github.com/gopherd/gonum@v0.0.4/stat/distuv/binomial_test.go (about) 1 // Copyright ©2018 The Gonum Authors. All rights reserved. 2 // Use of this source code is governed by a BSD-style 3 // license that can be found in the LICENSE file. 4 5 package distuv 6 7 import ( 8 "sort" 9 "testing" 10 11 "math/rand" 12 13 "github.com/gopherd/gonum/floats/scalar" 14 ) 15 16 func TestBinomialProb(t *testing.T) { 17 t.Parallel() 18 const tol = 1e-10 19 for i, tt := range []struct { 20 k float64 21 n float64 22 p float64 23 want float64 24 }{ 25 // Probabilities computed with Wolfram|Alpha (http://wwww.wolframalpha.com) 26 {0, 10, 0.5, 0.0009765625}, 27 {1, 10, 0.5, 0.009765625}, 28 {2, 10, 0.5, 0.0439453125}, 29 {3, 10, 0.5, 0.1171875}, 30 {4, 10, 0.5, 0.205078125}, 31 {5, 10, 0.75, 5.839920043945313e-02}, 32 {6, 10, 0.75, 0.1459980010986328}, 33 {7, 10, 0.75, 0.2502822875976563}, 34 {8, 10, 0.75, 0.2815675735473633}, 35 {9, 10, 0.75, 0.1877117156982422}, 36 {10, 10, 0.75, 5.6313514709472656e-02}, 37 38 {0, 25, 0.25, 7.525434581650003e-04}, 39 {2, 25, 0.25, 2.508478193883334e-02}, 40 {5, 25, 0.25, 0.1645375881987921}, 41 {7, 25, 0.25, 0.1654081574485211}, 42 {10, 25, 0.25, 4.165835076481272e-02}, 43 {12, 25, 0.01, 4.563372575901533e-18}, 44 {15, 25, 0.01, 2.956207951505780e-24}, 45 {17, 25, 0.01, 9.980175928758777e-29}, 46 {20, 25, 0.99, 4.345539559454088e-06}, 47 {22, 25, 0.99, 1.843750355939806e-03}, 48 {25, 25, 0.99, 0.7778213593991468}, 49 50 {0.5, 25, 0.5, 0}, 51 {1.5, 25, 0.5, 0}, 52 {2.5, 25, 0.5, 0}, 53 {3.5, 25, 0.5, 0}, 54 {4.5, 25, 0.5, 0}, 55 {5.5, 25, 0.5, 0}, 56 {6.5, 25, 0.5, 0}, 57 {7.5, 25, 0.5, 0}, 58 {8.5, 25, 0.5, 0}, 59 {9.5, 25, 0.5, 0}, 60 } { 61 b := Binomial{N: tt.n, P: tt.p} 62 got := b.Prob(tt.k) 63 if !scalar.EqualWithinRel(got, tt.want, tol) { 64 t.Errorf("test-%d: got=%e. want=%e\n", i, got, tt.want) 65 } 66 } 67 } 68 69 func TestBinomialCDF(t *testing.T) { 70 t.Parallel() 71 const tol = 1e-10 72 for i, tt := range []struct { 73 k float64 74 n float64 75 p float64 76 want float64 77 }{ 78 // Cumulative probabilities computed with SciPy 79 {-1, 10, 0.5, 0}, 80 {0, 10, 0.5, 9.765625e-04}, 81 {1, 10, 0.5, 1.0742187499999998e-02}, 82 {2, 10, 0.5, 5.468749999999999e-02}, 83 {3, 10, 0.5, 1.7187499999999994e-01}, 84 {4, 10, 0.5, 3.769531249999999e-01}, 85 {5, 10, 0.25, 9.802722930908203e-01}, 86 {6, 10, 0.25, 9.964942932128906e-01}, 87 {7, 10, 0.25, 9.995841979980469e-01}, 88 {8, 10, 0.25, 9.999704360961914e-01}, 89 {9, 10, 0.25, 9.999990463256836e-01}, 90 {10, 10, 0.25, 1.0}, 91 92 {0, 25, 0.75, 8.881784197001252e-16}, 93 {2.5, 25, 0.75, 2.4655832930875472e-12}, 94 {5, 25, 0.75, 1.243460090449844e-08}, 95 {7.5, 25, 0.75, 1.060837565347583e-06}, 96 {10, 25, 0.75, 2.1451240486669576e-04}, 97 {12.5, 25, 0.01, 9.999999999999999e-01}, 98 {15, 25, 0.01, 9.999999999999999e-01}, 99 {17.5, 25, 0.01, 9.999999999999999e-01}, 100 {20, 25, 0.99, 4.495958469027147e-06}, 101 {22.5, 25, 0.99, 1.9506768897388268e-03}, 102 {25, 25, 0.99, 1.0}, 103 } { 104 b := Binomial{N: tt.n, P: tt.p} 105 got := b.CDF(tt.k) 106 if !scalar.EqualWithinRel(got, tt.want, tol) { 107 t.Errorf("test-%d: got=%e. want=%e\n", i, got, tt.want) 108 } 109 got = b.Survival(tt.k) 110 want := 1 - tt.want 111 if !scalar.EqualWithinRel(got, want, tol) { 112 t.Errorf("test-%d: got=%e. want=%e\n", i, got, tt.want) 113 } 114 } 115 } 116 117 func TestBinomial(t *testing.T) { 118 t.Parallel() 119 src := rand.New(rand.NewSource(1)) 120 for i, b := range []Binomial{ 121 {100, 0.5, src}, 122 {15, 0.25, src}, 123 {10, 0.75, src}, 124 {9000, 0.102, src}, 125 {1e6, 0.001, src}, 126 {25, 0.02, src}, 127 {25, 0.99, src}, 128 {25, 0.46, src}, 129 {25, 0.55, src}, 130 {3, 0.8, src}, 131 } { 132 testBinomial(t, b, i) 133 } 134 } 135 136 func testBinomial(t *testing.T, b Binomial, i int) { 137 const ( 138 tol = 1e-2 139 n = 1e6 140 ) 141 x := make([]float64, n) 142 generateSamples(x, b) 143 sort.Float64s(x) 144 145 checkMean(t, i, x, b, tol) 146 checkVarAndStd(t, i, x, b, tol) 147 checkExKurtosis(t, i, x, b, 7e-2) 148 checkSkewness(t, i, x, b, tol) 149 150 if b.NumParameters() != 2 { 151 t.Errorf("Wrong number of parameters") 152 } 153 }