class_docstr: Base object for permutations test
class_docstr_tok: ["Base","object","for","permutations","test"]
docstr: Plot results of the permutation test.
  
  Parameters
  ----------
  nbins : integer or array_like or 'auto', default=10
      If an integer is given, bins + 1 bin edges are returned,
      consistently with np.histogram() for numpy version >= 1.3.
      Unequally spaced bins are supported if bins is a sequence.
  range : tuple or None, default=None
      The lower and upper range of the bins. Lower and upper outliers are
      ignored. If not provided, range is (x.min(), x.max()).
      Range has no effect if bins is a sequence.
      If bins is a sequence or range is specified, autoscaling is based
      on the specified bin range instead of the range of x.
  
  axes : axes handle, default=None
      Axes handle for matplotlib. if None a new figure will be created.
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code: def plot(self, nbins=10, range=None, axes=None):
      """Plot results of the permutation test.
  
      Parameters
      ----------
      nbins : integer or array_like or 'auto', default=10
          If an integer is given, bins + 1 bin edges are returned,
          consistently with np.histogram() for numpy version >= 1.3.
          Unequally spaced bins are supported if bins is a sequence.
      range : tuple or None, default=None
          The lower and upper range of the bins. Lower and upper outliers are
          ignored. If not provided, range is (x.min(), x.max()).
          Range has no effect if bins is a sequence.
          If bins is a sequence or range is specified, autoscaling is based
          on the specified bin range instead of the range of x.
  
      axes : axes handle, default=None
          Axes handle for matplotlib. if None a new figure will be created.
      """
      try:
          import matplotlib.pyplot as plt
      except ImportError:
          raise ImportError("Install matplotlib to plot permutation")
  
      if axes is None:
          fig, axes = plt.subplots(1, 1)
      axes.hist(self.scores_[1:], nbins, range)
      x_val = self.scores_[0]
      y_max = axes.get_ylim()[1]
      axes.plot([x_val, x_val], [0, y_max], "--r", lw=2)
      x_max = axes.get_xlim()[1]
      x_min = axes.get_xlim()[0]
      x_pos = x_min + ((x_max - x_min) * 0.25)
      axes.text(x_pos, y_max * 0.8, "p-value: %.3f" % self.p_value_)
      axes.set_xlabel("Score")
      axes.set_ylabel("Count")
      return axes
  
imports: import sys
  import math
  import numpy
  from .utils.utils import check_version
  from .utils.distance import distance, pairwise_distance
  from .utils.mean import mean_covariance
  from .classification import MDM, _check_metric
label_desc: Use image node_id 5 for calling the BasePermutation obj's underlying member method code with example usage: obj.plot(nbins, range, axes) and returns: axes