for key in self.support:
print(list(key), f"{self.support[key]:.2f}")
print()
if __name__ == "__main__":
# Init database and field list
db = Database(['A', 'B', 'C', 'D', 'E', 'F'])
# Create transactions
t1 = Transaction(0, frozenset(['A', 'B', 'C']))
t2 = Transaction(1, frozenset(['A', 'C']))
t3 = Transaction(2, frozenset(['A', 'D']))
t4 = Transaction(3, frozenset(['B', 'E', 'F']))
# Add transactions to database
db.add_transaction(t1)
db.add_transaction(t2)
db.add_transaction(t3)
db.add_transaction(t4)
# Output database
db.print_as_set()
db.print_as_boolean()
# Init and run Apriory
alg = AprioriAlgorithm(db, 0.30, 0.50)
alg.run()
# Print results
print('Support of frequent itemsets:')
alg.print_support()
'''Print support of frequent itemsets'''
itemsets = list(self.support.keys())
itemsets.sort(key=lambda item: self.support[item], reverse=True)
for item in itemsets:
print(f"{list(item)} supp = {self.support[item]:.2f}")
print()
if __name__ == "__main__":
# initialize database object with list of fields
db = Database(['A', 'B', 'C', 'D', 'E', 'F', 'G'])
# add transactions to database
db.add_transaction(Transaction(0, ['A', 'D', 'F']))
db.add_transaction(Transaction(1, ['A', 'C', 'D', 'E']))
db.add_transaction(Transaction(2, ['B', 'D']))
db.add_transaction(Transaction(3, ['B', 'C', 'D']))
db.add_transaction(Transaction(4, ['B', 'C']))
db.add_transaction(Transaction(5, ['A', 'B', 'D']))
db.add_transaction(Transaction(6, ['B', 'D', 'E']))
db.add_transaction(Transaction(7, ['B', 'C', 'E', 'G']))
db.add_transaction(Transaction(8, ['C', 'D', 'F']))
db.add_transaction(Transaction(9, ['A', 'B', 'D']))
# print database
db.print_as_boolean()
# create and build fp-tree
fpt = FPTree(db)
