

"""simple docstring"""




import heapq
import sys

import numpy as np

A_				:      Optional[Any]           =			tuple[int, int]





class  lowerCamelCase    :

			def __init__(       self					:    Dict							) ->     int:
						SCREAMING_SNAKE_CASE__										=   []
						SCREAMING_SNAKE_CASE__										=   set()

			def        SCREAMING_SNAKE_CASE					(       self					:    Dict							) ->     Any:
						if not self.empty():
									return self.elements[0][0]
						else:
									return float("""inf"""							)

			def        SCREAMING_SNAKE_CASE					(       self					:    List[str]							) ->     int:
						return len(self.elements							) == 0

			def        SCREAMING_SNAKE_CASE					(       self					:    Tuple     ,					__UpperCAmelCase					:    str     ,					__UpperCAmelCase					:    Any							) ->     Optional[Any]:
						if item not in self.set:
									heapq.heappush(self.elements     ,					(priority, item)							)
									self.set.add(__UpperCAmelCase							)
						else:
									# update
									# print("update", item)
									SCREAMING_SNAKE_CASE__										=   []
									((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   heapq.heappop(self.elements							)
									while x != item:
												temp.append((pri, x)							)
												((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   heapq.heappop(self.elements							)
									temp.append((priority, item)							)
									for pro, xxx in temp:
												heapq.heappush(self.elements     ,					(pro, xxx)							)

			def        SCREAMING_SNAKE_CASE					(       self					:    int     ,					__UpperCAmelCase					:    str							) ->     Union[str, Any]:
						if item in self.set:
									self.set.remove(__UpperCAmelCase							)
									SCREAMING_SNAKE_CASE__										=   []
									((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   heapq.heappop(self.elements							)
									while x != item:
												temp.append((pro, x)							)
												((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   heapq.heappop(self.elements							)
									for prito, yyy in temp:
												heapq.heappush(self.elements     ,					(prito, yyy)							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[int]							) ->     Optional[int]:
						return self.elements[0][1]





			def        SCREAMING_SNAKE_CASE					(       self					:    Any							) ->     int:
						((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   heapq.heappop(self.elements							)
						self.set.remove(__UpperCAmelCase							)
						return (priority, item)

def 						A							(  snake_case__		,					snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   np.array(snake_case__     )
			SCREAMING_SNAKE_CASE__										=   np.array(snake_case__     )
			return np.linalg.norm(a - b     )

def 						A							(  snake_case__		,					snake_case__     ):




			'''simple docstring'''


			return consistent_heuristic(snake_case__		,					snake_case__     ) // t

def 						A							(  snake_case__		,					snake_case__     ):




			'''simple docstring'''


			return abs(p[0] - goal[0]     ) + abs(p[1] - goal[1]     )

def 						A							(  snake_case__		,					snake_case__		,					snake_case__		,					snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   g_function[start] + Wa * heuristics[i](snake_case__		,					snake_case__     )
			return ans

def 						A							(  snake_case__		,					snake_case__		,					snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   np.chararray((n, n)     )
			for i in range(snake_case__     ):
						for j in range(snake_case__     ):
									SCREAMING_SNAKE_CASE__										=   """*"""

			for i in range(snake_case__     ):
						for j in range(snake_case__     ):
									if (j, (n - 1) - i) in blocks:
												SCREAMING_SNAKE_CASE__										=   """#"""

			SCREAMING_SNAKE_CASE__										=   """-"""
			SCREAMING_SNAKE_CASE__										=   back_pointer[goal]
			while x != start:
						((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   x
						# print(x)
						SCREAMING_SNAKE_CASE__										=   """-"""
						SCREAMING_SNAKE_CASE__										=   back_pointer[x]
			SCREAMING_SNAKE_CASE__										=   """-"""

			for i in range(snake_case__     ):
						for j in range(snake_case__     ):
									if (i, j) == (0, n - 1):
												print(grid[i][j]		,					end=""" """     )
												print("""<-- End position"""		,					end=""" """     )
									else:
												print(grid[i][j]		,					end=""" """     )
						print()
			print("""^"""     )
			print("""Start position"""     )
			print()
			print("""# is an obstacle"""     )
			print("""- is the path taken by algorithm"""     )
			print("""PATH TAKEN BY THE ALGORITHM IS:-"""     )
			SCREAMING_SNAKE_CASE__										=   back_pointer[goal]
			while x != start:
						print(snake_case__		,					end=""" """     )
						SCREAMING_SNAKE_CASE__										=   back_pointer[x]
			print(snake_case__     )
			sys.exit()

def 						A							(  snake_case__     ):




