/[escript]/trunk/escriptcore/test/python/run_symbolic.py
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revision 4019 by jfenwick, Thu Oct 11 08:12:55 2012 UTC revision 4084 by jfenwick, Tue Nov 20 06:22:07 2012 UTC
# Line 78  class SymbolicTestCase(unittest.TestCase Line 78  class SymbolicTestCase(unittest.TestCase
78    
79          x=Symbol('x', (3, 2))          x=Symbol('x', (3, 2))
80          e=Evaluator(x**2, x**3, x**4, x**5)          e=Evaluator(x**2, x**3, x**4, x**5)
81          xx=numpy.array([[9.2518231214758302, -5.4150410540605654], [-1.5781869039394181, -0.36601352461017989], [6.5486813875509249, -8.6886755722383953]])          xx=numpy.array([[9.2518231214758302, -5.4150410540605654], [-1.5781869039394181, -0.36601352461017989],
82    [6.5486813875509249, -8.6886755722383953]])
83          ref=[xx**2, xx**3, xx**4, xx**5]          ref=[xx**2, xx**3, xx**4, xx**5]
84          res=e(x=xx)          res=e(x=xx)
85          for i in range(len(ref)):          for i in range(len(ref)):
# Line 111  class SymbolicTestCase(unittest.TestCase Line 112  class SymbolicTestCase(unittest.TestCase
112          x=Symbol('x', shape)          x=Symbol('x', shape)
113          y=acos(x)          y=acos(x)
114          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
115          xx=numpy.array([[-0.37568218691765387, 0.34977584999862543, -0.80869238615355665], [-0.61035116375592269, -0.45335550273935099, -0.49960450460056949], [0.60717099273041053, 0.40289325250233188, -0.60444576587503174], [-0.89811930442918819, -0.60483960658905933, -0.63278204925929105]])          xx=numpy.array([[-0.37568218691765387, 0.34977584999862543, -0.80869238615355665], [-0.61035116375592269,
116    -0.45335550273935099, -0.49960450460056949], [0.60717099273041053, 0.40289325250233188, -0.60444576587503174],
117    [-0.89811930442918819, -0.60483960658905933, -0.63278204925929105]])
118          ref=acos(xx)          ref=acos(xx)
119          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
120          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 121  class SymbolicTestCase(unittest.TestCase Line 124  class SymbolicTestCase(unittest.TestCase
124          x=Symbol('x', shape)          x=Symbol('x', shape)
125          y=acos(x)          y=acos(x)
126          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
127          xx=numpy.array([[[-0.28294591921545531, -0.87338330651803453], [-0.50966631448739208, -0.082647248089423142]], [[-0.45342151180416645, 0.36377996422283188], [0.99314106052662066, 0.72462685364781954]]])          xx=numpy.array([[[-0.28294591921545531, -0.87338330651803453], [-0.50966631448739208, -0.082647248089423142]],
128    [[-0.45342151180416645, 0.36377996422283188], [0.99314106052662066, 0.72462685364781954]]])
129          ref=acos(xx)          ref=acos(xx)
130          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
131          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 131  class SymbolicTestCase(unittest.TestCase Line 135  class SymbolicTestCase(unittest.TestCase
135          x=Symbol('x', shape)          x=Symbol('x', shape)
136          y=acos(x)          y=acos(x)
137          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
138          xx=numpy.array([[[[0.9698639936970419, 0.6837726039759382, 0.90742758798111844], [-0.97227663936751973, 0.12941312303794317, 0.34064388973836879], [-0.75153064493473032, 0.77955915027583744, -0.86217224512120127], [0.89122414332908018, 0.19241639846981062, 0.93352976903707874]], [[0.66129652297119668, 0.084581076574701264, 0.62382889555490384], [0.95478101865901732, -0.41259469992458597, 0.44151899127334437], [0.70898860844260803, 0.53380541271000181, -0.92226566444061664], [0.029474738319820615, 0.69109257408120373, 0.65679968113840981]], [[0.86106944670139396, 0.6300234583142148, 0.076880670859732714], [0.2253925237077703, 0.76923724689273043, 0.77263960256789566], [0.53028082323498582, -0.78512526886701672, 0.49519041035562483], [0.63880816755864855, 0.29687000041718359, 0.38658795117197275]], [[-0.076534653557333687, -0.3967262582044091, -0.60920407381650032], [-0.87959884137085198, 0.027639242327631708, -0.78441365752273318], [-0.6728736320700619, -0.47539626079363306, -0.16413443643547598], [-0.45357877112754674, 0.87819571510931449, -0.67962166457285433]], [[0.46475540215850364, 0.53038929855347328, 0.38533054335427375], [-0.056933414398614879, 0.87909780297773343, -0.60784012891042138], [-0.11782523852976623, 0.32841583417825904, -0.79189397256603256], [0.16815502412904237, -0.21871279026588697, -0.35147548432928799]], [[-0.13023045018721024, 0.035884880737155012, -0.66955208894774043], [-0.4807859528270737, -0.51316577202791391, 0.36601609262240298], [0.91360389271710862, -0.64791045153437898, 0.19751409598025171], [0.97667411471292342, -0.84263066888080251, -0.46191358772467117]]], [[[-0.55350843875470956, 0.21770206487016952, 0.68727230392019445], [-0.50609180103825424, 0.68825091403321026, -0.7760339154688991], [-0.46193558256344125, 0.11789372150431743, -0.74085434055396937], [0.56848212359494266, -0.10376746859901886, -0.010021864289275761]], [[0.93048623596253388, 0.19148360464509762, -0.79925004487412599], [0.48480498404063566, 0.25393078928193069, 0.51222681362263045], [0.72310425057996586, 0.44717754486239314, 0.16741059458654095], [-0.20555454230013925, 0.63872811821577735, -0.34919818535405667]], [[0.70110068908338463, -0.38126175940887674, 0.70159062182272502], [0.052641384763922661, 0.16786429825581717, -0.14733654537642482], [0.60386749029708264, 0.8529942795078016, -0.46948405188166675], [-0.92077654666794828, 0.16169780784958543, -0.2030650375519758]], [[0.36750882282830855, -0.4359578151446144, 0.35912842832970782], [0.93699953036917893, 0.97654834215823794, -0.68367197487413156], [-0.30295985288220306, -0.40941499606856757, -0.94908608296417718], [-0.64059055491426808, 0.90284530756180836, 0.55061631301733427]], [[0.53295709723999352, -0.71116893562367367, -0.58471862851176715], [0.52375462400044159, 0.51461672037330386, 0.26483541966586177], [0.19896875118278379, 0.25198231321156705, 0.79292931653054155], [-0.17621633454316732, -0.33325927293358903, -0.076981041753686918]], [[-0.26658065892257654, -0.75339387717303641, 0.079831561811479768], [0.90472315300895434, -0.14365988178733358, 0.17638660656020311], [-0.53327932412847168, 0.87658604789509398, 0.49936165264109089], [-0.92816938072602495, -0.29934242401516031, -0.64588774632416901]]], [[[-0.38355843377305709, 0.78563582398487619, 0.32382887859826437], [0.59275912501572647, -0.78402355965068704, 0.62764171778814215], [-0.82237802750360101, -0.28097885679558621, 0.39572637315879389], [0.15918621805898292, -0.91447170817921886, -0.16502238896616994]], [[-0.51195619696033834, 0.076711319730985883, 0.10989025726043811], [-0.094582819535743878, 0.98170060791815494, -0.97518768279462109], [0.26496280614824497, -0.31971174173444217, -0.0096909350490550494], [-0.4231838002298538, -0.62291992635285887, -0.53553226076173854]], [[-0.99833582883762895, -0.99239226558123073, -0.78980897383771476], [-0.35394818355812951, -0.41568067535445263, -0.24120137319706592], [0.23098415690008811, 0.23058900574488961, -0.39429167965123368], [-0.65040520384228806, -0.51269216512870308, 0.26692185656325296]], [[0.16049932697272107, 0.32829773928445638, -0.95095524784147534], [0.86403210822314058, 0.70248869313527162, 0.478559297535045], [0.20887212178393688, -0.84276685154561548, 0.53338899953159813], [0.34042418198746804, -0.69470118627831257, 0.85834654145397593]], [[0.24465142369773996, -0.0053667556731387123, -0.78600963705702731], [0.81385501018918949, 0.045771927607326068, -0.0077607227734122208], [-0.68173005485970228, -0.031852333063610461, 0.33875569251682669], [0.83379653372429341, 0.82781334032487885, -0.31942053761903022]], [[-0.61390777120181661, -0.97740208556502028, 0.91610185576894643], [0.55012454593713311, -0.50211380007600082, -0.090480801507946351], [-0.49464402692937837, 0.90886554646299, 0.22650291911600795], [-0.53061207494879903, -0.054855613395369263, -0.76065777515270816]]], [[[0.53176236326759674, -0.62242500642560805, -0.55393000722339791], [0.70154449591876422, -0.62071654498640383, 0.13569263309222124], [-0.69094438993254492, -0.16841676940093997, -0.3195168638881436], [-0.89191308614526155, -0.62987357786396769, -0.70207182359669096]], [[-0.76251254075829156, -0.89540085990381613, 0.90523684171573926], [-0.87869886613999748, 0.81393545030251602, 0.12051959168250681], [0.5730084015564636, 0.85895024044720891, 0.084888272475384774], [0.12810559392423326, -0.73433637468352586, 0.19375397797704097]], [[-0.39200634144699364, -0.27469748116255488, 0.80693440427441487], [-0.51533102885391169, -0.083905779978496575, 0.76583379652294092], [0.59256287128575247, 0.9757663898417348, -0.84811182880816394], [-0.23663314288010984, 0.47289469732275236, -0.97680400334209994]], [[0.84655260410375255, -0.54409562453085858, 0.8029289207595951], [-0.96769439690341219, 0.80951596327566144, 0.022566075663047691], [-0.54845077396508923, -0.62604583144930825, -0.38508197458689453], [0.43055942936382707, 0.33545191565526977, -0.30548376107252273]], [[-0.40009263827234975, 0.13736272104150316, -0.70646692991901094], [-0.07873960687646786, -0.32245114605079528, 0.69243975538348779], [-0.15163716182844245, 0.31425769040540819, 0.12209935640047509], [0.63444587658478957, -0.40930735656533135, 0.5427556064802932]], [[-0.50794750224795671, -0.86735696196028766, 0.2259668336910452], [-0.01045378343849146, -0.48003357906858657, 0.59085313572942999], [-0.93826585091279613, -0.80422961068039833, 0.45316700325817316], [-0.44884080170125795, 0.021080459042064126, -0.79742694310000584]]], [[[-0.37634929703803133, -0.36435677308011072, -0.047421589140866471], [0.56532279889731263, -0.9677301256843851, -0.35144240500933632], [0.79247993192712163, 0.6316628128384989, -0.63222620033419896], [-0.64876375917649609, -0.96033549284807873, -0.23080965502955619]], [[0.63643164518928219, -0.83661082774574047, -0.51033612037930642], [-0.22732331709005571, -0.62599410478940221, 0.46632499504196723], [0.87235078585116699, -0.53279598404304229, 0.94628181910376252], [0.35586185162417738, -0.46061267693601993, -0.67028988378505683]], [[-0.2577884572570226, -0.13324993186931944, 0.87861212909113062], [-0.42299667637258276, 0.79034343514564087, -0.37673364574589829], [-0.69471921100553979, 0.097941387840716043, -0.47529672213699636], [-0.0630527691934335, -0.77906838973189596, 0.74999106701507157]], [[0.97743232286012405, 0.52446504043805464, 0.052557036531267087], [-0.70223910941029954, 0.34212881997278899, 0.13995878619138713], [-0.84943011272910995, -0.48392810765098049, -0.84803247155622974], [0.0065150542355560948, -0.87491406063401889, -0.53834270198323875]], [[-0.063749987050949031, 0.95285667156463605, 0.43438669676634123], [0.94125038073203871, -0.56630348520510365, 0.057499590406511869], [-0.59062834627401872, 0.26812168473300568, -0.09153769873034534], [0.7501319331741676, -0.37439330052687714, 0.48464143074284594]], [[0.33268979229742168, 0.74726793169682315, 0.027036921186866847], [-0.46212037500198311, 0.20441352644308552, 0.16484658883088943], [-0.37999391239234148, -0.33630721725795154, -0.54616203920730388], [-0.2193683558727324, 0.71838716749399123, -0.66927333500651232]]], [[[-0.80002646471787608, 0.91802088185054842, -0.25964283976295088], [-0.39721940798886202, 0.99098636136416984, 0.79196037285068854], [0.56818272938210379, -0.91793846026906722, 0.17647057804356692], [-0.075656004171821056, 0.5320883413093358, 0.59845023387586949]], [[0.38067576143131676, 0.56227008435509185, -0.0067675343525166465], [0.82181986806009988, 0.58200462805504749, -0.28727971847043365], [-0.85060565716037573, -0.96122488786034466, 0.29634788021521774], [0.4896935412365504, 0.25180556342234084, -0.64796733264795203]], [[-0.65249244450565969, -0.79760790638293533, 0.357837060059226], [-0.62425749657772411, 0.36321572614140685, -0.075239548982791726], [-0.10261430349384515, 0.73778682020857156, -0.8451572925727977], [-0.15404490705401019, 0.30409875617503612, -0.64993341323761356]], [[-0.47709028022190036, -0.53054883897661709, -0.89094046524654713], [-0.14949700674790289, -0.45480636961790144, 0.11198808626339063], [0.22710172582033716, 0.77767159491805393, -0.84553933847096219], [-0.29051950700472418, -0.71835822266783977, -0.21738708175396226]], [[0.5393057866871358, 0.23973330786728941, 0.10686108397635663], [-0.19221190383674047, 0.095173732476013351, 0.68770744950220686], [-0.37251953689431949, 0.11948226430709274, 0.47525628456678048], [0.88178969567661425, -0.85649316785802321, 0.9167561289501529]], [[-0.2812308369877583, 0.0043126017498942293, 0.89518002369774519], [-0.46527866855928113, 0.15331038774092076, 0.43046177301164268], [-0.75811258328949749, 0.038368298715327542, -0.89770359937192357], [0.86073358749110196, -0.93249409969206787, -0.36845812863748328]]]])          xx=numpy.array([[[[0.9698639936970419, 0.6837726039759382, 0.90742758798111844], [-0.97227663936751973,
139    0.12941312303794317, 0.34064388973836879], [-0.75153064493473032, 0.77955915027583744, -0.86217224512120127],
140    [0.89122414332908018, 0.19241639846981062, 0.93352976903707874]], [[0.66129652297119668, 0.084581076574701264,
141    0.62382889555490384], [0.95478101865901732, -0.41259469992458597, 0.44151899127334437], [0.70898860844260803,
142    0.53380541271000181, -0.92226566444061664], [0.029474738319820615, 0.69109257408120373, 0.65679968113840981]],
143    [[0.86106944670139396, 0.6300234583142148, 0.076880670859732714], [0.2253925237077703, 0.76923724689273043,
144    0.77263960256789566], [0.53028082323498582, -0.78512526886701672, 0.49519041035562483], [0.63880816755864855,
145    0.29687000041718359, 0.38658795117197275]], [[-0.076534653557333687, -0.3967262582044091, -0.60920407381650032],
146    [-0.87959884137085198, 0.027639242327631708, -0.78441365752273318], [-0.6728736320700619, -0.47539626079363306,
147    -0.16413443643547598], [-0.45357877112754674, 0.87819571510931449, -0.67962166457285433]], [[0.46475540215850364,
148    0.53038929855347328, 0.38533054335427375], [-0.056933414398614879, 0.87909780297773343, -0.60784012891042138],
149    [-0.11782523852976623, 0.32841583417825904, -0.79189397256603256], [0.16815502412904237, -0.21871279026588697,
150    -0.35147548432928799]], [[-0.13023045018721024, 0.035884880737155012, -0.66955208894774043], [-0.4807859528270737,
151    -0.51316577202791391, 0.36601609262240298], [0.91360389271710862, -0.64791045153437898, 0.19751409598025171],
152    [0.97667411471292342, -0.84263066888080251, -0.46191358772467117]]], [[[-0.55350843875470956, 0.21770206487016952,
153    0.68727230392019445], [-0.50609180103825424, 0.68825091403321026, -0.7760339154688991], [-0.46193558256344125,
154    0.11789372150431743, -0.74085434055396937], [0.56848212359494266, -0.10376746859901886, -0.010021864289275761]],
155    [[0.93048623596253388, 0.19148360464509762, -0.79925004487412599], [0.48480498404063566, 0.25393078928193069,
156    0.51222681362263045], [0.72310425057996586, 0.44717754486239314, 0.16741059458654095], [-0.20555454230013925,
157    0.63872811821577735, -0.34919818535405667]], [[0.70110068908338463, -0.38126175940887674, 0.70159062182272502],
158    [0.052641384763922661, 0.16786429825581717, -0.14733654537642482], [0.60386749029708264, 0.8529942795078016,
159    -0.46948405188166675], [-0.92077654666794828, 0.16169780784958543, -0.2030650375519758]], [[0.36750882282830855,
160    -0.4359578151446144, 0.35912842832970782], [0.93699953036917893, 0.97654834215823794, -0.68367197487413156],
161    [-0.30295985288220306, -0.40941499606856757, -0.94908608296417718], [-0.64059055491426808, 0.90284530756180836,
162    0.55061631301733427]], [[0.53295709723999352, -0.71116893562367367, -0.58471862851176715], [0.52375462400044159,
163    0.51461672037330386, 0.26483541966586177], [0.19896875118278379, 0.25198231321156705, 0.79292931653054155],
164    [-0.17621633454316732, -0.33325927293358903, -0.076981041753686918]], [[-0.26658065892257654, -0.75339387717303641,
165    0.079831561811479768], [0.90472315300895434, -0.14365988178733358, 0.17638660656020311], [-0.53327932412847168,
166    0.87658604789509398, 0.49936165264109089], [-0.92816938072602495, -0.29934242401516031, -0.64588774632416901]]],
167    [[[-0.38355843377305709, 0.78563582398487619, 0.32382887859826437], [0.59275912501572647, -0.78402355965068704,
168    0.62764171778814215], [-0.82237802750360101, -0.28097885679558621, 0.39572637315879389], [0.15918621805898292,
169    -0.91447170817921886, -0.16502238896616994]], [[-0.51195619696033834, 0.076711319730985883, 0.10989025726043811],
170    [-0.094582819535743878, 0.98170060791815494, -0.97518768279462109], [0.26496280614824497, -0.31971174173444217,
171    -0.0096909350490550494], [-0.4231838002298538, -0.62291992635285887, -0.53553226076173854]], [[-0.99833582883762895,
172    -0.99239226558123073, -0.78980897383771476], [-0.35394818355812951, -0.41568067535445263, -0.24120137319706592],
173    [0.23098415690008811, 0.23058900574488961, -0.39429167965123368], [-0.65040520384228806, -0.51269216512870308,
174    0.26692185656325296]], [[0.16049932697272107, 0.32829773928445638, -0.95095524784147534], [0.86403210822314058,
175    0.70248869313527162, 0.478559297535045], [0.20887212178393688, -0.84276685154561548, 0.53338899953159813],
176    [0.34042418198746804, -0.69470118627831257, 0.85834654145397593]], [[0.24465142369773996, -0.0053667556731387123,
177    -0.78600963705702731], [0.81385501018918949, 0.045771927607326068, -0.0077607227734122208], [-0.68173005485970228,
178    -0.031852333063610461, 0.33875569251682669], [0.83379653372429341, 0.82781334032487885, -0.31942053761903022]],
179    [[-0.61390777120181661, -0.97740208556502028, 0.91610185576894643], [0.55012454593713311, -0.50211380007600082,
180    -0.090480801507946351], [-0.49464402692937837, 0.90886554646299, 0.22650291911600795], [-0.53061207494879903,
181    -0.054855613395369263, -0.76065777515270816]]], [[[0.53176236326759674, -0.62242500642560805, -0.55393000722339791],
182    [0.70154449591876422, -0.62071654498640383, 0.13569263309222124], [-0.69094438993254492, -0.16841676940093997,
183    -0.3195168638881436], [-0.89191308614526155, -0.62987357786396769, -0.70207182359669096]], [[-0.76251254075829156,
184    -0.89540085990381613, 0.90523684171573926], [-0.87869886613999748, 0.81393545030251602, 0.12051959168250681],
185    [0.5730084015564636, 0.85895024044720891, 0.084888272475384774], [0.12810559392423326, -0.73433637468352586,
186    0.19375397797704097]], [[-0.39200634144699364, -0.27469748116255488, 0.80693440427441487], [-0.51533102885391169,
187    -0.083905779978496575, 0.76583379652294092], [0.59256287128575247, 0.9757663898417348, -0.84811182880816394],
188    [-0.23663314288010984, 0.47289469732275236, -0.97680400334209994]], [[0.84655260410375255, -0.54409562453085858,
189    0.8029289207595951], [-0.96769439690341219, 0.80951596327566144, 0.022566075663047691], [-0.54845077396508923,
190    -0.62604583144930825, -0.38508197458689453], [0.43055942936382707, 0.33545191565526977, -0.30548376107252273]],
191    [[-0.40009263827234975, 0.13736272104150316, -0.70646692991901094], [-0.07873960687646786, -0.32245114605079528,
192    0.69243975538348779], [-0.15163716182844245, 0.31425769040540819, 0.12209935640047509], [0.63444587658478957,
193    -0.40930735656533135, 0.5427556064802932]], [[-0.50794750224795671, -0.86735696196028766, 0.2259668336910452],
194    [-0.01045378343849146, -0.48003357906858657, 0.59085313572942999], [-0.93826585091279613, -0.80422961068039833,
195    0.45316700325817316], [-0.44884080170125795, 0.021080459042064126, -0.79742694310000584]]], [[[-0.37634929703803133,
196    -0.36435677308011072, -0.047421589140866471], [0.56532279889731263, -0.9677301256843851, -0.35144240500933632],
197    [0.79247993192712163, 0.6316628128384989, -0.63222620033419896], [-0.64876375917649609, -0.96033549284807873,
198    -0.23080965502955619]], [[0.63643164518928219, -0.83661082774574047, -0.51033612037930642], [-0.22732331709005571,
199    -0.62599410478940221, 0.46632499504196723], [0.87235078585116699, -0.53279598404304229, 0.94628181910376252],
200    [0.35586185162417738, -0.46061267693601993, -0.67028988378505683]], [[-0.2577884572570226, -0.13324993186931944,
201    0.87861212909113062], [-0.42299667637258276, 0.79034343514564087, -0.37673364574589829], [-0.69471921100553979,
202    0.097941387840716043, -0.47529672213699636], [-0.0630527691934335, -0.77906838973189596, 0.74999106701507157]],
203    [[0.97743232286012405, 0.52446504043805464, 0.052557036531267087], [-0.70223910941029954, 0.34212881997278899,
204    0.13995878619138713], [-0.84943011272910995, -0.48392810765098049, -0.84803247155622974], [0.0065150542355560948,
205    -0.87491406063401889, -0.53834270198323875]], [[-0.063749987050949031, 0.95285667156463605, 0.43438669676634123],
206    [0.94125038073203871, -0.56630348520510365, 0.057499590406511869], [-0.59062834627401872, 0.26812168473300568,
207    -0.09153769873034534], [0.7501319331741676, -0.37439330052687714, 0.48464143074284594]], [[0.33268979229742168,
208    0.74726793169682315, 0.027036921186866847], [-0.46212037500198311, 0.20441352644308552, 0.16484658883088943],
209    [-0.37999391239234148, -0.33630721725795154, -0.54616203920730388], [-0.2193683558727324, 0.71838716749399123,
210    -0.66927333500651232]]], [[[-0.80002646471787608, 0.91802088185054842, -0.25964283976295088], [-0.39721940798886202,
211    0.99098636136416984, 0.79196037285068854], [0.56818272938210379, -0.91793846026906722, 0.17647057804356692],
212    [-0.075656004171821056, 0.5320883413093358, 0.59845023387586949]], [[0.38067576143131676, 0.56227008435509185,
213    -0.0067675343525166465], [0.82181986806009988, 0.58200462805504749, -0.28727971847043365], [-0.85060565716037573,
214    -0.96122488786034466, 0.29634788021521774], [0.4896935412365504, 0.25180556342234084, -0.64796733264795203]],
215    [[-0.65249244450565969, -0.79760790638293533, 0.357837060059226], [-0.62425749657772411, 0.36321572614140685,
216    -0.075239548982791726], [-0.10261430349384515, 0.73778682020857156, -0.8451572925727977], [-0.15404490705401019,
217    0.30409875617503612, -0.64993341323761356]], [[-0.47709028022190036, -0.53054883897661709, -0.89094046524654713],
218    [-0.14949700674790289, -0.45480636961790144, 0.11198808626339063], [0.22710172582033716, 0.77767159491805393,
219    -0.84553933847096219], [-0.29051950700472418, -0.71835822266783977, -0.21738708175396226]], [[0.5393057866871358,
220    0.23973330786728941, 0.10686108397635663], [-0.19221190383674047, 0.095173732476013351, 0.68770744950220686],
221    [-0.37251953689431949, 0.11948226430709274, 0.47525628456678048], [0.88178969567661425, -0.85649316785802321,
222    0.9167561289501529]], [[-0.2812308369877583, 0.0043126017498942293, 0.89518002369774519], [-0.46527866855928113,
223    0.15331038774092076, 0.43046177301164268], [-0.75811258328949749, 0.038368298715327542, -0.89770359937192357],
224    [0.86073358749110196, -0.93249409969206787, -0.36845812863748328]]]])
225          ref=acos(xx)          ref=acos(xx)
226          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
227          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 161  class SymbolicTestCase(unittest.TestCase Line 251  class SymbolicTestCase(unittest.TestCase
251          x=Symbol('x', shape)          x=Symbol('x', shape)
252          y=asin(x)          y=asin(x)
253          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
254          xx=numpy.array([[0.56634296783306604, 0.037805628085990195, -0.57469140462117219, -0.30438670067179352, 0.041456806103785215], [0.40789838857518612, 0.12260000792836978, -0.10403114180169171, 0.21312345417816214, 0.26231205267127322], [0.36261359461200882, 0.88723883233865397, -0.62745800606911351, -0.57613437801666034, -0.5425382866399604], [0.46387588603562158, -0.85284525665191624, -0.21503031045810395, -0.014771027999943342, 0.059429031543783983], [0.26003868713177258, -0.75725385670275114, 0.0083671406201912824, -0.73448123821531119, 0.6341620118378164], [0.66733319694134541, -0.16796095486269813, 0.78372713738320754, -0.74613864128829999, -0.52712917854103369]])          xx=numpy.array([[0.56634296783306604, 0.037805628085990195, -0.57469140462117219, -0.30438670067179352,
255    0.041456806103785215], [0.40789838857518612, 0.12260000792836978, -0.10403114180169171, 0.21312345417816214,
256    0.26231205267127322], [0.36261359461200882, 0.88723883233865397, -0.62745800606911351, -0.57613437801666034,
257    -0.5425382866399604], [0.46387588603562158, -0.85284525665191624, -0.21503031045810395, -0.014771027999943342,
258    0.059429031543783983], [0.26003868713177258, -0.75725385670275114, 0.0083671406201912824, -0.73448123821531119,
259    0.6341620118378164], [0.66733319694134541, -0.16796095486269813, 0.78372713738320754, -0.74613864128829999,
260    -0.52712917854103369]])
261          ref=asin(xx)          ref=asin(xx)
262          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
263          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 171  class SymbolicTestCase(unittest.TestCase Line 267  class SymbolicTestCase(unittest.TestCase
267          x=Symbol('x', shape)          x=Symbol('x', shape)
268          y=asin(x)          y=asin(x)
269          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
270          xx=numpy.array([[[-0.094501833474667007, -0.55309441094429967, -0.79845169181526643, -0.47718075788077474]], [[-0.53893650589396858, 0.40619817971097305, 0.8323193433377194, -0.45748425513214586]], [[-0.27446979757932066, 0.15585816836170929, 0.17908000628525578, -0.30478315185262828]], [[-0.46563333114039285, -0.95138520727883846, 0.21982311155339862, 0.8023588658475711]]])          xx=numpy.array([[[-0.094501833474667007, -0.55309441094429967, -0.79845169181526643, -0.47718075788077474]],
271    [[-0.53893650589396858, 0.40619817971097305, 0.8323193433377194, -0.45748425513214586]], [[-0.27446979757932066,
272    0.15585816836170929, 0.17908000628525578, -0.30478315185262828]], [[-0.46563333114039285, -0.95138520727883846,
273    0.21982311155339862, 0.8023588658475711]]])
274          ref=asin(xx)          ref=asin(xx)
275          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
276          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 181  class SymbolicTestCase(unittest.TestCase Line 280  class SymbolicTestCase(unittest.TestCase
280          x=Symbol('x', shape)          x=Symbol('x', shape)
281          y=asin(x)          y=asin(x)
282          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
283          xx=numpy.array([[[[0.057716021525408445, -0.12949830236203796, 0.73380240825767729], [-0.81691890394422151, -0.52650289918927307, 0.34552929788374298], [-0.21245192113992162, -0.17161243160430972, -0.51511961260999506]], [[0.90756021579506063, -0.3107205591563913, 0.33295134258241132], [0.85370200679922514, 0.5366193189709676, -0.14274255028441996], [0.88890078056431965, 0.68562222822738672, 0.018555900167712691]], [[-0.7677210558059544, -0.42987450834181873, 0.34062555441769993], [-0.55986658192047134, 0.15201515248109487, 0.45041146571033996], [-0.5615338718338585, -0.016823107202138088, 0.75387972448354068]], [[0.49649541591284962, -0.35999032210058712, -0.038906185984071806], [-0.060990532417816157, 0.70237226968236466, -0.24468722193265968], [0.3769159898756107, -0.036594122044091959, -0.052124621375065239]], [[-0.86466788348798485, -0.98759430543087645, -0.092667065015815897], [0.50723899358724212, 0.14824318547867787, -0.91636836243450159], [-0.75941113428576323, -0.40903062862030071, -0.12642886840516221]]], [[[0.20641896211603683, 0.37030953085752882, -0.028314336414237751], [-0.7024858212833982, -0.97151210901123553, -0.49926440954650242], [0.89580677410305576, -0.051703255102513168, 0.33378884684669541]], [[0.69866737079972241, -0.075194555680634156, 0.82089277627832091], [-0.52509953409334398, -0.73815072391398506, 0.8691935555335939], [0.08322686715068417, -0.41221913620800055, -0.14739675677292707]], [[0.61836796685745554, 0.057258532063050538, 0.29646817711629558], [0.1277168091915617, -0.20905568063414237, 0.71190299719173566], [0.043137800002834403, -0.43544306961057555, -0.56880050119154912]], [[0.15363789130748984, -0.87928329129345784, 0.26228230280018416], [-0.10284743343442915, 0.26084056205453554, 0.64607086769574185], [0.39996598284453677, -0.43519684659670088, -0.74666422478079308]], [[0.94451459850895336, 0.28672311634628977, 0.890469820462791], [0.28150852647765356, 0.15920460597687747, 0.52768406334169571], [0.60989499786113188, -0.3127701449008693, -0.84694414681764907]]], [[[0.69088309678063275, -0.79357690073172571, -0.88062617029480639], [-0.3510177957761309, 0.37650805807444532, -0.44489301131961856], [-0.79698264433300481, -0.2947858634015319, 0.12179939737236545]], [[0.21472352548606888, 0.092305123063669559, 0.72862365773967452], [-0.7252024997813098, 0.40589966976130842, 0.61047021972883075], [0.68268381479533069, -0.2117854713910845, 0.16479372825960037]], [[-0.88350805916233321, -0.30369110745425987, 0.64148927354975238], [-0.15409842869327095, -0.7027962672332273, -0.9726797472599682], [0.26773083610372339, 0.86981707216870219, 0.8473443304424364]], [[0.20234644123389067, 0.95164080933576645, 0.73359703977810131], [0.82610063371896603, -0.90544532318544824, 0.050233038329991375], [0.79963014423104095, 0.72587100976899066, -0.24779234856866794]], [[-0.70795182286468683, -0.47767622395988951, -0.41990254704795249], [0.72314563407639754, 0.1984011315530918, -0.71010184351361305], [-0.10518522890243842, 0.779430085611863, -0.86796817185238195]]], [[[-0.77238710354022722, 0.67881736256439318, 0.80411363253476265], [-0.23948917098484679, 0.59349479185689868, 0.10091987770374122], [-0.58641485741372334, -0.38160458888832083, 0.34151293051834397]], [[-0.8705668303161318, -0.32899171892963719, -0.49180267630003915], [-0.78194382617690428, 0.12818271051860974, -0.20357098708991894], [-0.68478196286534532, -0.79382378836099554, -0.91424331527699709]], [[-0.33035665697444538, -0.042976304458228753, -0.08120501312507189], [0.18235536224202509, -0.082449095168907638, 0.9737312492776431], [-0.41017758740869636, -0.1194143991466301, -0.34183530125513828]], [[-0.15576032635901416, 0.59308642123742561, 0.81860342334818514], [0.44857249004056587, 0.85907673925536554, -0.85813671882627918], [-0.31543849869426555, -0.96095095792464202, -0.38398598431621012]], [[0.53036157753360347, -0.94490191155822756, 0.77575232170974773], [0.43056993349822936, -0.17278636508625977, -0.54535280058321156], [0.13325563745299163, -0.693394107791939, 0.055462899052198589]]]])          xx=numpy.array([[[[0.057716021525408445, -0.12949830236203796, 0.73380240825767729], [-0.81691890394422151,
284    -0.52650289918927307, 0.34552929788374298], [-0.21245192113992162, -0.17161243160430972, -0.51511961260999506]],
285    [[0.90756021579506063, -0.3107205591563913, 0.33295134258241132], [0.85370200679922514, 0.5366193189709676,
286    -0.14274255028441996], [0.88890078056431965, 0.68562222822738672, 0.018555900167712691]], [[-0.7677210558059544,
287    -0.42987450834181873, 0.34062555441769993], [-0.55986658192047134, 0.15201515248109487, 0.45041146571033996],
288    [-0.5615338718338585, -0.016823107202138088, 0.75387972448354068]], [[0.49649541591284962, -0.35999032210058712,
289    -0.038906185984071806], [-0.060990532417816157, 0.70237226968236466, -0.24468722193265968], [0.3769159898756107,
290    -0.036594122044091959, -0.052124621375065239]], [[-0.86466788348798485, -0.98759430543087645, -0.092667065015815897],
291    [0.50723899358724212, 0.14824318547867787, -0.91636836243450159], [-0.75941113428576323, -0.40903062862030071,
292    -0.12642886840516221]]], [[[0.20641896211603683, 0.37030953085752882, -0.028314336414237751], [-0.7024858212833982,
293    -0.97151210901123553, -0.49926440954650242], [0.89580677410305576, -0.051703255102513168, 0.33378884684669541]],
294    [[0.69866737079972241, -0.075194555680634156, 0.82089277627832091], [-0.52509953409334398, -0.73815072391398506,
295    0.8691935555335939], [0.08322686715068417, -0.41221913620800055, -0.14739675677292707]], [[0.61836796685745554,
296    0.057258532063050538, 0.29646817711629558], [0.1277168091915617, -0.20905568063414237, 0.71190299719173566],
297    [0.043137800002834403, -0.43544306961057555, -0.56880050119154912]], [[0.15363789130748984, -0.87928329129345784,
298    0.26228230280018416], [-0.10284743343442915, 0.26084056205453554, 0.64607086769574185], [0.39996598284453677,
299    -0.43519684659670088, -0.74666422478079308]], [[0.94451459850895336, 0.28672311634628977, 0.890469820462791],
300    [0.28150852647765356, 0.15920460597687747, 0.52768406334169571], [0.60989499786113188, -0.3127701449008693,
301    -0.84694414681764907]]], [[[0.69088309678063275, -0.79357690073172571, -0.88062617029480639], [-0.3510177957761309,
302    0.37650805807444532, -0.44489301131961856], [-0.79698264433300481, -0.2947858634015319, 0.12179939737236545]],
303    [[0.21472352548606888, 0.092305123063669559, 0.72862365773967452], [-0.7252024997813098, 0.40589966976130842,
304    0.61047021972883075], [0.68268381479533069, -0.2117854713910845, 0.16479372825960037]], [[-0.88350805916233321,
305    -0.30369110745425987, 0.64148927354975238], [-0.15409842869327095, -0.7027962672332273, -0.9726797472599682],
306    [0.26773083610372339, 0.86981707216870219, 0.8473443304424364]], [[0.20234644123389067, 0.95164080933576645,
307    0.73359703977810131], [0.82610063371896603, -0.90544532318544824, 0.050233038329991375], [0.79963014423104095,
308    0.72587100976899066, -0.24779234856866794]], [[-0.70795182286468683, -0.47767622395988951, -0.41990254704795249],
309    [0.72314563407639754, 0.1984011315530918, -0.71010184351361305], [-0.10518522890243842, 0.779430085611863,
310    -0.86796817185238195]]], [[[-0.77238710354022722, 0.67881736256439318, 0.80411363253476265], [-0.23948917098484679,
311    0.59349479185689868, 0.10091987770374122], [-0.58641485741372334, -0.38160458888832083, 0.34151293051834397]],
312    [[-0.8705668303161318, -0.32899171892963719, -0.49180267630003915], [-0.78194382617690428, 0.12818271051860974,
313    -0.20357098708991894], [-0.68478196286534532, -0.79382378836099554, -0.91424331527699709]], [[-0.33035665697444538,
314    -0.042976304458228753, -0.08120501312507189], [0.18235536224202509, -0.082449095168907638, 0.9737312492776431],
315    [-0.41017758740869636, -0.1194143991466301, -0.34183530125513828]], [[-0.15576032635901416, 0.59308642123742561,
316    0.81860342334818514], [0.44857249004056587, 0.85907673925536554, -0.85813671882627918], [-0.31543849869426555,
317    -0.96095095792464202, -0.38398598431621012]], [[0.53036157753360347, -0.94490191155822756, 0.77575232170974773],
318    [0.43056993349822936, -0.17278636508625977, -0.54535280058321156], [0.13325563745299163, -0.693394107791939,
319    0.055462899052198589]]]])
320          ref=asin(xx)          ref=asin(xx)
321          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
322          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 221  class SymbolicTestCase(unittest.TestCase Line 356  class SymbolicTestCase(unittest.TestCase
356          x=Symbol('x', shape)          x=Symbol('x', shape)
357          y=atan(x)          y=atan(x)
358          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
359          xx=numpy.array([[[0.31311567842844967, -0.264660574719773, 0.043138279716100625]], [[-0.63763538643211959, -0.12071031457376002, 0.7459399913878979]], [[-0.51656973815942453, 0.15844528717305906, -0.45363944849829152]], [[0.81554506872022881, 0.32406399554069254, -0.25300113720577122]], [[0.44230550766475218, -0.95146381418271075, -0.82685975829456293]]])          xx=numpy.array([[[0.31311567842844967, -0.264660574719773, 0.043138279716100625]], [[-0.63763538643211959,
360    -0.12071031457376002, 0.7459399913878979]], [[-0.51656973815942453, 0.15844528717305906, -0.45363944849829152]],
361    [[0.81554506872022881, 0.32406399554069254, -0.25300113720577122]], [[0.44230550766475218, -0.95146381418271075,
362    -0.82685975829456293]]])
363          ref=atan(xx)          ref=atan(xx)
364          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
365          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 231  class SymbolicTestCase(unittest.TestCase Line 369  class SymbolicTestCase(unittest.TestCase
369          x=Symbol('x', shape)          x=Symbol('x', shape)
370          y=atan(x)          y=atan(x)
371          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
372          xx=numpy.array([[[[-0.66215807646287272], [0.90857105447376663], [0.25062042740113455], [-0.095192598690087005], [0.8179547721935736], [-0.52572733482612399]], [[0.32073399601918573], [0.91149209435461565], [-0.38892607664183743], [-0.82477298300384772], [-0.10874676985131093], [0.60175485711854981]], [[-0.25995382604523121], [0.30528071758531405], [-0.65680378071090839], [-0.091887506307082534], [-0.35664958452656514], [-0.75112744155853428]], [[0.61178494692087937], [0.35334759767150659], [-0.020133112539715059], [-0.3329636393021953], [-0.38148797496239983], [-0.076854477822588585]], [[0.79500012025345179], [0.41606950304631951], [-0.29298890383567544], [-0.066123991907781621], [0.8273618358441388], [0.058979895072739597]]]])          xx=numpy.array([[[[-0.66215807646287272], [0.90857105447376663], [0.25062042740113455], [-0.095192598690087005],
373    [0.8179547721935736], [-0.52572733482612399]], [[0.32073399601918573], [0.91149209435461565], [-0.38892607664183743],
374    [-0.82477298300384772], [-0.10874676985131093], [0.60175485711854981]], [[-0.25995382604523121], [0.30528071758531405],
375    [-0.65680378071090839], [-0.091887506307082534], [-0.35664958452656514], [-0.75112744155853428]], [[0.61178494692087937],
376    [0.35334759767150659], [-0.020133112539715059], [-0.3329636393021953], [-0.38148797496239983], [-0.076854477822588585]],
377    [[0.79500012025345179], [0.41606950304631951], [-0.29298890383567544], [-0.066123991907781621], [0.8273618358441388],
378    [0.058979895072739597]]]])
379          ref=atan(xx)          ref=atan(xx)
380          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
381          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 261  class SymbolicTestCase(unittest.TestCase Line 405  class SymbolicTestCase(unittest.TestCase
405          x=Symbol('x', shape)          x=Symbol('x', shape)
406          y=abs(x)          y=abs(x)
407          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
408          xx=numpy.array([[0.99031083132616637, -0.017559781029514498, 0.1615399089922378, 0.80509817818269669, -0.85022093902582818, 0.47881000856377964], [-0.18498358265294268, 0.86385463770587423, 0.4528408182463266, 0.32053834700733508, 0.78323323668801614, 0.84222731937048878]])          xx=numpy.array([[0.99031083132616637, -0.017559781029514498, 0.1615399089922378, 0.80509817818269669,
409    -0.85022093902582818, 0.47881000856377964], [-0.18498358265294268, 0.86385463770587423, 0.4528408182463266,
410    0.32053834700733508, 0.78323323668801614, 0.84222731937048878]])
411          ref=abs(xx)          ref=abs(xx)
412          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
413          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 271  class SymbolicTestCase(unittest.TestCase Line 417  class SymbolicTestCase(unittest.TestCase
417          x=Symbol('x', shape)          x=Symbol('x', shape)
418          y=abs(x)          y=abs(x)
419          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
420          xx=numpy.array([[[0.53038245271077034, 0.15634028373634679], [-0.14566088317349579, -0.92430387504548661], [0.86485801245184257, 0.91451258710846073], [-0.67077388692313367, 0.3425396887241885], [-0.12915299531467062, -0.84515163412427352]], [[-0.17440154995442758, 0.41254655372410687], [-0.56244248983035128, 0.71780251479519341], [-0.52077657278269918, -0.65440787554808533], [0.12618225766279956, -0.2825363557187941], [0.74606380643387293, -0.17788922693678377]], [[-0.020655919907325959, 0.66019132198123165], [-0.20857147602043535, 0.47516900113687233], [-0.35246808744941327, -0.13077210928452754], [0.35576809100973428, 0.58154456805135069], [0.76830979394863141, 0.24360515506673308]], [[0.77272664278528236, 0.2058585059178244], [0.27536427404951191, -0.28018371036318546], [-0.72462987561483239, -0.95954451982133571], [0.90611242106785794, -0.66419849276092213], [-0.31239883222499998, 0.3452030039902394]]])          xx=numpy.array([[[0.53038245271077034, 0.15634028373634679], [-0.14566088317349579, -0.92430387504548661],
421    [0.86485801245184257, 0.91451258710846073], [-0.67077388692313367, 0.3425396887241885], [-0.12915299531467062,
422    -0.84515163412427352]], [[-0.17440154995442758, 0.41254655372410687], [-0.56244248983035128, 0.71780251479519341],
423    [-0.52077657278269918, -0.65440787554808533], [0.12618225766279956, -0.2825363557187941], [0.74606380643387293,
424    -0.17788922693678377]], [[-0.020655919907325959, 0.66019132198123165], [-0.20857147602043535, 0.47516900113687233],
425    [-0.35246808744941327, -0.13077210928452754], [0.35576809100973428, 0.58154456805135069], [0.76830979394863141,
426    0.24360515506673308]], [[0.77272664278528236, 0.2058585059178244], [0.27536427404951191, -0.28018371036318546],
427    [-0.72462987561483239, -0.95954451982133571], [0.90611242106785794, -0.66419849276092213], [-0.31239883222499998,
428    0.3452030039902394]]])
429          ref=abs(xx)          ref=abs(xx)
430          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
431          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 281  class SymbolicTestCase(unittest.TestCase Line 435  class SymbolicTestCase(unittest.TestCase
435          x=Symbol('x', shape)          x=Symbol('x', shape)
436          y=abs(x)          y=abs(x)
437          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
438          xx=numpy.array([[[[0.49336528797761026], [0.88507912406502709], [-0.82039739585199012]], [[0.21512209674028404], [0.67653568933664299], [-0.15613763416680815]], [[-0.76449472365328641], [0.16889840387675381], [0.53742253752596469]], [[0.1595421248149862], [0.089710393917641573], [-0.63320888587500446]], [[0.83754487648720866], [0.87900606451270691], [-0.44530434715397993]]], [[[-0.042313016418267679], [-0.11679391746043866], [-0.99871724466365497]], [[-0.067108125922443085], [-0.41368649823246151], [0.73510045767960763]], [[0.5322709135003576], [-0.36518440645839712], [0.21286470886734854]], [[-0.72111547394277586], [0.24290166871673224], [-0.068189617325046692]], [[-0.93272411267838273], [-0.76489811517705952], [-0.63684337090706822]]], [[[-0.98763470890192506], [-0.52146866985667439], [-0.71621840499134803]], [[-0.90948417135004189], [0.068051675706532366], [-0.27965484696909981]], [[0.23500234455218627], [0.032018805194052646], [-0.98736077180874449]], [[-0.51745451000646092], [0.41903709932018729], [0.018184680793931651]], [[-0.96016764667564858], [0.72706365949627227], [-0.35976000226958482]]], [[[0.58849083226548027], [-0.99920338622368576], [-0.69769506230129785]], [[0.51653413721430841], [0.97132313513481106], [-0.83423684846982615]], [[0.73791643479451885], [-0.7102239467832816], [0.17187068302369291]], [[0.19423839039149748], [-0.95163872504969071], [-0.41296303043287819]], [[0.20053488824142351], [-0.61109423114398931], [0.89624170350900223]]], [[[-0.5618392655558353], [-0.85048295823139242], [-0.43065853192755643]], [[-0.31629294731062751], [0.59471784097844549], [-0.18802993577888105]], [[0.48802383148818262], [-0.7652243456355492], [0.38768425175370158]], [[-0.89592391116840164], [-0.48962523093855292], [0.31131958720382502]], [[0.42839470245229072], [-0.054372701340328788], [-0.71496329963814498]]]])          xx=numpy.array([[[[0.49336528797761026], [0.88507912406502709], [-0.82039739585199012]], [[0.21512209674028404],
439    [0.67653568933664299], [-0.15613763416680815]], [[-0.76449472365328641], [0.16889840387675381], [0.53742253752596469]],
440    [[0.1595421248149862], [0.089710393917641573], [-0.63320888587500446]], [[0.83754487648720866], [0.87900606451270691],
441    [-0.44530434715397993]]], [[[-0.042313016418267679], [-0.11679391746043866], [-0.99871724466365497]], [[-0.067108125922443085],
442    [-0.41368649823246151], [0.73510045767960763]], [[0.5322709135003576], [-0.36518440645839712], [0.21286470886734854]],
443    [[-0.72111547394277586], [0.24290166871673224], [-0.068189617325046692]], [[-0.93272411267838273], [-0.76489811517705952],
444    [-0.63684337090706822]]], [[[-0.98763470890192506], [-0.52146866985667439], [-0.71621840499134803]], [[-0.90948417135004189],
445    [0.068051675706532366], [-0.27965484696909981]], [[0.23500234455218627], [0.032018805194052646], [-0.98736077180874449]],
446    [[-0.51745451000646092], [0.41903709932018729], [0.018184680793931651]], [[-0.96016764667564858], [0.72706365949627227],
447    [-0.35976000226958482]]], [[[0.58849083226548027], [-0.99920338622368576], [-0.69769506230129785]], [[0.51653413721430841],
448    [0.97132313513481106], [-0.83423684846982615]], [[0.73791643479451885], [-0.7102239467832816], [0.17187068302369291]],
449    [[0.19423839039149748], [-0.95163872504969071], [-0.41296303043287819]], [[0.20053488824142351], [-0.61109423114398931],
450    [0.89624170350900223]]], [[[-0.5618392655558353], [-0.85048295823139242], [-0.43065853192755643]], [[-0.31629294731062751],
451    [0.59471784097844549], [-0.18802993577888105]], [[0.48802383148818262], [-0.7652243456355492], [0.38768425175370158]],
452    [[-0.89592391116840164], [-0.48962523093855292], [0.31131958720382502]], [[0.42839470245229072], [-0.054372701340328788],
453    [-0.71496329963814498]]]])
454          ref=abs(xx)          ref=abs(xx)
455          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
456          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 311  class SymbolicTestCase(unittest.TestCase Line 480  class SymbolicTestCase(unittest.TestCase
480          x=Symbol('x', shape)          x=Symbol('x', shape)
481          y=acosh(x)          y=acosh(x)
482          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
483          xx=numpy.array([[6.4559785877944842, 9.8740724270298479], [8.7200118058068696, 1.2390063653757846], [4.1282413912798077, 9.2321720965034757], [3.4337749987007511, 1.2379431819313753], [8.3269533329508043, 3.2777640368117211]])          xx=numpy.array([[6.4559785877944842, 9.8740724270298479], [8.7200118058068696, 1.2390063653757846],
484    [4.1282413912798077, 9.2321720965034757], [3.4337749987007511, 1.2379431819313753], [8.3269533329508043, 3.2777640368117211]])
485          ref=acosh(xx)          ref=acosh(xx)
486          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
487          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 321  class SymbolicTestCase(unittest.TestCase Line 491  class SymbolicTestCase(unittest.TestCase
491          x=Symbol('x', shape)          x=Symbol('x', shape)
492          y=acosh(x)          y=acosh(x)
493          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
494          xx=numpy.array([[[6.0152026903794651, 9.4585362600850704, 2.1036572249496355], [2.8641630199523775, 7.1516554653015705, 3.6103103465334292], [9.1068166972732811, 3.5409833896784288, 5.2030471034872701], [8.715781487064227, 2.680074300359339, 4.8169564939819018], [8.5846648446168174, 4.8645025977459628, 5.8352661350837334]], [[3.9064063433950449, 7.8746178953272921, 1.1760997755490548], [3.4198643147185832, 8.3703307069653334, 3.4393591569429343], [7.6862875799102675, 4.9969016062086897, 8.1585598795916567], [5.2998765478150149, 5.6029343230277977, 9.9965526645506113], [3.4902270734397449, 1.0170873066216086, 5.5996348599482175]], [[7.0397343330225652, 4.1456383609425353, 4.0890909211623754], [8.8744511247068711, 7.4334387550260335, 7.16948368809412], [9.7897326727220335, 9.4348015706735442, 5.7567890238536652], [2.6216242190098327, 5.2669144511342241, 8.3108049400860828], [8.7677570541464256, 5.8891127662816736, 4.2279499791171267]], [[7.1880173169113686, 6.5932606805263525, 9.0212619891564714], [7.3596153224034833, 1.578590752827461, 5.8919114986073637], [4.0912644414625072, 1.8474712826264885, 3.7039419780782357], [9.873057695656998, 7.9011086271931505, 2.788397711610247], [7.89746023875799, 4.0160513288162338, 7.2726330156941152]], [[5.9810703245800498, 7.5495908540274668, 9.0865369611322411], [3.8417212858625192, 8.7008795677984097, 8.7035575591937899], [2.2251450363908121, 8.229707491988183, 9.1147663508626309], [2.0576178219797132, 9.1803765730631035, 4.5556102335562043], [1.6061620436629711, 1.0235823006529636, 5.8788874665146666]]])          xx=numpy.array([[[6.0152026903794651, 9.4585362600850704, 2.1036572249496355], [2.8641630199523775, 7.1516554653015705,
