'''simple docstring'''

import heapq
import sys

import numpy as np

UpperCamelCase__     :	Tuple				=			tuple[int, int]


class 				_lowercase	:
      '''simple docstring'''


      def __init__(				self							)			->			Union[str, Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				Any   				=  []
         UpperCAmelCase__							:				Union[str, Any]   				=  set()




      def 		lowerCAmelCase__					(				self							)			->			Optional[Any]:



         '''simple docstring'''



         if not self.empty():
            return self.elements[0][0]
         else:
            return float('''inf'''							)




      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



         return len(self.elements							) == 0




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_							)			->			Any:



         '''simple docstring'''



         if item not in self.set:
            heapq.heappush(self.elements					,(priority, item)							)
            self.set.add(lowerCamelCase_							)
         else:
            # update
            # print("update", item)
            UpperCAmelCase__							:				Dict   				=  []
            ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				str   				=  heapq.heappop(self.elements							)
            while x != item:
               temp.append((pri, x)							)
               ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				Optional[Any]   				=  heapq.heappop(self.elements							)
            temp.append((priority, item)							)
            for pro, xxx in temp:
               heapq.heappush(self.elements					,(pro, xxx)							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Optional[Any]:



         '''simple docstring'''



         if item in self.set:
            self.set.remove(lowerCamelCase_							)
            UpperCAmelCase__							:				Optional[Any]   				=  []
            ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				Any   				=  heapq.heappop(self.elements							)
            while x != item:
               temp.append((pro, x)							)
               ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				str   				=  heapq.heappop(self.elements							)
            for prito, yyy in temp:
               heapq.heappush(self.elements					,(prito, yyy)							)




      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         return self.elements[0][1]




      def 		lowerCAmelCase__					(				self							)			->			Optional[Any]:



         '''simple docstring'''



         ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				int   				=  heapq.heappop(self.elements							)
         self.set.remove(lowerCamelCase_							)
         return (priority, item)







def __UpperCamelCase(   _A					:				TPos  ,			_A					:				TPos    ):
   '''simple docstring'''
   # euclidean distance
   UpperCAmelCase__							:				int   				=  np.array(_A    )
   UpperCAmelCase__							:				List[str]   				=  np.array(_A    )
   return np.linalg.norm(a - b    )







def __UpperCamelCase(   _A					:				TPos  ,			_A					:				TPos    ):
   '''simple docstring'''
   # integer division by time variable
   return consistent_heuristic(_A  ,			_A    ) // t







def __UpperCamelCase(   _A					:				TPos  ,			_A					:				TPos    ):
   '''simple docstring'''
   # manhattan distance
   return abs(p[0] - goal[0]    ) + abs(p[1] - goal[1]    )







def __UpperCamelCase(   _A					:				TPos  ,			_A					:				int  ,			_A					:				TPos  ,			_A					:				dict[TPos, float]    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Dict   				=  g_function[start] + Wa * heuristics[i](_A  ,			_A    )
   return ans







def __UpperCamelCase(   _A					:				Dict  ,			_A					:				Tuple  ,			_A					:				Any    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Optional[int]   				=  np.chararray((n, n)    )
   for i in range(_A    ):
      for j in range(_A    ):
         UpperCAmelCase__							:				List[str]   				=  '''*'''

   for i in range(_A    ):
      for j in range(_A    ):
         if (j, (n - 1) - i) in blocks:
            UpperCAmelCase__							:				List[Any]   				=  '''#'''

   UpperCAmelCase__							:				Any   				=  '''-'''
   UpperCAmelCase__							:				Any   				=  back_pointer[goal]
   while x != start:
      ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				List[Any]   				=  x
      # print(x)
      UpperCAmelCase__							:				List[str]   				=  '''-'''
      UpperCAmelCase__							:				Any   				=  back_pointer[x]
   UpperCAmelCase__							:				Any   				=  '''-'''

   for i in range(_A    ):
      for j in range(_A    ):
         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:-'''    )
   UpperCAmelCase__							:				Optional[int]   				=  back_pointer[goal]
   while x != start:
      print(_A  ,			end=''' '''    )
      UpperCAmelCase__							:				int   				=  back_pointer[x]
   print(_A    )
   sys.exit()







def __UpperCamelCase(   _A					:				TPos    ):
   '''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 __UpperCamelCase(   _A					:				Union[str, Any]  ,			_A					:				List[Any]  ,			_A					:				str  ,			_A					:				Any  ,			_A					:				int  ,			_A					:				List[str]  ,			_A					:				List[str]  ,			_A					:				Optional[int]  ,			):
   '''simple docstring'''
   for itera in range(_A    ):
      open_list[itera].remove_element(_A    )
   # print("s", s)
   # print("j", j)
   ((UpperCAmelCase__)				,      (UpperCAmelCase__))							:				Any   				=  s
   UpperCAmelCase__							:				Optional[int]   				=  (x - 1, y)
   UpperCAmelCase__							:				List[Any]   				=  (x + 1, y)
   UpperCAmelCase__							:				str   				=  (x, y + 1)
   UpperCAmelCase__							:				Union[str, Any]   				=  (x, y - 1)

   for neighbours in [left, right, up, down]:
      if neighbours not in blocks:
         if valid(_A    ) and neighbours not in visited:
            # print("neighbour", neighbours)
            visited.add(_A    )
            UpperCAmelCase__							:				Any   				=  -1
            UpperCAmelCase__							:				Optional[int]   				=  float('''inf'''    )

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







def __UpperCamelCase(   ):
   '''simple docstring'''
   UpperCAmelCase__							:				int   				=  []
   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


UpperCamelCase__     :	Optional[Any]				=			{0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

