"""simple docstring"""




def 							lowerCAmelCase(     __lowerCamelCase						):
					__a		 =       0
					__a		 =       len(__lowerCamelCase						)

					for i in range(n - 1						):
										for j in range(i + 1				,    __lowerCamelCase						):
															if arr[i] > arr[j]:
																				num_inversions += 1

					return num_inversions
def 							lowerCAmelCase(     __lowerCamelCase						):
					if len(__lowerCamelCase						) <= 1:
										return arr, 0
					__a		 =       len(__lowerCamelCase						) // 2
					__a		 =       arr[0:mid]
					__a		 =       arr[mid:]

					__a		 =       count_inversions_recursive(__lowerCamelCase						)
					__a		 =       count_inversions_recursive(__lowerCamelCase						)
					__a		 =       _count_cross_inversions(__lowerCamelCase				,    __lowerCamelCase						)

					__a		 =       inversion_p + inversions_q + cross_inversions
					return c, num_inversions
def 							lowerCAmelCase(     __lowerCamelCase				,    __lowerCamelCase						):
					__a		 =       []
					__a		 =       0
					while i < len(__lowerCamelCase						) and j < len(__lowerCamelCase						):
										if p[i] > q[j]:
															# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
															# These are all inversions. The claim emerges from the
															# property that P is sorted.
															num_inversion += len(__lowerCamelCase						) - i
															r.append(q[j]						)
															j += 1
										else:
															r.append(p[i]						)
															i += 1

					if i < len(__lowerCamelCase						):
										r.extend(p[i:]						)
					else:
										r.extend(q[j:]						)

					return r, num_inversion
def 							lowerCAmelCase(     ):
					__a		 =       [10, 2, 1, 5, 5, 2, 11]

					# this arr has 8 inversions:
					# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

					__a		 =       count_inversions_bf(__lowerCamelCase						)
					__a		 =       count_inversions_recursive(__lowerCamelCase						)

					assert num_inversions_bf == num_inversions_recursive == 8

					print('number of inversions = '				,    __lowerCamelCase						)

					# testing an array with zero inversion (a sorted arr_1)

					arr_a.sort()
					__a		 =       count_inversions_bf(__lowerCamelCase						)
					__a		 =       count_inversions_recursive(__lowerCamelCase						)

					assert num_inversions_bf == num_inversions_recursive == 0
					print('number of inversions = '				,    __lowerCamelCase						)

					# an empty list should also have zero inversions
					__a		 =       []
					__a		 =       count_inversions_bf(__lowerCamelCase						)
					__a		 =       count_inversions_recursive(__lowerCamelCase						)

					assert num_inversions_bf == num_inversions_recursive == 0
					print('number of inversions = '				,    __lowerCamelCase						)


if __name__ == "__main__":
	main()





import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def 							lowerCAmelCase(     __lowerCamelCase						):
					return (data["data"], data["target"])
def 							lowerCAmelCase(     __lowerCamelCase				,    __lowerCamelCase				,    __lowerCamelCase						):
					__a		 =       XGBRegressor(verbosity=0				,    random_state=42						)
					xgb.fit(__lowerCamelCase				,    __lowerCamelCase						)
					# Predict target for test data
					__a		 =       xgb.predict(__lowerCamelCase						)
					__a		 =       predictions.reshape(len(__lowerCamelCase						)				,    1						)
					return predictions
def 							lowerCAmelCase(     ):
					__a		 =       fetch_california_housing()
					__a ,				__a		 =       data_handling(__lowerCamelCase						)
					__a ,				__a ,				__a ,				__a		 =       train_test_split(
					    __lowerCamelCase				,    __lowerCamelCase				,    test_size=0.25				,    random_state=1						)
					__a		 =       xgboost(__lowerCamelCase				,    __lowerCamelCase				,    __lowerCamelCase						)
					# Error printing
					print(f'''Mean Absolute Error : {mean_absolute_error(__lowerCamelCase				,    __lowerCamelCase						)}'''						)
					print(f'''Mean Square Error  : {mean_squared_error(__lowerCamelCase				,    __lowerCamelCase						)}'''						)


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)
	main()




