




"""simple docstring"""

import math
import os

import cva
import numpy as np

__A 		=			255.0



def   UpperCamelCase__     (		lowercase__  :     float       ,     lowercase__  :     float   ):
		snake_case		:						Tuple								=				np.mean((original - contrast) ** 2   )
		if mse == 0:
				return 100

		return 20 * math.logaa(PIXEL_MAX / math.sqrt(lowercase__   )   )



def   UpperCamelCase__     (		):
		snake_case		:						Union[str, Any]								=				os.path.dirname(os.path.realpath(lowercase__   )   )
		# Loading images (original image and compressed image)
		snake_case		:						int								=				cva.imread(os.path.join(lowercase__       ,     "image_data/original_image.png"   )   )
		snake_case		:						List[Any]								=				cva.imread(os.path.join(lowercase__       ,     "image_data/compressed_image.png"   )       ,     1   )

		snake_case		:						int								=				cva.imread(os.path.join(lowercase__       ,     "image_data/PSNR-example-base.png"   )   )
		snake_case		:						Optional[int]								=				cva.imread(
		    os.path.join(lowercase__       ,     "image_data/PSNR-example-comp-10.jpg"   )       ,     1   )

		# Value expected: 29.73dB
		print("-- First Test --"   )
		print(F'''PSNR value is {peak_signal_to_noise_ratio(lowercase__       ,     lowercase__   )} dB'''   )

		# # Value expected: 31.53dB (Wikipedia Example)
		print("\n-- Second Test --"   )
		print(F'''PSNR value is {peak_signal_to_noise_ratio(lowercase__       ,     lowercase__   )} dB'''   )


if __name__ == "__main__":
							main()







"""simple docstring"""

import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil



@pytest.fixture
def   UpperCamelCase__     (		lowercase__  :     str   ):
		snake_case		:						List[str]								=				tmp_path / "text.txt"
		snake_case		:						Tuple								=				textwrap.dedent(
		    "\\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n\n        Second paragraph:\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n        "   )
		with open(lowercase__       ,     "w"       ,     encoding="utf-8"   ) as f:
				f.write(lowercase__   )
		return str(lowercase__   )



@pytest.fixture
def   UpperCamelCase__     (		lowercase__  :     str       ,     lowercase__  :     Dict   ):
		snake_case		:						Any								=				tmp_path / "text_with_image.txt"
		with open(lowercase__       ,     "w"       ,     encoding="utf-8"   ) as f:
				f.write(lowercase__   )
		return str(lowercase__   )



@pytest.mark.parametrize("keep_linebreaks"       ,     [True, False]   )
def   UpperCamelCase__     (		lowercase__  :     Union[str, Any]       ,     lowercase__  :     Tuple   ):
		with open(lowercase__       ,     encoding="utf-8"   ) as f:
				snake_case		:						List[Any]								=				f.read().splitlines(keepends=lowercase__   )
		snake_case		:						List[Any]								=				Text(keep_linebreaks=lowercase__       ,     encoding="utf-8"   )
		snake_case		:						Optional[int]								=				text._generate_tables([[text_file]]   )
		snake_case		:						int								=				pa.concat_tables([table for _, table in generator]   ).to_pydict()["text"]
		assert generated_content == expected_content



@require_pil
def   UpperCamelCase__     (		lowercase__  :     Optional[Any]   ):
		with open(lowercase__       ,     encoding="utf-8"   ) as f:
				snake_case		:						Union[str, Any]								=				f.read().splitlines()[0]
		snake_case		:						List[Any]								=				Text(encoding="utf-8"       ,     features=Features({"image": Image()}   )   )
		snake_case		:						Tuple								=				text._generate_tables([[text_file_with_image]]   )
		snake_case		:						List[str]								=				pa.concat_tables([table for _, table in generator]   )
		assert pa_table.schema.field("image"   ).type == Image()()
		snake_case		:						Optional[Any]								=				pa_table.to_pydict()["image"]
		assert generated_content == [{"path": image_file, "bytes": None}]



@pytest.mark.parametrize("sample_by"       ,     ["line", "paragraph", "document"]   )
def   UpperCamelCase__     (		lowercase__  :     Union[str, Any]       ,     lowercase__  :     List[str]   ):
		with open(lowercase__       ,     encoding="utf-8"   ) as f:
				snake_case		:						Tuple								=				f.read()
		if sample_by == "line":
				snake_case		:						Optional[int]								=				expected_content.splitlines()
		elif sample_by == "paragraph":
				snake_case		:						str								=				expected_content.split("\n\n"   )
		elif sample_by == "document":
				snake_case		:						List[Any]								=				[expected_content]
		snake_case		:						str								=				Text(sample_by=lowercase__       ,     encoding="utf-8"       ,     chunksize=100   )
		snake_case		:						Optional[int]								=				text._generate_tables([[text_file]]   )
		snake_case		:						Optional[Any]								=				pa.concat_tables([table for _, table in generator]   ).to_pydict()["text"]
		assert generated_content == expected_content

