docarray.math.ndarray module#

docarray.math.ndarray.unravel(docs, field)[source]#

Return type:: Optional[ArrayType]

docarray.math.ndarray.ravel(value, docs, field)[source]#

Ravel value into doc.field of each documents

Parameters:

docs (DocumentArray) – the docs to set
field (str) – the field of the doc to set
value (ArrayType) – the value to be set on doc.field

Return type:

None

docarray.math.ndarray.get_array_type(array, raise_error_if_not_array=True)[source]#

Get the type of ndarray without importing the framework

Parameters:: array (ArrayType) – any array, scipy, numpy, tf, torch, etc.
Return type:: Tuple[str, bool]
Returns:: a tuple where the first element represents the framework, the second represents if it is sparse array

docarray.math.ndarray.to_numpy_array(value)[source]#

Return the value always in numpy.ndarray regardless the framework type.

Return type:: ndarray
Returns:: the value in numpy.ndarray.

docarray.math.ndarray.to_list(value)[source]#

Return type:: List[float]

docarray.math.ndarray.get_array_rows(array)[source]#

Get the number of rows of the ndarray without importing all frameworks

Parameters:: array (ArrayType) – input array
Return type:: Tuple[int, int]
Returns:: (num_rows, ndim)

Examples

>>> get_array_rows([1,2,3])
1, 1
>>> get_array_rows([[1,2,3], [4,5,6]])
2, 2
>>> get_array_rows([[1,2,3], [4,5,6], [7,8,9]])
3, 2
>>> get_array_rows(np.array([[1,2,3], [4,5,6], [7,8,9]]))
3, 2

docarray.math.ndarray.check_arraylike_equality(x, y)[source]#

Check if two array type objects are the same with the supported frameworks.

Examples

>>> import numpy as np
    x = np.array([[1,2,0,0,3],[1,2,0,0,3]])
    check_arraylike_equality(x,x)
True

>>> from scipy import sparse as sp
    x = sp.csr_matrix([[1,2,0,0,3],[1,2,0,0,3]])
    check_arraylike_equality(x,x)
True

>>> import torch
    x = torch.tensor([1,2,3])
    check_arraylike_equality(x,x)
True

docarray.math.ndarray.detach_tensor_if_present(x)[source]#: Check if input is a dense torch array and detaches the tensor from the current graph. :param array: input array :rtype: Any :return: (num_rows, ndim)