public void GenerateTest5()
{
Accord.Math.Tools.SetupGenerator(1);
var target = new GammaDistribution(42, 0.1337);
var samples = target.Generate(10000000);
var actual = GammaDistribution.Estimate(samples);
Assert.AreEqual(42, actual.Scale, 5e-2);
Assert.AreEqual(0.1337, actual.Shape, 5e-4);
}
public void FitTest()
{
// Gamma Distribution Fit stalls for some arrays #159
// https://github.com/accord-net/framework/issues/159
double[] x = { 1275.56, 1239.44, 1237.92, 1237.22, 1237.1, 1238.41, 1238.62, 1237.05, 1237.19, 1236.51, 1264.6, 1238.19, 1237.39, 1235.79, 1236.53, 1236.8, 1238.06, 1236.5, 1235.32, 1236.44, 1236.58, 1236.3, 1237.91, 1238.6, 1238.49, 1239.21, 1238.57, 1244.63, 1236.06, 1236.4, 1237.88, 1237.56, 1236.66, 1236.59, 1236.53, 1236.32, 1238.29, 1237.79, 1237.86, 1236.42, 1236.23, 1236.37, 1237.18, 1237.63, 1245.8, 1238.04, 1238.55, 1238.39, 1236.75, 1237.07, 1250.78, 1238.6, 1238.36, 1236.58, 1236.82, 1238.4, 1257.68, 1237.78, 1236.52, 1234.9, 1237.9, 1238.58, 1238.12, 1237.89, 1236.54, 1236.55, 1238.37, 1237.29, 1237.64, 1236.8, 1237.73, 1236.71, 1238.23, 1237.84, 1236.26, 1237.58, 1238.31, 1238.4, 1237.08, 1236.61, 1235.92, 1236.41, 1237.89, 1237.98, 1246.75, 1237.92, 1237.1, 1237.97, 1238.69, 1237.05, 1236.96, 1239.44, 1238.49, 1237.88, 1236.01, 1236.57, 1236.44, 1235.76, 1237.62, 1238, 1263.14, 1237.66, 1237, 1236, 1261.96, 1238.58, 1237.77, 1237.06, 1236.31, 1238.63, 1237.23, 1236.85, 1236.23, 1236.46, 1236.9, 1237.85, 1238, 1237.02, 1236.19, 1236.05, 1235.73, 1258.3, 1235.98, 1237.76, 1246.93, 1239.1, 1237.72, 1237.67, 1236.79, 1237.61, 1238.41, 1238.29, 1238.11, 1237, 1236.52, 1236.6, 1236.31, 1237.77, 1238.58, 1237.88, 1247.35, 1236.14, 1236.83, 1236.15, 1237.93, 1238.16, 1237.34, 1236.78, 1238.66, 1237.76, 1237.19, 1236.7, 1236.04, 1236.66, 1237.86, 1238.54, 1238.05, 1238.41, 1236.94, 1240.95, 1261.01, 1237.72, 1237.91, 1238.2, 1235.68, 1236.89, 1235.12, 1271.31, 1236.97, 1270.76, 1238.52, 1238.19, 1238.6, 1237.16, 1236.72, 1236.71, 1237.14, 1238.48, 1237.95, 1237.42, 1235.86, 1236.39, 1236.13, 1236.58, 1237.95, 1237.76, 1237.39, 1238.16, 1236.31, 1236.41, 1236.12, 1238.7, 1236.48, 1237.84, 1236.38, 1237.95, 1238.48, 1236.51, 1236.56 };
var gamma = GammaDistribution.Estimate(x);
Assert.AreEqual(1238.8734170854279, gamma.Mean);
Assert.AreEqual(41566.439533445438, gamma.Shape);
Assert.AreEqual(0.029804655654680219, gamma.Scale);
}
public void NegativeValueTest()
{
double[] samples = NormalDistribution.Standard.Generate(100);
try
{
GammaDistribution.Estimate(samples);
Assert.Fail();
}
catch (ArgumentException)
{
}
}
public void GenerateTest6()
{
// https://github.com/accord-net/framework/issues/281
Accord.Math.Random.Generator.Seed = 1;
var target = new GammaDistribution(1.5, 0.9);
var samples = target.Generate(10000000);
var actual = GammaDistribution.Estimate(samples);
Assert.AreEqual(1.5, actual.Scale, 5e-2);
Assert.AreEqual(0.9, actual.Shape, 5e-4);
}
public void GenerateTest2()
{
