traccuracy.loaders._ctc
Module Contents
Functions
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Create a Graph from DataFrame of CTC info with node attributes. |
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Load a directory of individual frames into a stack. |
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Read the CTC segmentations and track file and create a TrackingGraph. |
Attributes
- traccuracy.loaders._ctc.logger
- traccuracy.loaders._ctc.ctc_to_graph(df: pandas.DataFrame, detections: pandas.DataFrame) networkx.DiGraph[source]
Create a Graph from DataFrame of CTC info with node attributes.
- Parameters:
df (pd.DataFrame) – CTC-style dataframe with columns [segmentation_id, start_frame, end_frame, parent_id]
detections (pd.DataFrame) – Dataframe from _get_node_attributes with position and segmentation label for each cell detection
- Returns:
Graph representation of the CTC data.
- Return type:
networkx.DiGraph
- traccuracy.loaders._ctc.load_tiffs(data_dir: str) numpy.ndarray[source]
Load a directory of individual frames into a stack.
- Parameters:
data_dir (str) – Path to directory of tiff files
- Raises:
FileNotFoundError – No tif files found in data_dir
- Returns:
4D array with dims TYXC
- Return type:
np.array
- traccuracy.loaders._ctc.load_ctc_data(data_dir: str, track_path: str | None = None, name: str | None = None, run_checks: bool = True) traccuracy._tracking_graph.TrackingGraph[source]
Read the CTC segmentations and track file and create a TrackingGraph.
- Parameters:
data_dir (str) – Path to directory containing CTC tiffs.
track_path (optional, str) – Path to CTC track file. If not passed, finds
*_track.txtin data_dir.name (optional, str) – Name of data to store in TrackingGraph
run_checks (optional, bool) – If set to
True(default), runs checks on the data to ensure valid CTC format.
- Returns:
TrackingGraph object containing segmentations and graph.
- Return type:
- Raises:
ValueError – If the tracks file is not found. If
run_checksis True, whenever any of the CTC format checks are violated. Ifrun_checksis False, whenever any other Exception occurs while creating the graph.