diff options
Diffstat (limited to 'v_windows/v/old/vlib/math/stats/stats_test.v')
| -rw-r--r-- | v_windows/v/old/vlib/math/stats/stats_test.v | 269 |
1 files changed, 269 insertions, 0 deletions
diff --git a/v_windows/v/old/vlib/math/stats/stats_test.v b/v_windows/v/old/vlib/math/stats/stats_test.v new file mode 100644 index 0000000..c18daff --- /dev/null +++ b/v_windows/v/old/vlib/math/stats/stats_test.v @@ -0,0 +1,269 @@ +import math.stats +import math + +fn test_freq() { + // Tests were also verified on Wolfram Alpha + data := [f64(10.0), f64(10.0), f64(5.9), f64(2.7)] + mut o := stats.freq(data, 10.0) + assert o == 2 + o = stats.freq(data, 2.7) + assert o == 1 + o = stats.freq(data, 15) + assert o == 0 +} + +fn tst_res(str1 string, str2 string) bool { + if (math.abs(str1.f64() - str2.f64())) < 1e-5 { + return true + } + return false +} + +fn test_mean() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '5.762500') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '17.650000') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '37.708000') +} + +fn test_geometric_mean() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.geometric_mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '5.15993') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.geometric_mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert o.str() == 'nan' || o.str() == '-nan' || o.str() == '-1.#IND00' || o == f64(0) + || o.str() == '-nan(ind)' // Because in math it yields a complex number + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.geometric_mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '25.064496') +} + +fn test_harmonic_mean() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.harmonic_mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '4.626519') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.harmonic_mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '9.134577') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.harmonic_mean(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '16.555477') +} + +fn test_median() { + // Tests were also verified on Wolfram Alpha + // Assumes sorted array + + // Even + mut data := [f64(2.7), f64(4.45), f64(5.9), f64(10.0)] + mut o := stats.median(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '5.175000') + data = [f64(-3.0), f64(1.89), f64(4.4), f64(67.31)] + o = stats.median(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '3.145000') + data = [f64(7.88), f64(12.0), f64(54.83), f64(76.122)] + o = stats.median(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '33.415000') + + // Odd + data = [f64(2.7), f64(4.45), f64(5.9), f64(10.0), f64(22)] + o = stats.median(data) + assert o == f64(5.9) + data = [f64(-3.0), f64(1.89), f64(4.4), f64(9), f64(67.31)] + o = stats.median(data) + assert o == f64(4.4) + data = [f64(7.88), f64(3.3), f64(12.0), f64(54.83), f64(76.122)] + o = stats.median(data) + assert o == f64(12.0) +} + +fn test_mode() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(2.7), f64(2.7), f64(4.45), f64(5.9), f64(10.0)] + mut o := stats.mode(data) + assert o == f64(2.7) + data = [f64(-3.0), f64(1.89), f64(1.89), f64(1.89), f64(9), f64(4.4), f64(4.4), f64(9), + f64(67.31), + ] + o = stats.mode(data) + assert o == f64(1.89) + // Testing greedy nature + data = [f64(2.0), f64(4.0), f64(2.0), f64(4.0)] + o = stats.mode(data) + assert o == f64(2.0) +} + +fn test_rms() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.rms(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '6.362046') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.rms(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '33.773393') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.rms(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '47.452561') +} + +fn test_population_variance() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.population_variance(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '7.269219') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.population_variance(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '829.119550') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.population_variance(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '829.852282') +} + +fn test_sample_variance() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.sample_variance(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '9.692292') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.sample_variance(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '1105.492733') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.sample_variance(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '1106.469709') +} + +fn test_population_stddev() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.population_stddev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '2.696149') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.population_stddev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '28.794436') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.population_stddev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '28.807157') +} + +fn test_sample_stddev() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.sample_stddev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '3.113245') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.sample_stddev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '33.248951') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.sample_stddev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '33.263639') +} + +fn test_mean_absdev() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.mean_absdev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '2.187500') + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.mean_absdev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '24.830000') + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.mean_absdev(data) + // Some issue with precision comparison in f64 using == operator hence serializing to string + assert tst_res(o.str(), '27.768000') +} + +fn test_min() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.min(data) + assert o == f64(2.7) + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.min(data) + assert o == f64(-3.0) + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.min(data) + assert o == f64(7.88) +} + +fn test_max() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.max(data) + assert o == f64(10.0) + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.max(data) + assert o == f64(67.31) + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.max(data) + assert o == f64(76.122) +} + +fn test_range() { + // Tests were also verified on Wolfram Alpha + mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)] + mut o := stats.range(data) + assert o == f64(7.3) + data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)] + o = stats.range(data) + assert o == f64(70.31) + data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)] + o = stats.range(data) + assert o == f64(68.242) +} + +fn test_passing_empty() { + data := []f64{} + assert stats.freq(data, 0) == 0 + assert stats.mean(data) == f64(0) + assert stats.geometric_mean(data) == f64(0) + assert stats.harmonic_mean(data) == f64(0) + assert stats.median(data) == f64(0) + assert stats.mode(data) == f64(0) + assert stats.rms(data) == f64(0) + assert stats.population_variance(data) == f64(0) + assert stats.sample_variance(data) == f64(0) + assert stats.population_stddev(data) == f64(0) + assert stats.sample_stddev(data) == f64(0) + assert stats.mean_absdev(data) == f64(0) + assert stats.min(data) == f64(0) + assert stats.max(data) == f64(0) + assert stats.range(data) == f64(0) +} |