libpysal.weights.vecW¶

libpysal.weights.
vecW
(origin_x, origin_y, dest_x, dest_y, threshold, p=2, alpha=1.0, binary=True, ids=None, build_sp=False, **kwargs)[source]¶ Distancebased spatial weight for vectors that is computed using a 4dimensional distance between the origin x,ycoordinates and the destination x,ycoordinates
 Parameters
 origin_x
list
orarray
of vector origin xcoordinates
 origin_y
list
orarray
of vector origin ycoordinates
 dest_x
list
orarray
of vector destination xcoordinates
 dest_y
list
orarray
of vector destination ycoordinates
 threshold
float
distance band
 p
float
Minkowski pnorm distance metric parameter: 1<=p<=infinity 2: Euclidean distance 1: Manhattan distance
 binarybool
If true w_{ij}=1 if d_{i,j}<=threshold, otherwise w_{i,j}=0 If false wij=dij^{alpha}
 alpha
float
distance decay parameter for weight (default 1.0) if alpha is positive the weights will not decline with distance. If binary is True, alpha is ignored
 ids
list
values to use for keys of the neighbors and weights dicts
 build_spbool
True to build sparse distance matrix and false to build dense distance matrix; significant speed gains may be obtained dending on the sparsity of the of distance_matrix and threshold that is applied
 **kwargs
keyword
arguments
optional arguments for
pysal.weights.W
 Returns
 ——
 W
DistanceBand
W
object
that
uses
4dimenionaldistances
between
vectors origin and destination coordinates.
 origin_x
Examples
>>> import libpysal >>> x1 = [5,6,3] >>> y1 = [1,8,5] >>> x2 = [2,4,9] >>> y2 = [3,6,1] >>> W1 = libpysal.weights.vecW(x1, y1, x2, y2, threshold=999) >>> list(W1.neighbors[0]) [1, 2] >>> W2 = libpysal.weights.vecW(x1, y2, x1, y2, threshold=8.5) >>> list(W2.neighbors[0]) [1, 2]