class_docstr: Generate a set of probabilities on [0, 1].
class_docstr_tok: ["Generate","a","set","of","probabilities","on","[","0",",","1","]","."]
docstr: Return an array containing approximately n numbers.
docstr_tok: ["Return","an","array","containing","approximately","n","numbers","."]
code: def values(self, n):
      """Return an array containing approximately n numbers."""
      m = max(1, n // 3)
      v1 = np.logspace(-30, np.log10(0.3), m)
      v2 = np.linspace(0.3, 0.7, m + 1, endpoint=False)[1:]
      v3 = 1 - np.logspace(np.log10(0.3), -15, m)
      v = np.r_[v1, v2, v3]
      return np.unique(v)
  
imports: import itertools
  import numpy
  from numpy.testing import assert_equal, assert_allclose
  import pytest
  import scipy.special
  from scipy.special._testutils import MissingModule, check_version, FuncData
  from scipy.special._mptestutils import Arg, IntArg, get_args, mpf2float, assert_mpmath_equal
label_desc: Use image node_id 2 for calling the ProbArg obj's underlying member method code with example usage: obj.values(n) and returns: np