diff --git a/commands.md b/commands.md
index f1647c156f117969da9fc5363c27d262c9eeb800..ec78dce2ec0cfb32d3007e1c1920e0b1a86172f0 100644
--- a/commands.md
+++ b/commands.md
@@ -4,3 +4,6 @@ pdoc --html robofish.io robofish.evaluate --html-dir docs --force
## Code coverage:
pytest --cov=src --cov-report=html
+
+## Flake
+flake8 --ignore E203 --max-line-length 88
diff --git a/pyproject.toml b/pyproject.toml
index 57e73c268595219f619cc4da8846d349ab426f21..139acbc7f3d8ee316285ade2c7c1ef2d9efe4eed 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,3 +1,7 @@
[build-system]
# Minimum requirements for the build system to execute.
-requires = ["setuptools", "wheel", "pytest", "pandas", "deprecation"] # PEP 508 specifications.
+requires = ["setuptools", "wheel"] # PEP 508 specifications.
+
+[flake8]
+max-line-length = 88
+extend-ignore = "E203"
diff --git a/src/robofish/evaluate/evaluate.py b/src/robofish/evaluate/evaluate.py
index db339f14f3ef5cbaea23da1cf3ccffa09809f804..6670645a03ce8a6460a6e4febbbc63b3c8e32e74 100644
--- a/src/robofish/evaluate/evaluate.py
+++ b/src/robofish/evaluate/evaluate.py
@@ -1,8 +1,6 @@
# -*- coding: utf-8 -*-
-"""
-Evaluation functions, to generate graphs from files.
-"""
+"""Evaluation functions, to generate graphs from files."""
# Feb 2021 Andreas Gerken, Marc Groeling Berlin, Germany
# Released under GNU 3.0 License
@@ -10,6 +8,8 @@ Evaluation functions, to generate graphs from files.
# Last doku update Feb 2021
import robofish.io
+from pathlib import Path
+
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import seaborn as sns
@@ -20,29 +20,56 @@ from scipy import stats
def get_all_poses_from_paths(paths: Iterable[str]):
- """This function reads all poses from given paths.
-
- # Args:
- # paths: An array of strings, with files or folders
- # Returns:
- # An array, containing poses with the shape [paths][files][entities, timesteps, 4]
- #"""
- # # Open all files, shape (paths, files)
- # files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
-
- # Read all poses from the files, shape (paths, files)
- poses_per_path = [[f.entity_poses for f in files] for files in files_per_path]
-
-
-# # close all files
-# for p in files_per_path:
-# for f in p:
-# f.close()
+ """Read all poses from given paths.
-# return poses_per_path
+ The function shall be used by the evaluation functions.
+ Args:
+ paths: An array of strings, with files or folders.
+ The files are checked to have the same frequency.
