Lines Matching refs:samples
64 func getStatsResults(samples []float64) *statsResults {
67 for _, s := range samples {
71 res.mean = sum / float64(len(samples))
72 res.stddev = math.Sqrt(squaresum/float64(len(samples)) - res.mean*res.mean)
76 func checkSampleDistribution(t *testing.T, samples []float64, expected *statsResults) {
77 actual := getStatsResults(samples)
84 func checkSampleSliceDistributions(t *testing.T, samples []float64, nslices int, expected *statsResults) {
85 chunk := len(samples) / nslices
90 high = len(samples) - 1
94 checkSampleDistribution(t, samples[low:high], expected)
104 samples := make([]float64, nsamples)
105 for i := range samples {
106 samples[i] = r.NormFloat64()*stddev + mean
108 return samples
114 samples := generateNormalSamples(nsamples, mean, stddev, seed)
119 checkSampleDistribution(t, samples, expected)
122 checkSampleSliceDistributions(t, samples, 2, expected)
125 checkSampleSliceDistributions(t, samples, 7, expected)
161 samples := make([]float64, nsamples)
162 for i := range samples {
163 samples[i] = r.ExpFloat64() / rate
165 return samples
174 samples := generateExponentialSamples(nsamples, rate, seed)
179 checkSampleDistribution(t, samples, expected)
182 checkSampleSliceDistributions(t, samples, 2, expected)
185 checkSampleSliceDistributions(t, samples, 7, expected)
384 samples := make([]float64, n)
386 samples[i] = float64(val)
389 checkSampleDistribution(t, samples, expected)
