from __future__ import annotations

import math

_UpperCAmelCase            =		"""2020.9.26"""
_UpperCAmelCase            =		"""xcodz-dot, cclaus, dhruvmanila"""




def     UpperCamelCase						(	__lowercase						:			float						,__lowercase						:			float						,__lowercase						:			float						,__lowercase						:			float						,__lowercase						:			float     ):
			'''simple docstring'''




			if not all(isinstance(__lowercase						,(float, int)     ) for val in locals().values()     ):
						A_		:    Optional[Any]         =				f'''Input values must either be float or int: {list(locals().values()     )}'''
						raise TypeError(__lowercase     )
			A_		:    List[Any]         =				((x * distance) / (z + distance)) * scale
			A_		:    List[str]         =				((y * distance) / (z + distance)) * scale
			return projected_x, projected_y




def     UpperCamelCase						(	__lowercase						:			float						,__lowercase						:			float						,__lowercase						:			float						,__lowercase						:			str						,__lowercase						:			float     ):
			'''simple docstring'''




			if not isinstance(__lowercase						,__lowercase     ):
						raise TypeError('Axis must be a str'     )
			A_		:    List[Any]         =				locals()
			del input_variables["axis"]
			if not all(isinstance(__lowercase						,(float, int)     ) for val in input_variables.values()     ):
						A_		:    List[str]         =				(
						    'Input values except axis must either be float or int: '
						    f'''{list(input_variables.values()     )}'''
						)
						raise TypeError(__lowercase     )
			A_		:    Optional[Any]         =				(angle % 3_60) / 4_50 * 1_80 / math.pi
			if axis == "z":
						A_		:    List[Any]         =				x * math.cos(__lowercase     ) - y * math.sin(__lowercase     )
						A_		:    Optional[Any]         =				y * math.cos(__lowercase     ) + x * math.sin(__lowercase     )
						A_		:    Tuple         =				z
			elif axis == "x":
						A_		:    Tuple         =				y * math.cos(__lowercase     ) - z * math.sin(__lowercase     )
						A_		:    Any         =				z * math.cos(__lowercase     ) + y * math.sin(__lowercase     )
						A_		:    Optional[int]         =				x
			elif axis == "y":
						A_		:    Any         =				x * math.cos(__lowercase     ) - z * math.sin(__lowercase     )
						A_		:    str         =				z * math.cos(__lowercase     ) + x * math.sin(__lowercase     )
						A_		:    Dict         =				y
			else:
						raise ValueError('not a valid axis, choose one of \'x\', \'y\', \'z\''     )

			return new_x, new_y, new_z


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(F"""{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }""")
	print(F"""{rotate(1.0, 2.0, 3.0, 'y', 90.0) = }""")







from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase            =		{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase            =		[
	    """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """AutoformerForPrediction""",
	    """AutoformerModel""",
	    """AutoformerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

	_UpperCAmelCase            =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






