[pull] master from TheAlgorithms:master

DIRECTORY.md

@@ -351,7 +351,7 @@
   * [Longest Common Subsequence](dynamic_programming/longest_common_subsequence.py)
   * [Longest Common Substring](dynamic_programming/longest_common_substring.py)
   * [Longest Increasing Subsequence](dynamic_programming/longest_increasing_subsequence.py)
-  * [Longest Increasing Subsequence O(Nlogn)](dynamic_programming/longest_increasing_subsequence_o(nlogn).py)
+  * [Longest Increasing Subsequence O Nlogn](dynamic_programming/longest_increasing_subsequence_o_nlogn.py)
   * [Longest Palindromic Subsequence](dynamic_programming/longest_palindromic_subsequence.py)
   * [Matrix Chain Multiplication](dynamic_programming/matrix_chain_multiplication.py)
   * [Matrix Chain Order](dynamic_programming/matrix_chain_order.py)
@@ -465,7 +465,7 @@
   * [Dijkstra Alternate](graphs/dijkstra_alternate.py)
   * [Dijkstra Binary Grid](graphs/dijkstra_binary_grid.py)
   * [Dinic](graphs/dinic.py)
-  * [Directed And Undirected (Weighted) Graph](graphs/directed_and_undirected_(weighted)_graph.py)
+  * [Directed And Undirected Weighted Graph](graphs/directed_and_undirected_weighted_graph.py)
   * [Edmonds Karp Multiple Source And Sink](graphs/edmonds_karp_multiple_source_and_sink.py)
   * [Eulerian Path And Circuit For Undirected Graph](graphs/eulerian_path_and_circuit_for_undirected_graph.py)
   * [Even Tree](graphs/even_tree.py)
@@ -792,7 +792,6 @@
   * [Minimum Cut](networking_flow/minimum_cut.py)
 
 ## Neural Network
-  * [2 Hidden Layers Neural Network](neural_network/2_hidden_layers_neural_network.py)
   * Activation Functions
     * [Binary Step](neural_network/activation_functions/binary_step.py)
     * [Exponential Linear Unit](neural_network/activation_functions/exponential_linear_unit.py)
@@ -809,6 +808,7 @@
   * [Convolution Neural Network](neural_network/convolution_neural_network.py)
   * [Input Data](neural_network/input_data.py)
   * [Simple Neural Network](neural_network/simple_neural_network.py)
+  * [Two Hidden Layers Neural Network](neural_network/two_hidden_layers_neural_network.py)
 
 ## Other
   * [Activity Selection](other/activity_selection.py)

backtracking/crossword_puzzle_solver.py

@@ -28,9 +28,8 @@ def is_valid(
         if vertical:
             if row + i >= len(puzzle) or puzzle[row + i][col] != "":
                 return False
-        else:
-            if col + i >= len(puzzle[0]) or puzzle[row][col + i] != "":
-                return False
+        elif col + i >= len(puzzle[0]) or puzzle[row][col + i] != "":
+            return False
     return True
 
 

cellular_automata/game_of_life.py

@@ -101,9 +101,8 @@ def __judge_point(pt: bool, neighbours: list[list[bool]]) -> bool:
             state = True
         elif alive > 3:
             state = False
-    else:
-        if alive == 3:
-            state = True
+    elif alive == 3:
+        state = True
 
     return state
 

ciphers/decrypt_caesar_with_chi_squared.py

@@ -206,20 +206,19 @@ def decrypt_caesar_with_chi_squared(
 
                     # Add the margin of error to the total chi squared statistic
                     chi_squared_statistic += chi_letter_value
-            else:
-                if letter.lower() in frequencies:
-                    # Get the amount of times the letter occurs in the message
-                    occurrences = decrypted_with_shift.count(letter)
+            elif letter.lower() in frequencies:
+                # Get the amount of times the letter occurs in the message
+                occurrences = decrypted_with_shift.count(letter)
 
-                    # Get the excepcted amount of times the letter should appear based
-                    # on letter frequencies
-                    expected = frequencies[letter] * occurrences
+                # Get the excepcted amount of times the letter should appear based
+                # on letter frequencies
+                expected = frequencies[letter] * occurrences
 
-                    # Complete the chi squared statistic formula
-                    chi_letter_value = ((occurrences - expected) ** 2) / expected
+                # Complete the chi squared statistic formula
+                chi_letter_value = ((occurrences - expected) ** 2) / expected
 
-                    # Add the margin of error to the total chi squared statistic
-                    chi_squared_statistic += chi_letter_value
+                # Add the margin of error to the total chi squared statistic
+                chi_squared_statistic += chi_letter_value
 
