momepy.BlocksCount¶

class momepy.BlocksCount(gdf, block_id, spatial_weights, unique_id, weighted=True)[source]¶

Calculates the weighted number of blocks

Number of blocks within neighbours defined in spatial_weights.

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Parameters

gdfGeoDataFrame

GeoDataFrame containing morphological tessellation

block_idstr, list, np.array, pd.Series

the name of the objects dataframe column, np.array, or pd.Series where is stored block ID.

spatial_weightslibpysal.weights

spatial weights matrix

unique_idstr

name of the column with unique id used as spatial_weights index

weigtedbool, default True

return value weighted by the analysed area (True) or pure count (False)

References

Dibble J, Prelorendjos A, Romice O, et al. (2017) On the origin of spaces: Morphometric foundations of urban form evolution. Environment and Planning B: Urban Analytics and City Science 46(4): 707–730.

Examples

>>> sw4 = mm.sw_high(k=4, gdf='tessellation_df', ids='uID')
>>> tessellation_df['blocks_within_4'] = mm.BlocksCount(tessellation_df, 'bID', sw4, 'uID').series

Attributes

seriesSeries

Series containing resulting values

gdfGeoDataFrame

original GeoDataFrame

block_idSeries

Series containing used block ID

swlibpysal.weights

spatial weights matrix

idSeries

Series containing used unique ID

weightedbool

used weighted value

__init__(self, gdf, block_id, spatial_weights, unique_id, weighted=True)[source]¶

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(self, gdf, block_id, …[, weighted])

Initialize self.