momepy.StreetAlignment#

momepy.StreetAlignment(left, right, orientations, network_id=None, left_network_id=None, right_network_id=None)[source]#

Calculate the difference between street orientation and orientation of another object in degrees. The orientation of a street segment is represented by the orientation of line connecting the first and the last point of the segment. A network ID linking each object to specific street segment is needed, and can be generated by momepy.get_network_id(). Either network_id or both left_network_id and right_network_id are required.

\[\left|{\textit{building orientation} - \textit{street orientation}}\right|\]

Parameters:

leftGeoDataFrame: A GeoDataFrame containing objects to analyse.
rightGeoDataFrame: A GeoDataFrame containing a street network.
orientationsstr, list, np.array, pd.Series: The name of the dataframe column, np.array, or pd.Series where object orientation values are stored. The object can be calculated using momepy.Orientation.
network_idstr (default None): The name of the column storing network ID in both left and right.
left_network_idstr, list, np.array, pd.Series (default None): The name of the left dataframe column, np.array, or pd.Series where object network IDs are stored.
right_network_idstr, list, np.array, pd.Series (default None): The name of the right dataframe column, np.array, or pd.Series of streets with unique network IDs. These IDs have to be defined beforehand and can be defined using momepy.unique_id().

Attributes:

seriesSeries: A Series containing resulting values.
leftGeoDataFrame: The original left GeoDataFrame.
rightGeoDataFrame: The original right GeoDataFrame.
network_idstr: The name of the column storing network ID in both left and right.
left_network_idSeries: A Series containing used left ID.
right_network_idSeries: A Series containing used right ID.

Examples

>>> buildings_df['street_alignment'] = momepy.StreetAlignment(buildings_df,
...                                                           streets_df,
...                                                           'orientation',
...                                                           'nID',
...                                                           'nID').series
>>> buildings_df['street_alignment'][0]
0.29073888476702336

momepy.StreetAlignment#

This Page