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GaussianDistribution.h
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2014 Wu Lin
4  * Written (W) 2013 Heiko Strathmann
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32 
33 #ifndef GAUSSIANDISTRIBUTION_H
34 #define GAUSSIANDISTRIBUTION_H
35 
36 #include <shogun/lib/config.h>
37 
38 
40 #include <shogun/lib/SGVector.h>
42 
43 namespace shogun
44 {
45 
46 
61 {
62 public:
65 
76  bool cov_is_factor=false);
77 
79  virtual ~CGaussianDistribution();
80 
89  virtual SGMatrix<float64_t> sample(int32_t num_samples,
90  SGMatrix<float64_t> pre_samples=SGMatrix<float64_t>()) const;
91 
109 
111  virtual const char* get_name() const
112  {
113  return "GaussianDistribution";
114  }
115 
116 
124  static float64_t univariate_log_pdf(float64_t sample, float64_t mu = 0.0, float64_t sigma2 = 1.0)
125  {
126  REQUIRE(sigma2 > 0, "Variance should be positive\n");
127  return -0.5 * (CMath::pow(sample - mu, 2) / sigma2
128  + CMath::log(2.0 * CMath::PI) + CMath::log(sigma2));
129  }
130 private:
131 
133  void init();
134 
135 protected:
138 
142 };
143 
144 }
145 
146 #endif // GAUSSIANDISTRIBUTION_H
#define REQUIRE(x,...)
Definition: SGIO.h:206
A base class for representing n-dimensional probability distribution over the real numbers (64bit) fo...
double float64_t
Definition: common.h:50
static float64_t univariate_log_pdf(float64_t sample, float64_t mu=0.0, float64_t sigma2=1.0)
virtual SGVector< float64_t > log_pdf_multiple(SGMatrix< float64_t > samples) const
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
Dense version of the well-known Gaussian probability distribution, defined as .
static float64_t log(float64_t v)
Definition: Math.h:922
virtual SGVector< float64_t > sample() const
static int32_t pow(bool x, int32_t n)
Definition: Math.h:535
virtual const char * get_name() const
static const float64_t PI
Definition: Math.h:2055

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