-#-*-coding:iso-8859-1-*-
+# -*- coding: utf-8 -*-
#
# Copyright (C) 2008-2017 EDF R&D
#
#
# Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
-import logging
+import sys, logging
from daCore import BasicObjects, PlatformInfo
import numpy, copy
mpr = PlatformInfo.PlatformInfo().MachinePrecision()
mfp = PlatformInfo.PlatformInfo().MaximumPrecision()
+if sys.version_info.major > 2:
+ unicode = str
# ==============================================================================
class ElementaryAlgorithm(BasicObjects.Algorithm):
name = "NumberOfPrintedDigits",
default = 5,
typecast = int,
- message = "Nombre de chiffres affichés pour les impressions de réels",
+ message = "Nombre de chiffres affichés pour les impressions de réels",
minval = 0,
)
self.defineRequiredParameter(
name = "NumberOfRepetition",
default = 1,
typecast = int,
- message = "Nombre de fois où l'exécution de la fonction est répétée",
+ message = "Nombre de fois où l'exécution de la fonction est répétée",
minval = 1,
)
self.defineRequiredParameter(
name = "SetDebug",
default = False,
typecast = bool,
- message = "Activation du mode debug lors de l'exécution",
+ message = "Activation du mode debug lors de l'exécution",
)
self.defineRequiredParameter(
name = "StoreSupplementaryCalculations",
default = [],
typecast = tuple,
- message = "Liste de calculs supplémentaires à stocker et/ou effectuer",
+ message = "Liste de calculs supplémentaires à stocker et/ou effectuer",
listval = ["CurrentState", "SimulatedObservationAtCurrentState"]
)
Xn = copy.copy( Xb )
#
# ----------
+ __marge = 5*u" "
_p = self._parameters["NumberOfPrintedDigits"]
if len(self._parameters["ResultTitle"]) > 0:
- msg = " ====" + "="*len(self._parameters["ResultTitle"]) + "====\n"
- msg += " " + self._parameters["ResultTitle"] + "\n"
- msg += " ====" + "="*len(self._parameters["ResultTitle"]) + "====\n"
- print("%s"%msg)
+ __rt = unicode(self._parameters["ResultTitle"])
+ msgs = u"\n"
+ msgs += __marge + "====" + "="*len(__rt) + "====\n"
+ msgs += __marge + " " + __rt + "\n"
+ msgs += __marge + "====" + "="*len(__rt) + "====\n"
+ print("%s"%msgs)
#
- msg = ("===> Information before launching:\n")
- msg += (" -----------------------------\n")
- msg += (" Characteristics of input vector X, internally converted:\n")
- msg += (" Type...............: %s\n")%type( Xn )
- msg += (" Lenght of vector...: %i\n")%max(numpy.matrix( Xn ).shape)
- msg += (" Minimum value......: %."+str(_p)+"e\n")%numpy.min( Xn )
- msg += (" Maximum value......: %."+str(_p)+"e\n")%numpy.max( Xn )
- msg += (" Mean of vector.....: %."+str(_p)+"e\n")%numpy.mean( Xn, dtype=mfp )
- msg += (" Standard error.....: %."+str(_p)+"e\n")%numpy.std( Xn, dtype=mfp )
- msg += (" L2 norm of vector..: %."+str(_p)+"e\n")%numpy.linalg.norm( Xn )
- print(msg)
+ msgs = ("===> Information before launching:\n")
+ msgs += (" -----------------------------\n")
+ msgs += (" Characteristics of input vector X, internally converted:\n")
+ msgs += (" Type...............: %s\n")%type( Xn )
+ msgs += (" Lenght of vector...: %i\n")%max(numpy.matrix( Xn ).shape)
+ msgs += (" Minimum value......: %."+str(_p)+"e\n")%numpy.min( Xn )
+ msgs += (" Maximum value......: %."+str(_p)+"e\n")%numpy.max( Xn )
+ msgs += (" Mean of vector.....: %."+str(_p)+"e\n")%numpy.mean( Xn, dtype=mfp )
+ msgs += (" Standard error.....: %."+str(_p)+"e\n")%numpy.std( Xn, dtype=mfp )
+ msgs += (" L2 norm of vector..: %."+str(_p)+"e\n")%numpy.linalg.norm( Xn )
+ print(msgs)
#
if self._parameters["SetDebug"]:
CUR_LEVEL = logging.getLogger().getEffectiveLevel()
#
print("\n===> End of direct operator evaluation\n")
#
- 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)
+ 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 "SimulatedObservationAtCurrentState" in self._parameters["StoreSupplementaryCalculations"]:
self.StoredVariables["SimulatedObservationAtCurrentState"].store( numpy.ravel(Yn) )
#
logging.getLogger().setLevel(CUR_LEVEL)
#
if self._parameters["NumberOfRepetition"] > 1:
- msg = (" %s\n"%("-"*75,))
