API¶
Description
Classes
COO (coords[, data, shape, has_duplicates, …]) |
A sparse multidimensional array. |
DOK (shape[, data, dtype, fill_value]) |
A class for building sparse multidimensional arrays. |
SparseArray (shape[, fill_value]) |
An abstract base class for all the sparse array classes. |
Functions
as_coo (x[, shape, fill_value]) |
Converts any given format to COO . |
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. |
eye (N[, M, k, dtype]) |
Return a 2-D COO array with ones on the diagonal and zeros elsewhere. |
full (shape, fill_value[, dtype]) |
Return a COO array of given shape and type, filled with fill_value. |
full_like (a, fill_value[, dtype]) |
Return a full array with the same shape and type as a given array. |
kron (a, b) |
Kronecker product of 2 sparse arrays. |
load_npz (filename) |
Load a sparse matrix in numpy’s .npz format from disk. |
matmul (a, b) |
Perform the equivalent of numpy.matmul on two arrays. |
nanmax (x[, axis, keepdims, dtype, out]) |
Maximize along the given axes, skipping NaN values. |
nanmean (x[, axis, keepdims, dtype, out]) |
Performs a NaN skipping mean operation along the given axes. |
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. |
nanreduce (x, method[, identity, axis, keepdims]) |
Performs an NaN skipping reduction on this array. |
nansum (x[, axis, keepdims, dtype, out]) |
Performs a NaN skipping sum operation along the given axes. |
ones (shape[, dtype]) |
Return a COO array of given shape and type, filled with ones. |
ones_like (a[, dtype]) |
Return a COO array of ones with the same shape and type as a . |
random (shape[, density, random_state, …]) |
Generate a random sparse multidimensional array |
roll (a, shift[, axis]) |
Shifts elements of an array along specified axis. |
save_npz (filename, matrix[, compressed]) |
Save a sparse matrix to disk in numpy’s .npz format. |
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 . |
zeros (shape[, dtype]) |
Return a COO array of given shape and type, filled with zeros. |
zeros_like (a[, dtype]) |
Return a COO array of zeros with the same shape and type as a . |