"""simple docstring"""




import numpy as np



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Union[str, Any]  				=					np.array(_lowercase						)
					lowerCamelCase__		:   List[Any]  				=					np.array(_lowercase						)

					lowerCamelCase__		:   Optional[int]  				=					abs(predict - actual						)
					lowerCamelCase__		:   int  				=					difference.mean()

					return score



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Any  				=					np.array(_lowercase						)
					lowerCamelCase__		:   Tuple  				=					np.array(_lowercase						)

					lowerCamelCase__		:   List[Any]  				=					predict - actual
					lowerCamelCase__		:   List[str]  				=					np.square(_lowercase						)

					lowerCamelCase__		:   Optional[int]  				=					square_diff.mean()
					return score



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Tuple  				=					np.array(_lowercase						)
					lowerCamelCase__		:   Optional[Any]  				=					np.array(_lowercase						)

					lowerCamelCase__		:   List[str]  				=					predict - actual
					lowerCamelCase__		:   List[Any]  				=					np.square(_lowercase						)
					lowerCamelCase__		:   Any  				=					square_diff.mean()
					lowerCamelCase__		:   Optional[Any]  				=					np.sqrt(_lowercase						)
					return score



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Optional[Any]  				=					np.array(_lowercase						)
					lowerCamelCase__		:   Optional[Any]  				=					np.array(_lowercase						)

					lowerCamelCase__		:   Dict  				=					np.log(predict + 1						)
					lowerCamelCase__		:   Optional[int]  				=					np.log(actual + 1						)

					lowerCamelCase__		:   int  				=					log_predict - log_actual
					lowerCamelCase__		:   Tuple  				=					np.square(_lowercase						)
					lowerCamelCase__		:   Union[str, Any]  				=					square_diff.mean()

					lowerCamelCase__		:   int  				=					np.sqrt(_lowercase						)

					return score



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Union[str, Any]  				=					np.array(_lowercase						)
					lowerCamelCase__		:   List[Any]  				=					np.array(_lowercase						)

					lowerCamelCase__		:   Union[str, Any]  				=					predict - actual
					lowerCamelCase__		:   List[Any]  				=					np.sum(_lowercase						) / len(_lowercase						)
					lowerCamelCase__		:   int  				=					np.sum(_lowercase						) / len(_lowercase						)
					# print(numerator, denumerator)
					lowerCamelCase__		:   Union[str, Any]  				=					float(_lowercase						) / denumerator * 100

					return score





def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					return np.mean(np.array(_lowercase						) == np.array(_lowercase						)						)







"""simple docstring"""




def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					if not root or root not in binary_tree_mirror_dictionary:
										return
					lowerCamelCase__				,						lowerCamelCase__		:   Tuple  				=					binary_tree_mirror_dictionary[root][:2]
					lowerCamelCase__		:   Optional[Any]  				=					[right_child, left_child]
					binary_tree_mirror_dict(_lowercase							, _lowercase						)
					binary_tree_mirror_dict(_lowercase							, _lowercase						)



def 				__a       (			_lowercase							, _lowercase = 1						):







					"""simple docstring"""





					if not binary_tree:
										raise ValueError('''binary tree cannot be empty'''						)
					if root not in binary_tree:
										lowerCamelCase__		:   Dict  				=					f"""root {root} is not present in the binary_tree"""
										raise ValueError(_lowercase						)
					lowerCamelCase__		:   Optional[Any]  				=					dict(_lowercase						)
					binary_tree_mirror_dict(_lowercase							, _lowercase						)
					return binary_tree_mirror_dictionary


if __name__ == "__main__":
					UpperCAmelCase       :    Any									=			{1: [2, 3], 2: [4, 5], 3: [6, 7], 7: [8, 9]}
					print(f'''Binary tree: {binary_tree}''')
					UpperCAmelCase       :    List[Any]									=			binary_tree_mirror(binary_tree, 5)
					print(f'''Binary tree mirror: {binary_tree_mirror_dictionary}''')






