tensor_space

odl.space.space_utils.tensor_space(shape, dtype=None, impl='numpy', \*\*kwargs)[source]

Return a tensor space with arbitrary scalar data type.

Parameters
shapepositive int or sequence of positive ints

Number of entries per axis for elements in this space. A single integer results in a space with 1 axis.

dtypeoptional

Data type of each element. Can be provided in any way the numpy.dtype function understands, e.g. as built-in type or as a string. For None, the TensorSpace.default_dtype of the created space is used.

implstr, optional

Impmlementation back-end for the space. See tensor_space_impl_names for available options.

kwargs :

Extra keyword arguments passed to the space constructor.

Returns
spaceTensorSpace

See also

rn, cn

Constructors for real and complex spaces

Examples

Space of 3-tuples with uint64 entries (although not strictly a vector space):

>>> odl.tensor_space(3, dtype='uint64')
tensor_space(3, dtype='uint64')

2x3 tensors with same data type:

>>> odl.tensor_space((2, 3), dtype='uint64')
tensor_space((2, 3), dtype='uint64')

The default data type depends on the implementation. For impl='numpy', it is 'float64':

>>> ts = odl.tensor_space((2, 3))
>>> ts
rn((2, 3))
>>> ts.dtype
dtype('float64')