remove_unconnected_regions#

remove_unconnected_regions(samples: DataFrame, unconnected_threshold: float, unconnected_filter: str) → DataFrame[source]#

Removes unconnected regions.

Parameters:

  • samples – Sample cell ids and coordinates.

  • threshold – Distance for removing unconnected regions.

  • filter – Filter type for assigning unconnected coordinates.

Returns:

Samples with unconnected regions removed.

remove_unconnected_by_connectivity(samples: DataFrame) → DataFrame[source]#

Removes unconnected regions based on simple connectivity.

Parameters:

samples – Sample cell ids and coordinates.

Returns:

Samples with unconnected regions removed.

remove_unconnected_by_distance(samples: DataFrame, threshold: float) → DataFrame[source]#

Removes unconnected regions based on distance.

Parameters:

  • samples – Sample cell ids and coordinates.

  • threshold – Distance for removing unconnected regions.

Returns:

Samples with unconnected regions removed.

get_sample_minimums(samples: DataFrame) → tuple[int, int, int][source]#

Gets minimums in x, y, and z directions for samples.

Parameters:

samples – Sample cell ids and coordinates.

Return type:

Tuple of minimums.

get_sample_maximums(samples: DataFrame) → tuple[int, int, int][source]#

Gets maximums in x, y, and z directions for samples.

Parameters:

samples – Sample cell ids and coordinates.

Return type:

Tuple of maximums.

convert_to_integer_array(samples: DataFrame, minimums: tuple[int, int, int], maximums: tuple[int, int, int]) → ndarray[source]#

Converts ids and coordinate samples to integer array.

Parameters:

  • samples – Sample cell ids and coordinates.

  • minimums – Minimums in x, y, and z directions.

  • maximums – Maximums in x, y, and z directions.

Returns:

Array of ids.

convert_to_dataframe(array: ndarray, minimums: tuple[int, int, int]) → DataFrame[source]#

Converts integer array to ids and coordinate samples.

Parameters:

  • array – Integer array of ids.

  • minimums – Minimums in x, y, and z directions.

Returns:

Dataframe of ids and coordinates.

get_minimum_distance(source: ndarray, targets: ndarray) → float[source]#

Get the minimum distance from point to array of points.

Parameters:

  • source – Coordinates of source point with shape (1, 3)

  • targets – Coordinates for N target points with shape (3, N)

Returns:

Minimum distance between source and targets.