NumpyTensor.__getitem__

NumpyTensor.__getitem__(indices)

Return self[indices].

Parameters:

indicesindex expression

Integer, slice or sequence of these, defining the positions of the data array which should be accessed.

Returns:

valuesNumpyTensorSpace.dtype or NumpyTensor

The value(s) at the given indices. Note that the returned object is a writable view into the original tensor, except for the case when indices is a list.

Examples

For one-dimensional spaces, indexing is as in linear arrays:

>>> space = odl.rn(3)
>>> x = space.element([1, 2, 3])
>>> x[0]
1.0
>>> x[1:]
rn(2).element([ 2.,  3.])

In higher dimensions, the i-th index expression accesses the i-th axis:

>>> space = odl.rn((2, 3))
>>> x = space.element([[1, 2, 3],
...                    [4, 5, 6]])
>>> x[0, 1]
2.0
>>> x[:, 1:]
rn((2, 2)).element(
    [[ 2.,  3.],
     [ 5.,  6.]]
)

Slices can be assigned to, except if lists are used for indexing:

>>> y = x[:, ::2]  # view into x
>>> y[:] = -9
>>> x
rn((2, 3)).element(
    [[-9.,  2., -9.],
     [-9.,  5., -9.]]
)
>>> y = x[[0, 1], [1, 2]]  # not a view, won't modify x
>>> y
rn(2).element([ 2., -9.])
>>> y[:] = 0
>>> x
rn((2, 3)).element(
    [[-9.,  2., -9.],
     [-9.,  5., -9.]]
)