Distance calculations

point_distance(points, other, metrics='euclidean')

Calculates the euclidean distance from one group of points to another group of points.

Parameters:

pointsarray

Spatial coordinates.

otherarray

Other array with spatial coordinates.

metricsstr, default = ‘euclidean’

Metrics used to calculate distance. See scipy.spatial.distance.cdist for more details.

Returns:

distancesarray

Distances matrix. Row index = points point index, and column index = other point index.

Notes

The function creates array of size MxN, where M = number of points and N = number of other. Very big array with coordinates may cause a memory error.

Examples

>>> points = [(0, 0), (0, 1), (0, 2)]
>>> other = [(2, 2), (3, 3)]
>>> distances = point_distance(points=points, other=other)
>>> print(distances)
[[2.82842712 4.24264069]
 [2.23606798 3.60555128]
 [2.         3.16227766]]

calc_block_to_block_distance(blocks)

Function calculates distances between blocks.

Parameters:

blocksUnion[Dict, np.ndarray, gpd.GeoDataFrame, pd.DataFrame, PointSupport]

The point support of polygons.

• Dict: {block id: [[point x, point y, value]]},

• numpy array: [[block id, x, y, value]],

• DataFrame and GeoDataFrame: columns={x, y, ds, index},

• PointSupport.

Returns:

block_distancesDict

Ordered block ids (the order from the list of distances): {block id : [distances to other]}.

Raises:

TypeError

Wrong input’s data type.

deprecated

calc_point_to_point_distance(points_a, points_b=None)

Function calculates distances between two group of points of a single group to itself.

Parameters:

points_anumpy array

The point coordinates.

points_bnumpy array, default=None

Other point coordinates. If provided then algorithm calculates distances between points_a against points_b.

Returns:

distancesnumpy array

The distances from each point from the points_a to other point (from the same points_a or from the other set of points points_b).

Deprecated since version 0.5.1: This will be removed in 1.0. Use point_distance() instead

Gridding

create_grid(ds, min_number_of_cells, grid_type='box')

Function creates grid based on a set of points.

Parameters:

dsUnion[np.ndarray, List, gpd.GeoSeries]

Data to be transformed, point coordinates [x, y] <-> [lon, lat] or GeoSeries with Point geometry.

min_number_of_cellsint

Expected number of cells in the smaller dimension.

grid_typestr, default = “square”

Available types: box, hex.

Returns:

gridgpd.GeoSeries

Empty grid that can be used to aggregate points. It is GeoSeries of Polygons (squares or hexes).

points_to_grid(points, grid, fillna=None)

Function aggregates points over a specified grid.

Parameters:

pointsgeopandas GeoDataFrame

gridgeopandas GeoSeries

fillnaAny, optional

The value to fill NaN’s, if None given then this step is skipped.

Returns:

aggregatedgeopandas GeoDataFrame