- msg += ("\n===> Statistical analysis of the outputs obtained throught repeated evaluations\n")
- msg += ("\n (Remark: numbers that are (about) under %.0e represent 0 to machine precision)\n"%mpr)
+ msgs = (" %s\n"%("-"*75,))
+ msgs += ("\n===> Statistical analysis of the outputs obtained throught repeated evaluations\n")
+ msgs += ("\n (Remark: numbers that are (about) under %.0e represent 0 to machine precision)\n"%mpr)
Yy = numpy.array( Ys )
- msg += ("\n Characteristics of the whole set of outputs Y:\n")
- msg += (" Number of evaluations.........................: %i\n")%len( Ys )
- msg += (" Minimum value of the whole set of outputs.....: %."+str(_p)+"e\n")%numpy.min( Yy )
- msg += (" Maximum value of the whole set of outputs.....: %."+str(_p)+"e\n")%numpy.max( Yy )
- msg += (" Mean of vector of the whole set of outputs....: %."+str(_p)+"e\n")%numpy.mean( Yy, dtype=mfp )
- msg += (" Standard error of the whole set of outputs....: %."+str(_p)+"e\n")%numpy.std( Yy, dtype=mfp )
+ msgs += ("\n Characteristics of the whole set of outputs Y:\n")
+ msgs += (" Number of evaluations.........................: %i\n")%len( Ys )
+ msgs += (" Minimum value of the whole set of outputs.....: %."+str(_p)+"e\n")%numpy.min( Yy )
+ msgs += (" Maximum value of the whole set of outputs.....: %."+str(_p)+"e\n")%numpy.max( Yy )
+ msgs += (" Mean of vector of the whole set of outputs....: %."+str(_p)+"e\n")%numpy.mean( Yy, dtype=mfp )
+ msgs += (" Standard error of the whole set of outputs....: %."+str(_p)+"e\n")%numpy.std( Yy, dtype=mfp )
Ym = numpy.mean( numpy.array( Ys ), axis=0, dtype=mfp )
- msg += ("\n Characteristics of the vector Ym, mean of the outputs Y:\n")
- msg += (" Size of the mean of the outputs...............: %i\n")%Ym.size
- msg += (" Minimum value of the mean of the outputs......: %."+str(_p)+"e\n")%numpy.min( Ym )
- msg += (" Maximum value of the mean of the outputs......: %."+str(_p)+"e\n")%numpy.max( Ym )
- msg += (" Mean of the mean of the outputs...............: %."+str(_p)+"e\n")%numpy.mean( Ym, dtype=mfp )
- msg += (" Standard error of the mean of the outputs.....: %."+str(_p)+"e\n")%numpy.std( Ym, dtype=mfp )
+ msgs += ("\n Characteristics of the vector Ym, mean of the outputs Y:\n")
+ msgs += (" Size of the mean of the outputs...............: %i\n")%Ym.size
+ msgs += (" Minimum value of the mean of the outputs......: %."+str(_p)+"e\n")%numpy.min( Ym )
+ msgs += (" Maximum value of the mean of the outputs......: %."+str(_p)+"e\n")%numpy.max( Ym )
+ msgs += (" Mean of the mean of the outputs...............: %."+str(_p)+"e\n")%numpy.mean( Ym, dtype=mfp )
+ msgs += (" Standard error of the mean of the outputs.....: %."+str(_p)+"e\n")%numpy.std( Ym, dtype=mfp )
Ye = numpy.mean( numpy.array( Ys ) - Ym, axis=0, dtype=mfp )
- msg += "\n Characteristics of the mean of the differences between the outputs Y and their mean Ym:\n"
- msg += (" Size of the mean of the differences...........: %i\n")%Ym.size
- msg += (" Minimum value of the mean of the differences..: %."+str(_p)+"e\n")%numpy.min( Ye )
- msg += (" Maximum value of the mean of the differences..: %."+str(_p)+"e\n")%numpy.max( Ye )
- msg += (" Mean of the mean of the differences...........: %."+str(_p)+"e\n")%numpy.mean( Ye, dtype=mfp )
- msg += (" Standard error of the mean of the differences.: %."+str(_p)+"e\n")%numpy.std( Ye, dtype=mfp )
- msg += ("\n %s\n"%("-"*75,))
- print(msg)
+ msgs += "\n Characteristics of the mean of the differences between the outputs Y and their mean Ym:\n"
+ msgs += (" Size of the mean of the differences...........: %i\n")%Ym.size
+ msgs += (" Minimum value of the mean of the differences..: %."+str(_p)+"e\n")%numpy.min( Ye )
+ msgs += (" Maximum value of the mean of the differences..: %."+str(_p)+"e\n")%numpy.max( Ye )
+ msgs += (" Mean of the mean of the differences...........: %."+str(_p)+"e\n")%numpy.mean( Ye, dtype=mfp )
+ msgs += (" Standard error of the mean of the differences.: %."+str(_p)+"e\n")%numpy.std( Ye, dtype=mfp )
+ msgs += ("\n %s\n"%("-"*75,))
+ print(msgs)
#
self._post_run(HO)
return 0
