Comments (4)
@nnethery I've just fixed this bug! Please check it again.
It works great. You rock @jjjkkkjjj
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@nnethery
Thank you for reporting the bug. I misunderstood the fancy indexing rule...
Do you know why this operation returned the shape as (88,)?
I misunderstood the returned array's shape will be same as the shape combined by all input's shape. For the example you mentioned, input indexing array's shapes are (88,)=np.arange(88)
, (88,)=b[0, :, 0].astype(int)
, (0=scalar,). So, returned shape will be (88, 88, 0) = (88,88) by combining the input indexing array's shapes.
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Ah, I may understand.
The input indexing shape will be broadcasted.
>>> np.arange(8).reshape(4,2)[[2,3], [0,2,1]]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
IndexError: shape mismatch: indexing arrays could not be broadcast together with shapes (2,) (3,)
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@nnethery
I've just fixed this bug!
Please check it again.
from matft.
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