numeric exceptions in simple functions

[BishopWolf]

Numeric types shall be self contained and automatically typecasted

Reproducing code example:

import numpy as np
a = np.array([1, 1, 1, 1, 1])
a += 0.1

expected behaviour:

a is typecasted to float64 automatically before doing the add function. The following code works:

import numpy as np
a = np.array([1., 1., 1., 1., 1.])
a += 0.1

it returns array([1.1, 1.1, 1.1, 1.1, 1.1]). This shall be the returning value of the code above.

Error message:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
numpy.core._exceptions.UFuncTypeError: Cannot cast ufunc 'add' output from dtype('float64') to dtype('int64') with casting rule 'same_kind'

NumPy/Python version information:

1.19.1 3.8.5 (default, Jul 21 2020, 10:48:26)
[Clang 11.0.3 (clang-1103.0.32.62)]

[charris]

Doesn't work that way. The inplace operators in numpy reuse the same memory, so the result type must remain the same.

[BishopWolf]

this works

>>> b=1
>>> b+=0.1
>>> b
1.1

[charris]

It is also not "inplace". It is implemented as b = b + 0.1, which is completely different.