Fix plotting after update

src/batdetect2/evaluate/match.py

@@ -1,4 +1,5 @@
 from collections.abc import Callable, Iterable, Mapping
+from dataclasses import dataclass, field
 from typing import List, Literal, Optional, Tuple
 
 import numpy as np
@@ -340,3 +341,36 @@ def match_predictions_and_annotations(
         )
 
     return matches
+
+
+@dataclass
+class ClassExamples:
+    false_positives: List[MatchEvaluation] = field(default_factory=list)
+    false_negatives: List[MatchEvaluation] = field(default_factory=list)
+    true_positives: List[MatchEvaluation] = field(default_factory=list)
+    cross_triggers: List[MatchEvaluation] = field(default_factory=list)
+
+
+def group_matches(matches: List[MatchEvaluation]) -> ClassExamples:
+    class_examples = ClassExamples()
+
+    for match in matches:
+        gt_class = match.gt_class
+        pred_class = match.pred_class
+
+        if pred_class is None:
+            class_examples.false_negatives.append(match)
+            continue
+
+        if gt_class is None:
+            class_examples.false_positives.append(match)
+            continue
+
+        if gt_class != pred_class:
+            class_examples.cross_triggers.append(match)
+            class_examples.cross_triggers.append(match)
+            continue
+
+        class_examples.true_positives.append(match)
+
+    return class_examples

src/batdetect2/plotting/clips.py

@@ -37,6 +37,10 @@ def plot_clip(
 
     plot_spectrogram(
         spec,
+        start_time=clip.start_time,
+        end_time=clip.end_time,
+        min_freq=preprocessor.min_freq,
+        max_freq=preprocessor.max_freq,
         ax=ax,
         cmap=spec_cmap,
     )

src/batdetect2/plotting/common.py

@@ -3,6 +3,7 @@
 from typing import Optional, Tuple
 
 import matplotlib.pyplot as plt
+import numpy as np
 import torch
 from matplotlib import axes
 
@@ -25,10 +26,20 @@ def create_ax(
 
 def plot_spectrogram(
     spec: torch.Tensor,
+    start_time: float,
+    end_time: float,
+    min_freq: float,
+    max_freq: float,
     ax: Optional[axes.Axes] = None,
     figsize: Optional[Tuple[int, int]] = None,
     cmap="gray",
 ) -> axes.Axes:
     ax = create_ax(ax=ax, figsize=figsize)
-    ax.pcolormesh(spec.numpy(), cmap=cmap)
+
+    ax.pcolormesh(
+        np.linspace(start_time, end_time, spec.shape[-1], endpoint=False),
+        np.linspace(min_freq, max_freq, spec.shape[-2], endpoint=False),
+        spec.numpy(),
+        cmap=cmap,
+    )
     return ax

src/batdetect2/plotting/evaluation.py

@@ -100,7 +100,7 @@ def plot_class_examples(
                 preprocessor=preprocessor,
                 duration=duration,
             )
-        except (ValueError, AssertionError):
+        except (ValueError, AssertionError, RuntimeError):
             continue
 
     for index, match in enumerate(false_positives[:n_examples]):
@@ -112,7 +112,7 @@ def plot_class_examples(
                 preprocessor=preprocessor,
                 duration=duration,
             )
-        except (ValueError, AssertionError):
+        except (ValueError, AssertionError, RuntimeError):
             continue
 
     for index, match in enumerate(false_negatives[:n_examples]):
@@ -124,7 +124,7 @@ def plot_class_examples(
                 preprocessor=preprocessor,
                 duration=duration,
             )
-        except (ValueError, AssertionError):
+        except (ValueError, AssertionError, RuntimeError):
             continue
 
     for index, match in enumerate(cross_triggers[:n_examples]):
@@ -136,7 +136,7 @@ def plot_class_examples(
                 preprocessor=preprocessor,
                 duration=duration,
             )
-        except (ValueError, AssertionError):
+        except (ValueError, AssertionError, RuntimeError):
             continue
 
     return fig