class_docstr: Distribution of Ansari-Bradley W-statistic under the null hypothesis.
docstr: Probability mass function.
docstr_tok: ["Probability","mass","function","."]
code: def pmf(self, k, n, m):
      """Probability mass function."""
      self._recalc(n, m)
      # The convention here is that PMF at k = 12.5 is the same as at k = 12,
      # -> use `floor` in case of ties.
      ind = np.floor(k - self.astart).astype(int)
      return self.freqs[ind] / self.total
  
imports: from __future__ import annotations
  import math
  import warnings
  from collections import namedtuple
  import numpy
  from numpy import isscalar, r_, log, around, unique, asarray, zeros, arange, sort, amin, amax, atleast_1d, sqrt, array, compress, pi, exp, ravel, count_nonzero, sin, cos, arctan2, hypot
  from scipy import optimize
  from scipy import special
  from .None import statlib
  from .None import stats
  from .stats import find_repeats, _contains_nan, _normtest_finish
  from .contingency import chi2_contingency
  from .None import distributions
  from ._distn_infrastructure import rv_generic
  from ._hypotests import _get_wilcoxon_distr
label_desc: Use image node_id 3 for calling the _ABW obj's underlying member method code with example usage: obj.pmf(k, n, m) and returns: unknown