python system of nonlinear equations
import scipy.optimize as opt
from numpy import exp
def f(variables) :
(x,y) = variables
first_eq = x + y**2 - 4
second_eq = exp(x) + x*y - 3
return [first_eq, second_eq]
solution = opt.fsolve(f, (0.1, 1)) # fsolve(equations, X_0)
print(solution)
# [ 0.62034452 1.83838393]solving linear equation using numpy
import numpy as np
a = np.array([[6,2,-5], [3,3,-2], [7,5,-3]])
b = np.array([13,13,26])
x = np.linalg.solve(a, b)
print(x)python system of equations
import numpy as np
A = np.array([[8, 3, -2], [-4, 7, 5], [3, 4, -12]])
b = np.array([9, 15, 35])
x = np.linalg.solve(A, b)
xsolve equation python
>>> from sympy.solvers import solve
>>> from sympy import Symbol
>>> x = Symbol('x')
>>> solve(x**2 - 1, x) #Your equation here
[-1, 1]Copyright © 2021 Codeinu
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