def main():
model_file, color_scheme, dot_file, options = parse_args()
dot_object = None
file_object = None
try:
try:
model_type = options.format
if not model_type:
model_type = getModelType(model_file)
if not model_type:
print >>sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(sys.argv[0])
sys.exit(1)
if model_file == "-":
file_object=sys.stdin
else:
file_object=open(model_file)
if dot_file == "-":
dot_object=sys.stdout
else:
dot_object=open(dot_file,'w')
m=loadModel(model_type, file_object)
visualise(m,dot_object,not options.no_stateprops, not options.no_actions, "TEMA-Model %s" % model_file, options.compact, options.colored, color_scheme )
except Exception, e:
print >>sys.stderr,e
sys.exit(1)
finally:
if file_object and model_file != "-":
file_object.close()
if dot_object and dot_file != "-":
dot_object.close()
def main():
modelfile,options=readArgs()
if options.testdata:
testdata=load_testdata(options.testdata)
else:
testdata=None
try:
modeltype=options.format
if not modeltype:
modeltype = getModelType(modelfile)
if not modeltype:
print >>sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(sys.argv[0])
sys.exit(1)
if modelfile == "-":
file_object=sys.stdin
else:
file_object=open(modelfile)
m=loadModel(modeltype,file_object)
except Exception, e:
print >>sys.stderr,e
sys.exit(1)
def main():
modelfile, options = readArgs()
if options.testdata:
testdata = load_testdata(options.testdata)
else:
testdata = None
try:
modeltype = options.format
if not modeltype:
modeltype = getModelType(modelfile)
if not modeltype:
print >> sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(
sys.argv[0])
sys.exit(1)
if modelfile == "-":
file_object = sys.stdin
else:
file_object = open(modelfile)
m = loadModel(modeltype, file_object)
except Exception, e:
print >> sys.stderr, e
sys.exit(1)
def convert(options, filename):
format = options.format
outputfilename = options.output
if not format:
format = getModelType(filename)
if not format:
print >>sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(sys.argv[0])
sys.exit(1)
if filename == "-":
modelfile=sys.stdin
else:
modelfile=open(filename)
model = None
try:
model = loadModel(format,modelfile)
finally:
modelfile.close()
if outputfilename != "-":
out = open(outputfilename, 'w')
try:
convert_to_lsts(model, out)
finally:
out.close()
else:
convert_to_lsts(model, sys.stdout)
def prepareForRun(self):
self._is_running=True
self.log("OK to rock")
self._delay = int(self.getParameter("delay",0))
if self.getParameter("model"):
Adapter.sendInput = DelayedExecution(self,Adapter._model_guess, self._delay)
self.log("Checking from the model")
# from tema.model.parallellstsmodel import ParallelLstsModel as Oraakkeli
# self._oraakkeli = Oraakkeli()
# self._oraakkeli.loadFromFile(open(self.getParameter("model"),"r"))
self._oraakkeli = loadModel(self.getParameter("model_type"),open(self.getParameter("model"),"r"))
self._current_state = [self._oraakkeli.getInitialState()]
else:
Adapter.sendInput = DelayedExecution(self,Adapter._wild_guess, self._delay)
self.log("Taking a guess")
def main():
structure, files, options = readArgs()
commons = {
'multi': COMMONS_MULTITARGET,
'single': COMMONS_SINGLETARGET
}[structure]
models = []
for filename in files:
if options.format:
modelType = options.format
else:
modelType = getModelType(filename)
if modelType is None and filename.endswith('.analysis'):
file = open(filename)
try:
content = file.read()
finally:
file.close()
models.append(parseresult(content))
elif modelType is None:
print >> sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(
sys.argv[0])
sys.exit(1)
else:
model = None
if filename == "-":
file = sys.stdin
else:
file = open(filename)
try:
model = loadModel(modelType, file)
