From bc5ea988c98fa8888230ecaea61455d7ccd075d9 Mon Sep 17 00:00:00 2001
From: Andi <andi.gerken@gmail.com>
Date: Thu, 27 Mar 2025 11:33:19 +0100
Subject: [PATCH] Added evaluation to show all tracks in one plot.
---
src/robofish/evaluate/app.py | 1 +
src/robofish/evaluate/evaluate.py | 32 +++++++++++++++++++++++++++++++
2 files changed, 33 insertions(+)
diff --git a/src/robofish/evaluate/app.py b/src/robofish/evaluate/app.py
index 78697fd..ba38642 100644
--- a/src/robofish/evaluate/app.py
+++ b/src/robofish/evaluate/app.py
@@ -37,6 +37,7 @@ def function_dict() -> dict:
"follow_iid": base.evaluate_follow_iid,
"individual_speed": base.evaluate_individual_speed,
"individual_iid": base.evaluate_individual_iid,
+ "single_plot_tracks": base.evaluate_single_plot_tracks,
# "quiver": base.evaluate_quiver, # Quiver has issues with multiple paths and raises exceptions. The function is not used for now.
"all": base.evaluate_all,
}
diff --git a/src/robofish/evaluate/evaluate.py b/src/robofish/evaluate/evaluate.py
index 793eb31..79c85f0 100644
--- a/src/robofish/evaluate/evaluate.py
+++ b/src/robofish/evaluate/evaluate.py
@@ -627,6 +627,38 @@ def evaluate_quiver(
return fig
+def evaluate_single_plot_tracks(
+ paths: Iterable[Union[str, Path]],
+ labels: Iterable[str] = None,
+ predicate: Callable[[robofish.io.Entity], bool] = None,
+ poses_from_paths: Iterable[Iterable[np.ndarray]] = None,
+ max_files: int = None,
+):
+ """Evaluate the tracks of the entities as a plot."""
+ if poses_from_paths is None:
+ poses_from_paths, file_settings = utils.get_all_poses_from_paths(
+ paths, predicate, max_files=max_files
+ )
+
+ fig, ax = plt.subplots(
+ 1, len(poses_from_paths), figsize=(8 * len(poses_from_paths), 8)
+ )
+ if len(poses_from_paths) == 1:
+ ax = [ax]
+
+ cmap = plt.get_cmap("Blues")
+ for i, poses_per_path in enumerate(poses_from_paths):
+ for fi, poses in enumerate(poses_per_path):
+ for e in poses:
+ ax[i].plot(
+ e[:, 0], e[:, 1], c=cmap(fi / len(poses_per_path)), alpha=0.5
+ )
+ ax[i].set_title(labels[i])
+ ax[i].set_xlabel("x [cm]")
+ ax[i].set_ylabel("y [cm]")
+ return fig
+
+
def evaluate_social_vector(
paths: Iterable[Union[str, Path]],
labels: Iterable[str] = None,
--
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