atmosphere source code

1 /++
2 This module publicly imports all classes.
3 
4 Import:
5 --------
6 import atmosphere;
7 --------
8 
9 Class_hierarchy:
10 - [MixtureOptimizer](atmosphere/mixture/MixtureOptimizer.html)
11 	- [ExpectationMaximization](atmosphere/mixture/ExpectationMaximization.html)
12 		- [LikelihoodAscentEM](atmosphere/mixture/LikelihoodAscentEM.html) : [LikelihoodAscent](atmosphere/mixture/LikelihoodAscent.html)
13 	- [GradientDescent](atmosphere/mixture/GradientDescent.html)
14 	- [GradientDescentPartial](atmosphere/mixture/GradientDescentPartial.html)
15 		- [LikelihoodAscentGradient](atmosphere/mixture/LikelihoodAscentGradient.html) : [LikelihoodAscent](atmosphere/mixture/LikelihoodAscent.html)
16 	- [CoordinateDescent](atmosphere/mixture/CoordinateDescent.html)
17 	- [CoordinateDescentPartial](atmosphere/mixture/CoordinateDescentPartial.html)
18 		- [LikelihoodAscentCoordinate](atmosphere/mixture/LikelihoodAscentCoordinate.html) : [LikelihoodAscent](atmosphere/mixture/LikelihoodAscent.html)
19 	- [NvmmLikelihoodAscentEM](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEM.html) : [LikelihoodAscent](atmosphere/mixture/LikelihoodAscent.html)
20 		- [NvmmLikelihoodAscentEMEM](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEMEM.html)
21 		- [NvmmLikelihoodAscentEMGradient](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEMGradient.html)
22 		- [NvmmLikelihoodAscentEMCoordinate](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEMCoordinate.html)
23 
24 See_Also: [Atmosphere GM Test](https://github.com/9il/atmosphere_gm_test)
25 
26 +/
27 
28 /+
29 
30 Table of separating mixtures algorithms:
31 	$(TABLE
32 		$(TR  $(TH Class) $(TH BLAS Level 2 % of all computations) $(TH Non-BLAS parallel) $(TH   Speed (one thread & big data) ) $(TH Global maximum for convex function) $(TH Parameterized))
33 		$(TR $(TD [GradientDescent](atmosphere/mixture/GradientDescent.html), number of mixture components > ~16) $(TD ~95-99%) $(TD No) $(TD  normal ) $(TD Yes) $(TD No) )
34 		$(TR $(TD [GradientDescent](atmosphere/mixture/GradientDescent.html), number of mixture components < ~16) $(TD ~95-99%) $(TD No) $(TD  fast ) $(TD Yes) $(TD No) )
35 		$(TR $(TD [CoordinateDescent](atmosphere/mixture/CoordinateDescent.html)) $(TD ~10-50%) $(TD No) $(TD  fast ) $(TD Yes) $(TD No) )
36 		$(TR $(TD [CoordinateDescentPartial](atmosphere/mixture/LikelihoodAscentCoordinate.html)) $(TD ~10-50%) $(TD No) $(TD  fast, always faster then CoordinateDescent ) $(TD Yes) $(TD No) )
37 		$(TR $(TD [NvmmLikelihoodAscentEMEM](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEMEM.html)) $(TD ~10%) $(TD Yes) $(TD  slow ) $(TD No) $(TD Yes) )
38 		$(TR $(TD [NvmmLikelihoodAscentEMGradient](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEMGradient.html)) $(TD ~10%) $(TD Yes) $(TD  slow ) $(TD No) $(TD Yes) )
39 		$(TR $(TD [NvmmLikelihoodAscentEMCoordinate](atmosphere/parametrized/nvmm/NvmmLikelihoodAscentEMCoordinate.html)) $(TD ~5%) $(TD Partial) $(TD  slow ) $(TD No) $(TD Yes) ) )
40 +/
41 /**
42 Authors: [Ilya Yaroshenko](http://9il.github.io)
43 
44 Copyright: © 2014-2015 [Ilya Yaroshenko](http://9il.github.io)
45 
46 License: MIT
47 */
48 module atmosphere;
49 
50 ///
51 unittest
52 {
53 	import core.time;
54 	import std.random;
55 	import std.range;
56 	import std.algorithm;
57 	import atmosphere;
58 
59 	alias F = double;
60 
61 	final class ProperGeneralizedInverseGaussianQuantile(T) : NumericQuantile!T {
62 		this(T lambda, T eta, T omega) {
63 			auto cdf = new ProperGeneralizedInverseGaussianCDF!T(lambda, eta, omega);
64 			super(cdf, -1000, 1000);	
65 		}
66 	}
67 
68 	nothrow @nogc bool findRootTolerance(F a, F b) { return b/a < 1.001;}
69 	
70 	immutable quantileL  = 0.01;
71 	immutable quantileR  = 0.99;
72 	immutable gridSize   = 100;
73 	immutable dur        = TickDuration.from!"msecs"(100);
74 	immutable lambda     = 2;
75 	immutable eta        = 1; 
76 	immutable omega      = 2.3;
77 	immutable beta       = 0.5;
78 	immutable sampleSize = 1000;
79 	// GIG quantile function
80 	auto qf              = new ProperGeneralizedInverseGaussianQuantile!F(lambda, eta, omega);
81 	// GHyp random number generator
82 	auto rng             = new ProperGeneralizedHyperbolicRNG!F(rndGen, lambda, eta, omega, beta);
83 	// left GIG bound
84 	immutable begin      = qf(quantileL);
85 	// right GIG bound
86 	immutable end        = qf(quantileR);
87 	// grid's step
88 	immutable step       = (end-begin)/gridSize;
89 	// GIG grid
90 	immutable grid       = iota(begin, end+step/2, step).array;
91 	// Normal PDFs for common algorithms
92 	auto pdfs            = grid.map!(u => NvmmLikelihoodAscentEM!F.CorePDF(beta, u)).array;
93 	// GHyp sample
94 	immutable sample     = cast(immutable) rng.take(sampleSize).array;
95 	// Mixture optimizer
96 	auto optimizer       = new LikelihoodAscentEM!F(pdfs.length, sample.length);
97 	// Puts sample
98 	optimizer.put(pdfs, sample);
99 	// Tuple of time and iterations count
100 	immutable result     = optimizer.evaluate(dur, &findRootTolerance);
101 }
102 
103 public import atmosphere.cdf;
104 public import atmosphere.derivative;
105 public import atmosphere.finitemixture;
106 public import atmosphere.mixture;
107 public import atmosphere.moment;
108 public import atmosphere.params;
109 public import atmosphere.pdf;
110 public import atmosphere.quantile;
111 public import atmosphere.random;
112 
113 public import atmosphere.estimate;
114 public import atmosphere.likelihood;