fractopo.analysis.line_data module

Trace and branch data analysis with LineData class abstraction.

class fractopo.analysis.line_data.LineData(_line_gdf: ~geopandas.geodataframe.GeoDataFrame, using_branches: bool, azimuth_set_ranges: ~collections.abc.Sequence[tuple[float | int | ~numbers.Real, float | int | ~numbers.Real]], azimuth_set_names: ~collections.abc.Sequence[str], length_set_ranges: ~collections.abc.Sequence[tuple[float | int | ~numbers.Real, float | int | ~numbers.Real]] = (), length_set_names: ~collections.abc.Sequence[str] = (), area_boundary_intersects: ~numpy.ndarray = <factory>, _automatic_fit: ~powerlaw.Fit | None = None)

Bases: object

Wrapper around the given GeoDataFrame with trace or branch data.

The line_gdf reference is passed and LineData will modify the input line_gdf instead of copying the input frame. This means line_gdf columns are accessible in the passed input reference upstream.

area_boundary_intersects: ndarray

property automatic_fit: Fit | None: Get automatic powerlaw Fit.

property azimuth_array: ndarray: Array of trace or branch azimuths.

property azimuth_set_array: ndarray: Array of trace or branch azimuth set ids.

property azimuth_set_counts: dict[str, int]: Get dictionary of azimuth set counts.

property azimuth_set_length_arrays: dict[str, ndarray]: Get length arrays of each azimuth set.

azimuth_set_names: Sequence[str]

azimuth_set_ranges: Sequence[tuple[float | int | Real, float | int | Real]]

property boundary_intersect_count: dict[str, int]: Get counts of line intersects with boundary.

boundary_intersect_count_desc(label: str) → dict[str, int]: Get counts of line intersects with boundary.

describe_fit(label: str | None = None, cut_off: float | None = None): Return short description of automatic powerlaw fit.

determine_manual_fit(cut_off: float) → Fit | None: Get manually determined Fit with set cut off.

property geometry: GeoSeries: Get line geometries.

property length_array: ndarray

Array of trace or branch lengths.

Note: lengths can be 0.0 due to boundary weighting.

property length_array_non_weighted: ndarray: Array of trace or branch lengths not weighted by boundary conditions.

property length_boundary_weights: Array of weights for lines based on intersection count with boundary.

property length_set_array: ndarray: Array of trace or branch length set ids.

property length_set_counts: dict[str, int]: Get dictionary of length set counts.

length_set_names: Sequence[str] = ()

length_set_ranges: Sequence[tuple[float | int | Real, float | int | Real]] = ()

plot_azimuth(label: str, append_azimuth_set_text: bool = False, add_abundance_order: bool = False, visualize_sets: bool = False, bar_color: str = 'darkgrey', plain: bool = False) → tuple[AzimuthBins, Figure, PolarAxes]: Plot azimuth data in rose plot.

plot_azimuth_set_count(label: str) → tuple[Figure, Axes]: Plot azimuth set counts.

plot_azimuth_set_lengths(use_probability_density_function: bool = False) → tuple[list[Fit | None], list[Figure], list[Axes]]: Plot azimuth set length distributions with fits.

plot_length_set_count(label: str) → tuple[Figure, Axes]: Plot length set counts.

plot_lengths(label: str, use_probability_density_function: bool, fit: Fit | None = None, plain: bool = False, fits_to_plot: tuple[Dist, ...] = (Dist.POWERLAW, Dist.LOGNORMAL, Dist.EXPONENTIAL)) → tuple[Fit | None, Figure, Axes]: Plot length data with powerlaw fit.

using_branches: bool