`scipy.stats._multivariate:random_table_gen.logpmf`

Signature

def logpmf(self, x, row, col)

Log-probability of table to occur in the distribution.

x : array-like: Two-dimensional table of non-negative integers, or a multi-dimensional array with the last two dimensions corresponding with the tables.
row : array_like: Sum of table entries in each row.
col : array_like: Sum of table entries in each column.

logpmf : ndarray or scalar: Log of the probability mass function evaluated at x.

The row and column vectors must be one-dimensional, not empty, and each sum up to the same value. They cannot contain negative or noninteger entries.

If row and column marginals of x do not match row and col, negative infinity is returned.

from scipy.stats import random_table
import numpy as np

✓

x = [[1, 5, 1], [2, 3, 1]]
row = np.sum(x, axis=1)
col = np.sum(x, axis=0)

✓

random_table.logpmf(x, row, col)

✗

np.float64(-1.6306401200847027)

Alternatively, the object may be called (as a function) to fix the row and column vector sums, returning a "frozen" distribution.

d = random_table(row, col)

✓

d.logpmf(x)

✗

np.float64(-1.6306401200847027)