I have problem implementing residuals function for leastsq optimization of scipy when importing it from another file - scipy

Question

I have written a code in which functions are called in each other. The working code is as follows:
import numpy as np
from scipy.optimize import leastsq
import RF
func = RF.roots
# residuals = RF.residuals
def residuals(params, x, y):
return y - func(params, x)
def estimation(x, y):
p_guess = [1, 2, 0.5, 0]
params, cov, infodict, mesg, ier = leastsq(residuals, p_guess, args=(x, y), full_output=True)
return params
x = np.array([2.78e-03, 3.09e-03, 3.25e-03, 3.38e-03, 3.74e-03, 4.42e-03, 4.45e-03, 4.75e-03, 8.05e-03, 1.03e-02, 1.30e-02])
y = np.array([2.16e+02, 2.50e+02, 3.60e+02, 4.48e+02, 5.60e+02, 8.64e+02, 9.00e+02, 1.00e+03, 2.00e+03, 3.00e+03, 4.00e+03])
FIT_params = estimation(x, y)
print(FIT_params)
where RF file is:
def roots(params, x):
a, b, c, d = params
y = a * (b * x) ** c + d
return y
def residuals(params, x, y):
return y - func(params, x)
I would like to remove residuals function from the main code and use it by calling from RF file instead i.e. by activating the code line residuals = RF.residuals. By doing so, error NameError: name 'func' is not defined will be appeared. I put func argument in RF's residuals function as def residuals(func, params, x, y): which will face to error TypeError: residuals() missing 1 required positional argument: 'y'; It seems the error is related to the forth argument of the residuals function in this sample because it will get error for 'func' if the func argument be placed after the y argument. I couldn't find out the source of the issue, but I guess it must be related to limitation of arguments in functions. I would be appreciated if anyone could guide me to understand the error and its solution.
Is it possible to bring residual function from the main code to the RF file? How?

Answer 1

The problem is that there's no global variable func in your file RF.py, hence it can't be found. A simple solution would be to add an additional parameter to your residuals function:
# RF.py
def roots(params, x):
a, b, c, d = params
y = a * (b * x) ** c + d
return y
def residuals(params, func, x, y):
return y - func(params, x)
Then, you can use it inside your other file like this:
import numpy as np
from scipy.optimize import leastsq
from RF import residuals, roots as func
def estimation(func, x, y):
p_guess = [1, 2, 0.5, 0]
params, cov, infodict, mesg, ier = leastsq(residuals, p_guess, args=(func, x, y), full_output=True)
return params
x = np.array([2.78e-03, 3.09e-03, 3.25e-03, 3.38e-03, 3.74e-03, 4.42e-03, 4.45e-03, 4.75e-03, 8.05e-03, 1.03e-02, 1.30e-02])
y = np.array([2.16e+02, 2.50e+02, 3.60e+02, 4.48e+02, 5.60e+02, 8.64e+02, 9.00e+02, 1.00e+03, 2.00e+03, 3.00e+03, 4.00e+03])
FIT_params = estimation(func, x, y)
print(FIT_params)