UpperCamelCase__     :	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),
]
UpperCamelCase__     :	List[str]				=			make_common_ground()


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

# start and end destination
UpperCamelCase__     :	Any				=			(0, 0)
UpperCamelCase__     :	Union[str, Any]				=			(n - 1, n - 1)

UpperCamelCase__     :	List[str]				=			1







def __UpperCamelCase(   _A					:				TPos  ,			_A					:				TPos  ,			_A					:				int    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Optional[Any]   				=  {start: 0, goal: float('''inf'''    )}
   UpperCAmelCase__							:				str   				=  {start: -1, goal: -1}
   UpperCAmelCase__							:				List[str]   				=  []
   UpperCAmelCase__							:				int   				=  set()

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

   UpperCAmelCase__							:				list[int]   				=  []
   UpperCAmelCase__							:				list[int]   				=  []
   while open_list[0].minkey() < float('''inf'''    ):
      for i in range(1  ,			_A    ):
         # 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(_A  ,			_A  ,			_A    )
            else:
               UpperCAmelCase__				,      UpperCAmelCase__							:				int   				=  open_list[i].top_show()
               visited.add(_A    )
               expand_state(
                   _A  ,			_A  ,			_A  ,			_A  ,			_A  ,			_A  ,			_A  ,			_A  ,			)
               close_list_inad.append(_A    )
         else:
            if g_function[goal] <= open_list[0].minkey():
               if g_function[goal] < float('''inf'''    ):
                  do_something(_A  ,			_A  ,			_A    )
            else:
               UpperCAmelCase__							:				int   				=  open_list[0].top_show()
               visited.add(_A    )
               expand_state(
                   _A  ,			0  ,			_A  ,			_A  ,			_A  ,			_A  ,			_A  ,			_A  ,			)
               close_list_anchor.append(_A    )
   print('''No path found to goal'''    )
   print()
   for i in range(n - 1  ,			-1  ,			-1    ):
      for j in range(_A    ):
         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'''

# Logistic Regression from scratch

# In[62]:

# In[63]:

# importing all the required libraries

import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets







def __UpperCamelCase(   _A					:				str    ):
   '''simple docstring'''
   return 1 / (1 + np.exp(-z    ))







def __UpperCamelCase(   _A					:				int  ,			_A					:				str    ):
   '''simple docstring'''
   return (-y * np.log(_A    ) - (1 - y) * np.log(1 - h    )).mean()







def __UpperCamelCase(   _A					:				Optional[Any]  ,			_A					:				Tuple  ,			_A					:				Any    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Union[str, Any]   				=  np.dot(_A  ,			_A    )
   return np.sum(y * scores - np.log(1 + np.exp(_A    )    )    )







def __UpperCamelCase(   _A					:				Dict  ,			_A					:				Optional[int]  ,			_A					:				List[Any]  ,			_A					:				str=7_00_00    ):
   '''simple docstring'''
   UpperCAmelCase__							:				List[Any]   				=  np.zeros(x.shape[1]    )

   for iterations in range(_A    ):
      UpperCAmelCase__							:				Tuple   				=  np.dot(_A  ,			_A    )
      UpperCAmelCase__							:				Optional[Any]   				=  sigmoid_function(_A    )
      UpperCAmelCase__							:				Optional[int]   				=  np.dot(x.T  ,			h - y    ) / y.size
      UpperCAmelCase__							:				List[Any]   				=  theta - alpha * gradient  # updating the weights
      UpperCAmelCase__							:				Tuple   				=  np.dot(_A  ,			_A    )
      UpperCAmelCase__							:				Tuple   				=  sigmoid_function(_A    )
      UpperCAmelCase__							:				Optional[int]   				=  cost_function(_A  ,			_A    )
      if iterations % 1_00 == 0:
         print(F'''loss: {j} \t'''    )  # printing the loss after every 100 iterations
   return theta


# In[68]:

if __name__ == "__main__":
  UpperCamelCase__     :	str				=			datasets.load_iris()
  UpperCamelCase__     :	Tuple				=			iris.data[:, :2]
  UpperCamelCase__     :	str				=			(iris.target != 0) * 1

  UpperCamelCase__     :	Any				=			0.1
  UpperCamelCase__     :	List[str]				=			logistic_reg(alpha, x, y, max_iterations=70_000)
  print('theta: ', theta)  # printing the theta i.e our weights vector







  def __UpperCamelCase(   _A					:				Any    ):
     '''simple docstring'''
     return sigmoid_function(
         np.dot(_A  ,			_A    )    )  # predicting the value of probability from the logistic regression algorithm

  plt.figure(figsize=(10, 6))
  plt.scatter(x[y == 0][:, 0], x[y == 0][:, 1], color='b', label='0')
  plt.scatter(x[y == 1][:, 0], x[y == 1][:, 1], color='r', label='1')
  ((UpperCamelCase__)				,     (UpperCamelCase__))     :	Any				=			(x[:, 0].min(), x[:, 0].max())
  ((UpperCamelCase__)				,     (UpperCamelCase__))     :	Optional[Any]				=			(x[:, 1].min(), x[:, 1].max())
  ((UpperCamelCase__)				,     (UpperCamelCase__))     :	Any				=			np.meshgrid(np.linspace(xa_min, xa_max), np.linspace(xa_min, xa_max))
  UpperCamelCase__     :	str				=			np.c_[xxa.ravel(), xxa.ravel()]
  UpperCamelCase__     :	Union[str, Any]				=			predict_prob(grid).reshape(xxa.shape)
  plt.contour(xxa, xxa, probs, [0.5], linewidths=1, colors='black')

  plt.legend()
  plt.show()




