Cyai patch 3

arithmetic_analysis/in_static_equilibrium.py

@@ -19,8 +19,11 @@ def polar_force(
     True
     >>> math.isclose(force[1], 7.0710678118654755)
     True
-    >>> polar_force(10, 3.14, radian_mode=True)
-    [-9.999987317275396, 0.01592652916486828]
+    >>> force = polar_force(10, 3.14, radian_mode=True)
+    >>> math.isclose(force[0], -9.999987317275396)
+    True
+    >>> math.isclose(force[1], 0.01592652916486828)
+    True
     """
     if radian_mode:
         return [magnitude * cos(angle), magnitude * sin(angle)]

ciphers/elgamal_key_generator.py

@@ -38,8 +38,8 @@ def generate_key(key_size: int) -> tuple[tuple[int, int, int, int], tuple[int, i
 
 
 def make_key_files(name: str, keySize: int) -> None:
-    if os.path.exists("%s_pubkey.txt" % name) or os.path.exists(
-        "%s_privkey.txt" % name
+    if os.path.exists(f"{name}_pubkey.txt") or os.path.exists(
+        f"{name}_privkey.txt"
     ):
         print("\nWARNING:")
         print(
@@ -50,14 +50,14 @@ def make_key_files(name: str, keySize: int) -> None:
         sys.exit()
 
     publicKey, privateKey = generate_key(keySize)
-    print("\nWriting public key to file %s_pubkey.txt..." % name)
-    with open("%s_pubkey.txt" % name, "w") as fo:
+    print(f"\nWriting public key to file {name}_pubkey.txt...")
+    with open(f"{name}_pubkey.txt", "w") as fo:
         fo.write(
             "%d,%d,%d,%d" % (publicKey[0], publicKey[1], publicKey[2], publicKey[3])
         )
 
-    print("Writing private key to file %s_privkey.txt..." % name)
-    with open("%s_privkey.txt" % name, "w") as fo:
+    print(f"Writing private key to file {name}_privkey.txt...")
+    with open(f"{name}_privkey.txt", "w") as fo:
         fo.write("%d,%d" % (privateKey[0], privateKey[1]))
 
 

ciphers/rsa_cipher.py

@@ -129,15 +129,15 @@ def main() -> None:
 
         message = input("\nEnter message: ")
         pubkey_filename = "rsa_pubkey.txt"
-        print("Encrypting and writing to %s..." % (filename))
+        print(f"Encrypting and writing to {filename}...")
         encryptedText = encrypt_and_write_to_file(filename, pubkey_filename, message)
 
         print("\nEncrypted text:")
         print(encryptedText)
 
     elif mode == "decrypt":
         privkey_filename = "rsa_privkey.txt"
-        print("Reading from %s and decrypting..." % (filename))
+        print(f"Reading from {filename} and decrypting...")
         decrypted_text = read_from_file_and_decrypt(filename, privkey_filename)
         print("writing decryption to rsa_decryption.txt...")
         with open("rsa_decryption.txt", "w") as dec:

ciphers/rsa_key_generator.py

@@ -34,8 +34,8 @@ def generateKey(keySize: int) -> tuple[tuple[int, int], tuple[int, int]]:
 
 
 def makeKeyFiles(name: str, keySize: int) -> None:
-    if os.path.exists("%s_pubkey.txt" % (name)) or os.path.exists(
-        "%s_privkey.txt" % (name)
+    if os.path.exists(f"{name}_pubkey.txt") or os.path.exists(
+        f"{name}_privkey.txt"
     ):
         print("\nWARNING:")
         print(
@@ -46,12 +46,12 @@ def makeKeyFiles(name: str, keySize: int) -> None:
         sys.exit()
 
     publicKey, privateKey = generateKey(keySize)
-    print("\nWriting public key to file %s_pubkey.txt..." % name)
-    with open("%s_pubkey.txt" % name, "w") as out_file:
+    print(f"\nWriting public key to file {name}_pubkey.txt...")
+    with open(f"{name}_pubkey.txt", "w") as out_file:
         out_file.write(f"{keySize},{publicKey[0]},{publicKey[1]}")
 
-    print("Writing private key to file %s_privkey.txt..." % name)
-    with open("%s_privkey.txt" % name, "w") as out_file:
+    print(f"Writing private key to file {name}_privkey.txt...")
+    with open(f"{name}_privkey.txt", "w") as out_file:
         out_file.write(f"{keySize},{privateKey[0]},{privateKey[1]}")
 
 

ciphers/transposition_cipher.py

@@ -10,7 +10,7 @@
 
 def main() -> None:
     message = input("Enter message: ")
-    key = int(input("Enter key [2-%s]: " % (len(message) - 1)))
+    key = int(input(f"Enter key [2-{len(message) - 1}]: "))
     mode = input("Encryption/Decryption [e/d]: ")
 
     if mode.lower().startswith("e"):
@@ -19,7 +19,7 @@ def main() -> None:
         text = decryptMessage(key, message)
 
