scipy.optimize.newton typing

[wilgri]

Hello,

I'm using scipy-stubs and I'm new to optype. The following call of newton is flagged by basedpyright in strict mode:

def func(x: ArrayND[np.float64]) -> ArrayND[np.float64]:
    return -2 * x + 1

newton(func, x0=np.zeros((2, 4), dtype=float))

I gives

Type "(x: ArrayND[float64, AnyShape]) -> ArrayND[float64, AnyShape]" is not assignable to type "_Fun1D[ToFloat]"
   Function return type "ArrayND[float64, AnyShape]" is incompatible with type "ToFloat"

Looking at newton's doc and in practice, func accepts ndarray of floats. What am I doing wrong ?

Looking at scipy.optimize.newton typing, I see that func can be a generic callable _Fun1D with a type variable named _ToFloatT . I'm not sure to understand it entirely but it seems that basedpyright does not find an appropriate overload and defaults _ToFloatT to ToFloat which is incompatible with ArrayND[np.float64]. Is my understanding correct ? In addition I don't understand why arguments are onp.Array1D[np.float64] instead of ArrayND ? I feel like I'm missing something.

How would you type this basic example ?

[jorenham]

Hmm, the stubs seem to require that func callable returns a scalar. But as you show here, func returns an array, which is supported at runtime.

So this isn't your fault; the stubs are incorrect here. Thanks for reporting!

[jorenham]

I have opened an issue for this: #1518

I'll take care of it once I find some time to do so. Of course, you're also welcome to work on it if you want.

[wilgri]

Thank you :) I'll try to take a look