


import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
       # Create universe of discourse in Python using linspace ()
       __lowerCamelCase        =     np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)

       # Create two fuzzy sets by defining any membership function
       # (trapmf(), gbellmf(), gaussmf(), etc).
       __lowerCamelCase        =     [0, 25, 50]
       __lowerCamelCase        =     [25, 50, 75]
       __lowerCamelCase        =     fuzz.membership.trimf(X, abca)
       __lowerCamelCase        =     fuzz.membership.trimf(X, abca)

       # Compute the different operations using inbuilt functions.
       __lowerCamelCase        =     np.ones(75)
       __lowerCamelCase        =     np.zeros((75,))
       # 1. Union = max(µA(x), µB(x))
       __lowerCamelCase        =     fuzz.fuzzy_or(X, young, X, middle_aged)[1]
       # 2. Intersection = min(µA(x), µB(x))
       __lowerCamelCase        =     fuzz.fuzzy_and(X, young, X, middle_aged)[1]
       # 3. Complement (A) = (1- min(µA(x))
       __lowerCamelCase        =     fuzz.fuzzy_not(young)
       # 4. Difference (A/B) = min(µA(x),(1- µB(x)))
       __lowerCamelCase        =     fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
       # 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
       __lowerCamelCase        =     young + middle_aged - (young * middle_aged)
       # 6. Algebraic Product = (µA(x) * µB(x))
       __lowerCamelCase        =     young * middle_aged
       # 7. Bounded Sum = min[1,(µA(x), µB(x))]
       __lowerCamelCase        =     fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
       # 8. Bounded difference = min[0,(µA(x), µB(x))]
       __lowerCamelCase        =     fuzz.fuzzy_or(X, zero, X, young - middle_aged)[1]

       # max-min composition
       # max-product composition

       # Plot each set A, set B and each operation result using plot() and subplot().
       from matplotlib import pyplot as plt

       plt.figure()

       plt.subplot(4, 3, 1)
       plt.plot(X, young)
       plt.title('''Young''')
       plt.grid(True)

       plt.subplot(4, 3, 2)
       plt.plot(X, middle_aged)
       plt.title('''Middle aged''')
       plt.grid(True)

       plt.subplot(4, 3, 3)
       plt.plot(X, union)
       plt.title('''union''')
       plt.grid(True)

       plt.subplot(4, 3, 4)
       plt.plot(X, intersection)
       plt.title('''intersection''')
       plt.grid(True)

       plt.subplot(4, 3, 5)
       plt.plot(X, complement_a)
       plt.title('''complement_a''')
       plt.grid(True)

       plt.subplot(4, 3, 6)
       plt.plot(X, difference)
       plt.title('''difference a/b''')
       plt.grid(True)

       plt.subplot(4, 3, 7)
       plt.plot(X, alg_sum)
       plt.title('''alg_sum''')
       plt.grid(True)

       plt.subplot(4, 3, 8)
       plt.plot(X, alg_product)
       plt.title('''alg_product''')
       plt.grid(True)

       plt.subplot(4, 3, 9)
       plt.plot(X, bdd_sum)
       plt.title('''bdd_sum''')
       plt.grid(True)

       plt.subplot(4, 3, 10)
       plt.plot(X, bdd_difference)
       plt.title('''bdd_difference''')
       plt.grid(True)

       plt.subplots_adjust(hspace=0.5)
       plt.show()







from heapq import heappop, heappush

import numpy as np



def  _a			(						__UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase  ,  ):
     a_			,			a_    :     Any										=    grid.shape
     a_    :     Dict										=    [-1, 1, 0, 0]
     a_    :     List[Any]										=    [0, 0, -1, 1]
     if allow_diagonal:
          dx += [-1, -1, 1, 1]
          dy += [-1, 1, -1, 1]

     a_			,			a_    :     int										=    [(0, source)], set()
     a_    :     Optional[Any]										=    np.full((rows, cols)  ,  np.inf )
     a_    :     Tuple										=    0
     a_    :     Optional[Any]										=    np.empty((rows, cols)  ,  dtype=__UpperCamelCase )
     a_    :     Optional[Any]										=    None

     while queue:
          ((a_)			,			(a_))    :     Any										=    heappop(__UpperCamelCase )
          if (x, y) in visited:
               continue
          visited.add((x, y) )

          if (x, y) == destination:
               a_    :     Tuple										=    []
               while (x, y) != source:
                    path.append((x, y) )
                    a_			,			a_    :     Any										=    predecessors[x, y]
               path.append(__UpperCamelCase )  # add the source manually
               path.reverse()
               return matrix[destination], path

          for i in range(len(__UpperCamelCase ) ):
               a_			,			a_    :     Dict										=    x + dx[i], y + dy[i]
               if 0 <= nx < rows and 0 <= ny < cols:
                    a_    :     List[Any]										=    grid[nx][ny]
                    if next_node == 1 and matrix[nx, ny] > dist + 1:
                         heappush(__UpperCamelCase  ,  (dist + 1, (nx, ny)) )
                         a_    :     List[str]										=    dist + 1
                         a_    :     Union[str, Any]										=    (x, y)

     return np.inf, []


if __name__ == "__main__":
       import doctest

       doctest.testmod()



