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# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
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#
#     http://www.apache.org/licenses/LICENSE-2.0
#
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# Test no truncation
parameters = 3.0, 1.1, -Infinity, Infinity
mean = 3
variance = 1.21
lower = -Infinity
upper = Infinity
# Computed using Python with SciPy v1.6.0.
# mean, std, clip_a, clip_b = 3.0, 1.1, -float('inf'), float('inf')
# a, b = (clip_a - mean) / std, (clip_b - mean) / std
# truncnorm.var(a, b, loc=mean, scale=std)
cdf.points = \
  -Infinity, -2.5, -1.4, -0.300000000000001, 0.799999999999999, 1.9, 3,\
  4.1, 5.2, 6.3, 7.4, 8.49999999996719, Infinity
cdf.values = \
  0.0000000000000000e+00, 2.8665157187919328e-07,\
  3.1671241833119863e-05, 1.3498980316300905e-03,\
  2.2750131948179146e-02, 1.5865525393145707e-01,\
  5.0000000000000000e-01, 8.4134474606854281e-01,\
  9.7724986805182079e-01, 9.9865010196836990e-01,\
  9.9996832875816688e-01, 9.9999971334842808e-01,\
  1.0000000000000000e+00
pdf.values = \
  0.0000000000000000e+00, 1.3515631952129980e-06,\
  1.2166384160444124e-04, 4.0289531017618134e-03,\
  4.9082696830170865e-02, 2.1997338592649396e-01,\
  3.6267480036493877e-01, 2.1997338592649404e-01,\
  4.9082696830170962e-02, 4.0289531017618290e-03,\
  1.2166384160444124e-04, 1.3515631954145620e-06,\
  0.0000000000000000e+00
