DOK

class sparse.DOK(shape, data=None, dtype=None, fill_value=None)[source]

A class for building sparse multidimensional arrays.

Parameters:

shape (tuple[int] (DOK.ndim,)) – The shape of the array.
data (dict, optional) – The key-value pairs for the data in this array.
dtype (np.dtype, optional) – The data type of this array. If left empty, it is inferred from the first element.
fill_value (scalar, optional) – The fill value of this array.

dtype

The datatype of this array. Can be None if no elements have been set yet.

Type:: numpy.dtype

shape

The shape of this array.

Type:: tuple[int]

data

The keys of this dictionary contain all the indices and the values contain the nonzero entries.

Type:: dict

See also

COO: A read-only sparse array.

Examples

You can create DOK objects from Numpy arrays.

>>> x = np.eye(5, dtype=np.uint8)
>>> x[2, 3] = 5
>>> s = DOK.from_numpy(x)
>>> s
<DOK: shape=(5, 5), dtype=uint8, nnz=6, fill_value=0>

You can also create them from just shapes, and use slicing assignment.

>>> s2 = DOK((5, 5), dtype=np.int64)
>>> s2[1:3, 1:3] = [[4, 5], [6, 7]]
>>> s2
<DOK: shape=(5, 5), dtype=int64, nnz=4, fill_value=0>

You can convert DOK arrays to COO arrays, or numpy.ndarray objects.

>>> from sparse import COO
>>> s3 = COO(s2)
>>> s3
<COO: shape=(5, 5), dtype=int64, nnz=4, fill_value=0>
>>> s2.todense()  
array([[0, 0, 0, 0, 0],
       [0, 4, 5, 0, 0],
       [0, 6, 7, 0, 0],
       [0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0]])

>>> s4 = COO.from_numpy(np.eye(4, dtype=np.uint8))
>>> s4
<COO: shape=(4, 4), dtype=uint8, nnz=4, fill_value=0>
>>> s5 = DOK.from_coo(s4)
>>> s5
<DOK: shape=(4, 4), dtype=uint8, nnz=4, fill_value=0>

You can also create DOK arrays from a shape and a dict of values. Zeros are automatically ignored.

>>> values = {
...     (1, 2, 3): 4,
...     (3, 2, 1): 0,
... }
>>> s6 = DOK((5, 5, 5), values)
>>> s6
<DOK: shape=(5, 5, 5), dtype=int64, nnz=1, fill_value=0.0>

Attributes

`DOK.density`	The ratio of nonzero to all elements in this array.
`DOK.ndim`	The number of dimensions of this array.
`DOK.nnz`	The number of nonzero elements in this array.
`DOK.size`	The number of all elements (including zeros) in this array.

Methods

`DOK.asformat`(format, **kwargs)	Convert this sparse array to a given format.
`DOK.from_coo`(x)	Get a `DOK` array from a `COO` array.
`DOK.from_numpy`(x)	Get a `DOK` array from a Numpy array.
`DOK.from_scipy_sparse`(x, /, *[, fill_value])	Create a `DOK` array from a `scipy.sparse.spmatrix`.
`DOK.to_coo`()	Convert this `DOK` array to a `COO` array.
`DOK.todense`()	Convert this `DOK` array into a Numpy array.