Posts: 203 Threads: 35 Joined: Mar 2019 Reputation: 0 Likes received: 1 how do you write a function that takes a matrix as a parameter and for symmetric, skew and others returns respectively 1,1 and 0? here is what I have so far but I get errors. import numpy as np a=1 b=2 c=3 d=4 e=5 f=6 g=7 h=8 i=9 def a(x): return np.array([a,b,c], [d,e,f], [g,h,i]) def b(y): return np.array([a,d,e],[b,e,h],[c,f,i]) if a(x)==b(y): return 1 if A==(1)*B: return 1. else: return 0 Posts: 576 Threads: 1 Joined: Mar 2018 Reputation: 74 Likes received: 87 What errors did you get? Your function a is declared with argument x , why? it is not used in the function body. Posts: 203 Threads: 35 Joined: Mar 2019 Reputation: 0 Likes received: 1 Mar142019, 08:42 AM (This post was last modified: Mar142019, 08:57 AM by mcgrim.) x invalid syntax, that's the error. The program is supposed to return 1 if the matrix is symmetric, 1 if is skew symmetric and 0 in all other cases.
I have also changed a(x) to just x and b(y) to y. Posts: 576 Threads: 1 Joined: Mar 2018 Reputation: 74 Likes received: 87 Your code should be something like this: import numpy as np
def is_symmetric(A):
"""Returns True if input matrix is symmetric, False  otherwise.
Parameters
==========
:param A: a matrix (2D array, Numpy array or list of lists) to be tested;
:rtype: bool;
:returns: True if A == A.T, otherwise  False.
"""
return np.array(A) == np.array(A).T
def is_skew(A):
"""Returns True if input matrix is skew, False  otherwise.
# TODO: Docs needed (You need to accomplish docstring here!)
"""
return np.array(A) == np.array(A).T
def test_matrix(A):
"""Test matrix for special form
Returns 1 if input matrix is symmetric, 1 if
input matrix is skew, 0  otherwise.
Parameters
==========
:param A: # TODO: Docs needed
"""
if is_symmetric(A):
return 1
# TODO: Additional conditions should be added
if __name__ == '__main__':
a, b, c, d, e, f, g, h, i = 1, 2, 3, 4, 5, 6, 7, 8, 9
A = [[a, b, c],
[d, e, f],
[g, h, i]]
print("Testing matrix A: ", test_matrix(A)) You need to complete the code snippet I wrote... Posts: 203 Threads: 35 Joined: Mar 2019 Reputation: 0 Likes received: 1 Mar152019, 02:00 PM (This post was last modified: Mar152019, 02:10 PM by mcgrim. Edited 1 time in total. Edit Reason: fixed tags ) thanks a lot for your hints. I have kept your code and changed it a bit, however when I run it, there is a logical error in it as I always get 1, no matter how the matrix looks. import numpy as np
def is_symmetric(A):
return np.array(A) == np.array(A).T
def is_skew(A):
return np.array(A) == np.array(A).T
def test_matrix(A):
if is_symmetric(np.any(A)):
return 1
if is_skew(np.any(A)):
return 1
else:
return 0
if __name__ == '__main__':
a, b, c, d, e, f, g, h, i = 1,2,3,4,5,6,7,8,9
A = [[a, b, c],
[d, e, f],
[g, h, i]]
print("Testing matrix A: ", test_matrix(A))
import numpy as np
def is_symmetric(A):
return np.array(A) == np.array(A).T
def is_skew(A):
return np.array(A) == np.array(A).T
def test_matrix(A):
if is_symmetric(np.any(A)):
return 1
if is_skew(np.any(A)):
return 1
else:
return 0
if __name__ == '__main__':
a, b, c, d, e, f, g, h, i = 1,2,3,4,5,6,7,8,9
A = [[a, b, c],
[d, e, f],
[g, h, i]]
print("Testing matrix A: ", test_matrix(A))
ichabod801 wrote Mar152019, 02:02 PM:Use python tags (the python icon) for blocks of code. The icode tags (brackets icon) is for inline code . Posts: 576 Threads: 1 Joined: Mar 2018 Reputation: 74 Likes received: 87 (Mar152019, 02:00 PM)mcgrim Wrote: I have kept your code and changed it a bit, however when I run it, there is a logical error in it as I always get 1, no matter how the matrix looks. This is because you need to use .all() , e.g. return (np.array(A) == np.array(A).T).all() . Moreover, it would be better to use floatingpoint comparison, e.g. np.allclose(np.array(A), np.array(A).T) . This will allow correct handling of such cases as 0.99999999999 == 1.00000000000003, that, obviously, will return False , but we might expect (wish) that it should return True . Posts: 203 Threads: 35 Joined: Mar 2019 Reputation: 0 Likes received: 1 Thanks for your help, but the issue unfortunately remains. here is the changed code: import numpy as np
def is_symmetric(A):
return (np.array(A) == np.array(A.transpose())).all
def is_skew(A):
return (np.array(A) == np.array(A.transpose())).all
def test_matrix(A):
if is_symmetric(np.any(A)):
return 1
if is_skew(np.any(A)):
return 1
else:
return 0
if __name__ == '__main__':
a, b, c, d, e, f, g, h, i = 0,1,2,3,4,5,6,7,8
A = [[a, b, c],
[d, e, f],
[g, h, i]]
print("Testing matrix A: ", test_matrix(A))
Posts: 576 Threads: 1 Joined: Mar 2018 Reputation: 74 Likes received: 87 .all is a method, not a property, you forgot () at the end. Posts: 203 Threads: 35 Joined: Mar 2019 Reputation: 0 Likes received: 1 even after writing .all(), the outcome doesn't change. I keep getting the same outcome. Posts: 576 Threads: 1 Joined: Mar 2018 Reputation: 74 Likes received: 87 Mar182019, 12:48 PM (This post was last modified: Mar182019, 12:48 PM by scidam. Edited 1 time in total.) import numpy as np
def is_symmetric(A):
return (np.array(A) == np.array(A).transpose()).all()
def is_skew(A):
return (np.array(A) == np.array(A).transpose()).all()
def test_matrix(A):
if is_symmetric(A):
return 1
if is_skew(A):
return 1
else:
return 0
if __name__ == '__main__':
a, b, c, d, e, f, g, h, i = 0,1,2,3,4,5,6,7,8
symmetric_A = [[a, b, c],
[b, c, a],
[c, a, b]]
skew_A = [[0, b, c],
[b, 0, a],
[c, a, 0]]
arbitrary_A = [[a, b, c],
[d, e, f],
[g, h, i]]
print("Testing with symmetric matrix ", test_matrix(symmetric_A))
print("Testing with arbitrary matrix ", test_matrix(arbitrary_A))
print("Testing with skew matrix ", test_matrix(skew_A))
Output: Testing with symmetric matrix 1
Testing with arbitrary matrix 0
Testing with skew matrix 1
