import pyLHD
random_lhd = pyLHD.LatinHypercube(size = (10,3))
pyLHD.phi_p(random_lhd) 2.5128857125055477criteria.phi_p
criteria.phi_p(arr, p=15, q=1)
Calculate the phi_p Criterion
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
arr |
numpy.numpy.ArrayLike | A numpy ndarray | required |
p |
int | A positive integer, which is the parameter in the phi_p formula. The default is set to be 15. If (q) is 1, (inter_site) is the Manhattan (rectangular) distance. If (q) is 2, (inter_site) is the Euclidean distance. | 15 |
Returns
| Type | Description |
|---|---|
| float | A positive number indicating phi_p |
Examples: Calculate the phi_p criterion for random_lhd with default settings
Calculate the phi_p criterion of random_lhd with p=50 and q=2 (Euclidean)
pyLHD.phi_p(random_lhd,p=50,q=2) 4.082482950076924