segregation.decomposition.DecomposeSegregation

class segregation.decomposition.DecomposeSegregation(index1, index2, counterfactual_approach='composition')[source]

Decompose segregation differences into spatial and attribute components.

Given two segregation indices of the same type, use Shapley decomposition to measure whether the differences between index measures arise from differences in spatial structure or population structure

Examples

Several examples can be found at https://github.com/pysal/segregation/blob/master/notebooks/decomposition_wrapper_example.ipynb.

Methods

plot([plot_type, figsize, city_a, city_b, …])

Plot maps or CDFs of urban contexts used in calculating the Decomposition class.

__init__(index1, index2, counterfactual_approach='composition')[source]

Decompose segregation differences into spatial and attribute components.

Given two segregation indices of the same type, use Shapley decomposition to measure whether the differences between index measures arise from differences in spatial structure or population structure

Parameters
index1segregation.SegIndex class

First SegIndex class to compare.

index2segregation.SegIndex class

Second SegIndex class to compare.

counterfactual_approachstr, one of {“composition”, “share”, “dual_composition”}

The technique used to generate the counterfactual population distributions.

Attributes
c_sfloat

Shapley’s Spatial Component of the decomposition

c_afloat

Shapley’s Attribute Component of the decomposition

Methods

__init__(index1, index2[, …])

Decompose segregation differences into spatial and attribute components.

plot([plot_type, figsize, city_a, city_b, …])

Plot maps or CDFs of urban contexts used in calculating the Decomposition class.