API

Description

Classes

COO(coords[, data, shape, has_duplicates, …]) A sparse multidimensional array.
DOK(shape[, data, dtype]) A class for building sparse multidimensional arrays.
SparseArray(shape) An abstract base class for all the sparse array classes.

Functions

concatenate(arrays[, axis]) Concatenate the input arrays along the given dimension.
dot(a, b) Perform the equivalent of numpy.dot on two arrays.
elemwise(func, *args, **kwargs) Apply a function to any number of arguments.
nanmax(x[, axis, keepdims, dtype, out]) Maximize along the given axes, skipping NaN values.
nanmin(x[, axis, keepdims, dtype, out]) Minimize along the given axes, skipping NaN values.
nanprod(x[, axis, keepdims, dtype, out]) Performs a product operation along the given axes, skipping NaN values.
nansum(x[, axis, keepdims, dtype, out]) Performs a NaN skipping sum operation along the given axes.
random(shape[, density, canonical_order, …]) Generate a random sparse multidimensional array
stack(arrays[, axis]) Stack the input arrays along the given dimension.
tensordot(a, b[, axes]) Perform the equivalent of numpy.tensordot.
tril(x[, k]) Returns an array with all elements above the k-th diagonal set to zero.
triu(x[, k]) Returns an array with all elements below the k-th diagonal set to zero.
where(condition[, x, y]) Select values from either x or y depending on condition.