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import openturns as ot
from matplotlib import pyplot as plt
from openturns.viewer import View
ot.RandomGenerator.SetSeed(0)
def flooding(X):
Hd = 3.0
Zb = 55.5
L = 5.0e3
B = 300.0
Zd = Zb + Hd
Q, Ks, Zv, Zm = X
alpha = (Zm - Zv) / L
H = (Q / (Ks * B * alpha**0.5)) ** 0.6
Zc = H + Zv
S = Zc - Zd
return [S]
myFunction = ot.PythonFunction(4, 1, flooding)
Q = ot.Gumbel(558.0, 1013.0)
Q = ot.TruncatedDistribution(Q, 0.0, ot.SpecFunc.Infinity)
Ks = ot.Normal(30.0, 7.5)
Ks = ot.TruncatedDistribution(Ks, 0.0, ot.SpecFunc.Infinity)
Zv = ot.Uniform(49.0, 51.0)
Zm = ot.Uniform(54.0, 56.0)
inputX = ot.JointDistribution([Q, Ks, Zv, Zm])
inputX.setDescription(["Q", "Ks", "Zv", "Zm"])
size = 5000
computeSO = True
inputDesign = ot.SobolIndicesExperiment(inputX, size, computeSO).generate()
outputDesign = myFunction(inputDesign)
sensitivityAnalysis = ot.SaltelliSensitivityAlgorithm(inputDesign, outputDesign, size)
graph = sensitivityAnalysis.draw()
fig = plt.figure(figsize=(8, 4))
axis = fig.add_subplot(111)
axis.set_xlim(auto=True)
View(graph, figure=fig, axes=[axis], add_legend=True)
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