         # Add the data to the chi_squared_statistic_values dictionary
         chi_squared_statistic_values[shift] = (

ciphers/hill_cipher.py

@@ -38,7 +38,7 @@
 
 import string
 
-import numpy
+import numpy as np
 
 from maths.greatest_common_divisor import greatest_common_divisor
 
@@ -49,11 +49,11 @@ class HillCipher:
     # i.e. a total of 36 characters
 
     # take x and return x % len(key_string)
-    modulus = numpy.vectorize(lambda x: x % 36)
+    modulus = np.vectorize(lambda x: x % 36)
 
-    to_int = numpy.vectorize(round)
+    to_int = np.vectorize(round)
 
-    def __init__(self, encrypt_key: numpy.ndarray) -> None:
+    def __init__(self, encrypt_key: np.ndarray) -> None:
         """
         encrypt_key is an NxN numpy array
         """
@@ -63,7 +63,7 @@ def __init__(self, encrypt_key: numpy.ndarray) -> None:
 
     def replace_letters(self, letter: str) -> int:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.replace_letters('T')
         19
         >>> hill_cipher.replace_letters('0')
@@ -73,7 +73,7 @@ def replace_letters(self, letter: str) -> int:
 
     def replace_digits(self, num: int) -> str:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.replace_digits(19)
         'T'
         >>> hill_cipher.replace_digits(26)
@@ -83,10 +83,10 @@ def replace_digits(self, num: int) -> str:
 
     def check_determinant(self) -> None:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.check_determinant()
         """
-        det = round(numpy.linalg.det(self.encrypt_key))
+        det = round(np.linalg.det(self.encrypt_key))
 
         if det < 0:
             det = det % len(self.key_string)
@@ -101,7 +101,7 @@ def check_determinant(self) -> None:
 
     def process_text(self, text: str) -> str:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.process_text('Testing Hill Cipher')
         'TESTINGHILLCIPHERR'
         >>> hill_cipher.process_text('hello')
@@ -117,7 +117,7 @@ def process_text(self, text: str) -> str:
 
     def encrypt(self, text: str) -> str:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.encrypt('testing hill cipher')
         'WHXYJOLM9C6XT085LL'
         >>> hill_cipher.encrypt('hello')
@@ -129,7 +129,7 @@ def encrypt(self, text: str) -> str:
         for i in range(0, len(text) - self.break_key + 1, self.break_key):
             batch = text[i : i + self.break_key]
             vec = [self.replace_letters(char) for char in batch]
-            batch_vec = numpy.array([vec]).T
+            batch_vec = np.array([vec]).T
             batch_encrypted = self.modulus(self.encrypt_key.dot(batch_vec)).T.tolist()[
                 0
             ]
@@ -140,14 +140,14 @@ def encrypt(self, text: str) -> str:
 
         return encrypted
 
-    def make_decrypt_key(self) -> numpy.ndarray:
+    def make_decrypt_key(self) -> np.ndarray:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.make_decrypt_key()
         array([[ 6, 25],
                [ 5, 26]])
         """
-        det = round(numpy.linalg.det(self.encrypt_key))
+        det = round(np.linalg.det(self.encrypt_key))
 
         if det < 0:
             det = det % len(self.key_string)
@@ -158,16 +158,14 @@ def make_decrypt_key(self) -> numpy.ndarray:
                 break
 
         inv_key = (
-            det_inv
-            * numpy.linalg.det(self.encrypt_key)
-            * numpy.linalg.inv(self.encrypt_key)
+            det_inv * np.linalg.det(self.encrypt_key) * np.linalg.inv(self.encrypt_key)
         )
 
         return self.to_int(self.modulus(inv_key))
 
     def decrypt(self, text: str) -> str:
         """
-        >>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
+        >>> hill_cipher = HillCipher(np.array([[2, 5], [1, 6]]))
         >>> hill_cipher.decrypt('WHXYJOLM9C6XT085LL')
         'TESTINGHILLCIPHERR'
         >>> hill_cipher.decrypt('85FF00')
@@ -180,7 +178,7 @@ def decrypt(self, text: str) -> str:
         for i in range(0, len(text) - self.break_key + 1, self.break_key):
             batch = text[i : i + self.break_key]
             vec = [self.replace_letters(char) for char in batch]
-            batch_vec = numpy.array([vec]).T
+            batch_vec = np.array([vec]).T
             batch_decrypted = self.modulus(decrypt_key.dot(batch_vec)).T.tolist()[0]
             decrypted_batch = "".join(
                 self.replace_digits(num) for num in batch_decrypted
@@ -199,7 +197,7 @@ def main() -> None:
         row = [int(x) for x in input().split()]
         hill_matrix.append(row)
 
