/usr/include/shogun/features/SNPFeatures.h is in libshogun-dev 3.2.0-7.3build4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* Written (W) 2010 Soeren Sonnenburg
* Copyright (C) 2010 Berlin Institute of Technology
*/
#ifndef _SNPFEATURES_H___
#define _SNPFEATURES_H___
#include <shogun/lib/common.h>
#include <shogun/features/DotFeatures.h>
#include <shogun/features/StringFeatures.h>
namespace shogun
{
template <class ST> class CStringFeatures;
/** @brief Features that compute the Weighted Degreee Kernel feature space
* explicitly.
*
* \sa CWeightedDegreeStringKernel
*/
class CSNPFeatures : public CDotFeatures
{
public:
/** default constructor */
CSNPFeatures();
/** constructor
*
* @param str stringfeatures (of bytes)
*/
CSNPFeatures(CStringFeatures<uint8_t>* str);
/** copy constructor */
CSNPFeatures(const CSNPFeatures & orig);
/** destructor */
virtual ~CSNPFeatures();
/** obtain the dimensionality of the feature space
*
* (not mix this up with the dimensionality of the input space, usually
* obtained via get_num_features())
*
* @return dimensionality
*/
virtual int32_t get_dim_feature_space() const;
/** compute dot product between vector1 and vector2,
* appointed by their indices
*
* @param vec_idx1 index of first vector
* @param df DotFeatures (of same kind) to compute dot product with
* @param vec_idx2 index of second vector
*/
virtual float64_t dot(int32_t vec_idx1, CDotFeatures* df, int32_t vec_idx2);
/** compute dot product between vector1 and a dense vector
*
* @param vec_idx1 index of first vector
* @param vec2 pointer to real valued vector
* @param vec2_len length of real valued vector
*/
virtual float64_t dense_dot(int32_t vec_idx1, const float64_t* vec2, int32_t vec2_len);
/** add vector 1 multiplied with alpha to dense vector2
*
* @param alpha scalar alpha
* @param vec_idx1 index of first vector
* @param vec2 pointer to real valued vector
* @param vec2_len length of real valued vector
* @param abs_val if true add the absolute value
*/
virtual void add_to_dense_vec(float64_t alpha, int32_t vec_idx1,
float64_t* vec2, int32_t vec2_len, bool abs_val=false);
/** get number of non-zero features in vector
*
* @param num which vector
* @return number of non-zero features in vector
*/
virtual int32_t get_nnz_features_for_vector(int32_t num);
/** iterate over the non-zero features
*
* call get_feature_iterator first, followed by get_next_feature and
* free_feature_iterator to cleanup
*
* @param vector_index the index of the vector over whose components to
* iterate over
* @return feature iterator (to be passed to get_next_feature)
*/
virtual void* get_feature_iterator(int32_t vector_index);
/** iterate over the non-zero features
*
* call this function with the iterator returned by get_first_feature
* and call free_feature_iterator to cleanup
*
* @param index is returned by reference (-1 when not available)
* @param value is returned by reference
* @param iterator as returned by get_first_feature
* @return true if a new non-zero feature got returned
*/
virtual bool get_next_feature(int32_t& index, float64_t& value, void* iterator);
/** clean up iterator
* call this function with the iterator returned by get_first_feature
*
* @param iterator as returned by get_first_feature
*/
virtual void free_feature_iterator(void* iterator);
/** duplicate feature object
*
* @return feature object
*/
virtual CFeatures* duplicate() const;
/** get feature type
*
* @return templated feature type
*/
virtual EFeatureType get_feature_type() const;
/** get feature class
*
* @return feature class
*/
virtual EFeatureClass get_feature_class() const;
/** get number of vectors
*
* @return number of vectors
*/
virtual int32_t get_num_vectors() const;
/** set normalization constant
* @param n n=0 means automagic */
void set_normalization_const(float64_t n=0);
/** get normalization constant */
float64_t get_normalization_const();
/** set the minor base string
*
* @param str base string
*/
void set_minor_base_string(const char* str);
/** set the major base string
*
* @param str base string
*/
void set_major_base_string(const char* str);
/** get the minor base string
*
* @return the minor base string
*/
char* get_minor_base_string();
/** return the major base string
*
* @return major base string
*/
char* get_major_base_string();
/** compute the base strings from current strings optionally taking
* into account snp
*
* @param snp optionally compute base string for snp too
*/
void obtain_base_strings(CSNPFeatures* snp=NULL);
/** @return object name */
virtual const char* get_name() const { return "SNPFeatures"; }
/** compute histogram over strings
*/
virtual SGMatrix<float64_t> get_histogram(bool normalize=true);
/**
* compute 2x3 histogram table
*/
static SGMatrix<float64_t> get_2x3_table(CSNPFeatures* pos, CSNPFeatures* neg);
private:
/** determine minor and major base strings from current strings
* @arg minor - array of string_length inited with zero that will
* contain the minor base string
* @arg major - array of string_length inited with zero that will
* contain the major base string
*/
void find_minor_major_strings(uint8_t* minor, uint8_t* major);
protected:
/** stringfeatures the wdfeatures are based on*/
CStringFeatures<uint8_t>* strings;
/** length of string in vector */
int32_t string_length;
/** number of strings */
int32_t num_strings;
/** dim of feature space */
int32_t w_dim;
/** normalization const */
float64_t normalization_const;
/** allele A */
uint8_t* m_str_min;
/** allele B */
uint8_t* m_str_maj;
};
}
#endif // _SNPFEATURES_H___
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