/usr/include/openturns/swig/CompositeProcess_doc.i is in libopenturns-dev 1.7-3.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | %feature("docstring") OT::CompositeProcess
"Process obtained by transformation.
Parameters
----------
fdyn : :class:`~openturns.DynamicalFunction`
A dynamical function.
inputProc : :class:`~openturns.Process`
The input process.
Notes
-----
A composite process is the image of process :math:`X: \\\\Omega \\\\times\\\\cD \\\\mapsto \\\\Rset^d` by the dynamical function :math:`f_{dyn}:\\\\cD \\\\times \\\\Rset^d \\\\rightarrow \\\\cD' \\\\times \\\\Rset^q`:
.. math::
Y = fdyn(X)
where :math:`\\\\cD \\\\in \\\\Rset^n` and :math:`\\\\cD' \\\\in \\\\Rset^p`, defined by:
.. math::
f_{dyn}(\\\\vect{t}, \\\\vect{x}) = (t'(\\\\vect{t}), v'(\\\\vect{t}, \\\\vect{x}))
with :math:`t': \\\\cD \\\\rightarrow \\\\cD'` and :math:`v': \\\\cD \\\\times \\\\Rset^d \\\\rightarrow \\\\Rset^q`.
The process :math:`Y: \\\\Omega \\\\times \\\\cD' \\\\rightarrow \\\\Rset^q` is defined on the domain :math:`\\\\cD'` associated to the mesh :math:`\\\\cM'`.
Examples
--------
Create the process X:
>>> import openturns as ot
>>> amplitude = [1.0, 1.0]
>>> scale = [0.2, 0.3]
>>> myCovModel = ot.ExponentialModel(2,amplitude,scale)
>>> myMesh = ot.IntervalMesher([100]*2).build(ot.Interval([0.0]*2, [1.0]*2))
>>> myXProcess = ot.TemporalNormalProcess(myCovModel, myMesh)
Create a spatial dynamical function :math:`g_{dyn}` associated to :math:`g: \\\\Rset^2 \\\\mapsto \\\\Rset^2` where :math:`g(x_1,x_2)= (x_1^2, x_1+x_2)`:
>>> g = ot.NumericalMathFunction(['x1', 'x2'], ['x1^2', 'x1+x2'])
>>> nSpat = 2
>>> gdyn = ot.SpatialFunction(g, nSpat)
Create the Y process :math:`Y = g_{dyn}(X)`:
>>> myYProcess = ot.CompositeProcess(gdyn, myXProcess)
Add the trend :math:`f_{trend}: \\\\Rset^2 \\\\mapsto \\\\Rset^2` where :math:`f_{trend}(x_1,x_2)= (1+2x_1, 1+3x_2^2)`:
>>> f = ot.NumericalMathFunction(['x1', 'x2'], ['1+2*x1', '1+3*x2^2'])
>>> fTrend = ot.TrendTransform(f)
Create the process :math:`Y(\\\\omega, \\\\vect{t}) = X(\\\\omega, \\\\vect{t}) + f_{trend}(\\\\vect{t})`:
>>> myYProcess2 = ot.CompositeProcess(fTrend, myXProcess)
Apply the Box Cox transformation :math:`h=(h_1,h_2): \\\\Rset\\\\mapsto \\\\Rset^2` where :math:`h_i(x) = \\\\dfrac{x^3-1}{3}`:
>>> h = ot.BoxCoxTransform([3.0, 0.0])
>>> hBoxCox = ot.SpatialFunction(h, nSpat)
Create the Y process :math:`Y = hBoxCox(X)`:
>>> myYProcess3 = ot.CompositeProcess(hBoxCox, myXProcess)"
// ---------------------------------------------------------------------
%feature("docstring") OT::CompositeProcess::getAntecedent
"Get the antecedent process.
Returns
-------
XProcess : :class:`~openturns.Process`
The process :math:`X`."
// ---------------------------------------------------------------------
%feature("docstring") OT::CompositeProcess::getFunction
"Get the dynamical function.
Returns
-------
fdyn : :class:`~openturns.DynamicalFunction`
The dynamical function :math:`f_{dyn}`."
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