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Enable ruff ICN001 rule (#11329)

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* Enable ruff ICN001 rule

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This commit is contained in:
Maxim Smolskiy
2024-03-28 21:03:23 +03:00
committed by GitHub
parent efb7463cde
commit f2246ce7fd
8 changed files with 121 additions and 128 deletions
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34
fractals/koch_snowflake.py
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@@ -22,25 +22,25 @@ Requirements (pip):
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
import matplotlib.pyplot as plt
import numpy as np
# initial triangle of Koch snowflake
VECTOR_1 = numpy.array([0, 0])
VECTOR_2 = numpy.array([0.5, 0.8660254])
VECTOR_3 = numpy.array([1, 0])
VECTOR_1 = np.array([0, 0])
VECTOR_2 = np.array([0.5, 0.8660254])
VECTOR_3 = np.array([1, 0])
INITIAL_VECTORS = [VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]
# uncomment for simple Koch curve instead of Koch snowflake
# INITIAL_VECTORS = [VECTOR_1, VECTOR_3]
def iterate(initial_vectors: list[numpy.ndarray], steps: int) -> list[numpy.ndarray]:
def iterate(initial_vectors: list[np.ndarray], steps: int) -> list[np.ndarray]:
"""
Go through the number of iterations determined by the argument "steps".
Be careful with high values (above 5) since the time to calculate increases
exponentially.
>>> iterate([numpy.array([0, 0]), numpy.array([1, 0])], 1)
>>> iterate([np.array([0, 0]), np.array([1, 0])], 1)
[array([0, 0]), array([0.33333333, 0. ]), array([0.5 , \
0.28867513]), array([0.66666667, 0. ]), array([1, 0])]
"""
@@ -50,13 +50,13 @@ def iterate(initial_vectors: list[numpy.ndarray], steps: int) -> list[numpy.ndar
return vectors
def iteration_step(vectors: list[numpy.ndarray]) -> list[numpy.ndarray]:
def iteration_step(vectors: list[np.ndarray]) -> list[np.ndarray]:
"""
Loops through each pair of adjacent vectors. Each line between two adjacent
vectors is divided into 4 segments by adding 3 additional vectors in-between
the original two vectors. The vector in the middle is constructed through a
60 degree rotation so it is bent outwards.
>>> iteration_step([numpy.array([0, 0]), numpy.array([1, 0])])
>>> iteration_step([np.array([0, 0]), np.array([1, 0])])
[array([0, 0]), array([0.33333333, 0. ]), array([0.5 , \
0.28867513]), array([0.66666667, 0. ]), array([1, 0])]
"""
@@ -74,22 +74,22 @@ def iteration_step(vectors: list[numpy.ndarray]) -> list[numpy.ndarray]:
return new_vectors
def rotate(vector: numpy.ndarray, angle_in_degrees: float) -> numpy.ndarray:
def rotate(vector: np.ndarray, angle_in_degrees: float) -> np.ndarray:
"""
Standard rotation of a 2D vector with a rotation matrix
(see https://en.wikipedia.org/wiki/Rotation_matrix )
>>> rotate(numpy.array([1, 0]), 60)
>>> rotate(np.array([1, 0]), 60)
array([0.5 , 0.8660254])
>>> rotate(numpy.array([1, 0]), 90)
>>> rotate(np.array([1, 0]), 90)
array([6.123234e-17, 1.000000e+00])
"""
theta = numpy.radians(angle_in_degrees)
c, s = numpy.cos(theta), numpy.sin(theta)
rotation_matrix = numpy.array(((c, -s), (s, c)))
return numpy.dot(rotation_matrix, vector)
theta = np.radians(angle_in_degrees)
c, s = np.cos(theta), np.sin(theta)
rotation_matrix = np.array(((c, -s), (s, c)))
return np.dot(rotation_matrix, vector)
def plot(vectors: list[numpy.ndarray]) -> None:
def plot(vectors: list[np.ndarray]) -> None:
"""
Utility function to plot the vectors using matplotlib.pyplot
No doctest was implemented since this function does not have a return value