



'''simple docstring'''



import random






class 			_SCREAMING_SNAKE_CASE				:



			def __init__(     self		:						Tuple    ,			__UpperCamelCase		:						list[list[float]]    ,			__UpperCamelCase		:						list[int]    ,			__UpperCamelCase		:						float = 0.01    ,			__UpperCamelCase		:						int = 1000    ,			__UpperCamelCase		:						float = -1    ,			)      ->      None:
							"""simple docstring"""





							snake_case__      :   Union[str, Any]      =    sample
							if len(self.sample			) == 0:
											raise ValueError('''Sample data can not be empty'''			)
							snake_case__      :   List[str]      =    target
							if len(self.target			) == 0:
											raise ValueError('''Target data can not be empty'''			)
							if len(self.sample			) != len(self.target			):
											raise ValueError('''Sample data and Target data do not have matching lengths'''			)
							snake_case__      :   Tuple      =    learning_rate
							snake_case__      :   List[str]      =    epoch_number
							snake_case__      :   List[Any]      =    bias
							snake_case__      :   Tuple      =    len(__UpperCamelCase			)
							snake_case__      :   List[str]      =    len(sample[0]			)  # number of columns in dataset
							snake_case__      :   list      =    []



			def 				lowerCAmelCase (     self		:						Tuple			)      ->      None:
							"""simple docstring"""





							for sample in self.sample:
											sample.insert(0    ,			self.bias			)

							for _ in range(self.col_sample			):
											self.weight.append(random.random()			)

							self.weight.insert(0    ,			self.bias			)

							snake_case__      :   Any      =    0

							while True:
											snake_case__      :   Optional[int]      =    False
											for i in range(self.number_sample			):
															snake_case__      :   str      =    0
															for j in range(self.col_sample + 1			):
																			snake_case__      :   Dict      =    u + self.weight[j] * self.sample[i][j]
															snake_case__      :   Tuple      =    self.sign(__UpperCamelCase			)
															if y != self.target[i]:
																			for j in range(self.col_sample + 1			):
																							snake_case__      :   str      =    (
																							    self.weight[j]
																							    + self.learning_rate
																							    * (self.target[i] - y)
																							    * self.sample[i][j]
																							)
																			snake_case__      :   Tuple      =    True
            # print('Epoch: \n',epoch_count)
											snake_case__      :   List[Any]      =    epoch_count + 1
											# if you want control the epoch or just by error
											if not has_misclassified:
															print(('''\nEpoch:\n''', epoch_count)			)
															print('''------------------------\n'''			)
															# if epoch_count > self.epoch_number or not error:
															break



			def 				lowerCAmelCase (     self		:						List[str]    ,			__UpperCamelCase		:						list[float]			)      ->      None:
							"""simple docstring"""





							if len(self.sample			) == 0:
											raise ValueError('''Sample data can not be empty'''			)
							sample.insert(0    ,			self.bias			)
							snake_case__      :   str      =    0
							for i in range(self.col_sample + 1			):
											snake_case__      :   List[str]      =    u + self.weight[i] * sample[i]

							snake_case__      :   Optional[int]      =    self.sign(__UpperCamelCase			)

							if y == -1:
											print(('''Sample: ''', sample)			)
											print('''classification: P1'''			)
							else:
											print(('''Sample: ''', sample)			)
											print('''classification: P2'''			)







			def 				lowerCAmelCase (     self		:						Union[str, Any]    ,			__UpperCamelCase		:						float			)      ->      int:
							"""simple docstring"""





							return 1 if u >= 0 else -1



_lowercase       :						Dict						=[
    [-0.6508, 0.1097, 4.0009],
    [-1.4492, 0.8896, 4.4005],
    [2.0850, 0.6876, 12.0710],
    [0.2626, 1.1476, 7.7985],
    [0.6418, 1.0234, 7.0427],
    [0.2569, 0.6730, 8.3265],
    [1.1155, 0.6043, 7.4446],
    [0.0914, 0.3399, 7.0677],
    [0.0121, 0.5256, 4.6316],
    [-0.0429, 0.4660, 5.4323],
    [0.4340, 0.6870, 8.2287],
    [0.2735, 1.0287, 7.1934],
    [0.4839, 0.4851, 7.4850],
    [0.4089, -0.1267, 5.5019],
    [1.4391, 0.1614, 8.5843],
    [-0.9115, -0.1973, 2.1962],
    [0.3654, 1.0475, 7.4858],
    [0.2144, 0.7515, 7.1699],
    [0.2013, 1.0014, 6.5489],
    [0.6483, 0.2183, 5.8991],
    [-0.1147, 0.2242, 7.2435],
    [-0.7970, 0.8795, 3.8762],
    [-1.0625, 0.6366, 2.4707],
    [0.5307, 0.1285, 5.6883],
    [-1.2200, 0.7777, 1.7252],
    [0.3957, 0.1076, 5.6623],
    [-0.1013, 0.5989, 7.1812],
    [2.4482, 0.9455, 11.2095],
    [2.0149, 0.6192, 10.9263],
    [0.2012, 0.2611, 5.4631],
]

