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RF+TST: allow dtype specifiers as fileslice input #485

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Merged
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Sep 1, 2016
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RF+TST: allow dtype specifiers as fileslice input #485

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17 changes: 10 additions & 7 deletions nibabel/fileslice.py
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Original file line number Diff line number Diff line change
Expand Up @@ -719,17 +719,19 @@ def fileslice(fileobj, sliceobj, shape, dtype, offset=0, order='C',
Parameters
----------
fileobj : file-like object
binary file-like object. Implements ``read`` and ``seek``
file-like object, opened for reading in binary mode. Implements
``read`` and ``seek``.
sliceobj : object
something that can be used to slice an array as in ``arr[sliceobj]``
something that can be used to slice an array as in ``arr[sliceobj]``.
shape : sequence
shape of full array inside `fileobj`
dtype : dtype object
dtype of array inside `fileobj`
shape of full array inside `fileobj`.
dtype : dtype specifier
dtype of array inside `fileobj`, or input to ``numpy.dtype`` to specify
array dtype.
offset : int, optional
offset of array data within `fileobj`
order : {'C', 'F'}, optional
memory layout of array in `fileobj`
memory layout of array in `fileobj`.
heuristic : callable, optional
function taking slice object, axis length, stride length as arguments,
returning one of 'full', 'contiguous', None. See
Expand All @@ -743,7 +745,8 @@ def fileslice(fileobj, sliceobj, shape, dtype, offset=0, order='C',
"""
if is_fancy(sliceobj):
raise ValueError("Cannot handle fancy indexing")
itemsize = dtype.itemsize
dtype = np.dtype(dtype)
itemsize = int(dtype.itemsize)
segments, sliced_shape, post_slicers = calc_slicedefs(
sliceobj, shape, itemsize, offset, order)
n_bytes = reduce(operator.mul, sliced_shape, 1) * itemsize
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10 changes: 10 additions & 0 deletions nibabel/tests/test_fileslice.py
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Original file line number Diff line number Diff line change
Expand Up @@ -740,6 +740,16 @@ def test_fileslice():
_check_slicer(sliceobj, arr, fobj, offset, order)


def test_fileslice_dtype():
# Test that any valid dtype specifier works for fileslice
sliceobj = (slice(None), slice(2))
for dt in (np.dtype('int32'), np.int32, 'i4', 'int32', '>i4', '<i4'):
arr = np.arange(24, dtype=dt).reshape((2, 3, 4))
fobj = BytesIO(arr.tostring())
new_slice = fileslice(fobj, sliceobj, arr.shape, dt)
assert_array_equal(arr[sliceobj], new_slice)


def test_fileslice_errors():
# Test fileslice causes error on fancy indexing
arr = np.arange(24).reshape((2, 3, 4))
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