example.py

#!/usr/bin/python -tt
# -*- coding: utf-8 -*-

# import pyre library
from pyre import *


import time
import datetime
start_time = time.time()

def example_limitstatefunction(X1,X2,X3):
    """
    example limit state function
    """
    return 1 - X2*(1000*X3)**(-1) - (X1*(200*X3)**(-1))**2


# Define a main() function.
def main():

  # Define limit state function
  # - case 1: define directly as lambda function
  #limit_state = LimitState(lambda X1,X2,X3: 1 - X2*(1000*X3)**(-1) - (X1*(200*X3)**(-1))**2)
  # - case 2: use predefined function
  limit_state = LimitState(example_limitstatefunction)

  # Set some options (optional)
  options = AnalysisOptions()
  # options.printResults(False)
  
  stochastic_model = StochasticModel()
  # Define random variables
  stochastic_model.addVariable( Lognormal('X1',500,100) )
  stochastic_model.addVariable( Normal('X2',2000,400) )
  stochastic_model.addVariable( Uniform('X3',5,0.5) )

  # If the random variables are correlatet, then define a correlation matrix,
  # else no correlatin matrix is needed
  stochastic_model.setCorrelation( CorrelationMatrix([[1.0, 0.3, 0.2],
                            [0.3, 1.0, 0.2],
                            [0.2, 0.2, 1.0]]) )

  # Performe FORM analysis
  #Analysis = Form(analysis_options=options, stochastic_model=stochastic_model, limit_state=limit_state)

  # Performe Distribution analysis
  # Analysis = DistributionAnalysis(analysis_options=options, stochastic_model=stochastic_model, limit_state=limit_state)
  # Performe Crude Monte Carlo Simulation
  # Analysis = CrudeMonteCarlo(analysis_options=options, stochastic_model=stochastic_model, limit_state=limit_state)

  # Performe Importance Sampling
  # Analysis = ImportanceSampling(analysis_options=options, stochastic_model=stochastic_model, limit_state=limit_state)

  # Some single results:
  # beta = Analysis.getBeta()
  # failure = Analysis.getFailure()

  run_time = time.time() - start_time
  print str(datetime.timedelta(seconds=run_time))


  # This is the standard boilerplate that calls the main() function.
if __name__ == '__main__':
  main()