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(*args, **kwargs) Z-transform the columns or rows of an array, or list of arrays

Reduce

hypertools.reduce(*args, **kwargs) Reduces dimensionality of an array, or list of arrays

Align

hypertools.align(*args, **kwargs) Aligns a list of arrays

Cluster

hypertools.cluster(*args, **kwargs) Performs clustering analysis and returns a list of cluster labels

Describe

hypertools.describe(x[, reduce, max_dims, show]) Create plot describing covariance with as a function of number of dimensions

Tools

hypertools.tools.describe_pca(x[, show]) Create plot describing covariance with as a function of number of dimensions
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) Returns indices of missing data
hypertools.tools.df2mat(data[, return_labels]) Transforms a Pandas DataFrame into a Numpy array with binarized text columns