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#!/usr/bin/env python
import openturns as ot
import persalys
Study_0 = persalys.Study("Study_0")
persalys.Study.Add(Study_0)
# variables
dist_z0 = ot.Uniform(100, 150)
z0 = persalys.Input("z0", 100, dist_z0, "")
dist_v0 = ot.Normal(55, 10)
v0 = persalys.Input("v0", 55, dist_v0, "")
dist_m = ot.Normal(80, 8)
m = persalys.Input("m", 80, dist_m, "")
dist_c = ot.Uniform(0, 30)
c = persalys.Input("c", 16, dist_c, "")
z1 = persalys.Output("z1", "")
z2 = persalys.Output("z2", "fake output")
inputs = [z0, v0, m, c]
outputs = [z1, z2]
# mesh model
meshModel = persalys.GridMeshModel(ot.Interval(0.0, 12.0), [20])
# Python model
code = "from math import exp\n\n"
code += "def _exec(z0,v0,m,c):\n g = 9.81\n zmin = 0.\n tau = m / c\n vinf = -m * g / c\n\n"
code += " # mesh nodes\n t = getMesh().getVertices()\n\n"
code += " z = [max(z0 + vinf * t_i[0] + tau * (v0 - vinf) * (1 - exp(-t_i[0] / tau)), zmin) for t_i in t]\n"
code += " z2 = [2*max(z0 + vinf * t_i[0] + tau * (v0 - vinf) * (1 - exp(-t_i[0] / tau)), zmin) for t_i in t]\n\n"
code += " return z, z2"
PhysicalModel_1 = persalys.PythonFieldModel(
"PhysicalModel_1", meshModel, inputs, outputs, code
)
Study_0.add(PhysicalModel_1)
# central tendency
mcAnalysis1 = persalys.FieldMonteCarloAnalysis("mcAnalysis1", PhysicalModel_1)
mcAnalysis1.setMaximumCalls(30)
Study_0.add(mcAnalysis1)
print(mcAnalysis1)
mcAnalysis1.run()
result1 = mcAnalysis1.getResult()
print("result=", result1)
print(
"eigen values=",
result1.getKarhunenLoeveResults()[0].getEigenvalues(),
result1.getKarhunenLoeveResults()[1].getEigenvalues(),
)
PhysicalModel_1.setParallel(True)
c.setStochastic(False)
mcAnalysis2 = persalys.FieldMonteCarloAnalysis("mcAnalysis2", PhysicalModel_1)
mcAnalysis2.setMaximumCalls(100)
mcAnalysis2.setMaximumElapsedTime(50)
mcAnalysis2.setBlockSize(10)
mcAnalysis2.setInterestVariables(["z2"])
Study_0.add(mcAnalysis2)
print(mcAnalysis2)
mcAnalysis2.run()
result2 = mcAnalysis2.getResult()
print("eigen values=", result2.getKarhunenLoeveResults()[0].getEigenvalues())
# export z evaluation in csv
processSample = mcAnalysis1.getResult().getProcessSample()
fieldSample = ot.Sample(0, meshModel.getMesh().getVertices().getSize())
for field in processSample:
fieldSample.add(field.getMarginal(1).asPoint())
fieldSample.exportToCSVFile("zDoe.csv")
# import DoE in DataFieldModel
dataModel = persalys.DataFieldModel("dataModel", meshModel)
dataModel.importProcessSample("zDoe.csv", persalys.Tools.Columns)
Study_0.add(dataModel)
analysis3 = persalys.FieldKarhunenLoeveAnalysis("analysis3", dataModel)
analysis3.run()
result3 = analysis3.getResult()
print(result1.getXiSamples()[0] == result3.getXiSamples()[0])
Study_0.add(analysis3)
# script
script = Study_0.getPythonScript()
print(script)
exec(script)
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