diff --git a/src/napatrackmater/Trackmate.py b/src/napatrackmater/Trackmate.py index 57e447b1..fd950c41 100644 --- a/src/napatrackmater/Trackmate.py +++ b/src/napatrackmater/Trackmate.py @@ -43,7 +43,7 @@ def __init__( mask: np.ndarray = None, fourier=True, autoencoder_model=None, - enhance_trackmate_xml:bool=True, + enhance_trackmate_xml: bool = True, num_points=2048, batch_size=1, compute_with_autoencoder=False, @@ -67,7 +67,7 @@ def __init__( self.oneat_csv_file = oneat_csv_file self.oneat_threshold_cutoff = oneat_threshold_cutoff self.latent_features = latent_features - + if image is not None: self.image = image.astype(np.uint8) else: @@ -81,7 +81,9 @@ def __init__( self.autoencoder_model = autoencoder_model if self.autoencoder_model is not None: - self.pretrainer = Trainer(accelerator=self.accelerator, devices=self.devices) + self.pretrainer = Trainer( + accelerator=self.accelerator, devices=self.devices + ) else: self.pretrainer = None self.enhance_trackmate_xml = enhance_trackmate_xml @@ -501,7 +503,11 @@ def _create_generations(self, all_source_ids: list): if len(list(self.oneat_dividing_tracks.keys())) > 1: for cell_id in list(self.oneat_dividing_tracks.keys()): - if cell_id in all_source_ids and cell_id not in root_splits and cell_id not in root_leaf: + if ( + cell_id in all_source_ids + and cell_id not in root_splits + and cell_id not in root_leaf + ): root_splits.append(cell_id) return root_root, root_splits, root_leaf @@ -596,7 +602,6 @@ def _iterate_dividing_recursive( tracklet_count = self._unique_tracklet_count( tracklet_count_taken, tracklet_count ) - print(next_gen_count, tracklet_count, len(target_cells), sorted_root_splits) tracklet_count_taken.append(tracklet_count) self._iterate_dividing_recursive( root_leaf, @@ -676,9 +681,9 @@ def _iterate_dividing(self, root_root, root_leaf, root_splits): def _unique_tracklet_count(self, tracklet_count_taken, tracklet_count): while tracklet_count in tracklet_count_taken: - tracklet_count += 1 + tracklet_count += 1 if tracklet_count not in tracklet_count_taken: - break + break return tracklet_count def _iterate_split_down(self, root_root, root_leaf, root_splits): @@ -1710,7 +1715,9 @@ def _get_xml_data(self): self.channel_xml_name = new_name + ".xml" self.channel_xml_path = os.path.dirname(self.xml_path) self._create_channel_tree() - if (self.autoencoder_model is not None or self.enhance_trackmate_xml )and self.seg_image is not None: + if ( + self.autoencoder_model is not None or self.enhance_trackmate_xml + ) and self.seg_image is not None: self.master_xml_content = self.xml_content self.master_xml_tree = et.parse(self.xml_path) self.master_xml_root = self.master_xml_tree.getroot() @@ -1833,7 +1840,9 @@ def _get_xml_data(self): and self.edges_csv_path is not None ): self._get_attributes() - if (self.autoencoder_model or self.enhance_trackmate_xml) and self.seg_image is not None: + if ( + self.autoencoder_model or self.enhance_trackmate_xml + ) and self.seg_image is not None: print("Getting clouds") self._assign_cluster_class() @@ -2398,7 +2407,6 @@ def _compute_phenotypes(self): current_motion_angle_x, current_acceleration, current_distance_cell_mask, - current_radial_angle_z, current_radial_angle_y, current_radial_angle_x, @@ -3108,8 +3116,6 @@ def get_largest_size(timed_cell_size): return largest_size - - def compute_cell_size(seg_image): ndim = len(seg_image.shape) timed_cell_size = {} @@ -3131,7 +3137,7 @@ def compute_cell_size(seg_image): timed_cell_size[str(i)] = float(largest_size.feret_diameter_max) except ValueError as e: print(f"Skipping at index {i}: {e}") - + continue return timed_cell_size diff --git a/src/napatrackmater/_version.py b/src/napatrackmater/_version.py index 1315f902..d9984a37 100644 --- a/src/napatrackmater/_version.py +++ b/src/napatrackmater/_version.py @@ -1,2 +1,2 @@ -__version__ = version = "5.1.5" -__version_tuple__ = version_tuple = (5, 1, 5) +__version__ = version = "5.1.6" +__version_tuple__ = version_tuple = (5, 1, 6)