495    3.6103103465334292], [9.1068166972732811, 3.5409833896784288, 5.2030471034872701], [8.715781487064227, 2.680074300359339,
496    4.8169564939819018], [8.5846648446168174, 4.8645025977459628, 5.8352661350837334]], [[3.9064063433950449, 7.8746178953272921,
497    1.1760997755490548], [3.4198643147185832, 8.3703307069653334, 3.4393591569429343], [7.6862875799102675, 4.9969016062086897,
498    8.1585598795916567], [5.2998765478150149, 5.6029343230277977, 9.9965526645506113], [3.4902270734397449, 1.0170873066216086,
499    5.5996348599482175]], [[7.0397343330225652, 4.1456383609425353, 4.0890909211623754], [8.8744511247068711, 7.4334387550260335,
500    7.16948368809412], [9.7897326727220335, 9.4348015706735442, 5.7567890238536652], [2.6216242190098327, 5.2669144511342241,
501    8.3108049400860828], [8.7677570541464256, 5.8891127662816736, 4.2279499791171267]], [[7.1880173169113686, 6.5932606805263525,
502    9.0212619891564714], [7.3596153224034833, 1.578590752827461, 5.8919114986073637], [4.0912644414625072, 1.8474712826264885,
503    3.7039419780782357], [9.873057695656998, 7.9011086271931505, 2.788397711610247], [7.89746023875799, 4.0160513288162338,
504    7.2726330156941152]], [[5.9810703245800498, 7.5495908540274668, 9.0865369611322411], [3.8417212858625192, 8.7008795677984097,
505    8.7035575591937899], [2.2251450363908121, 8.229707491988183, 9.1147663508626309], [2.0576178219797132, 9.1803765730631035,
506    4.5556102335562043], [1.6061620436629711, 1.0235823006529636, 5.8788874665146666]]])
507          ref=acosh(xx)          ref=acosh(xx)
508          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
509          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 331  class SymbolicTestCase(unittest.TestCase Line 513  class SymbolicTestCase(unittest.TestCase
513          x=Symbol('x', shape)          x=Symbol('x', shape)
514          y=acosh(x)          y=acosh(x)
515          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
516          xx=numpy.array([[[[6.9002642431462471, 4.023864450357614, 5.271788526409229], [7.0139723450119975, 6.1653596269769704, 5.2559327323743696], [8.6478227887772938, 5.2907896815249407, 5.2057400674489394], [5.2705189230730305, 9.0190721171796557, 9.9793618657528107]], [[3.933562455134846, 4.007784362411746, 7.6216242444650488], [8.5725703663362793, 1.2652674678784197, 7.7441703030551787], [7.7165518032684997, 4.7650126873619829, 2.5850262464501452], [6.8833155914907289, 7.9919723517332732, 8.7897887179453278]], [[5.1980066707815364, 2.541154945231157, 2.1467892737252123], [2.7257493124117245, 4.2151583649078805, 5.4393368030384517], [7.1662036040643011, 8.0739111106256871, 2.2559977272849565], [3.4077211357113599, 1.0492471348491872, 8.675277588885919]], [[9.7125080553737533, 7.7915487686088216, 9.0807968358432625], [8.6705584613690228, 2.9806888909998728, 4.5160099869398627], [9.5229297356795364, 6.9394074945742634, 7.3253891893115686], [7.6688411691524339, 1.5091772718757848, 6.7135945195518971]], [[7.9748696252069609, 1.5302908004157565, 1.4115856946463001], [9.7506908066032487, 5.4668572315506552, 8.2493053816589565], [7.0336967544616904, 6.2051842422522991, 8.9167252840217159], [5.6762985089722457, 4.1475364846648155, 6.7575275010101734]]], [[[6.9361900384269486, 2.3922365155613985, 4.9546244391428225], [8.9531009701795305, 8.1421929234745001, 1.0139267363999811], [5.6334675755054429, 2.8932745641361244, 4.7189566783991932], [1.4276519606158355, 2.8873223577771325, 8.8154816464954404]], [[3.1282012187302604, 7.8948446281371503, 3.8560504833636635], [8.0762601160872691, 6.0939900756504395, 6.4452354516509933], [8.5495990173820218, 6.1795197714529717, 5.2986338347436828], [2.214535963462128, 5.9392069162386152, 2.5116447675734879]], [[3.7834430371447372, 5.9663799785524319, 1.9602188302414825], [2.9756085519100832, 8.784642024338801, 8.3918357159177326], [3.8150199276222807, 1.1734225521577613, 9.0590797664235279], [9.5253601099610901, 4.9792155221349157, 2.3499938495967667]], [[7.0455879246857087, 4.7539124617840045, 6.0545684070500982], [7.5041530321558412, 6.1528933090981734, 9.6551719375838303], [4.9023787266601184, 6.2457126459977443, 5.5862069259778364], [3.4215326388663341, 7.8061449245102139, 6.856321217898155]], [[6.7400782003873365, 3.9250047999184674, 2.2308431330118959], [3.1350703675234479, 3.9484188687573445, 8.952323993579288], [6.756205405557437, 6.3246920331199092, 5.4649387271667615], [1.3831791598588217, 9.2758532673631198, 2.9547932307108322]]], [[[2.8613682329650225, 8.1996849279018669, 4.1182462559058202], [3.1771740197911855, 2.7782090288230488, 6.627436674614942], [9.2734767938740426, 6.9832877839482732, 7.7205976290513796], [5.922247827240338, 1.1604362104968517, 5.1375919901808738]], [[4.257577907777458, 1.0459645067035588, 7.2429466774308944], [2.8601030431128973, 8.4845317263783198, 6.4323666143930769], [5.0075280698945308, 4.8644150752109701, 4.6035942085214376], [3.1151044926871396, 7.4649407868000459, 8.937884567233322]], [[9.7177329651489242, 4.1760634881191949, 3.1990219643846869], [7.3220294788471341, 9.4763763739737215, 8.4084095876470126], [5.7893759341468876, 2.1261279137706861, 3.3604322810005085], [5.994719361612022, 7.9654415797896645, 7.854342597029313]], [[7.2779883650888761, 7.9151829806347669, 6.5829210097881905], [1.1843103224173512, 6.7645722754536424, 3.6602294955652868], [9.8368695002377322, 6.7934398856819156, 2.6320414102704], [9.6288134486172154, 2.74781590694433, 7.4257810599430494]], [[9.7307655383745768, 6.8192774686112925, 9.4537497966902873], [2.8228406367739041, 1.9707933630613783, 3.0269165139224476], [9.138663911257936, 6.7006152579054321, 8.8218088563980288], [9.0150127611852575, 3.6351516467497458, 7.4040798195776141]]], [[[9.4508820926167214, 9.5393542159366653, 9.3858450418607777], [3.5459159309516401, 9.0826317720128316, 7.1421709359669157], [2.5503548815978978, 5.4933120809838698, 2.4915124906451571], [8.1683190952280391, 1.8061262870076487, 7.6317026705050122]], [[1.227076544697288, 6.3630637020177199, 2.9976443165827744], [4.5845784267352592, 5.5904928711456305, 2.5525451580526219], [8.9832392463646826, 6.2895147244752607, 2.4095810316450894], [9.5669079930218484, 8.4328142698416251, 4.2156906317867069]], [[2.0166277461644753, 4.8094387993056094, 2.742288876689285], [7.3192873363389337, 2.4550446907579397, 9.3769292144489], [5.404027531065192, 3.8496499562832582, 9.5760533893514115], [4.8553154895808932, 8.1849139888325553, 9.4672408070298708]], [[8.667063905733702, 1.5623384217345557, 6.2792744981269326], [9.259867357703607, 4.6213548899944623, 5.2974148879590039], [5.2168318654410433, 5.9498795913528575, 7.3954369070388521], [5.3864341710177133, 2.553144804117415, 8.2536442117377149]], [[6.1531231141973226, 2.4092489462217079, 7.7710708019060819], [5.1563761490595308, 8.8828896437681308, 1.5293841483889452], [1.5674499880091153, 8.4372090503985646, 1.9487247984772338], [2.2233717405495255, 7.3711370391825692, 6.1206646374330873]]]])          xx=numpy.array([[[[6.9002642431462471, 4.023864450357614, 5.271788526409229], [7.0139723450119975, 6.1653596269769704,
517    5.2559327323743696], [8.6478227887772938, 5.2907896815249407, 5.2057400674489394], [5.2705189230730305, 9.0190721171796557,
518    9.9793618657528107]], [[3.933562455134846, 4.007784362411746, 7.6216242444650488], [8.5725703663362793, 1.2652674678784197,
519    7.7441703030551787], [7.7165518032684997, 4.7650126873619829, 2.5850262464501452], [6.8833155914907289, 7.9919723517332732,
520    8.7897887179453278]], [[5.1980066707815364, 2.541154945231157, 2.1467892737252123], [2.7257493124117245, 4.2151583649078805,
521    5.4393368030384517], [7.1662036040643011, 8.0739111106256871, 2.2559977272849565], [3.4077211357113599, 1.0492471348491872,
522    8.675277588885919]], [[9.7125080553737533, 7.7915487686088216, 9.0807968358432625], [8.6705584613690228, 2.9806888909998728,
523    4.5160099869398627], [9.5229297356795364, 6.9394074945742634, 7.3253891893115686], [7.6688411691524339, 1.5091772718757848,
524    6.7135945195518971]], [[7.9748696252069609, 1.5302908004157565, 1.4115856946463001], [9.7506908066032487, 5.4668572315506552,
525    8.2493053816589565], [7.0336967544616904, 6.2051842422522991, 8.9167252840217159], [5.6762985089722457, 4.1475364846648155,
526    6.7575275010101734]]], [[[6.9361900384269486, 2.3922365155613985, 4.9546244391428225], [8.9531009701795305, 8.1421929234745001,
527    1.0139267363999811], [5.6334675755054429, 2.8932745641361244, 4.7189566783991932], [1.4276519606158355, 2.8873223577771325,
528    8.8154816464954404]], [[3.1282012187302604, 7.8948446281371503, 3.8560504833636635], [8.0762601160872691, 6.0939900756504395,
529    6.4452354516509933], [8.5495990173820218, 6.1795197714529717, 5.2986338347436828], [2.214535963462128, 5.9392069162386152,
530    2.5116447675734879]], [[3.7834430371447372, 5.9663799785524319, 1.9602188302414825], [2.9756085519100832, 8.784642024338801,
531    8.3918357159177326], [3.8150199276222807, 1.1734225521577613, 9.0590797664235279], [9.5253601099610901, 4.9792155221349157,
532    2.3499938495967667]], [[7.0455879246857087, 4.7539124617840045, 6.0545684070500982], [7.5041530321558412, 6.1528933090981734,
533    9.6551719375838303], [4.9023787266601184, 6.2457126459977443, 5.5862069259778364], [3.4215326388663341, 7.8061449245102139,
534    6.856321217898155]], [[6.7400782003873365, 3.9250047999184674, 2.2308431330118959], [3.1350703675234479, 3.9484188687573445,
535    8.952323993579288], [6.756205405557437, 6.3246920331199092, 5.4649387271667615], [1.3831791598588217, 9.2758532673631198,
536    2.9547932307108322]]], [[[2.8613682329650225, 8.1996849279018669, 4.1182462559058202], [3.1771740197911855, 2.7782090288230488,
537    6.627436674614942], [9.2734767938740426, 6.9832877839482732, 7.7205976290513796], [5.922247827240338, 1.1604362104968517,
538    5.1375919901808738]], [[4.257577907777458, 1.0459645067035588, 7.2429466774308944], [2.8601030431128973, 8.4845317263783198,
539    6.4323666143930769], [5.0075280698945308, 4.8644150752109701, 4.6035942085214376], [3.1151044926871396, 7.4649407868000459,
540    8.937884567233322]], [[9.7177329651489242, 4.1760634881191949, 3.1990219643846869], [7.3220294788471341, 9.4763763739737215,
541    8.4084095876470126], [5.7893759341468876, 2.1261279137706861, 3.3604322810005085], [5.994719361612022, 7.9654415797896645,
542    7.854342597029313]], [[7.2779883650888761, 7.9151829806347669, 6.5829210097881905], [1.1843103224173512, 6.7645722754536424,
543    3.6602294955652868], [9.8368695002377322, 6.7934398856819156, 2.6320414102704], [9.6288134486172154, 2.74781590694433,
544    7.4257810599430494]], [[9.7307655383745768, 6.8192774686112925, 9.4537497966902873], [2.8228406367739041, 1.9707933630613783,
545    3.0269165139224476], [9.138663911257936, 6.7006152579054321, 8.8218088563980288], [9.0150127611852575, 3.6351516467497458,
546    7.4040798195776141]]], [[[9.4508820926167214, 9.5393542159366653, 9.3858450418607777], [3.5459159309516401, 9.0826317720128316,
547    7.1421709359669157], [2.5503548815978978, 5.4933120809838698, 2.4915124906451571], [8.1683190952280391, 1.8061262870076487,
548    7.6317026705050122]], [[1.227076544697288, 6.3630637020177199, 2.9976443165827744], [4.5845784267352592, 5.5904928711456305,
549    2.5525451580526219], [8.9832392463646826, 6.2895147244752607, 2.4095810316450894], [9.5669079930218484, 8.4328142698416251,
550    4.2156906317867069]], [[2.0166277461644753, 4.8094387993056094, 2.742288876689285], [7.3192873363389337, 2.4550446907579397,
551    9.3769292144489], [5.404027531065192, 3.8496499562832582, 9.5760533893514115], [4.8553154895808932, 8.1849139888325553,
552    9.4672408070298708]], [[8.667063905733702, 1.5623384217345557, 6.2792744981269326], [9.259867357703607, 4.6213548899944623,
553    5.2974148879590039], [5.2168318654410433, 5.9498795913528575, 7.3954369070388521], [5.3864341710177133, 2.553144804117415,
554    8.2536442117377149]], [[6.1531231141973226, 2.4092489462217079, 7.7710708019060819], [5.1563761490595308, 8.8828896437681308,
555    1.5293841483889452], [1.5674499880091153, 8.4372090503985646, 1.9487247984772338], [2.2233717405495255, 7.3711370391825692,
556    6.1206646374330873]]]])
557          ref=acosh(xx)          ref=acosh(xx)
558          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
559          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 361  class SymbolicTestCase(unittest.TestCase Line 583  class SymbolicTestCase(unittest.TestCase
583          x=Symbol('x', shape)          x=Symbol('x', shape)
584          y=asinh(x)          y=asinh(x)
585          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
586          xx=numpy.array([[-0.66884637140450121, 0.95642857948690918, 0.97890589342265844, -0.18209001755176502], [-0.80675954530781646, 0.52896241620018314, 0.5732277311269689, 0.056171723930511064], [0.45873026331250855, 0.02554950186173266, -0.89124568646838376, -0.3661412755017337], [0.93151922153251898, 0.92979819289831722, -0.34031263262653111, -0.57814103158053176], [0.029767958951282925, 0.037128253243068343, 0.40892362341839483, 0.029348138001230373]])          xx=numpy.array([[-0.66884637140450121, 0.95642857948690918, 0.97890589342265844, -0.18209001755176502],
587    [-0.80675954530781646, 0.52896241620018314, 0.5732277311269689, 0.056171723930511064], [0.45873026331250855,
588    0.02554950186173266, -0.89124568646838376, -0.3661412755017337], [0.93151922153251898, 0.92979819289831722,
589    -0.34031263262653111, -0.57814103158053176], [0.029767958951282925, 0.037128253243068343, 0.40892362341839483,
590    0.029348138001230373]])
591          ref=asinh(xx)          ref=asinh(xx)
592          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
593          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 371  class SymbolicTestCase(unittest.TestCase Line 597  class SymbolicTestCase(unittest.TestCase
597          x=Symbol('x', shape)          x=Symbol('x', shape)
598          y=asinh(x)          y=asinh(x)
599          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
600          xx=numpy.array([[[0.95342726148287715, 0.44705579758591263], [-0.89286602287873351, 0.60149771948801911], [0.59820107147864654, -0.37374102728556835], [-0.81161846073814825, -0.60436808434566602], [-0.11316307408521453, -0.51556764029260371]], [[-0.47756317482879451, -0.25124811872307351], [0.96930648565950905, 0.75531318099706857], [-0.95735145191647297, -0.54798923400914745], [-0.65134356862325582, 0.3900720896190697], [0.24321639778980408, -0.021383993041474536]], [[0.57454101227038845, 0.24902589627051896], [-0.79288075758546706, -0.19007563638541969], [-0.23064499836221564, -0.29697869891695139], [0.021230677459263436, -0.72199878849337251], [-0.071089303678373295, -0.60963555333328978]], [[-0.99370418439719299, -0.47170996058340364], [0.085212272263422761, -0.70113235935880946], [0.043596531425463825, -0.22479547967460656], [-0.38429988447838714, -0.92433253771131207], [-0.9237549325024752, -0.99106268060090574]]])          xx=numpy.array([[[0.95342726148287715, 0.44705579758591263], [-0.89286602287873351, 0.60149771948801911],
601    [0.59820107147864654, -0.37374102728556835], [-0.81161846073814825, -0.60436808434566602], [-0.11316307408521453,
602    -0.51556764029260371]], [[-0.47756317482879451, -0.25124811872307351], [0.96930648565950905, 0.75531318099706857],
603    [-0.95735145191647297, -0.54798923400914745], [-0.65134356862325582, 0.3900720896190697], [0.24321639778980408,
604    -0.021383993041474536]], [[0.57454101227038845, 0.24902589627051896], [-0.79288075758546706, -0.19007563638541969],
605    [-0.23064499836221564, -0.29697869891695139], [0.021230677459263436, -0.72199878849337251], [-0.071089303678373295,
606    -0.60963555333328978]], [[-0.99370418439719299, -0.47170996058340364], [0.085212272263422761, -0.70113235935880946],
607    [0.043596531425463825, -0.22479547967460656], [-0.38429988447838714, -0.92433253771131207], [-0.9237549325024752,
608    -0.99106268060090574]]])
609          ref=asinh(xx)          ref=asinh(xx)
610          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
611          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 381  class SymbolicTestCase(unittest.TestCase Line 615  class SymbolicTestCase(unittest.TestCase
615          x=Symbol('x', shape)          x=Symbol('x', shape)
616          y=asinh(x)          y=asinh(x)
617          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
618          xx=numpy.array([[[[0.42035098785266833, -0.50778431023644743, 0.77497133342871649, 0.95898013564231999], [-0.38143020320576237, 0.076286333225312752, -0.13375494652561426, -0.44739293000483804]], [[-0.76352681886706697, 0.92127891949297736, 0.30704945189980615, -0.28748968697773813], [-0.68053453955594922, -0.75613002920399652, 0.58405172936008976, -0.10678418707380022]]], [[[0.62013742787709591, -0.83203516435875757, -0.65185106878223076, -0.63069164595597815], [0.85972884075343625, -0.77261992521611056, -0.54638314238045393, 0.27430277098076328]], [[-0.50394921636521239, -0.10708657712524894, -0.19087121846217325, 0.76144230533489488], [-0.37416664019788737, -0.18296624941410178, 0.63774499995510614, -0.3754493090942721]]], [[[0.72572753817086277, -0.67926711836090203, -0.96403435620328115, -0.67945607439120304], [0.42838332302945203, 0.92635428184704183, 0.54173257245863593, 0.85089995038126442]], [[0.44971715025354975, 0.16810955340952227, 0.51468434244816308, 0.42709071390013564], [-0.7667508983299427, -0.096265958069885471, 0.96511656550002933, 0.92241869655573261]]], [[[0.28141629592206452, 0.5600127797928991, 0.84702576906533111, -0.14922224690750574], [-0.29230493031675175, 0.1550391898544321, 0.42865591125132507, 0.44243344042127242]], [[0.42703875689850701, 0.713699903182206, -0.76163439659338383, -0.19660579665148714], [-0.67544690133148033, 0.072200405294204684, 0.34279093259046345, 0.26649948167735582]]], [[[-0.075404402880603572, 0.3781560772876924, 0.15611360275267261, -0.61625142766162644], [-0.76377704212014952, 0.62193411570684187, 0.27371063745346702, -0.40365045645814401]], [[-0.50564045223104159, 0.22463102688835201, 0.90405914033368484, 0.15958598687633074], [0.92040176694317033, -0.27378636583346716, -0.59708389661169314, 0.56133075582385938]]], [[[0.40163511134187524, 0.80568205285203831, -0.87601680322861086, -0.0258957454599269], [-0.25306916077509101, 0.10025751053562248, -0.65445089856615968, -0.80201810243847538]], [[-0.34026461978069067, -0.66732965980653325, -0.88050450060310803, -0.28769825727349629], [-0.56522116115075072, 0.58138006376728368, 0.64141501365240794, -0.087517488663966247]]]])          xx=numpy.array([[[[0.42035098785266833, -0.50778431023644743, 0.77497133342871649, 0.95898013564231999],
619    [-0.38143020320576237, 0.076286333225312752, -0.13375494652561426, -0.44739293000483804]], [[-0.76352681886706697,
620    0.92127891949297736, 0.30704945189980615, -0.28748968697773813], [-0.68053453955594922, -0.75613002920399652,
621    0.58405172936008976, -0.10678418707380022]]], [[[0.62013742787709591, -0.83203516435875757, -0.65185106878223076,
622    -0.63069164595597815], [0.85972884075343625, -0.77261992521611056, -0.54638314238045393, 0.27430277098076328]],
623    [[-0.50394921636521239, -0.10708657712524894, -0.19087121846217325, 0.76144230533489488], [-0.37416664019788737,
624    -0.18296624941410178, 0.63774499995510614, -0.3754493090942721]]], [[[0.72572753817086277, -0.67926711836090203,
625    -0.96403435620328115, -0.67945607439120304], [0.42838332302945203, 0.92635428184704183, 0.54173257245863593,
626    0.85089995038126442]], [[0.44971715025354975, 0.16810955340952227, 0.51468434244816308, 0.42709071390013564],
627    [-0.7667508983299427, -0.096265958069885471, 0.96511656550002933, 0.92241869655573261]]], [[[0.28141629592206452,
628    0.5600127797928991, 0.84702576906533111, -0.14922224690750574], [-0.29230493031675175, 0.1550391898544321, 0.42865591125132507,
629    0.44243344042127242]], [[0.42703875689850701, 0.713699903182206, -0.76163439659338383, -0.19660579665148714],
630    [-0.67544690133148033, 0.072200405294204684, 0.34279093259046345, 0.26649948167735582]]], [[[-0.075404402880603572,
631    0.3781560772876924, 0.15611360275267261, -0.61625142766162644], [-0.76377704212014952, 0.62193411570684187,
632    0.27371063745346702, -0.40365045645814401]], [[-0.50564045223104159, 0.22463102688835201, 0.90405914033368484,
633    0.15958598687633074], [0.92040176694317033, -0.27378636583346716, -0.59708389661169314, 0.56133075582385938]]],
634    [[[0.40163511134187524, 0.80568205285203831, -0.87601680322861086, -0.0258957454599269], [-0.25306916077509101,
635    0.10025751053562248, -0.65445089856615968, -0.80201810243847538]], [[-0.34026461978069067, -0.66732965980653325,
636    -0.88050450060310803, -0.28769825727349629], [-0.56522116115075072, 0.58138006376728368, 0.64141501365240794,
637    -0.087517488663966247]]]])
638          ref=asinh(xx)          ref=asinh(xx)
639          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
640          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 401  class SymbolicTestCase(unittest.TestCase Line 654  class SymbolicTestCase(unittest.TestCase
654          x=Symbol('x', shape)          x=Symbol('x', shape)
655          y=atanh(x)          y=atanh(x)
656          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
657          xx=numpy.array([-0.23377007393415838, 0.85082427200389166, -0.3672361188323976, 0.95699236676679145, 0.32329255767895848, -0.38277477043832997])          xx=numpy.array([-0.23377007393415838, 0.85082427200389166, -0.3672361188323976, 0.95699236676679145,
658    0.32329255767895848, -0.38277477043832997])
659          ref=atanh(xx)          ref=atanh(xx)
660          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
661          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 411  class SymbolicTestCase(unittest.TestCase Line 665  class SymbolicTestCase(unittest.TestCase
665          x=Symbol('x', shape)          x=Symbol('x', shape)
666          y=atanh(x)          y=atanh(x)
667          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
668          xx=numpy.array([[-0.79604197272552435, -0.71832440603900083, -0.39219883427249691, -0.32035896428214516, -0.3605081103133152], [-0.41481333820526656, -0.54343495874232373, 0.67230662132038033, -0.42991549666194606, -0.65897349668488836], [-0.89339993133389073, 0.069763867484796904, -0.82980439581318799, -0.5295288674178884, 0.18073438514528828], [0.94879914790673658, -0.72717881858519351, 0.61680262100356154, -0.66995209943988976, 0.78626676129120687], [-0.78305955423453888, -0.98343064085155563, -0.45613714001988592, 0.60653794115268211, 0.18604295662031234]])          xx=numpy.array([[-0.79604197272552435, -0.71832440603900083, -0.39219883427249691, -0.32035896428214516,
669    -0.3605081103133152], [-0.41481333820526656, -0.54343495874232373, 0.67230662132038033, -0.42991549666194606,
670    -0.65897349668488836], [-0.89339993133389073, 0.069763867484796904, -0.82980439581318799, -0.5295288674178884,
671    0.18073438514528828], [0.94879914790673658, -0.72717881858519351, 0.61680262100356154, -0.66995209943988976,
672    0.78626676129120687], [-0.78305955423453888, -0.98343064085155563, -0.45613714001988592, 0.60653794115268211,
673    0.18604295662031234]])
674          ref=atanh(xx)          ref=atanh(xx)
675          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
676          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 421  class SymbolicTestCase(unittest.TestCase Line 680  class SymbolicTestCase(unittest.TestCase
680          x=Symbol('x', shape)          x=Symbol('x', shape)
681          y=atanh(x)          y=atanh(x)
682          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
683          xx=numpy.array([[[0.2505756275545592, 0.68329655810518286], [0.14404635298981106, -0.97489158010327293], [-0.45795183709617993, 0.60269725861900048], [-0.56039317935671473, -0.78521056827171232], [0.67544999032819764, 0.95332621782119165]], [[-0.78468048507726018, -0.46026948904662213], [0.84829780700057067, -0.27697730443881752], [-0.22353692688457061, 0.14061063558953801], [0.30143955037123038, -0.44320585604229978], [-0.6291690150903968, -0.24285738695239201]], [[-0.77983556852210456, -0.52620696091088548], [-0.41127294772127354, 0.32396529787105011], [-0.025432166978220039, 0.38112840083359845], [-0.065146631765661045, 0.91275522290649014], [-0.015944424434559457, 0.38383419672934749]], [[-0.15110516801664109, 0.65151139101479427], [0.044776428273270774, 0.46455522316971742], [-0.78650407174021386, 0.93566600454547233], [-0.74522434814606453, -0.73691439802718883], [0.46232903971263983, 0.72289315441747903]], [[-0.3231902393414845, 0.1004468233938538], [0.79506641720685378, -0.41193338584394357], [0.23282874906430351, 0.8452513793209242], [-0.80912013900539437, -0.69506120669847027], [-0.27083398868358821, 0.92235669490614591]]])          xx=numpy.array([[[0.2505756275545592, 0.68329655810518286], [0.14404635298981106, -0.97489158010327293],
684    [-0.45795183709617993, 0.60269725861900048], [-0.56039317935671473, -0.78521056827171232], [0.67544999032819764,
685    0.95332621782119165]], [[-0.78468048507726018, -0.46026948904662213], [0.84829780700057067, -0.27697730443881752],
686    [-0.22353692688457061, 0.14061063558953801], [0.30143955037123038, -0.44320585604229978], [-0.6291690150903968,
687    -0.24285738695239201]], [[-0.77983556852210456, -0.52620696091088548], [-0.41127294772127354, 0.32396529787105011],
688    [-0.025432166978220039, 0.38112840083359845], [-0.065146631765661045, 0.91275522290649014], [-0.015944424434559457,
689    0.38383419672934749]], [[-0.15110516801664109, 0.65151139101479427], [0.044776428273270774, 0.46455522316971742],
690    [-0.78650407174021386, 0.93566600454547233], [-0.74522434814606453, -0.73691439802718883], [0.46232903971263983,
691    0.72289315441747903]], [[-0.3231902393414845, 0.1004468233938538], [0.79506641720685378, -0.41193338584394357],
692    [0.23282874906430351, 0.8452513793209242], [-0.80912013900539437, -0.69506120669847027], [-0.27083398868358821,
693    0.92235669490614591]]])
694          ref=atanh(xx)          ref=atanh(xx)
695          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
696          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 431  class SymbolicTestCase(unittest.TestCase Line 700  class SymbolicTestCase(unittest.TestCase
700          x=Symbol('x', shape)          x=Symbol('x', shape)
701          y=atanh(x)          y=atanh(x)
702          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
703          xx=numpy.array([[[[0.20971387407726128], [-0.41017784562343929], [0.92526679315453864], [-0.96604154709107237], [-0.88992278920919232], [-0.89757928997071623]], [[-0.75457723070136806], [-0.73501341204175952], [-0.054691368761987436], [0.093791543801928112], [-0.65557196448384225], [0.60019825060123111]], [[0.91233787400636412], [-0.5499959984043814], [0.99155155929892902], [-0.57370124127141864], [-0.20662784579353843], [0.75787303934343209]]], [[[0.79654936662500275], [-0.85177021351041193], [0.074753415012279056], [-0.2641206004735146], [0.11153832322535107], [0.15693811273347169]], [[0.92567752234134426], [-0.63740034307395055], [0.6487343176368785], [-0.55121237686193814], [-0.21329505519365632], [-0.44929207583425201]], [[0.57155412611977097], [0.87964691865786282], [0.6989429912547942], [0.94295165141537973], [0.001920697872647148], [-0.31997829037191239]]], [[[0.92371981536863679], [0.27838116581658556], [-0.056555061033674026], [0.4530367839907754], [-0.1893874618117577], [0.13122123745622916]], [[0.15842976217953764], [0.78718258116258566], [-0.20244099933371373], [0.048729565552966925], [-0.95385898077517495], [-0.19419025340281904]], [[0.10773941848498692], [0.34618706165061508], [0.78229446272764025], [0.75433888773270041], [-0.0024978625661338238], [0.016169681368193967]]], [[[0.097120067432626689], [0.144375667094365], [0.55503650616635114], [-0.72486550462586474], [0.083630122777541782], [-0.23107141934577902]], [[-0.18535629237550233], [0.043665093574946523], [0.11993297105437462], [0.21684171172366629], [0.56209137489464411], [-0.46315310043310309]], [[0.75398735355609503], [-0.1371133044213062], [0.38495914450868796], [-0.48529675864491639], [0.26292668486649107], [-0.66091882295572746]]], [[[0.42358160022377156], [-0.7278395216188438], [0.55786821012272148], [0.1867069149576901], [0.36128983658915859], [-0.78491987064307023]], [[0.82559112350987829], [-0.096220459574556827], [0.64380135888945356], [-0.19740961614989949], [-0.29584465102393387], [-0.65885431310797382]], [[-0.35786269260535208], [0.20617314114149266], [-0.35231051940200619], [0.81419458275840273], [-0.82227518410345657], [-0.26036455326162544]]]])          xx=numpy.array([[[[0.20971387407726128], [-0.41017784562343929], [0.92526679315453864], [-0.96604154709107237],
704    [-0.88992278920919232], [-0.89757928997071623]], [[-0.75457723070136806], [-0.73501341204175952], [-0.054691368761987436],
705    [0.093791543801928112], [-0.65557196448384225], [0.60019825060123111]], [[0.91233787400636412], [-0.5499959984043814],
706    [0.99155155929892902], [-0.57370124127141864], [-0.20662784579353843], [0.75787303934343209]]], [[[0.79654936662500275],
707    [-0.85177021351041193], [0.074753415012279056], [-0.2641206004735146], [0.11153832322535107], [0.15693811273347169]],
708    [[0.92567752234134426], [-0.63740034307395055], [0.6487343176368785], [-0.55121237686193814], [-0.21329505519365632],
709    [-0.44929207583425201]], [[0.57155412611977097], [0.87964691865786282], [0.6989429912547942], [0.94295165141537973],
710    [0.001920697872647148], [-0.31997829037191239]]], [[[0.92371981536863679], [0.27838116581658556], [-0.056555061033674026],
711    [0.4530367839907754], [-0.1893874618117577], [0.13122123745622916]], [[0.15842976217953764], [0.78718258116258566],
712    [-0.20244099933371373], [0.048729565552966925], [-0.95385898077517495], [-0.19419025340281904]], [[0.10773941848498692],
713    [0.34618706165061508], [0.78229446272764025], [0.75433888773270041], [-0.0024978625661338238], [0.016169681368193967]]],
714    [[[0.097120067432626689], [0.144375667094365], [0.55503650616635114], [-0.72486550462586474], [0.083630122777541782],
715    [-0.23107141934577902]], [[-0.18535629237550233], [0.043665093574946523], [0.11993297105437462], [0.21684171172366629],
716    [0.56209137489464411], [-0.46315310043310309]], [[0.75398735355609503], [-0.1371133044213062], [0.38495914450868796],
717    [-0.48529675864491639], [0.26292668486649107], [-0.66091882295572746]]], [[[0.42358160022377156], [-0.7278395216188438],
718    [0.55786821012272148], [0.1867069149576901], [0.36128983658915859], [-0.78491987064307023]], [[0.82559112350987829],
719    [-0.096220459574556827], [0.64380135888945356], [-0.19740961614989949], [-0.29584465102393387], [-0.65885431310797382]],
720    [[-0.35786269260535208], [0.20617314114149266], [-0.35231051940200619], [0.81419458275840273], [-0.82227518410345657],
721    [-0.26036455326162544]]]])
722          ref=atanh(xx)          ref=atanh(xx)
723          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
724          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 451  class SymbolicTestCase(unittest.TestCase Line 738  class SymbolicTestCase(unittest.TestCase
738          x=Symbol('x', shape)          x=Symbol('x', shape)
739          y=cos(x)          y=cos(x)
740          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
741          xx=numpy.array([0.5766008963270195, 0.48134317621709255, -0.69099148955093792, -0.022499338398933588, 0.64495835020537018])          xx=numpy.array([0.5766008963270195, 0.48134317621709255, -0.69099148955093792, -0.022499338398933588,
742    0.64495835020537018])
743          ref=cos(xx)          ref=cos(xx)
744          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
745          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 461  class SymbolicTestCase(unittest.TestCase Line 749  class SymbolicTestCase(unittest.TestCase
749          x=Symbol('x', shape)          x=Symbol('x', shape)
750          y=cos(x)          y=cos(x)
751          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
752          xx=numpy.array([[-0.34488447281026002], [-0.2156432164514368], [-0.50709251925268961], [-0.55502876901189802], [0.14009265888634115], [-0.40613042878272054]])          xx=numpy.array([[-0.34488447281026002], [-0.2156432164514368], [-0.50709251925268961], [-0.55502876901189802],
753    [0.14009265888634115], [-0.40613042878272054]])
754          ref=cos(xx)          ref=cos(xx)
755          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
756          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 481  class SymbolicTestCase(unittest.TestCase Line 770  class SymbolicTestCase(unittest.TestCase
770          x=Symbol('x', shape)          x=Symbol('x', shape)
771          y=cos(x)          y=cos(x)
772          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
773          xx=numpy.array([[[[-0.19907982561050064, 0.30353084912481343, 0.53722096316688805, 0.84005546422152744, -0.48155631620576944, -0.74716985554050441], [-0.10945890161850658, 0.49233217846051169, 0.58288429083063154, 0.57589773334033501, 0.91347177627136134, 0.82926042076398487], [-0.45050025042105002, -0.64163758228931944, -0.11867498581464697, -0.61428226242362349, -0.5681490740142765, 0.31182676814189914]], [[-0.18640484887126574, -0.29458350247786935, 0.31021822155024448, 0.15543101368975587, 0.94372810483738601, 0.94596061691367161], [0.77981903262407393, -0.1280769420882768, -0.91507670426075371, -0.31651675886156139, -0.18515942975231714, 0.22118213876422232], [0.70080246911031452, 0.97100721922944788, 0.15232090415237343, -0.50830600844829621, -0.44299228598984564, 0.97015955714172186]]], [[[0.90052336040760483, -0.19483939885852997, -0.071995587555530705, 0.72363256342604054, -0.74660493733607658, -0.19798046685496584], [-0.97779879034256956, -0.93659194549161229, 0.55201880047182073, -0.53606579828624801, -0.29401179627649188, 0.43678927994627958], [0.083560652594002915, 0.92009008040107254, -0.97255907829479549, -0.97967421428491952, 0.60354683571489409, 0.043141832577749506]], [[0.34483546830493461, 0.57344218277388048, 0.10962111147410725, 0.37176078745001195, 0.019358457577045574, 0.78681662089181392], [-0.11148829570451269, 0.63248565232979814, 0.26641064854606356, 0.25051527613940383, 0.1645040198371428, -0.3093543217552821], [-0.35060208758737144, 0.46874322714901062, 0.82103471093154279, 0.65887801342729069, 0.57173259609581306, -0.9019359004516625]]], [[[0.52364902857070916, -0.60862693024133407, 0.7079161176390536, -0.54753370235739474, -0.16157879084751081, 0.2347369013692997], [-0.30119311422568851, -0.67693029949165817, -0.44054777013294211, -0.17595510468230091, -0.3722573761659016, 0.65659148932273137], [0.61044366119250215, -0.18092684942538462, -0.13334316545753055, 0.67273477414384941, -0.32010645014433781, -0.17380363518066]], [[-0.31265178953405304, -0.049070594061846107, 0.86846200928806128, 0.95061018332202973, 0.46629594869434898, -0.69152902591122567], [0.43872521827099686, 0.43858746674163873, 0.34767628658906014, -0.018458574573531061, 0.81758120632848064, 0.79301236650063633], [-0.82798904316023658, 0.4349709104192212, 0.023311070907567011, -0.30743832703234153, 0.13671396984233608, -0.83851956878206835]]], [[[-0.8734939357686784, 0.33732283609570723, 0.41236518066874916, -0.95055809620416776, -0.98357746987052752, 0.95104084068664041], [0.88878898254669259, -0.16911847050551576, -0.24783333440009625, 0.82208119668585744, 0.0010431798911008094, 0.0082821615019470496], [0.1396509188825692, 0.094257822276048842, -0.13228750966572345, 0.89926170217127521, 0.077787334627457128, -0.17993373580123584]], [[-0.72769901784519031, 0.73016627869730022, 0.53694019977210439, 0.51397940947350396, 0.52801017839145081, 0.074316759499168938], [-0.64851869908713899, 0.2788395070141696, -0.92092142853747871, 0.13841382648580858, 0.14670057247971569, 0.24017939247346143], [-0.53458528754962442, -0.43934782222951374, 0.79996580192339883, -0.80162215269264214, -0.028852977523383894, -0.86626759977804757]]]])          xx=numpy.array([[[[-0.19907982561050064, 0.30353084912481343, 0.53722096316688805, 0.84005546422152744,
774    -0.48155631620576944, -0.74716985554050441], [-0.10945890161850658, 0.49233217846051169, 0.58288429083063154,
775    0.57589773334033501, 0.91347177627136134, 0.82926042076398487], [-0.45050025042105002, -0.64163758228931944,
776    -0.11867498581464697, -0.61428226242362349, -0.5681490740142765, 0.31182676814189914]], [[-0.18640484887126574,
777    -0.29458350247786935, 0.31021822155024448, 0.15543101368975587, 0.94372810483738601, 0.94596061691367161],
778    [0.77981903262407393, -0.1280769420882768, -0.91507670426075371, -0.31651675886156139, -0.18515942975231714,
779    0.22118213876422232], [0.70080246911031452, 0.97100721922944788, 0.15232090415237343, -0.50830600844829621,
780    -0.44299228598984564, 0.97015955714172186]]], [[[0.90052336040760483, -0.19483939885852997, -0.071995587555530705,
781    0.72363256342604054, -0.74660493733607658, -0.19798046685496584], [-0.97779879034256956, -0.93659194549161229,
782    0.55201880047182073, -0.53606579828624801, -0.29401179627649188, 0.43678927994627958], [0.083560652594002915,
783    0.92009008040107254, -0.97255907829479549, -0.97967421428491952, 0.60354683571489409, 0.043141832577749506]],
784    [[0.34483546830493461, 0.57344218277388048, 0.10962111147410725, 0.37176078745001195, 0.019358457577045574,
785    0.78681662089181392], [-0.11148829570451269, 0.63248565232979814, 0.26641064854606356, 0.25051527613940383, 0.1645040198371428,
786    -0.3093543217552821], [-0.35060208758737144, 0.46874322714901062, 0.82103471093154279, 0.65887801342729069,
787    0.57173259609581306, -0.9019359004516625]]], [[[0.52364902857070916, -0.60862693024133407, 0.7079161176390536,
788    -0.54753370235739474, -0.16157879084751081, 0.2347369013692997], [-0.30119311422568851, -0.67693029949165817,
789    -0.44054777013294211, -0.17595510468230091, -0.3722573761659016, 0.65659148932273137], [0.61044366119250215,
790    -0.18092684942538462, -0.13334316545753055, 0.67273477414384941, -0.32010645014433781, -0.17380363518066]],
791    [[-0.31265178953405304, -0.049070594061846107, 0.86846200928806128, 0.95061018332202973, 0.46629594869434898,
792    -0.69152902591122567], [0.43872521827099686, 0.43858746674163873, 0.34767628658906014, -0.018458574573531061,
793    0.81758120632848064, 0.79301236650063633], [-0.82798904316023658, 0.4349709104192212, 0.023311070907567011,
794    -0.30743832703234153, 0.13671396984233608, -0.83851956878206835]]], [[[-0.8734939357686784, 0.33732283609570723,
795    0.41236518066874916, -0.95055809620416776, -0.98357746987052752, 0.95104084068664041], [0.88878898254669259,
796    -0.16911847050551576, -0.24783333440009625, 0.82208119668585744, 0.0010431798911008094, 0.0082821615019470496],
797    [0.1396509188825692, 0.094257822276048842, -0.13228750966572345, 0.89926170217127521, 0.077787334627457128,
798    -0.17993373580123584]], [[-0.72769901784519031, 0.73016627869730022, 0.53694019977210439, 0.51397940947350396,
799    0.52801017839145081, 0.074316759499168938], [-0.64851869908713899, 0.2788395070141696, -0.92092142853747871,
800    0.13841382648580858, 0.14670057247971569, 0.24017939247346143], [-0.53458528754962442, -0.43934782222951374,
801    0.79996580192339883, -0.80162215269264214, -0.028852977523383894, -0.86626759977804757]]]])
802          ref=cos(xx)          ref=cos(xx)
803          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
804          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 511  class SymbolicTestCase(unittest.TestCase Line 828  class SymbolicTestCase(unittest.TestCase
828          x=Symbol('x', shape)          x=Symbol('x', shape)
829          y=cosh(x)          y=cosh(x)
830          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
831          xx=numpy.array([[0.48776155430046098, 0.51838439075389875, -0.025949362624035688, 0.76367991246737388, 0.05421265821947352, 0.31818128292100778], [0.85203189225961884, -0.23088542198435102, -0.45846863645622915, 0.93382631282261341, 0.90336058939397912, 0.20142486952202332], [0.52949873270766634, -0.77221653035421634, 0.74548788516908338, -0.85171273745031595, 0.057779925121308029, -0.38021502840326993], [0.58177405371136381, 0.16088033704555493, 0.69483691557124461, 0.6756295135267214, -0.60312840314075, -0.53194963237386528], [0.12459222760988409, -0.61534279763692989, -0.53171300505442476, -0.51689144120023633, -0.84049372089324526, 0.83079152836396597], [-0.45021434764043256, 0.078051886698744966, -0.63691519882769332, 0.41482117547581998, 0.345396830355579, 0.64290867709947563]])          xx=numpy.array([[0.48776155430046098, 0.51838439075389875, -0.025949362624035688, 0.76367991246737388,
832    0.05421265821947352, 0.31818128292100778], [0.85203189225961884, -0.23088542198435102, -0.45846863645622915,
833    0.93382631282261341, 0.90336058939397912, 0.20142486952202332], [0.52949873270766634, -0.77221653035421634,
834    0.74548788516908338, -0.85171273745031595, 0.057779925121308029, -0.38021502840326993], [0.58177405371136381,
835    0.16088033704555493, 0.69483691557124461, 0.6756295135267214, -0.60312840314075, -0.53194963237386528], [0.12459222760988409,
836    -0.61534279763692989, -0.53171300505442476, -0.51689144120023633, -0.84049372089324526, 0.83079152836396597],
837    [-0.45021434764043256, 0.078051886698744966, -0.63691519882769332, 0.41482117547581998, 0.345396830355579,
838    0.64290867709947563]])
839          ref=cosh(xx)          ref=cosh(xx)
840          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
841          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 521  class SymbolicTestCase(unittest.TestCase Line 845  class SymbolicTestCase(unittest.TestCase
845          x=Symbol('x', shape)          x=Symbol('x', shape)
846          y=cosh(x)          y=cosh(x)
847          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
848          xx=numpy.array([[[0.99075905148006616, -0.556563736711716, 0.482948365904738, 0.61848063263263042], [-0.21160117123689282, 0.93380107058377382, -0.38203158244434676, 0.40818891686662773]]])          xx=numpy.array([[[0.99075905148006616, -0.556563736711716, 0.482948365904738, 0.61848063263263042],
849    [-0.21160117123689282, 0.93380107058377382, -0.38203158244434676, 0.40818891686662773]]])
850          ref=cosh(xx)          ref=cosh(xx)
851          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
852          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 531  class SymbolicTestCase(unittest.TestCase Line 856  class SymbolicTestCase(unittest.TestCase
856          x=Symbol('x', shape)          x=Symbol('x', shape)
857          y=cosh(x)          y=cosh(x)
858          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
859          xx=numpy.array([[[[0.64169029258586607, -0.39602130811642078, -0.87047269158743235, -0.70671915506067906, -0.23013892219203136, 0.051279741176573967], [-0.1815823273156254, 0.22362787424663488, 0.086531134128640774, 0.2033832711169421, -0.29460998523122828, -0.29604077185914268], [0.17918530352350981, -0.95851230588757597, 0.6089039291143532, -0.23757756476073078, -0.030912603179279685, -0.44366381486624329], [-0.069859395893596909, 0.81133536902580095, 0.10767565447357419, 0.8824504020924937, -0.65509551955715173, 0.92272691816739782], [0.74133278082055698, 0.40911929431277216, 0.1822539168616113, 0.049516641695215746, 0.30250549837342944, -0.82264380500945622]]], [[[-0.30440534124661278, 0.45772207772993267, -0.23307067348130106, -0.47299200985722356, -0.70713971065210002, 0.63657827136991219], [-0.34568231546236672, -0.82773395989784282, 0.22061734040553627, -0.44947612583105667, -0.82579704972895351, 0.046140649241088294], [-0.20114859714917932, 0.62317698558045764, 0.43257530170170533, -0.51262532825183138, 0.046601230594965681, -0.95170817307557498], [-0.80642652621113942, -0.75405757465693624, -0.534964442795683, -0.050306363307079049, 0.86603326962096205, -0.30778937685069252], [-0.87863387509688473, 0.85097807490368438, -0.25108326762247146, 0.4937910293257215, 0.056690519953803031, -0.82101973588398902]]], [[[0.17526396588556215, -0.075652957124554998, -0.69110848195606445, 0.24208861806210247, 0.24904774014376052, 0.72231925877648662], [-0.68511614182752623, 0.041250777089497426, 0.4000072972000186, -0.87266655656284309, -0.4686214701437561, 0.86214782509815513], [0.34285298245488183, -0.072857735041811811, -0.75094545378399813, -0.8164507554195588, -0.63082644422203837, 0.30213883987979173], [0.55400445993054737, 0.48543645194975871, 0.44249440951834762, 0.81459036603800894, -0.43944947288524649, -0.13212404044942572], [-0.49653039338796079, 0.82084218457531311, 0.88279263592802959, 0.69105880560957389, 0.709818852462891, 0.1525990192290636]]]])          xx=numpy.array([[[[0.64169029258586607, -0.39602130811642078, -0.87047269158743235, -0.70671915506067906,
860    -0.23013892219203136, 0.051279741176573967], [-0.1815823273156254, 0.22362787424663488, 0.086531134128640774,
861    0.2033832711169421, -0.29460998523122828, -0.29604077185914268], [0.17918530352350981, -0.95851230588757597,
862    0.6089039291143532, -0.23757756476073078, -0.030912603179279685, -0.44366381486624329], [-0.069859395893596909,
863    0.81133536902580095, 0.10767565447357419, 0.8824504020924937, -0.65509551955715173, 0.92272691816739782], [0.74133278082055698,
864    0.40911929431277216, 0.1822539168616113, 0.049516641695215746, 0.30250549837342944, -0.82264380500945622]]],
865    [[[-0.30440534124661278, 0.45772207772993267, -0.23307067348130106, -0.47299200985722356, -0.70713971065210002,
866    0.63657827136991219], [-0.34568231546236672, -0.82773395989784282, 0.22061734040553627, -0.44947612583105667,
867    -0.82579704972895351, 0.046140649241088294], [-0.20114859714917932, 0.62317698558045764, 0.43257530170170533,
868    -0.51262532825183138, 0.046601230594965681, -0.95170817307557498], [-0.80642652621113942, -0.75405757465693624,
869    -0.534964442795683, -0.050306363307079049, 0.86603326962096205, -0.30778937685069252], [-0.87863387509688473,
870    0.85097807490368438, -0.25108326762247146, 0.4937910293257215, 0.056690519953803031, -0.82101973588398902]]],
871    [[[0.17526396588556215, -0.075652957124554998, -0.69110848195606445, 0.24208861806210247, 0.24904774014376052,
872    0.72231925877648662], [-0.68511614182752623, 0.041250777089497426, 0.4000072972000186, -0.87266655656284309,
873    -0.4686214701437561, 0.86214782509815513], [0.34285298245488183, -0.072857735041811811, -0.75094545378399813,
874    -0.8164507554195588, -0.63082644422203837, 0.30213883987979173], [0.55400445993054737, 0.48543645194975871,
875    0.44249440951834762, 0.81459036603800894, -0.43944947288524649, -0.13212404044942572], [-0.49653039338796079,
876    0.82084218457531311, 0.88279263592802959, 0.69105880560957389, 0.709818852462891, 0.1525990192290636]]]])
877          ref=cosh(xx)          ref=cosh(xx)
878          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
879          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 561  class SymbolicTestCase(unittest.TestCase Line 903  class SymbolicTestCase(unittest.TestCase
903          x=Symbol('x', shape)          x=Symbol('x', shape)
904          y=exp(x)          y=exp(x)
905          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
906          xx=numpy.array([[-0.15599078831709989, 0.83530855752181044, -0.61853037841860181, -0.9049813364629431], [0.48126403663398643, 0.65331890812203364, -0.038516438386840379, -0.43146228667932118], [-0.84621703464988318, 0.54969488534488598, 0.48884708476539385, -0.38979661635629914]])          xx=numpy.array([[-0.15599078831709989, 0.83530855752181044, -0.61853037841860181, -0.9049813364629431],
907    [0.48126403663398643, 0.65331890812203364, -0.038516438386840379, -0.43146228667932118], [-0.84621703464988318,
908    0.54969488534488598, 0.48884708476539385, -0.38979661635629914]])
909          ref=exp(xx)          ref=exp(xx)
