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<section id="deepof-utils-module">
<h1>deepof.utils module<a class="headerlink" href="#deepof-utils-module" title="Permalink to this heading"></a></h1>
<table class="autosummary longtable docutils align-default">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.html#module-deepof.utils" title="deepof.utils"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils</span></code></a></p></td>
<td><p>Functions and general utilities for the deepof package.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.align_trajectories.html#deepof.utils.align_trajectories" title="deepof.utils.align_trajectories"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.align_trajectories</span></code></a>(data[, mode])</p></td>
<td><p>Remove rotational variance on the trajectories.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.angle.html#deepof.utils.angle" title="deepof.utils.angle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.angle</span></code></a>(bpart_array)</p></td>
<td><p>Return a numpy.ndarray with the angles between the provided instances.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.arena_parameter_extraction.html#deepof.utils.arena_parameter_extraction" title="deepof.utils.arena_parameter_extraction"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.arena_parameter_extraction</span></code></a>(...)</p></td>
<td><p>Return x,y position of the center, the lengths of the major and minor axes, and the angle of the recognised arena.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.automatically_recognize_arena.html#deepof.utils.automatically_recognize_arena" title="deepof.utils.automatically_recognize_arena"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.automatically_recognize_arena</span></code></a>(...)</p></td>
<td><p>Return numpy.ndarray with information about the arena recognised from the first frames of the video.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.bp2polar.html#deepof.utils.bp2polar" title="deepof.utils.bp2polar"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.bp2polar</span></code></a>(tab)</p></td>
<td><p>Return the DataFrame in polar coordinates.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.bpart_distance.html#deepof.utils.bpart_distance" title="deepof.utils.bpart_distance"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.bpart_distance</span></code></a>(dataframe[, ...])</p></td>
<td><p>Return a pandas.DataFrame with the scaled distances between all pairs of body parts.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.closest_side.html#deepof.utils.closest_side" title="deepof.utils.closest_side"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.closest_side</span></code></a>(polygon, ...)</p></td>
<td><p>Find the closest side in other polygons to a reference side in the first polygon.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.cluster_transition_matrix.html#deepof.utils.cluster_transition_matrix" title="deepof.utils.cluster_transition_matrix"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.cluster_transition_matrix</span></code></a>(...)</p></td>
<td><p>Compute the transition matrix between clusters and the autocorrelation in the sequence.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.compute_animal_presence_mask.html#deepof.utils.compute_animal_presence_mask" title="deepof.utils.compute_animal_presence_mask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.compute_animal_presence_mask</span></code></a>(quality)</p></td>
<td><p>Compute a mask of the animal presence in the video.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.compute_areas.html#deepof.utils.compute_areas" title="deepof.utils.compute_areas"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.compute_areas</span></code></a>(polygon_xy_stack)</p></td>
<td><p>Compute polygon areas for the provided stack of sets of data point-xy coordinates.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.compute_dist.html#deepof.utils.compute_dist" title="deepof.utils.compute_dist"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.compute_dist</span></code></a>(pair_array[, ...])</p></td>
<td><p>Return a pandas.DataFrame with the scaled distances between a pair of body parts.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.connect_mouse.html#deepof.utils.connect_mouse" title="deepof.utils.connect_mouse"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.connect_mouse</span></code></a>([animal_ids, ...])</p></td>
<td><p>Create a nx.Graph object with the connectivity of the bodyparts in the DLC topview model for a single mouse.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.edges_to_weighted_adj.html#deepof.utils.edges_to_weighted_adj" title="deepof.utils.edges_to_weighted_adj"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.edges_to_weighted_adj</span></code></a>(adj, edges)</p></td>
<td><p>Convert an edge feature matrix to a weighted adjacency matrix.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.enumerate_all_bridges.html#deepof.utils.enumerate_all_bridges" title="deepof.utils.enumerate_all_bridges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.enumerate_all_bridges</span></code></a>(G)</p></td>
