[Fix] All thresholds, Increase Batch Predict Limit, Make "Back" Button on error page trigger a new pageload. (#432)

Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#432

epdb/models.py

@@ -3003,7 +3003,14 @@ class PackageBasedModel(EPModel):
 
             prec, rec = dict(), dict()
 
-            for t in np.arange(0, 1.05, 0.05):
+            thresholds = list(np.arange(0, 1.05, 0.05))
+
+            # Add specific threshold set during object creation if not already present
+            if np.float64(threshold) not in thresholds:
+                thresholds.append(np.float64(threshold))
+                thresholds.sort()
+
+            for t in thresholds:
                 temp_thresholded = (y_pred_filtered >= t).astype(int)
                 prec[f"{t:.2f}"] = precision_score(
                     y_test_filtered, temp_thresholded, zero_division=0
@@ -3013,7 +3020,14 @@ class PackageBasedModel(EPModel):
             return acc, prec, rec
 
         def evaluate_mg(model, pathways: Union[QuerySet["Pathway"] | List["Pathway"]], threshold):
-            thresholds = np.arange(0.1, 1.1, 0.1)
+            thresholds = list(np.arange(0, 1.05, 0.05))
+
+            # Add specific threshold set during object creation if not already present
+            if np.float64(threshold) not in thresholds:
+                thresholds.append(np.float64(threshold))
+                thresholds.sort()
+
+            logger.info(f"Thresholds: {thresholds}")
 
             precision = {f"{t:.2f}": [] for t in thresholds}
             recall = {f"{t:.2f}": [] for t in thresholds}
@@ -3039,7 +3053,7 @@ class PackageBasedModel(EPModel):
 
             s = Setting()
             s.model = mod
-            s.model_threshold = thresholds.min()
+            s.model_threshold = 0.0
             s.max_depth = 10
             s.max_nodes = 50