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import openturns as ot
from math import exp
from matplotlib import pyplot as plt
from openturns.viewer import View
# Create the frequency grid
fmin = 0.1
df = 0.2
N = int((10.0 - fmin) / df)
myFrequencyGrid = ot.RegularGrid(fmin, df, N)
# Spectral function
def s(f):
if f <= 5.0:
return 1.0
else:
x = f - 5.0
return exp(-2.0 * x * x)
# Create the collection of HermitianMatrix
myCollection = ot.HermitianMatrixCollection()
for k in range(N):
frequency = myFrequencyGrid.getValue(k)
matrix = ot.HermitianMatrix(1)
matrix[0, 0] = s(frequency)
myCollection.add(matrix)
# Create the spectral model
mySpectralModel = ot.UserDefinedSpectralModel(myFrequencyGrid, myCollection)
# Graph of the spectral function
x = ot.Sample(N, 2)
for k in range(N):
frequency = myFrequencyGrid.getValue(k)
x[k, 0] = frequency
value = mySpectralModel(frequency)
x[k, 1] = value[0, 0].real
# Create the curve of the spectral function
myCurve = ot.Curve(x, "UserSpectral")
# Create the graph
myGraph = ot.Graph(
"User Defined Spectral Model", "Frequency", "Spectral density value", True
)
myGraph.add(myCurve)
myGraph.setLegendPosition("upper right")
fig = plt.figure(figsize=(10, 4))
cov_axis = fig.add_subplot(111)
view = View(myGraph, figure=fig, axes=[cov_axis], add_legend=False)
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