Accord.Math.Tools.SetupGenerator(0);
GammaDistribution target = new GammaDistribution(5, 2);
double[] samples = target.Generate(10000000);
var actual = GammaDistribution.Estimate(samples);
Assert.AreEqual(5, actual.Scale, 1e-3);
Assert.AreEqual(2, actual.Shape, 1e-3);
}
public void FitTestOptions()
{
// Gamma Distribution Fit stalls for some arrays #301
// https://github.com/accord-net/framework/issues/301
double[] x = { 1.003, 1.012, 1.011, 1.057, 1.033, 1.051, 1.045, 1.045, 1.037, 1.059, 1.028, 1.032, 1.029, 1.031, 1.029, 1.023, 1.035 };
var gamma = GammaDistribution.Estimate(x, tol: 1e-2, iterations: 0);
Assert.AreEqual(1.0329411764705885, gamma.Mean, 1e-10);
Assert.AreEqual(4679.4730319532555, gamma.Shape, 1e-10);
Assert.AreEqual(0.00022073878178531338, gamma.Scale, 1e-10);
}
public void distribution_hangs()
{
// https://github.com/accord-net/framework/issues/304
double[] dataset1 = { 8.141, 8.516, 7.049, 7.555, 7.999, 9.638, 7.445, 8.322, 8.184, 9.138, 8.489, 7.138, 7.855, 8.354, 10.648, 9.036, 9.371, 7.243, 6.967, 7.570, 8.636, 9.734, 8.713, 8.898, 7.969, 7.223, 7.162, 9.536, 8.919, 8.304, 7.746, 8.911, 7.857, 9.024, 7.383, 8.928, 7.410, 9.033, 7.912, 7.751, 7.359, 7.920, 7.294, 7.583, 8.122, 7.586, 7.011, 8.460, 9.126, 7.247, 9.816, 8.411, 8.833, 9.028, 8.271, 7.698, 7.399, 9.823, 8.202, 8.413, 7.384, 7.721, 7.384, 7.660, 7.698, 8.396, 8.038, 7.295, 8.202, 9.214, 10.263, 7.990, 7.502, 8.502, 8.022, 7.824, 9.193, 9.490, 9.279, 8.961, 8.213, 7.448, 8.385, 9.276, 8.178, 7.102, 7.206, 7.594, 7.718, 7.770, 7.997, 7.866, 8.157, 9.319, 7.449, 8.559, 7.617, 8.074, 7.922, 9.178, 8.738, 7.679, 7.983, 8.307, 8.022, 9.407, 7.667, 8.844, 8.134, 8.383, 8.395, 8.004, 9.252, 8.130, 7.934, 8.140, 7.924, 8.893, 6.850, 8.238, 9.762, 7.544, 8.845, 7.595, 8.453, 7.892, 8.007, 8.352, 8.537, 9.402 };
double[] dataset2 = { 0.999, 0.996, 1.066, 1.041, 1.052, 1.043, 1.052, 1.046, 1.032, 1.038, 1.052, 1.038, 1.040, 1.056, 1.043, 1.044, 1.058, 1.044, 1.053, 1.046, 1.045, 1.046, 1.048, 1.051, 1.056, 1.058, 1.065, 1.051, 1.049, 1.049, 1.043, 1.042, 1.049, 1.042, 1.033, 1.042, 1.028, 1.031, 1.036, 1.044, 1.037, 1.054, 1.046, 1.061, 1.048, 1.048, 1.028, 1.030, 1.049, 1.038, 1.042, 1.057, 1.028, 1.047, 1.044, 1.040, 1.038, 1.044, 1.046, 1.035, 1.040, 1.039, 1.046, 1.050, 1.033, 1.032, 1.040, 1.040, 1.032, 1.045, 1.054, 1.040, 1.045, 1.045, 1.043, 1.066, 1.057, 1.052, 1.060, 1.069, 1.046, 1.041, 1.048, 1.057, 1.059, 1.076, 1.051, 1.057, 1.067, 1.062, 1.025, 1.072, 1.061, 1.067, 1.062, 1.055, 1.065, 1.047, 1.046, 1.047, 1.045, 1.038, 1.056, 1.037, 1.042, 1.044, 1.047, 1.037, 1.047, 1.041, 1.042, 1.042, 1.042, 1.040, 1.060, 1.066, 1.067, 1.077, 1.059, 1.067 };
// with Accord.NET the results of the gamma fit are
// Dataset1: k = 119.306665626699, θ = 0.0690958879514208 (rate=1/θ = 14.4726412764688)
// Dataset2: k = 6952.29276909337, θ = 0.00015060019786871 (rate=1/θ = 6640.0975174798)