<td><p>Enumerate all 3-node connected sequences in the given graph.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.extract_polygonal_arena_coordinates.html#deepof.utils.extract_polygonal_arena_coordinates" title="deepof.utils.extract_polygonal_arena_coordinates"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.extract_polygonal_arena_coordinates</span></code></a>(...)</p></td>
<td><p>Read a random frame from the selected video, and opens an interactive GUI to let the user delineate the arena manually.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.filter_columns.html#deepof.utils.filter_columns" title="deepof.utils.filter_columns"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.filter_columns</span></code></a>(columns, selected_id)</p></td>
<td><p>Given a set of TableDict columns, returns those that correspond to a given animal, specified in selected_id.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.filter_short_bouts.html#deepof.utils.filter_short_bouts" title="deepof.utils.filter_short_bouts"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.filter_short_bouts</span></code></a>(...[, ...])</p></td>
<td><p>Filter out cluster assignment bouts shorter than min_bout_duration.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.fit_ellipse_to_polygon.html#deepof.utils.fit_ellipse_to_polygon" title="deepof.utils.fit_ellipse_to_polygon"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.fit_ellipse_to_polygon</span></code></a>(polygon)</p></td>
<td><p>Fit an ellipse to the provided polygon.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.full_outlier_mask.html#deepof.utils.full_outlier_mask" title="deepof.utils.full_outlier_mask"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.full_outlier_mask</span></code></a>(experiment, ...)</p></td>
<td><p>Iterate over all body parts of experiment, and outputs a dataframe where all x, y positions are replaced by a boolean mask, where True indicates an outlier.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.get_arenas.html#deepof.utils.get_arenas" title="deepof.utils.get_arenas"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.get_arenas</span></code></a>(coordinates, tables, ...)</p></td>
<td><p>Extract arena parameters from a project or coordinates object.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.gmm_compute.html#deepof.utils.gmm_compute" title="deepof.utils.gmm_compute"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.gmm_compute</span></code></a>(x, n_components, ...)</p></td>
<td><p>Fit a Gaussian Mixture Model to the provided data and returns evaluation metrics.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.gmm_model_selection.html#deepof.utils.gmm_model_selection" title="deepof.utils.gmm_model_selection"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.gmm_model_selection</span></code></a>(x, ...[, ...])</p></td>
<td><p>Run GMM clustering model selection on the specified X dataframe.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.interpolate_outliers.html#deepof.utils.interpolate_outliers" title="deepof.utils.interpolate_outliers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.interpolate_outliers</span></code></a>(...[, ...])</p></td>
<td><p>Mark all outliers in experiment and replaces them using a uni-variate linear interpolation approach.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.iterative_imputation.html#deepof.utils.iterative_imputation" title="deepof.utils.iterative_imputation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.iterative_imputation</span></code></a>(project, ...)</p></td>
<td><p>Perform iterative imputation on occluded body parts.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.kleinberg.html#deepof.utils.kleinberg" title="deepof.utils.kleinberg"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.kleinberg</span></code></a>(offsets[, s, gamma, ...])</p></td>
<td><p>Apply Kleinberg's algorithm (described in 'Bursty and Hierarchical Structure in Streams').</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.load_segmentation_model.html#deepof.utils.load_segmentation_model" title="deepof.utils.load_segmentation_model"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.load_segmentation_model</span></code></a>(path)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.load_table.html#deepof.utils.load_table" title="deepof.utils.load_table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.load_table</span></code></a>(tab, table_path, ...)</p></td>
<td><p>Loads a table into a structured pandas data frame.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.mask_outliers.html#deepof.utils.mask_outliers" title="deepof.utils.mask_outliers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.mask_outliers</span></code></a>(time_series, ...)</p></td>
<td><p>Return a mask over the bivariate trajectory of a body part, identifying as True all detected outliers.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.moving_average.html#deepof.utils.moving_average" title="deepof.utils.moving_average"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.moving_average</span></code></a>(time_series[, lag])</p></td>
