pygeoda.local_bijoincount¶
- pygeoda.local_bijoincount(w, data, **kwargs)[source]¶
Bivariate Local Join Count Statistics
The function to apply (no-colocation) bivariate local Join Count statistics. The bivariate local join count only applies on two variables with no-colocation.
- Parameters
w (Weight) – An instance of Weight class
data (list or dataframe) – A list of numeric vectors of selected variable or a data frame of selected variables e.g. guerry[[‘Crm_prs’, ‘Literacy’]]
permutations (int, optional) – The number of permutations for the LISA computation
permutation_method (str, optional) – The permutation method used for the LISA computation. Options are {‘complete’, ‘lookup-table’}. Default is ‘complete’.
significance_cutoff (float, optional) – A cutoff value for significance p-values to filter not-significant clusters
cpu_threads (int, optional) – The number of cpu threads used for parallel LISA computation
seed (int, optional) – The seed for random number generator
- Returns
An instance of lisa class
- Return type
Examples
>>> import pygeoda >>> columbus = pygeoda.open("./data/columbus.shp") >>> columbus_q = pygeoda.queen_weights(columbus) >>> nsa = columbus.GetRealCol("nsa") >>> nsa_inv = [1-i for i in nsa] >>> lisa = pygeoda.local_bijoincount(columbus_q, [nsa, nsa_inv]) >>> jc = lisa.lisa_values() (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 3.0, 3.0, 2.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0) >>> pvals = lisa.lisa_pvalues() (nan, nan, nan, nan, nan, nan, nan, nan, 0.002, 0.034, nan, nan, nan, nan, nan, nan, 0.44, nan, nan, nan, nan, 0.262, nan, 0.125, 0.079, 0.053, nan, nan, nan, nan, 0.093, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan) >>> nn = lisa.lisa_num_nbrs() (2, 3, 4, 4, 8, 2, 4, 6, 8, 4, 5, 6, 4, 6, 6, 8, 3, 4, 3, 10, 3, 6, 3, 7, 8, 6, 4, 9, 7, 5, 3, 4, 4, 4, 7, 5, 6, 6, 3, 5, 3, 2, 6, 5, 4, 2, 2, 4, 3)