organoid_tracker.comparison.report module
- class organoid_tracker.comparison.report.ComparisonReport(**parameters: float | int | str | bool | List[float] | List[int] | List[str] | List[bool])
Bases:
object- calculate_time_statistics(true_positives_cat: Category, false_positives_cat: Category, false_negatives_cat: Category) Statistics
Calculate statistics using the given categories as false/true positives/negatives.
- calculate_z_statistics(true_positives_cat: Category, false_positives_cat: Category, false_negatives_cat: Category) Statistics
Calculate statistics using the given categories as false/true positives/negatives.
- count_positions(category: Category, *, time_point: TimePoint | None = None) int
Gets how many entries there are in the given category, optionally at the given time point. Returns 0 if the given category is not used.
- first_time_point_number() int | None
Gets the first time point number at which data exits for at least one category. Returns None if therea is no data at all in this object.
- get_entries(category: Category) Iterable[Tuple[Position, Details]]
Gets all entries for the given category.
- get_positions(category: Category, *, time_point: TimePoint | None) Iterable[Position]
Gets all positions in the given category, optionally filtered to the given time point.
- last_time_point_number() int | None
Gets the first time point number at which data exits for at least one category. Returns None if therea is no data at all in this object.
- recorded_parameters() Iterable[Tuple[str, float | int | str | bool | List[float] | List[int] | List[str] | List[bool]]]
Gets all parameters set for this comparison. Useful for reproducing this comparison.
- class organoid_tracker.comparison.report.Details(*detail: str | Position)
Bases:
objectRepresents the details of a certain entry in the report.
- class organoid_tracker.comparison.report.Statistics(first_x_axis_number: int, x_label: str, true_positives: ndarray, false_positives: ndarray, false_negatives: ndarray)
Bases:
objectUsed to plot the true positives, false positives, false negatives, recall, precisiion and F1
- debug_plot()
Shows a Matplotlib plot. Must only be called from the command line.