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Correct ruff failures (#8732)
* fix: Correct ruff problems * updating DIRECTORY.md * fix: Fix pre-commit errors * updating DIRECTORY.md --------- Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
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@ -294,7 +294,6 @@
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* [Mergesort](divide_and_conquer/mergesort.py)
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* [Mergesort](divide_and_conquer/mergesort.py)
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* [Peak](divide_and_conquer/peak.py)
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* [Peak](divide_and_conquer/peak.py)
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* [Power](divide_and_conquer/power.py)
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* [Power](divide_and_conquer/power.py)
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* [Strassen Matrix Multiplication](divide_and_conquer/strassen_matrix_multiplication.py)
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## Dynamic Programming
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## Dynamic Programming
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* [Abbreviation](dynamic_programming/abbreviation.py)
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* [Abbreviation](dynamic_programming/abbreviation.py)
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@ -632,6 +631,7 @@
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* [Radians](maths/radians.py)
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* [Radians](maths/radians.py)
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* [Radix2 Fft](maths/radix2_fft.py)
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* [Radix2 Fft](maths/radix2_fft.py)
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* [Relu](maths/relu.py)
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* [Relu](maths/relu.py)
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* [Remove Digit](maths/remove_digit.py)
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* [Runge Kutta](maths/runge_kutta.py)
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* [Runge Kutta](maths/runge_kutta.py)
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* [Segmented Sieve](maths/segmented_sieve.py)
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* [Segmented Sieve](maths/segmented_sieve.py)
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* Series
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* Series
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@ -694,6 +694,8 @@
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## Neural Network
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## Neural Network
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* [2 Hidden Layers Neural Network](neural_network/2_hidden_layers_neural_network.py)
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* [2 Hidden Layers Neural Network](neural_network/2_hidden_layers_neural_network.py)
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* Activation Functions
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* [Exponential Linear Unit](neural_network/activation_functions/exponential_linear_unit.py)
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* [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py)
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* [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py)
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* [Convolution Neural Network](neural_network/convolution_neural_network.py)
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* [Convolution Neural Network](neural_network/convolution_neural_network.py)
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* [Input Data](neural_network/input_data.py)
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* [Input Data](neural_network/input_data.py)
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@ -1080,6 +1082,7 @@
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## Sorts
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## Sorts
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* [Bead Sort](sorts/bead_sort.py)
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* [Bead Sort](sorts/bead_sort.py)
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* [Binary Insertion Sort](sorts/binary_insertion_sort.py)
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* [Bitonic Sort](sorts/bitonic_sort.py)
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* [Bitonic Sort](sorts/bitonic_sort.py)
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* [Bogo Sort](sorts/bogo_sort.py)
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* [Bogo Sort](sorts/bogo_sort.py)
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* [Bubble Sort](sorts/bubble_sort.py)
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* [Bubble Sort](sorts/bubble_sort.py)
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@ -1170,6 +1173,7 @@
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* [Reverse Words](strings/reverse_words.py)
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* [Reverse Words](strings/reverse_words.py)
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* [Snake Case To Camel Pascal Case](strings/snake_case_to_camel_pascal_case.py)
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* [Snake Case To Camel Pascal Case](strings/snake_case_to_camel_pascal_case.py)
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* [Split](strings/split.py)
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* [Split](strings/split.py)
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* [String Switch Case](strings/string_switch_case.py)
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* [Text Justification](strings/text_justification.py)
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* [Text Justification](strings/text_justification.py)
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* [Top K Frequent Words](strings/top_k_frequent_words.py)
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* [Top K Frequent Words](strings/top_k_frequent_words.py)
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* [Upper](strings/upper.py)
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* [Upper](strings/upper.py)
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@ -96,7 +96,7 @@ def add_si_prefix(value: float) -> str:
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for name_prefix, value_prefix in prefixes.items():
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for name_prefix, value_prefix in prefixes.items():
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numerical_part = value / (10**value_prefix)
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numerical_part = value / (10**value_prefix)
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if numerical_part > 1:
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if numerical_part > 1:
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return f"{str(numerical_part)} {name_prefix}"
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return f"{numerical_part!s} {name_prefix}"
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return str(value)
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return str(value)
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@ -111,7 +111,7 @@ def add_binary_prefix(value: float) -> str:
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for prefix in BinaryUnit:
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for prefix in BinaryUnit:
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numerical_part = value / (2**prefix.value)
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numerical_part = value / (2**prefix.value)
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if numerical_part > 1:
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if numerical_part > 1:
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return f"{str(numerical_part)} {prefix.name}"
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return f"{numerical_part!s} {prefix.name}"
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return str(value)
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return str(value)
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@ -121,8 +121,8 @@ def rgb_to_hsv(red: int, green: int, blue: int) -> list[float]:
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float_red = red / 255
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float_red = red / 255
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float_green = green / 255
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float_green = green / 255
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float_blue = blue / 255
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float_blue = blue / 255
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value = max(max(float_red, float_green), float_blue)
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value = max(float_red, float_green, float_blue)
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chroma = value - min(min(float_red, float_green), float_blue)
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chroma = value - min(float_red, float_green, float_blue)
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saturation = 0 if value == 0 else chroma / value
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saturation = 0 if value == 0 else chroma / value
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if chroma == 0:
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if chroma == 0:
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@ -96,7 +96,7 @@ def test_nearest_neighbour(
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def test_local_binary_pattern():
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def test_local_binary_pattern():
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file_path: str = "digital_image_processing/image_data/lena.jpg"
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file_path = "digital_image_processing/image_data/lena.jpg"
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# Reading the image and converting it to grayscale.
