diff --git a/src/robofish/evaluate/app.py b/src/robofish/evaluate/app.py
index 97e3fdd8b040cf0d802eef6c05e714c8af3c8201..cd52952f1431b8744e394a5feb1466057c2881e1 100644
--- a/src/robofish/evaluate/app.py
+++ b/src/robofish/evaluate/app.py
@@ -28,7 +28,7 @@ def function_dict():
"tracks_distance": base.evaluate_tracks_distance,
"evaluate_positionVec": base.evaluate_positionVec,
"follow_iid": base.evaluate_follow_iid,
- "avg_speeds": base.evaluate_avg_speed,
+ "individual_speeds": base.evaluate_individual_speeds,
"all": base.evaluate_all,
}
@@ -74,7 +74,7 @@ def evaluate(args=None):
help="The paths to files or folders. Multiple paths can be given to compare experiments.",
)
parser.add_argument(
- "--names",
+ "--labels",
type=str,
nargs="+",
help="Names, that should be used in the graphs instead of the pahts.",
@@ -96,8 +96,11 @@ def evaluate(args=None):
raise Exception("When the analysis type is all, a path must be given.")
if args.analysis_type in fdict:
+ if args.labels is None:
+ args.labels = args.paths
+
save_path = None if args.save_path is None else Path(args.save_path)
- params = {"paths": args.paths, "labels": args.names}
+ params = {"paths": args.paths, "labels": args.labels}
if args.analysis_type == "all":
normal_functions = function_dict()
normal_functions.pop("all")
diff --git a/src/robofish/evaluate/evaluate.py b/src/robofish/evaluate/evaluate.py
index 2596b22182dbf072e5f68ebba6b978f30afc6e2d..60c6e7fc1fc22180a1279921a7a3b8ca33cb14bf 100644
--- a/src/robofish/evaluate/evaluate.py
+++ b/src/robofish/evaluate/evaluate.py
@@ -92,9 +92,6 @@ def evaluate_speed(
right_quantiles.append(np.quantile(path_speeds, 0.999))
speeds.append(path_speeds)
- if labels is None:
- labels = paths
-
fig = plt.figure()
plt.hist(
list(speeds),
@@ -147,9 +144,6 @@ def evaluate_turn(
right_quantiles.append(np.quantile(path_turns, 0.999))
turns.append(path_turns)
- if labels is None:
- labels = paths
-
fig = plt.figure()
plt.hist(
turns,
@@ -212,18 +206,12 @@ def evaluate_orientation(
if len(orientations) == 1:
ax = [ax]
- if labels is None:
- labels = paths
-
for i in range(len(orientations)):
orientation = orientations[i]
s_1, x_edges, y_edges, bnr = orientation[0]
s_2, x_edges, y_edges, bnr = orientation[1]
- if labels is None:
- ax[i].set_title("Mean orientation in tank")
- else:
- ax[i].set_title("Mean orientation in tank (%s)" % labels[i])
+ ax[i].set_title("Mean orientation in tank (%s)" % labels[i])
ax[i].set_xlabel("x [cm]")
ax[i].set_ylabel("y [cm]")
@@ -278,9 +266,6 @@ def evaluate_relative_orientation(
file.close()
orientations.append(path_orientations)
- if labels is None:
- labels = paths
-
fig = plt.figure()
plt.hist(orientations, bins=40, label=labels, density=True, range=[0, np.pi])
plt.title("Relative orientation")
@@ -347,9 +332,6 @@ def evaluate_distanceToWall(
worldBoundsX, worldBoundsY = max(worldBoundsX), max(worldBoundsY)
- if labels is None:
- labels = paths
-
fig = plt.figure()
plt.hist(
distances,
@@ -405,8 +387,6 @@ def evaluate_tankpositions(
fig, ax = plt.subplots(1, len(x_pos), figsize=(8 * len(x_pos), 8))
if len(x_pos) == 1:
ax = [ax]
- if labels is None:
- labels = paths
for i in range(len(x_pos)):
ax[i].set_title("Tankpositions (%s)" % labels[i])
@@ -587,6 +567,7 @@ def evaluate_tracks(
labels: Iterable[str] = None,
predicate=None,
lw_distances=False,
+ seed=42,
):
"""Evaluate the track.
