
'''simple docstring'''





import random






class        UpperCAmelCase_       :

 '''simple docstring'''







 def __init__(				self		:     str ,							snake_case__		:     list[list[float]] ,							snake_case__		:     list[int] ,							snake_case__		:     float = 0.01 ,							snake_case__		:     int = 10_00 ,							snake_case__		:     float = -1 ,							):



   '''simple docstring'''




   UpperCAmelCase__			:				List[str]												=       sample
   if len(self.sample   ) == 0:
     raise ValueError("Sample data can not be empty"   )
   UpperCAmelCase__			:				Tuple												=       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"   )
   UpperCAmelCase__			:				Dict												=       learning_rate
   UpperCAmelCase__			:				Optional[int]												=       epoch_number
   UpperCAmelCase__			:				List[str]												=       bias
   UpperCAmelCase__			:				Tuple												=       len(snake_case__   )
   UpperCAmelCase__			:				int												=       len(sample[0]   )  # number of columns in dataset
   UpperCAmelCase__			:				list												=       []







 def        UpperCamelCase     (				self		:     Tuple   ):



   '''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   )

   UpperCAmelCase__			:				Optional[int]												=       0

   while True:
     UpperCAmelCase__			:				Tuple												=       False
     for i in range(self.number_sample   ):
       UpperCAmelCase__			:				List[Any]												=       0
       for j in range(self.col_sample + 1   ):
         UpperCAmelCase__			:				int												=       u + self.weight[j] * self.sample[i][j]
       UpperCAmelCase__			:				str												=       self.sign(snake_case__   )
       if y != self.target[i]:
         for j in range(self.col_sample + 1   ):
           UpperCAmelCase__			:				Optional[Any]												=       (
               self.weight[j]
               + self.learning_rate
               * (self.target[i] - y)
               * self.sample[i][j]
           )
         UpperCAmelCase__			:				Tuple												=       True
            # print('Epoch: \n',epoch_count)
     UpperCAmelCase__			:				int												=       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        UpperCamelCase     (				self		:     Union[str, Any] ,							snake_case__		:     list[float]   ):



   '''simple docstring'''




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

   UpperCAmelCase__			:				str												=       self.sign(snake_case__   )

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







 def        UpperCamelCase     (				self		:     Tuple ,							snake_case__		:     float   ):



   '''simple docstring'''




   return 1 if u >= 0 else -1



SCREAMING_SNAKE_CASE    =					[
    [-0.6_5_0_8, 0.1_0_9_7, 4.0_0_0_9],
    [-1.4_4_9_2, 0.8_8_9_6, 4.4_0_0_5],
    [2.0_8_5_0, 0.6_8_7_6, 1_2.0_7_1_0],
    [0.2_6_2_6, 1.1_4_7_6, 7.7_9_8_5],
    [0.6_4_1_8, 1.0_2_3_4, 7.0_4_2_7],
    [0.2_5_6_9, 0.6_7_3_0, 8.3_2_6_5],
    [1.1_1_5_5, 0.6_0_4_3, 7.4_4_4_6],
    [0.0_9_1_4, 0.3_3_9_9, 7.0_6_7_7],
    [0.0_1_2_1, 0.5_2_5_6, 4.6_3_1_6],
    [-0.0_4_2_9, 0.4_6_6_0, 5.4_3_2_3],
    [0.4_3_4_0, 0.6_8_7_0, 8.2_2_8_7],
    [0.2_7_3_5, 1.0_2_8_7, 7.1_9_3_4],
    [0.4_8_3_9, 0.4_8_5_1, 7.4_8_5_0],
    [0.4_0_8_9, -0.1_2_6_7, 5.5_0_1_9],
    [1.4_3_9_1, 0.1_6_1_4, 8.5_8_4_3],
    [-0.9_1_1_5, -0.1_9_7_3, 2.1_9_6_2],
    [0.3_6_5_4, 1.0_4_7_5, 7.4_8_5_8],
    [0.2_1_4_4, 0.7_5_1_5, 7.1_6_9_9],
    [0.2_0_1_3, 1.0_0_1_4, 6.5_4_8_9],
    [0.6_4_8_3, 0.2_1_8_3, 5.8_9_9_1],
    [-0.1_1_4_7, 0.2_2_4_2, 7.2_4_3_5],
    [-0.7_9_7_0, 0.8_7_9_5, 3.8_7_6_2],
    [-1.0_6_2_5, 0.6_3_6_6, 2.4_7_0_7],
    [0.5_3_0_7, 0.1_2_8_5, 5.6_8_8_3],
    [-1.2_2_0_0, 0.7_7_7_7, 1.7_2_5_2],
    [0.3_9_5_7, 0.1_0_7_6, 5.6_6_2_3],
    [-0.1_0_1_3, 0.5_9_8_9, 7.1_8_1_2],
    [2.4_4_8_2, 0.9_4_5_5, 1_1.2_0_9_5],
    [2.0_1_4_9, 0.6_1_9_2, 1_0.9_2_6_3],
    [0.2_0_1_2, 0.2_6_1_1, 5.4_6_3_1],
]

SCREAMING_SNAKE_CASE    =					[
    -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()

      SCREAMING_SNAKE_CASE    =					Perceptron(
          sample=samples, target=target, learning_rate=0.0_1, epoch_number=1_0_0_0, bias=-1
      )
      network.training()
      print("""Finished training perceptron""")
      print("""Enter values to predict or q to exit""")
      while True:
            SCREAMING_SNAKE_CASE    =					[]
            for i in range(len(samples[0])):
                  SCREAMING_SNAKE_CASE    =					input("""value: """).strip()
                  if user_input == "q":
                        break
                  SCREAMING_SNAKE_CASE    =					float(user_input)
                  sample.insert(i, observation)
            network.sort(sample)





'''simple docstring'''





from math import cos, sin







def snake_case_    (				lowercase__		):
  UpperCAmelCase__			:				List[Any]												=       float(lowercase__		)
  return [[scaling_factor * int(x == y		) for x in range(2		)] for y in range(2		)]







def snake_case_    (				lowercase__		):
  UpperCAmelCase__					, UpperCAmelCase__			:				List[Any]												=       cos(lowercase__		), sin(lowercase__		)
  return [[c, -s], [s, c]]







def snake_case_    (				lowercase__		):
  UpperCAmelCase__					, UpperCAmelCase__			:				Dict												=       cos(lowercase__		), sin(lowercase__		)
  UpperCAmelCase__			:				Tuple												=       c * s
  return [[c * c, cs], [cs, s * s]]







def snake_case_    (				lowercase__		):
  UpperCAmelCase__					, UpperCAmelCase__			:				Dict												=       cos(lowercase__		), sin(lowercase__		)
  UpperCAmelCase__			:				Any												=       c * s
  return [[2 * c - 1, 2 * cs], [2 * cs, 2 * s - 1]]


print(F'    {scaling(5) = }')
print(F'  {rotation(4_5) = }')
print(F'{projection(4_5) = }')






print(F'{reflection(4_5) = }')