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# Reading the image and converting it to grayscale.
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image = imread(file_path, 0)
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image = imread(file_path, 0)
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@ -122,7 +122,7 @@ def strassen(matrix1: list, matrix2: list) -> list:
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if dimension1[0] == dimension1[1] and dimension2[0] == dimension2[1]:
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if dimension1[0] == dimension1[1] and dimension2[0] == dimension2[1]:
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return [matrix1, matrix2]
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return [matrix1, matrix2]
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maximum = max(max(dimension1), max(dimension2))
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maximum = max(dimension1, dimension2)
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maxim = int(math.pow(2, math.ceil(math.log2(maximum))))
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maxim = int(math.pow(2, math.ceil(math.log2(maximum))))
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new_matrix1 = matrix1
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new_matrix1 = matrix1
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new_matrix2 = matrix2
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new_matrix2 = matrix2
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@ -24,7 +24,7 @@ class Fibonacci:
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return self.sequence[:index]
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return self.sequence[:index]
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def main():
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def main() -> None:
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print(
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print(
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"Fibonacci Series Using Dynamic Programming\n",
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"Fibonacci Series Using Dynamic Programming\n",
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"Enter the index of the Fibonacci number you want to calculate ",
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"Enter the index of the Fibonacci number you want to calculate ",
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from __future__ import annotations
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from __future__ import annotations
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import typing
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from collections.abc import Iterable
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from collections.abc import Iterable
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from typing import Union
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import numpy as np
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import numpy as np
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Vector = Union[Iterable[float], Iterable[int], np.ndarray]
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Vector = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
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VectorOut = Union[np.float64, int, float]
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VectorOut = typing.Union[np.float64, int, float] # noqa: UP007
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def euclidean_distance(vector_1: Vector, vector_2: Vector) -> VectorOut:
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def euclidean_distance(vector_1: Vector, vector_2: Vector) -> VectorOut:
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# Print results
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# Print results
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print()
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print()
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print("Results: ")
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print("Results: ")
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print(f"Horizontal Distance: {str(horizontal_distance(init_vel, angle))} [m]")
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print(f"Horizontal Distance: {horizontal_distance(init_vel, angle)!s} [m]")
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print(f"Maximum Height: {str(max_height(init_vel, angle))} [m]")
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print(f"Maximum Height: {max_height(init_vel, angle)!s} [m]")
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print(f"Total Time: {str(total_time(init_vel, angle))} [s]")
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print(f"Total Time: {total_time(init_vel, angle)!s} [s]")
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self.left = None
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self.left = None
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def build_tree():
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def build_tree() -> TreeNode:
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print("\n********Press N to stop entering at any point of time********\n")
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print("\n********Press N to stop entering at any point of time********\n")
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check = input("Enter the value of the root node: ").strip().lower() or "n"
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check = input("Enter the value of the root node: ").strip().lower()
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if check == "n":
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return None
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q: queue.Queue = queue.Queue()
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q: queue.Queue = queue.Queue()
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tree_node = TreeNode(int(check))
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tree_node = TreeNode(int(check))
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q.put(tree_node)
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q.put(tree_node)
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right_node = TreeNode(int(check))
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right_node = TreeNode(int(check))
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node_found.right = right_node
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node_found.right = right_node
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q.put(right_node)
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q.put(right_node)
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return None
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raise
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def pre_order(node: TreeNode) -> None:
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def pre_order(node: TreeNode) -> None:
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doctest.testmod()
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doctest.testmod()
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print(prompt("Binary Tree Traversals"))
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print(prompt("Binary Tree Traversals"))
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node = build_tree()
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node: TreeNode = build_tree()
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print(prompt("Pre Order Traversal"))
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print(prompt("Pre Order Traversal"))
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pre_order(node)
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pre_order(node)
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print(prompt() + "\n")
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print(prompt() + "\n")
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