+ Returns:
+ An array, containing poses with the shape
+ [paths][files][entities, timesteps, 4],
+ the common frequency of the files
+ """
+ # Open all files, shape (paths, files)
+ files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
-def evaluate_speed(paths, names=None, save_path=None, predicate=None):
+ # Read all poses from the files, shape (paths, files)
+ poses_per_path = [
+ [f.entity_poses for path, f in files_dict.items()]
+ for files_dict in files_per_path
+ ]
+
+ # close all files
+ frequencies = []
+ for files_dict in files_per_path:
+ for path, f in files_dict.items():
+ frequencies.append(f.frequency)
+ f.close()
+
+ # Check that all frequencies are equal
+ assert np.std(frequencies) == 0
+
+ return poses_per_path, frequencies[0]
+
+
+def evaluate_speed(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the speed of the entities as histogram.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
speeds = []
for k, files in enumerate(files_per_path):
@@ -57,10 +84,10 @@ def evaluate_speed(paths, names=None, save_path=None, predicate=None):
path_speeds.extend(e_speeds)
speeds.append(path_speeds)
- if names is None:
- names = paths
+ if labels is None:
+ labels = paths
- plt.hist(speeds, bins=20, label=names, density=True, range=[0, 50])
+ plt.hist(speeds, bins=20, label=labels, density=True, range=[0, 50])
plt.title("Agent speeds")
plt.xlabel("Speed [cm/s]")
plt.ylabel("Frequency")
@@ -75,7 +102,22 @@ def evaluate_speed(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_turn(paths, names=None, save_path=None, predicate=None):
+def evaluate_turn(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the turn angles of the entities as histogram.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
turns = []
for k, files in enumerate(files_per_path):
@@ -91,7 +133,8 @@ def evaluate_turn(paths, names=None, save_path=None, predicate=None):
for e_poses in poses:
# convert ori_x, ori_y to radians
ori_rad = np.arctan2(e_poses[:, 3], e_poses[:, 2])
- # calculate difference, also make it take the "shorter" turn (so that is in range of -pi, pi)
+ # calculate difference, also make it take the "shorter"
+ # turn (so that is in range of -pi, pi)
e_turns = ori_rad[1:] - ori_rad[:-1]
e_turns = np.where(e_turns < -np.pi, e_turns + 2 * np.pi, e_turns)
e_turns = np.where(e_turns > np.pi, e_turns - 2 * np.pi, e_turns)
@@ -100,11 +143,11 @@ def evaluate_turn(paths, names=None, save_path=None, predicate=None):
path_turns.extend(e_turns)
turns.append(path_turns)
- if names is None:
- names = paths
+ if labels is None:
+ labels = paths
# TODO: Quantil range
- plt.hist(turns, bins=40, label=names, density=True, range=[-30, 30])
+ plt.hist(turns, bins=40, label=labels, density=True, range=[-30, 30])
plt.title("Agent turns")
plt.xlabel("Change in orientation [Degree / timestep at %dhz]" % frequency)
plt.ylabel("Frequency")
@@ -119,7 +162,22 @@ def evaluate_turn(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_orientation(paths, names=None, save_path=None, predicate=None):
+def evaluate_orientation(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the orientations of the entities on a 2d grid.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
orientations = []
for k, files in enumerate(files_per_path):
@@ -149,18 +207,18 @@ def evaluate_orientation(paths, names=None, save_path=None, predicate=None):
if len(orientations) == 1:
ax = [ax]
- if names is None:
- names = paths
+ 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 names is None:
+ if labels is None:
ax[i].set_title("Mean orientation in tank")
else:
- ax[i].set_title("Mean orientation in tank (%s)" % names[i])
+ ax[i].set_title("Mean orientation in tank (%s)" % labels[i])
ax[i].set_xlabel("x [cm]")
ax[i].set_ylabel("y [cm]")
@@ -174,7 +232,7 @@ def evaluate_orientation(paths, names=None, save_path=None, predicate=None):
vmax=np.pi,
cmap="twilight",
)
- cbar = plt.colorbar(plot, ax=ax[i], pad=0.015, aspect=10)
+ # cbar = plt.colorbar(plot, ax=ax[i], pad=0.015, aspect=10)
show_values(plot)
if save_path is None:
@@ -184,7 +242,22 @@ def evaluate_orientation(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_relativeOrientation(paths, names=None, save_path=None, predicate=None):
+def evaluate_relativeOrientation(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the relative orientations of the entities as a histogram.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
orientations = []
for k, files in enumerate(files_per_path):
@@ -204,10 +277,10 @@ def evaluate_relativeOrientation(paths, names=None, save_path=None, predicate=No
path_orientations.extend(np.arctan2(ori_diff[1], ori_diff[0]))
