2 # Copyright (C) 2008-2011 EDF R&D
4 # This library is free software; you can redistribute it and/or
5 # modify it under the terms of the GNU General Public
6 # License as published by the Free Software Foundation; either
7 # version 2.1 of the License.
9 # This library is distributed in the hope that it will be useful,
10 # but WITHOUT ANY WARRANTY; without even the implied warranty of
11 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
12 # Lesser General Public License for more details.
14 # You should have received a copy of the GNU Lesser General Public
15 # License along with this library; if not, write to the Free Software
16 # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
19 # Author : André RIBES (EDF R&D)
28 logging.basicConfig(level=logging.DEBUG)
30 #----------- Templates Part ---------------#
31 begin_catalog_file = """
32 # -*- coding: utf-8 -*-
34 # --------------------------------------------------------
35 # generated by AdaoCatalogGenerator at ${date}
36 # --------------------------------------------------------
41 JdC = JDC_CATA (code = 'ADAO',
43 regles = ( AU_MOINS_UN ('ASSIMILATION_STUDY'), AU_PLUS_UN ('ASSIMILATION_STUDY')),
48 def F_${data_name}(statut) : return FACT(statut = statut,
49 FROM = SIMP(statut = "o", typ = "TXM", into=(${data_into}), defaut=${data_default}),
50 SCRIPT_DATA = BLOC ( condition = " FROM in ( 'Script', ) ",
52 SCRIPT_FILE = SIMP(statut = "o", typ = "FichierNoAbs", validators=(OnlyStr())),
54 STRING_DATA = BLOC ( condition = " FROM in ( 'String', ) ",
56 STRING = SIMP(statut = "o", typ = "TXM"),
58 FUNCTIONDICT_DATA = BLOC ( condition = " FROM in ( 'FunctionDict', ) ",
60 FUNCTIONDICT_FILE = SIMP(statut = "o", typ = "FichierNoAbs", validators=(OnlyStr())),
66 def F_InitChoice() : return ("Background",
70 "ObservationOperator",
71 "AlgorithmParameters",
75 def F_Init(statut) : return FACT(statut = statut,
76 INIT_FILE = SIMP(statut = "o", typ = "FichierNoAbs", validators=(OnlyStr())),
77 TARGET_LIST = SIMP(statut = "o", typ = "TXM", min=1, max="**", into=F_InitChoice(), validators=(VerifExiste(2))),
81 assim_data_method = """
82 def F_${assim_name}(statut) : return FACT(statut=statut,
83 INPUT_TYPE = SIMP(statut="o", typ = "TXM", into=(${choices}), defaut=${default_choice}),
88 assim_data_choice = """
89 ${choice_name} = BLOC ( condition = " INPUT_TYPE in ( '${choice_name}', ) ",
90 data = F_${choice_name}("o"),
94 observers_choice = """
95 ${var_name} = BLOC (condition=" '${var_name}' in set(SELECTION) ",
96 FREQUENCY = SIMP(statut = "o", typ = "TXM")
100 observers_method = """
101 def F_Observers(statut) : return FACT(statut=statut,
102 SELECTION = SIMP(statut="o", defaut=[], typ="TXM", max="**", validators=NoRepeat(), into=(${choices})),
109 def F_variables(statut) : return FACT(statut=statut,
110 regles = ( MEME_NOMBRE ('NAMES', 'SIZES')),
111 NAMES = SIMP(statut="o", typ="TXM", max="**", validators=NoRepeat()),
112 SIZES = SIMP(statut="o", typ="I", val_min=1, max="**")
115 ASSIMILATION_STUDY = PROC(nom="ASSIMILATION_STUDY",
118 Study_name = SIMP(statut="o", typ = "TXM"),
119 Study_repertory = SIMP(statut="f", typ = "TXM"),
120 Debug = SIMP(statut="o", typ = "I", into=(0, 1), defaut=0),
121 Algorithm = SIMP(statut="o", typ = "TXM", into=(${algos_names})),
122 Background = F_Background("o"),
123 BackgroundError = F_BackgroundError("o"),
124 Observation = F_Observation("o"),
125 ObservationError = F_ObservationError("o"),
126 ObservationOperator = F_ObservationOperator("o"),
127 AlgorithmParameters = F_AlgorithmParameters("f"),
128 UserDataInit = F_Init("f"),
129 UserPostAnalysis = F_UserPostAnalysis("f"),
130 InputVariables = F_variables("f"),
131 OutputVariables = F_variables("f"),
132 Observers = F_Observers("f")
136 begin_catalog_file = string.Template(begin_catalog_file)
137 data_method = string.Template(data_method)
138 assim_data_method = string.Template(assim_data_method)
