- msg = ("===> Information after evaluation:\n")
- msg += ("\n Characteristics of simulated output vector Y=H(X), to compare to others:\n")
- msg += (" Type...............: %s\n")%type( Yn )
- msg += (" Lenght of vector...: %i\n")%max(numpy.matrix( Yn ).shape)
- msg += (" Minimum value......: %."+str(_p)+"e\n")%numpy.min( Yn )
- msg += (" Maximum value......: %."+str(_p)+"e\n")%numpy.max( Yn )
- msg += (" Mean of vector.....: %."+str(_p)+"e\n")%numpy.mean( Yn, dtype=mfp )
- msg += (" Standard error.....: %."+str(_p)+"e\n")%numpy.std( Yn, dtype=mfp )
- msg += (" L2 norm of vector..: %."+str(_p)+"e\n")%numpy.linalg.norm( Yn )
- print(msg)
- if "SimulatedObservationAtCurrentState" in self._parameters["StoreSupplementaryCalculations"]:
+ msgs = ("===> Information after evaluation:\n")
+ msgs += ("\n Characteristics of simulated output vector Y=H(X), to compare to others:\n")
+ msgs += (" Type...............: %s\n")%type( Yn )
+ msgs += (" Lenght of vector...: %i\n")%max(numpy.matrix( Yn ).shape)
+ msgs += (" Minimum value......: %."+str(_p)+"e\n")%numpy.min( Yn )
+ msgs += (" Maximum value......: %."+str(_p)+"e\n")%numpy.max( Yn )
+ msgs += (" Mean of vector.....: %."+str(_p)+"e\n")%numpy.mean( Yn, dtype=mfp )
+ msgs += (" Standard error.....: %."+str(_p)+"e\n")%numpy.std( Yn, dtype=mfp )
+ msgs += (" L2 norm of vector..: %."+str(_p)+"e\n")%numpy.linalg.norm( Yn )
+ print(msgs)
+ if self._toStore("SimulatedObservationAtCurrentState"):