orientations.append(path_orientations)
- if names is None:
- names = paths
+ if labels is None:
+ labels = paths
- plt.hist(orientations, bins=40, label=names, density=True, range=[0, np.pi])
+ plt.hist(orientations, bins=40, label=labels, density=True, range=[0, np.pi])
plt.title("Relative orientation")
plt.xlabel("orientation in radians")
plt.ylabel("Frequency")
@@ -222,9 +295,21 @@ def evaluate_relativeOrientation(paths, names=None, save_path=None, predicate=No
plt.close()
-def evaluate_distanceToWall(paths, names=None, save_path=None, predicate=None):
- """
- only works for rectangular tanks
+def evaluate_distanceToWall(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the distances of the entities to the walls as a histogram.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
"""
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
distances = []
@@ -265,13 +350,13 @@ def evaluate_distanceToWall(paths, names=None, save_path=None, predicate=None):
worldBoundsX, worldBoundsY = max(worldBoundsX), max(worldBoundsY)
- if names is None:
- names = paths
+ if labels is None:
+ labels = paths
plt.hist(
distances,
bins=20,
- label=names,
+ label=labels,
density=True,
range=[0, min(worldBoundsX / 2, worldBoundsY / 2)],
)
@@ -289,10 +374,23 @@ def evaluate_distanceToWall(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_tankpositions(paths, names=None, save_path=None, predicate=None):
- """
- Heatmap of fishpositions
- By Moritz Maxeiner
+def evaluate_tankpositions(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the positions of the entities as a heatmap.
+
+ The original implementation is by Moritz Maxeiner.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
"""
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
x_pos, y_pos = [], []
@@ -313,11 +411,11 @@ def evaluate_tankpositions(paths, names=None, save_path=None, predicate=None):
fig, ax = plt.subplots(1, len(x_pos), figsize=(8 * len(x_pos), 8))
if len(x_pos) == 1:
ax = [ax]
- if names is None:
- names = paths
+ if labels is None:
+ labels = paths
for i in range(len(x_pos)):
- ax[i].set_title("Tankpositions (%s)" % names[i])
+ ax[i].set_title("Tankpositions (%s)" % labels[i])
ax[i].set_xlim(-world_bounds[i][0] / 2, world_bounds[i][0] / 2)
ax[i].set_ylim(-world_bounds[i][1] / 2, world_bounds[i][1] / 2)
@@ -330,10 +428,23 @@ def evaluate_tankpositions(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_trajectories(paths, names=None, save_path=None, predicate=None):
- """
- trajectories of fishes
- By Moritz Maxeiner
+def evaluate_trajectories(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the trajectories of the entities.
+
+ The original implementation is by Moritz Maxeiner.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
"""
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
pos = []
@@ -359,15 +470,15 @@ def evaluate_trajectories(paths, names=None, save_path=None, predicate=None):
fig, ax = plt.subplots(1, len(pos), figsize=(len(pos) * 8, 8))
if len(pos) == 1:
ax = [ax]
- if names is None:
- names = paths
+ if labels is None:
+ labels = paths
for i in range(len(pos)):
sns.set_style("white", {"axes.linewidth": 2, "axes.edgecolor": "black"})
sns.scatterplot(
x="x", y="y", hue="Agent", linewidth=0, s=4, data=pos[i][1], ax=ax[i]
)
- ax[i].set_title("Trajectories (%s)" % names[i])
+ ax[i].set_title("Trajectories (%s)" % labels[i])
ax[i].set_xlim(-world_bounds[i][0] / 2, world_bounds[i][0] / 2)
ax[i].set_ylim(-world_bounds[i][1] / 2, world_bounds[i][1] / 2)
ax[i].invert_yaxis()
@@ -400,7 +511,22 @@ def evaluate_trajectories(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_positionVec(paths, names=None, save_path=None, predicate=None):
+def evaluate_positionVec(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the vectors pointing from the focal fish to the conspecifics as heatmap.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
posVec = []
worldBoundsX, worldBoundsY = [], []
@@ -442,7 +568,7 @@ def evaluate_positionVec(paths, names=None, save_path=None, predicate=None):
fig = plt.figure(figsize=(8 * len(grids), 8))
- fig.suptitle("positionVector: from left to right: " + str(names), fontsize=16)
+ fig.suptitle("positionVector: from left to right: " + str(labels), fontsize=16)
gs = gridspec.GridSpec(1, len(grids))
for i in range(len(grids)):
@@ -455,7 +581,24 @@ def evaluate_positionVec(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_follow_iid(paths, names=None, save_path=None, predicate=None):
+def evaluate_follow_iid(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_path: str = None,
+ predicate=None,
+):
+ """Evaluate the follow metric in respect to the inter individual distance (iid).
