Linear Algebra in Python - HackerRank Solution
Linear Algebra in Python - HackerRank Solution
Problem :
The NumPy module also comes with a number of built-in routines for linear
algebra calculations. These can be found in the sub-module linalg.
print numpy.linalg.det([[1 , 2], [2, 1]]) #Output : -3.0
vals, vecs = numpy.linalg.eig([[1 , 2], [2, 1]]) print vals #Output : [ 3. -1.] print vecs #Output : [[ 0.70710678 -0.70710678] # [ 0.70710678 0.70710678]]
The linalg.inv tool computes the (multiplicative) inverse of a matrix.
print numpy.linalg.inv([[1 , 2], [2, 1]]) #Output : [[-0.33333333 0.66666667] # [ 0.66666667 -0.33333333]]
Other routines can be found
here
Task :
You are given a square matrix A with dimensions NXN. Your task is to find the
determinant. Note: Round the answer to 2 places after the decimal.
Input Format :
The first line contains the integer N.
The next N lines contains the N space separated elements of array A.
The next N lines contains the N space separated elements of array A.
Output Format :
Print the determinant of A.
Sample Input :
2 1.1 1.1 1.1 1.1
Sample Output :
0.0
Solution :
1 2 3 4 5 6 7 8 | # Linear Algebra in Python - Hacker Rank Solution # Python 3 # Linear Algebra in Python - Hacker Rank Solution START import numpy N = int(input()) A = numpy.array([input().split() for _ in range(N)], float) print(round(numpy.linalg.det(A),2)) # Linear Algebra in Python - Hacker Rank Solution END |
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