text: """A simple loss model based on a single loss scenario with
  * label = An identifier for the scenario
  * name = A descriptive name for the scenario
  * p = Probability of occurring within one year
  * low_loss = Low loss amount
  * high_loss = High loss amount
  
  The range low_loss -> high_loss should represent the 90% confidence interval
  that the loss will fall in that range.
  
  These values are then fit to a lognormal
  distribution so that they fall at the 5% and 95% cumulative probability points.
  """
  
  #   Copyright 2019-2020 Netflix, Inc.
  #
  #   Licensed under the Apache License, Version 2.0 (the "License");
  #   you may not use this file except in compliance with the License.
  #   You may obtain a copy of the License at
  #
  #       http://www.apache.org/licenses/LICENSE-2.0
  #
  #   Unless required by applicable law or agreed to in writing, software
  #   distributed under the License is distributed on an "AS IS" BASIS,
  #   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #   See the License for the specific language governing permissions and
  #   limitations under the License.
  
  from riskquant import loss
  from riskquant.model import poisson_frequency, lognormal_magnitude
  
  
  class SimpleLoss(loss.Loss):
      def __init__(self, label, name, frequency, low_loss, high_loss):
          self.label = label
          self.name = name
          self.frequency = frequency
          self.low_loss = low_loss
          self.high_loss = high_loss
          super(SimpleLoss, self).__init__(
              poisson_frequency.PoissonFrequency(frequency),
              lognormal_magnitude.LognormalMagnitude(low_loss, high_loss))
  
  