Initial commit

A题/ZJ_v2/validation.py

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+"""
+Validation utilities for figure quality control
+"""
+
+import os
+import numpy as np
+from scipy import stats
+
+def validate_figure_output(fig_num, output_files, computed_metrics, validation_flags, config):
+    """
+    Validate figure output against quality thresholds
+    
+    Args:
+        fig_num: Figure number (1-15)
+        output_files: List of generated file paths
+        computed_metrics: Dictionary of computed metrics
+        validation_flags: Dictionary of boolean validation flags
+        config: Configuration dictionary with validation thresholds
+        
+    Returns:
+        dict: Validation result with pass/fail status
+    """
+    
+    result = {
+        "figure": f"Fig{fig_num:02d}",
+        "output_files": output_files,
+        "metrics": computed_metrics,
+        "flags": validation_flags,
+        "pass": True,
+        "errors": []
+    }
+    
+    # Check file existence
+    for filepath in output_files:
+        if not os.path.exists(filepath):
+            result["pass"] = False
+            result["errors"].append(f"File not found: {filepath}")
+        elif os.path.getsize(filepath) == 0:
+            result["pass"] = False
+            result["errors"].append(f"Empty file: {filepath}")
+    
+    # Figure-specific validation
+    validation_thresholds = config.get('validation', {})
+    
+    if fig_num == 3:  # OCV fitting
+        r2 = computed_metrics.get('r2', 0)
+        r2_min = validation_thresholds.get('fig03_r2_min', 0.99)
+        if r2 < r2_min:
+            result["pass"] = False
+            result["errors"].append(f"R² too low: {r2:.4f} < {r2_min}")
+    
+    elif fig_num == 7:  # Baseline validation
+        v_i_corr = computed_metrics.get('v_i_correlation', 0)
+        corr_max = validation_thresholds.get('fig07_v_i_corr_max', -0.5)
+        if v_i_corr > corr_max:
+            result["pass"] = False
+            result["errors"].append(f"V-I correlation not negative enough: {v_i_corr:.3f} > {corr_max}")
+    
+    elif fig_num == 9:  # Scenario comparison
+        if 'delta_tte_match' in validation_flags:
+            if not validation_flags['delta_tte_match']:
+                result["pass"] = False
+                result["errors"].append("ΔTTE annotation mismatch")
+    
+    elif fig_num == 13:  # Survival curve
+        if 'survival_monotonic' in validation_flags:
+            if not validation_flags['survival_monotonic']:
+                result["pass"] = False
+                result["errors"].append("Survival curve not monotonic")
+    
+    return result
+
+def compute_r2(y_true, y_pred):
+    """Compute R-squared coefficient of determination"""
+    ss_res = np.sum((y_true - y_pred) ** 2)
+    ss_tot = np.sum((y_true - np.mean(y_true)) ** 2)
+    return 1 - (ss_res / ss_tot)
+
+def check_monotonic_decreasing(arr):
+    """Check if array is monotonically decreasing"""
+    return np.all(np.diff(arr) <= 0)