     # Append pipe symbol (vertical bar) to identify spaces at the end.
-    print("Output:\n%s" % (text + "|"))
+    print(f"Output:\n{text + '|'}")
 
 
 def encryptMessage(key: int, message: str) -> str:

ciphers/transposition_cipher_encrypt_decrypt_file.py

@@ -12,10 +12,10 @@ def main() -> None:
     mode = input("Encrypt/Decrypt [e/d]: ")
 
     if not os.path.exists(inputFile):
-        print("File %s does not exist. Quitting..." % inputFile)
+        print(f"File {inputFile} does not exist. Quitting...")
         sys.exit()
     if os.path.exists(outputFile):
-        print("Overwrite %s? [y/n]" % outputFile)
+        print(f"Overwrite {outputFile}? [y/n]")
         response = input("> ")
         if not response.lower().startswith("y"):
             sys.exit()

ciphers/vigenere_cipher.py

@@ -13,7 +13,7 @@ def main() -> None:
         mode = "decrypt"
         translated = decryptMessage(key, message)
 
-    print("\n%sed message:" % mode.title())
+    print(f"\n{mode.title()}ed message:")
     print(translated)
 
 

data_structures/binary_tree/binary_search_tree.py

@@ -15,7 +15,7 @@ def __repr__(self):
 
         if self.left is None and self.right is None:
             return str(self.value)
-        return pformat({"%s" % (self.value): (self.left, self.right)}, indent=1)
+        return pformat({f"{self.value}": (self.left, self.right)}, indent=1)
 
 
 class BinarySearchTree:

hashes/chaos_machine.py

@@ -96,7 +96,7 @@ def reset():
 
     # Pulling Data (Output)
     while inp in ("e", "E"):
-        print("%s" % format(pull(), "#04x"))
+        print(f"{format(pull(), '#04x')}")
         print(buffer_space)
         print(params_space)
         inp = input("(e)exit? ").strip()

machine_learning/gradient_boosting_regressor.py

@@ -47,9 +47,9 @@ def main():
     y_pred = model.predict(X_test)
 
     # The mean squared error
-    print("Mean squared error: %.2f" % mean_squared_error(y_test, y_pred))
+    print(f"Mean squared error: {mean_squared_error(y_test, y_pred):.2f}")
     # Explained variance score: 1 is perfect prediction
-    print("Test Variance score: %.2f" % r2_score(y_test, y_pred))
+    print(f"Test Variance score: {r2_score(y_test, y_pred):.2f}")
 
     # So let's run the model against the test data
     fig, ax = plt.subplots()

machine_learning/k_means_clust.py

@@ -164,9 +164,7 @@ def kmeans(
             num_changed = np.sum(prev_cluster_assignment != cluster_assignment)
             if verbose:
                 print(
-                    "    {:5d} elements changed their cluster assignment.".format(
-                        num_changed
-                    )
+                    f"    {num_changed:5d} elements changed their cluster assignment."
                 )
 
         # Record heterogeneity convergence metric

machine_learning/linear_regression.py

@@ -99,7 +99,7 @@ def main():
     len_result = theta.shape[1]
     print("Resultant Feature vector : ")
     for i in range(0, len_result):
-        print("%.5f" % (theta[0, i]))
+        print(f"{theta[0, i]:.5f}")
 
 
 if __name__ == "__main__":

matrix/sherman_morrison.py

@@ -256,7 +256,7 @@ def test1():
         v[0, 0], v[1, 0], v[2, 0] = 4, -2, 5
         print(f"u is {u}")
         print(f"v is {v}")
-        print("uv^T is %s" % (u * v.transpose()))
+        print(f"uv^T is {u * v.transpose()}")
         # Sherman Morrison
         print(f"(a + uv^T)^(-1) is {ainv.ShermanMorrison(u, v)}")
 

neural_network/convolution_neural_network.py

@@ -71,7 +71,7 @@ def save_model(self, save_path):
         with open(save_path, "wb") as f:
             pickle.dump(model_dic, f)
 
-        print("Model saved： %s" % save_path)
+        print(f"Model saved： {save_path}")
 
