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tools: make v test-cleancode test everything by default (#10050)
This commit is contained in:
Delyan Angelov
@@ -3,12 +3,12 @@ import math
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fn test_freq() {
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// Tests were also verified on Wolfram Alpha
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data := [f64(10.0),f64(10.0),f64(5.9),f64(2.7)]
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mut o := stats.freq(data,10.0)
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data := [f64(10.0), f64(10.0), f64(5.9), f64(2.7)]
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mut o := stats.freq(data, 10.0)
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assert o == 2
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o = stats.freq(data,2.7)
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o = stats.freq(data, 2.7)
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assert o == 1
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o = stats.freq(data,15)
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o = stats.freq(data, 15)
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assert o == 0
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}
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@@ -21,15 +21,15 @@ fn tst_res(str1 string, str2 string) bool {
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fn test_mean() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '5.762500')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '17.650000')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '37.708000')
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@@ -37,31 +37,32 @@ fn test_mean() {
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fn test_geometric_mean() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.geometric_mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(),'5.15993')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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assert tst_res(o.str(), '5.15993')
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.geometric_mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert o.str().eq('nan') || o.str().eq('-nan') || o.str().eq('-1.#IND00') || o == f64(0) || o.str().eq('-nan(ind)') // Because in math it yields a complex number
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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assert o.str().eq('nan') || o.str().eq('-nan') || o.str().eq('-1.#IND00') || o == f64(0)
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|| o.str().eq('-nan(ind)') // Because in math it yields a complex number
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.geometric_mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(),'25.064496')
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assert tst_res(o.str(), '25.064496')
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}
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fn test_harmonic_mean() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.harmonic_mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '4.626519')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.harmonic_mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '9.134577')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.harmonic_mean(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '16.555477')
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@@ -72,56 +73,58 @@ fn test_median() {
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// Assumes sorted array
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// Even
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mut data := [f64(2.7),f64(4.45),f64(5.9),f64(10.0)]
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mut data := [f64(2.7), f64(4.45), f64(5.9), f64(10.0)]
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mut o := stats.median(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '5.175000')
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data = [f64(-3.0),f64(1.89),f64(4.4),f64(67.31)]
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data = [f64(-3.0), f64(1.89), f64(4.4), f64(67.31)]
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o = stats.median(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '3.145000')
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data = [f64(7.88),f64(12.0),f64(54.83),f64(76.122)]
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data = [f64(7.88), f64(12.0), f64(54.83), f64(76.122)]
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o = stats.median(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '33.415000')
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// Odd
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data = [f64(2.7),f64(4.45),f64(5.9),f64(10.0),f64(22)]
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data = [f64(2.7), f64(4.45), f64(5.9), f64(10.0), f64(22)]
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o = stats.median(data)
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assert o == f64(5.9)
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data = [f64(-3.0),f64(1.89),f64(4.4),f64(9),f64(67.31)]
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data = [f64(-3.0), f64(1.89), f64(4.4), f64(9), f64(67.31)]
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o = stats.median(data)
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assert o == f64(4.4)
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data = [f64(7.88),f64(3.3),f64(12.0),f64(54.83),f64(76.122)]
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data = [f64(7.88), f64(3.3), f64(12.0), f64(54.83), f64(76.122)]
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o = stats.median(data)
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assert o == f64(12.0)
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}
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fn test_mode() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(2.7),f64(2.7),f64(4.45),f64(5.9),f64(10.0)]
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mut data := [f64(2.7), f64(2.7), f64(4.45), f64(5.9), f64(10.0)]
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mut o := stats.mode(data)
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assert o == f64(2.7)
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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)]
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data = [f64(-3.0), f64(1.89), f64(1.89), f64(1.89), f64(9), f64(4.4), f64(4.4), f64(9),
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f64(67.31),
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]
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o = stats.mode(data)
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assert o == f64(1.89)
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// Testing greedy nature
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data = [f64(2.0),f64(4.0),f64(2.0),f64(4.0)]
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data = [f64(2.0), f64(4.0), f64(2.0), f64(4.0)]
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o = stats.mode(data)
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assert o == f64(2.0)
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}
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fn test_rms() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.rms(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '6.362046')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.rms(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '33.773393')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.rms(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '47.452561')
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@@ -129,15 +132,15 @@ fn test_rms() {
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fn test_population_variance() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.population_variance(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '7.269219')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.population_variance(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '829.119550')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.population_variance(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '829.852282')
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@@ -145,15 +148,15 @@ fn test_population_variance() {
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fn test_sample_variance() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.sample_variance(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '9.692292')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.sample_variance(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '1105.492733')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.sample_variance(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '1106.469709')
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@@ -161,15 +164,15 @@ fn test_sample_variance() {
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fn test_population_stddev() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.population_stddev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '2.696149')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.population_stddev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '28.794436')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.population_stddev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '28.807157')
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@@ -177,15 +180,15 @@ fn test_population_stddev() {
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fn test_sample_stddev() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.sample_stddev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '3.113245')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.sample_stddev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '33.248951')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.sample_stddev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '33.263639')
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@@ -193,15 +196,15 @@ fn test_sample_stddev() {
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fn test_mean_absdev() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.mean_absdev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '2.187500')
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.mean_absdev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '24.830000')
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.mean_absdev(data)
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// Some issue with precision comparison in f64 using == operator hence serializing to string
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assert tst_res(o.str(), '27.768000')
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@@ -209,46 +212,46 @@ fn test_mean_absdev() {
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fn test_min() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.min(data)
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assert o == f64(2.7)
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.min(data)
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assert o == f64(-3.0)
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.min(data)
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assert o == f64(7.88)
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}
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fn test_max() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.max(data)
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assert o == f64(10.0)
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.max(data)
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assert o == f64(67.31)
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.max(data)
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assert o == f64(76.122)
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}
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fn test_range() {
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// Tests were also verified on Wolfram Alpha
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mut data := [f64(10.0),f64(4.45),f64(5.9),f64(2.7)]
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mut data := [f64(10.0), f64(4.45), f64(5.9), f64(2.7)]
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mut o := stats.range(data)
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assert o == f64(7.3)
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data = [f64(-3.0),f64(67.31),f64(4.4),f64(1.89)]
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data = [f64(-3.0), f64(67.31), f64(4.4), f64(1.89)]
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o = stats.range(data)
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assert o == f64(70.31)
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data = [f64(12.0),f64(7.88),f64(76.122),f64(54.83)]
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data = [f64(12.0), f64(7.88), f64(76.122), f64(54.83)]
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o = stats.range(data)
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assert o == f64(68.242)
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}
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fn test_passing_empty() {
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data := []f64{}
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assert stats.freq(data,0) == 0
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assert stats.freq(data, 0) == 0
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assert stats.mean(data) == f64(0)
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assert stats.geometric_mean(data) == f64(0)
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assert stats.harmonic_mean(data) == f64(0)
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