139 assim_data_choice = string.Template(assim_data_choice)
140 assim_study = string.Template(assim_study)
141 observers_method = string.Template(observers_method)
142 observers_choice = string.Template(observers_choice)
144 #----------- End of Templates Part ---------------#
148 #----------- Begin generation script -----------#
149 print "-- Starting AdaoCalatogGenerator.py --"
153 import daYacsSchemaCreator
154 import daCore.AssimilationStudy
155 import daYacsSchemaCreator.infos_daComposant as infos
157 logging.fatal("Import of ADAO python modules failed !" +
158 "\n add ADAO python installation directory in your PYTHONPATH")
159 traceback.print_exc()
162 def check_args(args):
163 logging.debug("Arguments are :" + str(args))
165 logging.fatal("Bad number of arguments: you have to provide two arguments (%d given)" % (len(args)))
169 from optparse import OptionParser
170 usage = "usage: %prog [options] catalog_path catalog_name"
172 my_parser = OptionParser(usage=usage, version=version)
173 (options, args) = my_parser.parse_args()
176 catalog_path = args[0]
177 catalog_name = args[1]
179 # Generates into a string
180 mem_file = StringIO.StringIO()
183 from time import strftime
184 mem_file.write(begin_catalog_file.substitute(date=strftime("%Y-%m-%d %H:%M:%S")))
186 # Step 1: A partir des infos, on crée les fonctions qui vont permettre
187 # d'entrer les données utilisateur
188 for data_input_name in infos.DataTypeDict.keys():
189 logging.debug('A data input Type is found: ' + data_input_name)
190 data_name = data_input_name
194 # On récupère les différentes façon d'entrer les données
195 for basic_type in infos.DataTypeDict[data_input_name]:
196 data_into += "\"" + basic_type + "\", "
198 # On choisit le défault
199 data_default = "\"" + infos.DataTypeDefaultDict[data_input_name] + "\""
201 mem_file.write(data_method.substitute(data_name = data_name,
202 data_into = data_into,
203 data_default = data_default))
205 # Step 2: On crée les fonctions qui permettent de rentrer les données des algorithmes
206 for assim_data_input_name in infos.AssimDataDict.keys():
207 logging.debug("An assimilation algorithm data input is found: " + assim_data_input_name)
208 assim_name = assim_data_input_name
213 for choice in infos.AssimDataDict[assim_data_input_name]:
214 choices += "\"" + choice + "\", "
215 decl_choices += assim_data_choice.substitute(choice_name = choice)
216 default_choice = "\"" + infos.AssimDataDefaultDict[assim_data_input_name] + "\""
218 mem_file.write(assim_data_method.substitute(assim_name = assim_name,
220 decl_choices = decl_choices,
221 default_choice=default_choice))
223 # Step 3: On ajoute les fonctions représentant les options possibles
224 for opt_name in infos.OptDict.keys():
225 logging.debug("An optional node is found: " + opt_name)
230 for choice in infos.OptDict[opt_name]:
231 data_into += "\"" + choice + "\", "
232 data_default = "\"" + infos.OptDefaultDict[opt_name] + "\""
234 mem_file.write(data_method.substitute(data_name = data_name,
235 data_into = data_into,
236 data_default = data_default))
238 # Step 4: On ajoute la méthode optionnelle init
239 # TODO uniformiser avec le step 3
240 mem_file.write(init_method)
242 # Step 5: Add observers
244 for obs_var in infos.ObserversList:
245 decl_choices += observers_choice.substitute(var_name=obs_var)
246 mem_file.write(observers_method.substitute(choices = infos.ObserversList,
247 decl_choices = decl_choices))
249 # Final step: Add algorithm and assim_study
253 assim_study_object = daCore.AssimilationStudy.AssimilationStudy()
254 algos_list = assim_study_object.get_available_algorithms()
255 for algo_name in algos_list:
256 logging.debug("An assimilation algorithm is found: " + algo_name)
257 algos_names += "\"" + algo_name + "\", "
259 mem_file.write(assim_study.substitute(algos_names=algos_names,
260 decl_algos=decl_algos))
262 final_file = open(catalog_path + "/" + catalog_name, "wr")
263 final_file.write(mem_file.getvalue())