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These test use code to mimic the C-Code indexing for selection.
NOTE: * This still lacks tests for complex item setting.
* If you change behavior of indexing, you might want to modify
these tests to try more combinations.
* Behavior was written to match numpy version 1.8. (though a
first version matched 1.7.)
* Only tuple indices are supported by the mimicking code.
(and tested as of writing this)
* Error types should match most of the time as long as there
is only one error. For multiple errors, what gets raised
will usually not be the same one. They are *not* tested.
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Parameters
----------
arr : ndarray
Array to be indexed.
indices : tuple of index objects
Returns
-------
out : ndarray
An array equivalent to the indexing operation (but always a copy).
`arr[indices]` should be identical.
no_copy : bool
Whether the indexing operation requires a copy. If this is `True`,
`np.may_share_memory(arr, arr[indicies])` should be `True` (with
some exceptions for scalars and possibly 0-d arrays).
Notes
-----
While the function may mostly match the errors of normal indexing this
is generally not the case.
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index : tuple of indexing objects
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index : indexing object
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