// with the same data a gamma distribution fit was performed online via "http://www.wessa.net/rwasp_fitdistrgamma.wasp"
// Dataset1: shape= 115.405346712493, rate = 13.9994954351296 (θ= 1/shape= 0.07143114583191708605319342679921)
// Dataset2: shape= 6930.15592532156 , rate = 6618.95473828367 (θ= 1/shape= 0.00015108125671506031378872360567992)
var a = GammaDistribution.Estimate(dataset1);
Assert.AreEqual(0.069095887951420826, a.Scale, 1e-8);
Assert.AreEqual(119.30666562669866, a.Shape, 1e-8);
var b = GammaDistribution.Estimate(dataset2);
Assert.AreEqual(0.00015060019786871043, b.Scale, 1e-8);
Assert.AreEqual(6952.2927690933739, b.Shape, 1e-8);
double[] pdfa = dataset1.Apply(a.ProbabilityDensityFunction);
double[] pdfb = dataset2.Apply(b.ProbabilityDensityFunction);
double[] ay = plot(dataset1, a);
string stra = ay.ToCSharp();
double[] expecteda = new double[] { 0.0927186751703724, 0.102929217255775, 0.113853912640037, 0.125490882412066, 0.137831384027626, 0.150859382782722, 0.164551205816893, 0.178875290227262, 0.193792035506903, 0.209253768840681, 0.225204829830127, 0.241581779018976, 0.25831373220303, 0.275322819989417, 0.292524769484354, 0.309829602400448, 0.327142441352633, 0.344364413721372, 0.36139364026723, 0.378126293740165, 0.394457711091658, 0.410283541612013, 0.425500912411485, 0.440009592166544, 0.453713133972042, 0.466519978477992, 0.478344499233706, 0.489107973291516, 0.498739461604722, 0.507176585549156, 0.514366187957508, 0.520264869325212, 0.524839392269736, 0.528066949839688, 0.529935295816686, 0.530442737670986, 0.529597995264547, 0.527419930690551, 0.523937156748862, 0.51918753344197, 0.513217563503365, 0.50608169931424, 0.497841574608112, 0.488565175098291, 0.478325962588825, 0.467201967252403, 0.455274862593154, 0.442629037177336, 0.429350676535845, 0.415526867748883, 0.401244738146801, 0.386590638336579, 0.37164937842665, 0.356503524908677, 0.341232764198471, 0.325913337372842, 0.310617549195024, 0.29541335312659, 0.280364012703018, 0.265527838423449, 0.250957998190604, 0.236702398346326, 0.222803631491404, 0.209298986560572, 0.196220516046194, 0.183595154826475, 0.171444884751058, 0.159786938962256, 0.148634039874823, 0.137994664790792, 0.127873333276316, 0.118270910662634, 0.109184922339614, 0.100609873875035, 0.0925375724026959, 0.0849574451652891, 0.0778568515617006, 0.0712213855225515, 0.0650351655120983, 0.0592811099206679, 0.0539411960619302, 0.0489967014173125, 0.0444284261704561, 0.0402168964441056, 0.0363425479871147, 0.0327858903587122, 0.0295276519198202, 0.0265489061670697, 0.0238311801347997, 0.0213565457451675, 0.0191076951082055, 0.0170680008645135, 0.0152215627257103, 0.0135532414045203, 0.012048681140193, 0.0106943220187805, 0.00947740326439647, 0.00838595863975468, 0.00740880504465858, 0.00653552534217913 };
Assert.IsTrue(ay.IsEqual(expecteda.Log(), 1e-8));
double[] by = plot(dataset2, b);
string strb = by.ToCSharp();
