def main() -> None:
print("Podaj pierwszy ciąg:")
string1 = input()
print("Podaj drugi ciąg:")
string2 = input()
matrix = Matrix(string1, string2)
print(f"Najdłuższy wspólny podciąg: {matrix.right_bottom}")
print(f"LCS: {matrix.lcs}")
def _gen_random_matrix(self, n_rows, n_colums):
"""Generate a n_rows * n_columns matrix with random numbers.
Arguments:
n_rows {int} -- The number of rows.
n_colums {int} -- The number of columns.
Returns:
Matrix
"""
data = [[random() for _ in range(n_colums)] for _ in range(n_rows)]
return Matrix(data)
def _items_mul_ratings(self, items, ratings):
"""Multiply a dense matrix(item matrix) with sparse matrix (rating matrix).
The result(users) is a k * m matrix, m stands for number of user_ids.
Arguments:
items {Matrix} -- k * n matrix, n stands for number of item_ids.
ratings {dict} -- The items ratings by users.
{user_id: {item_id: rating}}
Returns:
Matrix -- User matrix.
"""
def f(items_row, user_id):
item_ids = iter(ratings[user_id].keys())
scores = iter(ratings[user_id].values())
col_nos = map(lambda x: self.item_ids_dict[x], item_ids)
_items_row = map(lambda x: items_row[x], col_nos)
return sum(a * b for a, b in zip(_items_row, scores))
ret = [[f(items_row, user_id) for user_id in self.user_ids]
for items_row in items.data]
return Matrix(ret)
def handle(self, *args, **options):
m = Matrix()
m.pantsMatrixToCsv()
self.stdout.write(self.style.SUCCESS(f"All tops are added in matrix!"))