+
+ The original implementation is from Moritz Maxeiner.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
files_per_path = [robofish.io.read_multiple_files(p) for p in paths]
follow, iid = [], []
worldBoundsX, worldBoundsY = [], []
@@ -510,7 +653,7 @@ def evaluate_follow_iid(paths, names=None, save_path=None, predicate=None):
fig = plt.figure(figsize=(8 * len(grids), 8))
- fig.suptitle("follow/iid: from left to right: " + str(names), fontsize=16)
+ fig.suptitle("follow/iid: from left to right: " + str(labels), fontsize=16)
gs = gridspec.GridSpec(1, len(grids))
for i in range(len(grids)):
@@ -523,23 +666,43 @@ def evaluate_follow_iid(paths, names=None, save_path=None, predicate=None):
plt.close()
-def evaluate_all(paths, names=None, save_folder=None, predicate=None):
- evaluate_speed(paths, names, save_folder + "speed.png", predicate)
- evaluate_turn(paths, names, save_folder + "turn.png", predicate)
- evaluate_orientation(paths, names, save_folder + "orientation.png", predicate)
+def evaluate_all(
+ paths: Iterable[str],
+ labels: Iterable[str] = None,
+ save_folder: str = None,
+ predicate=None,
+):
+ """Generate all evaluation graphs and save them to a folder.
+
+ Args:
+ paths: An array of strings, with files of folders.
+ labels: Labels for the paths. If no labels are given, the paths will
+ be used
+ save_path: A path to a save location.
+ predicate: a lambda function, selecting entities
+ (example: lambda e: e.category == "fish")
+ """
+ save_folder = Path(save_folder)
+ evaluate_speed(paths, labels, save_folder + "speed.png", predicate)
+ evaluate_turn(paths, labels, save_folder + "turn.png", predicate)
+ evaluate_orientation(paths, labels, save_folder + "orientation.png", predicate)
evaluate_relativeOrientation(
- paths, names, save_folder + "relativeOrientation.png", predicate
+ paths, labels, save_folder + "relativeOrientation.png", predicate
+ )
+ evaluate_distanceToWall(
+ paths, labels, save_folder + "distanceToWall.png", predicate
)
- evaluate_distanceToWall(paths, names, save_folder + "distanceToWall.png", predicate)
- evaluate_tankpositions(paths, names, save_folder + "tankpositions.png", predicate)
- evaluate_trajectories(paths, names, save_folder + "trajectories.png", predicate)
- evaluate_positionVec(paths, names, save_folder + "posVec.png", predicate)
- evaluate_follow_iid(paths, names, save_folder + "follow_iid.png", predicate)
+ evaluate_tankpositions(paths, labels, save_folder + "tankpositions.png", predicate)
+ evaluate_trajectories(paths, labels, save_folder + "trajectories.png", predicate)
+ evaluate_positionVec(paths, labels, save_folder + "posVec.png", predicate)
+ evaluate_follow_iid(paths, labels, save_folder + "follow_iid.png", predicate)
def calculate_follow(a, b):
- """
- Given two series of poses - with X and Y coordinates of their positions as the first two elements -
+ """Calculate the follow metric.
+
+ Given two series of poses - with X and Y coordinates of their
+ positions as the first two elements
return the follow metric from the first to the second series.
