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>
This commit is contained in:
Caeden Perelli-Harris 2023-05-14 22:03:13 +01:00 committed by GitHub
parent 793e564e1d
commit 1faf10b5c2
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9 changed files with 22 additions and 20 deletions

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@ -294,7 +294,6 @@
* [Mergesort](divide_and_conquer/mergesort.py)
* [Peak](divide_and_conquer/peak.py)
* [Power](divide_and_conquer/power.py)
* [Strassen Matrix Multiplication](divide_and_conquer/strassen_matrix_multiplication.py)
## Dynamic Programming
* [Abbreviation](dynamic_programming/abbreviation.py)
@ -632,6 +631,7 @@
* [Radians](maths/radians.py)
* [Radix2 Fft](maths/radix2_fft.py)
* [Relu](maths/relu.py)
* [Remove Digit](maths/remove_digit.py)
* [Runge Kutta](maths/runge_kutta.py)
* [Segmented Sieve](maths/segmented_sieve.py)
* Series
@ -694,6 +694,8 @@
## Neural Network
* [2 Hidden Layers Neural Network](neural_network/2_hidden_layers_neural_network.py)
* Activation Functions
* [Exponential Linear Unit](neural_network/activation_functions/exponential_linear_unit.py)
* [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py)
* [Convolution Neural Network](neural_network/convolution_neural_network.py)
* [Input Data](neural_network/input_data.py)
@ -1080,6 +1082,7 @@
## Sorts
* [Bead Sort](sorts/bead_sort.py)
* [Binary Insertion Sort](sorts/binary_insertion_sort.py)
* [Bitonic Sort](sorts/bitonic_sort.py)
* [Bogo Sort](sorts/bogo_sort.py)
* [Bubble Sort](sorts/bubble_sort.py)
@ -1170,6 +1173,7 @@
* [Reverse Words](strings/reverse_words.py)
* [Snake Case To Camel Pascal Case](strings/snake_case_to_camel_pascal_case.py)
* [Split](strings/split.py)
* [String Switch Case](strings/string_switch_case.py)
* [Text Justification](strings/text_justification.py)
* [Top K Frequent Words](strings/top_k_frequent_words.py)
* [Upper](strings/upper.py)

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@ -96,7 +96,7 @@ def add_si_prefix(value: float) -> str:
for name_prefix, value_prefix in prefixes.items():
numerical_part = value / (10**value_prefix)
if numerical_part > 1:
return f"{str(numerical_part)} {name_prefix}"
return f"{numerical_part!s} {name_prefix}"
return str(value)
@ -111,7 +111,7 @@ def add_binary_prefix(value: float) -> str:
for prefix in BinaryUnit:
numerical_part = value / (2**prefix.value)
if numerical_part > 1:
return f"{str(numerical_part)} {prefix.name}"
return f"{numerical_part!s} {prefix.name}"
return str(value)

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@ -121,8 +121,8 @@ def rgb_to_hsv(red: int, green: int, blue: int) -> list[float]:
float_red = red / 255
float_green = green / 255
float_blue = blue / 255
value = max(max(float_red, float_green), float_blue)
chroma = value - min(min(float_red, float_green), float_blue)
value = max(float_red, float_green, float_blue)
chroma = value - min(float_red, float_green, float_blue)
saturation = 0 if value == 0 else chroma / value
if chroma == 0:

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@ -96,7 +96,7 @@ def test_nearest_neighbour(
def test_local_binary_pattern():
file_path: str = "digital_image_processing/image_data/lena.jpg"
file_path = "digital_image_processing/image_data/lena.jpg"
# Reading the image and converting it to grayscale.
image = imread(file_path, 0)

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@ -122,7 +122,7 @@ def strassen(matrix1: list, matrix2: list) -> list:
if dimension1[0] == dimension1[1] and dimension2[0] == dimension2[1]:
return [matrix1, matrix2]
maximum = max(max(dimension1), max(dimension2))
maximum = max(dimension1, dimension2)
maxim = int(math.pow(2, math.ceil(math.log2(maximum))))
new_matrix1 = matrix1
new_matrix2 = matrix2

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@ -24,7 +24,7 @@ class Fibonacci:
return self.sequence[:index]
def main():
def main() -> None:
print(
"Fibonacci Series Using Dynamic Programming\n",
"Enter the index of the Fibonacci number you want to calculate ",

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@ -1,12 +1,12 @@
from __future__ import annotations
import typing
from collections.abc import Iterable
from typing import Union
import numpy as np
Vector = Union[Iterable[float], Iterable[int], np.ndarray]
VectorOut = Union[np.float64, int, float]
Vector = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
VectorOut = typing.Union[np.float64, int, float] # noqa: UP007
def euclidean_distance(vector_1: Vector, vector_2: Vector) -> VectorOut:

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@ -147,6 +147,6 @@ if __name__ == "__main__":
# Print results
print()
print("Results: ")
print(f"Horizontal Distance: {str(horizontal_distance(init_vel, angle))} [m]")
print(f"Maximum Height: {str(max_height(init_vel, angle))} [m]")
print(f"Total Time: {str(total_time(init_vel, angle))} [s]")
print(f"Horizontal Distance: {horizontal_distance(init_vel, angle)!s} [m]")
print(f"Maximum Height: {max_height(init_vel, angle)!s} [m]")
print(f"Total Time: {total_time(init_vel, angle)!s} [s]")

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@ -13,11 +13,9 @@ class TreeNode:
self.left = None
def build_tree():
def build_tree() -> TreeNode:
print("\n********Press N to stop entering at any point of time********\n")
check = input("Enter the value of the root node: ").strip().lower() or "n"
if check == "n":
return None
check = input("Enter the value of the root node: ").strip().lower()
q: queue.Queue = queue.Queue()
tree_node = TreeNode(int(check))
q.put(tree_node)
@ -37,7 +35,7 @@ def build_tree():
right_node = TreeNode(int(check))
node_found.right = right_node
q.put(right_node)
return None
raise
def pre_order(node: TreeNode) -> None:
@ -272,7 +270,7 @@ if __name__ == "__main__":
doctest.testmod()
print(prompt("Binary Tree Traversals"))
node = build_tree()
node: TreeNode = build_tree()
print(prompt("Pre Order Traversal"))
pre_order(node)
print(prompt() + "\n")