Transforms chromagram to Tonnetz (Harte, Sandler, 2006).

Computes the PCP.

Computes the self similarity matrix that is key invariant from chromagram X.

Computes the score for a given segment. The score is computed by taking a look at the trace of the block of the ssm.

Compute a Self Similarity Matrix, normalized from 0 to 1.

Obtains a chromagram representation from a csv score.

Finds the segment inside the self similarity matrix X.

Returns the number of staves for the csv formatted score.

Checks whether the block of the ssm defined with start_i, start_j contains "squared" information or not.

L2 weight regularization :param weight: weight to regularize :return: loss

Lee sparsity and selectivity regularization on hidden activations :param act: hidden unit activations :return: loss

Applies a mean filter of size L to the matrix of row observations X.

Transformation of an observation vector in the M principal components Parameters ---------- x_vector: array _like

Plots a Chromagram example, as it appears on the ISMIR paper. Parameters ---------- C : np.array((N,12)) Chromagram.

Save a colormap of values titled with title in file filename.

Save a plot of a function (curve).

Plots input data :param data: a data batch to plot :param epoch: epoch nr :param out_dir: directory where to save the plot

Plots some histograms :param model: a C-GAE instance :param batch: the batch to use for computing histograms :param epoch: epoch nr

Plots the input weights of the C-GAE :param model: a C-GAE instance :param epoch: epoch nr (int) :param out_dir: directory where to

Plots the top most mapping layer given an input batch :param model: a C-GAE instance :param batch: the batch to reconstruct :param e

Plots matrix X.

Plots the reconstruction of an input batch :param model: a C-GAE instance :param batch: the batch to reconstruct :param epoch: epoch

Plots some examples of the score, as they appear on the ISMIR paper. Parameters ---------- X : np.array((N,N)) Self-similarity ma

Plots the segments on top of half of the self similarity matrix X.

Plots a self-similarity matrix, as it appears on the ISMIR paper. Parameters ---------- X : np.array((N,N)) Self-similarity matri

Prints the patterns and the occurrences included in pattterns. Parameters ---------- patterns : list Patterns list with all of it

Reads the cPickle file and returns its contents. @param file string: Path to the cPickle file. @return x Object: cPickle contents.

Reads a csv into a numpy array.

Saves the results into the output file, following the MIREX format.

Saves the raw results into the output file

Sonifies the patterns.

Splits the patterns in case they are included one inside the other.

Transposes axis 1 (zero-based) of x by [shift] steps. Missing information is padded with zeros. :param x: the array to transp

Write data into a cPickle file. @param file string: Path to the new cPickle file. @param data object: Data to be stored.

Write configuration (dict) into .ini file