910          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
911          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 571  class SymbolicTestCase(unittest.TestCase Line 915  class SymbolicTestCase(unittest.TestCase
915          x=Symbol('x', shape)          x=Symbol('x', shape)
916          y=exp(x)          y=exp(x)
917          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
918          xx=numpy.array([[[0.0047010214133329509], [0.58497005822233938], [0.190531375657647]], [[0.40618460242888199], [-0.48479595911885331], [0.67308933034827656]], [[-0.85316164151848084], [0.75444007790920686], [-0.95179352370710779]], [[0.57810743647134744], [-0.014212029108792601], [-0.31757235628998748]]])          xx=numpy.array([[[0.0047010214133329509], [0.58497005822233938], [0.190531375657647]], [[0.40618460242888199],
919    [-0.48479595911885331], [0.67308933034827656]], [[-0.85316164151848084], [0.75444007790920686], [-0.95179352370710779]],
920    [[0.57810743647134744], [-0.014212029108792601], [-0.31757235628998748]]])
921          ref=exp(xx)          ref=exp(xx)
922          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
923          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 581  class SymbolicTestCase(unittest.TestCase Line 927  class SymbolicTestCase(unittest.TestCase
927          x=Symbol('x', shape)          x=Symbol('x', shape)
928          y=exp(x)          y=exp(x)
929          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
930          xx=numpy.array([[[[-0.30596292185592877, 0.30366663235901425], [0.6231722659051504, -0.054728526294849367], [-0.44139589051371075, -0.25120205722386713], [0.7446610696609921, 0.094724919048205125], [0.14650070934907045, 0.70801091981612796], [-0.92050711984005651, 0.24685847906966507]], [[0.016532231248215012, -0.070321218023200016], [0.15423749362710448, -0.74674518498077402], [-0.87402020938257508, -0.75462133626457484], [0.032048778727314264, 0.099037186704303615], [0.7307718585816565, 0.79054777284779743], [0.38242541669168162, 0.35850368942989852]], [[-0.7974167093641269, -0.73067586437853116], [0.97693678947125462, 0.76489469869146487], [-0.58677638460680348, 0.19563004514794091], [0.20841425549350645, -0.15645084283457855], [-0.070711687011929314, -0.81559070077511575], [-0.21419661082485453, 0.45123310080509071]], [[-0.067287685193925917, 0.3753358617853324], [0.09214212746376016, -0.44585013366312976], [-0.51017734955982696, 0.95875741402337322], [0.76044897455281335, -0.98412720384937602], [0.20108459119786315, -0.80406413013483946], [-0.84990658490580007, -0.039581263271350586]], [[-0.10201832972678559, 0.14901314132472443], [0.82460662405809915, -0.3277445601261022], [0.80429497544969863, 0.58503382154684558], [-0.9029622511070321, -0.94842471817599439], [-0.87424311988110603, -0.5221757541687011], [-0.70731975290265092, -0.86207424292162638]]], [[[-0.018286445553016062, 0.13426114801666578], [-0.86065592524997658, -0.18414707772021566], [0.12401626306004254, 0.47792494262585739], [-0.26746537783893931, 0.61287209753963512], [0.87839205675558762, -0.81706751142132883], [-0.88493506578054171, 0.83653201763925344]], [[-0.94826370683013517, 0.89631237021278398], [-0.29260053818029208, 0.019735658145988655], [-0.83393977636172489, -0.8304031388909725], [0.79918645083485074, 0.028164076089578938], [0.099401675328516959, -0.73661730027692074], [-0.54617050015315072, -0.20618508714374184]], [[0.29500655335379022, -0.63914557204669897], [-0.78458797376840539, 0.75470073097403256], [0.98613948937213691, -0.46455905954917709], [0.44923419352389771, 0.34096106359171063], [0.90527793216545205, 0.68931172366431537], [0.50643534475243857, -0.99909209066321392]], [[0.23643933272399154, 0.42413493322088969], [0.92223926429637304, -0.13077833985235809], [-0.9867925158473887, 0.6674050590285765], [0.84603514612691333, -0.78345125440108832], [-0.26885985726915362, 0.29416519140636677], [-0.57881506763631174, 0.44904085829021878]], [[0.37679189347116226, 0.53322127023021926], [0.20282442370186526, 0.90161357034603884], [0.0672068732531379, -0.60805739580442353], [0.62001773310375285, -0.37964492510738235], [0.25931816851780609, 0.39537332146251702], [0.93415525099142505, -0.61777234694360916]]], [[[-0.46407961603856274, -0.66157985016240173], [0.88792583878263098, -0.19592922807156876], [-0.25767252745309843, -0.29622441630507801], [-0.95723157511556889, -0.89555026038533314], [-0.84104343356145828, -0.091959765142363148], [0.91139107437952993, -0.94561206260990227]], [[-0.53141031225283797, 0.6553900664158494], [-0.7782132818838956, 0.90675858578939361], [-0.80975120643773746, 0.37549105272290362], [-0.40788420558627259, 0.91264797523629126], [-0.57147655481112847, 0.37704319055136049], [-0.75715351320554047, -0.66149693595302361]], [[0.77741720769013178, 0.72110323844047852], [-0.85158161844112001, -0.090611850524293658], [0.93326323314347426, 0.7726635627126055], [0.096281110382635315, 0.30340728420934093], [0.98608223159614794, -0.19239473769493354], [-0.40866198985687752, -0.16761911697427001]], [[0.55424558881285013, 0.93232913878921786], [-0.78146532823059345, -0.83624093432571733], [-0.35866792771792211, -0.61434788720274125], [0.044470089454589745, 0.79722737716855052], [-0.51967777990673092, 0.9805923265705967], [0.0078293675338785285, -0.96149168680409192]], [[-0.60930713897313771, 0.70251075118522266], [0.35791335868253737, -0.73035308199412108], [0.82796146066830523, -0.92484044474111782], [0.054514328350172114, 0.84711134685166556], [0.83025616140982716, 0.34094003908064341], [0.45706712554547901, -0.9663983784464476]]], [[[0.64779801463869768, 0.58721995935270455], [-0.75329910729095451, -0.76682692418354059], [0.47506176675518885, 0.3948005109562045], [-0.058691608053078159, 0.9987090180383571], [-0.44551915179886969, 0.94574964748483459], [0.17204189129879488, -0.98771974586774647]], [[0.67928082123746769, -0.05233122102290011], [-0.018892855055411939, 0.27850855290407428], [-0.55737341163384357, -0.98999600102735608], [-0.45428940104007975, -0.34857798317415933], [0.050137568675821198, 0.017012489885865234], [0.33268505891125932, 0.12771514339664125]], [[-0.11931273629412309, 0.9801586659410122], [0.92760042419988653, 0.39800507526656514], [-0.47982410148597343, -0.98073202711940177], [0.51619044075156806, -0.86880772774727366], [0.58945407296162178, 0.38510534483341852], [0.20364603194121722, 0.010652215325434256]], [[-0.14817838895124957, -0.4607469432281821], [-0.73819401543217866, -0.67666933215309033], [0.069595965942202964, 0.17910738949221994], [0.23009301566395224, 0.24941073286595539], [-0.19664453728095443, 0.04980497792297145], [0.6487390160450297, -0.07079289533351707]], [[0.12990862618698085, -0.79361849919311722], [0.40260059549511729, 0.31886179661338243], [-0.39466248189362174, 0.22814049762743593], [-0.13359160643719603, 0.72398092938172187], [-0.83794024634630637, 0.12365309093544918], [-0.48560967498252894, -0.77788096851502364]]], [[[0.85173658319575529, 0.577014551294043], [0.21361424424692532, 0.08429221555423938], [-0.6123838194145752, -0.49635328297554349], [-0.46383776641446772, 0.70001544428571028], [-0.12519883760550754, -0.22063456640416979], [-0.95006519142511259, -0.90605087088889102]], [[0.86863876058824752, -0.3278910447973975], [0.29364232163030501, 0.38885761932368479], [-0.1852571169901791, -0.63087246032151323], [0.29726745520525344, -0.89863370459558256], [-0.27063027983317189, 0.48310918893602217], [0.13289112275020032, -0.52736063420011248]], [[0.087504974214698494, 0.07823070592583603], [0.10809543261682686, 0.016525785820925121], [-0.0247510226856964, -0.52870869225632955], [0.19454693791622146, 0.78619539918072978], [-0.58854544664397435, -0.75068637898166757], [-0.79933324122526206, -0.51443287175476149]], [[0.40926067203193406, -0.76109702660474143], [-0.45025011020737327, -0.19737478860499191], [-0.62891504474281024, -0.68490643525957351], [0.21572191650916772, 0.93204453007061971], [0.79366966684285623, 0.59025377667120993], [0.48257449867527802, 0.53769741230172263]], [[0.092875342126348848, -0.63995797782070274], [0.42438374474894713, -0.93870603931761321], [-0.22407544965425785, 0.36096169772142561], [0.20757103573027025, 0.73693895922021624], [0.69392908125765773, 0.43630699013762242], [0.070299234971340052, -0.48962956941167923]]], [[[0.1392910791907398, -0.19184781072474832], [-0.57817350526221234, 0.67046017137213476], [0.84334097701803579, 0.92194490582093636], [0.7344610296633145, -0.71325048214812492], [0.81005466541197757, 0.11462687735533406], [0.43147865789773499, -0.47540249062630613]], [[0.22146489672624026, -0.070224743042629267], [0.37190852159136001, -0.49038949960688982], [0.5768061787367067, -0.82397125662326132], [0.40992096386723653, -0.92741597936441122], [0.71608843694227464, -0.29014985382999003], [0.0087445773549872374, 0.0054133250537837796]], [[-0.45356421697562355, -0.82148436553156112], [0.86957033820002971, -0.64754595320426667], [0.65689985740452839, -0.025653863677893129], [0.15209545893793641, 0.35688892156821073], [-0.68881477588242679, -0.23401778209224866], [-0.87412906876778829, 0.028830446035241319]], [[0.90027677541748408, 0.10162761305094303], [-0.029923056747827914, 0.64024050328453486], [-0.57223935620071487, 0.2580835332951712], [-0.85403803518041776, 0.40707347706215513], [-0.60372887967650457, -0.68103364819956358], [0.35800132324020217, 0.21743248362508916]], [[-0.50101144015350685, 0.50676228110110633], [-0.86633010332152582, -0.23293592516880013], [0.79834894467327544, 0.97856055748655235], [0.38537515035061043, -0.032554076815270561], [-0.56571529738595117, -0.11411609009780688], [-0.045424841887348633, -0.91268440349210955]]]])          xx=numpy.array([[[[-0.30596292185592877, 0.30366663235901425], [0.6231722659051504, -0.054728526294849367],
931    [-0.44139589051371075, -0.25120205722386713], [0.7446610696609921, 0.094724919048205125], [0.14650070934907045,
932    0.70801091981612796], [-0.92050711984005651, 0.24685847906966507]], [[0.016532231248215012, -0.070321218023200016],
933    [0.15423749362710448, -0.74674518498077402], [-0.87402020938257508, -0.75462133626457484], [0.032048778727314264,
934    0.099037186704303615], [0.7307718585816565, 0.79054777284779743], [0.38242541669168162, 0.35850368942989852]],
935    [[-0.7974167093641269, -0.73067586437853116], [0.97693678947125462, 0.76489469869146487], [-0.58677638460680348,
936    0.19563004514794091], [0.20841425549350645, -0.15645084283457855], [-0.070711687011929314, -0.81559070077511575],
937    [-0.21419661082485453, 0.45123310080509071]], [[-0.067287685193925917, 0.3753358617853324], [0.09214212746376016,
938    -0.44585013366312976], [-0.51017734955982696, 0.95875741402337322], [0.76044897455281335, -0.98412720384937602],
939    [0.20108459119786315, -0.80406413013483946], [-0.84990658490580007, -0.039581263271350586]], [[-0.10201832972678559,
940    0.14901314132472443], [0.82460662405809915, -0.3277445601261022], [0.80429497544969863, 0.58503382154684558],
941    [-0.9029622511070321, -0.94842471817599439], [-0.87424311988110603, -0.5221757541687011], [-0.70731975290265092,
942    -0.86207424292162638]]], [[[-0.018286445553016062, 0.13426114801666578], [-0.86065592524997658, -0.18414707772021566],
943    [0.12401626306004254, 0.47792494262585739], [-0.26746537783893931, 0.61287209753963512], [0.87839205675558762,
944    -0.81706751142132883], [-0.88493506578054171, 0.83653201763925344]], [[-0.94826370683013517, 0.89631237021278398],
945    [-0.29260053818029208, 0.019735658145988655], [-0.83393977636172489, -0.8304031388909725], [0.79918645083485074,
946    0.028164076089578938], [0.099401675328516959, -0.73661730027692074], [-0.54617050015315072, -0.20618508714374184]],
947    [[0.29500655335379022, -0.63914557204669897], [-0.78458797376840539, 0.75470073097403256], [0.98613948937213691,
948    -0.46455905954917709], [0.44923419352389771, 0.34096106359171063], [0.90527793216545205, 0.68931172366431537],
949    [0.50643534475243857, -0.99909209066321392]], [[0.23643933272399154, 0.42413493322088969], [0.92223926429637304,
950    -0.13077833985235809], [-0.9867925158473887, 0.6674050590285765], [0.84603514612691333, -0.78345125440108832],
951    [-0.26885985726915362, 0.29416519140636677], [-0.57881506763631174, 0.44904085829021878]], [[0.37679189347116226,
952    0.53322127023021926], [0.20282442370186526, 0.90161357034603884], [0.0672068732531379, -0.60805739580442353],
953    [0.62001773310375285, -0.37964492510738235], [0.25931816851780609, 0.39537332146251702], [0.93415525099142505,
954    -0.61777234694360916]]], [[[-0.46407961603856274, -0.66157985016240173], [0.88792583878263098, -0.19592922807156876],
955    [-0.25767252745309843, -0.29622441630507801], [-0.95723157511556889, -0.89555026038533314], [-0.84104343356145828,
956    -0.091959765142363148], [0.91139107437952993, -0.94561206260990227]], [[-0.53141031225283797, 0.6553900664158494],
957    [-0.7782132818838956, 0.90675858578939361], [-0.80975120643773746, 0.37549105272290362], [-0.40788420558627259,
958    0.91264797523629126], [-0.57147655481112847, 0.37704319055136049], [-0.75715351320554047, -0.66149693595302361]],
959    [[0.77741720769013178, 0.72110323844047852], [-0.85158161844112001, -0.090611850524293658], [0.93326323314347426,
960    0.7726635627126055], [0.096281110382635315, 0.30340728420934093], [0.98608223159614794, -0.19239473769493354],
961    [-0.40866198985687752, -0.16761911697427001]], [[0.55424558881285013, 0.93232913878921786], [-0.78146532823059345,
962    -0.83624093432571733], [-0.35866792771792211, -0.61434788720274125], [0.044470089454589745, 0.79722737716855052],
963    [-0.51967777990673092, 0.9805923265705967], [0.0078293675338785285, -0.96149168680409192]], [[-0.60930713897313771,
964    0.70251075118522266], [0.35791335868253737, -0.73035308199412108], [0.82796146066830523, -0.92484044474111782],
965    [0.054514328350172114, 0.84711134685166556], [0.83025616140982716, 0.34094003908064341], [0.45706712554547901,
966    -0.9663983784464476]]], [[[0.64779801463869768, 0.58721995935270455], [-0.75329910729095451, -0.76682692418354059],
967    [0.47506176675518885, 0.3948005109562045], [-0.058691608053078159, 0.9987090180383571], [-0.44551915179886969,
968    0.94574964748483459], [0.17204189129879488, -0.98771974586774647]], [[0.67928082123746769, -0.05233122102290011],
969    [-0.018892855055411939, 0.27850855290407428], [-0.55737341163384357, -0.98999600102735608], [-0.45428940104007975,
970    -0.34857798317415933], [0.050137568675821198, 0.017012489885865234], [0.33268505891125932, 0.12771514339664125]],
971    [[-0.11931273629412309, 0.9801586659410122], [0.92760042419988653, 0.39800507526656514], [-0.47982410148597343,
972    -0.98073202711940177], [0.51619044075156806, -0.86880772774727366], [0.58945407296162178, 0.38510534483341852],
973    [0.20364603194121722, 0.010652215325434256]], [[-0.14817838895124957, -0.4607469432281821], [-0.73819401543217866,
974    -0.67666933215309033], [0.069595965942202964, 0.17910738949221994], [0.23009301566395224, 0.24941073286595539],
975    [-0.19664453728095443, 0.04980497792297145], [0.6487390160450297, -0.07079289533351707]], [[0.12990862618698085,
976    -0.79361849919311722], [0.40260059549511729, 0.31886179661338243], [-0.39466248189362174, 0.22814049762743593],
977    [-0.13359160643719603, 0.72398092938172187], [-0.83794024634630637, 0.12365309093544918], [-0.48560967498252894,
978    -0.77788096851502364]]], [[[0.85173658319575529, 0.577014551294043], [0.21361424424692532, 0.08429221555423938],
979    [-0.6123838194145752, -0.49635328297554349], [-0.46383776641446772, 0.70001544428571028], [-0.12519883760550754,
980    -0.22063456640416979], [-0.95006519142511259, -0.90605087088889102]], [[0.86863876058824752, -0.3278910447973975],
981    [0.29364232163030501, 0.38885761932368479], [-0.1852571169901791, -0.63087246032151323], [0.29726745520525344,
982    -0.89863370459558256], [-0.27063027983317189, 0.48310918893602217], [0.13289112275020032, -0.52736063420011248]],
983    [[0.087504974214698494, 0.07823070592583603], [0.10809543261682686, 0.016525785820925121], [-0.0247510226856964,
984    -0.52870869225632955], [0.19454693791622146, 0.78619539918072978], [-0.58854544664397435, -0.75068637898166757],
985    [-0.79933324122526206, -0.51443287175476149]], [[0.40926067203193406, -0.76109702660474143], [-0.45025011020737327,
986    -0.19737478860499191], [-0.62891504474281024, -0.68490643525957351], [0.21572191650916772, 0.93204453007061971],
987    [0.79366966684285623, 0.59025377667120993], [0.48257449867527802, 0.53769741230172263]], [[0.092875342126348848,
988    -0.63995797782070274], [0.42438374474894713, -0.93870603931761321], [-0.22407544965425785, 0.36096169772142561],
989    [0.20757103573027025, 0.73693895922021624], [0.69392908125765773, 0.43630699013762242], [0.070299234971340052,
990    -0.48962956941167923]]], [[[0.1392910791907398, -0.19184781072474832], [-0.57817350526221234, 0.67046017137213476],
991    [0.84334097701803579, 0.92194490582093636], [0.7344610296633145, -0.71325048214812492], [0.81005466541197757,
992    0.11462687735533406], [0.43147865789773499, -0.47540249062630613]], [[0.22146489672624026, -0.070224743042629267],
993    [0.37190852159136001, -0.49038949960688982], [0.5768061787367067, -0.82397125662326132], [0.40992096386723653,
994    -0.92741597936441122], [0.71608843694227464, -0.29014985382999003], [0.0087445773549872374, 0.0054133250537837796]],
995    [[-0.45356421697562355, -0.82148436553156112], [0.86957033820002971, -0.64754595320426667], [0.65689985740452839,
996    -0.025653863677893129], [0.15209545893793641, 0.35688892156821073], [-0.68881477588242679, -0.23401778209224866],
997    [-0.87412906876778829, 0.028830446035241319]], [[0.90027677541748408, 0.10162761305094303], [-0.029923056747827914,
998    0.64024050328453486], [-0.57223935620071487, 0.2580835332951712], [-0.85403803518041776, 0.40707347706215513],
999    [-0.60372887967650457, -0.68103364819956358], [0.35800132324020217, 0.21743248362508916]], [[-0.50101144015350685,
1000    0.50676228110110633], [-0.86633010332152582, -0.23293592516880013], [0.79834894467327544, 0.97856055748655235],
1001    [0.38537515035061043, -0.032554076815270561], [-0.56571529738595117, -0.11411609009780688], [-0.045424841887348633,
1002    -0.91268440349210955]]]])
1003          ref=exp(xx)          ref=exp(xx)
1004          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1005          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 611  class SymbolicTestCase(unittest.TestCase Line 1029  class SymbolicTestCase(unittest.TestCase
1029          x=Symbol('x', shape)          x=Symbol('x', shape)
1030          y=length(x)          y=length(x)
1031          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1032          xx=numpy.array([[0.13260333155331105, 0.39525615038106587, -0.55326108909072813, 0.79354424989024275], [0.52891999129590883, 0.70333119333369232, -0.0552835107927796, -0.3210300128192034], [0.30319067763433094, 0.38646115209166232, 0.32547988582039467, -0.89667353501088187]])          xx=numpy.array([[0.13260333155331105, 0.39525615038106587, -0.55326108909072813, 0.79354424989024275],
1033    [0.52891999129590883, 0.70333119333369232, -0.0552835107927796, -0.3210300128192034], [0.30319067763433094,
1034    0.38646115209166232, 0.32547988582039467, -0.89667353501088187]])
1035          ref=length(xx)          ref=length(xx)
1036          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1037          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 621  class SymbolicTestCase(unittest.TestCase Line 1041  class SymbolicTestCase(unittest.TestCase
1041          x=Symbol('x', shape)          x=Symbol('x', shape)
1042          y=length(x)          y=length(x)
1043          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1044          xx=numpy.array([[[0.093140445929148274], [0.97983436504786714], [0.84208144753830982], [0.82618104052595354], [-0.37862753498342494], [0.27940866408181542]], [[-0.83607886592584157], [-0.82456967253020941], [0.22264766877203246], [0.19469779479628335], [0.44849148482915768], [-0.92584590499595576]], [[0.80053922691304358], [-0.13965472658980693], [-0.2576168475142202], [-0.67500826543448533], [0.84520747498240878], [0.84339566285407508]]])          xx=numpy.array([[[0.093140445929148274], [0.97983436504786714], [0.84208144753830982], [0.82618104052595354],
1045    [-0.37862753498342494], [0.27940866408181542]], [[-0.83607886592584157], [-0.82456967253020941], [0.22264766877203246],
1046    [0.19469779479628335], [0.44849148482915768], [-0.92584590499595576]], [[0.80053922691304358], [-0.13965472658980693],
1047    [-0.2576168475142202], [-0.67500826543448533], [0.84520747498240878], [0.84339566285407508]]])
1048          ref=length(xx)          ref=length(xx)
1049          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1050          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 631  class SymbolicTestCase(unittest.TestCase Line 1054  class SymbolicTestCase(unittest.TestCase
1054          x=Symbol('x', shape)          x=Symbol('x', shape)
1055          y=length(x)          y=length(x)
1056          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1057          xx=numpy.array([[[[-0.96227112410543603], [-0.12050638141735903]], [[0.87273325402806878], [-0.25584647257048876]], [[0.79160210110028761], [0.95874831319406595]], [[-0.25526277185811397], [0.12860093807007833]], [[0.77707917717967412], [-0.82241062274357857]]], [[[-0.083413231921356967], [0.10634547407277606]], [[0.42178224093611827], [-0.43085933146824962]], [[-0.52028132586319442], [-0.1786174821736457]], [[-0.33859767969258514], [-0.66491410813576635]], [[0.40688271279765575], [0.030334005353135129]]], [[[0.59878422774359952], [-0.43871932661498381]], [[-0.5133626205912607], [-0.19094099020008604]], [[-0.96044413926750805], [0.42238311141132967]], [[0.17652606549605521], [-0.26047797028713449]], [[-0.4904543686001881], [0.47631874521309747]]], [[[0.026806001819245084], [0.084735312407115737]], [[-0.76741011667885539], [-0.045743828487355032]], [[-0.47156297268381131], [-0.10296068162737204]], [[0.35593520818048408], [0.22865256456033967]], [[0.71754048308526985], [-0.66622298148824299]]], [[[-0.079660464506897677], [-0.91199764792949423]], [[0.47496979244333271], [-0.76143899805412585]], [[-0.48807312137736036], [-0.094324605017867436]], [[0.18672819320501999], [0.78370694714744671]], [[0.53410345624584354], [0.29336853974672805]]], [[[-0.99609543824443647], [0.062370694203262689]], [[-0.95883914251372371], [-0.9057079570956883]], [[0.24404376671817452], [0.092660484415446831]], [[0.36768810533455176], [-0.83983817558627605]], [[-0.93708621001717196], [-0.51718559191438107]]]])          xx=numpy.array([[[[-0.96227112410543603], [-0.12050638141735903]], [[0.87273325402806878], [-0.25584647257048876]],
1058    [[0.79160210110028761], [0.95874831319406595]], [[-0.25526277185811397], [0.12860093807007833]], [[0.77707917717967412],
1059    [-0.82241062274357857]]], [[[-0.083413231921356967], [0.10634547407277606]], [[0.42178224093611827], [-0.43085933146824962]],
1060    [[-0.52028132586319442], [-0.1786174821736457]], [[-0.33859767969258514], [-0.66491410813576635]], [[0.40688271279765575],
1061    [0.030334005353135129]]], [[[0.59878422774359952], [-0.43871932661498381]], [[-0.5133626205912607], [-0.19094099020008604]],
1062    [[-0.96044413926750805], [0.42238311141132967]], [[0.17652606549605521], [-0.26047797028713449]], [[-0.4904543686001881],
1063    [0.47631874521309747]]], [[[0.026806001819245084], [0.084735312407115737]], [[-0.76741011667885539], [-0.045743828487355032]],
1064    [[-0.47156297268381131], [-0.10296068162737204]], [[0.35593520818048408], [0.22865256456033967]], [[0.71754048308526985],
1065    [-0.66622298148824299]]], [[[-0.079660464506897677], [-0.91199764792949423]], [[0.47496979244333271], [-0.76143899805412585]],
1066    [[-0.48807312137736036], [-0.094324605017867436]], [[0.18672819320501999], [0.78370694714744671]], [[0.53410345624584354],
1067    [0.29336853974672805]]], [[[-0.99609543824443647], [0.062370694203262689]], [[-0.95883914251372371], [-0.9057079570956883]],
1068    [[0.24404376671817452], [0.092660484415446831]], [[0.36768810533455176], [-0.83983817558627605]], [[-0.93708621001717196],
1069    [-0.51718559191438107]]]])
1070          ref=length(xx)          ref=length(xx)
1071          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1072          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 671  class SymbolicTestCase(unittest.TestCase Line 1106  class SymbolicTestCase(unittest.TestCase
1106          x=Symbol('x', shape)          x=Symbol('x', shape)
1107          y=log(x)          y=log(x)
1108          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1109          xx=numpy.array([[[0.12433529720706205, 0.49513931075732587, 0.85738319231370486, 0.38886084910667684, 0.72697626312357977, 0.4798385362520069], [0.33656189784196133, 0.34549629760579526, 0.40961827440380838, 0.90136689434795281, 0.54556037046914041, 0.054321654876574255]], [[0.49014475112872169, 0.58384583411152435, 0.28793797291503243, 0.98558828341689531, 0.47394779571067724, 0.91693431782552004], [0.56842572231035071, 0.09460471131244319, 0.22119301483383746, 0.68332830309557513, 0.13789251920418, 0.74379222666006339]], [[0.97593571771657284, 0.086828380361032576, 0.63819426725263118, 0.91611825288980409, 0.22483917274871412, 0.88771042265188249], [0.3249774766351492, 0.40259671229467109, 0.55227266433238964, 0.99638697603917548, 0.95026616262460017, 0.43307826205731914]]])          xx=numpy.array([[[0.12433529720706205, 0.49513931075732587, 0.85738319231370486, 0.38886084910667684,
1110    0.72697626312357977, 0.4798385362520069], [0.33656189784196133, 0.34549629760579526, 0.40961827440380838, 0.90136689434795281,
1111    0.54556037046914041, 0.054321654876574255]], [[0.49014475112872169, 0.58384583411152435, 0.28793797291503243,
1112    0.98558828341689531, 0.47394779571067724, 0.91693431782552004], [0.56842572231035071, 0.09460471131244319, 0.22119301483383746,
1113    0.68332830309557513, 0.13789251920418, 0.74379222666006339]], [[0.97593571771657284, 0.086828380361032576, 0.63819426725263118,
1114    0.91611825288980409, 0.22483917274871412, 0.88771042265188249], [0.3249774766351492, 0.40259671229467109, 0.55227266433238964,
1115    0.99638697603917548, 0.95026616262460017, 0.43307826205731914]]])
1116          ref=log(xx)          ref=log(xx)
1117          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1118          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 681  class SymbolicTestCase(unittest.TestCase Line 1122  class SymbolicTestCase(unittest.TestCase
1122          x=Symbol('x', shape)          x=Symbol('x', shape)
1123          y=log(x)          y=log(x)
1124          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1125          xx=numpy.array([[[[0.40312628568383169, 0.78927471816219374, 0.5775266558195542, 0.27655259411969813, 0.82765863328239186], [0.11476535063789561, 0.19059237573261978, 0.55510483652574394, 0.78191697417147665, 0.94919156884023348]]], [[[0.80477601484601513, 0.21864036792012775, 0.89659476950097283, 0.61601221228894731, 0.97345033196154296], [0.3184339673402341, 0.61723581856492982, 0.38779724121395009, 0.24140678678920258, 0.10669408838757477]]], [[[0.71989806979858428, 0.72860837054242167, 0.089470671080997488, 0.51690977251205006, 0.75464337597423148], [0.4869899172914971, 0.44781614962779659, 0.90959276060801564, 0.36524024237914154, 0.088684506657893847]]], [[[0.15515320366637486, 0.70798821971098636, 0.83468781417459925, 0.5342410035792502, 0.44830431756321187], [0.89470126436222164, 0.63679563517826232, 0.073884503153794134, 0.21032629030752192, 0.97855521778496624]]]])          xx=numpy.array([[[[0.40312628568383169, 0.78927471816219374, 0.5775266558195542, 0.27655259411969813,
1126    0.82765863328239186], [0.11476535063789561, 0.19059237573261978, 0.55510483652574394, 0.78191697417147665,
1127    0.94919156884023348]]], [[[0.80477601484601513, 0.21864036792012775, 0.89659476950097283, 0.61601221228894731,
1128    0.97345033196154296], [0.3184339673402341, 0.61723581856492982, 0.38779724121395009, 0.24140678678920258,
1129    0.10669408838757477]]], [[[0.71989806979858428, 0.72860837054242167, 0.089470671080997488, 0.51690977251205006,
1130    0.75464337597423148], [0.4869899172914971, 0.44781614962779659, 0.90959276060801564, 0.36524024237914154,
1131    0.088684506657893847]]], [[[0.15515320366637486, 0.70798821971098636, 0.83468781417459925, 0.5342410035792502,
1132    0.44830431756321187], [0.89470126436222164, 0.63679563517826232, 0.073884503153794134, 0.21032629030752192,
1133    0.97855521778496624]]]])
1134          ref=log(xx)          ref=log(xx)
1135          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1136          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 711  class SymbolicTestCase(unittest.TestCase Line 1160  class SymbolicTestCase(unittest.TestCase
1160          x=Symbol('x', shape)          x=Symbol('x', shape)
1161          y=log10(x)          y=log10(x)
1162          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1163          xx=numpy.array([[0.92202406720474384, 0.67395082319814115, 0.75170452687880451, 0.47119294350212904, 0.094763220450263086, 0.93099785282155867], [0.36748317679429243, 0.89841240489081309, 0.91273839155094505, 0.33280124097597752, 0.88099429186526579, 0.28265470522966174], [0.59630149232099627, 0.60102609380135308, 0.38883593906194791, 0.3353987113563639, 0.006458104437443879, 0.57399908608006966]])          xx=numpy.array([[0.92202406720474384, 0.67395082319814115, 0.75170452687880451, 0.47119294350212904,
1164    0.094763220450263086, 0.93099785282155867], [0.36748317679429243, 0.89841240489081309, 0.91273839155094505,
1165    0.33280124097597752, 0.88099429186526579, 0.28265470522966174], [0.59630149232099627, 0.60102609380135308, 0.38883593906194791,
1166    0.3353987113563639, 0.006458104437443879, 0.57399908608006966]])
1167          ref=log10(xx)          ref=log10(xx)
1168          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1169          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 721  class SymbolicTestCase(unittest.TestCase Line 1173  class SymbolicTestCase(unittest.TestCase
1173          x=Symbol('x', shape)          x=Symbol('x', shape)
1174          y=log10(x)          y=log10(x)
1175          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1176          xx=numpy.array([[[0.10186831498010007, 0.2135378272298486, 0.31887623832248724, 0.85136459127940955], [0.77153166093968795, 0.8652928608036673, 0.46016218707220957, 0.62890444485229324], [0.98869062585987, 0.31281721681265096, 0.1906763574452276, 0.56515032637816931], [0.7348964862594094, 0.75036482091225354, 0.57360632859050775, 0.028144415523908783], [0.74733565640450517, 0.39742848180168677, 0.0060276061159015848, 0.2187742244789499], [0.57449014167080514, 0.069653239933958333, 0.51890861215990913, 0.25933626043878222]], [[0.031646515221860683, 0.64487376072193425, 0.45726389653281596, 0.78701446127216668], [0.66658897097152503, 0.023361053058920556, 0.80364203008965451, 0.09981068764361356], [0.48849841526135229, 0.92824511652932273, 0.46801124296572805, 0.72367432307038315], [0.83799132329078574, 0.43689729832707169, 0.115925661579101, 0.025389205521198166], [0.60572885192125769, 0.23720439714228547, 0.79494750705733219, 0.7785426859626976], [0.1487089803665852, 0.65051885658155617, 0.62360438855189892, 0.30416090266304407]], [[0.71661296904853167, 0.64021531993790359, 0.52935063966439966, 0.88314418302587583], [0.88609687349172017, 0.89305619260106961, 0.9698460864899805, 0.10792208220968236], [0.63692222342691163, 0.72190870655932793, 0.43135282707676093, 0.15031292581714806], [0.76335707739926162, 0.7812290266080858, 0.37360067739644476, 0.11187183050823757], [0.18079628330852127, 0.87980589608824433, 0.80966864186077359, 0.52227629692961164], [0.74373136855176603, 0.56080991356987775, 0.025588609300598031, 0.7152144034319573]], [[0.65927102973313367, 0.96521136593413737, 0.84141290263575941, 0.39101320837398756], [0.24199442992122577, 0.083280172678730668, 0.059628655773365291, 0.45312774694270064], [0.071791848567499206, 0.58731034300167351, 0.13507446735484196, 0.63404459816759895], [0.064252976550993712, 0.86778730366242318, 0.24304038657150595, 0.80974135630859012], [0.86023351673257986, 0.28798037573245827, 0.18206336760687325, 0.865748805047305], [0.62688482281847191, 0.30678950404931271, 0.90879845914837798, 0.25264621185951885]], [[0.87929752218143675, 0.67613157227750442, 0.33207637942512758, 0.053658133777309658], [0.047498852091670818, 0.34361099621202074, 0.13033148088167945, 0.24614254127747925], [0.032630256788782952, 0.7044910000509903, 0.56028056063442266, 0.2961220335509267], [0.22336001930263272, 0.85800396522318489, 0.39779517527224895, 0.29852508428959745], [0.68954263727356824, 0.77664614962814849, 0.70091805915624272, 0.54407714611895186], [0.24346455168769077, 0.15214978129096468, 0.30266826105505595, 0.49516307475606802]]])          xx=numpy.array([[[0.10186831498010007, 0.2135378272298486, 0.31887623832248724, 0.85136459127940955],
1177    [0.77153166093968795, 0.8652928608036673, 0.46016218707220957, 0.62890444485229324], [0.98869062585987, 0.31281721681265096,
1178    0.1906763574452276, 0.56515032637816931], [0.7348964862594094, 0.75036482091225354, 0.57360632859050775, 0.028144415523908783],
1179    [0.74733565640450517, 0.39742848180168677, 0.0060276061159015848, 0.2187742244789499], [0.57449014167080514,
1180    0.069653239933958333, 0.51890861215990913, 0.25933626043878222]], [[0.031646515221860683, 0.64487376072193425,
1181    0.45726389653281596, 0.78701446127216668], [0.66658897097152503, 0.023361053058920556, 0.80364203008965451,
1182    0.09981068764361356], [0.48849841526135229, 0.92824511652932273, 0.46801124296572805, 0.72367432307038315],
1183    [0.83799132329078574, 0.43689729832707169, 0.115925661579101, 0.025389205521198166], [0.60572885192125769, 0.23720439714228547,
1184    0.79494750705733219, 0.7785426859626976], [0.1487089803665852, 0.65051885658155617, 0.62360438855189892, 0.30416090266304407]],
1185    [[0.71661296904853167, 0.64021531993790359, 0.52935063966439966, 0.88314418302587583], [0.88609687349172017,
1186    0.89305619260106961, 0.9698460864899805, 0.10792208220968236], [0.63692222342691163, 0.72190870655932793, 0.43135282707676093,
1187    0.15031292581714806], [0.76335707739926162, 0.7812290266080858, 0.37360067739644476, 0.11187183050823757],
1188    [0.18079628330852127, 0.87980589608824433, 0.80966864186077359, 0.52227629692961164], [0.74373136855176603,
1189    0.56080991356987775, 0.025588609300598031, 0.7152144034319573]], [[0.65927102973313367, 0.96521136593413737,
1190    0.84141290263575941, 0.39101320837398756], [0.24199442992122577, 0.083280172678730668, 0.059628655773365291,
1191    0.45312774694270064], [0.071791848567499206, 0.58731034300167351, 0.13507446735484196, 0.63404459816759895],
1192    [0.064252976550993712, 0.86778730366242318, 0.24304038657150595, 0.80974135630859012], [0.86023351673257986,
1193    0.28798037573245827, 0.18206336760687325, 0.865748805047305], [0.62688482281847191, 0.30678950404931271, 0.90879845914837798,
1194    0.25264621185951885]], [[0.87929752218143675, 0.67613157227750442, 0.33207637942512758, 0.053658133777309658],
1195    [0.047498852091670818, 0.34361099621202074, 0.13033148088167945, 0.24614254127747925], [0.032630256788782952,
1196    0.7044910000509903, 0.56028056063442266, 0.2961220335509267], [0.22336001930263272, 0.85800396522318489, 0.39779517527224895,
1197    0.29852508428959745], [0.68954263727356824, 0.77664614962814849, 0.70091805915624272, 0.54407714611895186],
1198    [0.24346455168769077, 0.15214978129096468, 0.30266826105505595, 0.49516307475606802]]])
1199          ref=log10(xx)          ref=log10(xx)
1200          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1201          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 731  class SymbolicTestCase(unittest.TestCase Line 1205  class SymbolicTestCase(unittest.TestCase
1205          x=Symbol('x', shape)          x=Symbol('x', shape)
1206          y=log10(x)          y=log10(x)
1207          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1208          xx=numpy.array([[[[0.97312304426062135, 0.50371673549785512, 0.49870441867539372, 0.59625629112644651], [0.42888281415509732, 0.28055418038266822, 0.4296807075614435, 0.62424267873607053], [0.90350985998662503, 0.054198134071435033, 0.11616282480998508, 0.46501534991987659], [0.1287851494651574, 0.66200503345999651, 0.71112315756212041, 0.33384528261264124]], [[0.10837906718437684, 0.19875300634263127, 0.65051862636948565, 0.91754958111895113], [0.14173672179569197, 0.87804513763209435, 0.68986536709156554, 0.3113445484731765], [0.98977049530489136, 0.50869263292346167, 0.93257624255206584, 0.28855380644732709], [0.32702113175874259, 0.62353487506545668, 0.99899932773462718, 0.032921795563313871]], [[0.18448698676767439, 0.13157492462247922, 0.32006295335594614, 0.43076675555860267], [0.10695016214699371, 0.93731742391031714, 0.21226381138561234, 0.52994216727644172], [0.56297525585828134, 0.83577378985879514, 0.67319920774363795, 0.88477828907358214], [0.69281935923496452, 0.93552425811791695, 0.84326252536112545, 0.66622129770632521]], [[0.16443323082227701, 0.56528531880131228, 0.86574203239515302, 0.50546407780568314], [0.78009877705008335, 0.90045042464017166, 0.29488767422917439, 0.6281037689097686], [0.80958221933004793, 0.18547986695556273, 0.34020693804141555, 0.80066838808481733], [0.26448409097676451, 0.21616187093260331, 0.17662862220520992, 0.28856819663532607]]], [[[0.62361277809576598, 0.18861573060671777, 0.77847278986377799, 0.85335109140807797], [0.93963975655730791, 0.35335993478614125, 0.52704405644282404, 0.091922289061672435], [0.51582102805455687, 0.2532646190714688, 0.39871072269656349, 0.53867363489946352], [0.70228965464648918, 0.30192517401216468, 0.12976367025344371, 0.6817212224046667]], [[0.44405943616873322, 0.41884685043497416, 0.32755622589773492, 0.4604437724614463], [0.12601428405739834, 0.82795233475270535, 0.71242308874675375, 0.22049695360764532], [0.14072345006800413, 0.63508586856069948, 0.3475256153379892, 0.24873836656201642], [0.8378293360316218, 0.90789559631760264, 0.67889488825771249, 0.12787966083913149]], [[0.60721920608567126, 0.26937480971793193, 0.071360957768064281, 0.89536518229145723], [0.16765910699083864, 0.53327625724280503, 0.42629930800958193, 0.92858203780749182], [0.048702709697830637, 0.27507825424178212, 0.68774474358335602, 0.56691344449418679], [0.68184043090517088, 0.92225464618116249, 0.31925701817294916, 0.73897665526599632]], [[0.54442688055787813, 0.30608150174334869, 0.32510361949852662, 0.17883613960790057], [0.1181904095798948, 0.86259263997056135, 0.80682913150521174, 0.076880450041311832], [0.86728806238220868, 0.85316500174000975, 0.29001953875090858, 0.88121889862628899], [0.72007882595288464, 0.37978478238119562, 0.65676751089282648, 0.068606123897136717]]], [[[0.93666797512755984, 0.96678305879304982, 0.36029356631245679, 0.92395670850800238], [0.78407410934143063, 0.60276020242395967, 0.39493636901797802, 0.136718123023709], [0.44357963223560382, 0.17466831124966198, 0.5794146677883204, 0.53480803015502665], [0.84793399085466148, 0.82026048970834098, 0.51427051542252966, 0.95595864436976785]], [[0.93407933329915294, 0.052272150458120614, 0.25779487498521214, 0.10837338763154591], [0.50553261102949909, 0.79819728052438987, 0.59419918297622898, 0.57481966358357472], [0.62769049843959612, 0.73678065070682375, 0.078552428407051345, 0.38280660429075219], [0.83114948715709813, 0.61658034375557624, 0.73828696605832278, 0.27473198529972709]], [[0.52465213046173209, 0.63570563035223027, 0.76982380183190746, 0.68517307682910367], [0.56112386041730222, 0.75363407820979023, 0.69146617762795959, 0.50939854781017035], [0.061670720957187064, 0.4239568690769483, 0.50925781053442865, 0.060371309176233567], [0.81580264074308206, 0.34130691984213835, 0.99293035736558632, 0.66027840394783122]], [[0.14279758406141252, 0.24618897041483667, 0.91829033235925439, 0.62119038094091295], [0.38409516842277669, 0.44653959064808257, 0.34322660371962865, 0.61374574958409256], [0.9322217407076836, 0.38946747476328158, 0.021048032763529623, 0.58962862788025583], [0.48450453389061188, 0.5524580527933648, 0.68791856345659252, 0.68692100861913852]]], [[[0.20288666471366812, 0.21251468699432219, 0.11887844351379706, 0.2331265265972009], [0.43708430950625643, 0.013404275426153522, 0.52141662463283045, 0.036465497571777195], [0.228587163615661, 0.095012204182163051, 0.83234434801514356, 0.24939455088823015], [0.9078003532174902, 0.19314684843395535, 0.30854339659531693, 0.22510267775199333]], [[0.25157928638119031, 0.54788173275266938, 0.41441682674583036, 0.53263209018095936], [0.15647859461481839, 0.6163414519019067, 0.94367170678459, 0.95068507087862486], [0.29684171117548386, 0.28665661411484022, 0.60247926465241519, 0.85811491419990515], [0.19521841666976958, 0.092821419609968925, 0.01425990608833827, 0.18166094551170653]], [[0.0033036073293121193, 0.68287440340125827, 0.53602175234153759, 0.54063657348642191], [0.81420880186180022, 0.12890187581694856, 0.33448712242369882, 0.72683888917771111], [0.19226341222916388, 0.066777094102526857, 0.077437378559695125, 0.52939971297816546], [0.61690895797045286, 0.068669013271507984, 0.72734490014589515, 0.84150217751157741]], [[0.078092859145982629, 0.99832339494776334, 0.4379333777432215, 0.58662391622221299], [0.077977562698650305, 0.73999448359752207, 0.4398007813755217, 0.10281504856819312], [0.86303228945558985, 0.97553035514179776, 0.61716208080203161, 0.90662715248490922], [0.1393701003478045, 0.076790012089785087, 0.2832171603046566, 0.77654529386538829]]], [[[0.21782796590226639, 0.07512103214570276, 0.98455722959671599, 0.27344728641268701], [0.91857759076970991, 0.42291769455947803, 0.8521597897429537, 0.56958559534799347], [0.77367575327646465, 0.25495852169270694, 0.12665151363318861, 0.14537389745394147], [0.25924138850455236, 0.44875033909235074, 0.9377404074205663, 0.23731283673217907]], [[0.37008450586672903, 0.070185485995460262, 0.24743756901449432, 0.86604932122346667], [0.05690300064064302, 0.37593474682807937, 0.16709682344146715, 0.94483922855975566], [0.059310439554258965, 0.73235040102988347, 0.99647669144487794, 0.95963373810949226], [0.2347697836231295, 0.82537429527495143, 0.56565214937433028, 0.37851067595349241]], [[0.78152276710629842, 0.011366634534990427, 0.87740429923487273, 0.030998181459716667], [0.799466766551161, 0.88221485460042204, 0.90011244476847396, 0.015604467911808029], [0.39219556976440761, 0.76619418926527305, 0.7477533848871275, 0.48884860223006599], [0.69146799762943012, 0.48379532359780231, 0.047618270405578089, 0.99673032363512459]], [[0.62051358781916344, 0.078270774794253262, 0.2567249704646174, 0.023575417864789783], [0.87843429426353281, 0.6384439792924067, 0.97689046994639417, 0.2650274153038098], [0.85671250627124729, 0.67276371060970652, 0.45410958421352454, 0.26392228878947077], [0.38475161167572025, 0.48845766221009312, 0.36361276193592518, 0.22245828063603057]]], [[[0.84621797783094344, 0.5484481540327818, 0.76140596998492649, 0.87541105306250933], [0.45859718748312528, 0.6620954059486196, 0.93159551635694915, 0.60410310545028545], [0.31346201372017846, 0.24678555343267194, 0.34008202134198862, 0.35467637806398844], [0.38876223613015237, 0.024054960104140322, 0.81771625791740221, 0.70642102209610891]], [[0.70553790795534677, 0.16500773848825501, 0.41015170751678265, 0.086176818672664801], [0.68164676614638264, 0.11651999466696039, 0.54400397137119683, 0.51766240590822998], [0.73019918691007357, 0.28673650032456788, 0.98076951933106249, 0.15915593813986884], [0.57518459258950527, 0.21863322693173837, 0.70647793792547331, 0.78536521379867552]], [[0.10842481095741796, 0.99159547299722317, 0.20227277613907357, 0.15623673793097148], [0.53506617197832562, 0.081032875381117475, 0.28776036934686611, 0.83160714159127624], [0.45782484407745527, 0.4778800373945864, 0.74308397002521243, 0.068098712817207141], [0.70880168627669671, 0.22377695255510155, 0.72182850040282087, 0.57488717589324523]], [[0.89668771054920693, 0.451379233033814, 0.11786580262967772, 0.36808126131044228], [0.42570694822107091, 0.28325902091440869, 0.60206040509084713, 0.60072114932904852], [0.39367069699174995, 0.64707556103482966, 0.33179150247234113, 0.22249386846449937], [0.14082245423836326, 0.66402201361650104, 0.90508158294925567, 0.75885527515643492]]]])          xx=numpy.array([[[[0.97312304426062135, 0.50371673549785512, 0.49870441867539372, 0.59625629112644651],
1209    [0.42888281415509732, 0.28055418038266822, 0.4296807075614435, 0.62424267873607053], [0.90350985998662503,
1210    0.054198134071435033, 0.11616282480998508, 0.46501534991987659], [0.1287851494651574, 0.66200503345999651, 0.71112315756212041,
1211    0.33384528261264124]], [[0.10837906718437684, 0.19875300634263127, 0.65051862636948565, 0.91754958111895113],
1212    [0.14173672179569197, 0.87804513763209435, 0.68986536709156554, 0.3113445484731765], [0.98977049530489136, 0.50869263292346167,
1213    0.93257624255206584, 0.28855380644732709], [0.32702113175874259, 0.62353487506545668, 0.99899932773462718,
1214    0.032921795563313871]], [[0.18448698676767439, 0.13157492462247922, 0.32006295335594614, 0.43076675555860267],
1215    [0.10695016214699371, 0.93731742391031714, 0.21226381138561234, 0.52994216727644172], [0.56297525585828134,
1216    0.83577378985879514, 0.67319920774363795, 0.88477828907358214], [0.69281935923496452, 0.93552425811791695, 0.84326252536112545,
1217    0.66622129770632521]], [[0.16443323082227701, 0.56528531880131228, 0.86574203239515302, 0.50546407780568314],
1218    [0.78009877705008335, 0.90045042464017166, 0.29488767422917439, 0.6281037689097686], [0.80958221933004793, 0.18547986695556273,
1219    0.34020693804141555, 0.80066838808481733], [0.26448409097676451, 0.21616187093260331, 0.17662862220520992,
1220    0.28856819663532607]]], [[[0.62361277809576598, 0.18861573060671777, 0.77847278986377799, 0.85335109140807797],
1221    [0.93963975655730791, 0.35335993478614125, 0.52704405644282404, 0.091922289061672435], [0.51582102805455687,
1222    0.2532646190714688, 0.39871072269656349, 0.53867363489946352], [0.70228965464648918, 0.30192517401216468, 0.12976367025344371,
1223    0.6817212224046667]], [[0.44405943616873322, 0.41884685043497416, 0.32755622589773492, 0.4604437724614463],
1224    [0.12601428405739834, 0.82795233475270535, 0.71242308874675375, 0.22049695360764532], [0.14072345006800413,
1225    0.63508586856069948, 0.3475256153379892, 0.24873836656201642], [0.8378293360316218, 0.90789559631760264, 0.67889488825771249,
1226    0.12787966083913149]], [[0.60721920608567126, 0.26937480971793193, 0.071360957768064281, 0.89536518229145723],
1227    [0.16765910699083864, 0.53327625724280503, 0.42629930800958193, 0.92858203780749182], [0.048702709697830637,
1228    0.27507825424178212, 0.68774474358335602, 0.56691344449418679], [0.68184043090517088, 0.92225464618116249, 0.31925701817294916,
1229    0.73897665526599632]], [[0.54442688055787813, 0.30608150174334869, 0.32510361949852662, 0.17883613960790057],
1230    [0.1181904095798948, 0.86259263997056135, 0.80682913150521174, 0.076880450041311832], [0.86728806238220868,
1231    0.85316500174000975, 0.29001953875090858, 0.88121889862628899], [0.72007882595288464, 0.37978478238119562, 0.65676751089282648,
1232    0.068606123897136717]]], [[[0.93666797512755984, 0.96678305879304982, 0.36029356631245679, 0.92395670850800238],
1233    [0.78407410934143063, 0.60276020242395967, 0.39493636901797802, 0.136718123023709], [0.44357963223560382, 0.17466831124966198,
1234    0.5794146677883204, 0.53480803015502665], [0.84793399085466148, 0.82026048970834098, 0.51427051542252966,
1235    0.95595864436976785]], [[0.93407933329915294, 0.052272150458120614, 0.25779487498521214, 0.10837338763154591],
1236    [0.50553261102949909, 0.79819728052438987, 0.59419918297622898, 0.57481966358357472], [0.62769049843959612,
1237    0.73678065070682375, 0.078552428407051345, 0.38280660429075219], [0.83114948715709813, 0.61658034375557624,
1238    0.73828696605832278, 0.27473198529972709]], [[0.52465213046173209, 0.63570563035223027, 0.76982380183190746,
1239    0.68517307682910367], [0.56112386041730222, 0.75363407820979023, 0.69146617762795959, 0.50939854781017035],
