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_matutils – Cython matutils

_matutils – Cython matutils

gensim._matutils.digamma

Digamma function for positive floats, using _digamma().

Parameters:x (float) – Positive value.
Returns:Digamma(x).
Return type:float
gensim._matutils.dirichlet_expectation(alpha)

Expected value of log(theta) where theta is drawn from a Dirichlet distribution. Using dirichlet_expectation_1d() or dirichlet_expectation_2d().

Parameters:alpha (numpy.ndarray) – Dirichlet parameter 2d matrix or 1d vector, if 2d - each row is treated as a separate parameter vector, supports float16, float32 and float64.
Returns:Log of expected values, dimension same as alpha.ndim.
Return type:numpy.ndarray
gensim._matutils.dirichlet_expectation_1d(alpha)

Expected value of log(theta) where theta is drawn from a Dirichlet distribution. Using _dirichlet_expectation_1d().

Parameters:alpha (numpy.ndarray) – Dirichlet parameter 1d vector, supports float16, float32 and float64.
Returns:Log of expected values, 1d vector.
Return type:numpy.ndarray
gensim._matutils.dirichlet_expectation_2d(alpha)

Expected value of log(theta) where theta is drawn from a Dirichlet distribution. Using _dirichlet_expectation_2d().

Parameters:alpha (numpy.ndarray) – Dirichlet parameter 2d matrix, each row is treated as a separate parameter vector, supports float16, float32 and float64.
Returns:Log of expected values, 2d matrix.
Return type:numpy.ndarray
gensim._matutils.logsumexp(x)

Log of sum of exponentials, using _logsumexp_2d().

Parameters:x (numpy.ndarray) – Input 2d matrix, supports float16, float32 and float64.
Returns:log of sum of exponentials of elements in x.
Return type:float

Warning

By performance reasons, doesn’t support NaNs or 1d, 3d, etc arrays like scipy.special.logsumexp().

gensim._matutils.mean_absolute_difference(a, b)

Mean absolute difference between two arrays, using _mean_absolute_difference().

Parameters:
  • a (numpy.ndarray) – Input 1d array, supports float16, float32 and float64.
  • b (numpy.ndarray) – Input 1d array, supports float16, float32 and float64.
Returns:

mean(abs(a - b)).

Return type:

float