self variable of class as an argument of a class method (python)

Question

here's my problem:

given any two functions, eg. f(x,a) and g(x,b), I want to build a new function, say F(f,g), which returns the product of the f and g. So:

F(f,g) = f*g = f(x, a) * g(x, b) = F(x, a, b)

I want to do this hardcoding the least possible. So, for h(x, c, d), I would get F(f,h) = F(x, a, c, d). Given that then I want to minimize F, I thought of building a class. Here's a MWE:

import numpy as np
from inspect import getargspec

def f(x, a):
    return np.tanh(x*a)

def g(x, b):
    return np.power(x,b)

def h(x, c, d):
    return x*c+np.log(x)

class fit_func(object):
    def __init__(self, data, *args):
        self.data = data
        self.func_a = args[0]
        self.func_b = args[1]
        self.args_a = getargspec(args[0])[0][1:]
        self.args_b = getargspec(args[1])[0][1:]

at this point, I thought of including the following __call__ method:

    def __call__(self, *self.args_a, *self.args_b):
        return self.func_a(self.data,self.args_a)*self.func_b(data,self.args_b)

I thought: this way an instance of the class, say F = fit_func(some_data_array,f,g), would be callable as F(a,b). However, python doesn't like the self.args_a and self.args_b among the arguments of __call__ and I understand why. Does anybody know a clever way to obtain this? Thank you very much in advance

I believe that you have meant f(x, a) * g(x, b) = F(x, a, b) — Mike
– Mike, Commented Nov 22, 2016 at 12:49
absolutely Mike and I've also corrected one thing: the unpacking * in front of self.args_a and b in the argument of the __call__ method — andrea
– andrea, Commented Nov 22, 2016 at 12:55

Kasravnd · Accepted Answer · 2016-11-22 13:26:30Z

If you just accept positional arguments you better to save the length of arguments for each functions, and then pas proper slices of args to each function in call method:

import numpy as np
from inspect import getargspec

class fit_func(object):
    def __init__(self, *args):
        self.func_a = args[0]
        self.func_b = args[1]
        self.size_arg_a = len(getargspec(self.func_a)[0])
        self.size_arg_b = len(getargspec(self.func_b)[0])
    def __call__(self, *args):
        return self.func_a(*args[:self.size_arg_a]) * self.func_b(*args[self.size_arg_b-1:])

Demo:

def f(x, a):
    return np.tanh(x*a)

def h(x, c, d):
    return x*c+np.log(x)

F = fit_func(f, h)
print(F(3, 4, 3, 5, 7))
16.0986122875

If you want to pass keyword arguments to final function:

import numpy as np
from inspect import getargspec
from operator import itemgetter


class fit_func(object):
    def __init__(self, *args):
        self.func_a = args[0]
        self.func_b = args[1]
        self.arg_a = getargspec(self.func_a)[0]
        self.arg_b = getargspec(self.func_b)[0]

    def __call__(self, **kwargs):
        arg_a = itemgetter(*self.arg_a)(kwargs)
        arg_b = itemgetter(*self.arg_b)(kwargs)
        return self.func_a(*arg_a) * self.func_b(*arg_b)

Demo:

def f(x, a):
    return np.tanh(x*a)

def h(x, c, d):
    return x*c+np.log(x)

F = fit_func(f, h)
print(F(x=3, a=4, c=5, d=7))
16.0986122875

what if I don't want positional arguments but instead to call the __call__ method with kwdargs corresponding to the definition of the functions f, g and h? so F(f,h) = F(a=...,c=...,d=...)
this is almost it. in your updated version, the user needs to know what the arguments names of f and h are. in other terms: is there a way to obtain from F(f,h) that getargspec(F)[0] = ['x', 'a' , 'c', 'd'] ?
I need a new function with a signature given by the extra parameters of the functions provided in the instantiation of F (eg. a,b) to be passed to iminuit. I cannot define it as def New_func(F.arg_a, F.arg_b): ..... I think the answer could be in [stackoverflow.com/q/1409295/4349869] but I'm not sure

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