1240    [0.061670720957187064, 0.4239568690769483, 0.50925781053442865, 0.060371309176233567], [0.81580264074308206,
1241    0.34130691984213835, 0.99293035736558632, 0.66027840394783122]], [[0.14279758406141252, 0.24618897041483667,
1242    0.91829033235925439, 0.62119038094091295], [0.38409516842277669, 0.44653959064808257, 0.34322660371962865,
1243    0.61374574958409256], [0.9322217407076836, 0.38946747476328158, 0.021048032763529623, 0.58962862788025583],
1244    [0.48450453389061188, 0.5524580527933648, 0.68791856345659252, 0.68692100861913852]]], [[[0.20288666471366812,
1245    0.21251468699432219, 0.11887844351379706, 0.2331265265972009], [0.43708430950625643, 0.013404275426153522, 0.52141662463283045,
1246    0.036465497571777195], [0.228587163615661, 0.095012204182163051, 0.83234434801514356, 0.24939455088823015],
1247    [0.9078003532174902, 0.19314684843395535, 0.30854339659531693, 0.22510267775199333]], [[0.25157928638119031,
1248    0.54788173275266938, 0.41441682674583036, 0.53263209018095936], [0.15647859461481839, 0.6163414519019067, 0.94367170678459,
1249    0.95068507087862486], [0.29684171117548386, 0.28665661411484022, 0.60247926465241519, 0.85811491419990515],
1250    [0.19521841666976958, 0.092821419609968925, 0.01425990608833827, 0.18166094551170653]], [[0.0033036073293121193,
1251    0.68287440340125827, 0.53602175234153759, 0.54063657348642191], [0.81420880186180022, 0.12890187581694856, 0.33448712242369882,
1252    0.72683888917771111], [0.19226341222916388, 0.066777094102526857, 0.077437378559695125, 0.52939971297816546],
1253    [0.61690895797045286, 0.068669013271507984, 0.72734490014589515, 0.84150217751157741]], [[0.078092859145982629,
1254    0.99832339494776334, 0.4379333777432215, 0.58662391622221299], [0.077977562698650305, 0.73999448359752207, 0.4398007813755217,
1255    0.10281504856819312], [0.86303228945558985, 0.97553035514179776, 0.61716208080203161, 0.90662715248490922],
1256    [0.1393701003478045, 0.076790012089785087, 0.2832171603046566, 0.77654529386538829]]], [[[0.21782796590226639,
1257    0.07512103214570276, 0.98455722959671599, 0.27344728641268701], [0.91857759076970991, 0.42291769455947803, 0.8521597897429537,
1258    0.56958559534799347], [0.77367575327646465, 0.25495852169270694, 0.12665151363318861, 0.14537389745394147],
1259    [0.25924138850455236, 0.44875033909235074, 0.9377404074205663, 0.23731283673217907]], [[0.37008450586672903,
1260    0.070185485995460262, 0.24743756901449432, 0.86604932122346667], [0.05690300064064302, 0.37593474682807937,
1261    0.16709682344146715, 0.94483922855975566], [0.059310439554258965, 0.73235040102988347, 0.99647669144487794,
1262    0.95963373810949226], [0.2347697836231295, 0.82537429527495143, 0.56565214937433028, 0.37851067595349241]],
1263    [[0.78152276710629842, 0.011366634534990427, 0.87740429923487273, 0.030998181459716667], [0.799466766551161,
1264    0.88221485460042204, 0.90011244476847396, 0.015604467911808029], [0.39219556976440761, 0.76619418926527305, 0.7477533848871275,
1265    0.48884860223006599], [0.69146799762943012, 0.48379532359780231, 0.047618270405578089, 0.99673032363512459]],
1266    [[0.62051358781916344, 0.078270774794253262, 0.2567249704646174, 0.023575417864789783], [0.87843429426353281,
1267    0.6384439792924067, 0.97689046994639417, 0.2650274153038098], [0.85671250627124729, 0.67276371060970652, 0.45410958421352454,
1268    0.26392228878947077], [0.38475161167572025, 0.48845766221009312, 0.36361276193592518, 0.22245828063603057]]],
1269    [[[0.84621797783094344, 0.5484481540327818, 0.76140596998492649, 0.87541105306250933], [0.45859718748312528,
1270    0.6620954059486196, 0.93159551635694915, 0.60410310545028545], [0.31346201372017846, 0.24678555343267194, 0.34008202134198862,
1271    0.35467637806398844], [0.38876223613015237, 0.024054960104140322, 0.81771625791740221, 0.70642102209610891]],
1272    [[0.70553790795534677, 0.16500773848825501, 0.41015170751678265, 0.086176818672664801], [0.68164676614638264,
1273    0.11651999466696039, 0.54400397137119683, 0.51766240590822998], [0.73019918691007357, 0.28673650032456788, 0.98076951933106249,
1274    0.15915593813986884], [0.57518459258950527, 0.21863322693173837, 0.70647793792547331, 0.78536521379867552]],
1275    [[0.10842481095741796, 0.99159547299722317, 0.20227277613907357, 0.15623673793097148], [0.53506617197832562,
1276    0.081032875381117475, 0.28776036934686611, 0.83160714159127624], [0.45782484407745527, 0.4778800373945864, 0.74308397002521243,
1277    0.068098712817207141], [0.70880168627669671, 0.22377695255510155, 0.72182850040282087, 0.57488717589324523]],
1278    [[0.89668771054920693, 0.451379233033814, 0.11786580262967772, 0.36808126131044228], [0.42570694822107091, 0.28325902091440869,
1279    0.60206040509084713, 0.60072114932904852], [0.39367069699174995, 0.64707556103482966, 0.33179150247234113,
1280    0.22249386846449937], [0.14082245423836326, 0.66402201361650104, 0.90508158294925567, 0.75885527515643492]]]])
1281          ref=log10(xx)          ref=log10(xx)
1282          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1283          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 771  class SymbolicTestCase(unittest.TestCase Line 1317  class SymbolicTestCase(unittest.TestCase
1317          x=Symbol('x', shape)          x=Symbol('x', shape)
1318          y=sign(x)          y=sign(x)
1319          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1320          xx=numpy.array([[[-0.72378804122203766], [0.57252446403624169]], [[-0.5622682101967813], [0.82690553559220836]], [[0.39377930282697982], [0.099583244262002824]], [[-0.5926447731844755], [0.45345400584270745]]])          xx=numpy.array([[[-0.72378804122203766], [0.57252446403624169]], [[-0.5622682101967813], [0.82690553559220836]],
1321    [[0.39377930282697982], [0.099583244262002824]], [[-0.5926447731844755], [0.45345400584270745]]])
1322          ref=sign(xx)          ref=sign(xx)
1323          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1324          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 781  class SymbolicTestCase(unittest.TestCase Line 1328  class SymbolicTestCase(unittest.TestCase
1328          x=Symbol('x', shape)          x=Symbol('x', shape)
1329          y=sign(x)          y=sign(x)
1330          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1331          xx=numpy.array([[[[0.73675827862553889, 0.91483877403995462, 0.88544806038709822], [0.20289925604258285, 0.49681253895088728, -0.12993315438114039]], [[-0.41051962546082166, 0.32972258960119438, 0.41612415640419931], [-0.3629990084703969, -0.7993222973959675, 0.90461900374117477]], [[0.87380421377509987, -0.64717971923231477, 0.12041310931561333], [0.011454488872085999, -0.85964731104678238, -0.98824556182761669]]], [[[-0.40224123111678534, -0.017132779055906155, -0.86504935027256358], [-0.29728365316699867, -0.91267470135866202, 0.94361155600394131]], [[-0.10134896144611116, 0.15937237080487043, 0.38050069387662866], [-0.24698252247994912, 0.35615792130786672, -0.96614170258007848]], [[-0.36416287584006146, 0.85971161200977186, -0.043051019340186736], [-0.0021576092624762122, 0.21350000314847861, 0.79220044489643704]]], [[[-0.73833628469383572, 0.57487778028930947, 0.9540897834401787], [-0.034279168411485816, -0.77873691901806796, 0.11719093621659105]], [[0.81893695504296726, -0.48035455150816397, 0.7060058906946014], [0.47633055348625897, 0.9712024802861563, 0.33421842773194776]], [[0.52575961663641402, 0.37781161222987669, -0.49864535672447152], [-0.56997962322850237, 0.050166891614832343, -0.27291002496026562]]], [[[-0.41595569588634995, 0.52999521006392092, -0.17170459060901866], [0.93873741356129536, 0.098996137061337919, 0.78191026790783891]], [[-0.47540397412853808, -0.81682572557752753, -0.46468133201496742], [-0.3942392464403941, 0.24897337387252083, -0.84311524023481055]], [[0.71528938597584202, -0.80049089776389226, 0.98596531426580269], [0.73191815193300069, -0.076983885753318271, 0.2817636222245723]]], [[[0.19247617425614472, -0.066366125321580816, -0.55279218562390464], [0.017469187199551595, 0.27398633923049531, 0.59435888154527006]], [[-0.62609777052479032, 0.60980575646670121, 0.96396067133187602], [0.049214315134996411, -0.31355478197115882, 0.28382169982433281]], [[-0.92315240462472414, 0.96150500748190293, -0.6845346601166713], [0.75825820500621632, 0.8620004836212849, 0.79272812163001483]]], [[[0.93710350559885525, 0.45394538309602117, 0.26129074628772386], [0.099486091312288139, -0.79989202448405528, -0.74523496658543098]], [[0.495499498536073, 0.4388822729917019, -0.80382922878486629], [0.2075710427779589, -0.089380121104465138, -0.19639060882269965]], [[0.26826700293085581, 0.57644629269118997, -0.50892587285306679], [-0.099397013894628516, -0.92030594627177797, -0.99008617084621808]]]])          xx=numpy.array([[[[0.73675827862553889, 0.91483877403995462, 0.88544806038709822], [0.20289925604258285,
1332    0.49681253895088728, -0.12993315438114039]], [[-0.41051962546082166, 0.32972258960119438, 0.41612415640419931],
1333    [-0.3629990084703969, -0.7993222973959675, 0.90461900374117477]], [[0.87380421377509987, -0.64717971923231477,
1334    0.12041310931561333], [0.011454488872085999, -0.85964731104678238, -0.98824556182761669]]], [[[-0.40224123111678534,
1335    -0.017132779055906155, -0.86504935027256358], [-0.29728365316699867, -0.91267470135866202, 0.94361155600394131]],
1336    [[-0.10134896144611116, 0.15937237080487043, 0.38050069387662866], [-0.24698252247994912, 0.35615792130786672,
1337    -0.96614170258007848]], [[-0.36416287584006146, 0.85971161200977186, -0.043051019340186736], [-0.0021576092624762122,
1338    0.21350000314847861, 0.79220044489643704]]], [[[-0.73833628469383572, 0.57487778028930947, 0.9540897834401787],
1339    [-0.034279168411485816, -0.77873691901806796, 0.11719093621659105]], [[0.81893695504296726, -0.48035455150816397,
1340    0.7060058906946014], [0.47633055348625897, 0.9712024802861563, 0.33421842773194776]], [[0.52575961663641402,
1341    0.37781161222987669, -0.49864535672447152], [-0.56997962322850237, 0.050166891614832343, -0.27291002496026562]]],
1342    [[[-0.41595569588634995, 0.52999521006392092, -0.17170459060901866], [0.93873741356129536, 0.098996137061337919,
1343    0.78191026790783891]], [[-0.47540397412853808, -0.81682572557752753, -0.46468133201496742], [-0.3942392464403941,
1344    0.24897337387252083, -0.84311524023481055]], [[0.71528938597584202, -0.80049089776389226, 0.98596531426580269],
1345    [0.73191815193300069, -0.076983885753318271, 0.2817636222245723]]], [[[0.19247617425614472, -0.066366125321580816,
1346    -0.55279218562390464], [0.017469187199551595, 0.27398633923049531, 0.59435888154527006]], [[-0.62609777052479032,
1347    0.60980575646670121, 0.96396067133187602], [0.049214315134996411, -0.31355478197115882, 0.28382169982433281]],
1348    [[-0.92315240462472414, 0.96150500748190293, -0.6845346601166713], [0.75825820500621632, 0.8620004836212849,
1349    0.79272812163001483]]], [[[0.93710350559885525, 0.45394538309602117, 0.26129074628772386], [0.099486091312288139,
1350    -0.79989202448405528, -0.74523496658543098]], [[0.495499498536073, 0.4388822729917019, -0.80382922878486629],
1351    [0.2075710427779589, -0.089380121104465138, -0.19639060882269965]], [[0.26826700293085581, 0.57644629269118997,
1352    -0.50892587285306679], [-0.099397013894628516, -0.92030594627177797, -0.99008617084621808]]]])
1353          ref=sign(xx)          ref=sign(xx)
1354          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1355          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 821  class SymbolicTestCase(unittest.TestCase Line 1389  class SymbolicTestCase(unittest.TestCase
1389          x=Symbol('x', shape)          x=Symbol('x', shape)
1390          y=sin(x)          y=sin(x)
1391          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1392          xx=numpy.array([[[0.12719341250253891, 0.94240805058335297, -0.86909746899297535, -0.30140578125466533], [0.81825173631703207, -0.43630012106697613, 0.83569604612838755, -0.81416580293443519], [-0.00020301755460416793, -0.15560407500011264, 0.54793528510549439, 0.86382840179995601]], [[0.49885493521351609, 0.81462242651477412, 0.23275443469675228, -0.21674790180269099], [-0.7821624220018919, -0.88051866675451884, 0.65789295590027552, 0.93234276414295225], [-0.25793802000447741, 0.60279182839018119, 0.50983979332071727, -0.98928307266384352]], [[0.66409681423819245, -0.1126276407936273, 0.86789106587410014, -0.81156662780578048], [0.04568617354929061, -0.082676650852101519, -0.28588547395675956, 0.84610563527160165], [0.21546862243589504, 0.026663031923359615, -0.48787866588477757, -0.34659781857768501]], [[-0.22843463423586319, 0.49676917265717457, -0.39524539046378382, -0.92279449190546536], [-0.19074534280274791, 0.89578986906775437, -0.33860659152453487, 0.099385397225141281], [0.92327715581396985, -0.29068143560427528, 0.61766952265221131, -0.26263716726458397]]])          xx=numpy.array([[[0.12719341250253891, 0.94240805058335297, -0.86909746899297535, -0.30140578125466533],
1393    [0.81825173631703207, -0.43630012106697613, 0.83569604612838755, -0.81416580293443519], [-0.00020301755460416793,
1394    -0.15560407500011264, 0.54793528510549439, 0.86382840179995601]], [[0.49885493521351609, 0.81462242651477412,
1395    0.23275443469675228, -0.21674790180269099], [-0.7821624220018919, -0.88051866675451884, 0.65789295590027552,
1396    0.93234276414295225], [-0.25793802000447741, 0.60279182839018119, 0.50983979332071727, -0.98928307266384352]],
1397    [[0.66409681423819245, -0.1126276407936273, 0.86789106587410014, -0.81156662780578048], [0.04568617354929061,
1398    -0.082676650852101519, -0.28588547395675956, 0.84610563527160165], [0.21546862243589504, 0.026663031923359615,
1399    -0.48787866588477757, -0.34659781857768501]], [[-0.22843463423586319, 0.49676917265717457, -0.39524539046378382,
1400    -0.92279449190546536], [-0.19074534280274791, 0.89578986906775437, -0.33860659152453487, 0.099385397225141281],
1401    [0.92327715581396985, -0.29068143560427528, 0.61766952265221131, -0.26263716726458397]]])
1402          ref=sin(xx)          ref=sin(xx)
1403          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1404          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 831  class SymbolicTestCase(unittest.TestCase Line 1408  class SymbolicTestCase(unittest.TestCase
1408          x=Symbol('x', shape)          x=Symbol('x', shape)
1409          y=sin(x)          y=sin(x)
1410          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1411          xx=numpy.array([[[[-0.86072117846153251, -0.019885060663697107], [-0.75596420490317695, 0.32635974831722647], [-0.92700886052822917, -0.20295271149419603]], [[0.56087967275611028, -0.74593470753875568], [-0.87115021310505059, 0.65703944484734844], [0.8452445692611863, 0.52556228616041656]], [[0.11340855624086399, -0.99113822454383094], [0.1482958797872409, -0.82905278835000318], [0.93562089630108169, -0.46224560103833556]], [[0.64277517260838746, -0.40274247637862648], [-0.80510217633866876, -0.5209708410699605], [-0.63301966565861534, -0.068342580535151853]], [[0.8263729251130838, 0.050211593544034816], [0.49238702440351956, -0.093240239446997331], [-0.23995676976991009, -0.083080595261635581]]], [[[0.61397129959987651, 0.40408480340977126], [0.086350805733938163, 0.15367708691986692], [0.27065837019542704, -0.43228842296737868]], [[0.70765273758478364, -0.36798368785345947], [-0.9899723962194924, -0.47290522770817822], [-0.62642431407007182, -0.48651185380472417]], [[-0.65402001961856904, 0.9065180648852682], [-0.78749946554104633, 0.45203097235082468], [0.97374565220766862, -0.24681403660502887]], [[0.56259917948190274, 0.69755021533510231], [0.20770189548762086, -0.57023351652855969], [0.98270817482027506, -0.91376351712170134]], [[0.55583021063293603, -0.55817864083258839], [-0.33894604692507357, -0.95292619377606735], [0.42765375302141662, 0.58898103376412037]]], [[[0.24341798478067833, -0.024645179148373053], [-0.67826428166543962, -0.91426078022945045], [0.3411072188458717, 0.70658098480681852]], [[-0.87681933497998621, -0.40489430363368761], [-0.32600422164756959, -0.58598334874061808], [0.90376876914414406, 0.029824078387123532]], [[0.58874466588853003, -0.82774962699531995], [0.91607363862422098, -0.79254174302484426], [-0.2644148749238695, 0.34053053372848652]], [[-0.91577964950737645, -0.69146674192578184], [-0.8977183107427702, 0.30048422166514044], [-0.16619420940308172, 0.54616054673573755]], [[0.84486754146636711, 0.68988790352389406], [0.46778140349805142, -0.71863324221692149], [0.10225625975272679, 0.34182079104071539]]], [[[0.91072383294596571, -0.49590171495518365], [-0.038314582897158278, -0.68563330667437472], [-0.63313318194534141, -0.91038897945540276]], [[0.24916330989826108, -0.56534062734783541], [-0.17252719027825592, 0.74957569378346589], [-0.63968063018884136, 0.50177550582088526]], [[0.93568476397885458, -0.93594419899311032], [-0.1817447116032751, -0.18999897705574575], [0.29765415309416277, -0.085041137255460697]], [[-0.3428987875787004, -0.61494312923538375], [0.77037994058704728, -0.57784965536584587], [0.019942654343778621, 0.31683116278372814]], [[0.17715614149827164, -0.78621638086609402], [0.39899437859837117, 0.51609297924211783], [0.65059708642966996, -0.094063078212815343]]], [[[0.96758424711675239, -0.89451370297444255], [0.45728487996661871, -0.55848557193517268], [0.77237147343588219, -0.68477204485039267]], [[0.41518673719657184, -0.22563771707467861], [-0.40284024326873147, 0.046432822245995986], [-0.92854654670917691, -0.24510098891604559]], [[0.72928399948698708, 0.2133530398493455], [-0.50333016134640873, -0.85457494281524649], [0.82055627088886673, -0.51906877954233743]], [[-0.57871567599408968, 0.11867295682968004], [-0.75066716147907231, 0.67255813066494197], [-0.35103424868504884, -0.76778391971732729]], [[-0.78519947150751657, -0.9261944511980289], [-0.055128778465886263, -0.15239107182086076], [-0.12461725975150895, 0.56121942561894489]]], [[[-0.43815201173493357, -0.24257698008360418], [-0.29280500267491161, 0.064850361200631035], [0.2183869009065198, -0.13294396152029209]], [[0.12385697793008643, -0.91458521402051196], [0.71619413751089223, -0.5969526950005235], [-0.98863207961723676, -0.10186755453120067]], [[0.59585107831775264, 0.24631692427877816], [0.0068705467302270229, 0.247657304010932], [-0.95973641229592288, 0.68965345238510745]], [[0.24473766858854673, 0.27037426996287039], [-0.73787209693898181, -0.056540963425711244], [0.62396998885054522, 0.41042344344095616]], [[-0.84642610310151167, 0.096445804050030226], [0.99848196110044296, -0.51915863199180023], [-0.13601993230775844, -0.60718971932510768]]]])          xx=numpy.array([[[[-0.86072117846153251, -0.019885060663697107], [-0.75596420490317695, 0.32635974831722647],
1412    [-0.92700886052822917, -0.20295271149419603]], [[0.56087967275611028, -0.74593470753875568], [-0.87115021310505059,
1413    0.65703944484734844], [0.8452445692611863, 0.52556228616041656]], [[0.11340855624086399, -0.99113822454383094],
1414    [0.1482958797872409, -0.82905278835000318], [0.93562089630108169, -0.46224560103833556]], [[0.64277517260838746,
1415    -0.40274247637862648], [-0.80510217633866876, -0.5209708410699605], [-0.63301966565861534, -0.068342580535151853]],
1416    [[0.8263729251130838, 0.050211593544034816], [0.49238702440351956, -0.093240239446997331], [-0.23995676976991009,
1417    -0.083080595261635581]]], [[[0.61397129959987651, 0.40408480340977126], [0.086350805733938163, 0.15367708691986692],
1418    [0.27065837019542704, -0.43228842296737868]], [[0.70765273758478364, -0.36798368785345947], [-0.9899723962194924,
1419    -0.47290522770817822], [-0.62642431407007182, -0.48651185380472417]], [[-0.65402001961856904, 0.9065180648852682],
1420    [-0.78749946554104633, 0.45203097235082468], [0.97374565220766862, -0.24681403660502887]], [[0.56259917948190274,
1421    0.69755021533510231], [0.20770189548762086, -0.57023351652855969], [0.98270817482027506, -0.91376351712170134]],
1422    [[0.55583021063293603, -0.55817864083258839], [-0.33894604692507357, -0.95292619377606735], [0.42765375302141662,
1423    0.58898103376412037]]], [[[0.24341798478067833, -0.024645179148373053], [-0.67826428166543962, -0.91426078022945045],
1424    [0.3411072188458717, 0.70658098480681852]], [[-0.87681933497998621, -0.40489430363368761], [-0.32600422164756959,
1425    -0.58598334874061808], [0.90376876914414406, 0.029824078387123532]], [[0.58874466588853003, -0.82774962699531995],
1426    [0.91607363862422098, -0.79254174302484426], [-0.2644148749238695, 0.34053053372848652]], [[-0.91577964950737645,
1427    -0.69146674192578184], [-0.8977183107427702, 0.30048422166514044], [-0.16619420940308172, 0.54616054673573755]],
1428    [[0.84486754146636711, 0.68988790352389406], [0.46778140349805142, -0.71863324221692149], [0.10225625975272679,
1429    0.34182079104071539]]], [[[0.91072383294596571, -0.49590171495518365], [-0.038314582897158278, -0.68563330667437472],
1430    [-0.63313318194534141, -0.91038897945540276]], [[0.24916330989826108, -0.56534062734783541], [-0.17252719027825592,
1431    0.74957569378346589], [-0.63968063018884136, 0.50177550582088526]], [[0.93568476397885458, -0.93594419899311032],
1432    [-0.1817447116032751, -0.18999897705574575], [0.29765415309416277, -0.085041137255460697]], [[-0.3428987875787004,
1433    -0.61494312923538375], [0.77037994058704728, -0.57784965536584587], [0.019942654343778621, 0.31683116278372814]],
1434    [[0.17715614149827164, -0.78621638086609402], [0.39899437859837117, 0.51609297924211783], [0.65059708642966996,
1435    -0.094063078212815343]]], [[[0.96758424711675239, -0.89451370297444255], [0.45728487996661871, -0.55848557193517268],
1436    [0.77237147343588219, -0.68477204485039267]], [[0.41518673719657184, -0.22563771707467861], [-0.40284024326873147,
1437    0.046432822245995986], [-0.92854654670917691, -0.24510098891604559]], [[0.72928399948698708, 0.2133530398493455],
1438    [-0.50333016134640873, -0.85457494281524649], [0.82055627088886673, -0.51906877954233743]], [[-0.57871567599408968,
1439    0.11867295682968004], [-0.75066716147907231, 0.67255813066494197], [-0.35103424868504884, -0.76778391971732729]],
1440    [[-0.78519947150751657, -0.9261944511980289], [-0.055128778465886263, -0.15239107182086076], [-0.12461725975150895,
1441    0.56121942561894489]]], [[[-0.43815201173493357, -0.24257698008360418], [-0.29280500267491161, 0.064850361200631035],
1442    [0.2183869009065198, -0.13294396152029209]], [[0.12385697793008643, -0.91458521402051196], [0.71619413751089223,
1443    -0.5969526950005235], [-0.98863207961723676, -0.10186755453120067]], [[0.59585107831775264, 0.24631692427877816],
1444    [0.0068705467302270229, 0.247657304010932], [-0.95973641229592288, 0.68965345238510745]], [[0.24473766858854673,
1445    0.27037426996287039], [-0.73787209693898181, -0.056540963425711244], [0.62396998885054522, 0.41042344344095616]],
1446    [[-0.84642610310151167, 0.096445804050030226], [0.99848196110044296, -0.51915863199180023], [-0.13601993230775844,
1447    -0.60718971932510768]]]])
1448          ref=sin(xx)          ref=sin(xx)
1449          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1450          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 861  class SymbolicTestCase(unittest.TestCase Line 1474  class SymbolicTestCase(unittest.TestCase
1474          x=Symbol('x', shape)          x=Symbol('x', shape)
1475          y=sinh(x)          y=sinh(x)
1476          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1477          xx=numpy.array([[0.70084091868990073, -0.37122093760650854, -0.98542437006495609], [-0.85293314037311685, 0.55234563280758864, 0.28910729615623465]])          xx=numpy.array([[0.70084091868990073, -0.37122093760650854, -0.98542437006495609], [-0.85293314037311685,
1478    0.55234563280758864, 0.28910729615623465]])
1479          ref=sinh(xx)          ref=sinh(xx)
1480          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1481          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 871  class SymbolicTestCase(unittest.TestCase Line 1485  class SymbolicTestCase(unittest.TestCase
1485          x=Symbol('x', shape)          x=Symbol('x', shape)
1486          y=sinh(x)          y=sinh(x)
1487          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1488          xx=numpy.array([[[0.6049409851077685, -0.060876864091317096, -0.91287636026437347, -0.42050089588498096, 0.067752967213508208, -0.81956681283255439]], [[0.98432036228063402, -0.89186551144514703, 0.71981933267454967, 0.47233832880070592, -0.54141614539879579, 0.30254425885779779]], [[-0.47418325474652412, 0.96433929261367002, 0.3681263669352226, 0.036021997887072388, 0.18826942276317205, -0.61084148500472191]]])          xx=numpy.array([[[0.6049409851077685, -0.060876864091317096, -0.91287636026437347, -0.42050089588498096,
1489    0.067752967213508208, -0.81956681283255439]], [[0.98432036228063402, -0.89186551144514703, 0.71981933267454967,
1490    0.47233832880070592, -0.54141614539879579, 0.30254425885779779]], [[-0.47418325474652412, 0.96433929261367002,
1491    0.3681263669352226, 0.036021997887072388, 0.18826942276317205, -0.61084148500472191]]])
1492          ref=sinh(xx)          ref=sinh(xx)
1493          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1494          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 881  class SymbolicTestCase(unittest.TestCase Line 1498  class SymbolicTestCase(unittest.TestCase
1498          x=Symbol('x', shape)          x=Symbol('x', shape)
1499          y=sinh(x)          y=sinh(x)
1500          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1501          xx=numpy.array([[[[-0.25184670553734478], [-0.90193559353129849]], [[0.012157397905095735], [0.78463782528086501]], [[-0.99880314565239048], [0.73395648897790311]]]])          xx=numpy.array([[[[-0.25184670553734478], [-0.90193559353129849]], [[0.012157397905095735], [0.78463782528086501]],
1502    [[-0.99880314565239048], [0.73395648897790311]]]])
1503          ref=sinh(xx)          ref=sinh(xx)
1504          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1505          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 921  class SymbolicTestCase(unittest.TestCase Line 1539  class SymbolicTestCase(unittest.TestCase
1539          x=Symbol('x', shape)          x=Symbol('x', shape)
1540          y=sqrt(x)          y=sqrt(x)
1541          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1542          xx=numpy.array([[[0.65496767364217046], [0.67783962327300917], [0.90007404601376473]], [[0.071997103388618311], [0.046235858883322378], [0.57362450572208434]]])          xx=numpy.array([[[0.65496767364217046], [0.67783962327300917], [0.90007404601376473]], [[0.071997103388618311],
1543    [0.046235858883322378], [0.57362450572208434]]])
1544          ref=sqrt(xx)          ref=sqrt(xx)
1545          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1546          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 931  class SymbolicTestCase(unittest.TestCase Line 1550  class SymbolicTestCase(unittest.TestCase
1550          x=Symbol('x', shape)          x=Symbol('x', shape)
1551          y=sqrt(x)          y=sqrt(x)
1552          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1553          xx=numpy.array([[[[0.72255651065698279, 0.83381610263629191, 0.088396309723070443], [0.79855742227758819, 0.839338005541306, 0.81495790516402389], [0.62626755304522941, 0.078799158362552024, 0.33267140687945473], [0.43940707734260109, 0.51599082070096458, 0.84321011444082217], [0.24171707936068787, 0.0060558032715870569, 0.56078845976765612]], [[0.57377382745965855, 0.49340859714655683, 0.2092972590061013], [0.68637889059321167, 0.11029705930136668, 0.96396795238233834], [0.55179714688174419, 0.35108623014240958, 0.51181447099189581], [0.32324557912243723, 0.78654583988331572, 0.33712954059082634], [0.079321394582968718, 0.23774608497170258, 0.69285790426559601]], [[0.85886317386456423, 0.13584169380100597, 0.24292242178587076], [0.61177645246068624, 0.3036432086030022, 0.53035500209869535], [0.28628042513462981, 0.24043761219547199, 0.94891705021835726], [0.60395478182149109, 0.083245941455203476, 0.13027004597807579], [0.15048976641157319, 0.11401314017400843, 0.18795600878276586]], [[0.09137780979901966, 0.32634976420570005, 0.61940335197091201], [0.37432581452719493, 0.97387697903168757, 0.60713072535399282], [0.81126283730616289, 0.72286470992579144, 0.33277102567004557], [0.65725608926170365, 0.22113878439984025, 0.39873142337432677], [0.56458095772442962, 0.69984805698516706, 0.13953969142708544]], [[0.14180888147181303, 0.6449607100547553, 0.31077677774512735], [0.78970211385749289, 0.35440985857825957, 0.33586351342060605], [0.31861742504282387, 0.0091224852408655632, 0.72485922708603734], [0.19028038521297774, 0.813785636029978, 0.96553983147048672], [0.91561864871190557, 0.11116693352450835, 0.70275695888285916]], [[0.93465367590426696, 0.08776495337568968, 0.92008576270779563], [0.55687479001255391, 0.72198162368591801, 0.93723076623527124], [0.62999175799626039, 0.36064429891165684, 0.59775442438928683], [0.22690790215469459, 0.4685878404511844, 0.89223770066308428], [0.92972243126999998, 0.46025840602562273, 0.40968201803367088]]], [[[0.94180597092282947, 0.96234744551267848, 0.87288463327476029], [0.41806750845644847, 0.22788237798369737, 0.11966406067717961], [0.69733599374787714, 0.18851158381113808, 0.16370374653731978], [0.63211076175223446, 0.41154348987607725, 0.98533970125915882], [0.65773473183219433, 0.041250994596582657, 0.96992667507584374]], [[0.40058859823800097, 0.12179652261476415, 0.99555017499337206], [0.68443796318239791, 0.88112987266527754, 0.6935433018004582], [0.85006065726887914, 0.79136227813817728, 0.44775493806515188], [0.17365733710621323, 0.15978381135481545, 0.71519613537661453], [0.52661904411861471, 0.52676789546431813, 0.48249638132196371]], [[0.19890220183563068, 0.6528046793768485, 0.39835999493439911], [0.30149513914196047, 0.41004970280230157, 0.095723514003266286], [0.59342390611233331, 0.64188662999081492, 0.94573923409175364], [0.97182053826713977, 0.030426067513154798, 0.61174589100753962], [0.72835687654810322, 0.68713012593738343, 0.31568564502713259]], [[0.95749206532668674, 0.93726678894579174, 0.4906774028313089], [0.38333713090398269, 0.31180194657763527, 0.87930430515980695], [0.43976370526311137, 0.044494145039117527, 0.74864265600876034], [0.26436773182558582, 0.13762336840153333, 0.063845322270331906], [0.28527952524657374, 0.64364843195737631, 0.47408670386667384]], [[0.61761106212360073, 0.62971040192959593, 0.49470735386519726], [0.41306026687735919, 0.55507624155570312, 0.92853759222310106], [0.3274674257337109, 0.87896980125888136, 0.39331161497503286], [0.43611526427398251, 0.72534207729003164, 0.57962529848022637], [0.69210299406574527, 0.062460995174160816, 0.93066659126857221]], [[0.083111660192682568, 0.99725328716841311, 0.27121278820489403], [0.73406289503925604, 0.80538390625619516, 0.29315139024767889], [0.082676638871250652, 0.37206452764369702, 0.2649049794742897], [0.12408227322470267, 0.74472176475463692, 0.8174354535597258], [0.21686067449726132, 0.62883396701473271, 0.86566439632322278]]], [[[0.89669530227407024, 0.19289830337776714, 0.089853089927319219], [0.98760388655662767, 0.89008462181980053, 0.69570048836621301], [0.14682408248171763, 0.54479399309445797, 0.72720013814912943], [0.045069230893828971, 0.11461994792470509, 0.27430837116265094], [0.67604305313005575, 0.052652824417676269, 0.63863799167616264]], [[0.74279794050475256, 0.098764285738637048, 0.90391176265205009], [0.031888689832916151, 0.91362524779923027, 0.825151695764614], [0.013540853593327129, 0.13613017881117784, 0.94594185269170306], [0.0055776780082078536, 0.19975775247355665, 0.072259244456054361], [0.74617514477019764, 0.32471755948895109, 0.083830790467844252]], [[0.66811203288133636, 0.27633938675577341, 0.040893602491139269], [0.51849181901456176, 0.011501661678884445, 0.77217244062645096], [0.14375142366801896, 0.90381912060700553, 0.20190196091630164], [0.21322538371212196, 0.36585148392876865, 0.083727919690708918], [0.3097408597687018, 0.59723759835045875, 0.4886767026543215]], [[0.16357973246609758, 0.92087932544946327, 0.3384708586629751], [0.067136871978869417, 0.21776940016537627, 0.7705745192216632], [0.98259021799791124, 0.50961837355614692, 0.83555050647205176], [0.67608441880904768, 0.90312717890505212, 0.18053751246433791], [0.29700456036496337, 0.37000347516593268, 0.96452501688322201]], [[0.32688708306221248, 0.8365877691645266, 0.17336317193714579], [0.90487915797856355, 0.50717605535081722, 0.33815521397532988], [0.11780315669470454, 0.84781686200603812, 0.56387171418123161], [0.025302923773783292, 0.51725791550326283, 0.091383009756073719], [0.77550897972876764, 0.78383408486529027, 0.39861904820998628]], [[0.38591849764482156, 0.88954837248020835, 0.94854305672295536], [0.57116041017796104, 0.26025685153372258, 0.087398933964749181], [0.9500891765988958, 0.91514518514695409, 0.41455805101908916], [0.49709796581897214, 0.58623087645333538, 0.99567144777732952], [0.46118329193118057, 0.5775973942356375, 0.50373425281250117]]], [[[0.50121029052250199, 0.97961710518990397, 0.25968884629076505], [0.34014901845291678, 0.46162800321732056, 0.46244053814165542], [0.52473426277986934, 0.62035771009638596, 0.67250736503998665], [0.38672422756992952, 0.2779946669756711, 0.20218957593196996], [0.59604573638981928, 0.024040951338803018, 0.61362301053778479]], [[0.83964586000872143, 0.99137647765888626, 0.3213278073048903], [0.50226612101424373, 0.63425549308364282, 0.26181637288077153], [0.70988178201479624, 0.01605697643006665, 0.65300994192816364], [0.66902642711157012, 0.12496171226451158, 0.97775281702208727], [0.43836631773999302, 0.65765546467850677, 0.98052750508062603]], [[0.90539506049457286, 0.5477116805032417, 0.65052354082147279], [0.24924938940701435, 0.33302080748158636, 0.42271974362844567], [0.49401780858839472, 0.17866077442511874, 0.13806221412494846], [0.15760354547519873, 0.427519458168096, 0.53801604177513895], [0.94249603564964812, 0.12238866172772112, 0.44347748909798668]], [[0.077420345199719076, 0.15127406852408509, 0.66676703504369916], [0.33541924877656193, 0.58965539531548805, 0.59602448266722396], [0.74814540749654013, 0.3405615434346374, 0.23258421912054961], [0.34254483202651698, 0.50051875556983916, 0.7066991552934766], [0.51876294455266225, 0.23871624932785562, 0.66835953935309655]], [[0.080238481120057381, 0.10002775155524224, 0.27219972402671833], [0.66024077280618931, 0.78142461690690623, 0.02138659211584526], [0.1733046507979048, 0.83740599399143623, 0.24763289061444038], [0.69604609867940004, 0.62515136615997291, 0.27251249907669461], [0.072460996251230703, 0.45182139135661836, 0.73082092555678158]], [[0.088423654573769661, 0.18339223736193833, 0.02175849452611256], [0.6058055700809617, 0.50324964416184914, 0.16445448952327724], [0.79230850413129672, 0.027228331505205983, 0.18313393017353108], [0.40327962525921779, 0.53399983584420663, 0.2644936614840051], [0.95300193272232647, 0.18083330185835367, 0.96908167133421397]]], [[[0.91385184246409168, 0.58113677477322401, 0.70231008005224593], [0.9474537951253309, 0.62016324060777628, 0.17138498474532138], [0.34849671492753898, 0.46869766397564316, 0.73763896217058134], [0.87211066934174009, 0.48734126881749473, 0.64174237807970491], [0.79905289900338639, 0.42435051812848124, 0.68150971117710202]], [[0.36588037184075373, 0.79537939361517529, 0.85181903232783007], [0.41141769837196351, 0.86786051623070848, 0.22414117656064658], [0.81640895923110746, 0.12992365640477233, 0.2355496056791454], [0.45371835055421261, 0.78160552803709338, 0.092958530073615653], [0.41049364219195672, 0.42702222368276033, 0.070574576044564519]], [[0.45831121140198006, 0.045085310497666065, 0.79294289698788456], [0.44302959532218689, 0.65443298771574432, 0.68173823126947375], [0.39094486774242743, 0.066819108786377535, 0.6808460172331281], [0.5046311706772918, 0.32051470604316801, 0.77716245540800988], [0.75707151715004528, 0.67614765942702015, 0.83284890164722847]], [[0.20347799733225258, 0.71006918737014257, 0.92588254441682205], [0.96207595455734829, 0.49552591933007439, 0.12398037176865617], [0.68313730954291374, 0.10415236445564258, 0.45816046027438184], [0.36162415054339936, 0.99131438275747452, 0.22372131074708346], [0.67086419049901891, 0.47845701936987228, 0.36985109558546647]], [[0.27775993248683417, 0.10092563911048058, 0.72711226482933478], [0.27741437292163063, 0.097359636516875292, 0.81506667907392638], [0.92134062138716277, 0.42785167607992813, 0.23324025474365606], [0.34160362940981959, 0.41289016296485281, 0.78760263706808065], [0.0083578369819241605, 0.83144296140885887, 0.33782688147606554]], [[0.46357765230192827, 0.13598683924850008, 0.99588735461627897], [0.84918521935812763, 0.023911125125060662, 0.44141960863528895], [0.15630046849864843, 0.27771188177990347, 0.34981662538526515], [0.45994233771683468, 0.63477232786494087, 0.97573238156786168], [0.57208602704347389, 0.11631534583474779, 0.86853091655212733]]]])          xx=numpy.array([[[[0.72255651065698279, 0.83381610263629191, 0.088396309723070443], [0.79855742227758819,
1554    0.839338005541306, 0.81495790516402389], [0.62626755304522941, 0.078799158362552024, 0.33267140687945473],
1555    [0.43940707734260109, 0.51599082070096458, 0.84321011444082217], [0.24171707936068787, 0.0060558032715870569,
1556    0.56078845976765612]], [[0.57377382745965855, 0.49340859714655683, 0.2092972590061013], [0.68637889059321167,
1557    0.11029705930136668, 0.96396795238233834], [0.55179714688174419, 0.35108623014240958, 0.51181447099189581],
1558    [0.32324557912243723, 0.78654583988331572, 0.33712954059082634], [0.079321394582968718, 0.23774608497170258,
1559    0.69285790426559601]], [[0.85886317386456423, 0.13584169380100597, 0.24292242178587076], [0.61177645246068624,
1560    0.3036432086030022, 0.53035500209869535], [0.28628042513462981, 0.24043761219547199, 0.94891705021835726],
1561    [0.60395478182149109, 0.083245941455203476, 0.13027004597807579], [0.15048976641157319, 0.11401314017400843,
1562    0.18795600878276586]], [[0.09137780979901966, 0.32634976420570005, 0.61940335197091201], [0.37432581452719493,
1563    0.97387697903168757, 0.60713072535399282], [0.81126283730616289, 0.72286470992579144, 0.33277102567004557],
1564    [0.65725608926170365, 0.22113878439984025, 0.39873142337432677], [0.56458095772442962, 0.69984805698516706,
1565    0.13953969142708544]], [[0.14180888147181303, 0.6449607100547553, 0.31077677774512735], [0.78970211385749289,
1566    0.35440985857825957, 0.33586351342060605], [0.31861742504282387, 0.0091224852408655632, 0.72485922708603734],
1567    [0.19028038521297774, 0.813785636029978, 0.96553983147048672], [0.91561864871190557, 0.11116693352450835,
1568    0.70275695888285916]], [[0.93465367590426696, 0.08776495337568968, 0.92008576270779563], [0.55687479001255391,
1569    0.72198162368591801, 0.93723076623527124], [0.62999175799626039, 0.36064429891165684, 0.59775442438928683],
1570    [0.22690790215469459, 0.4685878404511844, 0.89223770066308428], [0.92972243126999998, 0.46025840602562273,
1571    0.40968201803367088]]], [[[0.94180597092282947, 0.96234744551267848, 0.87288463327476029], [0.41806750845644847,
1572    0.22788237798369737, 0.11966406067717961], [0.69733599374787714, 0.18851158381113808, 0.16370374653731978],
1573    [0.63211076175223446, 0.41154348987607725, 0.98533970125915882], [0.65773473183219433, 0.041250994596582657,
1574    0.96992667507584374]], [[0.40058859823800097, 0.12179652261476415, 0.99555017499337206], [0.68443796318239791,
1575    0.88112987266527754, 0.6935433018004582], [0.85006065726887914, 0.79136227813817728, 0.44775493806515188],
1576    [0.17365733710621323, 0.15978381135481545, 0.71519613537661453], [0.52661904411861471, 0.52676789546431813,
1577    0.48249638132196371]], [[0.19890220183563068, 0.6528046793768485, 0.39835999493439911], [0.30149513914196047,
1578    0.41004970280230157, 0.095723514003266286], [0.59342390611233331, 0.64188662999081492, 0.94573923409175364],
1579    [0.97182053826713977, 0.030426067513154798, 0.61174589100753962], [0.72835687654810322, 0.68713012593738343,
1580    0.31568564502713259]], [[0.95749206532668674, 0.93726678894579174, 0.4906774028313089], [0.38333713090398269,
1581    0.31180194657763527, 0.87930430515980695], [0.43976370526311137, 0.044494145039117527, 0.74864265600876034],
1582    [0.26436773182558582, 0.13762336840153333, 0.063845322270331906], [0.28527952524657374, 0.64364843195737631,
1583    0.47408670386667384]], [[0.61761106212360073, 0.62971040192959593, 0.49470735386519726], [0.41306026687735919,
1584    0.55507624155570312, 0.92853759222310106], [0.3274674257337109, 0.87896980125888136, 0.39331161497503286],
1585    [0.43611526427398251, 0.72534207729003164, 0.57962529848022637], [0.69210299406574527, 0.062460995174160816,
1586    0.93066659126857221]], [[0.083111660192682568, 0.99725328716841311, 0.27121278820489403], [0.73406289503925604,
1587    0.80538390625619516, 0.29315139024767889], [0.082676638871250652, 0.37206452764369702, 0.2649049794742897],
1588    [0.12408227322470267, 0.74472176475463692, 0.8174354535597258], [0.21686067449726132, 0.62883396701473271,
1589    0.86566439632322278]]], [[[0.89669530227407024, 0.19289830337776714, 0.089853089927319219], [0.98760388655662767,
1590    0.89008462181980053, 0.69570048836621301], [0.14682408248171763, 0.54479399309445797, 0.72720013814912943],
1591    [0.045069230893828971, 0.11461994792470509, 0.27430837116265094], [0.67604305313005575, 0.052652824417676269,
1592    0.63863799167616264]], [[0.74279794050475256, 0.098764285738637048, 0.90391176265205009], [0.031888689832916151,
1593    0.91362524779923027, 0.825151695764614], [0.013540853593327129, 0.13613017881117784, 0.94594185269170306],
1594    [0.0055776780082078536, 0.19975775247355665, 0.072259244456054361], [0.74617514477019764, 0.32471755948895109,
1595    0.083830790467844252]], [[0.66811203288133636, 0.27633938675577341, 0.040893602491139269], [0.51849181901456176,
1596    0.011501661678884445, 0.77217244062645096], [0.14375142366801896, 0.90381912060700553, 0.20190196091630164],
1597    [0.21322538371212196, 0.36585148392876865, 0.083727919690708918], [0.3097408597687018, 0.59723759835045875,
1598    0.4886767026543215]], [[0.16357973246609758, 0.92087932544946327, 0.3384708586629751], [0.067136871978869417,
1599    0.21776940016537627, 0.7705745192216632], [0.98259021799791124, 0.50961837355614692, 0.83555050647205176],
1600    [0.67608441880904768, 0.90312717890505212, 0.18053751246433791], [0.29700456036496337, 0.37000347516593268,
1601    0.96452501688322201]], [[0.32688708306221248, 0.8365877691645266, 0.17336317193714579], [0.90487915797856355,
1602    0.50717605535081722, 0.33815521397532988], [0.11780315669470454, 0.84781686200603812, 0.56387171418123161],
1603    [0.025302923773783292, 0.51725791550326283, 0.091383009756073719], [0.77550897972876764, 0.78383408486529027,
1604    0.39861904820998628]], [[0.38591849764482156, 0.88954837248020835, 0.94854305672295536], [0.57116041017796104,
1605    0.26025685153372258, 0.087398933964749181], [0.9500891765988958, 0.91514518514695409, 0.41455805101908916],
1606    [0.49709796581897214, 0.58623087645333538, 0.99567144777732952], [0.46118329193118057, 0.5775973942356375,
1607    0.50373425281250117]]], [[[0.50121029052250199, 0.97961710518990397, 0.25968884629076505], [0.34014901845291678,
1608    0.46162800321732056, 0.46244053814165542], [0.52473426277986934, 0.62035771009638596, 0.67250736503998665],
1609    [0.38672422756992952, 0.2779946669756711, 0.20218957593196996], [0.59604573638981928, 0.024040951338803018,
1610    0.61362301053778479]], [[0.83964586000872143, 0.99137647765888626, 0.3213278073048903], [0.50226612101424373,
1611    0.63425549308364282, 0.26181637288077153], [0.70988178201479624, 0.01605697643006665, 0.65300994192816364],
1612    [0.66902642711157012, 0.12496171226451158, 0.97775281702208727], [0.43836631773999302, 0.65765546467850677,
1613    0.98052750508062603]], [[0.90539506049457286, 0.5477116805032417, 0.65052354082147279], [0.24924938940701435,
1614    0.33302080748158636, 0.42271974362844567], [0.49401780858839472, 0.17866077442511874, 0.13806221412494846],
1615    [0.15760354547519873, 0.427519458168096, 0.53801604177513895], [0.94249603564964812, 0.12238866172772112,
1616    0.44347748909798668]], [[0.077420345199719076, 0.15127406852408509, 0.66676703504369916], [0.33541924877656193,
1617    0.58965539531548805, 0.59602448266722396], [0.74814540749654013, 0.3405615434346374, 0.23258421912054961],
1618    [0.34254483202651698, 0.50051875556983916, 0.7066991552934766], [0.51876294455266225, 0.23871624932785562,
1619    0.66835953935309655]], [[0.080238481120057381, 0.10002775155524224, 0.27219972402671833], [0.66024077280618931,
1620    0.78142461690690623, 0.02138659211584526], [0.1733046507979048, 0.83740599399143623, 0.24763289061444038],
1621    [0.69604609867940004, 0.62515136615997291, 0.27251249907669461], [0.072460996251230703, 0.45182139135661836,
1622    0.73082092555678158]], [[0.088423654573769661, 0.18339223736193833, 0.02175849452611256], [0.6058055700809617,
1623    0.50324964416184914, 0.16445448952327724], [0.79230850413129672, 0.027228331505205983, 0.18313393017353108],
1624    [0.40327962525921779, 0.53399983584420663, 0.2644936614840051], [0.95300193272232647, 0.18083330185835367,
1625    0.96908167133421397]]], [[[0.91385184246409168, 0.58113677477322401, 0.70231008005224593], [0.9474537951253309,
1626    0.62016324060777628, 0.17138498474532138], [0.34849671492753898, 0.46869766397564316, 0.73763896217058134],
1627    [0.87211066934174009, 0.48734126881749473, 0.64174237807970491], [0.79905289900338639, 0.42435051812848124,
1628    0.68150971117710202]], [[0.36588037184075373, 0.79537939361517529, 0.85181903232783007], [0.41141769837196351,
1629    0.86786051623070848, 0.22414117656064658], [0.81640895923110746, 0.12992365640477233, 0.2355496056791454],
1630    [0.45371835055421261, 0.78160552803709338, 0.092958530073615653], [0.41049364219195672, 0.42702222368276033,
1631    0.070574576044564519]], [[0.45831121140198006, 0.045085310497666065, 0.79294289698788456], [0.44302959532218689,
1632    0.65443298771574432, 0.68173823126947375], [0.39094486774242743, 0.066819108786377535, 0.6808460172331281],
1633    [0.5046311706772918, 0.32051470604316801, 0.77716245540800988], [0.75707151715004528, 0.67614765942702015,
1634    0.83284890164722847]], [[0.20347799733225258, 0.71006918737014257, 0.92588254441682205], [0.96207595455734829,
1635    0.49552591933007439, 0.12398037176865617], [0.68313730954291374, 0.10415236445564258, 0.45816046027438184],
1636    [0.36162415054339936, 0.99131438275747452, 0.22372131074708346], [0.67086419049901891, 0.47845701936987228,
1637    0.36985109558546647]], [[0.27775993248683417, 0.10092563911048058, 0.72711226482933478], [0.27741437292163063,
1638    0.097359636516875292, 0.81506667907392638], [0.92134062138716277, 0.42785167607992813, 0.23324025474365606],
1639    [0.34160362940981959, 0.41289016296485281, 0.78760263706808065], [0.0083578369819241605, 0.83144296140885887,
1640    0.33782688147606554]], [[0.46357765230192827, 0.13598683924850008, 0.99588735461627897], [0.84918521935812763,
1641    0.023911125125060662, 0.44141960863528895], [0.15630046849864843, 0.27771188177990347, 0.34981662538526515],
1642    [0.45994233771683468, 0.63477232786494087, 0.97573238156786168], [0.57208602704347389, 0.11631534583474779,
1643    0.86853091655212733]]]])
1644          ref=sqrt(xx)          ref=sqrt(xx)
1645          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1646          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 951  class SymbolicTestCase(unittest.TestCase Line 1660  class SymbolicTestCase(unittest.TestCase
1660          x=Symbol('x', shape)          x=Symbol('x', shape)
1661          y=tan(x)          y=tan(x)
1662          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1663          xx=numpy.array([-0.14200146104850608, 0.55199436405695579, -0.72437980114165357, 0.54709933137129374, -0.87572550813546113, 0.54367761243658963])          xx=numpy.array([-0.14200146104850608, 0.55199436405695579, -0.72437980114165357, 0.54709933137129374,
1664    -0.87572550813546113, 0.54367761243658963])
1665          ref=tan(xx)          ref=tan(xx)
1666          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1667          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 961  class SymbolicTestCase(unittest.TestCase Line 1671  class SymbolicTestCase(unittest.TestCase
