Hello coders, In this post, you will learn how to solve Linear Algebra in Python HackerRank Solution. This problem is a part of the Python Hacker Rank series.
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. linalg.det The linalg.det tool computes the determinant of an array.
print numpy.linalg.det([[1 , 2], [2, 1]]) #Output : -3.0
linalg.eigThe linalg.eig computes the eigenvalues and right eigenvectors of a square array.
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]]
linalg.invThe 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.
Output Format :
Print the determinant of A.
Sample Input :
2 1.1 1.1 1.1 1.1
Sample Output :
0.0
Linear Algebra in Python HackerRank Solution
import numpy N = int(input()) A = numpy.array([input().split() for _ in range(N)], float) print(round(numpy.linalg.det(A),2))
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