In PR 12609 https://github.com/numpy/numpy/pull/12609 I added code to
emit a DepricationWarning when broadcast_arrays returns an array where
the output is repeated. While this is a minimal fix to the problem,
perhaps we should consider making the output readonly immediately instead?
- A depre
Hi!
Broadcasting almost always returns a repeated output
(except when all arrays are the same shape), that’s the entire point. I suspect
this function is in fairly widespread use and will therefore cause a lot of
downstream issues when repeating, so I’m -0.5 on a DeprecationWarning. A
FutureWar
Probably this will cause a lot of groans, but I've definitely written code
modifying `broadcast_to` outputs, intentionally. As such I am -1 on this whole
endeavour. My preference on making arrays read-only is to have a very light
touch if any. As an example, at some point `np.diag` started retur
Hi Juan,
I also use `broadcast_to` a lot, to save memory, but definitely have been
in a situation where in another piece of code the array is assumed to be
normal and writable (typically, that other piece was also written by me; so
much for awareness...). Fortunately, `broadcast_to` already return
hello,
sorry newbe to numpy.
I want to define a three-dim array.
I know this works:
>>> np.array([[[1,2],[3,4]],[[5,6],[7,8]]])
array([[[1, 2],
[3, 4]],
[[5, 6],
[7, 8]]])
But can you tell why this doesnt work?
>>> np.array([[1,2],[[1,2],[3,4]]])
Traceback (most recent
I believe numpy arrays must be rectangular, yours is jagged, instead try
>>> x3d = np.array([[[1, 2], [1, 2], [3, 4]]])
>>> x3d.shape
(1, 3, 2)
Note: 3 opening brackets, yours has 2
And single brackets around the 3 innermost arrays, yours has single
brackets for the 1st, and double brackets aroun
In the latest version of numpy, this runs without an error, although may or
may not be what you want:
In [1]: np.array([[1,2],[[1,2],[3,4]]])
Out[1]:
array([[1, 2],
[list([1, 2]), list([3, 4])]], dtype=object)
Here the result is a 2x2 array, where some elements are numbers and others
are l
