napari_track_edit.motile.backend.motile_run
Attributes
Classes
An object representing a motile tracking run. Contains a name, |
Module Contents
- napari_track_edit.motile.backend.motile_run.STAMP_FORMAT = '%m%d%Y_%H%M%S'
- napari_track_edit.motile.backend.motile_run.PARAMS_FILENAME = 'solver_params.json'
- napari_track_edit.motile.backend.motile_run.IN_POINTS_FILENAME = 'input_points.npy'
- napari_track_edit.motile.backend.motile_run.GAPS_FILENAME = 'gaps.txt'
- napari_track_edit.motile.backend.motile_run.ATTRS_FILENAME = 'attrs.json'
- napari_track_edit.motile.backend.motile_run._TRACKSDATA_INTERNAL_EDGE_KEYS
- class napari_track_edit.motile.backend.motile_run.MotileRun(graph: tracksdata.graph.BaseGraph, run_name: str, time_attr: str = 't', pos_attr: str | tuple[str] | list[str] = 'pos', scale: list[float] | None = None, ndim: int | None = None, solver_params: napari_track_edit.motile.backend.solver_params.SolverParams | None = None, input_segmentation: numpy.ndarray | None = None, input_points: numpy.ndarray | None = None, time: datetime.datetime | None = None, gaps: list[float] | None = None, status: str = 'done', _features=None, _segmentation=None)
Bases:
funtracks.data_model.TracksAn object representing a motile tracking run. Contains a name, parameters, time of creation, information about the solving process (status and list of solver gaps), and optionally the input and output segmentations and tracks. Mostly used for passing around the set of attributes needed to specify a run, as well as saving and loading.
- run_name
- solver_params = None
- input_segmentation = None
- input_points = None
- gaps = None
- status = 'done'
- time
- _make_id() str
Combine the time and run name into a unique id for the run
- Returns:
A unique id combining the timestamp and run name
- Return type:
str
- static _unpack_id(_id: str) tuple[datetime.datetime, str]
Unpack a string id created with _make_id into the time and run name
- Parameters:
_id (str) – The id to unpack into time and run name
- Raises:
ValueError – If the provided id is not in the expected format
- Returns:
A tuple of time and run name
- Return type:
tuple[datetime, str]
- classmethod _resolve_name_and_time(run_dir: pathlib.Path, attrs: dict | None) tuple[datetime.datetime | None, str]
Determine the run name and run time for a run being loaded.
Runs used to be saved in a directory named by _make_id, so the name and time could be recovered by unpacking the directory name. Newer runs store both in the attrs file instead, which lets them be saved to a directory the user named. Falls back through both, and finally to the directory name with no time, so that a run directory is loadable however it was named. A None time is replaced with the current time by __init__, so the run still displays.
- Parameters:
run_dir (Path) – The directory the run is being loaded from.
attrs (dict | None) – The loaded attrs, or None if there is no attrs file.
- Returns:
The run time and run name.
- Return type:
tuple[datetime | None, str]
- save(path: str | pathlib.Path, save_segmentation: bool = False) pathlib.Path
Save the run as a geff store at the provided path.
The geff store is written at exactly path — no subdirectory is created — and the rest of the run (solver params, attrs, input points, gaps) is stored inside that store alongside the graph. A geff is a zarr directory, and writing a geff only replaces geff-controlled groups, so these files survive re-saving over the same store.
- Parameters:
path (str | Path) – The geff store to save the run to. Created if it does not exist, and replaced if it does.
save_segmentation (bool) – Ignored. Kept for backwards compatibility; the segmentation is never written here.
- Returns:
The Path that the run was saved to.
- Return type:
(Path)
- static geff_path(run_dir: pathlib.Path | str) pathlib.Path | None
Return the geff store holding a saved run’s graph.
Mirrors the layouts that
load()accepts. Runs saved by the current version are themselves the geff store. Returns None for v1 runs, which stored the graph as graph.json rather than as a geff.- Parameters:
run_dir (Path | str) – A directory created by MotileRun.save.
- static _is_geff(directory: pathlib.Path) bool
Whether the given directory is itself a geff store.
Distinguishes a run saved as a geff from an older run directory that merely contains one, which is exactly what load() needs.
- classmethod load(run_dir: pathlib.Path | str, output_required: bool = True)
Load a run from disk into memory.
- Parameters:
run_dir (Path | str) – A directory containing the saved run. Should be the subdirectory created by MotileRun.save that includes the timestamp and run name.
output_required (bool) – If the model outputs are required. If true, will raise an error if the output files are not found. Defualts to True.
- Returns:
The run saved in the provided directory.
- Return type:
- _save_params(run_dir: pathlib.Path)
Save the run parameters in the provided run directory. Currently dumps the parameters dict into a json file. Skips writing if there are no params, which only happens for a run loaded from a directory that had no params file (see _load_params).
- Parameters:
run_dir (Path) – A directory in which to save the parameters file.
- static _load_params(run_dir: pathlib.Path) napari_track_edit.motile.backend.solver_params.SolverParams | None
Load parameters from the parameters json file in the provided directory. Returns None if the file is absent, which is the case for v1 run directories and for runs saved by versions that wrapped imported (CSV/geff) tracks in a MotileRun with no solver params.
- Parameters:
run_dir (Path) – The directory in which to find the parameters file.
- Returns:
- The solver parameters, or None if no params
file exists in the run directory.
- Return type:
SolverParams | None
- _save_array(run_dir: pathlib.Path, filename: str, array: numpy.ndarray)
Save a segmentation as a numpy array using np.save. In the future, could be changed to use zarr or other file types.
- Parameters:
run_dir (Path) – The directory in which to save the segmentation
filename (str) – The filename to use
array (np.array) – The array to save
- static _load_array(run_dir: pathlib.Path, filename: str, required: bool = True) numpy.ndarray | None
Load an array from file using np.load. In the future, could be lazy loading from a zarr.
- Parameters:
run_dir (Path) – The base run directory containing the array
filename (str) – The name of the file to load
required (bool, optional) – If true, will fail if the array file is not present. If false, will return None if the file is not present. Defaults to True.
- Raises:
FileNotFoundError – If the array file is not found, and it was required.
- Returns:
- The array, or None if the file was
not found and not required.
- Return type:
np.ndarray | None
- _save_attrs(directory: pathlib.Path)
Save the run name, run time, time_attr, scale, and shape in a json file.
The run name and time are stored here rather than being recoverable from the directory name alone (see _make_id), so that a run can be saved to a directory the user named.
Note that “time” is when the run was solved, while “time_attr” is the name of the graph’s time column.
- Parameters:
directory (Path) – The directory in which to save the attributes
- static _load_attrs(run_dir: pathlib.Path) dict | None
Load attrs from the attrs json file in the provided directory, if present.
- Parameters:
run_dir (Path) – The directory in which to find the attrs file.
- Returns:
The attrs dict, or None if the file was not found.
- Return type:
dict | None
- _save_list(list_to_save: list | None, run_dir: pathlib.Path, filename: str)
- static _load_list(run_dir: pathlib.Path, filename: str, required: bool = True) list[float]
- delete(base_path: str | pathlib.Path)
Delete this run from the file system. Will look inside base_path for the directory corresponding to this run and delete it.
- Parameters:
base_path (str | Path) – The parent directory where the run is saved (not the one created by self.save).