




'''simple docstring'''







import argparse
import copy



def        lowerCamelCase__				(      __lowercase				):
     snake_case			:      Optional[int]        =			{}

     with open(__lowercase				) as f:
          for line in f:
               if line.split()[0] not in dict_of_neighbours:
                    snake_case			:      int        =			[]
                    _list.append([line.split()[1], line.split()[2]]				)
                    snake_case			:      Dict        =			_list
               else:
                    dict_of_neighbours[line.split()[0]].append(
                        [line.split()[1], line.split()[2]]				)
               if line.split()[1] not in dict_of_neighbours:
                    snake_case			:      Optional[Any]        =			[]
                    _list.append([line.split()[0], line.split()[2]]				)
                    snake_case			:      Any        =			_list
               else:
                    dict_of_neighbours[line.split()[1]].append(
                        [line.split()[0], line.split()[2]]				)

     return dict_of_neighbours



def        lowerCamelCase__				(      __lowercase     ,   __lowercase				):

     with open(__lowercase				) as f:
          snake_case			:      str        =			f.read(1				)
     snake_case			:      Dict        =			start_node

     snake_case			:      Optional[Any]        =			[]

     snake_case			:      Optional[Any]        =			start_node

     snake_case			:      List[str]        =			0
     while visiting not in first_solution:
          snake_case			:      int        =			10_000
          for k in dict_of_neighbours[visiting]:
               if int(k[1]				) < int(__lowercase				) and k[0] not in first_solution:
                    snake_case			:      Any        =			k[1]
                    snake_case			:      Any        =			k[0]

          first_solution.append(__lowercase				)
          snake_case			:      Dict        =			distance_of_first_solution + int(__lowercase				)
          snake_case			:      Optional[int]        =			best_node

     first_solution.append(__lowercase				)

     snake_case			:      str        =			0
     for k in dict_of_neighbours[first_solution[-2]]:
          if k[0] == start_node:
               break
          position += 1

     snake_case			:      str        =			(
         distance_of_first_solution
         + int(dict_of_neighbours[first_solution[-2]][position][1]				)
         - 10_000
     )
     return first_solution, distance_of_first_solution



def        lowerCamelCase__				(      __lowercase     ,   __lowercase				):
     snake_case			:      Dict        =			[]

     for n in solution[1:-1]:
          snake_case			:      List[str]        =			solution.index(__lowercase				)
          for kn in solution[1:-1]:
               snake_case			:      str        =			solution.index(__lowercase				)
               if n == kn:
                    continue

               snake_case			:      Tuple        =			copy.deepcopy(__lowercase				)
               snake_case			:      Tuple        =			kn
               snake_case			:      Any        =			n

               snake_case			:      Tuple        =			0

               for k in _tmp[:-1]:
                    snake_case			:      Dict        =			_tmp[_tmp.index(__lowercase				) + 1]
                    for i in dict_of_neighbours[k]:
                         if i[0] == next_node:
                              snake_case			:      List[str]        =			distance + int(i[1]				)
               _tmp.append(__lowercase				)

               if _tmp not in neighborhood_of_solution:
                    neighborhood_of_solution.append(_tmp				)

     snake_case			:      Tuple        =			len(neighborhood_of_solution[0]				) - 1

     neighborhood_of_solution.sort(key=lambda __lowercase				: x[index_of_last_item_in_the_list]				)
     return neighborhood_of_solution



def        lowerCamelCase__				(      __lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase				):
     snake_case			:      Dict        =			1
     snake_case			:      Dict        =			first_solution
     snake_case			:      List[Any]        =			[]
     snake_case			:      Union[str, Any]        =			distance_of_first_solution
     snake_case			:      List[Any]        =			solution

     while count <= iters:
          snake_case			:      str        =			find_neighborhood(__lowercase     ,   __lowercase				)
          snake_case			:      Any        =			0
          snake_case			:      Optional[Any]        =			neighborhood[index_of_best_solution]
          snake_case			:      int        =			len(__lowercase				) - 1

          snake_case			:      Dict        =			False
          while not found:
               snake_case			:      List[str]        =			0
               while i < len(__lowercase				):
                    if best_solution[i] != solution[i]:
                         snake_case			:      str        =			best_solution[i]
                         snake_case			:      Union[str, Any]        =			solution[i]
                         break
                    snake_case			:      Dict        =			i + 1

               if [first_exchange_node, second_exchange_node] not in tabu_list and [
                   second_exchange_node,
                   first_exchange_node,
               ] not in tabu_list:
                    tabu_list.append([first_exchange_node, second_exchange_node]				)
                    snake_case			:      List[str]        =			True
                    snake_case			:      Tuple        =			best_solution[:-1]
                    snake_case			:      str        =			neighborhood[index_of_best_solution][best_cost_index]
                    if cost < best_cost:
                         snake_case			:      Optional[Any]        =			cost
                         snake_case			:      List[Any]        =			solution
               else:
                    snake_case			:      Optional[Any]        =			index_of_best_solution + 1
                    snake_case			:      Union[str, Any]        =			neighborhood[index_of_best_solution]

          if len(__lowercase				) >= size:
               tabu_list.pop(0				)