     @classmethod
     def ReadModel(cls, model_path):
@@ -303,7 +303,7 @@ def draw_error():
             plt.show()
 
         print("------------------Training Complished---------------------")
-        print((" - - Training epoch: ", rp, "     - - Mse: %.6f" % mse))
+        print((" - - Training epoch: ", rp, f"     - - Mse: {mse:.6f}"))
         if draw_e:
             draw_error()
         return mse

other/scoring_algorithm.py

@@ -69,7 +69,7 @@ def procentual_proximity(
 
         # weight not 0 or 1
         else:
-            raise ValueError("Invalid weight of %f provided" % (weight))
+            raise ValueError(f"Invalid weight of {weight:f} provided")
 
         score_lists.append(score)
 

quantum/ripple_adder_classic.py

@@ -3,7 +3,7 @@
 # https://en.wikipedia.org/wiki/Controlled_NOT_gate
 
 from qiskit import Aer, QuantumCircuit, execute
-from qiskit.providers import BaseBackend
+from qiskit.providers import Backend
 
 
 def store_two_classics(val1: int, val2: int) -> tuple[QuantumCircuit, str, str]:
@@ -62,7 +62,7 @@ def full_adder(
 def ripple_adder(
     val1: int,
     val2: int,
-    backend: BaseBackend = Aer.get_backend("qasm_simulator"),  # noqa: B008
+    backend: Backend = Aer.get_backend("qasm_simulator"),  # noqa: B008
 ) -> int:
     """
     Quantum Equivalent of a Ripple Adder Circuit

scheduling/shortest_job_first.py

@@ -111,7 +111,7 @@ def calculate_average_times(
     for i in range(no_of_processes):
         total_waiting_time = total_waiting_time + waiting_time[i]
         total_turn_around_time = total_turn_around_time + turn_around_time[i]
-    print("Average waiting time = %.5f" % (total_waiting_time / no_of_processes))
+    print(f"Average waiting time = {total_waiting_time / no_of_processes:.5f}")
     print("Average turn around time =", total_turn_around_time / no_of_processes)
 
 

searches/binary_tree_traversal.py

@@ -25,14 +25,14 @@ def build_tree():
     q.put(tree_node)
     while not q.empty():
         node_found = q.get()
-        msg = "Enter the left node of %s: " % node_found.data
+        msg = f"Enter the left node of {node_found.data}: "
         check = input(msg).strip().lower() or "n"
         if check == "n":
             return tree_node
         left_node = TreeNode(int(check))
         node_found.left = left_node
         q.put(left_node)
-        msg = "Enter the right node of %s: " % node_found.data
+        msg = f"Enter the right node of {node_found.data}: "
         check = input(msg).strip().lower() or "n"
         if check == "n":
             return tree_node

strings/hamming_distance.py

@@ -0,0 +1,41 @@
+def hamming_distance(string1: str, string2: str) -> int:
+    """Calculate the Hamming distance between two equal length strings
+    In information theory, the Hamming distance between two strings of equal
+    length is the number of positions at which the corresponding symbols are
+    different. https://en.wikipedia.org/wiki/Hamming_distance
+
+    Args:
+        string1 (str): Sequence 1
+        string2 (str): Sequence 2
+
+    Returns:
+        int: Hamming distance
+
+    >>> hamming_distance("python", "python")
+    0
+    >>> hamming_distance("karolin", "kathrin")
+    3
+    >>> hamming_distance("00000", "11111")
+    5
+    >>> hamming_distance("karolin", "kath")
+    Traceback (most recent call last):
+      ...
+    ValueError: String lengths must match!
+    """
+    if len(string1) != len(string2):
+        raise ValueError("String lengths must match!")
+
+    count = 0
+
+    for char1, char2 in zip(string1, string2):
+        if char1 != char2:
+            count += 1
+
+    return count
+
+
+if __name__ == "__main__":
+
+    import doctest
+
+    doctest.testmod()

strings/min_cost_string_conversion.py

@@ -31,28 +31,28 @@ def compute_transform_tables(
 
     for i in range(1, len_source_seq + 1):
         costs[i][0] = i * delete_cost
-        ops[i][0] = "D%c" % source_seq[i - 1]
+        ops[i][0] = f"D{source_seq[i - 1]:c}"
 
     for i in range(1, len_destination_seq + 1):
         costs[0][i] = i * insert_cost
-        ops[0][i] = "I%c" % destination_seq[i - 1]
+        ops[0][i] = f"I{destination_seq[i - 1]:c}"
 
     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] = "C%c" % source_seq[i - 1]
+                ops[i][j] = f"C{source_seq[i - 1]:c}"
             else:
                 costs[i][j] = costs[i - 1][j - 1] + replace_cost
-                ops[i][j] = "R%c" % source_seq[i - 1] + str(destination_seq[j - 1])
+                ops[i][j] = f"R{source_seq[i - 1]:c}" + 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] = "D%c" % source_seq[i - 1]
+                ops[i][j] = f"D{source_seq[i - 1]:c}"
 
             if costs[i][j - 1] + insert_cost < costs[i][j]:
                 costs[i][j] = costs[i][j - 1] + insert_cost
-                ops[i][j] = "I%c" % destination_seq[j - 1]
+                ops[i][j] = f"I{destination_seq[j - 1]:c}"
 
     return costs, ops