"""
a_v = a[1:, :2] - a[:-1, :2]
@@ -548,15 +711,18 @@ def calculate_follow(a, b):
def calculate_iid(a, b):
- """
- Given two series of poses - with X and Y coordinates of their positions as the first two elements -
+ """Calculate the iid metric.
+
+ Given two series of poses - with X and Y coordinates of their positions
+ as the first two elements
return the inter-individual distance (between the positions).
"""
return np.linalg.norm(b[:, :2] - a[:, :2], axis=-1)
def normalize_series(x):
- """
+ """Normalize series.
+
Given a series of vectors, return a series of normalized vectors.
Null vectors are mapped to `NaN` vectors.
"""
@@ -564,9 +730,11 @@ def normalize_series(x):
def calculate_posVec(data, angle):
- """
- data should be of the form (n, (x1, y1, x2, y2)) and angle of the form (n, 1)
- returns x, y distance from fish1 to fish2 with respect to the direction fish1 is facing (shape: (n, (x, y)))
+ """Calculate position vectors.
+
+ Data should be of the form (n, (x1, y1, x2, y2)) and angle of the form (n, 1)
+ returns x, y distance from fish1 to fish2 with respect to the direction
+ fish1 is facing (shape: (n, (x, y)))
"""
# rotate axes by angle and adjust x,y of points
temp = np.copy(data)
@@ -579,10 +747,13 @@ def calculate_posVec(data, angle):
def calculate_distLinePoint(x1, y1, x2, y2, points):
- """
- computes distance between line (x1, y1, x2, y2) and points (np array of shape (n, 2), (x,y) on each row)
+ """Compute the distance between a line and points.
+
+ Compute the distance between line (x1, y1, x2, y2) and points
+ (np array of shape (n, 2), (x,y) on each row)
returns np array of shape (n, ) with corresponding distances
- from: https://stackoverflow.com/questions/849211/shortest-distance-between-a-point-and-a-line-segment
+ from: https://stackoverflow.com/questions/849211/
+ shortest-distance-between-a-point-and-a-line-segment
theory: http://paulbourke.net/geometry/pointlineplane/
"""
px = x2 - x1
@@ -607,9 +778,10 @@ def calculate_distLinePoint(x1, y1, x2, y2, points):
def show_values(pc, fmt="%.2f", **kw):
- """
- shows numbers on plt.ax.pccolormesh plot
- https://stackoverflow.com/questions/25071968/heatmap-with-text-in-each-cell-with-matplotlibs-pyplot
+ """Show numbers on plt.ax.pccolormesh plot.
+
+ https://stackoverflow.com/questions/25071968/
+ heatmap-with-text-in-each-cell-with-matplotlibs-pyplot
"""
pc.update_scalarmappable()
ax = pc.axes
@@ -624,11 +796,14 @@ def show_values(pc, fmt="%.2f", **kw):
class SeabornFig2Grid:
- """
- copied from https://stackoverflow.com/questions/35042255/how-to-plot-multiple-seaborn-jointplot-in-subplot
+ """Seaborn Figure class.
+
+ copied from https://stackoverflow.com/questions/35042255/
+ how-to-plot-multiple-seaborn-jointplot-in-subplot
"""
def __init__(self, seaborngrid, fig, subplot_spec):
+ """Init function."""
self.fig = fig
self.sg = seaborngrid
self.subplot = subplot_spec
@@ -641,7 +816,7 @@ class SeabornFig2Grid:
self._finalize()
def _movegrid(self):
- """ Move PairGrid or Facetgrid """
+ """Move PairGrid or Facetgrid."""
self._resize()
n = self.sg.axes.shape[0]
m = self.sg.axes.shape[1]
@@ -651,7 +826,7 @@ class SeabornFig2Grid:
self._moveaxes(self.sg.axes[i, j], self.subgrid[i, j])
def _movejointgrid(self):
- """ Move Jointgrid """
+ """Move Jointgrid."""
h = self.sg.ax_joint.get_position().height
h2 = self.sg.ax_marg_x.get_position().height
r = int(np.round(h / h2))
@@ -665,7 +840,11 @@ class SeabornFig2Grid:
self._moveaxes(self.sg.ax_marg_y, self.subgrid[1:, -1])
def _moveaxes(self, ax, gs):
- # https://stackoverflow.com/a/46906599/4124317
+ """
+ Move axes.
