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)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)
xpython linear equation components
def liner(x,y):
""" 'y(x) = ax + b' --> get a & b by providing arrays x & y"""
sum_xy = sum([i*j for i,j in zip(x,y)])
sum_x2 = sum([pow(i,2)for i in x ])
a = ( len(y)*sum_xy - sum(x)*sum(y) ) / ( len(y)*sum_x2 - pow(sum(x),2))
b = ( sum(y)*sum_x2 - sum(x)*sum_xy) / ( len(y)*sum_x2 - pow(sum(x),2))
return a,b
xx = [0,2,6,11,12,13,17,21,24,26,31,36,37]
yy = [0,4,7,11,16,26,27,31,39,47,49,57,58]
a,b = liner(xx,yy)
print("a:",a," b:",b) # a: 1.631407787762088 b: -1.000941377834831
# Or use numpy
import numpy as np
np.polyfit(xx, yy, 1) # [ 1.63140779 -1.00094138]solve linear system python
>>> a = np.array([[3,1], [1,2]])
>>> b = np.array([9,8])
>>> x = np.linalg.solve(a, b)
>>> x
array([2., 3.])Copyright © 2021 Codeinu
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