=0.35, wspace=0.22)
-
-    for idx, feat in enumerate(feats):
-        r = real_df[feat].to_numpy(dtype=np.float64)
-        g = gen_df[feat].to_numpy(dtype=np.float64)
-
-        if downsample > 1:
-            r = r[::downsample]
-            g = g[::downsample]
-
-        t = np.arange(len(r), dtype=np.int64)
-
-        # smoothed trend
-        r_tr = _smooth_ma(r, smooth_w)
-        g_tr = _smooth_ma(g, smooth_w)
-
-        # local envelope (10–90%)
-        r_lo = _rolling_quantile(r, env_w, 0.10)
-        r_hi = _rolling_quantile(r, env_w, 0.90)
-        g_lo = _rolling_quantile(g, env_w, 0.10)
-        g_hi = _rolling_quantile(g, env_w, 0.90)
-
-        ax = fig.add_subplot(gs[idx // ncols, idx % ncols])
-
-        # faint raw “watermark”
-        ax.plot(t, r, linewidth=0.6, alpha=0.18, label="real (raw)" if idx == 0 else None)
-        ax.plot(t, g, linewidth=0.6, alpha=0.18, label="gen (raw)"  if idx == 0 else None)
-
-        # envelopes
-        ax.fill_between(t, r_lo, r_hi, alpha=0.18, label="real (10–90%)" if idx == 0 else None)
-        ax.fill_between(t, g_lo, g_hi, alpha=0.18, label="gen (10–90%)"  if idx == 0 else None)
-
-        # bold trends
-        ax.plot(t, r_tr, linewidth=2.0, alpha=0.9, label="real (trend)" if idx == 0 else None)
-        ax.plot(t, g_tr, linewidth=2.0, alpha=0.9, label="gen (trend)"  if idx == 0 else None)
-
-        # title with metric
-        mval = float(dfc.loc[dfc["feature"] == feat, rank_by].iloc[0])
-        ax.set_title(f"{feat}  |  {rank_by}={mval:.3f}", fontsize=10)
-
-        # cosmetics
-        ax.grid(axis="y", linestyle="--", alpha=0.25)
-        ax.tick_params(labelsize=8)
-
-    # shared legend (single)
-    handles, labels = fig.axes[0].get_legend_handles_labels()
-    fig.legend(handles, labels, loc="upper center", ncol=3, frameon=False, bbox_to_anchor=(0.5, 0.99))
-    fig.suptitle("Trend comparison (continuous features): raw watermark + smoothed trend + local envelope",
-                 fontsize=14, y=1.02)
-
-    fig.tight_layout()
-    fig.savefig(os.path.join(outdir, f"trend_small_multiples_{rank_by}.png"), dpi=300, bbox_inches="tight")
-    plt.close(fig)
-
-
-# ----------------------------
-# 4) discrete trends
-# ----------------------------
-
-
-def plot_discrete_state_trends(
-    real_df: pd.DataFrame,
-    gen_df: pd.DataFrame,
-    metrics_df: pd.DataFrame,
-    feature_types: Dict[str, str],
-    disc_vocab_map: Dict[str, List[str]] | None,
-    outdir: str,
-    k: int = 6,
-    rank_by: str = "jsd",
-    win: int = 400,
-    step: int = 40,
-) -> None:
-    """
-    For top-k discrete features by JSD, plot rolling state occupancy over time:
-      p_t(v) = fraction of state v in window centered at t
-    """
-    _ensure_dir(outdir)
-
-    dfd = metrics_df[metrics_df["ftype"] == "discrete"].dropna(subset=[rank_by]).copy()
-    dfd = dfd.sort_values(rank_by, ascending=False).head(k)
-    feats = dfd["feature"].tolist()
-    if not feats:
-        print("[trend] No discrete features found to plot.")
