How to Solve a System of Equations in Python?

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The solution of a system of equations in Python depends on the type of equations you are dealing with.

If you have a system of linear equations, you can use the numpy library to solve it as shown in the previous answer.

If you have a system of nonlinear equations, you can use the scipy.optimize module. Here’s an example of how to solve a system of nonlinear equations in Python:

import numpy as np
from scipy.optimize import root

# Define the system of equations
def system(x):
    y = np.zeros(2)
    y[0] = x[0]**2 + x[1]**2 - 1
    y[1] = x[0] - x[1]**3 - 1
    return y

# Define the initial guess
x0 = np.array([0.5, 0.5])

# Solve the system of equations
sol = root(system, x0)

# Print the solution
print(sol.x)

In this example, we first import the numpy and scipy.optimize modules using import numpy as np and from scipy.optimize import root.

We define the system of equations using a function called system. This function takes in a vector x containing the variables x and y, and returns a vector y containing the values of the equations.

We define an initial guess for the variables using x0 = np.array([0.5, 0.5]).

We solve the system of equations using sol = root(system, x0). This function takes in the system of equations and the initial guess, and returns a solution as an object. We access the solution vector using sol.x.

Finally, we print the solution using print(sol.x).

Note: You’ll need to modify the code to define your own system of equations and initial guess.

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