def sim_matrix_shuffle(m, row_order, check=True):
'''Re-arrange a similarity matrix based on a new row order
Params:
- m: Similarity matrix. Can be dense (Numpy array / matrix) or sparse (as long as it supports arithmetic operations)
- row_order: A list of integers, which makes a permutation of the matrix rows
- check: Should the permutation be checked before creating the matrix (can be turned off in case you are sure and want to save some time)
Returns: A re-ordered similarity matrix (type depends on the input type. Sparse should return sparse)
'''
if check:
if not m.shape[0] == len(row_order):
raise ValueError(
'''Length of `row_order` must match the number of rows in the matrix'''
)
if not is_permutation(row_order):
raise ValueError('''`row_order` is not a permutation''')
sh = row_shuffle_matrix(row_order)
return sh * m * sh
def test_is_permutation():
p = [9, 4, 5, 7, 2, 6, 3, 8, 0, 1]
assert is_permutation(p)
def test_not_permutation3():
p = [9, 10, 5, 7, 2, 6, 5, 8, 0, 1]
assert not is_permutation(p)
def test_not_permutation1():
p = [9, 4, 7, 2, 6, 3, 8, 0, 1]
assert not is_permutation(p)