Added Gaussian Elimination method for inverse of matrix

python/Gaussian Method for inverse/GaussianElimination.py

@@ -0,0 +1,40 @@
+import numpy as np
+m = int(input('number of rows and columns, m = '))
+matrix = []; columns = []
+matrix1 = []
+# initialize the number of rows
+for i in range(0,m):
+    matrix += [0]
+    matrix1 += [0]
+# initialize the matrix
+for i in range (0,m):
+    matrix[i] = [0]*m
+    matrix1[i] = [0]*m
+
+for i in range (0,m):
+    for j in range (0,m):
+        print ('entry in row: ',i+1,' column: ',j+1)
+        matrix[i][j] = float(input())
+for i in range (0,m):
+	for j in range (0,m):
+		if i==j:
+			matrix1[i][j] = 1.0;	        
+
+A = np.array(matrix);
+B = np.array(matrix1);
+if(np.linalg.det(A)!=0):
+	for i in range(0,m):
+		c = A[i,i];
+		A[i,:] = A[i,:]/c;
+		B[i,:] = B[i,:]/c;
+
+		for j in range(0,m):
+			if i!=j:
+				d = A[j,i];
+				print(d)
+				A[j,:] = A[j,:]-d*A[i,:];
+				B[j,:] = B[j,:]-d*B[i,:];
+	print(B)
+else:
+	print("Inverse not possible as determinant of matrix is zero");
+