def    lowerCAmelCase_ (     __A,  __A,  __A							)     ->				int:







      '''simple docstring'''


      if len(__A							) != len(__A							):
            raise ValueError("The length of profit and weight must be same."							)
      if max_weight <= 0:
            raise ValueError("max_weight must greater than zero."							)
      if any(p < 0 for p in profit							):
            raise ValueError("Profit can not be negative."							)
      if any(w < 0 for w in weight							):
            raise ValueError("Weight can not be negative."							)

      # List created to store profit gained for the 1kg in case of each weight
      # respectively.  Calculate and append profit/weight for each element.
      UpperCAmelCase__								=  [p / w for p, w in zip(__A,  __A							)]

      # Creating a copy of the list and sorting profit/weight in ascending order
      UpperCAmelCase__								=  sorted(__A							)

      # declaring useful variables
      UpperCAmelCase__								=  len(__A							)
      UpperCAmelCase__								=  0
      UpperCAmelCase__								=  0
      UpperCAmelCase__								=  0

      # loop till the total weight do not reach max limit e.g. 15 kg and till i<length
      while limit <= max_weight and i < length:
            # flag value for encountered greatest element in sorted_profit_by_weight
            UpperCAmelCase__								=  sorted_profit_by_weight[length - i - 1]
            UpperCAmelCase__								=  profit_by_weight.index(__A							)
            UpperCAmelCase__								=  -1

            # check if the weight encountered is less than the total weight
            # encountered before.
            if max_weight - limit >= weight[index]:
                  limit += weight[index]
                  # Adding profit gained for the given weight 1 ===
                  # weight[index]/weight[index]
                  gain += 1 * profit[index]
            else:
                  # Since the weight encountered is greater than limit, therefore take the
                  # required number of remaining kgs and calculate profit for it.
                  # weight remaining / weight[index]
                  gain += (max_weight - limit) / weight[index] * profit[index]
                  break
            i += 1
      return gain


if __name__ == "__main__":
      print(
          'Input profits, weights, and then max_weight (all positive ints) separated by '
          'spaces.'
      )

      UpperCamelCase__											=					[int(x) for x in input('Input profits separated by spaces: ').split()]
      UpperCamelCase__											=					[int(x) for x in input('Input weights separated by spaces: ').split()]
      UpperCamelCase__											=					int(input('Max weight allowed: '))

      # Function Call
      calc_profit(profit, weight, max_weight)




import math
import random




def    lowerCAmelCase_ (     __A,  __A = False							)     ->				float:







      '''simple docstring'''


      if deriv:
            return value * (1 - value)
      return 1 / (1 + math.exp(-value							))


# Initial Value
UpperCamelCase__											=					0.0_2




def    lowerCAmelCase_ (     __A,  __A							)     ->				float:







      '''simple docstring'''


      UpperCAmelCase__								=  float(2 * (random.randint(1,  100							)) - 1							)

      for _ in range(__A							):
            # Forward propagation
            UpperCAmelCase__								=  sigmoid_function(INITIAL_VALUE * weight							)
            # How much did we miss?
            UpperCAmelCase__								=  (expected / 100) - layer_a
            # Error delta
            UpperCAmelCase__								=  layer_1_error * sigmoid_function(__A,  __A							)
            # Update weight
            weight += INITIAL_VALUE * layer_1_delta

      return layer_a * 100


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      UpperCamelCase__											=					int(input('Expected value: '))
      UpperCamelCase__											=					int(input('Number of propagations: '))
      print(forward_propagation(expected, number_propagations))



