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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
# Default dimension parameter to evaluate the model
defaultDimension = 1
inputDimension = 1
# Amplitude values
amplitude = [1.0]
# Scale values
scale = [1.0]
# Frequency values
for frequency in [0.1, 0.2]:
# Default constructor
myDefaultModel = ot.ExponentiallyDampedCosineModel()
print("myDefaultModel = ", myDefaultModel)
# Second order model with parameters
myModel = ot.ExponentiallyDampedCosineModel(scale, amplitude, frequency)
print("myModel = ", myModel)
timeValueOne = 1.0
print("covariance matrix at t = ", timeValueOne, " : ", myModel(timeValueOne))
print(
"covariance matrix at t = ",
-1.0 * timeValueOne,
" : ",
myModel(-1.0 * timeValueOne),
)
# Evaluation at time higher to check the decrease of the
# exponentiallyDampedCosine values
timeValueHigh = 15.0
print(
"covariance matrix at t = ",
timeValueHigh,
" : ",
myModel(timeValueHigh).__str__(),
)
timeGrid = ot.RegularGrid(0.0, 1.0 / 3.0, 4)
print(
"discretized covariance over the time grid=",
timeGrid,
"is=",
myModel.discretize(timeGrid),
)
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