Fix comparison with NumPy of slicing with negative step - #1319
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nilgoyette merged 1 commit intoAug 6, 2023
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The existing documentation states that the behavior of slicing is the same as in NumPy except when `step < -1`, implying that the behavior is the same when `step = -1`. But this is not true: In [1]: import numpy as np In [2]: x = np.arange(10) In [3]: x[2 : 5 : -1] # Analogous slice in `ndarray`: `array![4, 3, 2]` Out[3]: array([], dtype=int32) In [4]: x[5 : 2 : -1] # Analogous slice in `ndarray`: `array![]` Out[4]: array([5, 4, 3]) So `step < -1` should be replaced by `step < 0` in the documentation. There are some further differences in slicing behavior with negative step, having to do with the default values for `start` and `end`: In [5]: x[: 7 : -1] # Analogous slice in `ndarray`: `array![6, 5, 4, 3, 2, 1, 0]` Out[5]: array([9, 8]) In [6]: x[7 : : -1] # Analogous slice in `ndarray`: `array![9, 8, 7]` Out[6]: array([7, 6, 5, 4, 3, 2, 1, 0])
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Thank you @venkat0791 for fixing this wrong information. The CI tests are failing, but it's not related to this MR so I'll merge anyway. I don't remember using negative slicing in ndarray so I learned something :) |
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The existing documentation states that the behavior of slicing is the same as in NumPy except when step < -1, implying that the behavior is the same when step = -1. But this is not true:
In [1]: import numpy as np
In [2]: x = np.arange(10)
In [3]: x[2 : 5 : -1] # Analogous slice in ndarray: array![4, 3, 2]
Out[3]: array([], dtype=int32)
In [4]: x[5 : 2 : -1] # Analogous slice in ndarray: array![]
Out[4]: array([5, 4, 3])
So step < -1 should be replaced by step < 0 in the documentation.
There are some further differences in slicing behavior with negative step, having to do with the default values for start and end:
In [5]: x[: 7 : -1] # Analogous slice in ndarray: array![6, 5, 4, 3, 2, 1, 0]
Out[5]: array([9, 8])
In [6]: x[7 : : -1] # Analogous slice in ndarray: array![9, 8, 7]
Out[6]: array([7, 6, 5, 4, 3, 2, 1, 0])