_lowercase       :						Union[str, Any]						=[
    -1,
    -1,
    -1,
    1,
    1,
    -1,
    1,
    -1,
    1,
    1,
    -1,
    1,
    -1,
    -1,
    -1,
    -1,
    1,
    1,
    1,
    1,
    -1,
    1,
    1,
    1,
    1,
    -1,
    -1,
    1,
    -1,
    1,
]


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				_lowercase       :						Dict						=Perceptron(
				    sample=samples, target=target, learning_rate=0.01, epoch_number=1000, bias=-1
				)
				network.training()
				print("Finished training perceptron")
				print("Enter values to predict or q to exit")
				while True:
								_lowercase       :						list						=[]
								for i in range(len(samples[0])):
												_lowercase       :						Union[str, Any]						=input("value: ").strip()
												if user_input == "q":
																break
												_lowercase       :						List[Any]						=float(user_input)
												sample.insert(i, observation)
								network.sort(sample)










"""simple docstring"""



from __future__ import annotations

import sys




class       UpperCAmelCase_    :




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




     '''simple docstring'''

     A__			=							letter
     A__			=							freq
     A__			=							{}




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




     '''simple docstring'''

     return F"""{self.letter}:{self.freq}"""






class       UpperCAmelCase_    :




    def __init__(       self		:			Dict      ,					snake_case_		:			int      ,					snake_case_		:			Letter | TreeNode      ,					snake_case_		:			Letter | TreeNode ) ->				Optional[Any]:




     '''simple docstring'''

     A__			=							freq
     A__			=							left
     A__			=							right







def     _SCREAMING_SNAKE_CASE  (				lowercase_		)		->						list[Letter]:
 A__			=							{}
 with open(lowercase_		) as f:
  while True:
   A__			=							f.read(1		)
   if not c:
    break
   A__			=							chars[c] + 1 if c in chars else 1
 return sorted((Letter(lowercase_     ,					lowercase_		) for c, f in chars.items())     ,					key=lambda lowercase_		: x.freq		)







def     _SCREAMING_SNAKE_CASE  (				lowercase_		)		->						Letter | TreeNode:
 A__			=							letters  # type: ignore
 while len(lowercase_		) > 1:
  A__			=							response.pop(0		)
  A__			=							response.pop(0		)
  A__			=							left.freq + right.freq
  A__			=							TreeNode(lowercase_     ,					lowercase_     ,					lowercase_		)
  response.append(lowercase_		)
  response.sort(key=lambda lowercase_		: x.freq		)
 return response[0]







def     _SCREAMING_SNAKE_CASE  (				lowercase_     ,					lowercase_		)		->						list[Letter]:
 if isinstance(lowercase_     ,					lowercase_		):
  A__			=							bitstring
  return [root]
 A__			=							root  # type: ignore
 A__			=							[]
 letters += traverse_tree(treenode.left     ,					bitstring + "0"		)
 letters += traverse_tree(treenode.right     ,					bitstring + "1"		)
 return letters







def     _SCREAMING_SNAKE_CASE  (				lowercase_		)		->						None:
 A__			=							parse_file(lowercase_		)
 A__			=							build_tree(lowercase_		)
 A__			=							{
     k: v for letter in traverse_tree(lowercase_     ,					""		) for k, v in letter.bitstring.items()
 }
 print(f"""Huffman Coding  of {file_path}: """		)
 with open(lowercase_		) as f:
  while True:
   A__			=							f.read(1		)
   if not c:
    break
   print(letters[c]     ,					end=" "		)
 print()


if __name__ == "__main__":
      # pass the file path to the huffman function
      huffman(sys.argv[1])





