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bundles / scipy latest / scipy / stats / _qmc / update_discrepancy

function

scipy.stats._qmc:update_discrepancy

source: /scipy/stats/_qmc.py :464

Signature

def   update_discrepancy ( x_new : npt.ArrayLike ,  sample : npt.ArrayLike ,  initial_disc : DecimalNumber )  →  float

Summary

Update the centered discrepancy with a new sample.

Parameters

x_new : array_like (1, d)

The new sample to add in sample.

sample : array_like (n, d)

The initial sample.

initial_disc : float

Centered discrepancy of the sample.

Returns

discrepancy : float

Centered discrepancy of the sample composed of x_new and sample.

Examples

We can also compute iteratively the discrepancy by using ``iterative=True``. 
import numpy as np
from scipy.stats import qmc
space = np.array([[1, 3], [2, 6], [3, 2], [4, 5], [5, 1], [6, 4]])
l_bounds = [0.5, 0.5]
u_bounds = [6.5, 6.5]
space = qmc.scale(space, l_bounds, u_bounds, reverse=True)
disc_init = qmc.discrepancy(space[:-1], iterative=True)
disc_init
qmc.update_discrepancy(space[-1], space[:-1], disc_init)
✓

Aliases

  • scipy.stats._qmc.update_discrepancy

Referenced by

This package