File: plot_control_termination.py

package info (click to toggle)
openturns 1.26-4
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 67,708 kB
  • sloc: cpp: 261,605; python: 67,030; ansic: 4,378; javascript: 406; sh: 185; xml: 164; makefile: 101
file content (81 lines) | stat: -rw-r--r-- 2,095 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
"""
Control algorithm termination
=============================
"""

# %%
# In this examples we are going to expose ways to control the termination of optimization and simulation algorithms using callbacks.
#

# %%
import openturns as ot


# %%
# Define an event to compute a probability
myFunction = ot.SymbolicFunction(["E", "F", "L", "I"], ["-F*L^3/(3.0*E*I)"])
dim = myFunction.getInputDimension()
mean = [50.0, 1.0, 10.0, 5.0]
sigma = [1.0] * dim
R = ot.IdentityMatrix(dim)
myDistribution = ot.Normal(mean, sigma, R)
vect = ot.RandomVector(myDistribution)
output = ot.CompositeRandomVector(myFunction, vect)
myEvent = ot.ThresholdEvent(output, ot.Less(), -3.0)

# %%
# **Stop a FORM algorithm using a calls number limit**
#
# A FORM algorithm termination can be controlled by the maximum number of iterations
#
# of its underlying optimization solver, but not directly by a maximum number of evaluations.

# %%
# Create the optimization algorithm
myCobyla = ot.Cobyla()
myCobyla.setMaximumCallsNumber(400)
myCobyla.setMaximumAbsoluteError(1.0e-10)
myCobyla.setMaximumRelativeError(1.0e-10)
myCobyla.setMaximumResidualError(1.0e-10)
myCobyla.setMaximumConstraintError(1.0e-10)


# %%
# Define the stopping criterion
def stop():
    return myFunction.getCallsNumber() > 100


myCobyla.setStopCallback(stop)

# %%
# Run FORM
myCobyla.setStartingPoint(mean)
algo = ot.FORM(myCobyla, myEvent)
algo.run()
result = algo.getResult()
print("event probability:", result.getEventProbability())
print("calls number:", myFunction.getCallsNumber())

# %%
# **Stop a simulation algorithm using a time limit**
#
# Here we will create a callback to not exceed a specified simulation time.

# %%
# Create simulation
experiment = ot.MonteCarloExperiment()
algo = ot.ProbabilitySimulationAlgorithm(myEvent, experiment)
algo.setMaximumOuterSampling(1000000)
algo.setMaximumCoefficientOfVariation(-1.0)

# %%
# Define the stopping criterion
algo.setMaximumTimeDuration(0.01)

# %%
# Run the algorithm
algo.run()
result = algo.getResult()
pf = result.getProbabilityEstimate()
nCalls = myFunction.getCallsNumber()