momepy.Neighbors#

class momepy.Neighbors(gdf, spatial_weights, unique_id, weighted=False, verbose=True)[source]#

Calculate the number of neighbours captured by spatial_weights. If weighted=True, the number of neighbours will be divided by the perimeter of the object to return relative value.

Adapted from [Hermosilla et al., 2012].

Parameters
gdfGeoDataFrame

A GeoDataFrame containing objects to analyse.

spatial_weightslibpysal.weights

A spatial weights matrix.

unique_idstr

The name of the unique ID column used as the spatial_weights index.

weightedbool (default False)

If True, the number of neighbours will be divided by the perimeter of object, to return the relative value.

verbosebool (default True)

If True, shows progress bars in loops and indication of steps.

Examples

>>> sw = libpysal.weights.contiguity.Queen.from_dataframe(tessellation_df,
...                                                       ids='uID')
>>> tessellation_df['neighbours'] = momepy.Neighbors(tessellation_df,
...                                                  sw,
...                                                  'uID').series
100%|██████████| 144/144 [00:00<00:00, 6909.50it/s]
>>> tessellation_df['neighbours'][0]
4
Attributes
seriesSeries

A Series containing resulting values.

gdfGeoDataFrame

The original GeoDataFrame.

valuesSeries

A Series containing used values.

swlibpysal.weights

The spatial weights matrix.

idSeries

A Series containing used unique ID.

weightedbool

Whether object is weighted or not.

__init__(gdf, spatial_weights, unique_id, weighted=False, verbose=True)[source]#

Methods

__init__(gdf, spatial_weights, unique_id[, ...])