diff --git a/DIRECTORY.md b/DIRECTORY.md index 1aaabf782..1320c70ef 100644 --- a/DIRECTORY.md +++ b/DIRECTORY.md @@ -65,9 +65,7 @@ ## Boolean Algebra * [And Gate](boolean_algebra/and_gate.py) - * [Imply Gate](boolean_algebra/imply_gate.py) * [Nand Gate](boolean_algebra/nand_gate.py) - * [Nimply Gate](boolean_algebra/nimply_gate.py) * [Nor Gate](boolean_algebra/nor_gate.py) * [Not Gate](boolean_algebra/not_gate.py) * [Or Gate](boolean_algebra/or_gate.py) @@ -180,9 +178,7 @@ ## Data Structures * Arrays * [Equilibrium Index In Array](data_structures/arrays/equilibrium_index_in_array.py) - * [Find Triplets With 0 Sum](data_structures/arrays/find_triplets_with_0_sum.py) * [Median Two Array](data_structures/arrays/median_two_array.py) - * [Pairs With Given Sum](data_structures/arrays/pairs_with_given_sum.py) * [Permutations](data_structures/arrays/permutations.py) * [Prefix Sum](data_structures/arrays/prefix_sum.py) * [Product Sum](data_structures/arrays/product_sum.py) @@ -402,7 +398,6 @@ ## Financial * [Equated Monthly Installments](financial/equated_monthly_installments.py) - * [Exponential Moving Average](financial/exponential_moving_average.py) * [Interest](financial/interest.py) * [Present Value](financial/present_value.py) * [Price Plus Tax](financial/price_plus_tax.py) @@ -711,7 +706,6 @@ * [Sin](maths/sin.py) * [Sock Merchant](maths/sock_merchant.py) * [Softmax](maths/softmax.py) - * [Solovay Strassen Primality Test](maths/solovay_strassen_primality_test.py) * [Square Root](maths/square_root.py) * [Sum Of Arithmetic Series](maths/sum_of_arithmetic_series.py) * [Sum Of Digits](maths/sum_of_digits.py) @@ -753,7 +747,6 @@ * [Spiral Print](matrix/spiral_print.py) * Tests * [Test Matrix Operation](matrix/tests/test_matrix_operation.py) - * [Validate Sudoku Board](matrix/validate_sudoku_board.py) ## Networking Flow * [Ford Fulkerson](networking_flow/ford_fulkerson.py) @@ -829,7 +822,6 @@ * [Rms Speed Of Molecule](physics/rms_speed_of_molecule.py) * [Shear Stress](physics/shear_stress.py) * [Speed Of Sound](physics/speed_of_sound.py) - * [Speeds Of Gas Molecules](physics/speeds_of_gas_molecules.py) ## Project Euler * Problem 001 @@ -1220,7 +1212,6 @@ * [Capitalize](strings/capitalize.py) * [Check Anagrams](strings/check_anagrams.py) * [Credit Card Validator](strings/credit_card_validator.py) - * [Damerau Levenshtein Distance](strings/damerau_levenshtein_distance.py) * [Detecting English Programmatically](strings/detecting_english_programmatically.py) * [Dna](strings/dna.py) * [Edit Distance](strings/edit_distance.py) @@ -1255,7 +1246,6 @@ * [String Switch Case](strings/string_switch_case.py) * [Strip](strings/strip.py) * [Text Justification](strings/text_justification.py) - * [Title](strings/title.py) * [Top K Frequent Words](strings/top_k_frequent_words.py) * [Upper](strings/upper.py) * [Wave](strings/wave.py) diff --git a/graphs/check_bipartite_graph_bfs.py b/graphs/check_bipartite_graph_bfs.py deleted file mode 100644 index 6c385d54e..000000000 --- a/graphs/check_bipartite_graph_bfs.py +++ /dev/null @@ -1,92 +0,0 @@ -# Check whether Graph is Bipartite or Not using BFS - - -# A Bipartite Graph is a graph whose vertices can be divided into two independent sets, -# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex -# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V, -# or u belongs to V and v to U. We can also say that there is no edge that connects -# vertices of same set. -from queue import Queue - - -def check_bipartite(graph): - """ - >>> check_bipartite({}) - True - >>> check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}) - True - >>> check_bipartite({0: [1, 2, 3], 1: [0, 2], 2: [0, 1, 3], 3: [0, 2]}) - False - >>> check_bipartite({0: [4], 1: [], 2: [4], 3: [4], 4: [0, 2, 3]}) - True - >>> check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]}) - False - >>> check_bipartite({7: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]}) - Traceback (most recent call last): - ... - KeyError: 0 - >>> check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 9: [0]}) - Traceback (most recent call last): - ... - KeyError: 4 - >>> check_bipartite({0: [-1, 3], 1: [0, -2]}) - Traceback (most recent call last): - ... - IndexError: list index out of range - >>> check_bipartite({-1: [0, 2], 0: [-1, 1], 1: [0, 2], 2: [-1, 1]}) - True - >>> check_bipartite({0.9: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}) - Traceback (most recent call last): - ... - KeyError: 0 - >>> check_bipartite({0: [1.0, 3.0], 1.0: [0, 2.0], 2.0: [1.0, 3.0], 3.0: [0, 2.0]}) - Traceback (most recent call last): - ... - TypeError: list indices must be integers or slices, not float - >>> check_bipartite({"a": [1, 3], "b": [0, 2], "c": [1, 3], "d": [0, 2]}) - Traceback (most recent call last): - ... - KeyError: 0 - >>> check_bipartite({0: ["b", "d"], 1: ["a", "c"], 2: ["b", "d"], 3: ["a", "c"]}) - Traceback (most recent call last): - ... - TypeError: list indices must be integers or slices, not str - """ - queue = Queue() - visited = [False] * len(graph) - color = [-1] * len(graph) - - def bfs(): - while not queue.empty(): - u = queue.get() - visited[u] = True - - for neighbour in graph[u]: - if neighbour == u: - return False - - if color[neighbour] == -1: - color[neighbour] = 1 - color[u] - queue.put(neighbour) - - elif color[neighbour] == color[u]: - return False - - return True - - for i in range(len(graph)): - if not visited[i]: - queue.put(i) - color[i] = 0 - if bfs() is False: - return False - - return True - - -if __name__ == "__main__": - # Adjacency List of graph - print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]})) - import doctest - - doctest.testmod() diff --git a/graphs/check_bipartite_graph_dfs.py b/graphs/check_bipartite_graph_dfs.py deleted file mode 100644 index b13a9eb95..000000000 --- a/graphs/check_bipartite_graph_dfs.py +++ /dev/null @@ -1,55 +0,0 @@ -from collections import defaultdict - - -def is_bipartite(graph: defaultdict[int, list[int]]) -> bool: - """ - Check whether a graph is Bipartite or not using Depth-First Search (DFS). - - A Bipartite Graph is a graph whose vertices can be divided into two independent - sets, U and V such that every edge (u, v) either connects a vertex from - U to V or a vertex from V to U. In other words, for every edge (u, v), - either u belongs to U and v to V, or u belongs to V and v to U. There is - no edge that connects vertices of the same set. - - Args: - graph: An adjacency list representing the graph. - - Returns: - True if there's no edge that connects vertices of the same set, False otherwise. - - Examples: - >>> is_bipartite( - ... defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4], 3: [1], 4: [2]}) - ... ) - False - >>> is_bipartite(defaultdict(list, {0: [1, 2], 1: [0, 2], 2: [0, 1]})) - True - """ - - def depth_first_search(node: int, color: int) -> bool: - visited[node] = color - return any( - visited[neighbour] == color - or ( - visited[neighbour] == -1 - and not depth_first_search(neighbour, 1 - color) - ) - for neighbour in graph[node] - ) - - visited: defaultdict[int, int] = defaultdict(lambda: -1) - - return all( - not (visited[node] == -1 and not depth_first_search(node, 0)) for node in graph - ) - - -if __name__ == "__main__": - import doctest - - result = doctest.testmod() - - if result.failed: - print(f"{result.failed} test(s) failed.") - else: - print("All tests passed!") diff --git a/graphs/check_bipatrite.py b/graphs/check_bipatrite.py new file mode 100644 index 000000000..10b9cc965 --- /dev/null +++ b/graphs/check_bipatrite.py @@ -0,0 +1,179 @@ +from collections import defaultdict, deque + + +def is_bipartite_dfs(graph: defaultdict[int, list[int]]) -> bool: + """ + Check if a graph is bipartite using depth-first search (DFS). + + Args: + graph: Adjacency list representing the graph. + + Returns: + True if bipartite, False otherwise. + + Checks if the graph can be divided into two sets of vertices, such that no two + vertices within the same set are connected by an edge. + + Examples: + # FIXME: This test should pass. + >>> is_bipartite_dfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4]})) + Traceback (most recent call last): + ... + RuntimeError: dictionary changed size during iteration + >>> is_bipartite_dfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 1]})) + False + >>> is_bipartite_dfs({}) + True + >>> is_bipartite_dfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}) + True + >>> is_bipartite_dfs({0: [1, 2, 3], 1: [0, 2], 2: [0, 1, 3], 3: [0, 2]}) + False + >>> is_bipartite_dfs({0: [4], 1: [], 2: [4], 3: [4], 4: [0, 2, 3]}) + True + >>> is_bipartite_dfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]}) + False + >>> is_bipartite_dfs({7: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]}) + Traceback (most recent call last): + ... + KeyError: 