There is a long-standing request to require an explicit opt-in for
dtype=object: https://github.com/numpy/numpy/issues/5353
-- Marten
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The rationale for the change allowing that construction was twofold: it's
easier to understand what has gone wrong when seeing the `list`s in the
repr than it was from the cryptic error message; and there were some jagged
cases that already succeeded in this way, and it was less confusing to be
On 27/12/18 3:21 am, Benjamin Root wrote:
Ewww, kinda wish that would be an error... It would be too easy for a
typo to get accepted this way.
On Wed, Dec 26, 2018 at 1:59 AM Eric Wieser
mailto:wieser.eric%2bnu...@gmail.com>>
wrote:
In the latest version of numpy, this runs without an
Ewww, kinda wish that would be an error... It would be too easy for a typo
to get accepted this way.
On Wed, Dec 26, 2018 at 1:59 AM Eric Wieser
wrote:
> In the latest version of numpy, this runs without an error, although may
> or may not be what you want:
>
> In [1]:
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
