chat

🔍

question:def stable_matching(N, M, doctor_preferences, patient_preferences): Finds the stable matches between doctors and patients. Args: N (int): Number of doctors. M (int): Number of patients. doctor_preferences (list of lists): Each doctor's list of preferred patients. patient_preferences (list of lists): Each patient's list of preferred doctors. Returns: list of tuples: List of stable matches (doctor_id, patient_id). # Implement the algorithm to find stable matches following the given rules def parse_input(input_string): Parses the input string into respective components. Args: input_string (str): The input string in the given format. Returns: (N, M, doctor_preferences, patient_preferences): Parsed input components. # Implement the function to parse the input string def main(input_string): Main function to use the parse_input and stable_matching functions. Args: input_string (str): The input string in the given format. Returns: str: Formatted string of stable matches. N, M, doctor_preferences, patient_preferences = parse_input(input_string) stable_matches = stable_matching(N, M, doctor_preferences, patient_preferences) output = "n".join(f"{doctor} {patient}" for doctor, patient in stable_matches) return output # Unit Tests def test_stable_matching_case_1(): input_string = 4 4 P1 0: 2, 1, 3 1: 0, 2, 3 2: 3, 0, 1 3: 1, 2, 0 P2 0: 1, 2, 3 1: 3, 0, 2 2: 0, 1, 3 3: 2, 1, 0 expected_output = "0 2n1 0n2 3n3 1" assert main(input_string) == expected_output def test_stable_matching_case_2(): input_string = 3 3 P1 0: 0, 1, 2 1: 1, 0, 2 2: 2, 0, 1 P2 0: 0, 1, 2 1: 1, 0, 2 2: 2, 0, 1 expected_output = "0 0n1 1n2 2" assert main(input_string) == expected_output def test_stable_matching_case_3(): input_string = 2 3 P1 0: 1, 0 1: 0, 2 P2 0: 0, 1 1: 1, 0 2: 0, 1 expected_output = "0 1n1 0" assert main(input_string) == expected_output def test_parse_input(): input_string = 2 3 P1 0: 1, 0 1: 0, 2 P2 0: 0, 1 1: 1, 0 2: 0, 1 expected_N = 2 expected_M = 3 expected_doctor_preferences = [[1, 0], [0, 2]] expected_patient_preferences = [[0, 1], [1, 0], [0, 1]] N, M, doctor_preferences, patient_preferences = parse_input(input_string) assert N == expected_N assert M == expected_M assert doctor_preferences == expected_doctor_preferences assert patient_preferences == expected_patient_preferences

answer:def stable_matching(N, M, doctor_preferences, patient_preferences): Finds the stable matches between doctors and patients. Args: N (int): Number of doctors. M (int): Number of patients. doctor_preferences (list of lists): Each doctor's list of preferred patients. patient_preferences (list of lists): Each patient's list of preferred doctors. Returns: list of tuples: List of stable matches (doctor_id, patient_id). # Initializing the proposals and pairings free_doctors = list(range(N)) engaged_patients = [-1] * M doctor_to_patient = [-1] * N patient_preference_rankings = [{d: i for i, d in enumerate(patient_preferences[p])} for p in range(M)] while free_doctors: doctor = free_doctors.pop(0) for patient in doctor_preferences[doctor]: if engaged_patients[patient] == -1: doctor_to_patient[doctor] = patient engaged_patients[patient] = doctor break else: current_doctor = engaged_patients[patient] if patient_preference_rankings[patient][doctor] < patient_preference_rankings[patient][current_doctor]: free_doctors.append(current_doctor) doctor_to_patient[doctor] = patient engaged_patients[patient] = doctor break stable_matches = [(doctor, patient) for doctor, patient in enumerate(doctor_to_patient) if patient != -1] return stable_matches def parse_input(input_string): lines = input_string.strip().split('n') N, M = map(int, lines[0].split()) index = 2 doctor_preferences = [] for _ in range(N): line = lines[index].split(':')[1] doctor_preferences.append(list(map(int, line.split(',')))) index += 1 index += 1 patient_preferences = [] for _ in range(M): line = lines[index].split(':')[1] patient_preferences.append(list(map(int, line.split(',')))) index += 1 return N, M, doctor_preferences, patient_preferences def main(input_string): N, M, doctor_preferences, patient_preferences = parse_input(input_string) stable_matches = stable_matching(N, M, doctor_preferences, patient_preferences) output = "n".join(f"{doctor} {patient}" for doctor, patient in stable_matches) return output

