BALL
1.4.2
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#include <BALL/QSAR/statistics.h>
Public Member Functions | |
Constructors and Destructors | |
Statistics () | |
~Statistics () | |
Static Public Member Functions | |
static functions | |
static void | scaling (std::vector< double > &v) |
static void | scaling (std::vector< std::vector< double > > &m) |
static void | centering (std::vector< std::vector< double > > &m) |
static void | centering (std::vector< double > &v) |
static void | centering (vector< double > &v, double &mean, double &std) |
static double | getVariance (const std::vector< double > &v, double mean=-1) |
static double | getStddev (const vector< double > &v, double mean=-1) |
static double | getCovariance (const vector< double > &v1, const vector< double > &v2, double mean1, double mean2) |
static double | getMean (const std::vector< double > &v) |
static double | getRowCovariance (const vector< vector< double > > &v, int row1, int row2, double mean1=-1, double mean2=-1, std::multiset< int > *features_to_use=0) |
static double | getRowMean (const vector< vector< double > > &v, int row, std::multiset< int > *features_to_use=0) |
static double | getRowVariance (const vector< vector< double > > &v, int row, double mean=-1, std::multiset< int > *features_to_use=0) |
static double | getRowStddev (const vector< vector< double > > &v, int row, double mean=-1, std::multiset< int > *features_to_use=0) |
static void | centering (BALL::Matrix< double > &m) |
static void | centering (BALL::Matrix< double > &m, int col) |
static double | getMean (const BALL::Matrix< double > &m, int col) |
static double | getVariance (const BALL::Matrix< double > &m, int col, double mean=-1) |
static double | getStddev (const BALL::Matrix< double > &m, int col, double mean=-1) |
static double | getCovariance (const BALL::Matrix< double > &m, int col1, int col2, double mean1=-1, double mean2=-1) |
static double | sq (const BALL::Matrix< double > &m, int col, double mean=-1) |
static double | distance (const BALL::Matrix< double > &m, int &row1, int &row2, double &p) |
static double | distance (const BALL::Matrix< double > &m1, const BALL::Matrix< double > &m2, int &row1, int &row2, double &p) |
static double | distance (const BALL::Matrix< double > &m1, const BALL::Matrix< double > &m2, int &row1, int &row2, String &f, String &g) |
static double | euclDistance (const BALL::Matrix< double > &m1, const BALL::Matrix< double > &m2, int row1, int row2) |
static double | euclNorm (const Vector< double > &cv) |
static double | euclDistance (const Vector< double > &c1, const Vector< double > &c2) |
static double | scalarProduct (const Vector< double > &cv) |
class for statistical correction of input-data
Definition at line 42 of file statistics.h.
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defaut constructor
Definition at line 49 of file statistics.h.
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defaut destructor
Definition at line 52 of file statistics.h.
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centers each colum of the given vector-based matrix to a variance of 1 and mean of 0
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centers the given vector to a variance of 1 and mean of 0
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centers the given vector to a variance of 1 and mean of 0
mean | the mean of v will be saved here |
std | the standart deviation of v will be saved here |
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scales each column of the given newmat-matrix to a variance of 1
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scales column col of the given newmat-matrix m to a variance of 1
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calculates polynomial distance between two rows of newmat-matrix m
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calculates polynomial distance between row1 of BALL::Matrix<double> m1 and row2 of BALL::Matrix<double> m2.\n
m1 and m2 must therefore have the same number of columns.
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calculates the distance between row1 of BALL::Matrix<double> m1 and row2 of BALL::Matrix<double> m2 according to the given equations
f | equation f, determines how elements "x1" of row1 are charged against elements "x2" of row2. Use "x1" and "x2" in the String, e.g. "x1*x2" |
g | equation g, determines what is to be done with the calculated "sum" over all elements (use "sum" in String); e.g. "sum^0.5" => euclidean distance if f=="x1*x2" |
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calculates euclidean distance between row1 of BALL::Matrix<double> m1 and row2 of BALL::Matrix<double> m2 as \form#82\n
m1 and m2 must therefore have the same number of columns.
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Returns the euclidician difference between two ColumnVectors as
Returns the euclidic norm of a ColumnVector as
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calculate covariance between two given vectors
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calculates covariance between columns col1 and col2 of matrix m
calculate mean of given vector
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calculates mean of column col of newmat-matrix m
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calculates covarianve between two rows of the given matrix
features_to_use | if specified, only the contained features are used for calculation of the covariance |
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calculates mean of a row of the given matrix
features_to_use | if specified, only the contained features are used for calculation of the mean |
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calculates standard deviation of a row of the given matrix
features_to_use | if specified, only the contained features are used for calculation of the standard deviation |
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calculates variance of a row of the given matrix
features_to_use | if specified, only the contained features are used for calculation of the variance |
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calculate standart deviation of a given vector
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calculated standard deviation of column col of matrix m
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calculate variance of a given vector
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calculates variance of column col of newmat-matrix m
returns the scalar product
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scales the given vector to a variance of 1
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scales each column of the given vector-based matrix to a variance of 1
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calculates the sum-of-square of column col of newmat-matrix m