double[] expectedb = new double[] { -5.02287583851557, -4.75049252465396, -4.48269919286031, -4.21948839264951, -3.96085269165997, -3.7067846755981, -3.45727694817651, -3.21232213106123, -2.97191286381076, -2.73604180381335, -2.50470162623969, -2.27788502397743, -2.05558470757569, -1.8377934051905, -1.62450386252749, -1.41570884278372, -1.21140112659032, -1.01157351196434, -0.816218814241438, -0.62532986603037, -0.438899517150276, -0.256920634583366, -0.079386102411263, 0.0937111782322972, 0.262378289222397, 0.426622295487505, 0.586450245075866, 0.741869169200072, 0.892886082292534, 1.03950798206188, 1.18174184954296, 1.31959464915144, 1.45307332873381, 1.58218481962467, 1.70693603669679, 1.82733387840926, 1.94338522686394, 2.05509694785906, 2.16247589093564, 2.26552888942933, 2.36426276052498, 2.45868430530481, 2.5488003087994, 2.63461754003947, 2.71614275210504, 2.79338268217543, 2.86634405157747, 2.93503356584097, 2.99945791474238, 3.05962377235392, 3.11553779709811, 3.16720663179149, 3.21463690369819, 3.25783522457004, 3.29680819070381, 3.33156238298761, 3.36210436694364, 3.38844069278093, 3.41057789544175, 3.42852249464886, 3.44228099495103, 3.45185988577396, 3.45726564146389, 3.45850472133588, 3.45558356971742, 3.44850861599934, 3.43728627467954, 3.42192294540746, 3.40242501303237, 3.37879884764789, 3.35105080463927, 3.31918722472255, 3.28321443399909, 3.24313874399377, 3.19896645169865, 3.15070383962393, 3.0983571758361, 3.04193271400709, 2.98143669345427, 2.91687533918594, 2.84825486194768, 2.77558145825969, 2.69886131046587, 2.61810058677565, 2.53330544130586, 2.44448201412342, 2.35163643128908, 2.2547748049019, 2.15390323313659, 2.04902780028988, 1.94015457682235, 1.82728961939847, 1.71043897092841, 1.5896086606117, 1.4648047039791, 1.33603310292983, 1.20329984577529, 1.06661090728176, 0.925972248708604, 0.781389817848321 };
Assert.IsTrue(by.IsEqual(expectedb, 1e-8));
double[] x = Vector.Range(0.0, 10.0, 0.05);
double[] pdf = x.Apply(b.LogProbabilityDensityFunction).Exp();
string str = pdf.ToCSharp();
double[] expected = new double[] { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.60168777623766E-293, 5.51885646801681E-214, 6.87229105720087E-150, 3.05548162854266E-99, 2.07661256908294E-60, 4.84694366550593E-32, 5.26688946739727E-13, 0.0241774294264879, 30.7996636820675, 0.0054993586504859, 5.60031174239992E-13, 1.10634606299171E-28, 1.24123786224247E-49, 2.04031751961623E-75, 1.13865913049715E-105, 4.56124541509388E-140, 2.56251968244235E-178, 3.68510891441049E-220, 2.33359893081555E-265, 1.06302359249589E-313, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };;
Assert.IsTrue(pdf.IsEqual(expected, 1e-8));
}
public void GenerateTest4()
{
Accord.Math.Tools.SetupGenerator(1);
GammaDistribution target = new GammaDistribution(0.4, 0.2);
double[] samples = new double[10000000];
for (int i = 0; i < samples.Length; i++)
{
samples[i] = target.Generate();
}
var actual = GammaDistribution.Estimate(samples);
Assert.AreEqual(0.4, actual.Scale, 1e-3);
Assert.AreEqual(0.2, actual.Shape, 1e-3);
}