Reputation: 7145
I want to solve a linear equation with three or more variables. Is there a good library in python to do it?
Upvotes: 50
Views: 89393
Reputation: 129755
Yes, the very-popular NumPy package has a function to do this. Their example:
Solve the system of equations
3 * x0 + x1 = 9
andx0 + 2 * x1 = 8
:>>> import numpy as np >>> a = np.array([[3,1], [1,2]]) >>> b = np.array([9,8]) >>> x = np.linalg.solve(a, b) >>> x array([ 2., 3.])
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.linalg.solve.html
Upvotes: 73
Reputation: 176760
See http://sympy.org/ and Link.
Specifically, http://docs.scipy.org/doc/numpy/reference/routines.linalg.html
And http://docs.sympy.org/0.7.0/tutorial.html#algebra, http://docs.sympy.org/dev/modules/solvers/solvers.html
Edit: Added solvers link from the comment.
Upvotes: 32
Reputation: 31
You can write a simple function which solves a system of linear equations.
def solve(equations):
#the constants of a system of linear equations are stored in a list for each equation in the system
"""
for example the system below:
2x+9y-3z+7w+8=0
7x-2y+6z-1w-10=0
-8x-3y+2z+5w+4=0
0x+2y+z+w+0=0
is expressed as the list:
[[2,9,-3,7,8],[7,-2,6,-1,-10],[-8,-3,2,5,4],[0,2,1,1,0]]
"""
lists=[] # I failed to name it meaningfully
for eq in range(len(equations)):
#print "equations 1", equations
#find an equation whose first element is not zero and call it index
index=0
for i in range(len(equations)):
if equations[i][0]<>0:
index=i;
break;
#print "index "+str(eq)+": ",index
#for the equation[index] calc the lists next itam as follows
lists.append([-1.0*i/equations[index][0] for i in equations[index][1:]])
#print "list"+str(eq)+": ", lists[-1]
#remve equation[index] and modify the others
equations.pop(index)
for i in equations:
for j in range(len(lists[-1])):
i[j+1]+=i[0]*lists[-1][j]
i.pop(0)
lists.reverse()
answers=[lists[0][0]]
for i in range(1,len(lists)):
tmpans=lists[i][-1]
for j in range(len(lists[i])-1):
tmpans+=lists[i][j]*answers[-1-j]
answers.append(tmpans)
answers.reverse()
return answers
Upvotes: 3
Reputation: 11
You can also add constrains (upper bound and lower bound) on x with lsq_linear: scipy.optimize.lsq_linear
Upvotes: 0
Reputation: 565
Using @Jeremy's example:
from sympy import *
x0, x1 = symbols(['x0', 'x1'])
sol = solve([3 * x0 + x1 - 9, x0 + 2 * x1 - 8], [x0, x1])
print(sol)
output:
{x0: 2, x1: 3}
Using @004 example with slightly different notation:
from sympy import *
x, y = symbols(['x', 'y'])
system = [
Eq(3*x + 4*y, 7),
Eq(5*x + 6*y, 8)
]
soln = solve(system, [x, y])
print(soln)
{x: -5, y: 11/2}
Note: Sometimes one may see the following notation for symbols: x, y = symbols('x, y')
, which seems to be less pythonic.
Upvotes: 8
Reputation: 89
You can use least square method in python to solve system of equations for example for solving equations 3x+4y=7 and 5x+6y=8
>>> import numpy
>>> a=[[3,4],[5,6]]
>>> b=[7,8]
>>> numpy.linalg.lstsq(a,b)
(array([-5. , 5.5]), array([], dtype=float64), 2, array([ 9.27110906, 0.21572392]))
Upvotes: 9