






def      lowercase__      (     __snake_case    :							List[str]     ,       __snake_case    :							Any  ):


					'''simple docstring'''


					return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2




def      lowercase__      (     __snake_case    :							List[Any]     ,       __snake_case    :							List[Any]=0  ):


					'''simple docstring'''


					return sorted(__snake_case     ,       key=lambda __snake_case  : x[column]  )




def      lowercase__      (     __snake_case    :							Union[str, Any]     ,       __snake_case    :							Union[str, Any]     ,       __snake_case    :							Optional[int]=float('inf'  )  ):


					'''simple docstring'''


					for i in range(points_counts - 1  ):
										for j in range(i + 1     ,       __snake_case  ):
															UpperCAmelCase_    :      int            =						euclidean_distance_sqr(points[i]     ,       points[j]  )
															if current_dis < min_dis:
																				UpperCAmelCase_    :      Union[str, Any]            =						current_dis
					return min_dis




def      lowercase__      (     __snake_case    :							List[Any]     ,       __snake_case    :							Optional[Any]     ,       __snake_case    :							Union[str, Any]=float('inf'  )  ):


					'''simple docstring'''


					for i in range(min(6     ,       points_counts - 1  )     ,       __snake_case  ):
										for j in range(max(0     ,       i - 6  )     ,       __snake_case  ):
															UpperCAmelCase_    :      Union[str, Any]            =						euclidean_distance_sqr(points[i]     ,       points[j]  )
															if current_dis < min_dis:
																				UpperCAmelCase_    :      List[str]            =						current_dis
					return min_dis




def      lowercase__      (     __snake_case    :							Any     ,       __snake_case    :							str     ,       __snake_case    :							List[Any]  ):


					'''simple docstring'''


					if points_counts <= 3:
										return dis_between_closest_pair(__snake_case     ,       __snake_case  )

					# recursion
					UpperCAmelCase_    :      int            =						points_counts // 2
					UpperCAmelCase_    :      Union[str, Any]            =						closest_pair_of_points_sqr(
					    __snake_case     ,       points_sorted_on_y[:mid]     ,       __snake_case  )
					UpperCAmelCase_    :      Dict            =						closest_pair_of_points_sqr(
					    __snake_case     ,       points_sorted_on_y[mid:]     ,       points_counts - mid  )
					UpperCAmelCase_    :      List[Any]            =						min(__snake_case     ,       __snake_case  )
					UpperCAmelCase_    :      Optional[int]            =						[]
					for point in points_sorted_on_x:
										if abs(point[0] - points_sorted_on_x[mid][0]  ) < closest_pair_dis:
															cross_strip.append(__snake_case  )

					UpperCAmelCase_    :      int            =						dis_between_closest_in_strip(
					    __snake_case     ,       len(__snake_case  )     ,       __snake_case  )
					return min(__snake_case     ,       __snake_case  )




def      lowercase__      (     __snake_case    :							List[Any]     ,       __snake_case    :							Dict  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Dict            =						column_based_sort(__snake_case     ,       column=0  )
					UpperCAmelCase_    :      Optional[int]            =						column_based_sort(__snake_case     ,       column=1  )
					return (
					    closest_pair_of_points_sqr(
					        __snake_case     ,       __snake_case     ,       __snake_case  )
					) ** 0.5


if __name__ == "__main__":
		__UpperCAmelCase								=						[(2, 3), (12, 30), (40, 50), (5, 1), (12, 10), (3, 4)]
		print('Distance:', closest_pair_of_points(points, len(points)))














from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase								=						{
    'configuration_time_series_transformer': [
        'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TimeSeriesTransformerConfig',
    ],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TimeSeriesTransformerForPrediction',
		    'TimeSeriesTransformerModel',
		    'TimeSeriesTransformerPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_time_series_transformer import (
		    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    TimeSeriesTransformerConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_time_series_transformer import (
				    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TimeSeriesTransformerForPrediction,
				    TimeSeriesTransformerModel,
				    TimeSeriesTransformerPreTrainedModel,
				)

else:
		import sys

		__UpperCAmelCase								=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