1671          x=Symbol('x', shape)          x=Symbol('x', shape)
1672          y=tan(x)          y=tan(x)
1673          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1674          xx=numpy.array([[-0.28165724053839392], [-0.9979812387072815], [0.6196421842440949], [-0.55984839501305284], [-0.90025481208944447], [0.039912238206123662]])          xx=numpy.array([[-0.28165724053839392], [-0.9979812387072815], [0.6196421842440949], [-0.55984839501305284],
1675    [-0.90025481208944447], [0.039912238206123662]])
1676          ref=tan(xx)          ref=tan(xx)
1677          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1678          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 971  class SymbolicTestCase(unittest.TestCase Line 1682  class SymbolicTestCase(unittest.TestCase
1682          x=Symbol('x', shape)          x=Symbol('x', shape)
1683          y=tan(x)          y=tan(x)
1684          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1685          xx=numpy.array([[[-0.32601211340980618, 0.63454643711267789, -0.45601589073511661, 0.74928379052525806, 0.044787945982150079, -0.84750426268279266], [0.59672024350466324, 0.60118070196120521, 0.73000920374303635, 0.95615655945060252, -0.16391789424129, -0.93003036732378042]], [[0.33600995453074667, -0.33380626353926068, 0.32296628695685414, -0.84507985878052083, 0.45550744326858905, 0.92956275280795997], [0.092215953473159473, -0.92624398799798224, 0.88877673878896624, -0.90947264228186619, 0.91763999125337503, -0.23639346745535073]]])          xx=numpy.array([[[-0.32601211340980618, 0.63454643711267789, -0.45601589073511661, 0.74928379052525806,
1686    0.044787945982150079, -0.84750426268279266], [0.59672024350466324, 0.60118070196120521, 0.73000920374303635,
1687    0.95615655945060252, -0.16391789424129, -0.93003036732378042]], [[0.33600995453074667, -0.33380626353926068,
1688    0.32296628695685414, -0.84507985878052083, 0.45550744326858905, 0.92956275280795997], [0.092215953473159473,
1689    -0.92624398799798224, 0.88877673878896624, -0.90947264228186619, 0.91763999125337503, -0.23639346745535073]]])
1690          ref=tan(xx)          ref=tan(xx)
1691          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1692          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 981  class SymbolicTestCase(unittest.TestCase Line 1696  class SymbolicTestCase(unittest.TestCase
1696          x=Symbol('x', shape)          x=Symbol('x', shape)
1697          y=tan(x)          y=tan(x)
1698          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1699          xx=numpy.array([[[[-0.39361167932986962, 0.74522581327046944, 0.60340274502183977], [-0.6594807460274732, 0.58589637220463398, -0.11734763382586055], [0.80638763124208013, -0.64402850551432045, 0.36021742857944283], [0.021008293536134204, 0.97682781575076816, -0.10551371038954671], [0.45272674007823088, -0.85178595769433008, 0.55624629341747567]], [[0.31391820874752718, 0.21075784758815663, 0.26314878859007695], [-0.98448333512712716, -0.72386430989711426, -0.26227979662440482], [0.96810162374605735, -0.83650196524727338, -0.59800258471380374], [0.23607297469872379, -0.24038831390187276, 0.11086313735031772], [-0.39471124201884034, -0.48352767341106229, 0.21186754666535212]], [[-0.92540364716984591, 0.39613198860468768, 0.40648440480928327], [0.47970852348990078, -0.51595317096476734, 0.019379089520323856], [0.99883716946833001, 0.20405300322814135, -0.28044851950989402], [0.60005623011836895, -0.41740832183053578, 0.32623688963170117], [0.84656326181286734, -0.17647518491381819, 0.82349636481198618]], [[0.16905962725378498, 0.98168860100078037, 0.9353114074077038], [0.19224595065824857, -0.066366531515243965, 0.29121472159397022], [0.86700433635139884, -0.79216700487801117, 0.69402792626896992], [-0.38719928456391628, 0.48160408888843276, 0.8230283146023567], [-0.034941545895473158, 0.11207736007529601, -0.76628638474929756]]], [[[0.8686966875749631, -0.62065531097846649, -0.46180638263063289], [0.11048319908775661, -0.94827689038381124, -0.55165165131652838], [-0.22050584520475791, 0.40277438568381108, 0.14008031400767562], [-0.99935387872751602, -0.71543940516080284, -0.43778571710569425], [0.37798157306313129, -0.94338234063989135, -0.42152333436894796]], [[0.43703301877468159, 0.39748667010044048, -0.48045382845548423], [-0.034882375838574564, 0.93307896081154906, 0.5563628429503451], [-0.94652875131975178, 0.75880890900809206, -0.51068487819970043], [0.3221147597656433, -0.37159197684999445, 0.34493062162810562], [-0.60506673953023959, 0.51339586409976645, 0.56922924643395412]], [[0.29716600159661311, -0.17816615862073992, -0.86445473447538435], [-0.35327015227085168, -0.56939353868570652, -0.085554286062446749], [0.2790841392787613, -0.34591132364831556, -0.72410488581237797], [0.37497587768910234, -0.35746717094914926, -0.056680969361326827], [0.18448099324282152, 0.14874815449357204, 0.59801648660396767]], [[0.90371247560747991, -0.14391938108674629, -0.70974621137275418], [-0.40373973907758876, 0.52028563903355174, -0.89764982436604335], [0.29560404854999356, 0.87638099062861352, 0.50647543392228189], [-0.62959804758651794, 0.76104749591985699, -0.65246519534456882], [-0.21062711278245239, -0.59382460014460814, -0.71289385582368081]]], [[[-0.057250620340783653, 0.77854761025428609, -0.38648357938612898], [0.45542175255587547, -0.19609171451182972, -0.63002638687212631], [-0.85247705442935584, -0.84366299228257202, 0.09426362678490352], [-0.016577883362343337, -0.74879437402571525, -0.68366817051255491], [-0.33604040313252814, -0.27164630945300972, -0.99475638768020791]], [[-0.70130149091787586, 0.021562173043616184, 0.028213936211842094], [-0.78481956059302371, 0.15649596053059134, 0.46454870329897213], [-0.9149659414389737, -0.22891758886102731, 0.41037262794506679], [-0.21207892294129871, 0.98005671987894072, 0.20078126352133818], [-0.90786908894320839, -0.9292322436731113, -0.93804227944070973]], [[0.66602248301188327, -0.036918117482479529, 0.95756625797125583], [-0.98482796202997291, 0.74646671050364821, 0.37761108311585767], [0.70069203580671968, -0.026580657560474341, -0.52863034488962501], [0.91109958034323801, 0.83013879029514004, 0.86314305237022082], [-0.15983859961928082, 0.26188047697492101, 0.4520224761020788]], [[-0.23753974221656171, 0.69903406974916571, 0.078831077157341722], [-0.60754659217688189, 0.87886737408616855, -0.16926573195254613], [-0.396356714566515, -0.45995800030317469, 0.46968566755059604], [0.004171700121168076, 0.18929502726741632, 0.74122834576831154], [-0.88950872921628754, 0.85812775846443068, 0.090850855338491909]]], [[[0.94272405729076003, -0.18978264009146129, 0.71108734775582194], [-0.60356815477109649, 0.2966157597336696, 0.60844941792654161], [0.00070885034533185731, -0.75060628565340282, -0.42600443605384442], [0.096238135067595154, 0.25901881694088336, 0.91590062410211792], [-0.39030807410637514, -0.75907117662165935, -0.20254736582842359]], [[0.58754460092193561, -0.24371471431563485, 0.58627489581326597], [0.88913896291886241, 0.67488959799173909, 0.93377638758907922], [0.48859512249307491, -0.44057956114388985, 0.52751079353868247], [-0.88386673247457836, -0.92181365018497652, 0.87664934709731623], [-0.093747856591055889, 0.50375815759268705, -0.10854436426015468]], [[-0.36247514070986986, 0.28805372072027136, 0.0074580022781263189], [0.21178312012491851, 0.17124067789062924, -0.81397797570729957], [-0.45432214958372841, -0.34287904328486429, 0.16559848179841796], [0.32622875399077267, 0.8831115716331901, 0.49293335318565323], [0.37786144819047274, -0.64318613413115933, 0.37213148926932593]], [[0.45778076631363485, -0.45488393452463471, 0.86244580239817781], [-0.54667031890171836, 0.56956513702652378, -0.29001978466158107], [-0.27371847261131044, -0.26805148200740891, -0.7138030282340837], [0.86535912062485276, -0.36626574115645316, 0.69491108145358949], [0.7486178910065886, -0.32082327504674524, -0.88028371669550376]]]])          xx=numpy.array([[[[-0.39361167932986962, 0.74522581327046944, 0.60340274502183977], [-0.6594807460274732,
1700    0.58589637220463398, -0.11734763382586055], [0.80638763124208013, -0.64402850551432045, 0.36021742857944283],
1701    [0.021008293536134204, 0.97682781575076816, -0.10551371038954671], [0.45272674007823088, -0.85178595769433008,
1702    0.55624629341747567]], [[0.31391820874752718, 0.21075784758815663, 0.26314878859007695], [-0.98448333512712716,
1703    -0.72386430989711426, -0.26227979662440482], [0.96810162374605735, -0.83650196524727338, -0.59800258471380374],
1704    [0.23607297469872379, -0.24038831390187276, 0.11086313735031772], [-0.39471124201884034, -0.48352767341106229,
1705    0.21186754666535212]], [[-0.92540364716984591, 0.39613198860468768, 0.40648440480928327], [0.47970852348990078,
1706    -0.51595317096476734, 0.019379089520323856], [0.99883716946833001, 0.20405300322814135, -0.28044851950989402],
1707    [0.60005623011836895, -0.41740832183053578, 0.32623688963170117], [0.84656326181286734, -0.17647518491381819,
1708    0.82349636481198618]], [[0.16905962725378498, 0.98168860100078037, 0.9353114074077038], [0.19224595065824857,
1709    -0.066366531515243965, 0.29121472159397022], [0.86700433635139884, -0.79216700487801117, 0.69402792626896992],
1710    [-0.38719928456391628, 0.48160408888843276, 0.8230283146023567], [-0.034941545895473158, 0.11207736007529601,
1711    -0.76628638474929756]]], [[[0.8686966875749631, -0.62065531097846649, -0.46180638263063289], [0.11048319908775661,
1712    -0.94827689038381124, -0.55165165131652838], [-0.22050584520475791, 0.40277438568381108, 0.14008031400767562],
1713    [-0.99935387872751602, -0.71543940516080284, -0.43778571710569425], [0.37798157306313129, -0.94338234063989135,
1714    -0.42152333436894796]], [[0.43703301877468159, 0.39748667010044048, -0.48045382845548423], [-0.034882375838574564,
1715    0.93307896081154906, 0.5563628429503451], [-0.94652875131975178, 0.75880890900809206, -0.51068487819970043],
1716    [0.3221147597656433, -0.37159197684999445, 0.34493062162810562], [-0.60506673953023959, 0.51339586409976645,
1717    0.56922924643395412]], [[0.29716600159661311, -0.17816615862073992, -0.86445473447538435], [-0.35327015227085168,
1718    -0.56939353868570652, -0.085554286062446749], [0.2790841392787613, -0.34591132364831556, -0.72410488581237797],
1719    [0.37497587768910234, -0.35746717094914926, -0.056680969361326827], [0.18448099324282152, 0.14874815449357204,
1720    0.59801648660396767]], [[0.90371247560747991, -0.14391938108674629, -0.70974621137275418], [-0.40373973907758876,
1721    0.52028563903355174, -0.89764982436604335], [0.29560404854999356, 0.87638099062861352, 0.50647543392228189],
1722    [-0.62959804758651794, 0.76104749591985699, -0.65246519534456882], [-0.21062711278245239, -0.59382460014460814,
1723    -0.71289385582368081]]], [[[-0.057250620340783653, 0.77854761025428609, -0.38648357938612898], [0.45542175255587547,
1724    -0.19609171451182972, -0.63002638687212631], [-0.85247705442935584, -0.84366299228257202, 0.09426362678490352],
1725    [-0.016577883362343337, -0.74879437402571525, -0.68366817051255491], [-0.33604040313252814, -0.27164630945300972,
1726    -0.99475638768020791]], [[-0.70130149091787586, 0.021562173043616184, 0.028213936211842094], [-0.78481956059302371,
1727    0.15649596053059134, 0.46454870329897213], [-0.9149659414389737, -0.22891758886102731, 0.41037262794506679],
1728    [-0.21207892294129871, 0.98005671987894072, 0.20078126352133818], [-0.90786908894320839, -0.9292322436731113,
1729    -0.93804227944070973]], [[0.66602248301188327, -0.036918117482479529, 0.95756625797125583], [-0.98482796202997291,
1730    0.74646671050364821, 0.37761108311585767], [0.70069203580671968, -0.026580657560474341, -0.52863034488962501],
1731    [0.91109958034323801, 0.83013879029514004, 0.86314305237022082], [-0.15983859961928082, 0.26188047697492101,
1732    0.4520224761020788]], [[-0.23753974221656171, 0.69903406974916571, 0.078831077157341722], [-0.60754659217688189,
1733    0.87886737408616855, -0.16926573195254613], [-0.396356714566515, -0.45995800030317469, 0.46968566755059604],
1734    [0.004171700121168076, 0.18929502726741632, 0.74122834576831154], [-0.88950872921628754, 0.85812775846443068,
1735    0.090850855338491909]]], [[[0.94272405729076003, -0.18978264009146129, 0.71108734775582194], [-0.60356815477109649,
1736    0.2966157597336696, 0.60844941792654161], [0.00070885034533185731, -0.75060628565340282, -0.42600443605384442],
1737    [0.096238135067595154, 0.25901881694088336, 0.91590062410211792], [-0.39030807410637514, -0.75907117662165935,
1738    -0.20254736582842359]], [[0.58754460092193561, -0.24371471431563485, 0.58627489581326597], [0.88913896291886241,
1739    0.67488959799173909, 0.93377638758907922], [0.48859512249307491, -0.44057956114388985, 0.52751079353868247],
1740    [-0.88386673247457836, -0.92181365018497652, 0.87664934709731623], [-0.093747856591055889, 0.50375815759268705,
1741    -0.10854436426015468]], [[-0.36247514070986986, 0.28805372072027136, 0.0074580022781263189], [0.21178312012491851,
1742    0.17124067789062924, -0.81397797570729957], [-0.45432214958372841, -0.34287904328486429, 0.16559848179841796],
1743    [0.32622875399077267, 0.8831115716331901, 0.49293335318565323], [0.37786144819047274, -0.64318613413115933,
1744    0.37213148926932593]], [[0.45778076631363485, -0.45488393452463471, 0.86244580239817781], [-0.54667031890171836,
1745    0.56956513702652378, -0.29001978466158107], [-0.27371847261131044, -0.26805148200740891, -0.7138030282340837],
1746    [0.86535912062485276, -0.36626574115645316, 0.69491108145358949], [0.7486178910065886, -0.32082327504674524,
1747    -0.88028371669550376]]]])
1748          ref=tan(xx)          ref=tan(xx)
1749          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1750          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1001  class SymbolicTestCase(unittest.TestCase Line 1764  class SymbolicTestCase(unittest.TestCase
1764          x=Symbol('x', shape)          x=Symbol('x', shape)
1765          y=tanh(x)          y=tanh(x)
1766          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1767          xx=numpy.array([-0.39196480149974411, -0.54251526921511051, -0.52139480864543208, 0.17868359648887799, 0.0089005037204492599, 0.23043826836232895])          xx=numpy.array([-0.39196480149974411, -0.54251526921511051, -0.52139480864543208, 0.17868359648887799,
1768    0.0089005037204492599, 0.23043826836232895])
1769          ref=tanh(xx)          ref=tanh(xx)
1770          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1771          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1011  class SymbolicTestCase(unittest.TestCase Line 1775  class SymbolicTestCase(unittest.TestCase
1775          x=Symbol('x', shape)          x=Symbol('x', shape)
1776          y=tanh(x)          y=tanh(x)
1777          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1778          xx=numpy.array([[-0.48553795664137289, -0.54266228456823828, 0.28217202264662422, -0.29216615510382327, 0.50459507430806538], [0.93381590221704958, 0.35428267816381576, -0.20203290604780344, -0.84060951155846686, -0.92373613333293636], [0.91344206146861673, 0.59459160694248836, -0.064996620389091264, 0.72847859506056656, 0.41412421220478057]])          xx=numpy.array([[-0.48553795664137289, -0.54266228456823828, 0.28217202264662422, -0.29216615510382327,
1779    0.50459507430806538], [0.93381590221704958, 0.35428267816381576, -0.20203290604780344, -0.84060951155846686,
1780    -0.92373613333293636], [0.91344206146861673, 0.59459160694248836, -0.064996620389091264, 0.72847859506056656,
1781    0.41412421220478057]])
1782          ref=tanh(xx)          ref=tanh(xx)
1783          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1784          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1021  class SymbolicTestCase(unittest.TestCase Line 1788  class SymbolicTestCase(unittest.TestCase
1788          x=Symbol('x', shape)          x=Symbol('x', shape)
1789          y=tanh(x)          y=tanh(x)
1790          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1791          xx=numpy.array([[[0.94545473952359593, -0.88260767783755489, -0.39608996855442458], [-0.38084063931365431, 0.0084523510667395829, 0.48032048546370709], [0.52747664660496429, 0.24265492367668973, 0.18447217429205365], [0.84444752845755211, 0.09694699724475675, 0.93071570178439722], [0.78815805833653085, 0.2650987641752085, 0.1453372965779669]], [[-0.70234909882964303, -0.54019981751523027, 0.75060083688122536], [0.43383860659626383, 0.78214973033753021, 0.99438285869115606], [0.50897931090996273, -0.40361560071442049, 0.75175326664108044], [0.078491553080030974, 0.25640940637265919, 0.05849443439337354], [0.45036803442872086, 0.34400943330161837, -0.32026785810909519]], [[-0.17242359211073288, -0.76525329107995455, 0.1203010267264395], [-0.75378149034427544, -0.13784972986763488, 0.082743915100908838], [-0.11608570364014636, 0.6827892088482328, 0.82572499503393493], [-0.028093708749234114, -0.82979850639587394, 0.017586892786316755], [0.15875914618255837, -0.80165770170308548, 0.98409276246266053]]])          xx=numpy.array([[[0.94545473952359593, -0.88260767783755489, -0.39608996855442458], [-0.38084063931365431,
1792    0.0084523510667395829, 0.48032048546370709], [0.52747664660496429, 0.24265492367668973, 0.18447217429205365],
1793    [0.84444752845755211, 0.09694699724475675, 0.93071570178439722], [0.78815805833653085, 0.2650987641752085,
1794    0.1453372965779669]], [[-0.70234909882964303, -0.54019981751523027, 0.75060083688122536], [0.43383860659626383,
1795    0.78214973033753021, 0.99438285869115606], [0.50897931090996273, -0.40361560071442049, 0.75175326664108044],
1796    [0.078491553080030974, 0.25640940637265919, 0.05849443439337354], [0.45036803442872086, 0.34400943330161837,
1797    -0.32026785810909519]], [[-0.17242359211073288, -0.76525329107995455, 0.1203010267264395], [-0.75378149034427544,
1798    -0.13784972986763488, 0.082743915100908838], [-0.11608570364014636, 0.6827892088482328, 0.82572499503393493],
1799    [-0.028093708749234114, -0.82979850639587394, 0.017586892786316755], [0.15875914618255837, -0.80165770170308548,
1800    0.98409276246266053]]])
1801          ref=tanh(xx)          ref=tanh(xx)
1802          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1803          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1031  class SymbolicTestCase(unittest.TestCase Line 1807  class SymbolicTestCase(unittest.TestCase
1807          x=Symbol('x', shape)          x=Symbol('x', shape)
1808          y=tanh(x)          y=tanh(x)
1809          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1810          xx=numpy.array([[[[0.36925408088861333, -0.8166319668013422]], [[-0.89110935322929175, -0.51815528579516568]]], [[[0.062831611367165863, -0.97227775668697092]], [[0.10014974357021189, -0.41000660621777607]]], [[[0.94663237418617285, 0.10102569077065815]], [[0.50958152199552398, 0.60908667764083657]]], [[[0.82223521505244812, 0.090202510262551217]], [[-0.25598596995961342, -0.087247739516351563]]], [[[-0.65399577676006637, 0.47061701394300859]], [[-0.066621211630382149, -0.28358502274278785]]]])          xx=numpy.array([[[[0.36925408088861333, -0.8166319668013422]], [[-0.89110935322929175, -0.51815528579516568]]],
1811    [[[0.062831611367165863, -0.97227775668697092]], [[0.10014974357021189, -0.41000660621777607]]], [[[0.94663237418617285,
1812    0.10102569077065815]], [[0.50958152199552398, 0.60908667764083657]]], [[[0.82223521505244812, 0.090202510262551217]],
1813    [[-0.25598596995961342, -0.087247739516351563]]], [[[-0.65399577676006637, 0.47061701394300859]], [[-0.066621211630382149,
1814    -0.28358502274278785]]]])
1815          ref=tanh(xx)          ref=tanh(xx)
1816          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1817          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1061  class SymbolicTestCase(unittest.TestCase Line 1841  class SymbolicTestCase(unittest.TestCase
1841          x=Symbol('x', shape)          x=Symbol('x', shape)
1842          y=whereNegative(x)          y=whereNegative(x)
1843          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1844          xx=numpy.array([[-0.14011610947358055, -0.38805302447048895, 0.47561730929995116, -0.77667238101643576, -0.37986729287196019, 0.72856527351504985], [-0.67583271624282593, 0.92113521837041623, -0.35285985999595937, -0.00072694303930620485, 0.30706411106352749, 0.26488405944565829], [0.051641850619284835, 0.26502732831505638, 0.90212370337781222, 0.21647194253753432, -0.70321392303226737, 0.833807393173152], [0.43233299002919967, 0.45638736339005925, 0.10986686261026546, -0.67368624490597528, 0.80637536196952175, -0.47101703933152583]])          xx=numpy.array([[-0.14011610947358055, -0.38805302447048895, 0.47561730929995116, -0.77667238101643576,
1845    -0.37986729287196019, 0.72856527351504985], [-0.67583271624282593, 0.92113521837041623, -0.35285985999595937,
1846    -0.00072694303930620485, 0.30706411106352749, 0.26488405944565829], [0.051641850619284835, 0.26502732831505638,
1847    0.90212370337781222, 0.21647194253753432, -0.70321392303226737, 0.833807393173152], [0.43233299002919967, 0.45638736339005925,
1848    0.10986686261026546, -0.67368624490597528, 0.80637536196952175, -0.47101703933152583]])
1849          ref=whereNegative(xx)          ref=whereNegative(xx)
1850          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1851          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1071  class SymbolicTestCase(unittest.TestCase Line 1855  class SymbolicTestCase(unittest.TestCase
1855          x=Symbol('x', shape)          x=Symbol('x', shape)
1856          y=whereNegative(x)          y=whereNegative(x)
1857          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1858          xx=numpy.array([[[0.49709022708318096, -0.9991658813647768, -0.68067770532082417, 0.74988986529507029, 0.24231678461175354, 0.85378207208974777]], [[-0.76040345958316724, -0.059898982578544979, 0.10810456256312384, -0.91104887556788361, 0.40065022601288525, 0.9359618888837109]], [[-0.019273629089193278, 0.6143577869376613, 0.4856067117008025, 0.30228820566695114, -0.9928344551428856, 0.66465766019824812]], [[0.2680662661555, -0.18993888196503383, 0.70276125137285428, 0.332625441549254, -0.11206420205646839, -0.85817986798511914]], [[0.25050673309941041, -0.7934972165131271, 0.13564988832164571, 0.76169589157055451, 0.82021914074941371, 0.50506063253799782]], [[0.015631009039995147, -0.61471460656535504, -0.078217724751007411, -0.96164985262782943, 0.33996006854056282, -0.1453091316545736]]])          xx=numpy.array([[[0.49709022708318096, -0.9991658813647768, -0.68067770532082417, 0.74988986529507029,
1859    0.24231678461175354, 0.85378207208974777]], [[-0.76040345958316724, -0.059898982578544979, 0.10810456256312384,
1860    -0.91104887556788361, 0.40065022601288525, 0.9359618888837109]], [[-0.019273629089193278, 0.6143577869376613,
1861    0.4856067117008025, 0.30228820566695114, -0.9928344551428856, 0.66465766019824812]], [[0.2680662661555, -0.18993888196503383,
1862    0.70276125137285428, 0.332625441549254, -0.11206420205646839, -0.85817986798511914]], [[0.25050673309941041,
1863    -0.7934972165131271, 0.13564988832164571, 0.76169589157055451, 0.82021914074941371, 0.50506063253799782]],
1864    [[0.015631009039995147, -0.61471460656535504, -0.078217724751007411, -0.96164985262782943, 0.33996006854056282,
1865    -0.1453091316545736]]])
1866          ref=whereNegative(xx)          ref=whereNegative(xx)
1867          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1868          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1081  class SymbolicTestCase(unittest.TestCase Line 1872  class SymbolicTestCase(unittest.TestCase
1872          x=Symbol('x', shape)          x=Symbol('x', shape)
1873          y=whereNegative(x)          y=whereNegative(x)
1874          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1875          xx=numpy.array([[[[0.18974799375992091, -0.89108848362168769, -0.99714838299326281, 0.15249233338699208, 0.35957697555334356, 0.0026964635517325863], [0.81288676358349488, -0.55497556685445781, 0.14014349703379936, 0.53500622875005144, -0.49468091449001084, -0.38934372479683033], [-0.70361562777255093, 0.52526544230973138, 0.5236459438683021, 0.65030043386032688, 0.3879680498655822, -0.7772188274809384]], [[-0.89339417655282438, -0.75228567087285692, -0.37606670786279861, 0.91297244769514485, -0.19350022841894088, -0.87375837452688709], [0.46694468277904244, 0.30798220921990649, 0.31554988566138453, -0.75648202290336819, 0.48383147595272513, -0.81399300811832087], [0.60296097170486984, 0.021356348549628423, 0.2607642307185789, -0.94952078952058128, 0.24260355482321927, 0.60906558053832982]], [[-0.38066433290396806, -0.94870340225840488, 0.16058623987334486, -0.99611411941266459, -0.82802023608626008, -0.11801781120206933], [-0.74951880715332653, 0.6038713537010032, 0.54236727703212351, -0.70469285254505287, -0.040976379652611472, -0.43390087339746164], [0.68267152175592405, 0.27835218888779001, 0.69871414599867321, -0.79259665551123226, -0.30008126454631867, -0.70180994888941872]], [[-0.68594092435762111, -0.053075832861085859, 0.07887458075822984, -0.14218846086926518, -0.51052555466914074, -0.32701355014331757], [-0.63649710059441955, -0.86040882988643008, -0.97385072027451192, 0.7917511606704617, -0.84187256165209789, -0.40101814099489896], [-0.077746097857161134, 0.30112420220774094, -0.76818619783445397, -0.35794543999325557, 0.33887985064692661, -0.82990621623696281]]], [[[-0.80690628106308626, 0.40109497567058439, 0.52142561477784732, 0.24390447050316655, 0.87195861906037386, -0.090738828411722539], [0.45782011983131365, 0.31251675977073212, -0.93522614783781988, 0.43991924129339566, 0.35726314361532774, -0.58360258407955734], [-0.51216694640659233, 0.51193580936832839, 0.64455230444360367, -0.67077362526142492, 0.096158543871722291, 0.043800334104726169]], [[0.68096525264272167, -0.98242719399176193, -0.89313016799388811, -0.13915770300695951, 0.96356700295681974, -0.71897653548488294], [0.9636830744321212, 0.63482782004923011, 0.010919100922413438, 0.69878620109067091, -0.086215388227256495, 0.51046997837604824], [0.13411174149486715, -0.34521163824355261, -0.21894617654166271, 0.020868122216789686, -0.61656485953710005, -0.77343621011717145]], [[-0.9577139723603536, 0.97035643539947269, -0.98463097936228117, -0.55864742528816325, 0.49901739448068172, -0.17619766385790103], [-0.55986434762291548, 0.41413001853387543, -0.22505413307320854, -0.92533317691440242, -0.75109592815075787, -0.49422235332136277], [-0.25134953219705047, 0.24150314538117468, -0.24748864789190872, -0.7284540531082766, 0.9698307658796026, 0.10010963500185732]], [[0.67563784112332703, -0.90031344983507933, -0.048220490193214394, -0.36987816266014217, 0.6825046071919243, -0.37146472268073771], [-0.74424957729773533, 0.65990647561505877, 0.81724935924684905, 0.7646269460748718, 0.46476390448806915, 0.30739813222244394], [-0.91206389966747525, -0.88333604683083222, -0.15746144446950261, 0.19693990233037995, -0.90169038562510972, -0.10237160713244786]]], [[[-0.97880009174036808, 0.13099119007059579, -0.11348428836676572, -0.25551815297419789, 0.40969232568856606, 0.51579541143530339], [-0.12632132927937034, -0.94200103769019061, 0.69233945032092947, 0.94323068263860388, -0.670629898238428, 0.33667996562186575], [-0.50312943390465548, -0.77477287887478719, 0.54616957044912318, 0.53101149021329586, 0.43875470195025401, 0.67413263293162506]], [[0.91274190318547022, 0.95377885620910474, -0.10452164583464052, -0.34478639159056756, 0.025354367755849649, -0.37141703424550832], [-0.25394650784661099, -0.12353479418147018, -0.21756821989854092, 0.7466304578848455, -0.62278337419276042, -0.35646304594085398], [-0.40933239644373853, 0.8718571933046062, 0.74817849767028122, 0.88801850462608267, -0.74106504733924905, -0.46883403300100168]], [[-0.08032948625767844, 0.0343491049345237, 0.10179424674738691, -0.281192978792977, -0.88090175041305319, 0.0068611680228787275], [0.19524094466058206, -0.53620296581105431, 0.38940209010553817, -0.88389309286710249, -0.65162896721296426, 0.46257338110776325], [-0.11939963998961844, -0.12459170323504432, 0.56721445924492242, -0.5434934377046885, -0.94097319686236203, 0.10843818162615082]], [[0.94156569655681088, 0.97937047999438565, 0.58328860247766023, 0.49999512882630359, 0.98498409635330897, -0.77617703005476235], [-0.79368894718950678, -0.49094875856870313, -0.47268575315274686, -0.48423087666296949, -0.15705360364959353, -0.092347853598065299], [-0.43773529882492035, -0.97330976684408221, 0.62275243482370546, 0.16243417577414521, -0.27746950274070858, -0.17634930756002976]]], [[[-0.57257563296277136, 0.051131913300164644, -0.095495549766847265, -0.19510866832630236, -0.71009423852663178, 0.76085183088330033], [0.060680252469367701, -0.77048545231645305, 0.26366428280734966, -0.69041926752783755, 0.718088216916698, -0.49745431621938097], [0.12318995194046978, 0.86936537085873766, 0.83918180976058321, 0.68380718722273914, 0.93333036673857861, -0.40802153642780503]], [[-0.39080649731083716, 0.89846016192617917, -0.43753436018584635, -0.54164172029960556, 0.26500666447283927, -0.80442084034012318], [-0.61280888117488774, 0.19901497307242777, -0.38809942782108231, -0.15304848336510446, -0.89682030092543341, 0.81682968047844762], [-0.37083147403347305, -0.5694861159060336, 0.82079574997354832, 0.16313708350728251, -0.96148263023930025, 0.61619631755008997]], [[-0.60218852847857085, -0.30606863782057858, -0.37854212049919034, -0.6189813873806298, -0.27466810355256932, 0.11312041334540823], [-0.24450376261524176, -0.3446492538039585, -0.11428337189518412, 0.86141817541072485, 0.01994360774629178, -0.9869163482668879], [0.83076429114401584, 0.90701559122745246, -0.11515468013785246, -0.35636953652376158, 0.60173165224519298, -0.0041944503459219185]], [[-0.72486769047997224, 0.11125913628158135, -0.94325817369156395, -0.22227144314457647, 0.73184381474788585, -0.42269341360248136], [0.3322788694093366, 0.48675876476849655, 0.95199984348648936, 0.77336176266100121, -0.75298460572165227, -0.64919265433333395], [0.97951110380594075, 0.7606183719435895, -0.92931969801866887, -0.76656529512374871, -0.96565563744445226, -0.44206017089366356]]], [[[0.06437051353673251, 0.16064165673082509, 0.66075872754206277, -0.024405885296694185, 0.83365693142502217, -0.68157234542080869], [-0.46145077162972359, 0.44283796650491913, -0.25107173989879983, 0.99700063016208107, 0.63626965157409332, 0.67543716935101461], [-0.19144043467308913, 0.0084624137917301834, -0.011459481336658861, 0.020765982666997251, -0.66394566462368454, -0.13595799606345849]], [[0.48666927295430273, -0.54018652177965421, -0.60712253356220014, 0.86032968494357509, 0.93646381542687074, 0.62229000542074231], [-0.48204694443669815, -0.043441074127007484, 0.52089066069776302, -0.14263968353974321, 0.67784661619051523, 0.67683914159762426], [-0.36406246921881258, 0.52484974557021125, -0.83945534497593077, -0.56626235962196247, -0.92874439106110906, -0.84316505863262137]], [[-0.61694738907429159, -0.84155413094960885, -0.059449787766562068, 0.75512682823773636, -0.47056126199970127, -0.94014349555090271], [0.38488296050771642, -0.68470636052993017, 0.9360344045616662, -0.38978549121193184, 0.25843508056533948, -0.4154997886443399], [0.98397174568093337, -0.17687534177156738, 0.15000998147481748, 0.67926300051950217, 0.70188052710294779, 0.76571096090863833]], [[0.10520283712355649, 0.46358590529577093, -0.23107955221500487, -0.10221032014082643, -0.40083861723237568, -0.79077105783256307], [-0.45962678686990333, -0.37161803581831654, 0.90407168311308617, -0.63118786505135183, -0.87881942461714035, -0.50043032112907881], [-0.40905017398749832, -0.78414396535965936, 0.52243010681437196, -0.34857967525022726, -0.79063821885581809, -0.44655427796158786]]], [[[-0.26830770663674852, 0.052309820978976962, -0.71260517345213703, 0.068649426504235889, -0.79584911074378639, -0.73341766864885805], [0.73182847261033501, -0.96117438640838193, 0.13525338817090482, -0.45877788351575455, -0.8514202874979051, -0.80721379845257357], [0.17064064304210924, 0.64156952246470644, 0.8579149441905618, 0.42505886722614017, -0.84192631535491813, 0.07347356074778566]], [[-0.0508167938616777, 0.79593473366420087, -0.18915387572251285, -0.78860288867907991, -0.78833850850429199, -0.034960906396380276], [0.63553534416742985, 0.54104290380014675, 0.83137356210702995, 0.21568011240898222, -0.20580699671693359, 0.521832276659004], [0.87116328689755851, 0.92974282626786442, 0.15936378842429577, 0.69133337125801075, 0.7608669199256719, -0.87784165352731791]], [[-0.75122215790102453, -0.11551204851061558, -0.95370414115103053, -0.59947328175015779, 0.30395159242315106, 0.13066616906441419], [0.061420488872834911, 0.30147702994470338, 0.27861956239959107, 0.28579025178671458, 0.36624849173491181, 0.72786096607107176], [-0.949934981054112, -0.013206267446552067, -0.22928309991217377, 0.11095083320713495, -0.69546530710777343, 0.64638482716139301]], [[0.25305577703676563, 0.42897469852970049, -0.84969441201530493, 0.49601628592368896, 0.18913452811455134, -0.42761115621334911], [-0.71085347752670947, -0.2320109793524352, 0.56299071564628056, -0.47484796914866267, -0.11629577973670235, 0.2662526509891876], [-0.60078256931253216, -0.68333526085038865, 0.22683430437623353, 0.9676042368650819, 0.77154035736113635, -0.11928404003074666]]]])          xx=numpy.array([[[[0.18974799375992091, -0.89108848362168769, -0.99714838299326281, 0.15249233338699208,
1876    0.35957697555334356, 0.0026964635517325863], [0.81288676358349488, -0.55497556685445781, 0.14014349703379936,
1877    0.53500622875005144, -0.49468091449001084, -0.38934372479683033], [-0.70361562777255093, 0.52526544230973138,
1878    0.5236459438683021, 0.65030043386032688, 0.3879680498655822, -0.7772188274809384]], [[-0.89339417655282438,
1879    -0.75228567087285692, -0.37606670786279861, 0.91297244769514485, -0.19350022841894088, -0.87375837452688709],
1880    [0.46694468277904244, 0.30798220921990649, 0.31554988566138453, -0.75648202290336819, 0.48383147595272513,
1881    -0.81399300811832087], [0.60296097170486984, 0.021356348549628423, 0.2607642307185789, -0.94952078952058128,
1882    0.24260355482321927, 0.60906558053832982]], [[-0.38066433290396806, -0.94870340225840488, 0.16058623987334486,
1883    -0.99611411941266459, -0.82802023608626008, -0.11801781120206933], [-0.74951880715332653, 0.6038713537010032,
1884    0.54236727703212351, -0.70469285254505287, -0.040976379652611472, -0.43390087339746164], [0.68267152175592405,
1885    0.27835218888779001, 0.69871414599867321, -0.79259665551123226, -0.30008126454631867, -0.70180994888941872]],
1886    [[-0.68594092435762111, -0.053075832861085859, 0.07887458075822984, -0.14218846086926518, -0.51052555466914074,
1887    -0.32701355014331757], [-0.63649710059441955, -0.86040882988643008, -0.97385072027451192, 0.7917511606704617,
1888    -0.84187256165209789, -0.40101814099489896], [-0.077746097857161134, 0.30112420220774094, -0.76818619783445397,
1889    -0.35794543999325557, 0.33887985064692661, -0.82990621623696281]]], [[[-0.80690628106308626, 0.40109497567058439,
1890    0.52142561477784732, 0.24390447050316655, 0.87195861906037386, -0.090738828411722539], [0.45782011983131365,
1891    0.31251675977073212, -0.93522614783781988, 0.43991924129339566, 0.35726314361532774, -0.58360258407955734],
1892    [-0.51216694640659233, 0.51193580936832839, 0.64455230444360367, -0.67077362526142492, 0.096158543871722291,
1893    0.043800334104726169]], [[0.68096525264272167, -0.98242719399176193, -0.89313016799388811, -0.13915770300695951,
1894    0.96356700295681974, -0.71897653548488294], [0.9636830744321212, 0.63482782004923011, 0.010919100922413438,
1895    0.69878620109067091, -0.086215388227256495, 0.51046997837604824], [0.13411174149486715, -0.34521163824355261,
1896    -0.21894617654166271, 0.020868122216789686, -0.61656485953710005, -0.77343621011717145]], [[-0.9577139723603536,
1897    0.97035643539947269, -0.98463097936228117, -0.55864742528816325, 0.49901739448068172, -0.17619766385790103],
1898    [-0.55986434762291548, 0.41413001853387543, -0.22505413307320854, -0.92533317691440242, -0.75109592815075787,
1899    -0.49422235332136277], [-0.25134953219705047, 0.24150314538117468, -0.24748864789190872, -0.7284540531082766,
1900    0.9698307658796026, 0.10010963500185732]], [[0.67563784112332703, -0.90031344983507933, -0.048220490193214394,
1901    -0.36987816266014217, 0.6825046071919243, -0.37146472268073771], [-0.74424957729773533, 0.65990647561505877,
1902    0.81724935924684905, 0.7646269460748718, 0.46476390448806915, 0.30739813222244394], [-0.91206389966747525,
1903    -0.88333604683083222, -0.15746144446950261, 0.19693990233037995, -0.90169038562510972, -0.10237160713244786]]],
1904    [[[-0.97880009174036808, 0.13099119007059579, -0.11348428836676572, -0.25551815297419789, 0.40969232568856606,
1905    0.51579541143530339], [-0.12632132927937034, -0.94200103769019061, 0.69233945032092947, 0.94323068263860388,
1906    -0.670629898238428, 0.33667996562186575], [-0.50312943390465548, -0.77477287887478719, 0.54616957044912318,
1907    0.53101149021329586, 0.43875470195025401, 0.67413263293162506]], [[0.91274190318547022, 0.95377885620910474,
1908    -0.10452164583464052, -0.34478639159056756, 0.025354367755849649, -0.37141703424550832], [-0.25394650784661099,
1909    -0.12353479418147018, -0.21756821989854092, 0.7466304578848455, -0.62278337419276042, -0.35646304594085398],
1910    [-0.40933239644373853, 0.8718571933046062, 0.74817849767028122, 0.88801850462608267, -0.74106504733924905,
1911    -0.46883403300100168]], [[-0.08032948625767844, 0.0343491049345237, 0.10179424674738691, -0.281192978792977,
1912    -0.88090175041305319, 0.0068611680228787275], [0.19524094466058206, -0.53620296581105431, 0.38940209010553817,
1913    -0.88389309286710249, -0.65162896721296426, 0.46257338110776325], [-0.11939963998961844, -0.12459170323504432,
1914    0.56721445924492242, -0.5434934377046885, -0.94097319686236203, 0.10843818162615082]], [[0.94156569655681088,
1915    0.97937047999438565, 0.58328860247766023, 0.49999512882630359, 0.98498409635330897, -0.77617703005476235],
1916    [-0.79368894718950678, -0.49094875856870313, -0.47268575315274686, -0.48423087666296949, -0.15705360364959353,
1917    -0.092347853598065299], [-0.43773529882492035, -0.97330976684408221, 0.62275243482370546, 0.16243417577414521,
1918    -0.27746950274070858, -0.17634930756002976]]], [[[-0.57257563296277136, 0.051131913300164644, -0.095495549766847265,
1919    -0.19510866832630236, -0.71009423852663178, 0.76085183088330033], [0.060680252469367701, -0.77048545231645305,
1920    0.26366428280734966, -0.69041926752783755, 0.718088216916698, -0.49745431621938097], [0.12318995194046978, 0.86936537085873766,
1921    0.83918180976058321, 0.68380718722273914, 0.93333036673857861, -0.40802153642780503]], [[-0.39080649731083716,
1922    0.89846016192617917, -0.43753436018584635, -0.54164172029960556, 0.26500666447283927, -0.80442084034012318],
1923    [-0.61280888117488774, 0.19901497307242777, -0.38809942782108231, -0.15304848336510446, -0.89682030092543341,
1924    0.81682968047844762], [-0.37083147403347305, -0.5694861159060336, 0.82079574997354832, 0.16313708350728251,
1925    -0.96148263023930025, 0.61619631755008997]], [[-0.60218852847857085, -0.30606863782057858, -0.37854212049919034,
1926    -0.6189813873806298, -0.27466810355256932, 0.11312041334540823], [-0.24450376261524176, -0.3446492538039585,
1927    -0.11428337189518412, 0.86141817541072485, 0.01994360774629178, -0.9869163482668879], [0.83076429114401584,
1928    0.90701559122745246, -0.11515468013785246, -0.35636953652376158, 0.60173165224519298, -0.0041944503459219185]],
1929    [[-0.72486769047997224, 0.11125913628158135, -0.94325817369156395, -0.22227144314457647, 0.73184381474788585,
1930    -0.42269341360248136], [0.3322788694093366, 0.48675876476849655, 0.95199984348648936, 0.77336176266100121,
1931    -0.75298460572165227, -0.64919265433333395], [0.97951110380594075, 0.7606183719435895, -0.92931969801866887,
1932    -0.76656529512374871, -0.96565563744445226, -0.44206017089366356]]], [[[0.06437051353673251, 0.16064165673082509,
1933    0.66075872754206277, -0.024405885296694185, 0.83365693142502217, -0.68157234542080869], [-0.46145077162972359,
1934    0.44283796650491913, -0.25107173989879983, 0.99700063016208107, 0.63626965157409332, 0.67543716935101461],
1935    [-0.19144043467308913, 0.0084624137917301834, -0.011459481336658861, 0.020765982666997251, -0.66394566462368454,
1936    -0.13595799606345849]], [[0.48666927295430273, -0.54018652177965421, -0.60712253356220014, 0.86032968494357509,
1937    0.93646381542687074, 0.62229000542074231], [-0.48204694443669815, -0.043441074127007484, 0.52089066069776302,
1938    -0.14263968353974321, 0.67784661619051523, 0.67683914159762426], [-0.36406246921881258, 0.52484974557021125,
1939    -0.83945534497593077, -0.56626235962196247, -0.92874439106110906, -0.84316505863262137]], [[-0.61694738907429159,
1940    -0.84155413094960885, -0.059449787766562068, 0.75512682823773636, -0.47056126199970127, -0.94014349555090271],
1941    [0.38488296050771642, -0.68470636052993017, 0.9360344045616662, -0.38978549121193184, 0.25843508056533948,
1942    -0.4154997886443399], [0.98397174568093337, -0.17687534177156738, 0.15000998147481748, 0.67926300051950217,
1943    0.70188052710294779, 0.76571096090863833]], [[0.10520283712355649, 0.46358590529577093, -0.23107955221500487,
1944    -0.10221032014082643, -0.40083861723237568, -0.79077105783256307], [-0.45962678686990333, -0.37161803581831654,
1945    0.90407168311308617, -0.63118786505135183, -0.87881942461714035, -0.50043032112907881], [-0.40905017398749832,
1946    -0.78414396535965936, 0.52243010681437196, -0.34857967525022726, -0.79063821885581809, -0.44655427796158786]]],
1947    [[[-0.26830770663674852, 0.052309820978976962, -0.71260517345213703, 0.068649426504235889, -0.79584911074378639,
1948    -0.73341766864885805], [0.73182847261033501, -0.96117438640838193, 0.13525338817090482, -0.45877788351575455,
1949    -0.8514202874979051, -0.80721379845257357], [0.17064064304210924, 0.64156952246470644, 0.8579149441905618, 0.42505886722614017,
1950    -0.84192631535491813, 0.07347356074778566]], [[-0.0508167938616777, 0.79593473366420087, -0.18915387572251285,
1951    -0.78860288867907991, -0.78833850850429199, -0.034960906396380276], [0.63553534416742985, 0.54104290380014675,
1952    0.83137356210702995, 0.21568011240898222, -0.20580699671693359, 0.521832276659004], [0.87116328689755851, 0.92974282626786442,
1953    0.15936378842429577, 0.69133337125801075, 0.7608669199256719, -0.87784165352731791]], [[-0.75122215790102453,
1954    -0.11551204851061558, -0.95370414115103053, -0.59947328175015779, 0.30395159242315106, 0.13066616906441419],
1955    [0.061420488872834911, 0.30147702994470338, 0.27861956239959107, 0.28579025178671458, 0.36624849173491181,
1956    0.72786096607107176], [-0.949934981054112, -0.013206267446552067, -0.22928309991217377, 0.11095083320713495,
1957    -0.69546530710777343, 0.64638482716139301]], [[0.25305577703676563, 0.42897469852970049, -0.84969441201530493,
1958    0.49601628592368896, 0.18913452811455134, -0.42761115621334911], [-0.71085347752670947, -0.2320109793524352,
1959    0.56299071564628056, -0.47484796914866267, -0.11629577973670235, 0.2662526509891876], [-0.60078256931253216,
1960    -0.68333526085038865, 0.22683430437623353, 0.9676042368650819, 0.77154035736113635, -0.11928404003074666]]]])
1961          ref=whereNegative(xx)          ref=whereNegative(xx)
1962          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1963          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1111  class SymbolicTestCase(unittest.TestCase Line 1987  class SymbolicTestCase(unittest.TestCase
1987          x=Symbol('x', shape)          x=Symbol('x', shape)
1988          y=whereNonNegative(x)          y=whereNonNegative(x)
1989          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
1990          xx=numpy.array([[0.16255465443162831, -0.075401548451550893, 0.61998992448153811, 0.98751665287362922, 0.24334557776878274, 0.036731677371431237]])          xx=numpy.array([[0.16255465443162831, -0.075401548451550893, 0.61998992448153811, 0.98751665287362922,
1991    0.24334557776878274, 0.036731677371431237]])
1992          ref=whereNonNegative(xx)          ref=whereNonNegative(xx)
1993          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
1994          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1121  class SymbolicTestCase(unittest.TestCase Line 1998  class SymbolicTestCase(unittest.TestCase
1998          x=Symbol('x', shape)          x=Symbol('x', shape)
1999          y=whereNonNegative(x)          y=whereNonNegative(x)
2000          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2001          xx=numpy.array([[[0.07183553646709262, 0.571643111411134, 0.12210418158332104, -0.47933340822013881, -0.77963131659386908]]])          xx=numpy.array([[[0.07183553646709262, 0.571643111411134, 0.12210418158332104, -0.47933340822013881,
2002    -0.77963131659386908]]])
2003          ref=whereNonNegative(xx)          ref=whereNonNegative(xx)
2004          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2005          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1131  class SymbolicTestCase(unittest.TestCase Line 2009  class SymbolicTestCase(unittest.TestCase
2009          x=Symbol('x', shape)          x=Symbol('x', shape)
2010          y=whereNonNegative(x)          y=whereNonNegative(x)
2011          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2012          xx=numpy.array([[[[0.066993725840136076, -0.27545326516945057]], [[-0.42934072165626236, 0.42229356051693978]], [[-0.33267038317537279, 0.46893642688311576]], [[0.89266708946409734, 0.948473021117479]], [[0.52550545701405671, -0.16055292901173135]], [[0.52759295897665881, -0.54697795638017133]]], [[[3.661909080543424e-05, 0.2314045423354878]], [[-0.87463870704858038, 0.33691234404370474]], [[-0.24384623670510375, 0.76583873747605868]], [[-0.70439457329825306, 0.79652728100315717]], [[0.89550406565185514, 0.056023942007641381]], [[-0.54812946125181439, 0.84663276137296695]]], [[[-0.40853943317595021, 0.57640997505014013]], [[-0.26371556266792195, -0.45625428604054785]], [[-0.74467882611750369, 0.61126061359405348]], [[-0.49001100790246377, 0.29246177028397646]], [[0.29827578910576835, -0.60501268542676612]], [[-0.8927902525418363, 0.20127128252117599]]], [[[0.0906171701040972, -0.41160009957079779]], [[-0.90862039262623417, -0.55145680964277322]], [[-0.98000949136755855, 0.6511419686649127]], [[0.5222457343094018, 0.89406970239489447]], [[-0.39112557307084583, -0.3173281519283313]], [[-0.84876063366959853, 0.86272055297540673]]]])          xx=numpy.array([[[[0.066993725840136076, -0.27545326516945057]], [[-0.42934072165626236, 0.42229356051693978]],
2013    [[-0.33267038317537279, 0.46893642688311576]], [[0.89266708946409734, 0.948473021117479]], [[0.52550545701405671,
2014    -0.16055292901173135]], [[0.52759295897665881, -0.54697795638017133]]], [[[3.661909080543424e-05, 0.2314045423354878]],
2015    [[-0.87463870704858038, 0.33691234404370474]], [[-0.24384623670510375, 0.76583873747605868]], [[-0.70439457329825306,
2016    0.79652728100315717]], [[0.89550406565185514, 0.056023942007641381]], [[-0.54812946125181439, 0.84663276137296695]]],
2017    [[[-0.40853943317595021, 0.57640997505014013]], [[-0.26371556266792195, -0.45625428604054785]], [[-0.74467882611750369,
2018    0.61126061359405348]], [[-0.49001100790246377, 0.29246177028397646]], [[0.29827578910576835, -0.60501268542676612]],
2019    [[-0.8927902525418363, 0.20127128252117599]]], [[[0.0906171701040972, -0.41160009957079779]], [[-0.90862039262623417,
2020    -0.55145680964277322]], [[-0.98000949136755855, 0.6511419686649127]], [[0.5222457343094018, 0.89406970239489447]],
2021    [[-0.39112557307084583, -0.3173281519283313]], [[-0.84876063366959853, 0.86272055297540673]]]])
2022          ref=whereNonNegative(xx)          ref=whereNonNegative(xx)
2023          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2024          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1151  class SymbolicTestCase(unittest.TestCase Line 2038  class SymbolicTestCase(unittest.TestCase
2038          x=Symbol('x', shape)          x=Symbol('x', shape)
