libpysal.weights.
block_weights
(regimes, ids=None, sparse=False, **kwargs)[source]¶Construct spatial weights for regime neighbors.
Block contiguity structures are relevant when defining neighbor relations based on membership in a regime. For example, all counties belonging to the same state could be defined as neighbors, in an analysis of all counties in the US.
ids of which regime an observation belongs to
Ordered sequence of IDs for the observations
If True return WSP instance If False return W instance
optional arguments for pysal.weights.W
Examples
>>> from libpysal.weights import block_weights
>>> import numpy as np
>>> regimes = np.ones(25)
>>> regimes[range(10,20)] = 2
>>> regimes[range(21,25)] = 3
>>> regimes
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 2., 2., 2., 2., 2., 2., 2.,
2., 2., 2., 1., 3., 3., 3., 3.])
>>> w = block_weights(regimes)
>>> w.weights[0]
[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
>>> w.neighbors[0]
[1, 2, 3, 4, 5, 6, 7, 8, 9, 20]
>>> regimes = ['n','n','s','s','e','e','w','w','e']
>>> n = len(regimes)
>>> w = block_weights(regimes)
>>> w.neighbors == {0: [1], 1: [0], 2: [3], 3: [2], 4: [5, 8], 5: [4, 8], 6: [7], 7: [6], 8: [4, 5]}
True