""" Algorithm for calculating the most cost-efficient sequence for converting one string into another. The only allowed operations are --- Cost to copy a character is copy_cost --- Cost to replace a character is replace_cost --- Cost to delete a character is delete_cost --- Cost to insert a character is insert_cost """ def compute_transform_tables( source_string: str, destination_string: str, copy_cost: int, replace_cost: int, delete_cost: int, insert_cost: int, ) -> tuple[list[list[int]], list[list[str]]]: """ Finds the most cost efficient sequence for converting one string into another. >>> costs, operations = compute_transform_tables("cat", "cut", 1, 2, 3, 3) >>> costs[0][:4] [0, 3, 6, 9] >>> costs[2][:4] [6, 4, 3, 6] >>> operations[0][:4] ['0', 'Ic', 'Iu', 'It'] >>> operations[3][:4] ['Dt', 'Dt', 'Rtu', 'Ct'] >>> compute_transform_tables("", "", 1, 2, 3, 3) ([[0]], [['0']]) """ source_seq = list(source_string) destination_seq = list(destination_string) len_source_seq = len(source_seq) len_destination_seq = len(destination_seq) costs = [ [0 for _ in range(len_destination_seq + 1)] for _ in range(len_source_seq + 1) ] ops = [ ["0" for _ in range(len_destination_seq + 1)] for _ in range(len_source_seq + 1) ] for i in range(1, len_source_seq + 1): costs[i][0] = i * delete_cost ops[i][0] = f"D{source_seq[i - 1]}" for i in range(1, len_destination_seq + 1): costs[0][i] = i * insert_cost ops[0][i] = f"I{destination_seq[i - 1]}" for i in range(1, len_source_seq + 1): for j in range(1, len_destination_seq + 1): if source_seq[i - 1] == destination_seq[j - 1]: costs[i][j] = costs[i - 1][j - 1] + copy_cost ops[i][j] = f"C{source_seq[i - 1]}" else: costs[i][j] = costs[i - 1][j - 1] + replace_cost ops[i][j] = f"R{source_seq[i - 1]}" + str(destination_seq[j - 1]) if costs[i - 1][j] + delete_cost < costs[i][j]: costs[i][j] = costs[i - 1][j] + delete_cost ops[i][j] = f"D{source_seq[i - 1]}" if costs[i][j - 1] + insert_cost < costs[i][j]: costs[i][j] = costs[i][j - 1] + insert_cost ops[i][j] = f"I{destination_seq[j - 1]}" return costs, ops def assemble_transformation(ops: list[list[str]], i: int, j: int) -> list[str]: """ Assembles the transformations based on the ops table. >>> ops = [['0', 'Ic', 'Iu', 'It'], ... ['Dc', 'Cc', 'Iu', 'It'], ... ['Da', 'Da', 'Rau', 'Rat'], ... ['Dt', 'Dt', 'Rtu', 'Ct']] >>> x = len(ops) - 1 >>> y = len(ops[0]) - 1 >>> assemble_transformation(ops, x, y) ['Cc', 'Rau', 'Ct'] >>> ops1 = [['0']] >>> x1 = len(ops1) - 1 >>> y1 = len(ops1[0]) - 1 >>> assemble_transformation(ops1, x1, y1) [] """ if i == 0 and j == 0: return [] elif ops[i][j][0] in {"C", "R"}: seq = assemble_transformation(ops, i - 1, j - 1) seq.append(ops[i][j]) return seq elif ops[i][j][0] == "D": seq = assemble_transformation(ops, i - 1, j) seq.append(ops[i][j]) return seq else: seq = assemble_transformation(ops, i, j - 1) seq.append(ops[i][j]) return seq if __name__ == "__main__": _, operations = compute_transform_tables("Python", "Algorithms", -1, 1, 2, 2) m = len(operations) n = len(operations[0]) sequence = assemble_transformation(operations, m - 1, n - 1) string = list("Python") i = 0 cost = 0 with open("min_cost.txt", "w") as file: for op in sequence: print("".join(string)) if op[0] == "C": file.write("%-16s" % "Copy %c" % op[1]) # noqa: UP031 file.write("\t\t\t" + "".join(string)) file.write("\r\n") cost -= 1 elif op[0] == "R": string[i] = op[2] file.write("%-16s" % ("Replace %c" % op[1] + " with " + str(op[2]))) # noqa: UP031 file.write("\t\t" + "".join(string)) file.write("\r\n") cost += 1 elif op[0] == "D": string.pop(i) file.write("%-16s" % "Delete %c" % op[1]) # noqa: UP031 file.write("\t\t\t" + "".join(string)) file.write("\r\n") cost += 2 else: string.insert(i, op[1]) file.write("%-16s" % "Insert %c" % op[1]) # noqa: UP031 file.write("\t\t\t" + "".join(string)) file.write("\r\n") cost += 2 i += 1 print("".join(string)) print("Cost: ", cost) file.write("\r\nMinimum cost: " + str(cost))