2039          y=whereNonPositive(x)          y=whereNonPositive(x)
2040          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2041          xx=numpy.array([-0.90018358136070309, 0.30348641340688465, -0.85618120763971728, -0.53960506171544309, -0.17715605479196417, -0.65288288011449302])          xx=numpy.array([-0.90018358136070309, 0.30348641340688465, -0.85618120763971728, -0.53960506171544309,
2042    -0.17715605479196417, -0.65288288011449302])
2043          ref=whereNonPositive(xx)          ref=whereNonPositive(xx)
2044          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2045          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1161  class SymbolicTestCase(unittest.TestCase Line 2049  class SymbolicTestCase(unittest.TestCase
2049          x=Symbol('x', shape)          x=Symbol('x', shape)
2050          y=whereNonPositive(x)          y=whereNonPositive(x)
2051          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2052          xx=numpy.array([[0.52054333812889153, 0.93244502782155192, 0.23950589542474909, -0.27867700605384416], [0.136236165289082, -0.72973716446443526, 0.78345715642418656, -0.55231976912870806], [0.16068847831312683, 0.69803624461720348, -0.56066314352940427, -0.048324609040210298], [-0.43917432100497389, 0.20836742086495308, -0.47887558228230453, -0.24601140217225681], [-0.36325465701947768, -0.7549630422808371, 0.54364541523192855, 0.71680613627149858], [-0.018200507730612214, -0.70132178626132835, -0.067011377948262618, 0.93498344549668744]])          xx=numpy.array([[0.52054333812889153, 0.93244502782155192, 0.23950589542474909, -0.27867700605384416],
2053    [0.136236165289082, -0.72973716446443526, 0.78345715642418656, -0.55231976912870806], [0.16068847831312683,
2054    0.69803624461720348, -0.56066314352940427, -0.048324609040210298], [-0.43917432100497389, 0.20836742086495308,
2055    -0.47887558228230453, -0.24601140217225681], [-0.36325465701947768, -0.7549630422808371, 0.54364541523192855,
2056    0.71680613627149858], [-0.018200507730612214, -0.70132178626132835, -0.067011377948262618, 0.93498344549668744]])
2057          ref=whereNonPositive(xx)          ref=whereNonPositive(xx)
2058          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2059          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1171  class SymbolicTestCase(unittest.TestCase Line 2063  class SymbolicTestCase(unittest.TestCase
2063          x=Symbol('x', shape)          x=Symbol('x', shape)
2064          y=whereNonPositive(x)          y=whereNonPositive(x)
2065          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2066          xx=numpy.array([[[-0.27817206633072811, -0.081436436743882457, 0.75875807911236803], [-0.50343361180037705, -0.40952155515557176, 0.30633704565770836], [0.09713396455163692, 0.37971816691593219, -0.64528055605836387], [-0.40766608291627149, 0.42126635202766272, -0.36870570089878796], [-0.12999309462561448, -0.013452703166594748, 0.62628550647076664]], [[0.92143294803926001, 0.87265908348850463, 0.72934818835787651], [0.72670061199951252, 0.69405462234812743, -0.5375658770167584], [-0.21848892506997553, -0.1416308903572896, -0.18228425021307304], [0.59161630465569415, -0.59952258150667359, 0.073642971852158068], [0.20827259131225784, -0.16844724692462698, -0.29075535603128211]]])          xx=numpy.array([[[-0.27817206633072811, -0.081436436743882457, 0.75875807911236803], [-0.50343361180037705,
2067    -0.40952155515557176, 0.30633704565770836], [0.09713396455163692, 0.37971816691593219, -0.64528055605836387],
2068    [-0.40766608291627149, 0.42126635202766272, -0.36870570089878796], [-0.12999309462561448, -0.013452703166594748,
2069    0.62628550647076664]], [[0.92143294803926001, 0.87265908348850463, 0.72934818835787651], [0.72670061199951252,
2070    0.69405462234812743, -0.5375658770167584], [-0.21848892506997553, -0.1416308903572896, -0.18228425021307304],
2071    [0.59161630465569415, -0.59952258150667359, 0.073642971852158068], [0.20827259131225784, -0.16844724692462698,
2072    -0.29075535603128211]]])
2073          ref=whereNonPositive(xx)          ref=whereNonPositive(xx)
2074          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2075          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1181  class SymbolicTestCase(unittest.TestCase Line 2079  class SymbolicTestCase(unittest.TestCase
2079          x=Symbol('x', shape)          x=Symbol('x', shape)
2080          y=whereNonPositive(x)          y=whereNonPositive(x)
2081          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2082          xx=numpy.array([[[[0.76421090018782389, 0.22500582739784702, 0.19670981066640381, -0.029815196145000167], [-0.0023715023631671883, -0.25808105968817818, -0.77605684947970355, 0.02245024313203392], [-0.25729342994919935, 0.54374427642860157, 0.98101283270914585, -0.46768270335386197]], [[0.70839406887585588, -0.37921199056531996, -0.027693666176255682, 0.18410753019338655], [0.9844664514717536, -0.68571594713891648, -0.87874566403081622, 0.99836777995287473], [-0.60137381647439248, -0.96185559798925757, 0.26042164790889832, -0.21938871838079232]], [[-0.40465011497491798, -0.60126899021307523, 0.33212611684344351, 0.93945147833669984], [-0.17919578647888335, -0.29192839059809184, -0.16587643761468995, 0.5787318075152601], [0.088931359495969087, -0.49762262591243611, -0.8824559154533953, 0.69337053676631966]], [[-0.44259804575998496, -0.42643461551484818, 0.76308712257434186, 0.52791080632128651], [0.43904901084960435, 0.58786748614643591, -0.89969054547864102, -0.81453674264286136], [-0.20388022961359886, 0.98704014958763309, 0.28779316308141101, 0.45902180644882029]], [[0.21488201234892346, 0.15786087222573109, 0.14117129920118709, 0.89719639382806582], [0.44952238681525203, -0.20300718914847482, 0.37907878593516453, 0.4012439149905449], [-0.053623080473312879, -0.47534453051260162, -0.73601106510348324, -0.1727295413441754]], [[0.65587612271205287, 0.061348381925462325, -0.6563598036663767, 0.22986828041081742], [-0.62435207387666525, -0.39642223631815066, -0.216712697339845, 0.7064737188000676], [0.63493925912402394, -0.97427339204813213, -0.60492536457553392, -0.79397528537512141]]]])          xx=numpy.array([[[[0.76421090018782389, 0.22500582739784702, 0.19670981066640381, -0.029815196145000167],
2083    [-0.0023715023631671883, -0.25808105968817818, -0.77605684947970355, 0.02245024313203392], [-0.25729342994919935,
2084    0.54374427642860157, 0.98101283270914585, -0.46768270335386197]], [[0.70839406887585588, -0.37921199056531996,
2085    -0.027693666176255682, 0.18410753019338655], [0.9844664514717536, -0.68571594713891648, -0.87874566403081622,
2086    0.99836777995287473], [-0.60137381647439248, -0.96185559798925757, 0.26042164790889832, -0.21938871838079232]],
2087    [[-0.40465011497491798, -0.60126899021307523, 0.33212611684344351, 0.93945147833669984], [-0.17919578647888335,
2088    -0.29192839059809184, -0.16587643761468995, 0.5787318075152601], [0.088931359495969087, -0.49762262591243611,
2089    -0.8824559154533953, 0.69337053676631966]], [[-0.44259804575998496, -0.42643461551484818, 0.76308712257434186,
2090    0.52791080632128651], [0.43904901084960435, 0.58786748614643591, -0.89969054547864102, -0.81453674264286136],
2091    [-0.20388022961359886, 0.98704014958763309, 0.28779316308141101, 0.45902180644882029]], [[0.21488201234892346,
2092    0.15786087222573109, 0.14117129920118709, 0.89719639382806582], [0.44952238681525203, -0.20300718914847482,
2093    0.37907878593516453, 0.4012439149905449], [-0.053623080473312879, -0.47534453051260162, -0.73601106510348324,
2094    -0.1727295413441754]], [[0.65587612271205287, 0.061348381925462325, -0.6563598036663767, 0.22986828041081742],
2095    [-0.62435207387666525, -0.39642223631815066, -0.216712697339845, 0.7064737188000676], [0.63493925912402394,
2096    -0.97427339204813213, -0.60492536457553392, -0.79397528537512141]]]])
2097          ref=whereNonPositive(xx)          ref=whereNonPositive(xx)
2098          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2099          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1211  class SymbolicTestCase(unittest.TestCase Line 2123  class SymbolicTestCase(unittest.TestCase
2123          x=Symbol('x', shape)          x=Symbol('x', shape)
2124          y=whereNonZero(x)          y=whereNonZero(x)
2125          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2126          xx=numpy.array([[0.47272239608212874, 0.10051789240176356, 0.26272994868293043, -0.6159223154289033, -0.56667582585484544, -0.89253107859479286], [-0.55924657895182772, 0.93545079547557064, -0.34898656014938312, 0.21953807462211961, 0.25492564264834683, -0.35726796840497133], [-0.40094701225180507, 0.1960349067873679, 0.50731479699854276, -0.78686042102984066, 0.8672231296988846, -0.74804964207566349], [0.95531464602079019, -0.89226901941682035, -0.16304450424456007, -0.76454645659342102, -0.78708434678011052, 0.98801488744620647]])          xx=numpy.array([[0.47272239608212874, 0.10051789240176356, 0.26272994868293043, -0.6159223154289033,
2127    -0.56667582585484544, -0.89253107859479286], [-0.55924657895182772, 0.93545079547557064, -0.34898656014938312,
2128    0.21953807462211961, 0.25492564264834683, -0.35726796840497133], [-0.40094701225180507, 0.1960349067873679,
2129    0.50731479699854276, -0.78686042102984066, 0.8672231296988846, -0.74804964207566349], [0.95531464602079019,
2130    -0.89226901941682035, -0.16304450424456007, -0.76454645659342102, -0.78708434678011052, 0.98801488744620647]])
2131          ref=whereNonZero(xx)          ref=whereNonZero(xx)
2132          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2133          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1221  class SymbolicTestCase(unittest.TestCase Line 2137  class SymbolicTestCase(unittest.TestCase
2137          x=Symbol('x', shape)          x=Symbol('x', shape)
2138          y=whereNonZero(x)          y=whereNonZero(x)
2139          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2140          xx=numpy.array([[[-0.7414892712283081, 0.41363030109393706], [-0.23348792044545874, 0.20376154349293718], [-0.39749859654170105, 0.60619331026813517], [0.19770196299714726, 0.47778531754573339], [-0.2785730022253452, 0.74385409779061096]], [[0.39811958523569135, 0.98827673008103467], [-0.77742925379355432, -0.36327654260828868], [-0.24261210554539181, 0.76381491096289666], [0.71356756598505622, 0.42134472339801898], [-0.32787878885926935, 0.36977573897534355]], [[0.81553089557162184, 0.65142084303833125], [0.26952185474651191, 0.23717538996324716], [-0.4178969152405565, 0.65966116581440826], [0.72266687659103757, 0.23151347657044385], [-0.93144901070650543, 0.5533107522228673]]])          xx=numpy.array([[[-0.7414892712283081, 0.41363030109393706], [-0.23348792044545874, 0.20376154349293718],
2141    [-0.39749859654170105, 0.60619331026813517], [0.19770196299714726, 0.47778531754573339], [-0.2785730022253452,
2142    0.74385409779061096]], [[0.39811958523569135, 0.98827673008103467], [-0.77742925379355432, -0.36327654260828868],
2143    [-0.24261210554539181, 0.76381491096289666], [0.71356756598505622, 0.42134472339801898], [-0.32787878885926935,
2144    0.36977573897534355]], [[0.81553089557162184, 0.65142084303833125], [0.26952185474651191, 0.23717538996324716],
2145    [-0.4178969152405565, 0.65966116581440826], [0.72266687659103757, 0.23151347657044385], [-0.93144901070650543,
2146    0.5533107522228673]]])
2147          ref=whereNonZero(xx)          ref=whereNonZero(xx)
2148          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2149          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1231  class SymbolicTestCase(unittest.TestCase Line 2153  class SymbolicTestCase(unittest.TestCase
2153          x=Symbol('x', shape)          x=Symbol('x', shape)
2154          y=whereNonZero(x)          y=whereNonZero(x)
2155          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2156          xx=numpy.array([[[[0.90238883836103856, -0.078141430869900885], [0.96964248790199536, 0.86899132288638437], [-0.68707659301961588, -0.53073339851774448], [0.32688170956882767, -0.96921857548468071], [0.18196874278375952, 0.57135339374463401]], [[0.25930891270158085, -0.315440727828324], [0.037520854381012825, 0.53261366081014083], [-0.15489495244200047, -0.84806312372317638], [0.092612945156565596, -0.25692276023115479], [0.17533235647978307, 0.89313440080952344]], [[-0.64717308780928406, -0.75805104889803432], [-0.041739580260959475, -0.6205789153566017], [-0.25842404105910255, 0.23701518807315436], [0.31089303563347515, -0.51399810672806678], [-0.023306677944956888, 0.81352506797068447]], [[0.76578954037946101, -0.30328270768759968], [-0.094894717069517798, 0.84307215381835277], [0.20655482690635352, -0.68118968257486001], [-0.031341709663070594, 0.7128253675049403], [0.61449090253099015, -0.41198959986501915]], [[0.40509351567157026, -0.69086923203639139], [0.43516889791102709, -0.3416724751663851], [-0.97964128140528683, -0.22791528480958068], [0.98482909258012752, -0.031469684482034577], [-0.2739148315804234, 0.093180455447071431]], [[-0.7719005715950038, 0.43813213374298354], [-0.51396005960844726, 0.47137453974714116], [-0.46097779903586078, -0.063960915243740812], [0.26352848643891602, -0.48662867823453326], [0.66105464029555128, -0.87140048147775584]]], [[[-0.94916583974794411, -0.98499608201877042], [0.05418684797282558, 0.037422050745511637], [0.83557151410760477, 0.17226939821781873], [-0.58926990995905659, -0.97834331011266551], [0.30666874303114255, -0.2205888292045417]], [[0.33897197902963261, 0.71029540183574058], [0.087210612460627557, 0.8644231149968451], [0.38136782120964852, 0.78052625701905143], [0.8317510524713001, -0.014682435119764303], [0.75669358591385327, 0.22159820191463875]], [[0.47631111031225082, -0.2432820015617243], [-0.056353663947721788, 0.94396356593922226], [0.093599462496724462, 0.98409700596138738], [0.51684918605680874, -0.20311323832637695], [0.031403436997070155, 0.30752607757491823]], [[-0.66062234522460495, 0.98244061952736805], [0.71323974544343227, -0.99294274205841693], [0.085382602021304876, 0.34928281809030182], [0.95574038217827284, -0.63922033438378123], [-0.1510988417007515, -0.18232263718951058]], [[-0.86857459107290524, 0.27065376653408668], [0.34778882991636229, -0.69468078501349817], [-0.05621391859787872, -0.43113805766482893], [-0.21117099401216355, 0.47907566520267908], [0.99631903581124215, 0.60545973609585002]], [[0.089327664796902129, -0.42328912150739639], [0.028808105423793418, -0.067461200204752769], [-0.86739525852770538, 0.60974321136693921], [0.78007851991957211, 0.52984603439955991], [0.82381822897434076, -0.096806791764524114]]], [[[-0.64847860728835283, -0.012817456365514346], [0.99972603703845064, -0.1654871349583027], [-0.48707077346066852, 0.38641150018763981], [-0.34858104546955748, -0.29831215451161652], [0.0013535663519075314, 0.97429208816815671]], [[-0.66436036915097763, 0.7797349360947321], [-0.057540181599951445, 0.96084247891800678], [0.16745893815999846, -0.79480870410089799], [0.75887588500278524, 0.50015393183957935], [0.2201538536602945, -0.91465858939733891]], [[0.46221695878101121, -0.85543254542049985], [-0.79511261729439076, -0.78783008964239776], [-0.82020806490717169, -0.41979080265752078], [0.16681258015526867, -0.24042603202357271], [0.13735109423318947, 0.74666019064984002]], [[-0.089558492701826919, 0.085142350465663208], [0.58353640055793665, -0.56820577095080083], [-0.93851521767397306, 0.12873063390745187], [-0.55662024343650884, 0.47890143961389775], [-0.77804687365059011, -0.28618046680866893]], [[-0.11520321604725736, -0.47181694802762109], [0.53172168116819973, 0.049579400427356424], [0.49159269264521122, 0.13546216707799741], [-0.11678849129062785, -0.76408076913005374], [-0.4191053917656975, 0.48543625969583348]], [[-0.99253540206564139, 0.62751540233591219], [0.92479658199101622, -0.50793356938360823], [-0.66602828599508412, 0.64847360599262305], [0.1256913139099114, -0.070639983370629045], [0.52157580012214688, 0.097535376596756374]]], [[[-0.57264487061083935, -0.52288880591820197], [-0.025742670244710775, -0.9170247460533445], [-0.48679517977387832, 0.64730955653708522], [-0.71406706864020308, 0.11107789589413164], [-0.34729260237235438, 0.27372244225734632]], [[0.34789886396352321, 0.3054893282236173], [-0.43858235630977571, -0.93001449046583118], [-0.22582623588475315, -0.025163803596387035], [0.17634778066393886, -0.98755299203544178], [0.73172600806325594, 0.59069588394537109]], [[-0.029584834339910104, -0.77713653122341264], [-0.7295543139272771, -0.99458301783387015], [-0.2150254830760292, -0.024387346615555527], [0.41364448121677078, 0.99185633963935982], [-0.17526406176681331, 0.69496091879238597]], [[0.17731947095940614, 0.94603342650519973], [-0.77387354449747758, 0.29832428430509217], [0.94536466081511739, -0.32578078437216829], [0.32124342502797631, -0.38798755655698414], [0.90133877643029958, 0.044111442161604897]], [[-0.14130265836940303, 0.81573218035119055], [-0.52307465861006031, 0.56184286344010603], [0.33004086040356784, -0.039891232212105443], [-0.85072814696072729, -0.53465904480572002], [-0.18414968349884031, -0.85314057271375754]], [[-0.27062891991592997, 0.81372863018676567], [0.4799755270102728, -0.4476182527576904], [0.69041788912015711, 0.36404717548231247], [0.94513419717329872, -0.71989397993530257], [-0.26780541921419498, -0.68483698187810105]]]])          xx=numpy.array([[[[0.90238883836103856, -0.078141430869900885], [0.96964248790199536, 0.86899132288638437],
2157    [-0.68707659301961588, -0.53073339851774448], [0.32688170956882767, -0.96921857548468071], [0.18196874278375952,
2158    0.57135339374463401]], [[0.25930891270158085, -0.315440727828324], [0.037520854381012825, 0.53261366081014083],
2159    [-0.15489495244200047, -0.84806312372317638], [0.092612945156565596, -0.25692276023115479], [0.17533235647978307,
2160    0.89313440080952344]], [[-0.64717308780928406, -0.75805104889803432], [-0.041739580260959475, -0.6205789153566017],
2161    [-0.25842404105910255, 0.23701518807315436], [0.31089303563347515, -0.51399810672806678], [-0.023306677944956888,
2162    0.81352506797068447]], [[0.76578954037946101, -0.30328270768759968], [-0.094894717069517798, 0.84307215381835277],
2163    [0.20655482690635352, -0.68118968257486001], [-0.031341709663070594, 0.7128253675049403], [0.61449090253099015,
2164    -0.41198959986501915]], [[0.40509351567157026, -0.69086923203639139], [0.43516889791102709, -0.3416724751663851],
2165    [-0.97964128140528683, -0.22791528480958068], [0.98482909258012752, -0.031469684482034577], [-0.2739148315804234,
2166    0.093180455447071431]], [[-0.7719005715950038, 0.43813213374298354], [-0.51396005960844726, 0.47137453974714116],
2167    [-0.46097779903586078, -0.063960915243740812], [0.26352848643891602, -0.48662867823453326], [0.66105464029555128,
2168    -0.87140048147775584]]], [[[-0.94916583974794411, -0.98499608201877042], [0.05418684797282558, 0.037422050745511637],
2169    [0.83557151410760477, 0.17226939821781873], [-0.58926990995905659, -0.97834331011266551], [0.30666874303114255,
2170    -0.2205888292045417]], [[0.33897197902963261, 0.71029540183574058], [0.087210612460627557, 0.8644231149968451],
2171    [0.38136782120964852, 0.78052625701905143], [0.8317510524713001, -0.014682435119764303], [0.75669358591385327,
2172    0.22159820191463875]], [[0.47631111031225082, -0.2432820015617243], [-0.056353663947721788, 0.94396356593922226],
2173    [0.093599462496724462, 0.98409700596138738], [0.51684918605680874, -0.20311323832637695], [0.031403436997070155,
2174    0.30752607757491823]], [[-0.66062234522460495, 0.98244061952736805], [0.71323974544343227, -0.99294274205841693],
2175    [0.085382602021304876, 0.34928281809030182], [0.95574038217827284, -0.63922033438378123], [-0.1510988417007515,
2176    -0.18232263718951058]], [[-0.86857459107290524, 0.27065376653408668], [0.34778882991636229, -0.69468078501349817],
2177    [-0.05621391859787872, -0.43113805766482893], [-0.21117099401216355, 0.47907566520267908], [0.99631903581124215,
2178    0.60545973609585002]], [[0.089327664796902129, -0.42328912150739639], [0.028808105423793418, -0.067461200204752769],
2179    [-0.86739525852770538, 0.60974321136693921], [0.78007851991957211, 0.52984603439955991], [0.82381822897434076,
2180    -0.096806791764524114]]], [[[-0.64847860728835283, -0.012817456365514346], [0.99972603703845064, -0.1654871349583027],
2181    [-0.48707077346066852, 0.38641150018763981], [-0.34858104546955748, -0.29831215451161652], [0.0013535663519075314,
2182    0.97429208816815671]], [[-0.66436036915097763, 0.7797349360947321], [-0.057540181599951445, 0.96084247891800678],
2183    [0.16745893815999846, -0.79480870410089799], [0.75887588500278524, 0.50015393183957935], [0.2201538536602945,
2184    -0.91465858939733891]], [[0.46221695878101121, -0.85543254542049985], [-0.79511261729439076, -0.78783008964239776],
2185    [-0.82020806490717169, -0.41979080265752078], [0.16681258015526867, -0.24042603202357271], [0.13735109423318947,
2186    0.74666019064984002]], [[-0.089558492701826919, 0.085142350465663208], [0.58353640055793665, -0.56820577095080083],
2187    [-0.93851521767397306, 0.12873063390745187], [-0.55662024343650884, 0.47890143961389775], [-0.77804687365059011,
2188    -0.28618046680866893]], [[-0.11520321604725736, -0.47181694802762109], [0.53172168116819973, 0.049579400427356424],
2189    [0.49159269264521122, 0.13546216707799741], [-0.11678849129062785, -0.76408076913005374], [-0.4191053917656975,
2190    0.48543625969583348]], [[-0.99253540206564139, 0.62751540233591219], [0.92479658199101622, -0.50793356938360823],
2191    [-0.66602828599508412, 0.64847360599262305], [0.1256913139099114, -0.070639983370629045], [0.52157580012214688,
2192    0.097535376596756374]]], [[[-0.57264487061083935, -0.52288880591820197], [-0.025742670244710775, -0.9170247460533445],
2193    [-0.48679517977387832, 0.64730955653708522], [-0.71406706864020308, 0.11107789589413164], [-0.34729260237235438,
2194    0.27372244225734632]], [[0.34789886396352321, 0.3054893282236173], [-0.43858235630977571, -0.93001449046583118],
2195    [-0.22582623588475315, -0.025163803596387035], [0.17634778066393886, -0.98755299203544178], [0.73172600806325594,
2196    0.59069588394537109]], [[-0.029584834339910104, -0.77713653122341264], [-0.7295543139272771, -0.99458301783387015],
2197    [-0.2150254830760292, -0.024387346615555527], [0.41364448121677078, 0.99185633963935982], [-0.17526406176681331,
2198    0.69496091879238597]], [[0.17731947095940614, 0.94603342650519973], [-0.77387354449747758, 0.29832428430509217],
2199    [0.94536466081511739, -0.32578078437216829], [0.32124342502797631, -0.38798755655698414], [0.90133877643029958,
2200    0.044111442161604897]], [[-0.14130265836940303, 0.81573218035119055], [-0.52307465861006031, 0.56184286344010603],
2201    [0.33004086040356784, -0.039891232212105443], [-0.85072814696072729, -0.53465904480572002], [-0.18414968349884031,
2202    -0.85314057271375754]], [[-0.27062891991592997, 0.81372863018676567], [0.4799755270102728, -0.4476182527576904],
2203    [0.69041788912015711, 0.36404717548231247], [0.94513419717329872, -0.71989397993530257], [-0.26780541921419498,
2204    -0.68483698187810105]]]])
2205          ref=whereNonZero(xx)          ref=whereNonZero(xx)
2206          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2207          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1251  class SymbolicTestCase(unittest.TestCase Line 2221  class SymbolicTestCase(unittest.TestCase
2221          x=Symbol('x', shape)          x=Symbol('x', shape)
2222          y=wherePositive(x)          y=wherePositive(x)
2223          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2224          xx=numpy.array([0.31183363348694781, -0.93037534848467796, 0.36068356078961328, -0.46454210720927702, 0.25340754345513461])          xx=numpy.array([0.31183363348694781, -0.93037534848467796, 0.36068356078961328, -0.46454210720927702,
2225    0.25340754345513461])
2226          ref=wherePositive(xx)          ref=wherePositive(xx)
2227          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2228          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1261  class SymbolicTestCase(unittest.TestCase Line 2232  class SymbolicTestCase(unittest.TestCase
2232          x=Symbol('x', shape)          x=Symbol('x', shape)
2233          y=wherePositive(x)          y=wherePositive(x)
2234          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2235          xx=numpy.array([[0.13591127534951108, -0.12739880165333806, 0.14507359534802755], [0.59535385598268742, 0.33953584270588988, -0.19906200104176852], [0.18362571608830569, -0.79899653225101086, 0.37942105104987678], [-0.47201581043531471, -0.77541914147114688, 0.96465645411216316]])          xx=numpy.array([[0.13591127534951108, -0.12739880165333806, 0.14507359534802755], [0.59535385598268742,
2236    0.33953584270588988, -0.19906200104176852], [0.18362571608830569, -0.79899653225101086, 0.37942105104987678],
2237    [-0.47201581043531471, -0.77541914147114688, 0.96465645411216316]])
2238          ref=wherePositive(xx)          ref=wherePositive(xx)
2239          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2240          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1271  class SymbolicTestCase(unittest.TestCase Line 2244  class SymbolicTestCase(unittest.TestCase
2244          x=Symbol('x', shape)          x=Symbol('x', shape)
2245          y=wherePositive(x)          y=wherePositive(x)
2246          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2247          xx=numpy.array([[[0.40969347572725723], [0.72580022565361202]], [[-0.26443539125114923], [-0.91530007460262364]], [[0.14573116670359365], [-0.28164407682569004]], [[-0.46679193029472099], [-0.57181051152013929]]])          xx=numpy.array([[[0.40969347572725723], [0.72580022565361202]], [[-0.26443539125114923], [-0.91530007460262364]],
2248    [[0.14573116670359365], [-0.28164407682569004]], [[-0.46679193029472099], [-0.57181051152013929]]])
2249          ref=wherePositive(xx)          ref=wherePositive(xx)
2250          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2251          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1281  class SymbolicTestCase(unittest.TestCase Line 2255  class SymbolicTestCase(unittest.TestCase
2255          x=Symbol('x', shape)          x=Symbol('x', shape)
2256          y=wherePositive(x)          y=wherePositive(x)
2257          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2258          xx=numpy.array([[[[-0.54939235178738421, 0.45983766515917179, -0.6768799220754369, -0.31120246648743488, 0.13119139528703361, 0.93576894990156778], [0.75331042184998975, 0.86866146502192887, 0.94776229316272675, 0.96712428160924713, 0.62154805391266121, 0.68121672514452269], [-0.43417781860910809, 0.65552746664802375, 0.71063461804308181, 0.98778791451902781, -0.48232886555150478, -0.42649944923789374], [0.31062822963226555, -0.30711614218979921, 0.38303258582904376, -0.59276849280094313, -0.3648303465358953, 0.70202576069688627], [-0.62819924058846577, -0.37419798273224547, -0.27130053284023625, 0.9072224174154484, -0.23462453856372756, 0.89263095914991464], [0.95858819953941832, -0.070679013453496919, -0.19253023047449003, -0.53174292805497925, 0.56862431614704834, 0.25371483994251687]], [[0.95871997420741484, 0.01728114303581707, -0.53156136312545055, -0.98155837218866471, -0.10670820122709679, 0.26495340950333346], [-0.22967727261849369, 0.4375650694850719, -0.0042250610877931916, -0.5421661597598515, -0.84860859311034709, 0.59444229974550478], [0.97540045404987885, 0.65678666686341391, -0.035364867222089647, -0.3522032557572381, 0.61915266241839007, 0.94883330926640097], [0.84278744960115071, -0.55705943130933733, 0.32014782490667293, -0.32586020208420519, -0.78332186691390748, -0.76260991085881802], [-0.29737017596223536, -0.31086711994128269, -0.97532896318861551, -0.094277060177684113, 0.22788292175498737, 0.7891252898086718], [0.97106594995803519, -0.93962773023973756, 0.52294109109502873, 0.86086141945254657, 0.34533706171782752, -0.052510031380444078]]], [[[0.67088753599260298, 0.60809788477592441, -0.77868218557713131, 0.50903109698323856, 0.29858367870053315, -0.59306223460141338], [-0.47260467286240315, -0.39697435587335805, -0.89083357067986224, -0.10260983752890573, 0.56629157310250111, -0.023725279045225811], [-0.55232860144942308, 0.15188533926301861, 0.64907089070588975, -0.90588370288039721, 0.36514909616019686, -0.55073669616405829], [-0.92748683215923933, -0.32679326500380479, 0.24029000646839771, -0.94828824884128604, 0.51573172499226461, 0.33426328315607057], [-0.33160559056410177, 0.1381088469968208, 0.81829873108118534, 0.19608670410260665, 0.43676662620148976, -0.49395935494495902], [-0.89744665081428976, -0.72520257870888472, -0.25699988567772225, 0.1452157451602043, 0.85825985207490185, -0.17571346384249575]], [[0.20556011229018423, -0.4406987701618672, -0.35679132088310639, 0.45463147548831095, 0.58981698516923786, 0.17201232788965282], [-0.060579641690733155, -0.39603147303547059, -0.58120873083145685, 0.14328246231837394, 0.07241743712817561, -0.98959634528852281], [-0.38295089355659506, 0.061816079373679722, 0.26721144541178243, -0.11927829364986708, -0.051279697343907804, -0.47804261526385483], [-0.025809521544123193, -0.84617220153247308, 0.11499038006493412, 0.34486144600936797, 0.99238056859336488, 0.287112601037254], [0.76038815575866914, 0.21802590045316728, 0.72634242544958671, -0.47094029961256623, -0.24638423765838557, -0.82286490046142857], [0.37163982157702424, 0.37654232010832778, 0.34791476598157045, 0.82143544452640405, 0.59277828841993485, -0.45118263524964508]]], [[[0.29521007595604143, -0.63179603594099976, 0.077261193518442628, 0.66774304786667282, -0.52226601400274797, -0.89958005256034101], [-0.54816558685324268, -0.64457692936298461, 0.6236779652746034, -0.49567014905254259, -0.71656765859202665, -0.51340090886531975], [0.81122918603327743, 0.67477141780547023, 0.98673641636939036, 0.9771761206805365, 0.0069183417410505488, -0.59540714802187855], [0.68867105619772562, -0.43177753685648002, 0.20120432038778735, -0.54767093106879772, -0.39249228174625972, 0.057934672256320985], [-0.92217033048550312, -0.99762539640674675, 0.09083701809526401, -0.39936954891299159, -0.66466083743049476, -0.40207381070198411], [0.78877940780013556, -0.17183676675590709, 0.0093884540845652342, -0.43212358869427314, 0.76020883863712441, -0.46419855612306904]], [[0.40986152639742146, 0.20858406387860251, 0.2223442693147093, -0.56678886373069481, 0.98618299637569695, 0.61763886209190932], [-0.22639122498865993, 0.58118970991825791, -0.72547211951949686, 0.45228512524564946, 0.027889137077418136, 0.69723536325392699], [-0.63555290638233486, 0.87674986607485139, 0.80071488208678843, -0.69167780346176122, -0.79748774927404065, 0.67552090311939672], [-0.23605617449770877, -0.24565927714151137, 0.41763899785877645, 0.49433701430402288, -0.35742877299856746, -0.84022180228469989], [0.85524675881098045, -0.73395332594232321, -0.69374858487743141, 0.81140367658791446, -0.11215059436514774, -0.075936402122574354], [-0.28730947176915089, -0.90792495056576339, -0.53400548361351863, -0.74285157211058417, 0.48154969096498523, 0.063966517560076097]]]])          xx=numpy.array([[[[-0.54939235178738421, 0.45983766515917179, -0.6768799220754369, -0.31120246648743488,
2259    0.13119139528703361, 0.93576894990156778], [0.75331042184998975, 0.86866146502192887, 0.94776229316272675, 0.96712428160924713,
2260    0.62154805391266121, 0.68121672514452269], [-0.43417781860910809, 0.65552746664802375, 0.71063461804308181,
2261    0.98778791451902781, -0.48232886555150478, -0.42649944923789374], [0.31062822963226555, -0.30711614218979921,
2262    0.38303258582904376, -0.59276849280094313, -0.3648303465358953, 0.70202576069688627], [-0.62819924058846577,
2263    -0.37419798273224547, -0.27130053284023625, 0.9072224174154484, -0.23462453856372756, 0.89263095914991464],
2264    [0.95858819953941832, -0.070679013453496919, -0.19253023047449003, -0.53174292805497925, 0.56862431614704834,
2265    0.25371483994251687]], [[0.95871997420741484, 0.01728114303581707, -0.53156136312545055, -0.98155837218866471,
2266    -0.10670820122709679, 0.26495340950333346], [-0.22967727261849369, 0.4375650694850719, -0.0042250610877931916,
2267    -0.5421661597598515, -0.84860859311034709, 0.59444229974550478], [0.97540045404987885, 0.65678666686341391,
2268    -0.035364867222089647, -0.3522032557572381, 0.61915266241839007, 0.94883330926640097], [0.84278744960115071,
2269    -0.55705943130933733, 0.32014782490667293, -0.32586020208420519, -0.78332186691390748, -0.76260991085881802],
2270    [-0.29737017596223536, -0.31086711994128269, -0.97532896318861551, -0.094277060177684113, 0.22788292175498737,
2271    0.7891252898086718], [0.97106594995803519, -0.93962773023973756, 0.52294109109502873, 0.86086141945254657, 0.34533706171782752,
2272    -0.052510031380444078]]], [[[0.67088753599260298, 0.60809788477592441, -0.77868218557713131, 0.50903109698323856,
2273    0.29858367870053315, -0.59306223460141338], [-0.47260467286240315, -0.39697435587335805, -0.89083357067986224,
2274    -0.10260983752890573, 0.56629157310250111, -0.023725279045225811], [-0.55232860144942308, 0.15188533926301861,
2275    0.64907089070588975, -0.90588370288039721, 0.36514909616019686, -0.55073669616405829], [-0.92748683215923933,
2276    -0.32679326500380479, 0.24029000646839771, -0.94828824884128604, 0.51573172499226461, 0.33426328315607057],
2277    [-0.33160559056410177, 0.1381088469968208, 0.81829873108118534, 0.19608670410260665, 0.43676662620148976,
2278    -0.49395935494495902], [-0.89744665081428976, -0.72520257870888472, -0.25699988567772225, 0.1452157451602043,
2279    0.85825985207490185, -0.17571346384249575]], [[0.20556011229018423, -0.4406987701618672, -0.35679132088310639,
2280    0.45463147548831095, 0.58981698516923786, 0.17201232788965282], [-0.060579641690733155, -0.39603147303547059,
2281    -0.58120873083145685, 0.14328246231837394, 0.07241743712817561, -0.98959634528852281], [-0.38295089355659506,
2282    0.061816079373679722, 0.26721144541178243, -0.11927829364986708, -0.051279697343907804, -0.47804261526385483],
2283    [-0.025809521544123193, -0.84617220153247308, 0.11499038006493412, 0.34486144600936797, 0.99238056859336488,
2284    0.287112601037254], [0.76038815575866914, 0.21802590045316728, 0.72634242544958671, -0.47094029961256623, -0.24638423765838557,
2285    -0.82286490046142857], [0.37163982157702424, 0.37654232010832778, 0.34791476598157045, 0.82143544452640405,
2286    0.59277828841993485, -0.45118263524964508]]], [[[0.29521007595604143, -0.63179603594099976, 0.077261193518442628,
2287    0.66774304786667282, -0.52226601400274797, -0.89958005256034101], [-0.54816558685324268, -0.64457692936298461,
2288    0.6236779652746034, -0.49567014905254259, -0.71656765859202665, -0.51340090886531975], [0.81122918603327743,
2289    0.67477141780547023, 0.98673641636939036, 0.9771761206805365, 0.0069183417410505488, -0.59540714802187855],
2290    [0.68867105619772562, -0.43177753685648002, 0.20120432038778735, -0.54767093106879772, -0.39249228174625972,
2291    0.057934672256320985], [-0.92217033048550312, -0.99762539640674675, 0.09083701809526401, -0.39936954891299159,
2292    -0.66466083743049476, -0.40207381070198411], [0.78877940780013556, -0.17183676675590709, 0.0093884540845652342,
2293    -0.43212358869427314, 0.76020883863712441, -0.46419855612306904]], [[0.40986152639742146, 0.20858406387860251,
2294    0.2223442693147093, -0.56678886373069481, 0.98618299637569695, 0.61763886209190932], [-0.22639122498865993,
2295    0.58118970991825791, -0.72547211951949686, 0.45228512524564946, 0.027889137077418136, 0.69723536325392699],
2296    [-0.63555290638233486, 0.87674986607485139, 0.80071488208678843, -0.69167780346176122, -0.79748774927404065,
2297    0.67552090311939672], [-0.23605617449770877, -0.24565927714151137, 0.41763899785877645, 0.49433701430402288,
2298    -0.35742877299856746, -0.84022180228469989], [0.85524675881098045, -0.73395332594232321, -0.69374858487743141,
2299    0.81140367658791446, -0.11215059436514774, -0.075936402122574354], [-0.28730947176915089, -0.90792495056576339,
2300    -0.53400548361351863, -0.74285157211058417, 0.48154969096498523, 0.063966517560076097]]]])
2301          ref=wherePositive(xx)          ref=wherePositive(xx)
2302          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2303          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1311  class SymbolicTestCase(unittest.TestCase Line 2327  class SymbolicTestCase(unittest.TestCase
2327          x=Symbol('x', shape)          x=Symbol('x', shape)
2328          y=whereZero(x)          y=whereZero(x)
2329          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2330          xx=numpy.array([[0.10622499961348031, -0.19082329294362066], [0.87822205186483915, -0.227570581816261], [0.66017937209601008, 0.43072185463506951], [-0.74991448789446014, -0.3100002758198217], [-0.51712579145451465, -0.70750035422006019]])          xx=numpy.array([[0.10622499961348031, -0.19082329294362066], [0.87822205186483915, -0.227570581816261],
2331    [0.66017937209601008, 0.43072185463506951], [-0.74991448789446014, -0.3100002758198217], [-0.51712579145451465,
2332    -0.70750035422006019]])
2333          ref=whereZero(xx)          ref=whereZero(xx)
2334          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2335          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1321  class SymbolicTestCase(unittest.TestCase Line 2339  class SymbolicTestCase(unittest.TestCase
2339          x=Symbol('x', shape)          x=Symbol('x', shape)
2340          y=whereZero(x)          y=whereZero(x)
2341          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2342          xx=numpy.array([[[-0.89987449420628129, 0.44176718894605771, 0.84278036910056686, 0.62192038982245967, 0.37469813386654316], [0.44263670237461361, 0.47974259554063403, 0.21880355302135523, -0.99678239055867879, 0.64599329362555924], [0.71665124130686442, 0.71606435130574031, -0.75650804974459507, 0.82859451747546475, -0.034729697394938919], [0.81957258409569311, 0.13604363619082505, -0.22386709023448881, -0.70124352476305707, 0.29007292902149584], [0.017253258203504762, -0.97219754130253877, 0.11953387372384583, 0.0012251948724546491, -0.8433888133511056]], [[-0.29573415646179679, -0.16112108649231671, -0.65405436533907779, -0.76504430864747164, 0.065591620731848765], [0.1230529204234696, 0.45750665883044639, -0.24863429421650451, 0.90805100101538661, 0.43106369312103832], [-0.45255394102027768, -0.7708342898403413, 0.3569365489231302, 0.48515730469223373, -0.26660148832145936], [-0.15668590902657975, -0.30190701092645433, -0.1645703502153022, -0.81266608219504799, -0.49516234113184021], [-0.17495143651323897, 0.57202504858300274, 0.97362734085889935, 0.47097997558209292, -0.25753904085924262]], [[0.079668528057362131, 0.070373802041083566, 0.38037582302327744, 0.66277699527962497, -0.69081416648919203], [-0.19772575123040892, -0.084538607629316198, -0.92242025609493661, 0.68098269876058781, -0.89180009281883343], [0.077789712032067193, -0.60641025717530339, -0.028683412891698623, 0.22193601451721934, 0.6513529374238638], [-0.22633428720737436, 0.85835116682624801, -0.19667612000958967, 0.34666016205682371, 0.48687613932426577], [-0.73350490519888023, -0.76996015076308533, 0.20401724886134454, 0.97783986487668551, -0.097781308653667409]], [[-0.65651283187735432, -0.48754905420466255, -0.79475108913985437, -0.73064515993996038, 0.46590720575206057], [-0.77492382103531865, 0.23868136345558622, 0.54530663160147674, -0.1735577582824015, 0.25728144167719824], [0.60969501001983506, -0.02889586029527913, -0.1210183483182683, 0.14001630349981831, -0.36024256211146599], [0.8963576166338787, 0.56742574160442771, 0.96618862908484893, -0.45856528487907955, 0.47724790543271212], [0.14235966019163016, 0.53124462653844851, 0.65221925434946604, -0.61131393378219001, -0.97528452689210066]]])          xx=numpy.array([[[-0.89987449420628129, 0.44176718894605771, 0.84278036910056686, 0.62192038982245967,
2343    0.37469813386654316], [0.44263670237461361, 0.47974259554063403, 0.21880355302135523, -0.99678239055867879,
2344    0.64599329362555924], [0.71665124130686442, 0.71606435130574031, -0.75650804974459507, 0.82859451747546475,
2345    -0.034729697394938919], [0.81957258409569311, 0.13604363619082505, -0.22386709023448881, -0.70124352476305707,
2346    0.29007292902149584], [0.017253258203504762, -0.97219754130253877, 0.11953387372384583, 0.0012251948724546491,
2347    -0.8433888133511056]], [[-0.29573415646179679, -0.16112108649231671, -0.65405436533907779, -0.76504430864747164,
2348    0.065591620731848765], [0.1230529204234696, 0.45750665883044639, -0.24863429421650451, 0.90805100101538661,
2349    0.43106369312103832], [-0.45255394102027768, -0.7708342898403413, 0.3569365489231302, 0.48515730469223373,
2350    -0.26660148832145936], [-0.15668590902657975, -0.30190701092645433, -0.1645703502153022, -0.81266608219504799,
2351    -0.49516234113184021], [-0.17495143651323897, 0.57202504858300274, 0.97362734085889935, 0.47097997558209292,
2352    -0.25753904085924262]], [[0.079668528057362131, 0.070373802041083566, 0.38037582302327744, 0.66277699527962497,
2353    -0.69081416648919203], [-0.19772575123040892, -0.084538607629316198, -0.92242025609493661, 0.68098269876058781,
2354    -0.89180009281883343], [0.077789712032067193, -0.60641025717530339, -0.028683412891698623, 0.22193601451721934,
2355    0.6513529374238638], [-0.22633428720737436, 0.85835116682624801, -0.19667612000958967, 0.34666016205682371,
2356    0.48687613932426577], [-0.73350490519888023, -0.76996015076308533, 0.20401724886134454, 0.97783986487668551,
2357    -0.097781308653667409]], [[-0.65651283187735432, -0.48754905420466255, -0.79475108913985437, -0.73064515993996038,
2358    0.46590720575206057], [-0.77492382103531865, 0.23868136345558622, 0.54530663160147674, -0.1735577582824015,
2359    0.25728144167719824], [0.60969501001983506, -0.02889586029527913, -0.1210183483182683, 0.14001630349981831,
2360    -0.36024256211146599], [0.8963576166338787, 0.56742574160442771, 0.96618862908484893, -0.45856528487907955,
2361    0.47724790543271212], [0.14235966019163016, 0.53124462653844851, 0.65221925434946604, -0.61131393378219001,
2362    -0.97528452689210066]]])
2363          ref=whereZero(xx)          ref=whereZero(xx)
2364          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2365          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1331  class SymbolicTestCase(unittest.TestCase Line 2369  class SymbolicTestCase(unittest.TestCase
2369          x=Symbol('x', shape)          x=Symbol('x', shape)
2370          y=whereZero(x)          y=whereZero(x)
2371          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2372          xx=numpy.array([[[[0.87917924924094204, 0.92576082229381873, 0.31182535354339991, -0.86214749809692592, -0.27507709543943437], [-0.0016382939288797083, 0.43307986157908585, 0.52636371100155199, -0.043319908450309308, 0.20091228183885401], [0.71583896980535289, 0.50199360637469881, -0.67746890499802959, 0.73499870395620159, 0.63277338423504914], [-0.59257453161192131, 0.66091287836835622, -0.19325788610358763, 0.57712882367912877, -0.7563530936539633]], [[-0.48965026554891877, -0.32764373599077956, -0.5131590362892775, 0.85592981071649832, 0.99561636195898173], [0.24222780295446933, 0.28730806112554474, -0.32041176685276618, 0.78323831462368121, -0.72040929168456769], [0.95423747440270379, 0.39687818036239664, -0.77878094662206365, 0.75880557194836884, -0.1218416672560394], [-0.53785770919122489, 0.67105013676368763, 0.42864708225385661, -0.78784834304583429, -0.2681253344477097]], [[0.46875429958618664, 0.38741628037005071, -0.081056386101901357, -0.23469920628069518, -0.40907581999438447], [0.065494837299773234, 0.38170940261789488, -0.79236472117163403, -0.45228389456840379, 0.55163355897584609], [-0.22355146021048489, -0.93756490876746912, 0.9241257141019481, 0.60698441154913452, -0.21265210744597973], [0.21034749440796197, 0.1659692307697147, 0.78720887852180499, 0.71946077138975917, -0.85985855270766165]], [[0.34986386801299396, 0.35619084924105593, -0.1952077124592666, -0.22518203420372651, -0.59920836063901772], [-0.58104191295806817, 0.29689367250987697, -0.10221810014905208, 0.096526465218390367, 0.055496030226582782], [0.12128925311183991, -0.36085110995947267, -0.69818945730712589, -0.54447063194246215, 0.28238768912002654], [0.5685290343654088, 0.90491556875163925, -0.83800696608599567, -0.11641347846076111, 0.44596200041220047]], [[-0.59532265019171771, -0.27066391467944517, -0.89311609332930963, -0.99850338961193308, 0.15639571601440827], [0.41583353392337186, 0.030126889068769591, -0.18653046086180169, 0.71825314848840516, -0.59319353551728171], [0.35800182346025844, -0.6648117590030429, -0.26482259771960504, 0.54772429609472284, -0.58930805496179794], [-0.3705568042330003, 0.13914156728520855, 0.83616254382469846, 0.6609224092875603, 0.12930292638032426]]], [[[-0.040652326769339941, -0.28000548584426599, -0.64476634965815371, -0.54049639115735393, -0.86161774681830083], [-0.61013140491056395, 0.54541436881577199, -0.54601847713291751, -0.31621881114237693, -0.61724019337500291], [-0.44644750286742663, 0.59518192305072182, -0.7693498325029422, -0.42060186241232422, -0.55489928209223538], [-0.010271097007732655, -0.22885352817942128, -0.23461127002541859, 0.2259662465741632, -0.75911861057241303]], [[-0.58916400291939897, 0.38944538474440882, -0.63829862105093849, 0.72019195488661647, 0.52235809650215592], [0.13114169583575852, -0.58533255793898586, -0.68420879335952733, 0.92417522487531101, 0.7272342344782925], [-0.56777601453995841, -0.99375451020494832, 0.23729078199002207, -0.37389917191977862, -0.6758356849508167], [0.45071814163626911, 0.80301641829374315, -0.34653672569319238, -0.33515189137311152, 0.63975761694188726]], [[-0.78979414604272868, -0.43983713317632156, -0.74203230273291054, -0.88020557636880481, 0.47328240527524712], [-0.82389677158683061, 0.7178390238645278, -0.11098357077701571, 0.73262520297238942, 0.09735578528861577], [-0.88385341167453579, 0.61275720586751614, 0.76125858815934855, 0.14815442457054129, -0.54087876314080385], [0.85068577624506925, -0.46444971606055296, -0.62601913837363177, 0.2972222055112097, 0.66067056423975701]], [[-0.72007073982328085, 0.90956585931155076, 0.88200178773846005, -0.69430533795630245, -0.49857629281722504], [0.58092394474421427, 0.23240811382528248, -0.16824649980781214, 0.55878471927179807, 0.79568431021078023], [0.86166989839988894, 0.91296231064238254, 0.31164821231411866, -0.56046677494371044, 0.0385512568580888], [0.93714843860938113, 0.12260670095667692, 0.41615058741030264, -0.53179227427253117, -0.26098397322251543]], [[0.0028558200394461775, -0.50060512460961681, -0.93283479021249138, 0.82618003523249883, 0.21003657367784623], [-0.44588288887982475, -0.18118625551999723, -0.99177445676917753, -0.96873602172290019, -0.98701490005244841], [-0.93938608592020412, -0.016437629841765444, -0.36278147050642118, 0.52186707271265531, 0.89250194233082958], [0.84314628295750893, -0.098344859482383917, 0.66383189141986532, -0.47591027885241921, 0.59605402918250672]]], [[[-0.95794362834059377, -0.93767110890167471, -0.59649558326393914, 0.92707879675054206, -0.26646654731611896], [0.71313621784956482, 0.48496748630067921, -0.056901419366484518, 0.61280929565097964, 0.74294037098969978], [-0.48859644796388979, -0.44214089667786016, 0.62644178280749219, -0.060536138800636019, -0.57599606335652731], [-0.83904456131168415, -0.74905532220546855, 0.7486912362306215, -0.22402222230020863, -0.067386476775930682]], [[0.3184385936276124, -0.48262522108105022, -0.15510478911798553, -0.88527377048903855, 0.14896925645860337], [0.93368201508427573, 0.70361207151476601, 0.54827381187668389, -0.30181573690390695, 0.93407788633099109], [-0.41953515397211016, -0.99699015474725328, 0.077039550676741619, 0.084209448590547131, 0.76015066749097127], [0.54201663917636989, 0.12742530960610221, -0.12814330189633583, 0.51769077187580215, 0.82486105615641492]], [[0.64354010561109676, -0.42473695374832476, 0.3063589610119255, 0.35974954581874252, -0.51335607714264087], [-0.83565577834576166, -0.4308190974476882, -0.17313285404785406, -0.70522642627212995, -0.64687941557652229], [-0.18599656731065095, -0.044712449778867569, 0.49716990327674271, 0.30430680138579724, 0.08057899424959758], [0.58586637100455774, -0.13301988125684039, -0.044158021238169365, 0.053245830039011732, -0.53906389981826885]], [[0.21962406823739866, -0.71314553563905903, 0.54111730219890264, 0.19650615982926523, -0.059214339554341411], [-0.908481783495934, 0.33772345316258168, -0.86313443774430842, -0.57635827404614903, 0.52176471220549625], [-0.96424795883461867, -0.31443781628771283, -0.86245198160612913, -0.6565037382017811, -0.35318228761977455], [0.14426706591786842, 0.58298102985131806, -0.49066513703465353, -0.9150068286814601, 0.40374237858154149]], [[-0.69674134110121377, -0.71482950999283856, -0.59670958247227612, -0.91637682393291175, -0.25938985991666352], [0.45459801956464618, 0.74426900735359625, -0.22984550468363252, -0.43189830219709369, 0.8058729071921289], [0.25819553521791616, -0.095869899831380279, 0.85491697659907051, -0.57530704702476676, -0.50441247934023292], [0.69625438900313252, 0.28897970313322419, 0.71872510620750329, -0.055458863026323524, -0.082229736356652872]]]])          xx=numpy.array([[[[0.87917924924094204, 0.92576082229381873, 0.31182535354339991, -0.86214749809692592,
