1 # -*- coding: utf-8 -*-
3 # Copyright (C) 2008-2023 EDF R&D
5 # This library is free software; you can redistribute it and/or
6 # modify it under the terms of the GNU Lesser General Public
7 # License as published by the Free Software Foundation; either
8 # version 2.1 of the License.
10 # This library is distributed in the hope that it will be useful,
11 # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
13 # Lesser General Public License for more details.
15 # You should have received a copy of the GNU Lesser General Public
16 # License along with this library; if not, write to the Free Software
17 # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
19 # See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
21 # Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
22 "Verification d'un exemple de la documentation"
27 # ==============================================================================
28 class Test_Adao(unittest.TestCase):
32 print("""Exemple de la doc :
34 Creation detaillee d'un cas de calcul TUI ADAO
35 ++++++++++++++++++++++++++++++++++++++++++++++
36 Les deux resultats sont testes pour etre identiques.
38 from numpy import array
39 from adao import adaoBuilder
40 case = adaoBuilder.New()
41 case.set( 'AlgorithmParameters', Algorithm='3DVAR' )
42 case.set( 'Background', Vector=[0, 1, 2] )
43 case.set( 'BackgroundError', ScalarSparseMatrix=1.0 )
44 case.set( 'Observation', Vector=array([0.5, 1.5, 2.5]) )
45 case.set( 'ObservationError', DiagonalSparseMatrix='1 1 1' )
46 case.set( 'ObservationOperator', Matrix='1 0 0;0 2 0;0 0 3' )
47 case.set( 'Observer', Variable="Analysis", Template="ValuePrinter" )
50 xa = case.get("Analysis")[-1]
51 Test_Adao.results.append( xa )
55 from numpy import array
56 from adao import adaoBuilder
57 case = adaoBuilder.New()
58 case.set( 'AlgorithmParameters', Algorithm='3DVAR' )
59 case.set( 'Background', Vector=[0, 1, 2] )
60 case.set( 'BackgroundError', ScalarSparseMatrix=1.0 )
61 case.set( 'Observation', Vector=array([0.5, 1.5, 2.5]) )
62 case.set( 'ObservationError', DiagonalSparseMatrix='1 1 1' )
66 __H = numpy.diag([1.,2.,3.])
69 case.set( 'ObservationOperator',
70 OneFunction = simulation,
71 Parameters = {"DifferentialIncrement":0.01},
73 case.set( 'Observer', Variable="Analysis", Template="ValuePrinter" )
76 xa = case.get("Analysis")[-1]
77 Test_Adao.results.append( xa )
81 xa2 = Test_Adao.results.pop()
82 xa1 = Test_Adao.results.pop()
83 ecart = assertAlmostEqualArrays(xa1, xa2, places = 15)
85 print(" L'écart absolu maximal obtenu lors du test est de %.2e."%ecart)
86 print(" Les résultats obtenus sont corrects.")
89 # ==============================================================================
90 def assertAlmostEqualArrays(first, second, places=7, msg=None, delta=None):
91 "Compare two vectors, like unittest.assertAlmostEqual"
96 if ( numpy.abs(numpy.asarray(first) - numpy.asarray(second)) > float(delta) ).any():
97 raise AssertionError("%s != %s within %s places"%(first,second,delta))
99 if ( numpy.abs(numpy.asarray(first) - numpy.asarray(second)) > 10**(-int(places)) ).any():
100 raise AssertionError("%s != %s within %i places"%(first,second,places))
101 return max(abs(numpy.asarray(first) - numpy.asarray(second)))
103 # ==============================================================================
104 if __name__ == "__main__":
105 print('\nAUTODIAGNOSTIC\n')
106 sys.stderr = sys.stdout
107 unittest.main(verbosity=2)