irfpy.util.ndsparse

Multidimensional sparse array.

Interface could be very similar to scipy:scipy.sparse.dok_matrix. However, this class is developed “on demand”, so that the implementation is not fully completed.

Code author: Yoshifumi Futaana

class irfpy.util.ndsparse.ndsparse_container(arg1)

Bases: object

N-dimensional sparse array.

This class provide a container part.

Construct multi-dimensional sparse array.

1. From a dense array:

>>> mat = ndsparse([[0, 0, 0, 0, 2], [0, 3, 0, 0, 1], [0, 1, -1, 0, 0]])

will create (3, 5) shaped array.

>>> print(mat.shape)
(3, 5)

2. From a sparse array

>>> mat2 = ndsparse(mat)
>>> print(mat2.shape)
(3, 5)

3. By specifying the shape, if arg1 is a tuple.

>>> mat3 = ndsparse((5, 3, 2))
>>> print(mat3.shape)
(5, 3, 2)

todense()

Convert to dense matrix.

>>> mat = ndsparse_container([[0, 0, 0, 0, 2], [0, 3, 0, 0, 1], [0, 1, -1, 0, 0]])
>>> print(mat.todense())
[[ 0.  0.  0.  0.  2.]
 [ 0.  3.  0.  0.  1.]
 [ 0.  1. -1.  0.  0.]]

class irfpy.util.ndsparse.ndsparse(arg1, **argv)

Bases: object

N-dimensional sparse array.

Create a sparse array container.

See ndsparse_container.

todense()

sum(axis=None)

irfpy.util.ndsparse.doctests()