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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
# Create a KarhunenLoeveResult
mesh = ot.IntervalMesher([9]).build(ot.Interval(-1.0, 1.0))
cov1D = ot.AbsoluteExponential([1.0])
algo = ot.KarhunenLoeveP1Algorithm(mesh, cov1D, 0.0)
algo.run()
result = algo.getResult()
projection = ot.KarhunenLoeveProjection(result)
# Construction based on a FieldFunction followed by a FieldToPointFunction
fieldFunction = ot.ValueFunction(ot.SymbolicFunction("x", "x"), mesh)
# Create an instance
myFunc = ot.FieldToPointConnection(projection, fieldFunction)
print("myFunc=", myFunc)
# Get the input and output description
print("myFunc input description=", myFunc.getInputDescription())
print("myFunc output description=", myFunc.getOutputDescription())
# Get the input and output dimension
print("myFunc input dimension=", myFunc.getInputDimension())
print("myFunc output dimension=", myFunc.getOutputDimension())
# Connection on a field
field = result.getModesAsProcessSample().computeMean()
print("field=", field)
print("myFunc(field)=", myFunc(field.getValues()))
print("called ", myFunc.getCallsNumber(), " times")
# Connection on a sample
sample = result.getModesAsProcessSample()
print("sample=", sample)
Y = myFunc(sample)
print("myFunc(sample)=", len(Y), Y.getDimension())
print("called ", myFunc.getCallsNumber(), " times")
# Construction based on a FieldToPointFunction followed by a Function
dimension = projection.getOutputDimension()
function = ot.SymbolicFunction(
ot.Description.BuildDefault(dimension, "x"),
ot.Description.BuildDefault(dimension, "x"),
)
# Create an instance
myFunc = ot.FieldToPointConnection(function, projection)
print("myFunc=", myFunc)
# Get the input and output description
print("myFunc input description=", myFunc.getInputDescription())
print("myFunc output description=", myFunc.getOutputDescription())
# Get the input and output dimension
print("myFunc input dimension=", myFunc.getInputDimension())
print("myFunc output dimension=", myFunc.getOutputDimension())
# Connection on a field
field = result.getModesAsProcessSample().computeMean()
print("field=", field)
print("myFunc(field)=", myFunc(field.getValues()))
# Get the number of calls
print("called ", myFunc.getCallsNumber(), " times")
# 2-d mesh
n = 5
indices = [n, n]
intervalMesher = ot.IntervalMesher(indices)
interval = ot.Interval([0.0] * 2, [1.0] * 2)
mesh2D = intervalMesher.build(interval)
def f2Pfunc(X):
Y = ot.Sample(X).computeMean()
return Y
field2PFunction = ot.PythonFieldToPointFunction(mesh2D, 1, 1, f2Pfunc)
fieldFunction = ot.ValueFunction(ot.SymbolicFunction(["x", "y"], ["3x"]), mesh2D)
myFunc = ot.FieldToPointConnection(field2PFunction, fieldFunction)
print("myFunc=", myFunc)
# Get the input and output description
print("myFunc input description=", myFunc.getInputDescription())
print("myFunc output description=", myFunc.getOutputDescription())
# Get the input and output dimension
print("myFunc input dimension=", myFunc.getInputDimension())
print("myFunc output dimension=", myFunc.getOutputDimension())
field = ot.Field(mesh2D, ot.Normal(2).getSample(mesh2D.getVerticesNumber()))
print("myFunc(field)=", myFunc(field))
print("called ", myFunc.getCallsNumber(), " times")
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