reskit.norms

Functions of norms.

reskit.normalizations.binar_norm(X)

Binary matrix normalization.

Transforms a matrix to binarized one.

Parameters:

X : numpy matrix

Matrix you want to binarize.

Returns:

normed_X : numpy matrix

Binarized matrix.

reskit.normalizations.max_norm(X)

Maximum matrix normalization.

Transforms a matrix to normalized by the maximum matrix value.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.mean_norm(X)

Mean matrix normalization.

Transforms a matrix to normalized by the mean matrix value.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.spectral_norm(X)

Spectral matrix normalization.

Transforms a matrix to normalized by the geometric mean of adjacent degrees.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.rwalk_norm(X)

Random walk matrix normalization.

Transforms a matrix to normalized by degree of a destination node.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.double_norm(function, X1, X2)

Double normalization.

Applies normalization function to two matrices.

Parameters:

function : function

X1 : 1-st function input

X2 : 2-nd function input

Returns:

normed_X1, normed_X2 : 1-st function output, 2-nd function output

reskit.normalizations.sqrtw(X)

Square root matrix normalization.

Transforms each matrix value to square root of this value.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.invdist(X, dist)

Inverse distance matrix normalization.

Inverces each matrix number.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.rootwbydist(X, dist)

Root weight by distance matrix normalization.

Transforms each matrix value to square root of this value normalized by some defined weight.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.

reskit.normalizations.wbysqdist(X, dist)

Weights by squared distance matrix normalization.

Transforms a matrix to normalized by square root of some defined weight.

Parameters:

X : numpy matrix

Matrix you want to normalize.

Returns:

normed_X : numpy matrix

Normalized matrix.