          snake_case			:      List[Any]        =			count + 1

     return best_solution_ever, best_cost



def        lowerCamelCase__				(      __lowercase=None				):
     snake_case			:      Union[str, Any]        =			generate_neighbours(args.File				)

     snake_case ,		snake_case			:      Tuple        =			generate_first_solution(
         args.File     ,   __lowercase				)

     snake_case ,		snake_case			:      Union[str, Any]        =			tabu_search(
         __lowercase     ,   __lowercase     ,   __lowercase     ,   args.Iterations     ,   args.Size     ,   )

     print(F'''Best solution: {best_sol}, with total distance: {best_cost}.'''				)


if __name__ == "__main__":
      lowercase      :   Dict      =       argparse.ArgumentParser(description="""Tabu Search""")
      parser.add_argument(
          """-f""",
          """--File""",
          type=str,
          help="""Path to the file containing the data""",
          required=True,
      )
      parser.add_argument(
          """-i""",
          """--Iterations""",
          type=int,
          help="""How many iterations the algorithm should perform""",
          required=True,
      )
      parser.add_argument(
          """-s""", """--Size""", type=int, help="""Size of the tabu list""", required=True
      )

      # Pass the arguments to main method
      main(parser.parse_args())









'''simple docstring'''







import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

lowercase      :   Any      =       imread(R"""digital_image_processing/image_data/lena_small.jpg""")
lowercase      :   List[str]      =       cvtColor(img, COLOR_BGR2GRAY)



def        lowerCamelCase__				(      ):
     snake_case			:      Optional[int]        =			cn.convert_to_negative(__lowercase				)
     # assert negative_img array for at least one True
     assert negative_img.any()



def        lowerCamelCase__				(      ):
     with Image.open("""digital_image_processing/image_data/lena_small.jpg"""				) as img:
          # Work around assertion for response
          assert str(cc.change_contrast(__lowercase     ,   110				)				).startswith(
              """<PIL.Image.Image image mode=RGB size=100x100 at"""				)



def        lowerCamelCase__				(      ):
     snake_case			:      Union[str, Any]        =			canny.gen_gaussian_kernel(9     ,   sigma=1.4				)
     # Assert ambiguous array
     assert resp.all()



def        lowerCamelCase__				(      ):
     snake_case			:      Optional[Any]        =			imread("""digital_image_processing/image_data/lena_small.jpg"""     ,   0				)
     # assert ambiguous array for all == True
     assert canny_img.all()
     snake_case			:      Any        =			canny.canny(__lowercase				)
     # assert canny array for at least one True
     assert canny_array.any()



def        lowerCamelCase__				(      ):
     assert gg.gaussian_filter(__lowercase     ,   5     ,   sigma=0.9				).all()



def        lowerCamelCase__				(      ):
     # laplace diagonals
     snake_case			:      int        =			array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]				)
     snake_case			:      Tuple        =			conv.img_convolve(__lowercase     ,   __lowercase				).astype(__lowercase				)
     assert res.any()



def        lowerCamelCase__				(      ):
     assert med.median_filter(__lowercase     ,   3				).any()



def        lowerCamelCase__				(      ):
     snake_case ,		snake_case			:      Dict        =			sob.sobel_filter(__lowercase				)
     assert grad.any() and theta.any()



def        lowerCamelCase__				(      ):
     snake_case			:      int        =			sp.make_sepia(__lowercase     ,   20				)
     assert sepia.all()



def        lowerCamelCase__				(      __lowercase = "digital_image_processing/image_data/lena_small.jpg"				):
     snake_case			:      int        =			bs.Burkes(imread(__lowercase     ,   1				)     ,   120				)
     burkes.process()
     assert burkes.output_img.any()



def        lowerCamelCase__				(      __lowercase = "digital_image_processing/image_data/lena_small.jpg"     ,   ):
     snake_case			:      Dict        =			rs.NearestNeighbour(imread(__lowercase     ,   1				)     ,   400     ,   200				)
     nn.process()
     assert nn.output.any()







def        lowerCamelCase__				(      ):
     snake_case			:      int        =			"""digital_image_processing/image_data/lena.jpg"""

     # Reading the image and converting it to grayscale.
     snake_case			:      Tuple        =			imread(__lowercase     ,   0				)

     # Test for get_neighbors_pixel function() return not None
     snake_case			:      Optional[int]        =			0
     snake_case			:      Tuple        =			0
     snake_case			:      Any        =			image[x_coordinate][y_coordinate]

     snake_case			:      Any        =			lbp.get_neighbors_pixel(
         __lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase				)

     assert neighbors_pixels is not None

     # Test for local_binary_pattern function()
     # Create a numpy array as the same height and width of read image
     snake_case			:      List[Any]        =			np.zeros((image.shape[0], image.shape[1])				)

     # Iterating through the image and calculating the local binary pattern value
     # for each pixel.
     for i in range(0     ,   image.shape[0]				):
          for j in range(0     ,   image.shape[1]				):
               snake_case			:      Optional[Any]        =			lbp.local_binary_value(__lowercase     ,   __lowercase     ,   __lowercase				)

     assert lbp_image.any()



