API reference

DataGeometry class

hypertools.DataGeometry([fig, ax, line_ani, ...])

Hypertools data object class

Load

hypertools.load(dataset[, reduce, ndims, ...])

Load a .geo file or example data

Analyze

hypertools.analyze(data[, normalize, ...])

Wrapper function for normalize -> reduce -> align transformations.

Plot

hypertools.plot(x[, fmt, marker, markers, ...])

Plots dimensionality reduced data and parses plot arguments

Normalize

hypertools.normalize(x[, normalize, ...])

Z-transform the columns or rows of an array, or list of arrays

Reduce

hypertools.reduce(x[, reduce, ndims, ...])

Reduces dimensionality of an array, or list of arrays

Align

hypertools.align(data[, align, normalize, ...])

Aligns a list of arrays

Cluster

hypertools.cluster(x[, cluster, n_clusters, ...])

Performs clustering analysis and returns a list of cluster labels

Describe

hypertools.describe(x[, reduce, max_dims, ...])

Create plot describing covariance with as a function of number of dimensions

Tools

hypertools.tools.format_data(x[, ...])

Formats data into a list of numpy arrays

hypertools.tools.procrustes(source, target)

Function to project from one space to another using Procrustean transformation (shift + scaling + rotation + reflection).

hypertools.tools.missing_inds(x[, format_data])

Returns indices of missing data

hypertools.tools.df2mat(data[, return_labels])

Transforms a Pandas DataFrame into a Numpy array with binarized text columns