convergence_probability_failure
This function calculates the convergence rate of a given column in a data frame. This function is used to check the convergence of the probability of failure or reliability index.
div, m, ci_l, ci_u = convergence_probability_failure(df, column)
Input variables
Name | Description | Type |
---|---|---|
df | DataFrame containing the data with indicator function column | DataFrame |
column | Name of the column to be used for calculating the convergence rate | String |
Output variables
Name | Description | Type |
---|---|---|
div | List containing sample sizes | List |
m | List containing the mean values of the column. pf value rate | List |
ci_l | List containing the lower confidence interval values of the column | List |
ci_u | List containing the upper confidence interval values of the column | List |
Example 1
Use convergence_probability_failure
function is used to determine the convergence rate of the failure probability of the limit state function I_0.
# Libraries
import pandas as pd
pd.set_option('display.max_columns', None)
from parepy_toolbox import sampling_algorithm_structural_analysis, convergence_probability_failure
from obj_function import nowak_collins_example
# Check structural reliability
f = {'type': 'normal',
'parameters': {'mean': 40.3, 'sigma': 4.64},
'stochastic variable': False,
}
p = {'type': 'gumbel max',
'parameters': {'mean': 10.2, 'sigma': 1.12},
'stochastic variable': False,
}
w = {'type': 'lognormal',
'parameters': {'mean': 0.25, 'sigma': 0.025},
'stochastic variable': False,
}
var = [f, p, w]
setup = {
'number of samples': 100000,
'numerical model': {'model sampling': 'mcs'},
'variables settings': var,
'number of state limit functions or constraints': 1,
'none variable': None,
'objective function': nowak_collins_example,
'name simulation': 'nowak_collins_example',
}
results, pf, beta = sampling_algorithm_structural_analysis(setup)
# Convergence rate
x, m, l, u = convergence_probability_failure(results, 'I_0')
We can construct the convergence rate chart using the results m
, ci_l
, and ci_u
. We using x
in x-axis.
Figure 1. Failure probability - convergence rate.