momepy.NeighborDistance

class momepy.NeighborDistance(gdf, spatial_weights, unique_id, verbose=True)

Calculate the mean distance to adjacent buildings (based on spatial_weights)

If no neighbours are found, return np.nan.

\[\frac{1}{n}\sum_{i=1}^n dist_i=\frac{dist_1+dist_2+\cdots+dist_n}{n}\]

Adapted from [Schirmer and Axhausen, 2015].

Parameters

gdfGeoDataFrame

GeoDataFrame containing objects to analyse

spatial_weightslibpysal.weights

spatial weights matrix based on unique_id

unique_idstr

name of the column with unique id used as spatial_weights index.

verbosebool (default True)

if True, shows progress bars in loops and indication of steps

Examples

>>> buildings_df['neighbour_distance'] = momepy.NeighborDistance(buildings_df,
...                                                              sw,
...                                                              'uID').series
100%|██████████| 144/144 [00:00<00:00, 345.78it/s]
>>> buildings_df['neighbour_distance'][0]
29.18589019096464

Attributes

seriesSeries

Series containing resulting values

gdfGeoDataFrame

original GeoDataFrame

swlibpysal.weights

spatial weights matrix

idSeries

Series containing used unique ID

__init__(gdf, spatial_weights, unique_id, verbose=True)

Methods

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