CODEWITHSUNDEEP
pythonparametersfsolve
Ostrich
Ostrich

Reputation: 39

Guessing parameter values using fsolve to find solution values

I have a system of 3 equations - 3 unknowns that I can solve if I know the values of the parameters (z,a). The issue is that I don't know them. Is it possible to write a code that given a guess for (z,a) finds (x,y,w) such that the system of equations is satisfied, while updating the guess for (z,a) - below I am fixing numbers for (z,a) but would like to confirm that. Also I need to make sure that x,y,w are between zero and one.

A sample of the code I am working on is below. Thanks for your help.

import scipy.optimize as so
import numpy as np

def test(variables,z,a): #Define function of variables and adjustable arg
    
    x,y,w = variables     #Declare variables
    
    eq1 = x**a+y**2-1-z*10 #Equation to solve #1
    eq2 = 2*x+1-w/a         #Equation to solve #2
    eq3 = x+y+w-1
    
    return [eq1,eq2,eq3]    #Return equation array

z,a = 1,1                                       #Ajustable parameter
initial = [0.1,0.2,0.5]                         #Initial condition list                          
sol = so.fsolve(test , initial, args = (z,a))   #Call fsolve
print(np.array(sol))                            #Display sol

Upvotes: 0

Views: 145

Answers (1)

rochard4u
rochard4u

Reputation: 736

You can create a list of guesses: guesses=[(1,1),(1,0),(0,1)] for instance, and iterate through that list using a for loop.

initial = [0.1,0.2,0.5]                             #Initial condition list  
guesses=[(1,1),(1,0),(0,1)]
for (z, a) in guesses:
    sol = so.fsolve(test , initial, args = (z,a))   #Call fsolve
    print(np.array(sol))                            #Display sol

As for the bounds for x,y and w, I believe that it is not possible to add bounds with scipy.optimize.fsolve. You can check scipy.optimize.minimize instead.

Upvotes: 1

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