question:def max_balanced_substrings(n: int, s: str) -> int: Returns the maximum number of balanced substrings that can be obtained from the given binary string s of length n. >>> max_balanced_substrings(8, '01010101') 4 >>> max_balanced_substrings(4, '1100') 1 >>> max_balanced_substrings(7, '0011010') 2 from solution import max_balanced_substrings def test_max_balanced_substrings_example1(): assert max_balanced_substrings(8, '01010101') == 4 def test_max_balanced_substrings_example2(): assert max_balanced_substrings(4, '1100') == 1 def test_max_balanced_substrings_example3(): assert max_balanced_substrings(7, '0011010') == 2 def test_max_balanced_substrings_single_characters(): assert max_balanced_substrings(1, '0') == 0 assert max_balanced_substrings(1, '1') == 0 def test_max_balanced_substrings_no_balanced(): assert max_balanced_substrings(5, '00000') == 0 assert max_balanced_substrings(5, '11111') == 0 def test_max_balanced_substrings_all_balanced(): assert max_balanced_substrings(6, '001100') == 1 assert max_balanced_substrings(10, '0101010101') == 5 def test_max_balanced_substrings_unbalanced_chunks(): assert max_balanced_substrings(8, '00001111') == 1 assert max_balanced_substrings(10, '0000111100') == 1

answer:def max_balanced_substrings(n, s): Returns the maximum number of balanced substrings that can be obtained from the given binary string s of length n. balance = 0 max_balanced_count = 0 for char in s: if char == '0': balance += 1 elif char == '1': balance -= 1 if balance == 0: max_balanced_count += 1 return max_balanced_count

question:def process_operations(operations): Process a series of operations on a list and maintain the number of distinct elements. :param operations: List of operations where each operation is a tuple. The first element of the tuple is an integer representing the type of operation: - 1 x: Insert the integer x into the list. - 2 x: Remove one occurrence of the integer x from the list. - 3: Output the number of distinct integers currently in the list. :return: List of integers representing the number of distinct elements after each type 3 operation. >>> process_operations([(1, 4), (1, 4), (1, 2), (3,), (2, 4), (3,)]) [2, 2] >>> process_operations([(1, 5), (1, 10), (1, 15), (3,)]) [3] >>> process_operations([(1, 5), (1, 10), (2, 5), (2, 10), (3,)]) [0] >>> process_operations([(1, 8), (2, 10), (3,)]) [1] >>> process_operations([(1, 1), (2, 1), (1, 2), (3,), (1, 2), (1, 3), (3,)]) [1, 2] >>> process_operations([(1, 3), (1, 3), (1, 3), (3,), (2, 3), (2, 3), (2, 3), (3,)]) [1, 0]

answer:def process_operations(operations): from collections import defaultdict element_count = defaultdict(int) distinct_count = 0 results = [] for operation in operations: if operation[0] == 1: x = operation[1] if element_count[x] == 0: distinct_count += 1 element_count[x] += 1 elif operation[0] == 2: x = operation[1] if element_count[x] > 0: element_count[x] -= 1 if element_count[x] == 0: distinct_count -= 1 elif operation[0] == 3: results.append(distinct_count) return results

question:def maximize_absolute_difference(N: int) -> List[int]: Returns a permutation of the sequence from 1 to N that maximizes the absolute difference between adjacent elements. >>> maximize_absolute_difference(1) [1] >>> maximize_absolute_difference(2) [1, 2] >>> maximize_absolute_difference(3) [1, 3, 2] >>> maximize_absolute_difference(4) [1, 4, 2, 3] >>> maximize_absolute_difference(5) [1, 5, 2, 4, 3]

answer:def maximize_absolute_difference(N): Returns a permutation of the sequence from 1 to N that maximizes the absolute difference between adjacent elements. result = [] left, right = 1, N while left <= right: if left <= right: result.append(left) left += 1 if left <= right: result.append(right) right -= 1 return result