2 Copyright (C) 2008-2023 EDF R&D
4 This file is part of SALOME ADAO module.
6 This library is free software; you can redistribute it and/or
7 modify it under the terms of the GNU Lesser General Public
8 License as published by the Free Software Foundation; either
9 version 2.1 of the License, or (at your option) any later version.
11 This library is distributed in the hope that it will be useful,
12 but WITHOUT ANY WARRANTY; without even the implied warranty of
13 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
14 Lesser General Public License for more details.
16 You should have received a copy of the GNU Lesser General Public
17 License along with this library; if not, write to the Free Software
18 Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
20 See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
22 Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
24 .. index:: single: MeasurementsOptimalPositioningTask
25 .. index:: single: Optimal positioning of measurements
26 .. index:: single: Measurement locations
27 .. index:: single: Measurements (Optimal positioning)
28 .. index:: single: Ensemble of simulations
29 .. index:: single: Ensemble of snapshots
30 .. index:: single: Simulations (Ensemble)
31 .. index:: single: Snapshots (Ensemble)
32 .. _section_ref_algorithm_MeasurementsOptimalPositioningTask:
34 Task algorithm "*MeasurementsOptimalPositioningTask*"
35 -----------------------------------------------------
37 .. ------------------------------------ ..
38 .. include:: snippets/Header2Algo00.rst
42 This algorithm is only available in textual user interface (TUI) and not in
43 graphical user interface (GUI).
45 .. ------------------------------------ ..
46 .. include:: snippets/Header2Algo01.rst
48 This algorithm provides optimal positioning of measurement points by an EIM
49 (Empirical Interpolation Method) analysis. These positions are determined in a
50 iterative greedy way, from a pre-existing set of state vectors (usually called
51 "snapshots" in reduced basis methodology) or obtained by a direct simulation
52 during the algorithm. Each of these state vectors are usually (but not
53 necessarily) the result :math:`\mathbf{y}` of a simulation or an observation
54 using the operator :math:`H` for a given set of parameters :math:`\mathbf{x}`.
56 There are two ways to use this algorithm:
58 #. In its simplest use, if the set of state vectors is pre-existing, it is only
59 necessary to provide it by the algorithm option "*EnsembleOfSnapshots*". It
60 is for example the case when set of states has been generated by an
61 :ref:`section_ref_algorithm_EnsembleOfSimulationGenerationTask`.
62 #. If the set of state vectors is to be obtained by simulations during the
63 course of the algorithm, then one must provide the :math:`H` simulation or
64 observation operator and the parametric :math:`\mathbf{x}` state space
65 design of experiments.
67 The sampling of the states :math:`\mathbf{x}` can be given explicitly or under
68 form of hyper-cubes, explicit or sampled according to classic distributions.
69 Beware of the size of the hyper-cube (and then to the number of computations)
70 that can be reached, it can grow quickly to be quite large.
72 It is possible to exclude a priori potential positions for optimal measurement
73 points, using the analysis variant "*lcEIM*" for a constrained positioning
76 .. ------------------------------------ ..
77 .. include:: snippets/Header2Algo02.rst
81 .. ------------------------------------ ..
82 .. include:: snippets/Header2Algo03Task.rst
84 .. include:: snippets/EnsembleOfSnapshots.rst
86 .. include:: snippets/ExcludeLocations.rst
88 .. include:: snippets/ErrorNorm.rst
90 .. include:: snippets/ErrorNormTolerance.rst
92 .. include:: snippets/MaximumNumberOfLocations.rst
94 .. include:: snippets/SampleAsExplicitHyperCube.rst
96 .. include:: snippets/SampleAsIndependantRandomVariables.rst
98 .. include:: snippets/SampleAsMinMaxStepHyperCube.rst
100 .. include:: snippets/SampleAsnUplet.rst
102 .. include:: snippets/SetDebug.rst
104 .. include:: snippets/SetSeed.rst
106 StoreSupplementaryCalculations
107 .. index:: single: StoreSupplementaryCalculations
109 *List of names*. This list indicates the names of the supplementary
110 variables, that can be available during or at the end of the algorithm, if
111 they are initially required by the user. Their avalability involves,
112 potentially, costly calculations or memory consumptions. The default is then
113 a void list, none of these variables being calculated and stored by default
114 (excepted the unconditionnal variables). The possible names are in the
115 following list (the detailed description of each named variable is given in
116 the following part of this specific algorithmic documentation, in the
117 sub-section "*Information and variables available at the end of the
119 "EnsembleOfSimulations",
127 ``{"StoreSupplementaryCalculations":["CurrentState", "Residu"]}``
129 .. include:: snippets/Variant_MOP.rst
131 .. ------------------------------------ ..
132 .. include:: snippets/Header2Algo04.rst
134 .. include:: snippets/OptimalPoints.rst
136 .. ------------------------------------ ..
137 .. include:: snippets/Header2Algo05.rst
139 .. include:: snippets/EnsembleOfSimulations.rst
141 .. include:: snippets/EnsembleOfStates.rst
143 .. include:: snippets/OptimalPoints.rst
145 .. include:: snippets/ReducedBasis.rst
147 .. include:: snippets/Residus.rst
149 .. ------------------------------------ ..
150 .. _section_ref_algorithm_MeasurementsOptimalPositioningTask_examples:
151 .. include:: snippets/Header2Algo06.rst
153 - :ref:`section_ref_algorithm_FunctionTest`
154 - :ref:`section_ref_algorithm_ParallelFunctionTest`
155 - :ref:`section_ref_algorithm_EnsembleOfSimulationGenerationTask`
157 .. ------------------------------------ ..
158 .. include:: snippets/Header2Algo07.rst