spaghetti.PointPattern

class spaghetti.PointPattern(in_data=None, idvariable=None, attribute=False)

A stub point pattern class used to store a point pattern.

Note from the original author of pysal.network: This class is monkey patched with network specific attributes when the points are snapped to a network. In the future this class may be replaced with a generic point pattern class.

Parameters:

in_data{str, list, tuple, libpysal.cg.Point, geopandas.GeoDataFrame}

The input geographic data. Either (1) a path to a shapefile (str); (2) an iterable containing libpysal.cg.Point objects; (3) a single libpysal.cg.Point; or (4) a geopandas.GeoDataFrame.

idvariablestr

Field in the shapefile to use as an ID variable.

attributebool

A flag to indicate whether all attributes are tagged to this class (True) or excluded (False). Default is False.

Attributes:

pointsdict

Keys are the point IDs (int). Values are the \((x,y)\) coordinates (tuple).

npointsint

The number of points.

obs_to_arcdict

Keys are arc IDs (tuple). Values are snapped point information (dict). Within the snapped point information (dict) keys are observation IDs (int), and values are snapped coordinates.

obs_to_vertexlist

List of incident network vertices to snapped observation points converted from a default_dict. Originally in the form of paired left/right nearest network vertices {netvtx1: obs_id1, netvtx2: obs_id1, netvtx1: obs_id2… netvtx1: obs_idn}, then simplified to a list in the form [netvtx1, netvtx2, netvtx1, netvtx2, …].

dist_to_vertexdict

Keys are observations IDs (int). Values are distance lookup (dict). Within distance lookup (dict) keys are the two incident vertices of the arc and values are distance to each of those arcs.

snapped_coordinatesdict

Keys are the point IDs (int). Values are the snapped \((x,y)\) coordinates (tuple).

snap_distbool

Flag as True to include the distance from the original location to the snapped location along the network. Default is False.

__init__(in_data=None, idvariable=None, attribute=False)

Methods

__init__([in_data, idvariable, attribute])