



'''simple docstring'''

def      __lowerCamelCase     (      lowerCAmelCase_ = "The quick brown fox jumps over the lazy dog"						,			)			->      bool:
		_a     :      Dict        =							set()

		# Replace all the whitespace in our sentence
		_a     :      Union[str, Any]        =							input_str.replace(' '						,			''  )
		for alpha in input_str:
				if "a" <= alpha.lower() <= "z":
						frequency.add(alpha.lower()  )
		return len(lowerCAmelCase_  ) == 26



def      __lowerCamelCase     (      lowerCAmelCase_ = "The quick brown fox jumps over the lazy dog"						,			)			->      bool:
		_a     :      str        =							[False] * 26
		for char in input_str:
				if char.islower():
						_a     :      List[str]        =							True
				elif char.isupper():
						_a     :      str        =							True
		return all(lowerCAmelCase_  )



def      __lowerCamelCase     (      lowerCAmelCase_ = "The quick brown fox jumps over the lazy dog"						,			)			->      bool:
		return len({char for char in input_str.lower() if char.isalpha()}  ) == 26



def      __lowerCamelCase     (      )			->      None:
		from timeit import timeit

		_a     :      List[Any]        =							'from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'
		print(timeit('is_pangram()'						,			setup=lowerCAmelCase_  )  )
		print(timeit('is_pangram_faster()'						,			setup=lowerCAmelCase_  )  )
		print(timeit('is_pangram_fastest()'						,			setup=lowerCAmelCase_  )  )
		# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
		# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							benchmark()









'''simple docstring'''

from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_  )			->      np.ndarray:
		_a     :      Union[str, Any]        =							cva.getAffineTransform(lowerCAmelCase_						,			lowerCAmelCase_  )
		return cva.warpAffine(lowerCAmelCase_						,			lowerCAmelCase_						,			(rows, cols)  )


if __name__ == "__main__":
							# read original image
							__lowerCAmelCase									=   cva.imread(
							    str(Path(__file__).resolve().parent.parent / '''image_data''' / '''lena.jpg''')
							)
							# turn image in gray scale value
							__lowerCAmelCase									=   cva.cvtColor(image, cva.COLOR_BGR2GRAY)
							# get image shape
							__lowerCAmelCase			,					__lowerCAmelCase									=   gray_img.shape

							# set different points to rotate image
							__lowerCAmelCase									=   np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
							__lowerCAmelCase									=   np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
							__lowerCAmelCase									=   np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
							__lowerCAmelCase									=   np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

							# add all rotated images in a list
							__lowerCAmelCase									=   [
							    gray_img,
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							]

							# plot different image rotations
							__lowerCAmelCase									=   plt.figure(1)
							__lowerCAmelCase									=   ['''Original''', '''Rotation 1''', '''Rotation 2''', '''Rotation 3''']
							for i, image in enumerate(images):
														plt.subplot(2, 2, i + 1), plt.imshow(image, '''gray''')
														plt.title(titles[i])
														plt.axis('''off''')
														plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
							plt.show()




