Mutating NumPy array inplace with cp.Expression should have a clear error message

[PTNobel]

Currently, when calling a NumPy function on a CVXPY variable such as np.log(cp.Variable()), we raise an error telling people to use a CVXPY atom inside. This error incorrectly triggers on the following code:

import numpy as np
import cvxpy as cp

x = np.array([0])
x += cp.Variable()

This errors because of this line, since NumPy sets kwargs = {'out': x}.

Expected behavior

It isn't clear to me what we want to do here. On the one hand people might expect this to mutate x the way it would for a non-NumPy array. It may not possible to both keep the error and make this have the same behaviour as x = x + cp.Variable().

We could add a new error message that says to do x = x + expression in this case, I think this is probably better than trying to get this to work because of my concerns about people expecting mutation. It is possible to write a function that works when given a NumPy array but which depends on mutation that doesn't have the same behaviour when given a CVXPY expression and I think we want to make this an error.

Version

• OS: Linux
• CVXPY Version: 1.4.1

[rileyjmurray]

I think the most we'd want to do is raise an error saying x = x + expression. The idea of an in-place assignment on a numerical array with changing data types doesn't even make sense. Consider the following code as a non-cvxpy example:

>>> import numpy as np
>>> a = np.array([0],'d')
>>> a
array([0.])
>>> a += 1j
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
numpy.core._exceptions._UFuncOutputCastingError: Cannot cast ufunc 'add' output from dtype('complex128') to dtype('float64') with casting rule 'same_kind'

I suggest we look into adding an informative error message to help users who try to do this. Until we get around to that, I suggest we change the title of this GitHub issue.

Oh, and one more thing, @PTNobel. I believe you're either using cvxpy 1.4.1 or you're using the version on master (1.5.0+commit identifier).