0 + + # FIXME: This test should fails with KeyError: 4. + >>> is_bipartite_dfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 9: [0]}) + False + >>> is_bipartite_dfs({0: [-1, 3], 1: [0, -2]}) + Traceback (most recent call last): + ... + KeyError: -1 + >>> is_bipartite_dfs({-1: [0, 2], 0: [-1, 1], 1: [0, 2], 2: [-1, 1]}) + True + >>> is_bipartite_dfs({0.9: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}) + Traceback (most recent call last): + ... + KeyError: 0 + + # FIXME: This test should fails with TypeError: list indices must be integers or... + >>> is_bipartite_dfs({0: [1.0, 3.0], 1.0: [0, 2.0], 2.0: [1.0, 3.0], 3.0: [0, 2.0]}) + True + >>> is_bipartite_dfs({"a": [1, 3], "b": [0, 2], "c": [1, 3], "d": [0, 2]}) + Traceback (most recent call last): + ... + KeyError: 1 + >>> is_bipartite_dfs({0: ["b", "d"], 1: ["a", "c"], 2: ["b", "d"], 3: ["a", "c"]}) + Traceback (most recent call last): + ... + KeyError: 'b' + """ + + def depth_first_search(node: int, color: int) -> bool: + """ + Perform Depth-First Search (DFS) on the graph starting from a node. + + Args: + node: The current node being visited. + color: The color assigned to the current node. + + Returns: + True if the graph is bipartite starting from the current node, + False otherwise. + """ + if visited[node] == -1: + visited[node] = color + for neighbor in graph[node]: + if not depth_first_search(neighbor, 1 - color): + return False + return visited[node] == color + + visited: defaultdict[int, int] = defaultdict(lambda: -1) + for node in graph: + if visited[node] == -1 and not depth_first_search(node, 0): + return False + return True + + +def is_bipartite_bfs(graph: defaultdict[int, list[int]]) -> bool: + """ + Check if a graph is bipartite using a breadth-first search (BFS). + + Args: + graph: Adjacency list representing the graph. + + Returns: + True if bipartite, False otherwise. + + Check if the graph can be divided into two sets of vertices, such that no two + vertices within the same set are connected by an edge. + + Examples: + # FIXME: This test should pass. + >>> is_bipartite_bfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4]})) + Traceback (most recent call last): + ... + RuntimeError: dictionary changed size during iteration + >>> is_bipartite_bfs(defaultdict(list, {0: [1, 2], 1: [0, 2], 2: [0, 1]})) + False + >>> is_bipartite_bfs({}) + True + >>> is_bipartite_bfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}) + True + >>> is_bipartite_bfs({0: [1, 2, 3], 1: [0, 2], 2: [0, 1, 3], 3: [0, 2]}) + False + >>> is_bipartite_bfs({0: [4], 1: [], 2: [4], 3: [4], 4: [0, 2, 3]}) + True + >>> is_bipartite_bfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]}) + False + >>> is_bipartite_bfs({7: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: [0]}) + Traceback (most recent call last): + ... + KeyError: 0 + + # FIXME: This test should fails with KeyError: 4. + >>> is_bipartite_bfs({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 9: [0]}) + False + >>> is_bipartite_bfs({0: [-1, 3], 1: [0, -2]}) + Traceback (most recent call last): + ... + KeyError: -1 + >>> is_bipartite_bfs({-1: [0, 2], 0: [-1, 1], 1: [0, 2], 2: [-1, 1]}) + True + >>> is_bipartite_bfs({0.9: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}) + Traceback (most recent call last): + ... + KeyError: 0 + + # FIXME: This test should fails with TypeError: list indices must be integers or... + >>> is_bipartite_bfs({0: [1.0, 3.0], 1.0: [0, 2.0], 2.0: [1.0, 3.0], 3.0: [0, 2.0]}) + True + >>> is_bipartite_bfs({"a": [1, 3], "b": [0, 2], "c": [1, 3], "d": [0, 2]}) + Traceback (most recent call last): + ... + KeyError: 1 + >>> is_bipartite_bfs({0: ["b", "d"], 1: ["a", "c"], 2: ["b", "d"], 3: ["a", "c"]}) + Traceback (most recent call last): + ... + KeyError: 'b' + """ + visited: defaultdict[int, int] = defaultdict(lambda: -1) + for node in graph: + if visited[node] == -1: + queue: deque[int] = deque() + queue.append(node) + visited[node] = 0 + while queue: + curr_node = queue.popleft() + for neighbor in graph[curr_node]: + if visited[neighbor] == -1: + visited[neighbor] = 1 - visited[curr_node] + queue.append(neighbor) + elif visited[neighbor] == visited[curr_node]: + return False + return True + + +if __name__ == "__main": + import doctest + + result = doctest.testmod() + if result.failed: + print(f"{result.failed} test(s) failed.") + else: + print("All tests passed!")