






import random




class        snake_case_					:

						"""simple docstring"""



						def __init__(self:				Any   ,				__UpperCAmelCase:				Union[str, Any]   ,				__UpperCAmelCase:				str   ,				__UpperCAmelCase:				List[str] = 0.01   ,				__UpperCAmelCase:				List[str] = 1000   ,				__UpperCAmelCase:				List[Any] = -1   ,				)						->    None:




											'''simple docstring'''



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



						def 					UpperCAmelCase__				(self:				str      )						->    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      )

											__a				:	Tuple			=				0

											while True:
																__a				:	Optional[Any]			=				False
																for i in range(self.number_sample      ):
																					__a				:	Dict			=				0
																					for j in range(self.col_sample + 1      ):
																										__a				:	str			=				u + self.weight[j] * self.sample[i][j]
																					__a				:	Any			=				self.sign(__A      )
																					if y != self.target[i]:
																										for j in range(self.col_sample + 1      ):
																															__a				:	List[str]			=				(
																															    self.weight[j]
																															    + self.learning_rate
																															    * (self.target[i] - y)
																															    * self.sample[i][j]
																															)
																										__a				:	Dict			=				True
            # print('Epoch: \n',epoch_count)
																__a				:	Tuple			=				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:				Dict   ,				__UpperCAmelCase:				Optional[Any]      )						->    None:




											'''simple docstring'''



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

											__a				:	str			=				self.sign(__A      )

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



						def 					UpperCAmelCase__				(self:				List[Any]   ,				__UpperCAmelCase:				List[Any]      )						->    int:




											'''simple docstring'''



											return 1 if u >= 0 else -1


UpperCAmelCase__			 =	[
    [-0.6_508, 0.1_097, 4.0_009],
    [-1.4_492, 0.8_896, 4.4_005],
    [2.0_850, 0.6_876, 12.0_710],
    [0.2_626, 1.1_476, 7.7_985],
    [0.6_418, 1.0_234, 7.0_427],
    [0.2_569, 0.6_730, 8.3_265],
    [1.1_155, 0.6_043, 7.4_446],
    [0.0_914, 0.3_399, 7.0_677],
    [0.0_121, 0.5_256, 4.6_316],
    [-0.0_429, 0.4_660, 5.4_323],
    [0.4_340, 0.6_870, 8.2_287],
    [0.2_735, 1.0_287, 7.1_934],
    [0.4_839, 0.4_851, 7.4_850],
    [0.4_089, -0.1_267, 5.5_019],
    [1.4_391, 0.1_614, 8.5_843],
    [-0.9_115, -0.1_973, 2.1_962],
    [0.3_654, 1.0_475, 7.4_858],
    [0.2_144, 0.7_515, 7.1_699],
    [0.2_013, 1.0_014, 6.5_489],
    [0.6_483, 0.2_183, 5.8_991],
    [-0.1_147, 0.2_242, 7.2_435],
    [-0.7_970, 0.8_795, 3.8_762],
    [-1.0_625, 0.6_366, 2.4_707],
    [0.5_307, 0.1_285, 5.6_883],
    [-1.2_200, 0.7_777, 1.7_252],
    [0.3_957, 0.1_076, 5.6_623],
    [-0.1_013, 0.5_989, 7.1_812],
    [2.4_482, 0.9_455, 11.2_095],
    [2.0_149, 0.6_192, 10.9_263],
    [0.2_012, 0.2_611, 5.4_631],
]

UpperCAmelCase__			 =	[
    -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()

			UpperCAmelCase__			 =	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:
						UpperCAmelCase__			 =	[]
						for i in range(len(samples[0])):
									UpperCAmelCase__			 =	input('''value: ''').strip()
									if user_input == "q":
												break
									UpperCAmelCase__			 =	float(user_input)
									sample.insert(i, observation)
						network.sort(sample)












import math







def 						a_      (__A			)							->	bool:



					"""simple docstring"""

					if 1 < number < 4:
										# 2 and 3 are primes
										return True
					elif number < 2 or number % 2 == 0 or number % 3 == 0:
										# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
										return False

					# All primes number are in format of 6k +/- 1
					for i in range(5							,					int(math.sqrt(__A			) + 1			)							,					6			):
										if number % i == 0 or number % (i + 2) == 0:
															return False
					return True







def 						a_      (__A = 1_000							,					__A = 1_000			)							->	int:



					"""simple docstring"""
					__a				:	Optional[int]			=				[0, 0, 0]  # length, a, b
					for a in range((a_limit * -1) + 1							,					__A			):
										for b in range(2							,					__A			):
															if is_prime(__A			):
																				__a				:	Any			=				0
																				__a				:	List[str]			=				0
																				while is_prime((n**2) + (a * n) + b			):
																									count += 1
																									n += 1
																				if count > longest[0]:
																									__a				:	Any			=				[count, a, b]
					__a				:	str			=				longest[1] * longest[2]
					return ans


if __name__ == "__main__":
			print(solution(1000, 1000))





