| // Copyright ©2014 The gonum Authors. All rights reserved. |
| // Use of this source code is governed by a BSD-style |
| // license that can be found in the LICENSE file. |
| |
| package distuv |
| |
| import ( |
| "math" |
| "testing" |
| ) |
| |
| func TestHalfKStandardWeibullProb(t *testing.T) { |
| pts := []univariateProbPoint{ |
| { |
| loc: 0, |
| prob: math.Inf(1), |
| cumProb: 0, |
| logProb: math.Inf(1), |
| }, |
| { |
| loc: -1, |
| prob: 0, |
| cumProb: 0, |
| logProb: 0, |
| }, |
| { |
| loc: 1, |
| prob: 0.183939720585721, |
| cumProb: 0.632120558828558, |
| logProb: -1.693147180559950, |
| }, |
| { |
| loc: 20, |
| prob: 0.001277118038048, |
| cumProb: 0.988577109006533, |
| logProb: -6.663149272336520, |
| }, |
| } |
| testDistributionProbs(t, Weibull{K: 0.5, Lambda: 1}, "0.5K Standard Weibull", pts) |
| } |
| |
| func TestExponentialStandardWeibullProb(t *testing.T) { |
| pts := []univariateProbPoint{ |
| { |
| loc: 0, |
| prob: 1, |
| cumProb: 0, |
| logProb: math.Inf(1), |
| }, |
| { |
| loc: -1, |
| prob: 0, |
| cumProb: 0, |
| logProb: 0, |
| }, |
| { |
| loc: 1, |
| prob: 0.367879441171442, |
| cumProb: 0.632120558828558, |
| logProb: -1.0, |
| }, |
| { |
| loc: 20, |
| prob: 0.000000002061154, |
| cumProb: 0.999999997938846, |
| logProb: -20.0, |
| }, |
| } |
| testDistributionProbs(t, Weibull{K: 1, Lambda: 1}, "1K (Exponential) Standard Weibull", pts) |
| } |
| |
| func TestRayleighStandardWeibullProb(t *testing.T) { |
| pts := []univariateProbPoint{ |
| { |
| loc: 0, |
| prob: 0, |
| cumProb: 0, |
| logProb: math.Inf(-1), |
| }, |
| { |
| loc: -1, |
| prob: 0, |
| cumProb: 0, |
| logProb: 0, |
| }, |
| { |
| loc: 1, |
| prob: 0.735758882342885, |
| cumProb: 0.632120558828558, |
| logProb: -0.306852819440055, |
| }, |
| { |
| loc: 20, |
| prob: 0, |
| cumProb: 1, |
| logProb: -396.31112054588607, |
| }, |
| } |
| testDistributionProbs(t, Weibull{K: 2, Lambda: 1}, "2K (Rayleigh) Standard Weibull", pts) |
| } |
| |
| func TestFiveKStandardWeibullProb(t *testing.T) { |
| pts := []univariateProbPoint{ |
| { |
| loc: 0, |
| prob: 0, |
| cumProb: 0, |
| logProb: math.Inf(-1), |
| }, |
| { |
| loc: -1, |
| prob: 0, |
| cumProb: 0, |
| logProb: 0, |
| }, |
| { |
| loc: 1, |
| prob: 1.839397205857210, |
| cumProb: 0.632120558828558, |
| logProb: 0.609437912434100, |
| }, |
| { |
| loc: 20, |
| prob: 0, |
| cumProb: 1, |
| logProb: -3199986.4076329935, |
| }, |
| } |
| testDistributionProbs(t, Weibull{K: 5, Lambda: 1}, "5K Standard Weibull", pts) |
| } |
| |
| func TestScaledUpHalfKStandardWeibullProb(t *testing.T) { |
| pts := []univariateProbPoint{ |
| { |
| loc: 0, |
| prob: math.Inf(1), |
| cumProb: 0, |
| logProb: math.Inf(1), |
| }, |
| { |
| loc: -1, |
| prob: 0, |
| cumProb: 0, |
| logProb: 0, |
| }, |
| { |
| loc: 1, |
| prob: 0.180436508682207, |
| cumProb: 0.558022622759326, |
| logProb: -1.712376315541750, |
| }, |
| { |
| loc: 20, |
| prob: 0.002369136850928, |
| cumProb: 0.974047406098605, |
| logProb: -6.045229588092130, |
| }, |
| } |
| testDistributionProbs(t, Weibull{K: 0.5, Lambda: 1.5}, "0.5K 1.5λ Weibull", pts) |
| } |
| |
| func TestScaledDownHalfKStandardWeibullProb(t *testing.T) { |
| pts := []univariateProbPoint{ |
| { |
| loc: 0, |
| prob: math.Inf(1), |
| cumProb: 0, |
| logProb: math.Inf(1), |
| }, |
| { |
| loc: -1, |
| prob: 0, |
| cumProb: 0, |
| logProb: 0, |
| }, |
| { |
| loc: 1, |
| prob: 0.171909491538362, |
| cumProb: 0.756883265565786, |
| logProb: -1.760787152653070, |
| }, |
| { |
| loc: 20, |
| prob: 0.000283302579100, |
| cumProb: 0.998208237166091, |
| logProb: -8.168995047393730, |
| }, |
| } |
| testDistributionProbs(t, Weibull{K: 0.5, Lambda: 0.5}, "0.5K 0.5λ Weibull", pts) |
| } |
| |
| func TestWeibullScore(t *testing.T) { |
| for _, test := range []*Weibull{ |
| { |
| K: 1, |
| Lambda: 1, |
| }, |
| { |
| K: 2, |
| Lambda: 3.6, |
| }, |
| { |
| K: 3.4, |
| Lambda: 8, |
| }, |
| } { |
| testDerivParam(t, test) |
| } |
| } |