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
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
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
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
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
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
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