			'''simple docstring'''


			if p[0] < 0 or p[0] > n - 1:
						return False
			if p[1] < 0 or p[1] > n - 1:
						return False
			return True

def 						A							(  snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					):




			'''simple docstring'''


			for itera in range(snake_case__     ):
						open_list[itera].remove_element(snake_case__     )
			# print("s", s)
			# print("j", j)
			((SCREAMING_SNAKE_CASE__)				,		(SCREAMING_SNAKE_CASE__))										=   s
			SCREAMING_SNAKE_CASE__										=   (x - 1, y)
			SCREAMING_SNAKE_CASE__										=   (x + 1, y)
			SCREAMING_SNAKE_CASE__										=   (x, y + 1)
			SCREAMING_SNAKE_CASE__										=   (x, y - 1)

			for neighbours in [left, right, up, down]:
						if neighbours not in blocks:
									if valid(snake_case__     ) and neighbours not in visited:
												# print("neighbour", neighbours)
												visited.add(snake_case__     )
												SCREAMING_SNAKE_CASE__										=   -1
												SCREAMING_SNAKE_CASE__										=   float("""inf"""     )

									if valid(snake_case__     ) and g_function[neighbours] > g_function[s] + 1:
												SCREAMING_SNAKE_CASE__										=   g_function[s] + 1
												SCREAMING_SNAKE_CASE__										=   s
												if neighbours not in close_list_anchor:
															open_list[0].put(snake_case__		,					key(snake_case__		,					0		,					snake_case__		,					snake_case__     )     )
															if neighbours not in close_list_inad:
																		for var in range(1		,					snake_case__     ):
																					if key(snake_case__		,					snake_case__		,					snake_case__		,					snake_case__     ) <= Wa * key(
																					    snake_case__		,					0		,					snake_case__		,					snake_case__     ):
																								open_list[j].put(
																								    snake_case__		,					key(snake_case__		,					snake_case__		,					snake_case__		,					snake_case__     )     )

def 						A							(  ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   []
			for x in range(1		,					5     ):
						for y in range(1		,					6     ):
									some_list.append((x, y)     )

			for x in range(15		,					20     ):
						some_list.append((x, 17)     )

			for x in range(10		,					19     ):
						for y in range(1		,					15     ):
									some_list.append((x, y)     )

    # L block
			for x in range(1		,					4     ):
						for y in range(12		,					19     ):
									some_list.append((x, y)     )
			for x in range(3		,					13     ):
						for y in range(16		,					19     ):
									some_list.append((x, y)     )
			return some_list


A_				:      Optional[int]           =			{0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

A_				:      Optional[Any]           =			[
    (0, 1),
    (1, 1),
    (2, 1),
    (3, 1),
    (4, 1),
    (5, 1),
    (6, 1),
    (7, 1),
    (8, 1),
    (9, 1),
    (10, 1),
    (11, 1),
    (12, 1),
    (13, 1),
    (14, 1),
    (15, 1),
    (16, 1),
    (17, 1),
    (18, 1),
    (19, 1),
]
A_				:      List[str]           =			make_common_ground()


A_				:      Optional[Any]           =			blocks_blk
# hyper parameters
A_				:      str           =			1
A_				:      List[str]           =			1
A_				:      Tuple           =			20
A_				:      Union[str, Any]           =			3  # one consistent and two other inconsistent

# start and end destination
A_				:      Optional[Any]           =			(0, 0)
A_				:      Dict           =			(n - 1, n - 1)