2373    -0.27507709543943437], [-0.0016382939288797083, 0.43307986157908585, 0.52636371100155199, -0.043319908450309308,
2374    0.20091228183885401], [0.71583896980535289, 0.50199360637469881, -0.67746890499802959, 0.73499870395620159,
2375    0.63277338423504914], [-0.59257453161192131, 0.66091287836835622, -0.19325788610358763, 0.57712882367912877,
2376    -0.7563530936539633]], [[-0.48965026554891877, -0.32764373599077956, -0.5131590362892775, 0.85592981071649832,
2377    0.99561636195898173], [0.24222780295446933, 0.28730806112554474, -0.32041176685276618, 0.78323831462368121,
2378    -0.72040929168456769], [0.95423747440270379, 0.39687818036239664, -0.77878094662206365, 0.75880557194836884,
2379    -0.1218416672560394], [-0.53785770919122489, 0.67105013676368763, 0.42864708225385661, -0.78784834304583429,
2380    -0.2681253344477097]], [[0.46875429958618664, 0.38741628037005071, -0.081056386101901357, -0.23469920628069518,
2381    -0.40907581999438447], [0.065494837299773234, 0.38170940261789488, -0.79236472117163403, -0.45228389456840379,
2382    0.55163355897584609], [-0.22355146021048489, -0.93756490876746912, 0.9241257141019481, 0.60698441154913452,
2383    -0.21265210744597973], [0.21034749440796197, 0.1659692307697147, 0.78720887852180499, 0.71946077138975917,
2384    -0.85985855270766165]], [[0.34986386801299396, 0.35619084924105593, -0.1952077124592666, -0.22518203420372651,
2385    -0.59920836063901772], [-0.58104191295806817, 0.29689367250987697, -0.10221810014905208, 0.096526465218390367,
2386    0.055496030226582782], [0.12128925311183991, -0.36085110995947267, -0.69818945730712589, -0.54447063194246215,
2387    0.28238768912002654], [0.5685290343654088, 0.90491556875163925, -0.83800696608599567, -0.11641347846076111,
2388    0.44596200041220047]], [[-0.59532265019171771, -0.27066391467944517, -0.89311609332930963, -0.99850338961193308,
2389    0.15639571601440827], [0.41583353392337186, 0.030126889068769591, -0.18653046086180169, 0.71825314848840516,
2390    -0.59319353551728171], [0.35800182346025844, -0.6648117590030429, -0.26482259771960504, 0.54772429609472284,
2391    -0.58930805496179794], [-0.3705568042330003, 0.13914156728520855, 0.83616254382469846, 0.6609224092875603,
2392    0.12930292638032426]]], [[[-0.040652326769339941, -0.28000548584426599, -0.64476634965815371, -0.54049639115735393,
2393    -0.86161774681830083], [-0.61013140491056395, 0.54541436881577199, -0.54601847713291751, -0.31621881114237693,
2394    -0.61724019337500291], [-0.44644750286742663, 0.59518192305072182, -0.7693498325029422, -0.42060186241232422,
2395    -0.55489928209223538], [-0.010271097007732655, -0.22885352817942128, -0.23461127002541859, 0.2259662465741632,
2396    -0.75911861057241303]], [[-0.58916400291939897, 0.38944538474440882, -0.63829862105093849, 0.72019195488661647,
2397    0.52235809650215592], [0.13114169583575852, -0.58533255793898586, -0.68420879335952733, 0.92417522487531101,
2398    0.7272342344782925], [-0.56777601453995841, -0.99375451020494832, 0.23729078199002207, -0.37389917191977862,
2399    -0.6758356849508167], [0.45071814163626911, 0.80301641829374315, -0.34653672569319238, -0.33515189137311152,
2400    0.63975761694188726]], [[-0.78979414604272868, -0.43983713317632156, -0.74203230273291054, -0.88020557636880481,
2401    0.47328240527524712], [-0.82389677158683061, 0.7178390238645278, -0.11098357077701571, 0.73262520297238942,
2402    0.09735578528861577], [-0.88385341167453579, 0.61275720586751614, 0.76125858815934855, 0.14815442457054129,
2403    -0.54087876314080385], [0.85068577624506925, -0.46444971606055296, -0.62601913837363177, 0.2972222055112097,
2404    0.66067056423975701]], [[-0.72007073982328085, 0.90956585931155076, 0.88200178773846005, -0.69430533795630245,
2405    -0.49857629281722504], [0.58092394474421427, 0.23240811382528248, -0.16824649980781214, 0.55878471927179807,
2406    0.79568431021078023], [0.86166989839988894, 0.91296231064238254, 0.31164821231411866, -0.56046677494371044,
2407    0.0385512568580888], [0.93714843860938113, 0.12260670095667692, 0.41615058741030264, -0.53179227427253117,
2408    -0.26098397322251543]], [[0.0028558200394461775, -0.50060512460961681, -0.93283479021249138, 0.82618003523249883,
2409    0.21003657367784623], [-0.44588288887982475, -0.18118625551999723, -0.99177445676917753, -0.96873602172290019,
2410    -0.98701490005244841], [-0.93938608592020412, -0.016437629841765444, -0.36278147050642118, 0.52186707271265531,
2411    0.89250194233082958], [0.84314628295750893, -0.098344859482383917, 0.66383189141986532, -0.47591027885241921,
2412    0.59605402918250672]]], [[[-0.95794362834059377, -0.93767110890167471, -0.59649558326393914, 0.92707879675054206,
2413    -0.26646654731611896], [0.71313621784956482, 0.48496748630067921, -0.056901419366484518, 0.61280929565097964,
2414    0.74294037098969978], [-0.48859644796388979, -0.44214089667786016, 0.62644178280749219, -0.060536138800636019,
2415    -0.57599606335652731], [-0.83904456131168415, -0.74905532220546855, 0.7486912362306215, -0.22402222230020863,
2416    -0.067386476775930682]], [[0.3184385936276124, -0.48262522108105022, -0.15510478911798553, -0.88527377048903855,
2417    0.14896925645860337], [0.93368201508427573, 0.70361207151476601, 0.54827381187668389, -0.30181573690390695,
2418    0.93407788633099109], [-0.41953515397211016, -0.99699015474725328, 0.077039550676741619, 0.084209448590547131,
2419    0.76015066749097127], [0.54201663917636989, 0.12742530960610221, -0.12814330189633583, 0.51769077187580215,
2420    0.82486105615641492]], [[0.64354010561109676, -0.42473695374832476, 0.3063589610119255, 0.35974954581874252,
2421    -0.51335607714264087], [-0.83565577834576166, -0.4308190974476882, -0.17313285404785406, -0.70522642627212995,
2422    -0.64687941557652229], [-0.18599656731065095, -0.044712449778867569, 0.49716990327674271, 0.30430680138579724,
2423    0.08057899424959758], [0.58586637100455774, -0.13301988125684039, -0.044158021238169365, 0.053245830039011732,
2424    -0.53906389981826885]], [[0.21962406823739866, -0.71314553563905903, 0.54111730219890264, 0.19650615982926523,
2425    -0.059214339554341411], [-0.908481783495934, 0.33772345316258168, -0.86313443774430842, -0.57635827404614903,
2426    0.52176471220549625], [-0.96424795883461867, -0.31443781628771283, -0.86245198160612913, -0.6565037382017811,
2427    -0.35318228761977455], [0.14426706591786842, 0.58298102985131806, -0.49066513703465353, -0.9150068286814601,
2428    0.40374237858154149]], [[-0.69674134110121377, -0.71482950999283856, -0.59670958247227612, -0.91637682393291175,
2429    -0.25938985991666352], [0.45459801956464618, 0.74426900735359625, -0.22984550468363252, -0.43189830219709369,
2430    0.8058729071921289], [0.25819553521791616, -0.095869899831380279, 0.85491697659907051, -0.57530704702476676,
2431    -0.50441247934023292], [0.69625438900313252, 0.28897970313322419, 0.71872510620750329, -0.055458863026323524,
2432    -0.082229736356652872]]]])
2433          ref=whereZero(xx)          ref=whereZero(xx)
2434          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2435          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1342  class SymbolicTestCase(unittest.TestCase Line 2440  class SymbolicTestCase(unittest.TestCase
2440          x=Symbol('x', shape)          x=Symbol('x', shape)
2441          y=nonsymmetric(x)          y=nonsymmetric(x)
2442          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2443          xx=numpy.array([[-0.66708916764681492, -0.74238465201633974, -0.079353161755557622, 0.30257601442541904], [0.20925829383746208, -0.022009924374370327, 0.10502873236092491, -0.15884250966193902], [0.1797060494083087, 0.023139755304512288, 0.45170178441767739, 0.48507784807517917], [0.059968719280828253, -0.41251906740163857, 0.2910687977002866, -0.63445501785955627]])          xx=numpy.array([[-0.66708916764681492, -0.74238465201633974, -0.079353161755557622, 0.30257601442541904],
2444    [0.20925829383746208, -0.022009924374370327, 0.10502873236092491, -0.15884250966193902], [0.1797060494083087,
2445    0.023139755304512288, 0.45170178441767739, 0.48507784807517917], [0.059968719280828253, -0.41251906740163857,
2446    0.2910687977002866, -0.63445501785955627]])
2447          ref=nonsymmetric(xx)          ref=nonsymmetric(xx)
2448          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2449          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1352  class SymbolicTestCase(unittest.TestCase Line 2453  class SymbolicTestCase(unittest.TestCase
2453          x=Symbol('x', shape)          x=Symbol('x', shape)
2454          y=nonsymmetric(x)          y=nonsymmetric(x)
2455          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2456          xx=numpy.array([[[[0.55376735565955926, -0.26986726052539045, 0.99540130065296051], [-0.66278909769325844, 0.47418600478729656, -0.57224349831177945]], [[0.26869674765376628, 0.87439268666551895, -0.58960755596620462], [-0.40755988519135888, -0.12284324214732534, -0.31617642601932183]], [[-0.025792397075229179, 0.33857483183258519, -0.39641658275864589], [-0.13242160052866581, -0.025186857396592099, 0.95590380942335851]]], [[[0.27725575342422726, -0.50385473604694497, 0.11901129980645275], [0.75590460511710589, 0.096085673196859789, -0.72791893038598321]], [[0.38794533456732516, 0.68280080521959974, 0.95500219859151003], [-0.58249140643372388, -0.38374270163626578, 0.49303266750299435]], [[-0.34681269192922426, -0.24778438052869323, 0.72024308366404277], [0.768229749916157, -0.79962778314547212, 0.70336464030375567]]]])          xx=numpy.array([[[[0.55376735565955926, -0.26986726052539045, 0.99540130065296051], [-0.66278909769325844,
2457    0.47418600478729656, -0.57224349831177945]], [[0.26869674765376628, 0.87439268666551895, -0.58960755596620462],
2458    [-0.40755988519135888, -0.12284324214732534, -0.31617642601932183]], [[-0.025792397075229179, 0.33857483183258519,
2459    -0.39641658275864589], [-0.13242160052866581, -0.025186857396592099, 0.95590380942335851]]], [[[0.27725575342422726,
2460    -0.50385473604694497, 0.11901129980645275], [0.75590460511710589, 0.096085673196859789, -0.72791893038598321]],
2461    [[0.38794533456732516, 0.68280080521959974, 0.95500219859151003], [-0.58249140643372388, -0.38374270163626578,
2462    0.49303266750299435]], [[-0.34681269192922426, -0.24778438052869323, 0.72024308366404277], [0.768229749916157,
2463    -0.79962778314547212, 0.70336464030375567]]]])
2464          ref=nonsymmetric(xx)          ref=nonsymmetric(xx)
2465          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2466          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1372  class SymbolicTestCase(unittest.TestCase Line 2480  class SymbolicTestCase(unittest.TestCase
2480          x=Symbol('x', shape)          x=Symbol('x', shape)
2481          y=symmetric(x)          y=symmetric(x)
2482          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2483          xx=numpy.array([[[[-0.47931228708865947, 0.10507685665916622, 0.1706306038031824, -0.48682627958350611, -0.052761050334725113, -0.61764395051469689], [0.33131346993926525, -0.17831168870543523, 0.83269324896567931, 0.49711792481658645, -0.15160508118267435, 0.034823661795621907]], [[0.83488102623337146, 0.48444595120803413, -0.2438647943575607, 0.65263344181761029, -0.53266665587602979, 0.042392390454812912], [0.32082347612712003, 0.24207481544942144, 0.90481421627507386, 0.58968892722797084, -0.37243554407799118, -0.95360987465922764]], [[0.54236303554410048, -0.77750655420008474, 0.86347524214181703, -0.60045464519880043, 0.6614103843852106, 0.1661581628512927], [-0.27633818658200648, -0.0092044623033202821, -0.77064836472526466, 0.27939966240494951, 0.71809970608669804, -0.0030250095390851328]], [[0.67629609745977559, 0.35017051906040519, 0.045207039627761736, -0.83837847095041584, 0.41784669604739855, 0.56574060434330353], [-0.085647568466385771, -0.70722504353285265, -0.2413437677613961, 0.65173300274030099, 0.49740733632840528, 0.78483628566812902]], [[-0.15655167722843855, -0.2643217130737634, -0.1907507722854267, 0.88643511791047569, 0.68916193655212843, -0.37723536389790091], [-0.55626566044838754, -0.98938031969368567, 0.72037970472566815, 0.08304233980247222, 0.57646971145679315, -0.53992799288622106]], [[-0.11144991273379024, 0.99118197843158296, 0.0042934206493501215, -0.61263222801310269, 0.4938389815759765, -0.053018311339752655], [0.87098646055584861, 0.2188430651448523, -0.26804136146176893, -0.92535908367104325, 0.52121221487688008, -0.61711018990565591]]], [[[0.71270846704492241, -0.074743332130423612, 0.12785251114370033, -0.79341710107657581, -0.017885731858772402, 0.68651610814691755], [0.063052501554288876, -0.35341399674809737, -0.22893402939136953, -0.28425123214766757, 0.66054323380507807, 0.061862036873020054]], [[0.67397793373178727, -0.34430769423381391, 0.32484940571520093, 0.073882587656904031, -0.69318017790826914, 0.80042677264669448], [0.29304891549348078, -0.39990075961382399, -0.50334862380676815, -0.68412227199254638, -0.17985296091249903, 0.88016340392243464]], [[0.91132543158899537, 0.24474430946290204, 0.15332311503635343, 0.15948665282678909, 0.18086292106026147, 0.7737255853795324], [-0.16063567286120239, -0.89954764701723167, -0.011648068495271113, 0.76021363407728981, 0.3648652547595066, -0.7163207516373884]], [[-0.5260529219985961, -0.5341824038899905, -0.24546004667603727, -0.68556445585168557, 0.00058699621817481784, 0.90805266220693048], [0.10346080847946149, 0.32661168806987351, -0.98860366824673807, 0.23210015251566563, -0.67778840377649785, -0.75819552887923702]], [[0.034695288275003344, -0.063434136501459459, 0.17626561461887391, -0.012597705074078869, -0.23908751605985867, 0.36337197419679801], [-0.40742067576725938, -0.28910284114307694, -0.034942103406036651, 0.91056413009275716, -0.82944439530144787, 0.96920580528501543]], [[0.93536972885023206, 0.77182940845310055, 0.027417593751139835, -0.26678735403398601, 0.49140092371614807, 0.46218190299367357], [0.79603807023119111, 0.65706269041412702, -0.38729966802179794, 0.28924104766767744, 0.63848678811732884, -0.99073927196286404]]]])          xx=numpy.array([[[[-0.47931228708865947, 0.10507685665916622, 0.1706306038031824, -0.48682627958350611,
2484    -0.052761050334725113, -0.61764395051469689], [0.33131346993926525, -0.17831168870543523, 0.83269324896567931,
2485    0.49711792481658645, -0.15160508118267435, 0.034823661795621907]], [[0.83488102623337146, 0.48444595120803413,
2486    -0.2438647943575607, 0.65263344181761029, -0.53266665587602979, 0.042392390454812912], [0.32082347612712003,
2487    0.24207481544942144, 0.90481421627507386, 0.58968892722797084, -0.37243554407799118, -0.95360987465922764]],
2488    [[0.54236303554410048, -0.77750655420008474, 0.86347524214181703, -0.60045464519880043, 0.6614103843852106,
2489    0.1661581628512927], [-0.27633818658200648, -0.0092044623033202821, -0.77064836472526466, 0.27939966240494951,
2490    0.71809970608669804, -0.0030250095390851328]], [[0.67629609745977559, 0.35017051906040519, 0.045207039627761736,
2491    -0.83837847095041584, 0.41784669604739855, 0.56574060434330353], [-0.085647568466385771, -0.70722504353285265,
2492    -0.2413437677613961, 0.65173300274030099, 0.49740733632840528, 0.78483628566812902]], [[-0.15655167722843855,
2493    -0.2643217130737634, -0.1907507722854267, 0.88643511791047569, 0.68916193655212843, -0.37723536389790091],
2494    [-0.55626566044838754, -0.98938031969368567, 0.72037970472566815, 0.08304233980247222, 0.57646971145679315,
2495    -0.53992799288622106]], [[-0.11144991273379024, 0.99118197843158296, 0.0042934206493501215, -0.61263222801310269,
2496    0.4938389815759765, -0.053018311339752655], [0.87098646055584861, 0.2188430651448523, -0.26804136146176893,
2497    -0.92535908367104325, 0.52121221487688008, -0.61711018990565591]]], [[[0.71270846704492241, -0.074743332130423612,
2498    0.12785251114370033, -0.79341710107657581, -0.017885731858772402, 0.68651610814691755], [0.063052501554288876,
2499    -0.35341399674809737, -0.22893402939136953, -0.28425123214766757, 0.66054323380507807, 0.061862036873020054]],
2500    [[0.67397793373178727, -0.34430769423381391, 0.32484940571520093, 0.073882587656904031, -0.69318017790826914,
2501    0.80042677264669448], [0.29304891549348078, -0.39990075961382399, -0.50334862380676815, -0.68412227199254638,
2502    -0.17985296091249903, 0.88016340392243464]], [[0.91132543158899537, 0.24474430946290204, 0.15332311503635343,
2503    0.15948665282678909, 0.18086292106026147, 0.7737255853795324], [-0.16063567286120239, -0.89954764701723167,
2504    -0.011648068495271113, 0.76021363407728981, 0.3648652547595066, -0.7163207516373884]], [[-0.5260529219985961,
2505    -0.5341824038899905, -0.24546004667603727, -0.68556445585168557, 0.00058699621817481784, 0.90805266220693048],
2506    [0.10346080847946149, 0.32661168806987351, -0.98860366824673807, 0.23210015251566563, -0.67778840377649785,
2507    -0.75819552887923702]], [[0.034695288275003344, -0.063434136501459459, 0.17626561461887391, -0.012597705074078869,
2508    -0.23908751605985867, 0.36337197419679801], [-0.40742067576725938, -0.28910284114307694, -0.034942103406036651,
2509    0.91056413009275716, -0.82944439530144787, 0.96920580528501543]], [[0.93536972885023206, 0.77182940845310055,
2510    0.027417593751139835, -0.26678735403398601, 0.49140092371614807, 0.46218190299367357], [0.79603807023119111,
2511    0.65706269041412702, -0.38729966802179794, 0.28924104766767744, 0.63848678811732884, -0.99073927196286404]]]])
2512          ref=symmetric(xx)          ref=symmetric(xx)
2513          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2514          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1403  class SymbolicTestCase(unittest.TestCase Line 2539  class SymbolicTestCase(unittest.TestCase
2539          x=Symbol('x', shape)          x=Symbol('x', shape)
2540          y=maxval(x)          y=maxval(x)
2541                    
2542          xx=numpy.array([[0.34735121468535302, 0.31792373377370797, -0.34362504765406632, 0.74644673081162916, -0.057418925515936081], [0.6732366131700307, -0.95238446096007912, -0.21844674633886907, -0.18926547437334618, 0.52984603152753795]])          xx=numpy.array([[0.34735121468535302, 0.31792373377370797, -0.34362504765406632, 0.74644673081162916,
2543    -0.057418925515936081], [0.6732366131700307, -0.95238446096007912, -0.21844674633886907, -0.18926547437334618,
2544    0.52984603152753795]])
2545          ref=maxval(xx)          ref=maxval(xx)
2546          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2547          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1413  class SymbolicTestCase(unittest.TestCase Line 2551  class SymbolicTestCase(unittest.TestCase
2551          x=Symbol('x', shape)          x=Symbol('x', shape)
2552          y=maxval(x)          y=maxval(x)
2553                    
2554          xx=numpy.array([[[0.42364784215934548, 0.66444692360687774, -0.29567189694092244], [0.99530022127084483, 0.30806444685979906, 0.73704625719821393], [0.95488935047107915, -0.16103673114816508, 0.32508484387903103]], [[0.42646650140936937, 0.25758089523264083, -0.10299917300444994], [-0.32512913895080708, 0.60765404003443413, 0.75746102375083146], [0.47427065451552686, -0.36709593744995073, -0.62234298674588739]], [[-0.51625772797208214, -0.17477544865889505, -0.2467213054045394], [0.21391484080459633, -0.11023541870594666, 0.52879222463793352], [-0.6115252143321559, -0.69548674713370429, -0.84959851655955743]], [[-0.047735520296660727, 0.63725644772456125, -0.81320293399414489], [0.033442410991393778, -0.52485955963669739, -0.87579195407828703], [0.099747411226758453, -0.48623897347358258, 0.18561580925432075]]])          xx=numpy.array([[[0.42364784215934548, 0.66444692360687774, -0.29567189694092244], [0.99530022127084483,
2555    0.30806444685979906, 0.73704625719821393], [0.95488935047107915, -0.16103673114816508, 0.32508484387903103]],
2556    [[0.42646650140936937, 0.25758089523264083, -0.10299917300444994], [-0.32512913895080708, 0.60765404003443413,
2557    0.75746102375083146], [0.47427065451552686, -0.36709593744995073, -0.62234298674588739]], [[-0.51625772797208214,
2558    -0.17477544865889505, -0.2467213054045394], [0.21391484080459633, -0.11023541870594666, 0.52879222463793352],
2559    [-0.6115252143321559, -0.69548674713370429, -0.84959851655955743]], [[-0.047735520296660727, 0.63725644772456125,
2560    -0.81320293399414489], [0.033442410991393778, -0.52485955963669739, -0.87579195407828703], [0.099747411226758453,
2561    -0.48623897347358258, 0.18561580925432075]]])
2562          ref=maxval(xx)          ref=maxval(xx)
2563          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2564          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1423  class SymbolicTestCase(unittest.TestCase Line 2568  class SymbolicTestCase(unittest.TestCase
2568          x=Symbol('x', shape)          x=Symbol('x', shape)
2569          y=maxval(x)          y=maxval(x)
2570                    
2571          xx=numpy.array([[[[-0.97772645022484239, 0.57304243484894912, -0.23114792233740067], [0.5009967216273834, 0.98728285370921998, 0.88165326175944081]], [[-0.86554004095808312, 0.79967438864226104, -0.52356143827663781], [0.33910376076389492, -0.33715271820715276, 0.7471336395988164]], [[0.97807293621863911, -0.32426795551673915, 0.97086761927014531], [0.69521998223272985, -0.50921868802924752, -0.4707875985687946]], [[0.32088835906711743, -0.67641005811719257, 0.6053555811404927], [-0.9755684596801586, -0.54801753900404271, -0.51569531087459231]], [[0.87859901272230245, -0.93819203169497767, 0.48552591270387691], [-0.90623293966225638, -0.56821898651640379, -0.70114717419616346]]], [[[0.7074153550653195, -0.065789330921568245, 0.1975906581408009], [-0.70031376520506416, -0.58588697093854769, 0.28784685846180036]], [[-0.37927702124416784, -0.25619886766039057, -0.75820003470201258], [0.75522605658504749, -0.86607222560760899, 0.77087852691254444]], [[0.78983241202496002, -0.93807825839461723, -0.64157008373209368], [-0.67265163687234764, -0.38384738076458658, 0.83095367437218925]], [[0.44769461663793142, 0.4681548319926121, 0.89179461494471446], [0.79244020458833186, 0.69571626917307383, 0.91369455881021167]], [[-0.20838088102066532, 0.74001065048887726, -0.21044275890782416], [0.89884395702714248, 0.42077808513336179, 0.89751742525902301]]], [[[0.13406499519690329, 0.93048539905404448, -0.88878801153635401], [-0.32682928056521643, -0.02669348688107398, 0.97150663926803249]], [[-0.97754157146727216, -0.52649319587800592, 0.51006871063667658], [-0.11775631034214085, -0.92540518843525632, -0.60798901233999914]], [[-0.26252763601616658, -0.10106038459184274, -0.35449159770172978], [-0.34352827137217257, 0.2131126361783362, -0.52225770770455338]], [[-0.99904658805863944, -0.03571103471541015, 0.34522288509344889], [-0.16466365212076028, -0.32272992229399655, -0.1104994415867564]], [[-0.58008507722437108, -0.41010112955007627, -0.77315836526542392], [0.20309194480149784, -0.46019343937075385, -0.25587082608895906]]], [[[0.87800190688704949, 0.14755820295840882, -0.66380548135485773], [-0.38373986766386214, 0.35559704316537077, 0.42892933288907176]], [[-0.14611087776987608, 0.84852402939259775, -0.47292417128454423], [0.7686091241664712, 0.070435421419021704, -0.17088786425027247]], [[-0.85107214556959176, -0.069124539395263307, -0.84046317240118973], [0.59678265942099928, 0.88283476525309879, -0.24815533144527979]], [[-0.28723087974789396, -0.83621864123734024, 0.020689401256574813], [0.9232387272498741, -0.68810732653308104, -0.81093541699621685]], [[0.73105323790407883, 0.51454885036546982, -0.72394828813224632], [-0.25287960060139225, 0.64569479592808587, 0.62813882863773229]]]])          xx=numpy.array([[[[-0.97772645022484239, 0.57304243484894912, -0.23114792233740067], [0.5009967216273834,
2572    0.98728285370921998, 0.88165326175944081]], [[-0.86554004095808312, 0.79967438864226104, -0.52356143827663781],
2573    [0.33910376076389492, -0.33715271820715276, 0.7471336395988164]], [[0.97807293621863911, -0.32426795551673915,
2574    0.97086761927014531], [0.69521998223272985, -0.50921868802924752, -0.4707875985687946]], [[0.32088835906711743,
2575    -0.67641005811719257, 0.6053555811404927], [-0.9755684596801586, -0.54801753900404271, -0.51569531087459231]],
2576    [[0.87859901272230245, -0.93819203169497767, 0.48552591270387691], [-0.90623293966225638, -0.56821898651640379,
2577    -0.70114717419616346]]], [[[0.7074153550653195, -0.065789330921568245, 0.1975906581408009], [-0.70031376520506416,
2578    -0.58588697093854769, 0.28784685846180036]], [[-0.37927702124416784, -0.25619886766039057, -0.75820003470201258],
2579    [0.75522605658504749, -0.86607222560760899, 0.77087852691254444]], [[0.78983241202496002, -0.93807825839461723,
2580    -0.64157008373209368], [-0.67265163687234764, -0.38384738076458658, 0.83095367437218925]], [[0.44769461663793142,
2581    0.4681548319926121, 0.89179461494471446], [0.79244020458833186, 0.69571626917307383, 0.91369455881021167]],
2582    [[-0.20838088102066532, 0.74001065048887726, -0.21044275890782416], [0.89884395702714248, 0.42077808513336179,
2583    0.89751742525902301]]], [[[0.13406499519690329, 0.93048539905404448, -0.88878801153635401], [-0.32682928056521643,
2584    -0.02669348688107398, 0.97150663926803249]], [[-0.97754157146727216, -0.52649319587800592, 0.51006871063667658],
2585    [-0.11775631034214085, -0.92540518843525632, -0.60798901233999914]], [[-0.26252763601616658, -0.10106038459184274,
2586    -0.35449159770172978], [-0.34352827137217257, 0.2131126361783362, -0.52225770770455338]], [[-0.99904658805863944,
2587    -0.03571103471541015, 0.34522288509344889], [-0.16466365212076028, -0.32272992229399655, -0.1104994415867564]],
2588    [[-0.58008507722437108, -0.41010112955007627, -0.77315836526542392], [0.20309194480149784, -0.46019343937075385,
2589    -0.25587082608895906]]], [[[0.87800190688704949, 0.14755820295840882, -0.66380548135485773], [-0.38373986766386214,
2590    0.35559704316537077, 0.42892933288907176]], [[-0.14611087776987608, 0.84852402939259775, -0.47292417128454423],
2591    [0.7686091241664712, 0.070435421419021704, -0.17088786425027247]], [[-0.85107214556959176, -0.069124539395263307,
2592    -0.84046317240118973], [0.59678265942099928, 0.88283476525309879, -0.24815533144527979]], [[-0.28723087974789396,
2593    -0.83621864123734024, 0.020689401256574813], [0.9232387272498741, -0.68810732653308104, -0.81093541699621685]],
2594    [[0.73105323790407883, 0.51454885036546982, -0.72394828813224632], [-0.25287960060139225, 0.64569479592808587,
2595    0.62813882863773229]]]])
2596          ref=maxval(xx)          ref=maxval(xx)
2597          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2598          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1443  class SymbolicTestCase(unittest.TestCase Line 2612  class SymbolicTestCase(unittest.TestCase
2612          x=Symbol('x', shape)          x=Symbol('x', shape)
2613          y=minval(x)          y=minval(x)
2614                    
2615          xx=numpy.array([-0.85135969885833096, 0.7532816318813329, -0.5882678068887619, 0.89119141508691402, -0.9379977266076569])          xx=numpy.array([-0.85135969885833096, 0.7532816318813329, -0.5882678068887619, 0.89119141508691402,
2616    -0.9379977266076569])
2617          ref=minval(xx)          ref=minval(xx)
2618          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2619          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1453  class SymbolicTestCase(unittest.TestCase Line 2623  class SymbolicTestCase(unittest.TestCase
2623          x=Symbol('x', shape)          x=Symbol('x', shape)
2624          y=minval(x)          y=minval(x)
2625                    
2626          xx=numpy.array([[0.04757935417938719, 0.56448960316435781], [-0.7967017037359494, -0.24401431507973848], [-0.59131630413733083, -0.52722327369086197], [-0.18374212137163393, -0.60315054526379708], [0.22196503091420383, 0.12665575107549576], [0.71319493777219689, 0.2752127433396967]])          xx=numpy.array([[0.04757935417938719, 0.56448960316435781], [-0.7967017037359494, -0.24401431507973848],
2627    [-0.59131630413733083, -0.52722327369086197], [-0.18374212137163393, -0.60315054526379708], [0.22196503091420383,
2628    0.12665575107549576], [0.71319493777219689, 0.2752127433396967]])
2629          ref=minval(xx)          ref=minval(xx)
2630          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2631          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1463  class SymbolicTestCase(unittest.TestCase Line 2635  class SymbolicTestCase(unittest.TestCase
2635          x=Symbol('x', shape)          x=Symbol('x', shape)
2636          y=minval(x)          y=minval(x)
2637                    
2638          xx=numpy.array([[[-0.37545612635023939]], [[0.2230129304822781]], [[-0.45233309721956294]], [[-0.26620859057037216]], [[-0.30837618713582637]], [[0.78814029871507829]]])          xx=numpy.array([[[-0.37545612635023939]], [[0.2230129304822781]], [[-0.45233309721956294]], [[-0.26620859057037216]],
2639    [[-0.30837618713582637]], [[0.78814029871507829]]])
2640          ref=minval(xx)          ref=minval(xx)
2641          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2642          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1473  class SymbolicTestCase(unittest.TestCase Line 2646  class SymbolicTestCase(unittest.TestCase
2646          x=Symbol('x', shape)          x=Symbol('x', shape)
2647          y=minval(x)          y=minval(x)
2648                    
2649          xx=numpy.array([[[[0.90578355615023698, -0.51094614506705494]]], [[[-0.63501200952398085, -0.46547690121911156]]], [[[0.67638924191025884, 0.55257795954409628]]], [[[0.68011812217900491, -0.53935030654427019]]], [[[0.51457282740049237, -0.65201714679111422]]], [[[-0.54031827299109603, -0.059011224051143341]]]])          xx=numpy.array([[[[0.90578355615023698, -0.51094614506705494]]], [[[-0.63501200952398085, -0.46547690121911156]]],
2650    [[[0.67638924191025884, 0.55257795954409628]]], [[[0.68011812217900491, -0.53935030654427019]]], [[[0.51457282740049237,
2651    -0.65201714679111422]]], [[[-0.54031827299109603, -0.059011224051143341]]]])
2652          ref=minval(xx)          ref=minval(xx)
2653          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2654          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1504  class SymbolicTestCase(unittest.TestCase Line 2679  class SymbolicTestCase(unittest.TestCase
2679          x=Symbol('x', shape)          x=Symbol('x', shape)
2680          y=inverse(x)          y=inverse(x)
2681          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2682          xx=numpy.array([[0.45028554514700891, -0.071572787871187593, -0.39441942665859409], [0.73229203641636409, -0.40855316211290282, -0.12348705744184918], [-0.47530902424927413, 0.45609397667651108, -0.3860382301700751]])          xx=numpy.array([[0.45028554514700891, -0.071572787871187593, -0.39441942665859409], [0.73229203641636409,
2683    -0.40855316211290282, -0.12348705744184918], [-0.47530902424927413, 0.45609397667651108, -0.3860382301700751]])
2684          ref=inverse(xx)          ref=inverse(xx)
2685          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2686          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1535  class SymbolicTestCase(unittest.TestCase Line 2711  class SymbolicTestCase(unittest.TestCase
2711          x=Symbol('x', shape)          x=Symbol('x', shape)
2712          y=transpose(x,1)          y=transpose(x,1)
2713          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2714          xx=numpy.array([-0.60705531324714634, 0.62810480691473658, 0.77189612790979578, -0.71300060089285577, -0.35861924250677912])          xx=numpy.array([-0.60705531324714634, 0.62810480691473658, 0.77189612790979578, -0.71300060089285577,
2715    -0.35861924250677912])
2716          ref=transpose(xx,1)          ref=transpose(xx,1)
2717          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2718          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1545  class SymbolicTestCase(unittest.TestCase Line 2722  class SymbolicTestCase(unittest.TestCase
2722          x=Symbol('x', shape)          x=Symbol('x', shape)
2723          y=transpose(x,0)          y=transpose(x,0)
2724          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2725          xx=numpy.array([[0.29824722631373124, 0.63375418610212408, 0.21922442998100244, 0.12715532157523968, -0.29643893323918102, -0.16166333104335817], [-0.89328765219407691, 0.27683764917068565, 0.34017377147969219, -0.53274644593651321, -0.1422658361691147, 0.28161907229446315], [-0.38203701914488764, -0.2961521871919941, 0.80071418498487024, 0.83878791977835077, -0.69075507497575783, -0.16169785100459899], [-0.032504150913533314, -0.64123342525770588, -0.084919983774251584, 0.92118199386482202, 0.26012548701114357, 0.72035325070640543], [-0.24685236184450643, 0.36815987147920048, -0.24045842732995948, -0.93481032202233783, 0.53659798717183871, -0.25927629660414153], [0.52973705424869744, 0.32004608474978991, 0.90380715550842816, -0.65392860402124442, 0.63799552939147652, -0.27587752537198384]])          xx=numpy.array([[0.29824722631373124, 0.63375418610212408, 0.21922442998100244, 0.12715532157523968,
2726    -0.29643893323918102, -0.16166333104335817], [-0.89328765219407691, 0.27683764917068565, 0.34017377147969219,
2727    -0.53274644593651321, -0.1422658361691147, 0.28161907229446315], [-0.38203701914488764, -0.2961521871919941,
2728    0.80071418498487024, 0.83878791977835077, -0.69075507497575783, -0.16169785100459899], [-0.032504150913533314,
2729    -0.64123342525770588, -0.084919983774251584, 0.92118199386482202, 0.26012548701114357, 0.72035325070640543],
2730    [-0.24685236184450643, 0.36815987147920048, -0.24045842732995948, -0.93481032202233783, 0.53659798717183871,
2731    -0.25927629660414153], [0.52973705424869744, 0.32004608474978991, 0.90380715550842816, -0.65392860402124442,
2732    0.63799552939147652, -0.27587752537198384]])
2733          ref=transpose(xx,0)          ref=transpose(xx,0)
2734          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2735          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1555  class SymbolicTestCase(unittest.TestCase Line 2739  class SymbolicTestCase(unittest.TestCase
2739          x=Symbol('x', shape)          x=Symbol('x', shape)
2740          y=transpose(x,1)          y=transpose(x,1)
2741          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2742          xx=numpy.array([[-0.73357955978002387, 0.32007537987130541, 0.80392128184540268, 0.075907889124529948, -0.039990110087071651, 0.12075338135391833]])          xx=numpy.array([[-0.73357955978002387, 0.32007537987130541, 0.80392128184540268, 0.075907889124529948,
2743    -0.039990110087071651, 0.12075338135391833]])
2744          ref=transpose(xx,1)          ref=transpose(xx,1)
2745          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2746          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1565  class SymbolicTestCase(unittest.TestCase Line 2750  class SymbolicTestCase(unittest.TestCase
2750          x=Symbol('x', shape)          x=Symbol('x', shape)
2751          y=transpose(x,2)          y=transpose(x,2)
2752          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2753          xx=numpy.array([[0.25551832867199376, 0.42008002231810315, 0.078215128725729111, 0.70039085616518548, -0.88204165217907637], [-0.34979785984659939, 0.08315537698343678, 0.43326454393298341, -0.062646735390029296, 0.41602450028477334], [-0.41495962824919475, 0.64372525733542396, 0.31391836076533819, 0.4939984978067602, -0.053702510243994528]])          xx=numpy.array([[0.25551832867199376, 0.42008002231810315, 0.078215128725729111, 0.70039085616518548,
2754    -0.88204165217907637], [-0.34979785984659939, 0.08315537698343678, 0.43326454393298341, -0.062646735390029296,
2755    0.41602450028477334], [-0.41495962824919475, 0.64372525733542396, 0.31391836076533819, 0.4939984978067602,
2756    -0.053702510243994528]])
2757          ref=transpose(xx,2)          ref=transpose(xx,2)
2758          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2759          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1575  class SymbolicTestCase(unittest.TestCase Line 2763  class SymbolicTestCase(unittest.TestCase
2763          x=Symbol('x', shape)          x=Symbol('x', shape)
2764          y=transpose(x,0)          y=transpose(x,0)
2765          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2766          xx=numpy.array([[[0.26311042905201254, 0.35909401464904889, 0.90408965239472594, 0.064216765615245475, 0.89018018616522032, 0.61515401166904038], [-0.30989721207991727, 0.01554721397885328, 0.52855204676559642, 0.93771990426057239, -0.15268008182723269, -0.72186799095134035], [0.29533985198855883, 0.84120750629942131, -0.22819454447353227, 0.53533756476516925, -0.17828320712265366, -0.78412542334949542], [-0.60495885555969942, -0.25855652778532168, -0.15744952045553418, 0.5567093392784852, 0.23570396793559212, 0.19344156929131118]], [[-0.42782972938810349, 0.93496323651712765, -0.20729448187853028, 0.15464520183866215, 0.0043514616865014677, -0.51750038510802732], [-0.22811855804368841, -0.48794731937174163, 0.92444939190764486, -0.82797921663444662, -0.78083506656193813, -0.63163718067425112], [0.56047492548799616, -0.2744337823672458, -0.6547449031228918, 0.56648635685738769, -0.11694804353070998, -0.038687755044935379], [-0.40048029851421107, 0.58145660627249818, -0.71158323850172178, -0.92609046734296485, 0.47425311825021166, 0.24907305314740569]], [[-0.26289340847029763, -0.6627578090201578, 0.62394979447651489, -0.47215367721990265, -0.64661615031822905, -0.57803380349174183], [-0.99219145036848722, 0.025564187125975968, -0.84489002798303048, 0.1859355185991034, -0.10171106325521784, -0.96678921742804902], [-0.047487603598241224, -0.32327046729535125, 0.59358325902723896, 0.2430229651630238, 0.9924605637701025, -0.9095931432779174], [-0.14746705870069343, 0.8316033803487568, -0.51338609129446722, 0.26829256656137224, 0.15800350230147164, 0.74083217352043351]]])          xx=numpy.array([[[0.26311042905201254, 0.35909401464904889, 0.90408965239472594, 0.064216765615245475,
2767    0.89018018616522032, 0.61515401166904038], [-0.30989721207991727, 0.01554721397885328, 0.52855204676559642,
2768    0.93771990426057239, -0.15268008182723269, -0.72186799095134035], [0.29533985198855883, 0.84120750629942131,
2769    -0.22819454447353227, 0.53533756476516925, -0.17828320712265366, -0.78412542334949542], [-0.60495885555969942,
2770    -0.25855652778532168, -0.15744952045553418, 0.5567093392784852, 0.23570396793559212, 0.19344156929131118]],
2771    [[-0.42782972938810349, 0.93496323651712765, -0.20729448187853028, 0.15464520183866215, 0.0043514616865014677,
2772    -0.51750038510802732], [-0.22811855804368841, -0.48794731937174163, 0.92444939190764486, -0.82797921663444662,
2773    -0.78083506656193813, -0.63163718067425112], [0.56047492548799616, -0.2744337823672458, -0.6547449031228918,
2774    0.56648635685738769, -0.11694804353070998, -0.038687755044935379], [-0.40048029851421107, 0.58145660627249818,
2775    -0.71158323850172178, -0.92609046734296485, 0.47425311825021166, 0.24907305314740569]], [[-0.26289340847029763,
2776    -0.6627578090201578, 0.62394979447651489, -0.47215367721990265, -0.64661615031822905, -0.57803380349174183],
2777    [-0.99219145036848722, 0.025564187125975968, -0.84489002798303048, 0.1859355185991034, -0.10171106325521784,
2778    -0.96678921742804902], [-0.047487603598241224, -0.32327046729535125, 0.59358325902723896, 0.2430229651630238,
2779    0.9924605637701025, -0.9095931432779174], [-0.14746705870069343, 0.8316033803487568, -0.51338609129446722, 0.26829256656137224,
2780    0.15800350230147164, 0.74083217352043351]]])
2781          ref=transpose(xx,0)          ref=transpose(xx,0)
2782          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2783          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1585  class SymbolicTestCase(unittest.TestCase Line 2787  class SymbolicTestCase(unittest.TestCase
2787          x=Symbol('x', shape)          x=Symbol('x', shape)
2788          y=transpose(x,1)          y=transpose(x,1)
2789          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2790          xx=numpy.array([[[0.068231745020743695, 0.28497669381507706], [0.16579540496302525, -0.0073004211699192467], [0.048763180867146261, -0.90650544874903161], [-0.77560606065477233, -0.22408349827566187], [0.17941319486573315, 0.95839772281795654]]])          xx=numpy.array([[[0.068231745020743695, 0.28497669381507706], [0.16579540496302525, -0.0073004211699192467],
2791    [0.048763180867146261, -0.90650544874903161], [-0.77560606065477233, -0.22408349827566187], [0.17941319486573315,
2792    0.95839772281795654]]])
2793          ref=transpose(xx,1)          ref=transpose(xx,1)
2794          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2795          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1595  class SymbolicTestCase(unittest.TestCase Line 2799  class SymbolicTestCase(unittest.TestCase
2799          x=Symbol('x', shape)          x=Symbol('x', shape)
2800          y=transpose(x,2)          y=transpose(x,2)
2801          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2802          xx=numpy.array([[[-0.44441954295782415, 0.57951688465897666, 0.97759547928033852]], [[0.9694383324351068, 0.95911385829077767, 0.34153788003972307]]])          xx=numpy.array([[[-0.44441954295782415, 0.57951688465897666, 0.97759547928033852]], [[0.9694383324351068,
2803    0.95911385829077767, 0.34153788003972307]]])
2804          ref=transpose(xx,2)          ref=transpose(xx,2)
2805          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2806          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1605  class SymbolicTestCase(unittest.TestCase Line 2810  class SymbolicTestCase(unittest.TestCase
2810          x=Symbol('x', shape)          x=Symbol('x', shape)
2811          y=transpose(x,3)          y=transpose(x,3)
2812          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2813          xx=numpy.array([[[-0.56750193647189295], [0.74203408066371557], [0.88359255309208407], [-0.1420561936189324], [-0.1832315325470717], [0.67350071639095455]], [[-0.12986823051754137], [-0.62214225719818117], [0.76051722748179884], [0.19372894258576401], [0.51431220823279777], [-0.55327737164253321]], [[-0.12774343291108359], [0.91719475963576147], [0.91573642478780415], [-0.61521915077800782], [-0.40787721375622787], [-0.0061586053369555582]], [[0.057062787602994103], [0.49344734797982026], [-0.82845047193545973], [-0.68097806860425036], [-0.53065790567095972], [-0.21476705851128997]]])          xx=numpy.array([[[-0.56750193647189295], [0.74203408066371557], [0.88359255309208407], [-0.1420561936189324],
2814    [-0.1832315325470717], [0.67350071639095455]], [[-0.12986823051754137], [-0.62214225719818117], [0.76051722748179884],
2815    [0.19372894258576401], [0.51431220823279777], [-0.55327737164253321]], [[-0.12774343291108359], [0.91719475963576147],
2816    [0.91573642478780415], [-0.61521915077800782], [-0.40787721375622787], [-0.0061586053369555582]], [[0.057062787602994103],
2817    [0.49344734797982026], [-0.82845047193545973], [-0.68097806860425036], [-0.53065790567095972], [-0.21476705851128997]]])
2818          ref=transpose(xx,3)          ref=transpose(xx,3)
2819          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2820          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1615  class SymbolicTestCase(unittest.TestCase Line 2824  class SymbolicTestCase(unittest.TestCase
2824          x=Symbol('x', shape)          x=Symbol('x', shape)
2825          y=transpose(x,0)          y=transpose(x,0)
2826          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2827          xx=numpy.array([[[[0.54824608108340733, -0.95881993351872175, 0.096047244291673994, 0.052360005545741606, 0.12490898613666901, 0.37925568740922189], [-0.55124438933079856, -0.52935244195563946, 0.27908541506517448, -0.1830678527428955, -0.61244328503367873, -0.010607705370612397], [-0.80506898031795937, -0.21539423990251261, 0.73483184561396819, 0.3218480929559373, 0.63228046571224295, -0.11544050682355489], [0.50999066506659219, 0.61608238345318789, 0.85718098893486228, -0.82554569171674919, 0.67239454553509659, -0.77128236726181387], [0.77415761641002478, -0.21788051784728957, -0.79355077597956836, -0.1361323772856724, -0.86290682182908185, 0.02622965736996985], [0.74395099341159487, 0.13786029833658375, 0.64251511260194349, -0.30926165348941947, 0.066002055058048015, -0.18373875123993755]], [[0.80181502648535408, -0.31866470950275949, -0.33856607958158369, -0.60420044839061493, -0.48291079444954743, 0.24475260440995461], [0.22283617220107033, -0.6615458160126455, -0.66676148321169748, 0.97999033040506101, 0.06108795758199248, 0.040226927587740491], [-0.67186168564203053, -0.14276728079247003, 0.19541571657523216, -0.75136887419362108, -0.59956121332937018, 0.059908246353421513], [-0.20724545062697186, -0.17856278158186711, 0.047379025453474055, 0.15840963916227646, 0.13540917508687045, 0.85895067204573583], [-0.83872496960394871, 0.23265853232152711, 0.19453704633971625, -0.96538534645560392, -0.89514948083720092, 0.52011941028029685], [-0.97139300748704027, 0.7819520140439693, -0.015898695567955201, 0.29189177705966207, 0.7814405901040784, -0.027981993399570637]], [[0.024367179589735111, -0.92559202239623994, 0.0380332273061188, 0.36881267312762245, 0.20795105074551024, 0.69371808897843201], [0.49435054361558683, 0.58132683830046772, -0.76010694324043038, 0.28394316877079939, -0.82021099055909619, 0.49870600029852086], [-0.51039201474247053, 0.56336641890331585, -0.52323759045305485, 0.52986550038889946, 0.5034221907692511, 0.18849560067453153], [0.60090832298881591, 0.12268166503962252, 0.65511543959119356, -0.97314981949878665, 0.93457616725728321, -0.36648294820963012], [-0.51170849654484218, -0.50879187831813777, 0.10542578094698452, 0.45077764740856896, -0.31197154971763363, -0.45296904314713959], [0.14168707080581178, 0.062913177405235166, 0.65635509363307154, -0.11073208661229672, -0.16755936854126485, 0.9561185477484222]]]])          xx=numpy.array([[[[0.54824608108340733, -0.95881993351872175, 0.096047244291673994, 0.052360005545741606,
2828    0.12490898613666901, 0.37925568740922189], [-0.55124438933079856, -0.52935244195563946, 0.27908541506517448,
2829    -0.1830678527428955, -0.61244328503367873, -0.010607705370612397], [-0.80506898031795937, -0.21539423990251261,
2830    0.73483184561396819, 0.3218480929559373, 0.63228046571224295, -0.11544050682355489], [0.50999066506659219, 0.61608238345318789,
2831    0.85718098893486228, -0.82554569171674919, 0.67239454553509659, -0.77128236726181387], [0.77415761641002478,
2832    -0.21788051784728957, -0.79355077597956836, -0.1361323772856724, -0.86290682182908185, 0.02622965736996985],
2833    [0.74395099341159487, 0.13786029833658375, 0.64251511260194349, -0.30926165348941947, 0.066002055058048015,
2834    -0.18373875123993755]], [[0.80181502648535408, -0.31866470950275949, -0.33856607958158369, -0.60420044839061493,
2835    -0.48291079444954743, 0.24475260440995461], [0.22283617220107033, -0.6615458160126455, -0.66676148321169748,
2836    0.97999033040506101, 0.06108795758199248, 0.040226927587740491], [-0.67186168564203053, -0.14276728079247003,
