cunumeric.array#

cunumeric.array(object, dtype=None, copy=True)#

Create an array.

Parameters:
  • object (array_like) – An array, any object exposing the array interface, an object whose __array__ method returns an array, or any (nested) sequence.

  • dtype (data-type, optional) – The desired data-type for the array. If not given, then the type will be determined as the minimum type required to hold the objects in the sequence.

  • copy (bool, optional) – If true (default), then the object is copied. Otherwise, a copy will only be made if __array__ returns a copy, if obj is a nested sequence, or if a copy is needed to satisfy any of the other requirements (dtype, order, etc.).

  • order ({'K', 'A', 'C', 'F'}, optional) –

    Specify the memory layout of the array. If object is not an array, the newly created array will be in C order (row major) unless ‘F’ is specified, in which case it will be in Fortran order (column major). If object is an array the following holds.

    order

    no copy

    copy=True

    ’K’

    unchanged

    F & C order preserved, otherwise most similar order

    ’A’

    unchanged

    F order if input is F and not C, otherwise C order

    ’C’

    C order

    C order

    ’F’

    F order

    F order

    When copy=False and a copy is made for other reasons, the result is the same as if copy=True, with some exceptions for ‘A’, see the Notes section. The default order is ‘K’.

  • subok (bool, optional) – If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default).

  • ndmin (int, optional) – Specifies the minimum number of dimensions that the resulting array should have. Ones will be pre-pended to the shape as needed to meet this requirement.

Returns:

out – An array object satisfying the specified requirements.

Return type:

ndarray

See also

numpy.array

Availability:

Multiple GPUs, Multiple CPUs