A_				:      Any           =			1

def 						A							(  snake_case__		,					snake_case__		,					snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   {start: 0, goal: float("""inf"""     )}
			SCREAMING_SNAKE_CASE__										=   {start: -1, goal: -1}
			SCREAMING_SNAKE_CASE__										=   []
			SCREAMING_SNAKE_CASE__										=   set()

			for i in range(snake_case__     ):
						open_list.append(PriorityQueue()     )
						open_list[i].put(snake_case__		,					key(snake_case__		,					snake_case__		,					snake_case__		,					snake_case__     )     )

			SCREAMING_SNAKE_CASE__										=   []
			SCREAMING_SNAKE_CASE__										=   []
			while open_list[0].minkey() < float("""inf"""     ):
						for i in range(1		,					snake_case__     ):
									# print(open_list[0].minkey(), open_list[i].minkey())
									if open_list[i].minkey() <= Wa * open_list[0].minkey():
												global t
												t += 1
												if g_function[goal] <= open_list[i].minkey():
															if g_function[goal] < float("""inf"""     ):
																		do_something(snake_case__		,					snake_case__		,					snake_case__     )
												else:
															SCREAMING_SNAKE_CASE__				,		SCREAMING_SNAKE_CASE__										=   open_list[i].top_show()
															visited.add(snake_case__     )
															expand_state(
															    snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					)
															close_list_inad.append(snake_case__     )
									else:
												if g_function[goal] <= open_list[0].minkey():
															if g_function[goal] < float("""inf"""     ):
																		do_something(snake_case__		,					snake_case__		,					snake_case__     )
												else:
															SCREAMING_SNAKE_CASE__										=   open_list[0].top_show()
															visited.add(snake_case__     )
															expand_state(
															    snake_case__		,					0		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					snake_case__		,					)
															close_list_anchor.append(snake_case__     )
			print("""No path found to goal"""     )
			print()
			for i in range(n - 1		,					-1		,					-1     ):
						for j in range(snake_case__     ):
									if (j, i) in blocks:
												print("""#"""		,					end=""" """     )
									elif (j, i) in back_pointer:
												if (j, i) == (n - 1, n - 1):
															print("""*"""		,					end=""" """     )
												else:
															print("""-"""		,					end=""" """     )
									else:
												print("""*"""		,					end=""" """     )
									if (j, i) == (n - 1, n - 1):
												print("""<-- End position"""		,					end=""" """     )
						print()
			print("""^"""     )
			print("""Start position"""     )
			print()
			print("""# is an obstacle"""     )
			print("""- is the path taken by algorithm"""     )


if __name__ == "__main__":
						multi_a_star(start, goal, n_heuristic)





"""simple docstring"""




import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression

# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split

# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeatures

# Importing the dataset
A_				:      int           =			pd.read_csv(
    "https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/"
    "position_salaries.csv"
)
A_				:      int           =			dataset.iloc[:, 1:2].values
A_				:      Optional[Any]           =			dataset.iloc[:, 2].values


A_       ,						A_       ,						A_       ,						A_				:      str           =			train_test_split(X, y, test_size=0.2, random_state=0)


A_				:      Optional[Any]           =			PolynomialFeatures(degree=4)
A_				:      Tuple           =			poly_reg.fit_transform(X)
A_				:      str           =			LinearRegression()
pol_reg.fit(X_poly, y)

def 						A							(  ):




			'''simple docstring'''


			plt.scatter(snake_case__		,					snake_case__		,					color="""red"""     )
			plt.plot(snake_case__		,					pol_reg.predict(poly_reg.fit_transform(snake_case__     )     )		,					color="""blue"""     )
			plt.title("""Truth or Bluff (Linear Regression)"""     )
			plt.xlabel("""Position level"""     )
			plt.ylabel("""Salary"""     )
			plt.show()


if __name__ == "__main__":
						viz_polymonial()

						# Predicting a new result with Polymonial Regression
						pol_reg.predict(poly_reg.fit_transform([[5.5]]))
						# output should be 132148.43750003