@@ -598,7 +579,7 @@ def evaluate_tracks(
(example: lambda e: e.category == "fish")
"""
- random.seed()
+ random.seed(seed)
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
max_files_per_path = max([len(files) for files in files_per_path])
@@ -632,13 +613,13 @@ def evaluate_tracks(
return fig
-def evaluate_avg_speed(
+def evaluate_individual_speeds(
paths: Iterable[str],
labels: Iterable[str] = None,
predicate=None,
lw_distances=False,
):
- """Evaluate the track.
+ """Evaluate the average speeds per individual.
Args:
paths: An array of strings, with files of folders.
@@ -652,9 +633,6 @@ def evaluate_avg_speed(
fig = plt.figure(figsize=(10, 4))
- if labels is None:
- labels = paths
-
offset = 0
for k, files in enumerate(files_per_path):
all_avg_speeds = []
diff --git a/tests/robofish/evaluate/test_app_evaluate.py b/tests/robofish/evaluate/test_app_evaluate.py
index ac3d8c084d85f5525ea48c45abcd2c58f5ddc3c7..5a89d399dffde8ced6002c35782abbba629fdbae 100644
--- a/tests/robofish/evaluate/test_app_evaluate.py
+++ b/tests/robofish/evaluate/test_app_evaluate.py
@@ -22,6 +22,7 @@ def test_app_validate(tmp_path):
self.names = None
self.analysis_type = analysis_type
self.save_path = save_path
+ self.labels = None
for mode in app.function_dict().keys():
if mode == "all":
diff --git a/tests/robofish/io/test_file.py b/tests/robofish/io/test_file.py
index c4d800fc9f48465f65c3a86ee9558b9a0b30fe84..aa30a26af3dfc6db0acd4820d653428db572d9e6 100644
--- a/tests/robofish/io/test_file.py
+++ b/tests/robofish/io/test_file.py
@@ -39,7 +39,7 @@ def test_missing_attribute():
sf.close()
-def test_single_entity_monotonic_step():
+def test_single_entity_frequency_hz():
sf = robofish.io.File(world_size_cm=[100, 100], frequency_hz=(1000 / 40))
test_poses = np.ones(shape=(10, 4))
test_poses[:, 3] = 0 # All Fish pointing right
@@ -51,9 +51,10 @@ def test_single_entity_monotonic_step():
def test_single_entity_monotonic_time_points_us():
- sf = robofish.io.File(
- world_size_cm=[100, 100], monotonic_time_points_us=np.ones(10)
- )
+ with pytest.warns(Warning):
+ sf = robofish.io.File(
+ world_size_cm=[100, 100], monotonic_time_points_us=np.ones(10)
+ )
test_poses = np.ones(shape=(10, 4))
test_poses[:, 3] = 0 # All Fish pointing right
sf.create_entity("robofish", poses=test_poses)
@@ -72,7 +73,10 @@ def test_multiple_entities():
m_points = np.arange(timesteps)
- sf = robofish.io.File(world_size_cm=[100, 100], monotonic_time_points_us=m_points)
+ with pytest.warns(Warning):
+ sf = robofish.io.File(
+ world_size_cm=[100, 100], monotonic_time_points_us=m_points
+ )
returned_entities = sf.create_multiple_entities("fish", poses)
returned_names = [entity.name for entity in returned_entities]
@@ -115,9 +119,10 @@ def test_multiple_entities():
c_points[:5] = "2020-12-02T10:21:58.100000+00:00"
c_points[5:] = robofish.io.now_iso8061()
- new_sampling = sf.create_sampling(
- monotonic_time_points_us=m_points, calendar_time_points=c_points
- )
+ with pytest.warns(Warning):
+ new_sampling = sf.create_sampling(
+ monotonic_time_points_us=m_points, calendar_time_points=c_points
+ )
returned_names = sf.create_multiple_entities(
"fish", poses, outlines=outlines, sampling=new_sampling