
import numpy as np


def    A (      lowercase					, lowercase					, lowercase					, lowercase					, lowercase				)     ->						int:
		'''simple docstring'''

		UpperCamelCase						=  int(np.ceil((x_end - xa) / h				)				)
		UpperCamelCase						=  np.zeros((n + 1,)				)
		UpperCamelCase						=  ya
		UpperCamelCase						=  xa

		for k in range(lowercase				):
				UpperCamelCase						=  f(lowercase					, y[k]				)
				UpperCamelCase						=  f(x + 0.5 * h					, y[k] + 0.5 * h * ka				)
				UpperCamelCase						=  f(x + 0.5 * h					, y[k] + 0.5 * h * ka				)
				UpperCamelCase						=  f(x + h					, y[k] + h * ka				)
				UpperCamelCase						=  y[k] + (1 / 6) * h * (ka + 2 * ka + 2 * ka + ka)
				x += h

		return y


if __name__ == "__main__":
					import doctest

					doctest.testmod()


import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset


@pytest.mark.parametrize('dataset_size'					, [None, 400 * 2**20, 600 * 2**20]				)
@pytest.mark.parametrize('input_in_memory_max_size'					, ['default', 0, 100 * 2**20, 900 * 2**20]				)
def    A (      lowercase					, lowercase					, lowercase				)     ->						Union[str, Any]:
		'''simple docstring'''

		if input_in_memory_max_size != "default":
				monkeypatch.setattr(datasets.config					, 'IN_MEMORY_MAX_SIZE'					, lowercase				)
		UpperCamelCase						=  datasets.config.IN_MEMORY_MAX_SIZE
		if input_in_memory_max_size == "default":
				assert in_memory_max_size == 0
		else:
				assert in_memory_max_size == input_in_memory_max_size
		if dataset_size and in_memory_max_size:
				UpperCamelCase						=  dataset_size < in_memory_max_size
		else:
				UpperCamelCase						=  False
		UpperCamelCase						=  is_small_dataset(lowercase				)
		assert result == expected