<td><p>Fast implementation of a moving average function.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.rename_track_bps.html#deepof.utils.rename_track_bps" title="deepof.utils.rename_track_bps"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.rename_track_bps</span></code></a>(loaded_tab, ...)</p></td>
<td><p>Renames all body parts in the provided dataframe.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.retrieve_corners_from_image.html#deepof.utils.retrieve_corners_from_image" title="deepof.utils.retrieve_corners_from_image"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.retrieve_corners_from_image</span></code></a>(...)</p></td>
<td><p>Open a window and waits for the user to click on all corners of the polygonal arena.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.rolling_speed.html#deepof.utils.rolling_speed" title="deepof.utils.rolling_speed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.rolling_speed</span></code></a>(dframe[, window, ...])</p></td>
<td><p>Return the average speed over n frames in pixels per frame.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.rolling_window.html#deepof.utils.rolling_window" title="deepof.utils.rolling_window"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.rolling_window</span></code></a>(a, window_size, ...)</p></td>
<td><p>Return a 3D numpy.array with a sliding-window extra dimension.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.rotate.html#deepof.utils.rotate" title="deepof.utils.rotate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.rotate</span></code></a>(p, angles[, origin])</p></td>
<td><p>Return a 2D numpy.ndarray with the initial values rotated by angles radians.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.rupture_per_experiment.html#deepof.utils.rupture_per_experiment" title="deepof.utils.rupture_per_experiment"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.rupture_per_experiment</span></code></a>(...[, ...])</p></td>
<td><p>Apply the rupture method independently to each experiment, and concatenate into a single dataset at the end.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.scale_animal.html#deepof.utils.scale_animal" title="deepof.utils.scale_animal"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.scale_animal</span></code></a>(feature_array, scale)</p></td>
<td><p>Scales features in the provided array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.scale_table.html#deepof.utils.scale_table" title="deepof.utils.scale_table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.scale_table</span></code></a>(coordinates, ...[, ...])</p></td>
<td><p>Scales features in a table controlling for both individual body size and interanimal variability.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.set_missing_animals.html#deepof.utils.set_missing_animals" title="deepof.utils.set_missing_animals"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.set_missing_animals</span></code></a>(...[, ...])</p></td>
<td><p>Set the coordinates of the missing animals to NaN.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.simplify_polygon.html#deepof.utils.simplify_polygon" title="deepof.utils.simplify_polygon"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.simplify_polygon</span></code></a>(polygon[, ...])</p></td>
<td><p>Simplify a polygon using the Ramer-Douglas-Peucker algorithm.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.smooth_boolean_array.html#deepof.utils.smooth_boolean_array" title="deepof.utils.smooth_boolean_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.smooth_boolean_array</span></code></a>(a[, scale])</p></td>
<td><p>Return a boolean array in which isolated appearances of a feature are smoothed.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.smooth_mult_trajectory.html#deepof.utils.smooth_mult_trajectory" title="deepof.utils.smooth_mult_trajectory"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.smooth_mult_trajectory</span></code></a>(series)</p></td>
<td><p>Return a smoothed a trajectory using a Savitzky-Golay 1D filter.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.split_with_breakpoints.html#deepof.utils.split_with_breakpoints" title="deepof.utils.split_with_breakpoints"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.split_with_breakpoints</span></code></a>(a, ...)</p></td>
<td><p>Split a numpy.ndarray at the given breakpoints.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="_generated/deepof.utils.str2bool.html#deepof.utils.str2bool" title="deepof.utils.str2bool"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.str2bool</span></code></a>(v)</p></td>
<td><p>Return the passed string as a boolean.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="_generated/deepof.utils.tab2polar.html#deepof.utils.tab2polar" title="deepof.utils.tab2polar"><code class="xref py py-obj docutils literal notranslate"><span class="pre">deepof.utils.tab2polar</span></code></a>(cartesian_df)</p></td>
<td><p>Return a pandas.DataFrame in which all the coordinates are polar.</p></td>
</tr>
</tbody>
</table>
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