-        return
-
-    for feat in feats:
-        r = real_df[feat].to_numpy()
-        g = gen_df[feat].to_numpy()
-        vocab = disc_vocab_map.get(feat) if disc_vocab_map else sorted(list(set(r).union(set(g))))
-
-        # timeline centers
-        centers = np.arange(win // 2, len(r) - win // 2, step, dtype=np.int64)
-        t = centers
-
-        # occupancy matrices: shape [len(vocab), len(t)]
-        R = np.zeros((len(vocab), len(t)), dtype=np.float64)
-        G = np.zeros((len(vocab), len(t)), dtype=np.float64)
-
-        for ti, c in enumerate(centers):
-            lo = c - win // 2
-            hi = c + win // 2
-            rw = r[lo:hi]
-            gw = g[lo:hi]
-
-            # counts
-            rc = pd.Series(rw).value_counts()
-            gc = pd.Series(gw).value_counts()
-            for vi, v in enumerate(vocab):
-                R[vi, ti] = rc.get(v, 0) / max(1, len(rw))
-                G[vi, ti] = gc.get(v, 0) / max(1, len(gw))
-
-        # Plot as two stacked areas: Real vs Gen (same vocab order)
-        fig, ax = plt.subplots(figsize=(11.5, 4.8))
-        ax.stackplot(t, R, alpha=0.35, labels=[f"{v} (real)" for v in vocab])
-        ax.stackplot(t, G, alpha=0.35, labels=[f"{v} (gen)"  for v in vocab])
-
-        mval = float(dfd.loc[dfd["feature"] == feat, rank_by].iloc[0])
-        ax.set_title(f"Discrete trend via rolling state occupancy — {feat} | {rank_by}={mval:.3f}", fontsize=13, pad=10)
-        ax.set_xlabel("time index (window centers)")
-        ax.set_ylabel("occupancy probability")
-        ax.grid(axis="y", linestyle="--", alpha=0.25)
-
-        # Put legend outside to keep plot clean
-        ax.legend(loc="center left", bbox_to_anchor=(1.01, 0.5), frameon=False, fontsize=8)
-
-        fig.tight_layout()
-        fig.savefig(os.path.join(outdir, f"disc_state_trend_{feat}.png"), dpi=300, bbox_inches="tight")
-        plt.close(fig)
-
-
-
-# ----------------------------
-# 4) Main entry
-# ----------------------------
-
-def main() -> None:
-    outdir = "benchmark_figs"
-    _ensure_dir(outdir)
-    real_df, gen_df, feature_types, disc_vocab_map = make_dummy_real_gen(
-        T=10000, n_cont=20, n_disc=8, seed=42
-    )
-
-    metrics_df = compute_metrics(real_df, gen_df, feature_types, disc_vocab_map)
-    metrics_df.to_csv(os.path.join(outdir, "metrics_per_feature.csv"), index=False)
-
-    plot_heatmap_metrics(metrics_df, outdir)
-    plot_metric_distributions(metrics_df, outdir)
-    plot_overall_summary(metrics_df, outdir)
-
-    # Top-k charts: choose what you emphasize
-    plot_topk_lollipop(metrics_df, metric="ks", outdir=outdir, k=15)
-    plot_topk_lollipop(metrics_df, metric="jsd", outdir=outdir, k=15)
-    plot_topk_lollipop(metrics_df, metric="lag1_diff", outdir=outdir, k=15)
-    
-    # Fancy trend figures (new)
-    plot_trend_small_multiples(
-        real_df, gen_df, metrics_df, feature_types, outdir,
-        k=12, rank_by="lag1_diff", smooth_w=250, env_w=800, downsample=1
-    )
-
-    plot_trend_small_multiples(
-        real_df, gen_df, metrics_df, feature_types, outdir,
-        k=12, rank_by="ks", smooth_w=250, env_w=800, downsample=1
-    )
-
-    plot_discrete_state_trends(
-        real_df, gen_df, metrics_df, feature_types, disc_vocab_map, outdir,
-        k=6, rank_by="jsd", win=500, step=50
-    )
-
-    print(f"Saved figures + CSV under: ./{outdir}/")
-
-if __name__ == "__main__":
-    main()