+
+ https://stackoverflow.com/a/46906599/4124317
+ """
ax.remove()
ax.figure = self.fig
self.fig.axes.append(ax)
@@ -675,9 +854,11 @@ class SeabornFig2Grid:
ax.set_subplotspec(gs)
def _finalize(self):
+ """Finalize the graphics."""
plt.close(self.sg.fig)
self.fig.canvas.mpl_connect("resize_event", self._resize)
self.fig.canvas.draw()
def _resize(self, evt=None):
+ """Resize the graphics."""
self.sg.fig.set_size_inches(self.fig.get_size_inches())
diff --git a/src/robofish/io/validation.py b/src/robofish/io/validation.py
index 0e1ae54889dcbe9a674e19187ff6128d33889c84..8ea10175c7fed8d0e4a813856290116d86d83b54 100644
--- a/src/robofish/io/validation.py
+++ b/src/robofish/io/validation.py
@@ -334,13 +334,18 @@ def validate_positions_range(world_size, positions, e_name):
def validate_orientations_length(orientations, e_name):
ori_lengths = np.linalg.norm(orientations, axis=1)
+ # import matplotlib.pyplot as plt
+ #
+ # plt.plot(ori_lengths)
+ # plt.show()
+
# Check if all orientation lengths are all 1. Different lengths cause warnings.
assert_validate(
np.isclose(ori_lengths, 1).all(),
- "The orientation vectors were not unit vectors. Their length was in the range [%.2f, %.2f] when it should be 1"
+ "The orientation vectors were not unit vectors. Their length was in the range [%.4f, %.4f] when it should be 1"
% (min(ori_lengths), max(ori_lengths)),
e_name,
- strict_validate=False,
+ strict_validate=True,
)
diff --git a/tests/robofish/evaluate/test_evaluate.py b/tests/robofish/evaluate/test_evaluate.py
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..65aa7271cff6a82026cf38620a1fd68220656446 100644
--- a/tests/robofish/evaluate/test_evaluate.py
+++ b/tests/robofish/evaluate/test_evaluate.py
@@ -0,0 +1,13 @@
+import pytest
+import robofish.evaluate
+from robofish.io import utils
+import numpy as np
+
+
+def test_get_all_poses_from_paths():
+ valid_file_path = utils.full_path(__file__, "../../resources/valid.hdf5")
+ poses, frequency = robofish.evaluate.get_all_poses_from_paths([valid_file_path])
+
+ # (1 input array, 1 file, 2 fishes, 100 timesteps, 4 poses)
+ assert np.array(poses).shape == (1, 1, 2, 100, 4)
+ assert frequency == 25
diff --git a/tests/robofish/io/test_examples.py b/tests/robofish/io/test_examples.py
index c81b1eed99221e9d92a82f0d354352fa869cfbae..82ea16dd4153f2449a52be691d457d3bf25df827 100644
--- a/tests/robofish/io/test_examples.py
+++ b/tests/robofish/io/test_examples.py
@@ -1,7 +1,7 @@
import robofish.io
from robofish.io import utils
from pathlib import Path
-from testbook import testbook
+
import sys
@@ -29,6 +29,8 @@ def test_example_basic():
# This test can be executed manually. The CI/CD System has issues with testbook.
def manual_test_example_basic_ipynb():
+ from testbook import testbook
+
# Executing the notebook should not lead to an exception
with testbook(str(ipynb_path), execute=True) as tb:
pass