




import random

class 	__lowerCAmelCase			:
							def __init__(		self		:Optional[Any]	,   __magic_name__		:list[list[float]]	,   __magic_name__		:list[int]	,   __magic_name__		:float = 0.01	,   __magic_name__		:int = 1000	,   __magic_name__		:float = -1	,   ):







								'''simple docstring'''







								a		       =							sample
								if len(self.sample       ) == 0:
									raise ValueError("""Sample data can not be empty"""       )
								a		       =							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		       =							learning_rate
								a		       =							epoch_number
								a		       =							bias
								a		       =							len(__magic_name__       )
								a		       =							len(sample[0]       )  # number of columns in dataset
								a		       =							[]
							def    lowerCamelCase__							(		self		:Optional[Any]       ):







								'''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		       =							0

								while True:
									a		       =							False
									for i in range(self.number_sample       ):
										a		       =							0
										for j in range(self.col_sample + 1       ):
											a		       =							u + self.weight[j] * self.sample[i][j]
										a		       =							self.sign(__magic_name__       )
										if y != self.target[i]:
											for j in range(self.col_sample + 1       ):
												a		       =							(
												    self.weight[j]
												    + self.learning_rate
												    * (self.target[i] - y)
												    * self.sample[i][j]
												)
											a		       =							True
            # print('Epoch: \n',epoch_count)
									a		       =							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		:str	,   __magic_name__		:list[float]       ):







								'''simple docstring'''







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

								a		       =							self.sign(__magic_name__       )

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





							def    lowerCamelCase__							(		self		:int	,   __magic_name__		:float       ):







								'''simple docstring'''







								return 1 if u >= 0 else -1







__UpperCamelCase      : Union[str, Any]					      =   [
    [-0.65_08, 0.10_97, 4.00_09],
    [-1.44_92, 0.88_96, 4.40_05],
    [2.08_50, 0.68_76, 12.07_10],
    [0.26_26, 1.14_76, 7.79_85],
    [0.64_18, 1.02_34, 7.04_27],
    [0.25_69, 0.67_30, 8.32_65],
    [1.11_55, 0.60_43, 7.44_46],
    [0.09_14, 0.33_99, 7.06_77],
    [0.01_21, 0.52_56, 4.63_16],
    [-0.04_29, 0.46_60, 5.43_23],
    [0.43_40, 0.68_70, 8.22_87],
    [0.27_35, 1.02_87, 7.19_34],
    [0.48_39, 0.48_51, 7.48_50],
    [0.40_89, -0.12_67, 5.50_19],
    [1.43_91, 0.16_14, 8.58_43],
    [-0.91_15, -0.19_73, 2.19_62],
    [0.36_54, 1.04_75, 7.48_58],
    [0.21_44, 0.75_15, 7.16_99],
    [0.20_13, 1.00_14, 6.54_89],
    [0.64_83, 0.21_83, 5.89_91],
    [-0.11_47, 0.22_42, 7.24_35],
    [-0.79_70, 0.87_95, 3.87_62],
    [-1.06_25, 0.63_66, 2.47_07],
    [0.53_07, 0.12_85, 5.68_83],
    [-1.22_00, 0.77_77, 1.72_52],
    [0.39_57, 0.10_76, 5.66_23],
    [-0.10_13, 0.59_89, 7.18_12],
    [2.44_82, 0.94_55, 11.20_95],
    [2.01_49, 0.61_92, 10.92_63],
    [0.20_12, 0.26_11, 5.46_31],
]

__UpperCamelCase      : Dict					      =   [
    -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      : str					      =   Perceptron(
		    sample=samples, target=target, learning_rate=0.01, epoch_number=1_000, bias=-1
		)
		network.training()
		print("Finished training perceptron")
		print("Enter values to predict or q to exit")
		while True:
				__UpperCamelCase      : list					      =   []
				for i in range(len(samples[0])):
						__UpperCamelCase      : Optional[int]					      =   input("value: ").strip()
						if user_input == "q":
								break
						__UpperCamelCase      : Any					      =   float(user_input)
						sample.insert(i, observation)
				network.sort(sample)







import math





def 	__A	(			__lowerCamelCase					)   -> bool:

	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(__lowerCamelCase					) + 1					)							,    6					):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True





def 	__A	(			__lowerCamelCase = 6008_5147_5143					)   -> int:

	try:
		a		       =							int(__lowerCamelCase					)
	except (TypeError, ValueError):
		raise TypeError("""Parameter n must be int or castable to int."""					)
	if n <= 0:
		raise ValueError("""Parameter n must be greater than or equal to one."""					)
	a		       =							0
	if is_prime(__lowerCamelCase					):
		return n
	while n % 2 == 0:
		n //= 2
	if is_prime(__lowerCamelCase					):
		return n
	for i in range(3							,    int(math.sqrt(__lowerCamelCase					)					) + 1							,    2					):
		if n % i == 0:
			if is_prime(n // i					):
				a		       =							n // i
				break
			elif is_prime(__lowerCamelCase					):
				a		       =							i
	return max_number


if __name__ == "__main__":
		print(F'{solution() = }')