-    hc = HillCipher(numpy.array(hill_matrix))
+    hc = HillCipher(np.array(hill_matrix))
 
     print("Would you like to encrypt or decrypt some text? (1 or 2)")
     option = input("\n1. Encrypt\n2. Decrypt\n")

data_structures/binary_tree/avl_tree.py

@@ -215,11 +215,11 @@ def del_node(root: MyNode, data: Any) -> MyNode | None:
             return root
         else:
             root.set_left(del_node(left_child, data))
-    else:  # root.get_data() < data
-        if right_child is None:
-            return root
-        else:
-            root.set_right(del_node(right_child, data))
+    # root.get_data() < data
+    elif right_child is None:
+        return root
+    else:
+        root.set_right(del_node(right_child, data))
 
     if get_height(right_child) - get_height(left_child) == 2:
         assert right_child is not None

data_structures/binary_tree/binary_search_tree.py

@@ -185,12 +185,11 @@ def __insert(self, value) -> None:
                         break
                     else:
                         parent_node = parent_node.left
+                elif parent_node.right is None:
+                    parent_node.right = new_node
+                    break
                 else:
-                    if parent_node.right is None:
-                        parent_node.right = new_node
-                        break
-                    else:
-                        parent_node = parent_node.right
+                    parent_node = parent_node.right
             new_node.parent = parent_node
 
     def insert(self, *values) -> Self:

data_structures/binary_tree/binary_search_tree_recursive.py

@@ -74,14 +74,13 @@ def put(self, label: int) -> None:
     def _put(self, node: Node | None, label: int, parent: Node | None = None) -> Node:
         if node is None:
             node = Node(label, parent)
+        elif label < node.label:
+            node.left = self._put(node.left, label, node)
+        elif label > node.label:
+            node.right = self._put(node.right, label, node)
         else:
-            if label < node.label:
-                node.left = self._put(node.left, label, node)
-            elif label > node.label:
-                node.right = self._put(node.right, label, node)
-            else:
-                msg = f"Node with label {label} already exists"
-                raise ValueError(msg)
+            msg = f"Node with label {label} already exists"
+            raise ValueError(msg)
 
         return node
 
@@ -106,11 +105,10 @@ def _search(self, node: Node | None, label: int) -> Node:
         if node is None:
             msg = f"Node with label {label} does not exist"
             raise ValueError(msg)
-        else:
-            if label < node.label:
-                node = self._search(node.left, label)
-            elif label > node.label:
-                node = self._search(node.right, label)
+        elif label < node.label:
+            node = self._search(node.left, label)
+        elif label > node.label:
+            node = self._search(node.right, label)
 
         return node
 

data_structures/binary_tree/binary_tree_traversals.py

@@ -97,6 +97,8 @@ def level_order(root: Node | None) -> Generator[int, None, None]:
     """
     Returns a list of nodes value from a whole binary tree in Level Order Traverse.
     Level Order traverse: Visit nodes of the tree level-by-level.
+    >>> list(level_order(make_tree()))
+    [1, 2, 3, 4, 5]
     """
 
     if root is None:
@@ -120,6 +122,10 @@ def get_nodes_from_left_to_right(
     """
     Returns a list of nodes value from a particular level:
     Left to right direction of the binary tree.
+    >>> list(get_nodes_from_left_to_right(make_tree(), 1))
+    [1]
+    >>> list(get_nodes_from_left_to_right(make_tree(), 2))
+    [2, 3]
     """
 
     def populate_output(root: Node | None, level: int) -> Generator[int, None, None]:
@@ -140,10 +146,14 @@ def get_nodes_from_right_to_left(
     """
     Returns a list of nodes value from a particular level:
     Right to left direction of the binary tree.
+    >>> list(get_nodes_from_right_to_left(make_tree(), 1))
+    [1]
+    >>> list(get_nodes_from_right_to_left(make_tree(), 2))
+    [3, 2]
     """
 
     def populate_output(root: Node | None, level: int) -> Generator[int, None, None]:
-        if root is None:
+        if not root:
             return
         if level == 1:
             yield root.data
@@ -158,6 +168,8 @@ def zigzag(root: Node | None) -> Generator[int, None, None]:
     """
     ZigZag traverse:
     Returns a list of nodes value from left to right and right to left, alternatively.
+    >>> list(zigzag(make_tree()))
+    [1, 3, 2, 4, 5]
     """
     if root is None:
         return