From: Jean-Philippe ARGAUD Date: Sat, 11 Sep 2021 20:07:40 +0000 (+0200) Subject: Minor internal modifications and performance improvements X-Git-Tag: V9_8_0a1~14 X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=460cf7f4df541b72a55f3ac6ffac15310d318274;p=modules%2Fadao.git Minor internal modifications and performance improvements --- diff --git a/src/daComposant/daCore/NumericObjects.py b/src/daComposant/daCore/NumericObjects.py index ebd3d35..2aa13c9 100644 --- a/src/daComposant/daCore/NumericObjects.py +++ b/src/daComposant/daCore/NumericObjects.py @@ -716,9 +716,9 @@ def ForceNumericBounds( __Bounds ): # Converti toutes les bornes individuelles None à +/- l'infini __Bounds = numpy.asarray( __Bounds, dtype=float ) if len(__Bounds.shape) != 2 or min(__Bounds.shape) <= 0 or __Bounds.shape[1] != 2: - raise ValueError("Incorrectly defined bounds data") - __Bounds[numpy.isnan(__Bounds)[:,0],0] = -sys.float_info.max - __Bounds[numpy.isnan(__Bounds)[:,1],1] = sys.float_info.max + raise ValueError("Incorrectly shaped bounds data") + __Bounds[numpy.isnan(__Bounds[:,0]),0] = -sys.float_info.max + __Bounds[numpy.isnan(__Bounds[:,1]),1] = sys.float_info.max return __Bounds # ============================================================================== @@ -729,6 +729,33 @@ def RecentredBounds( __Bounds, __Center): # Recentre les valeurs numériques de bornes return ForceNumericBounds( __Bounds ) - numpy.ravel( __Center ).transpose((-1,1)) +# ============================================================================== +def ApplyBounds( __Vector, __Bounds, __newClip = True): + "Applique des bornes numériques à un point" + # Conserve une valeur par défaut s'il n'y a pas de bornes + if __Bounds is None: return __Vector + # + if not isinstance(__Vector, numpy.ndarray): # Is an array + raise ValueError("Incorrect array definition of vector data") + if not isinstance(__Bounds, numpy.ndarray): # Is an array + raise ValueError("Incorrect array definition of bounds data") + if 2*__Vector.size != __Bounds.size: # Is a 2 column array of vector lenght + raise ValueError("Incorrect bounds number to be applied for this vector") + if len(__Bounds.shape) != 2 or min(__Bounds.shape) <= 0 or __Bounds.shape[1] != 2: + raise ValueError("Incorrectly shaped bounds data") + # + if __newClip: + __Vector = __Vector.clip( + __Bounds[:,0].reshape(__Vector.shape), + __Bounds[:,1].reshape(__Vector.shape), + ) + else: + __Vector = numpy.max(numpy.hstack((__Vector.reshape((-1,1)),numpy.asmatrix(__Bounds)[:,0])),axis=1) + __Vector = numpy.min(numpy.hstack((__Vector.reshape((-1,1)),numpy.asmatrix(__Bounds)[:,1])),axis=1) + __Vector = numpy.asarray(__Vector) + # + return __Vector + # ============================================================================== def cekf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): """ @@ -816,8 +843,7 @@ def cekf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): Un = None # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - Xn = numpy.max(numpy.hstack((Xn,numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xn = numpy.min(numpy.hstack((Xn,numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xn = ApplyBounds( Xn, selfA._parameters["Bounds"] ) # if selfA._parameters["EstimationOf"] == "State": # Forecast + Q and observation of forecast Xn_predicted = numpy.ravel( M( (Xn, Un) ) ).reshape((__n,1)) @@ -831,8 +857,7 @@ def cekf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): Pn_predicted = Pn # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - Xn_predicted = numpy.max(numpy.hstack((Xn_predicted,numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xn_predicted = numpy.min(numpy.hstack((Xn_predicted,numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xn_predicted = ApplyBounds( Xn_predicted, selfA._parameters["Bounds"] ) # if selfA._parameters["EstimationOf"] == "State": HX_predicted = numpy.ravel( H( (Xn_predicted, None) ) ).reshape((__p,1)) @@ -848,8 +873,7 @@ def cekf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): Pn = Pn_predicted - Kn * Ht * Pn_predicted # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - Xn = numpy.max(numpy.hstack((Xn,numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xn = numpy.min(numpy.hstack((Xn,numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xn = ApplyBounds( Xn, selfA._parameters["Bounds"] ) # Xa = Xn # Pointeurs #-------------------------- @@ -3323,9 +3347,7 @@ def std4dvar(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): pass # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - __Bounds = ForceNumericBounds( selfA._parameters["Bounds"] ) - _Xn = numpy.max(numpy.hstack((_Xn,numpy.asmatrix(__Bounds)[:,0])),axis=1) - _Xn = numpy.min(numpy.hstack((_Xn,numpy.asmatrix(__Bounds)[:,1])),axis=1) + _Xn = ApplyBounds( _Xn, ForceNumericBounds(selfA._parameters["Bounds"]) ) # # Etape de différence aux observations if selfA._parameters["EstimationOf"] == "State": @@ -3760,8 +3782,7 @@ def uckf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": for point in range(nbSpts): - Xnp[:,point] = numpy.max(numpy.hstack((Xnp[:,point],numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xnp[:,point] = numpy.min(numpy.hstack((Xnp[:,point],numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xnp[:,point] = ApplyBounds( Xnp[:,point], selfA._parameters["Bounds"] ) # XEtnnp = [] for point in range(nbSpts): @@ -3771,8 +3792,7 @@ def uckf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): Cm = Cm.reshape(Xn.size,Un.size) # ADAO & check shape XEtnnpi = XEtnnpi + Cm * Un if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - XEtnnpi = numpy.max(numpy.hstack((XEtnnpi,numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - XEtnnpi = numpy.min(numpy.hstack((XEtnnpi,numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + XEtnnpi = ApplyBounds( XEtnnpi, selfA._parameters["Bounds"] ) elif selfA._parameters["EstimationOf"] == "Parameters": # --- > Par principe, M = Id, Q = 0 XEtnnpi = Xnp[:,point] @@ -3782,8 +3802,7 @@ def uckf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): Xncm = numpy.matrix( XEtnnp.getA()*numpy.array(Wm) ).sum(axis=1) # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - Xncm = numpy.max(numpy.hstack((Xncm,numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xncm = numpy.min(numpy.hstack((Xncm,numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xncm = ApplyBounds( Xncm, selfA._parameters["Bounds"] ) # if selfA._parameters["EstimationOf"] == "State": Pnm = Q elif selfA._parameters["EstimationOf"] == "Parameters": Pnm = 0. @@ -3799,8 +3818,7 @@ def uckf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": for point in range(nbSpts): - Xnnp[:,point] = numpy.max(numpy.hstack((Xnnp[:,point],numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xnnp[:,point] = numpy.min(numpy.hstack((Xnnp[:,point],numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xnnp[:,point] = ApplyBounds( Xnnp[:,point], selfA._parameters["Bounds"] ) # Ynnp = [] for point in range(nbSpts): @@ -3829,8 +3847,7 @@ def uckf(selfA, Xb, Y, U, HO, EM, CM, R, B, Q): Pn = Pnm - Kn * Pyyn * Kn.T # if selfA._parameters["Bounds"] is not None and selfA._parameters["ConstrainedBy"] == "EstimateProjection": - Xn = numpy.max(numpy.hstack((Xn,numpy.asmatrix(selfA._parameters["Bounds"])[:,0])),axis=1) - Xn = numpy.min(numpy.hstack((Xn,numpy.asmatrix(selfA._parameters["Bounds"])[:,1])),axis=1) + Xn = ApplyBounds( Xn, selfA._parameters["Bounds"] ) # Xa = Xn # Pointeurs #-------------------------- diff --git a/test/test1002/Performances.py b/test/test1002/Performances.py index 319dd95..795c615 100644 --- a/test/test1002/Performances.py +++ b/test/test1002/Performances.py @@ -48,6 +48,7 @@ class Test_Adao(unittest.TestCase): print("") return True + #~ @unittest.skip("Debug") def test_Numpy01(self, dimension = 10000, precision = 1.e-17, repetitions = 10): "Test Numpy" __d = int(dimension) @@ -70,6 +71,7 @@ class Test_Adao(unittest.TestCase): print("") del A, x, b + #~ @unittest.skip("Debug") def test_Numpy02(self, dimension = 3000, precision = 1.e-17, repetitions = 100): "Test Numpy" __d = int(dimension) @@ -87,6 +89,7 @@ class Test_Adao(unittest.TestCase): print("") del A, x, b + #~ @unittest.skip("Debug") def test_Scipy01(self, dimension = 3000, precision = 1.e-17, repetitions = 10): "Test Scipy" __d = int(dimension)