2837    0.19541571657523216, -0.75136887419362108, -0.59956121332937018, 0.059908246353421513], [-0.20724545062697186,
2838    -0.17856278158186711, 0.047379025453474055, 0.15840963916227646, 0.13540917508687045, 0.85895067204573583],
2839    [-0.83872496960394871, 0.23265853232152711, 0.19453704633971625, -0.96538534645560392, -0.89514948083720092,
2840    0.52011941028029685], [-0.97139300748704027, 0.7819520140439693, -0.015898695567955201, 0.29189177705966207,
2841    0.7814405901040784, -0.027981993399570637]], [[0.024367179589735111, -0.92559202239623994, 0.0380332273061188,
2842    0.36881267312762245, 0.20795105074551024, 0.69371808897843201], [0.49435054361558683, 0.58132683830046772,
2843    -0.76010694324043038, 0.28394316877079939, -0.82021099055909619, 0.49870600029852086], [-0.51039201474247053,
2844    0.56336641890331585, -0.52323759045305485, 0.52986550038889946, 0.5034221907692511, 0.18849560067453153], [0.60090832298881591,
2845    0.12268166503962252, 0.65511543959119356, -0.97314981949878665, 0.93457616725728321, -0.36648294820963012],
2846    [-0.51170849654484218, -0.50879187831813777, 0.10542578094698452, 0.45077764740856896, -0.31197154971763363,
2847    -0.45296904314713959], [0.14168707080581178, 0.062913177405235166, 0.65635509363307154, -0.11073208661229672,
2848    -0.16755936854126485, 0.9561185477484222]]]])
2849          ref=transpose(xx,0)          ref=transpose(xx,0)
2850          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2851          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1625  class SymbolicTestCase(unittest.TestCase Line 2855  class SymbolicTestCase(unittest.TestCase
2855          x=Symbol('x', shape)          x=Symbol('x', shape)
2856          y=transpose(x,1)          y=transpose(x,1)
2857          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2858          xx=numpy.array([[[[-0.61981582085444975, -0.96131273801498329, 0.74219386268038434], [0.55966010365844987, 0.71389079962454427, 0.8989592580659409]], [[-0.32362828871796334, -0.19464923533132406, -0.077071376688295556], [-0.31631546071958838, -0.63804519499196855, 0.034469021777733255]]], [[[-0.98013465627214558, 0.55692938312034257, -0.069876839824936088], [0.23107446680923793, 0.20970489689947236, 0.63734275566499932]], [[-0.38904775463304775, 0.071793925322782615, -0.46938272402469572], [0.81376007574910103, 0.72212779041170472, -0.7900188086653761]]], [[[-0.21364296019115114, 0.44694321429953288, 0.013273984088666202], [-0.30688415384900836, -0.79173559959507545, 0.21393561197226707]], [[0.11643782235065991, -0.91447688288862561, 0.8191757449265018], [0.18102464836223464, 0.23160336066416609, 0.59871147260783464]]], [[[0.99733195033134581, -0.3095466388403092, 0.3954110325522926], [0.46142982683595646, -0.47003892539287939, 0.94950085174619647]], [[0.16984700471120551, 0.15805429609841348, 0.24500674000556089], [-0.55165958732539777, -0.92936800791598762, -0.022951588393276046]]], [[[-0.47677497240186817, -0.29108181048886861, -0.46273092627976475], [0.1273672188319761, -0.45995292810695965, 0.63194581534140681]], [[-0.55300845786078279, 0.7533517791070008, -0.13448526871956634], [-0.37358334038389174, 0.20829676253681684, -0.45687485563287189]]], [[[-0.036755848169893302, 0.30727556288418967, -0.21041329338872861], [0.20182923263729791, 0.65877866222054271, -0.24646229766737426]], [[-0.98252816636757379, -0.36713378601223945, -0.80808457042378978], [-0.26267367173420597, -0.2518970867644057, 0.011477505796322118]]]])          xx=numpy.array([[[[-0.61981582085444975, -0.96131273801498329, 0.74219386268038434], [0.55966010365844987,
2859    0.71389079962454427, 0.8989592580659409]], [[-0.32362828871796334, -0.19464923533132406, -0.077071376688295556],
2860    [-0.31631546071958838, -0.63804519499196855, 0.034469021777733255]]], [[[-0.98013465627214558, 0.55692938312034257,
2861    -0.069876839824936088], [0.23107446680923793, 0.20970489689947236, 0.63734275566499932]], [[-0.38904775463304775,
2862    0.071793925322782615, -0.46938272402469572], [0.81376007574910103, 0.72212779041170472, -0.7900188086653761]]],
2863    [[[-0.21364296019115114, 0.44694321429953288, 0.013273984088666202], [-0.30688415384900836, -0.79173559959507545,
2864    0.21393561197226707]], [[0.11643782235065991, -0.91447688288862561, 0.8191757449265018], [0.18102464836223464,
2865    0.23160336066416609, 0.59871147260783464]]], [[[0.99733195033134581, -0.3095466388403092, 0.3954110325522926],
2866    [0.46142982683595646, -0.47003892539287939, 0.94950085174619647]], [[0.16984700471120551, 0.15805429609841348,
2867    0.24500674000556089], [-0.55165958732539777, -0.92936800791598762, -0.022951588393276046]]], [[[-0.47677497240186817,
2868    -0.29108181048886861, -0.46273092627976475], [0.1273672188319761, -0.45995292810695965, 0.63194581534140681]],
2869    [[-0.55300845786078279, 0.7533517791070008, -0.13448526871956634], [-0.37358334038389174, 0.20829676253681684,
2870    -0.45687485563287189]]], [[[-0.036755848169893302, 0.30727556288418967, -0.21041329338872861], [0.20182923263729791,
2871    0.65877866222054271, -0.24646229766737426]], [[-0.98252816636757379, -0.36713378601223945, -0.80808457042378978],
2872    [-0.26267367173420597, -0.2518970867644057, 0.011477505796322118]]]])
2873          ref=transpose(xx,1)          ref=transpose(xx,1)
2874          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2875          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1635  class SymbolicTestCase(unittest.TestCase Line 2879  class SymbolicTestCase(unittest.TestCase
2879          x=Symbol('x', shape)          x=Symbol('x', shape)
2880          y=transpose(x,2)          y=transpose(x,2)
2881          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2882          xx=numpy.array([[[[-0.16214769600244305, 0.24217872120946082, -0.30028030966869657], [-0.48045998353105079, 0.95693823823765212, 0.52916178178914697], [-0.48954360115331808, 0.85861012301924489, -0.81692988730865213], [-0.087644936882469437, -0.3842832680291377, 0.35011196871912009], [0.57129365131241583, -0.026003764280923436, -0.75091671858302056], [-0.74212966728321961, 0.12594020322095445, -0.49899956224796882]], [[-0.63238633088294094, -0.34904744665375165, -0.77820922334570719], [0.9223856580495613, -0.092757622542367635, 0.072822560962293004], [-0.070993587117452295, -0.14883635172390397, -0.76366672463695995], [-0.58165146796847944, 0.25485622479175296, -0.4385367103246629], [-0.6718851054540862, -0.54227121325719052, 0.22659211333469198], [-0.77256203431387149, 0.32093113572510412, -0.024748143906698106]]], [[[-0.81065249686006191, 0.85744411886085925, -0.6926225063339142], [0.1359015377696986, 0.16676992366466048, -0.25508688732693452], [0.51534906080188891, -0.51302456371614524, -0.13403185580745269], [-0.83972439581808334, 0.43981616780551591, 0.32672995034070751], [0.65639618069998873, -0.89753193640920048, 0.85900236622478832], [0.38497532723462147, 0.83291046269513536, -0.80651708700513747]], [[-0.51373944818354556, -0.72195574816716812, 0.90186186159805426], [-0.56332521605329755, 0.49732930230749539, 0.1484166126253168], [-0.72917908882955729, -0.95729599166703117, 0.72755275645534057], [0.4921919188713737, -0.96432237192190851, -0.036083259295467185], [0.1723714120524098, 0.040941543603711272, 0.62521746283269097], [-0.1690314543596303, 0.47940137593575449, 0.42640711858738989]]], [[[0.10390397381997918, -0.24977943617300435, -0.98869850717150864], [-0.96639652829702083, 0.35034662237955816, -0.56248828327408051], [0.96408180547845057, -0.23999573384656303, -0.81951160331181905], [-0.47170906450449324, 0.6419551236751726, -0.48542637867915861], [0.70176197798886486, 0.96442202464370985, 0.83401799166885082], [0.79732376621020729, 0.70856863055292596, -0.28971110032777569]], [[-0.44536694566283019, 0.53490318645652013, -0.040524017414241387], [0.8017156672864223, -0.035466342245163318, 0.14641512106385846], [0.38200951751843482, 0.55381128552992576, 0.62196907345612029], [-0.59415983609316458, -0.057552239669435235, -0.87044248211447695], [-0.20880226272887281, 0.89867393628607095, -0.27599039986863305], [0.38668431971946848, 0.77159353796456487, -0.049495448837690637]]]])          xx=numpy.array([[[[-0.16214769600244305, 0.24217872120946082, -0.30028030966869657], [-0.48045998353105079,
2883    0.95693823823765212, 0.52916178178914697], [-0.48954360115331808, 0.85861012301924489, -0.81692988730865213],
2884    [-0.087644936882469437, -0.3842832680291377, 0.35011196871912009], [0.57129365131241583, -0.026003764280923436,
2885    -0.75091671858302056], [-0.74212966728321961, 0.12594020322095445, -0.49899956224796882]], [[-0.63238633088294094,
2886    -0.34904744665375165, -0.77820922334570719], [0.9223856580495613, -0.092757622542367635, 0.072822560962293004],
2887    [-0.070993587117452295, -0.14883635172390397, -0.76366672463695995], [-0.58165146796847944, 0.25485622479175296,
2888    -0.4385367103246629], [-0.6718851054540862, -0.54227121325719052, 0.22659211333469198], [-0.77256203431387149,
2889    0.32093113572510412, -0.024748143906698106]]], [[[-0.81065249686006191, 0.85744411886085925, -0.6926225063339142],
2890    [0.1359015377696986, 0.16676992366466048, -0.25508688732693452], [0.51534906080188891, -0.51302456371614524,
2891    -0.13403185580745269], [-0.83972439581808334, 0.43981616780551591, 0.32672995034070751], [0.65639618069998873,
2892    -0.89753193640920048, 0.85900236622478832], [0.38497532723462147, 0.83291046269513536, -0.80651708700513747]],
2893    [[-0.51373944818354556, -0.72195574816716812, 0.90186186159805426], [-0.56332521605329755, 0.49732930230749539,
2894    0.1484166126253168], [-0.72917908882955729, -0.95729599166703117, 0.72755275645534057], [0.4921919188713737,
2895    -0.96432237192190851, -0.036083259295467185], [0.1723714120524098, 0.040941543603711272, 0.62521746283269097],
2896    [-0.1690314543596303, 0.47940137593575449, 0.42640711858738989]]], [[[0.10390397381997918, -0.24977943617300435,
2897    -0.98869850717150864], [-0.96639652829702083, 0.35034662237955816, -0.56248828327408051], [0.96408180547845057,
2898    -0.23999573384656303, -0.81951160331181905], [-0.47170906450449324, 0.6419551236751726, -0.48542637867915861],
2899    [0.70176197798886486, 0.96442202464370985, 0.83401799166885082], [0.79732376621020729, 0.70856863055292596,
2900    -0.28971110032777569]], [[-0.44536694566283019, 0.53490318645652013, -0.040524017414241387], [0.8017156672864223,
2901    -0.035466342245163318, 0.14641512106385846], [0.38200951751843482, 0.55381128552992576, 0.62196907345612029],
2902    [-0.59415983609316458, -0.057552239669435235, -0.87044248211447695], [-0.20880226272887281, 0.89867393628607095,
2903    -0.27599039986863305], [0.38668431971946848, 0.77159353796456487, -0.049495448837690637]]]])
2904          ref=transpose(xx,2)          ref=transpose(xx,2)
2905          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2906          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1645  class SymbolicTestCase(unittest.TestCase Line 2910  class SymbolicTestCase(unittest.TestCase
2910          x=Symbol('x', shape)          x=Symbol('x', shape)
2911          y=transpose(x,3)          y=transpose(x,3)
2912          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2913          xx=numpy.array([[[[-0.83238397427219324, -0.80304945166676078, 0.2854233137814719]], [[-0.91700546179705711, -0.22967008232906316, -0.60376458756856954]], [[0.07087208457013805, 0.23117593172042072, -0.12667944419566446]], [[-0.27200565347308125, 0.31727021914865827, 0.40540640410723383]], [[-0.53708975045053231, 0.91228973325189755, 0.72515582140538837]]], [[[-0.61931193506441096, 0.7057311962617685, 0.2507426651584741]], [[0.17997388476323595, 0.60139517535377163, -0.99877115073110456]], [[0.016442022227512787, 0.061371032402413483, 0.14647605667883545]], [[-0.92003654886571784, 0.93042703193588072, -0.50427650232776866]], [[0.8567830545963715, -0.70882639028041727, 0.47142817123861858]]], [[[-0.79629613633692742, 0.13970958592350069, 0.66198023787987537]], [[-0.15629334358873193, 0.67125849304731378, -0.92132493615015476]], [[-0.41171369866982177, -0.67940087016833228, 0.84573809886934348]], [[-0.78634627557816228, -0.6648718173586603, 0.21803065010397238]], [[0.37245027723075919, 0.29269247650633523, -0.0530539286124041]]], [[[-0.42592013319073696, -0.54209531077082307, -0.48001439083151332]], [[-0.60430944008617171, -0.037657491348902949, 0.24493847028405114]], [[0.62609446119907131, -0.07190756457311509, -0.45046379127096903]], [[0.81443692227546949, -0.7066437837821713, 0.35296959921526638]], [[-0.58194723647967472, 0.85647238833506845, 0.81985576259105364]]]])          xx=numpy.array([[[[-0.83238397427219324, -0.80304945166676078, 0.2854233137814719]], [[-0.91700546179705711,
2914    -0.22967008232906316, -0.60376458756856954]], [[0.07087208457013805, 0.23117593172042072, -0.12667944419566446]],
2915    [[-0.27200565347308125, 0.31727021914865827, 0.40540640410723383]], [[-0.53708975045053231, 0.91228973325189755,
2916    0.72515582140538837]]], [[[-0.61931193506441096, 0.7057311962617685, 0.2507426651584741]], [[0.17997388476323595,
2917    0.60139517535377163, -0.99877115073110456]], [[0.016442022227512787, 0.061371032402413483, 0.14647605667883545]],
2918    [[-0.92003654886571784, 0.93042703193588072, -0.50427650232776866]], [[0.8567830545963715, -0.70882639028041727,
2919    0.47142817123861858]]], [[[-0.79629613633692742, 0.13970958592350069, 0.66198023787987537]], [[-0.15629334358873193,
2920    0.67125849304731378, -0.92132493615015476]], [[-0.41171369866982177, -0.67940087016833228, 0.84573809886934348]],
2921    [[-0.78634627557816228, -0.6648718173586603, 0.21803065010397238]], [[0.37245027723075919, 0.29269247650633523,
2922    -0.0530539286124041]]], [[[-0.42592013319073696, -0.54209531077082307, -0.48001439083151332]], [[-0.60430944008617171,
2923    -0.037657491348902949, 0.24493847028405114]], [[0.62609446119907131, -0.07190756457311509, -0.45046379127096903]],
2924    [[0.81443692227546949, -0.7066437837821713, 0.35296959921526638]], [[-0.58194723647967472, 0.85647238833506845,
2925    0.81985576259105364]]]])
2926          ref=transpose(xx,3)          ref=transpose(xx,3)
2927          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
2928          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1655  class SymbolicTestCase(unittest.TestCase Line 2932  class SymbolicTestCase(unittest.TestCase
2932          x=Symbol('x', shape)          x=Symbol('x', shape)
2933          y=transpose(x,4)          y=transpose(x,4)
2934          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
2935          xx=numpy.array([[[[0.33229462774359297, 0.90247279128446456, 0.50592066073757391, 0.060785036392947633, 0.42887145358406364], [-0.907257269597191, 0.52593749893545261, 0.15806565139728712, 0.4014828795632972, 0.98069834651678889], [0.78648392989100535, -0.44370613604769593, -0.72850353165390147, -0.41298403201285483, 0.025500239778559974], [0.78312787656340843, 0.46791222498024743, 0.95311416319375231, -0.19391900054967337, -0.63841532569780779]], [[0.055027042647902036, 0.64399634269251083, 0.043106313163026266, -0.42193734992166587, -0.092307643484398794], [0.10064133409920628, 0.99940644225073805, -0.089336766142547264, -0.061535743483655203, -0.087024495000410651], [0.62741569832910571, -0.13599676515695536, 0.60970511662460902, 0.35050057112562061, -0.97838088249442912], [-0.39701550275339881, -0.94985980809765569, -0.94899518147143125, 0.19270095654119879, 0.055309394501884768]], [[0.048051840217318231, -0.51611293546959436, -0.40344898509551674, 0.17995256572278184, 0.75323171075063233], [-0.99737547946521543, -0.32300767971023481, 0.77295013504894339, 0.085248835129112743, -0.79439340442316086], [0.28222606480472634, -0.69527230454542521, -0.983488098301734, 0.86535616608678056, 0.41114575238879292], [-0.74078317645750813, -0.97945625176002649, -0.12625344089155188, -0.18298243111472701, -0.58222353017599215]], [[-0.0073724431427701909, 0.23504978886316708, -0.83090125959908101, 0.66530051906939836, 0.70266107220036167], [0.093890127834725723, 0.95900150757180191, 0.51197073529543435, -0.78425850996472746, -0.94470603565335387], [-0.071388551913005971, -0.47544393822466469, -0.068033180782151481, -0.21648824917734188, -0.48983248930826551], [-0.2890450213375646, 0.18194665582133607, 0.02109813507365943, -0.016889345412850698, 0.23762415001400372]], [[-0.87281897425177246, -0.96798831153907439, 0.98829641983199701, 0.36852869737264848, 0.030443638702282838], [0.70009727153104762, 0.30750607403016739, -0.067944927837938707, 0.50497652483500488, 0.74142142074795814], [0.94524474872090281, 0.61664148567473354, 0.30011498538454373, -0.18702691685130746, 0.67586267221196716], [-0.15715611674830132, -0.2664838239013203, 0.53499529703408633, 0.68966212533316895, 0.31706456142302786]], [[-0.61361056925887447, 0.2651271574376759, -0.058034816405870826, 0.026096774527163191, 0.86449606511668353], [0.66167065604121955, -0.76850782791683336, -0.31082833544595068, 0.10214720450989412, -0.13996060580137493], [0.81897939427689592, 0.98054333564702012, 0.64032021643575998, 0.0095206241554930404, -0.50399470919082723], [0.90867727408752286, 0.22213931062196868, 0.95267282274457266, 0.86263400660543099, 0.7519551789241945]]], [[[0.38191401430698102, 0.37730075198834445, -0.79991143368809481, -0.49974624670391177, 0.066369343448481777], [-0.91707771405962335, 0.59062252835510964, 0.82758172000123942, 0.32449099313834506, -0.81055151761968358], [0.44989031480621278, -0.54521499045113608, -0.53121692022940681, 0.24072105071115835, -0.12817241596903073], [0.13904976457703833, 0.030046961917888471, 0.70753775663615404, -0.60469897584877352, -0.12383354192837315]], [[-0.17727864548962713, -0.29320776189295783, -0.33076432225775898, 0.28775293953035663, 0.070466399800353852], [-0.94538163707919876, -0.59277722582268999, -0.93478437032776429, 0.54592562272539324, -0.61030865305945481], [-0.78174718345966432, 0.053898699368549963, 0.26068252952423698, 0.02860510133045624, 0.53860692587466485], [-0.1677595962509808, 0.84891644487260676, 0.25757512667578952, 0.010676947915794655, -0.38341410260612996]], [[-0.21063887494948252, 0.17940535968361693, 0.010336624497043534, -0.36892140792062067, -0.60349140836207993], [0.94352144795039594, 0.90594742886621549, -0.032237236043826556, -0.72815081506583357, -0.50488589347928992], [-0.044996589584375801, -0.54777479364307013, -0.25880117240478318, 0.092166950955798077, -0.74453035849522009], [-0.0021105882174756729, 0.92030237977249985, 0.48667071082933555, -0.71770449050514529, 0.20374645355617482]], [[-0.32968158110806312, -0.15882891043306024, -0.98973554045080636, -0.46311489579039278, -0.28189430873894583], [0.9462604680209814, 0.92990752172800017, 0.53141975729159108, 0.80570831962889522, 0.80396606987612818], [-0.20932447128280707, 0.055029256719247854, -0.96667008775210883, 0.46228702000070787, 0.6804861239115374], [-0.68254922808630791, -0.22923051538212302, -0.37598228292009517, 0.01642607444030153, -0.48762298517017322]], [[-0.73601485167433878, -0.086222233111941549, -0.25490018975133566, 0.59236131424013672, 0.97329818123254719], [0.036033089069700042, 0.12180976819687284, 0.37160256484045684, -0.70025744765373799, -0.78626985060205223], [0.14244157766668519, 0.35013755700794147, -0.42932738749017552, -0.95409618877765179, 0.62460606190112], [0.42470339031954674, 0.11776945347732748, 0.97030071735149681, -0.030508385181680531, 0.2341359040188209]], [[-0.93019751564333197, -0.45361092731092323, -0.19723516978348754, 0.11582714865699772, -0.70071075045657172], [-0.574365934807338, -0.58283445893977137, 0.85997922228632362, 0.6777778161939656, 0.57937573444265911], [-0.29846108057039755, -0.95162324677220944, -0.9197625947297654, 0.78405565495850182, -0.55548401533165159], [-0.52864799493321701, -0.18196487033621067, -0.90739419753799266, -0.37273831977874727, -0.94605963276711336]]], [[[0.48867050622665253, 0.50121200272268362, -0.11522914048382393, 0.40787887450728166, -0.047539751893834525], [0.46759103431805826, 0.28114873662918072, -0.17744521938483748, 0.58822856341940177, -0.38153988957565566], [-0.44061179634452663, -0.97565902758452139, 0.45256693803279813, 0.35926683335150811, -0.21176594268102877], [0.92085622317262916, -0.11550419843494253, -0.96096571736481673, -0.77038222079052243, -0.78634403588930968]], [[-0.64191213335186137, 0.0012017391400909183, 0.31513898199573154, -0.08724292833766234, 0.69241486856808221], [0.99597325069704978, 0.49476384913356641, 0.42693038367571745, 0.50553024031512317, 0.025567401569908332], [-0.014350826868655853, 0.06809959353037498, -0.94297390373874101, -0.22267232157528749, -0.50795581870192175], [0.47382389590740637, 0.095664306022194889, 0.89734507254336293, 0.006974189965401667, 0.15898671363577122]], [[0.69901858702680331, -0.18710464818378902, 0.96414709435312784, -0.41086102283106962, 0.53578954843965398], [-0.98270251036616241, -0.80015058555456253, 0.25054328458308972, -0.16571504695518979, 0.58952623827739048], [-0.43057416854909114, 0.92712034950679234, -0.0069512131742137662, -0.70334861768288848, -0.02654826105951491], [0.92741698205395462, 0.92240331651669449, -0.94369884276001037, -0.71376796410123156, -0.27929588390311211]], [[0.8272907790057249, -0.10993839660087423, 0.96961173322751715, 0.36192353096889596, -0.70514828393138296], [-0.61215992865588342, 0.375812873280017, 0.15828578451417141, -0.34315695877440189, -0.066783092137497224], [-0.22753764985447877, -0.0064898197588376672, 0.5847156917989782, 0.4630485492203853, -0.22693788606996823], [-0.70770906782317744, 0.067426433242679717, -0.0088942713036097576, -0.42422727266183835, -0.61539593803778936]], [[-0.74120217114854592, 0.066393910745510931, -0.73166587465353961, -0.025741071124232073, -0.30193486264924707], [0.22982289274604351, 0.055835313713102241, 0.34815861007438209, -0.74389621152296437, 0.0077697667670584281], [-0.21763783415548121, -0.53681100602365928, 0.73158981322736794, -0.82545419131046871, 0.173428993559126], [0.68555782326953962, -0.7475989526480995, -0.40053248998810997, -0.68343194660083739, 0.19963556636740898]], [[-0.3497760449808982, -0.1566899029471458, -0.34378168284104782, 0.9016146890123149, 0.55751379359429087], [-0.0790899710491757, -0.54746513804520935, -0.89109379870634475, -0.93370678186121547, 0.08942389999118161], [0.44361763785236397, -0.68300690757588245, 0.73919581973812498, 0.64529392753214432, -0.55324878497848751], [-0.969086352230907, -0.09773940808175019, 0.023440100726240143, 0.10655036124361694, 0.62932270875795182]]]])          xx=numpy.array([[[[0.33229462774359297, 0.90247279128446456, 0.50592066073757391, 0.060785036392947633,
2936    0.42887145358406364], [-0.907257269597191, 0.52593749893545261, 0.15806565139728712, 0.4014828795632972, 0.98069834651678889],
2937    [0.78648392989100535, -0.44370613604769593, -0.72850353165390147, -0.41298403201285483, 0.025500239778559974],
2938    [0.78312787656340843, 0.46791222498024743, 0.95311416319375231, -0.19391900054967337, -0.63841532569780779]],
2939    [[0.055027042647902036, 0.64399634269251083, 0.043106313163026266, -0.42193734992166587, -0.092307643484398794],
2940    [0.10064133409920628, 0.99940644225073805, -0.089336766142547264, -0.061535743483655203, -0.087024495000410651],
2941    [0.62741569832910571, -0.13599676515695536, 0.60970511662460902, 0.35050057112562061, -0.97838088249442912],
2942    [-0.39701550275339881, -0.94985980809765569, -0.94899518147143125, 0.19270095654119879, 0.055309394501884768]],
2943    [[0.048051840217318231, -0.51611293546959436, -0.40344898509551674, 0.17995256572278184, 0.75323171075063233],
2944    [-0.99737547946521543, -0.32300767971023481, 0.77295013504894339, 0.085248835129112743, -0.79439340442316086],
2945    [0.28222606480472634, -0.69527230454542521, -0.983488098301734, 0.86535616608678056, 0.41114575238879292],
2946    [-0.74078317645750813, -0.97945625176002649, -0.12625344089155188, -0.18298243111472701, -0.58222353017599215]],
2947    [[-0.0073724431427701909, 0.23504978886316708, -0.83090125959908101, 0.66530051906939836, 0.70266107220036167],
2948    [0.093890127834725723, 0.95900150757180191, 0.51197073529543435, -0.78425850996472746, -0.94470603565335387],
2949    [-0.071388551913005971, -0.47544393822466469, -0.068033180782151481, -0.21648824917734188, -0.48983248930826551],
2950    [-0.2890450213375646, 0.18194665582133607, 0.02109813507365943, -0.016889345412850698, 0.23762415001400372]],
2951    [[-0.87281897425177246, -0.96798831153907439, 0.98829641983199701, 0.36852869737264848, 0.030443638702282838],
2952    [0.70009727153104762, 0.30750607403016739, -0.067944927837938707, 0.50497652483500488, 0.74142142074795814],
2953    [0.94524474872090281, 0.61664148567473354, 0.30011498538454373, -0.18702691685130746, 0.67586267221196716],
2954    [-0.15715611674830132, -0.2664838239013203, 0.53499529703408633, 0.68966212533316895, 0.31706456142302786]],
2955    [[-0.61361056925887447, 0.2651271574376759, -0.058034816405870826, 0.026096774527163191, 0.86449606511668353],
2956    [0.66167065604121955, -0.76850782791683336, -0.31082833544595068, 0.10214720450989412, -0.13996060580137493],
2957    [0.81897939427689592, 0.98054333564702012, 0.64032021643575998, 0.0095206241554930404, -0.50399470919082723],
2958    [0.90867727408752286, 0.22213931062196868, 0.95267282274457266, 0.86263400660543099, 0.7519551789241945]]],
2959    [[[0.38191401430698102, 0.37730075198834445, -0.79991143368809481, -0.49974624670391177, 0.066369343448481777],
2960    [-0.91707771405962335, 0.59062252835510964, 0.82758172000123942, 0.32449099313834506, -0.81055151761968358],
2961    [0.44989031480621278, -0.54521499045113608, -0.53121692022940681, 0.24072105071115835, -0.12817241596903073],
2962    [0.13904976457703833, 0.030046961917888471, 0.70753775663615404, -0.60469897584877352, -0.12383354192837315]],
2963    [[-0.17727864548962713, -0.29320776189295783, -0.33076432225775898, 0.28775293953035663, 0.070466399800353852],
2964    [-0.94538163707919876, -0.59277722582268999, -0.93478437032776429, 0.54592562272539324, -0.61030865305945481],
2965    [-0.78174718345966432, 0.053898699368549963, 0.26068252952423698, 0.02860510133045624, 0.53860692587466485],
2966    [-0.1677595962509808, 0.84891644487260676, 0.25757512667578952, 0.010676947915794655, -0.38341410260612996]],
2967    [[-0.21063887494948252, 0.17940535968361693, 0.010336624497043534, -0.36892140792062067, -0.60349140836207993],
2968    [0.94352144795039594, 0.90594742886621549, -0.032237236043826556, -0.72815081506583357, -0.50488589347928992],
2969    [-0.044996589584375801, -0.54777479364307013, -0.25880117240478318, 0.092166950955798077, -0.74453035849522009],
2970    [-0.0021105882174756729, 0.92030237977249985, 0.48667071082933555, -0.71770449050514529, 0.20374645355617482]],
2971    [[-0.32968158110806312, -0.15882891043306024, -0.98973554045080636, -0.46311489579039278, -0.28189430873894583],
2972    [0.9462604680209814, 0.92990752172800017, 0.53141975729159108, 0.80570831962889522, 0.80396606987612818],
2973    [-0.20932447128280707, 0.055029256719247854, -0.96667008775210883, 0.46228702000070787, 0.6804861239115374],
2974    [-0.68254922808630791, -0.22923051538212302, -0.37598228292009517, 0.01642607444030153, -0.48762298517017322]],
2975    [[-0.73601485167433878, -0.086222233111941549, -0.25490018975133566, 0.59236131424013672, 0.97329818123254719],
2976    [0.036033089069700042, 0.12180976819687284, 0.37160256484045684, -0.70025744765373799, -0.78626985060205223],
2977    [0.14244157766668519, 0.35013755700794147, -0.42932738749017552, -0.95409618877765179, 0.62460606190112], [0.42470339031954674,
2978    0.11776945347732748, 0.97030071735149681, -0.030508385181680531, 0.2341359040188209]], [[-0.93019751564333197,
2979    -0.45361092731092323, -0.19723516978348754, 0.11582714865699772, -0.70071075045657172], [-0.574365934807338,
2980    -0.58283445893977137, 0.85997922228632362, 0.6777778161939656, 0.57937573444265911], [-0.29846108057039755,
2981    -0.95162324677220944, -0.9197625947297654, 0.78405565495850182, -0.55548401533165159], [-0.52864799493321701,
2982    -0.18196487033621067, -0.90739419753799266, -0.37273831977874727, -0.94605963276711336]]], [[[0.48867050622665253,
2983    0.50121200272268362, -0.11522914048382393, 0.40787887450728166, -0.047539751893834525], [0.46759103431805826,
2984    0.28114873662918072, -0.17744521938483748, 0.58822856341940177, -0.38153988957565566], [-0.44061179634452663,
2985    -0.97565902758452139, 0.45256693803279813, 0.35926683335150811, -0.21176594268102877], [0.92085622317262916,
2986    -0.11550419843494253, -0.96096571736481673, -0.77038222079052243, -0.78634403588930968]], [[-0.64191213335186137,
2987    0.0012017391400909183, 0.31513898199573154, -0.08724292833766234, 0.69241486856808221], [0.99597325069704978,
2988    0.49476384913356641, 0.42693038367571745, 0.50553024031512317, 0.025567401569908332], [-0.014350826868655853,
2989    0.06809959353037498, -0.94297390373874101, -0.22267232157528749, -0.50795581870192175], [0.47382389590740637,
2990    0.095664306022194889, 0.89734507254336293, 0.006974189965401667, 0.15898671363577122]], [[0.69901858702680331,
2991    -0.18710464818378902, 0.96414709435312784, -0.41086102283106962, 0.53578954843965398], [-0.98270251036616241,
2992    -0.80015058555456253, 0.25054328458308972, -0.16571504695518979, 0.58952623827739048], [-0.43057416854909114,
2993    0.92712034950679234, -0.0069512131742137662, -0.70334861768288848, -0.02654826105951491], [0.92741698205395462,
2994    0.92240331651669449, -0.94369884276001037, -0.71376796410123156, -0.27929588390311211]], [[0.8272907790057249,
2995    -0.10993839660087423, 0.96961173322751715, 0.36192353096889596, -0.70514828393138296], [-0.61215992865588342,
2996    0.375812873280017, 0.15828578451417141, -0.34315695877440189, -0.066783092137497224], [-0.22753764985447877,
2997    -0.0064898197588376672, 0.5847156917989782, 0.4630485492203853, -0.22693788606996823], [-0.70770906782317744,
2998    0.067426433242679717, -0.0088942713036097576, -0.42422727266183835, -0.61539593803778936]], [[-0.74120217114854592,
2999    0.066393910745510931, -0.73166587465353961, -0.025741071124232073, -0.30193486264924707], [0.22982289274604351,
3000    0.055835313713102241, 0.34815861007438209, -0.74389621152296437, 0.0077697667670584281], [-0.21763783415548121,
3001    -0.53681100602365928, 0.73158981322736794, -0.82545419131046871, 0.173428993559126], [0.68555782326953962, -0.7475989526480995,
3002    -0.40053248998810997, -0.68343194660083739, 0.19963556636740898]], [[-0.3497760449808982, -0.1566899029471458,
3003    -0.34378168284104782, 0.9016146890123149, 0.55751379359429087], [-0.0790899710491757, -0.54746513804520935,
3004    -0.89109379870634475, -0.93370678186121547, 0.08942389999118161], [0.44361763785236397, -0.68300690757588245,
3005    0.73919581973812498, 0.64529392753214432, -0.55324878497848751], [-0.969086352230907, -0.09773940808175019,
3006    0.023440100726240143, 0.10655036124361694, 0.62932270875795182]]]])
3007          ref=transpose(xx,4)          ref=transpose(xx,4)
3008          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
3009          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1686  class SymbolicTestCase(unittest.TestCase Line 3034  class SymbolicTestCase(unittest.TestCase
3034          x=Symbol('x', shape)          x=Symbol('x', shape)
3035          y=trace(x,1)          y=trace(x,1)
3036          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
3037          xx=numpy.array([[[-0.30432006371619469, -0.22905338913674456, 0.42351956170977667], [0.35214002575912429, 0.88921105503504827, -0.42739439460751671], [0.82999770972542053, -0.24368152054346126, 0.76327903699750377]], [[-0.27689661683308042, -0.47821019640402174, 0.050972678260606807], [0.3188234216192698, 0.40086532317431378, -0.77800871533307103], [-0.18065414138947311, -0.69993699005811294, -0.34667089306001908]], [[0.99684849266554032, -0.26053787631755632, 0.95412756688176081], [0.59498862532584784, -0.69512502548550681, -0.064097498492544203], [-0.13649401503153857, -0.21781863588425487, -0.048509177218103883]], [[-0.39222703275865856, -0.93666463077435935, 0.06728383106782565], [-0.97258445996510789, 0.010034442276707356, -0.90229604923295037], [0.69358418855440673, -0.53650098576171312, -0.50681953935116653]]])          xx=numpy.array([[[-0.30432006371619469, -0.22905338913674456, 0.42351956170977667], [0.35214002575912429,
3038    0.88921105503504827, -0.42739439460751671], [0.82999770972542053, -0.24368152054346126, 0.76327903699750377]],
3039    [[-0.27689661683308042, -0.47821019640402174, 0.050972678260606807], [0.3188234216192698, 0.40086532317431378,
3040    -0.77800871533307103], [-0.18065414138947311, -0.69993699005811294, -0.34667089306001908]], [[0.99684849266554032,
3041    -0.26053787631755632, 0.95412756688176081], [0.59498862532584784, -0.69512502548550681, -0.064097498492544203],
3042    [-0.13649401503153857, -0.21781863588425487, -0.048509177218103883]], [[-0.39222703275865856, -0.93666463077435935,
3043    0.06728383106782565], [-0.97258445996510789, 0.010034442276707356, -0.90229604923295037], [0.69358418855440673,
3044    -0.53650098576171312, -0.50681953935116653]]])
3045          ref=trace(xx,1)          ref=trace(xx,1)
3046          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
3047          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1696  class SymbolicTestCase(unittest.TestCase Line 3051  class SymbolicTestCase(unittest.TestCase
3051          x=Symbol('x', shape)          x=Symbol('x', shape)
3052          y=trace(x,0)          y=trace(x,0)
3053          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
3054          xx=numpy.array([[[[-0.3694750359037331, 0.71358743964939397], [-0.093742282652185427, 0.50896359122836432]], [[0.85347316428928743, 0.49118560683579515], [-0.25941831681141836, -0.4320010783967263]], [[-0.2760108419751206, 0.66793883720063874], [0.46227421258471102, -0.72413722178984985]], [[-0.74883130435508782, 0.070076073887716417], [0.64130431490622786, -0.98394733537310208]], [[-0.95412264969001881, -0.51566417255248354], [-0.16307641236026793, 0.98363829896164612]], [[0.88586020150573708, -0.3397016558961703], [-0.57491311360772857, -0.78690905828319946]]], [[[0.39836393700999206, -0.63270208738135136], [-0.2959641344970767, 0.1331199240600347]], [[0.051134315403124964, 0.63834753921918486], [0.94123408446203127, 0.63148116557776945]], [[0.38719619871015465, 0.63773576445595159], [-0.15000442219899179, -0.96078834001896318]], [[-0.56830030967894141, 0.74951162375423319], [0.8395447319472884, -0.14752461139071049]], [[0.17528853308372816, -0.53219338427670637], [0.048377969228808881, 0.14990742625452413]], [[0.053265153324379755, 0.92122213425272759], [0.83732746437009009, 0.43814166275704092]]], [[[0.81171997323018741, 0.050189284623568087], [0.64368659625527402, -0.031103407826538421]], [[-0.89197465872384885, 0.50337420157698687], [0.95355395692917422, -0.50173533160056949]], [[0.2227005087016205, 0.84604906711247607], [0.74404874157118295, -0.31652247299227598]], [[0.20936533302820881, -0.47981411883936986], [-0.79812429019827413, -0.85006412570612411]], [[-0.34835305494224622, -0.28092858143638266], [-0.67836053479335412, -0.47092592927447807]], [[-0.4762265854343517, 0.81066118213106519], [-0.52882160024668434, 0.23628622262664289]]], [[[-0.57714452658067983, -0.94459848277577452], [-0.22672215011737284, 0.75032447956233628]], [[0.60122975251361677, -0.34985235574140461], [0.058731385889433385, 0.15621376590694092]], [[-0.73200655163930595, 0.21280839946856744], [0.81080911750417894, 0.69177135210443019]], [[0.32599640139949404, 0.66077480225915508], [-0.13983375872693049, 0.22753385790507874]], [[-0.8682379214958087, -0.94723615876099809], [-0.87056385033891615, -0.33792034125295589]], [[-0.86656851371244348, -0.34621403404401452], [0.40223101468808031, -0.47519853367365861]]], [[[0.63748179252209658, -0.5832056708017519], [0.90776206571008866, -0.43989465495579316]], [[-0.016474025722121866, 0.02187634681734707], [0.51992814008881871, 0.10846874003557327]], [[0.25254642503400238, 0.081802611693857274], [-0.55153027830967716, 0.3166821429560871]], [[-0.36703105520601986, 0.35544509617061326], [0.70282199240315446, -0.2300975445344966]], [[0.68435837894355567, 0.25451709779959808], [0.21240874629983164, 0.21352558990199499]], [[0.31146533234807361, 0.3408700862763987], [-0.504329395303029, -0.89868721112966266]]], [[[0.97319504931670986, 0.56038442308741265], [-0.98093512597846488, 0.86123144490484749]], [[-0.33044930087386093, 0.63303634393803776], [0.50876715774738623, -0.42559630596165055]], [[0.131034837386522, -0.60521301245014536], [0.74470564639832104, 0.24450946961218123]], [[-0.91043823411503166, 0.077426268565379486], [-0.60978162133764302, 0.96395292244762465]], [[-0.85800175044000815, 0.95347198454173121], [0.97624761215874734, 0.52351282878229899]], [[0.38893272392032885, 0.78013022187631176], [0.48928755294691362, 0.018595406529023917]]]])          xx=numpy.array([[[[-0.3694750359037331, 0.71358743964939397], [-0.093742282652185427, 0.50896359122836432]],
3055    [[0.85347316428928743, 0.49118560683579515], [-0.25941831681141836, -0.4320010783967263]], [[-0.2760108419751206,
3056    0.66793883720063874], [0.46227421258471102, -0.72413722178984985]], [[-0.74883130435508782, 0.070076073887716417],
3057    [0.64130431490622786, -0.98394733537310208]], [[-0.95412264969001881, -0.51566417255248354], [-0.16307641236026793,
3058    0.98363829896164612]], [[0.88586020150573708, -0.3397016558961703], [-0.57491311360772857, -0.78690905828319946]]],
3059    [[[0.39836393700999206, -0.63270208738135136], [-0.2959641344970767, 0.1331199240600347]], [[0.051134315403124964,
3060    0.63834753921918486], [0.94123408446203127, 0.63148116557776945]], [[0.38719619871015465, 0.63773576445595159],
3061    [-0.15000442219899179, -0.96078834001896318]], [[-0.56830030967894141, 0.74951162375423319], [0.8395447319472884,
3062    -0.14752461139071049]], [[0.17528853308372816, -0.53219338427670637], [0.048377969228808881, 0.14990742625452413]],
3063    [[0.053265153324379755, 0.92122213425272759], [0.83732746437009009, 0.43814166275704092]]], [[[0.81171997323018741,
3064    0.050189284623568087], [0.64368659625527402, -0.031103407826538421]], [[-0.89197465872384885, 0.50337420157698687],
3065    [0.95355395692917422, -0.50173533160056949]], [[0.2227005087016205, 0.84604906711247607], [0.74404874157118295,
3066    -0.31652247299227598]], [[0.20936533302820881, -0.47981411883936986], [-0.79812429019827413, -0.85006412570612411]],
3067    [[-0.34835305494224622, -0.28092858143638266], [-0.67836053479335412, -0.47092592927447807]], [[-0.4762265854343517,
3068    0.81066118213106519], [-0.52882160024668434, 0.23628622262664289]]], [[[-0.57714452658067983, -0.94459848277577452],
3069    [-0.22672215011737284, 0.75032447956233628]], [[0.60122975251361677, -0.34985235574140461], [0.058731385889433385,
3070    0.15621376590694092]], [[-0.73200655163930595, 0.21280839946856744], [0.81080911750417894, 0.69177135210443019]],
3071    [[0.32599640139949404, 0.66077480225915508], [-0.13983375872693049, 0.22753385790507874]], [[-0.8682379214958087,
3072    -0.94723615876099809], [-0.87056385033891615, -0.33792034125295589]], [[-0.86656851371244348, -0.34621403404401452],
3073    [0.40223101468808031, -0.47519853367365861]]], [[[0.63748179252209658, -0.5832056708017519], [0.90776206571008866,
3074    -0.43989465495579316]], [[-0.016474025722121866, 0.02187634681734707], [0.51992814008881871, 0.10846874003557327]],
3075    [[0.25254642503400238, 0.081802611693857274], [-0.55153027830967716, 0.3166821429560871]], [[-0.36703105520601986,
3076    0.35544509617061326], [0.70282199240315446, -0.2300975445344966]], [[0.68435837894355567, 0.25451709779959808],
3077    [0.21240874629983164, 0.21352558990199499]], [[0.31146533234807361, 0.3408700862763987], [-0.504329395303029,
3078    -0.89868721112966266]]], [[[0.97319504931670986, 0.56038442308741265], [-0.98093512597846488, 0.86123144490484749]],
3079    [[-0.33044930087386093, 0.63303634393803776], [0.50876715774738623, -0.42559630596165055]], [[0.131034837386522,
3080    -0.60521301245014536], [0.74470564639832104, 0.24450946961218123]], [[-0.91043823411503166, 0.077426268565379486],
3081    [-0.60978162133764302, 0.96395292244762465]], [[-0.85800175044000815, 0.95347198454173121], [0.97624761215874734,
3082    0.52351282878229899]], [[0.38893272392032885, 0.78013022187631176], [0.48928755294691362, 0.018595406529023917]]]])
3083          ref=trace(xx,0)          ref=trace(xx,0)
3084          res=Evaluator(y)(x=xx)          res=Evaluator(y)(x=xx)
3085          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")          self.assertAlmostEqual(Lsup(res-ref), 0.0, self.TOL_DIGITS, "wrong result")
# Line 1706  class SymbolicTestCase(unittest.TestCase Line 3089  class SymbolicTestCase(unittest.TestCase
3089          x=Symbol('x', shape)          x=Symbol('x', shape)
3090          y=trace(x,1)          y=trace(x,1)
3091          self.assertTrue(isinstance(y, Symbol), "wrong type of result")          self.assertTrue(isinstance(y, Symbol), "wrong type of result")
3092          xx=numpy.array([[[[0.12378126686132851, 0.29155430683608241, 0.86271434614578979, -0.11742093960687883], [0.3096490754214456, 0.98424686084231072, 0.047682319007110952, 0.11037750647267308], [0.80979559930294309, -0.55558374103286456, 0.30562481889393234, -0.060107448876047798], [0.32137687306255303, 0.11409107193014689, 0.68863630213987848, -0.162339956706401], [-0.39678271595530479, 0.30823105783625726, 0.12481730156956949, -0.65655838356788188]], [[0.37190278270105592, 0.78087211009681878, -0.5712115602293879, -0.65678410030306233], [0.85257932570352102, -0.31908654965102068, 0.63411344983405282, -0.07680893575290515], [0.58099397171973477, -0.71698105785074984, -0.24354660896668157, 0.054323298860495139], [0.68519067831836811, -0.51251533167560348, 0.62512754825557981, 0.50202928337687514], [0.79097760009172324, 0.36549819541627904, -0.35203980568116777, 0.20959919307404018]], [[-0.81855419336037771, 0.03743773635384362, 0.77393976718134372, 0.17800308193249093], [0.9013417133178967, 0.97515203300010778, 0.92165156323643171, -0.27478200800050034], [-0.48006943841831262, -0.27726682525385704, 0.95102150281345432, 0.14269614427468058], [-0.53685584840593581, -0.19315649116132594, 0.93091078259406013, -0.63208654722143365], [-0.91336292112565109, 0.39960911985000824, 0.62774042665873453, -0.4427910366440122]], [[0.96824982888547328, -0.76501446377948046, -0.084497317308873887, 0.35032191290416548], [0.45443874475115043, -0.67614747915686824, 0.35805507604279252, -0.65059154003009678], [-0.41981881920489528, 0.64465722182163154, -0.45026362107301221, 0.66400052134070697], [-0.77864604744808918, 0.71753354687874582, -0.12511081275772229, 0.44152114585158397], [0.64615286685206974, 0.081113596793409126, -0.65488336674976022, 0.1023686069245946]], [[0.66379766906805271, 0.17680814597757299, 0.23909690168058795, 0.62590288468658084], [-0.25037965360293613, -0.36319608732506903, 0.69856637614502426, 0.4975322249035723], [-0.049546003812601214, 0.38249739847050179, 0.79461708872500747, 0.62941103922900377], [0.21893696910986726, -0.56594695446454857, -0.18451669262766912, 0.21622622136160619], [0.96117830325624687, -0.40565786959688022, -0.96361376264333809, -0.053661942793668427]]], [[[-0.4143734903349654, 0.015399175391612063, 0.03832389528949709, -0.02385534187482885], [0.39815239331466024, -0.32861245029375752, 0.54439771480435373, 0.22421570472444685], [-0.82140951647577398, -0.4962265612251815, 0.032276579168338593, -0.49920067177959715], [0.45421036728853426, 0.48205242543613158, -0.38468060784405789, -0.14689287020958464], [0.3801524842284878, 0.98958020513308442, -0.43475282256103931, 0.53216608336887194]], [[0.57932442496651171, 0.29630529144309459, 0.38848702703468097, -0.97610661839641688], [0.019511053194284367, 0.087635528798853057, -0.11436457458590699, 0.89227169675701457], [0.45163471627961216, 0.66436067041036351, 0.12395604030213492, 0.67045108762381167], [0.68795232894921332, -0.71406167213591476, 0.61953408439302238, 0.36251154108701789], [0.93441188109710827, 0.43556955049545421, 0.64070329546365312, 0.65383091190779585]], [[-0.7016324464114323, 0.48505659903570231, -0.62335659611951, -0.82467710141799766], [-0.00042357129587644593, -0.20895930532523566, 0.812423626676406, 0.82611561790288879], [0.48411706244884156, -0.084240741576977918, -0.25716822245247184, 0.62651637027671736], [-0.40943584403797506, -0.031945014291086649, -0.0098778087467032982, 0.91894796215157282], [-0.49086739641756272, 0.1805687025513798, -0.1261966568390942, 0.43189663935468636]], [[-0.3613020149755688, -0.9364911512735099, 0.87409915068366684, -0.88796435875076196], [0.68955547419937058, -0.81471022221303735, 0.43887314869493066, 0.18475746015895744], [-0.97239674671757115, -0.51396510884131552, 0.42370739391811751, -0.57011771919372456], [-0.7598240962451801, 0.92502422612822177, 0.44171920084267935, 0.18702900909141928], [0.85402195042094697, 0.7478630873905423, -0.11755556573379056, 0.34764067266925336]], [[-0.84257914804615286, -0.37674785057143101, -0.67583596409386693, -0.30733938462062049], [0.49784772219676698, -0.87003179461678926, -0.61042075186317679, 0.74471521471017676], [-0.78414158502422859, -0.48804683157127116, 0.57169548435639528, 0.41243380496985704], [0.82238557009799917, -0.72865911005203476, -0.2871712630429426, -0.78757071588335292], [0.85111951836744892, 0.5123591436083319, -0.40010480491793321, 0.22046127662744452]]]])          xx=numpy.array([[[[0.12378126686132851, 0.29155430683608241, 0.86271434614578979, -0.11742093960687883],
3093    [0.3096490754214456, 0.98424686084231072, 0.047682319007110952, 0.11037750647267308], [0.80979559930294309,
3094    -0.55558374103286456, 0.30562481889393234, -0.060107448876047798], [0.32137687306255303, 0.11409107193014689,
3095    0.68863630213987848, -0.162339956706401], [-0.39678271595530479, 0.30823105783625726, 0.12481730156956949,
3096    -0.65655838356788188]], [[0.37190278270105592, 0.78087211009681878, -0.5712115602293879, -0.65678410030306233],
3097    [0.85257932570352102, -0.31908654965102068, 0.63411344983405282, -0.07680893575290515], [0.58099397171973477,
3098    -0.71698105785074984, -0.24354660896668157, 0.054323298860495139], [0.68519067831836811, -0.51251533167560348,
3099    0.62512754825557981, 0.50202928337687514], [0.79097760009172324, 0.36549819541627904, -0.35203980568116777,
3100    0.20959919307404018]], [[-0.81855419336037771, 0.03743773635384362, 0.77393976718134372, 0.17800308193249093],
3101    [0.9013417133178967, 0.97515203300010778, 0.92165156323643171, -0.27478200800050034], [-0.48006943841831262,
3102    -0.27726682525385704, 0.95102150281345432, 0.14269614427468058], [-0.53685584840593581, -0.19315649116132594,
3103    0.93091078259406013, -0.63208654722143365], [-0.91336292112565109, 0.39960911985000824, 0.62774042665873453,
3104    -0.4427910366440122]], [[0.96824982888547328, -0.76501446377948046, -0.084497317308873887, 0.35032191290416548],
3105    [0.45443874475115043, -0.67614747915686824, 0.35805507604279252, -0.65059154003009678], [-0.41981881920489528,
3106    0.64465722182163154, -0.45026362107301221, 0.66400052134070697], [-0.77864604744808918, 0.71753354687874582,
3107    -0.12511081275772229, 0.44152114585158397], [0.64615286685206974, 0.081113596793409126, -0.65488336674976022,
3108    0.1023686069245946]], [[0.66379766906805271, 0.17680814597757299, 0.23909690168058795, 0.62590288468658084],
3109    [-0.25037965360293613, -0.36319608732506903, 0.69856637614502426, 0.4975322249035723], [-0.049546003812601214,
3110    0.38249739847050179, 0.79461708872500747, 0.62941103922900377], [0.21893696910986726, -0.56594695446454857,
3111    -0.18451669262766912, 0.21622622136160619], [0.96117830325624687, -0.40565786959688022, -0.96361376264333809,
3112    -0.053661942793668427]]], [[[-0.4143734903349654, 0.015399175391612063, 0.03832389528949709, -0.02385534187482885],
3113    [0.39815239331466024, -0.32861245029375752, 0.54439771480435373, 0.22421570472444685], [-0.82140951647577398,
3114    -0.4962265612251815, 0.032276579168338593, -0.49920067177959715], [0.45421036728853426, 0.48205242543613158,
3115    -0.38468060784405789, -0.14689287020958464], [0.3801524842284878, 0.98958020513308442, -0.43475282256103931,
3116    0.53216608336887194]], [[0.57932442496651171, 0.296305