modAL.density¶
Measures for estimating the information density of a given sample.

modAL.density.
information_density
(X: Union[list, numpy.ndarray, scipy.sparse.csr.csr_matrix], metric: Union[str, Callable] = 'euclidean') → numpy.ndarray[source]¶ Calculates the information density metric of the given data using the given metric.
Parameters:  X – The data for which the information density is to be calculated.
 metric – The metric to be used. Should take two 1d numpy.ndarrays for argument.
Returns: The information density for each sample.

modAL.density.
similarize_distance
(distance_measure: Callable) → Callable[source]¶ Takes a distance measure and converts it into a information_density measure.
Parameters: distance_measure – The distance measure to be converted into information_density measure. Returns: The information_density measure obtained from the given distance measure.