Question

Write a function or script that will solve linear systems of any size by Gaussian elimination with partial pivoting in Python.

Answer 1

# The 'gauss' function takes two matrices, 'a' and 'b', with 'a' square, and it return the determinant of 'a' and a matrix 'x' such that a*x = b.
# If 'b' is the identity, then 'x' is the inverse of 'a'.
 
import copy
from fractions import Fraction
 
def gauss(a, b):
    a = copy.deepcopy(a)
    b = copy.deepcopy(b)
    n = len(a)
    p = len(b[0])
    det = 1
    for i in range(n - 1):
        k = i
        for j in range(i + 1, n):
            if abs(a[j][i]) > abs(a[k][i]):
                k = j
        if k != i:
            a[i], a[k] = a[k], a[i]
            b[i], b[k] = b[k], b[i]
            det = -det
 
        for j in range(i + 1, n):
            t = a[j][i]/a[i][i]
            for k in range(i + 1, n):
                a[j][k] -= t*a[i][k]
            for k in range(p):
                b[j][k] -= t*b[i][k]
 
    for i in range(n - 1, -1, -1):
        for j in range(i + 1, n):
            t = a[i][j]
            for k in range(p):
                b[i][k] -= t*b[j][k]
        t = 1/a[i][i]
        det *= a[i][i]
        for j in range(p):
            b[i][j] *= t
    return det, b
 
def zeromat(p, q):
    return [[0]*q for i in range(p)]
 
def matmul(a, b):
    n, p = len(a), len(a[0])
    p1, q = len(b), len(b[0])
    if p != p1:
        raise ValueError("Incompatible dimensions")
    c = zeromat(n, q)
    for i in range(n):
        for j in range(q):
                c[i][j] = sum(a[i][k]*b[k][j] for k in range(p))
    return c
 
 
def mapmat(f, a):
    return [list(map(f, v)) for v in a]
 
def ratmat(a):
    return mapmat(Fraction, a)