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# Untitled

a guest Sep 24th, 2018 91 Never
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1. import numpy as np
2.
3. A = np.array([[3.0,-0.1,-0.2],[0.1,7.0,-0.3],[0.3,-0.2,10.2]])
4.
5. B = np.array([[7.85],[-19.3],[71.4]])
6.
7.
8. ##########################################################################################
9. aMat = np.hstack([A, B]) # combine matrix A and B to create augmented matrix
10.
11. nRows = len(aMat[:,0]) # get how many rows
12. nCols = len(aMat[0,:]) # get how many columns
13.
14. #print 'Augmented Matrix'
15. #print aMat
16. #print '*****************************************************************************'
17.
18. # forward elimination
19.
20. #Matrix in Python [row,col]
21.
22. #1) keep row0
23. #2) from row1 ; calculate scale factor c= aMat[1,0]/aMat[0,0]
24. #3) find new row1 ; row1_new = row1 - c*row0
25.
26. #4) from row2 ; calculate scale factor c=aMat[2,0]/aMat[0,0]
27. #5) find new row2 ; row2_new = row2 - c*row0
28.
29. #Repeat step in row1 and row2
30.
31.
32. for row in range(1,3):
33.     c = aMat[row,0]/aMat[0,0]
34.
35.     for col in range(4):
36.         aMat[row,col] =  aMat[row,col]-(aMat[0,col]*c)
37. print "Step1: "
38. print aMat
39.
40. #Step2
41.
42. for row in range(2,3):
43.     c = aMat[row,1]/aMat[1,1]
44.
45.     for col in range(4):
46.         aMat[row,col] =  aMat[row,col]-(aMat[1,col]*c)
47. print "Step2: "
48. print aMat
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