finally:
file.close()
models.append(model)
results = analyseModels(models, commons)
print
for nameresult in zip(files, results[0]):
printresult(nameresult[0], nameresult[1])
print
printresult('Estimated total', results[1])
print
def prepareForRun(self):
self._is_running = True
self.log("OK to rock")
self._delay = int(self.getParameter("delay", 0))
if self.getParameter("model"):
Adapter.sendInput = DelayedExecution(self, Adapter._model_guess,
self._delay)
self.log("Checking from the model")
# from tema.model.parallellstsmodel import ParallelLstsModel as Oraakkeli
# self._oraakkeli = Oraakkeli()
# self._oraakkeli.loadFromFile(open(self.getParameter("model"),"r"))
self._oraakkeli = loadModel(self.getParameter("model_type"),
open(self.getParameter("model"), "r"))
self._current_state = [self._oraakkeli.getInitialState()]
else:
Adapter.sendInput = DelayedExecution(self, Adapter._wild_guess,
self._delay)
self.log("Taking a guess")
def main():
structure,files,options = readArgs()
commons = {'multi':COMMONS_MULTITARGET, 'single':COMMONS_SINGLETARGET}[structure]
models = []
for filename in files:
if options.format:
modelType = options.format
else:
modelType = getModelType(filename)
if modelType is None and filename.endswith('.analysis'):
file = open(filename)
try:
content = file.read()
finally:
file.close()
models.append(parseresult(content))
elif modelType is None:
print >>sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(sys.argv[0])
sys.exit(1)
else:
model = None
if filename == "-":
file = sys.stdin
else:
file = open(filename)
try:
model = loadModel(modelType,file)
finally:
file.close()
models.append(model)
results = analyseModels(models, commons)
print
for nameresult in zip(files, results[0]):
printresult(nameresult[0], nameresult[1])
print
printresult('Estimated total', results[1])
print
def main():
model_file, color_scheme, dot_file, options = parse_args()
dot_object = None
file_object = None
try:
try:
model_type = options.format
if not model_type:
model_type = getModelType(model_file)
if not model_type:
print >> sys.stderr, "%s: Error. Unknown model type. Specify model type using '-f'" % os.path.basename(
sys.argv[0])
sys.exit(1)
if model_file == "-":
file_object = sys.stdin
else:
file_object = open(model_file)
if dot_file == "-":
dot_object = sys.stdout
else:
dot_object = open(dot_file, 'w')
m = loadModel(model_type, file_object)
visualise(m, dot_object, not options.no_stateprops,
not options.no_actions, "TEMA-Model %s" % model_file,
options.compact, options.colored, color_scheme)
except Exception, e:
print >> sys.stderr, e
sys.exit(1)
finally:
if file_object and model_file != "-":
file_object.close()
if dot_object and dot_file != "-":
dot_object.close()
def validateModel(modelName, modelFormat, modelType):
if not modelFormat:
modelFormat = getModelType(modelName)
if modelType:
modelType = eval("ModelValidator.%s" % modelType.upper())
else:
modelFormats = ["mdm", "lsts"]
for format in modelFormats:
if modelName.endswith(".refined.%s" % format):
modelType = ModelValidator.REFINED_MACHINE
elif modelName.endswith("-im.%s" % format):
modelType = ModelValidator.INITIALIZATION_MACHINE
elif modelName.endswith("-lm.%s" % format):
modelType = ModelValidator.LAUNCH_MACHINE
elif modelName.endswith("-rm.%s" % format):
modelType = ModelValidator.REFINEMENT_MACHINE
elif modelName.endswith(".%s" % format):
modelType = ModelValidator.ACTION_MACHINE
elif modelName.endswith(".ext") or modelName.endswith(
".parallellsts") or modelName.endswith(".parallel"):
modelType = ModelValidator.COMPOSED_MACHINE
if modelType is not None:
break
else:
print 'File %s is in unknown format' % modelName
print ''
return
model = None
if modelName == "-":
modelFile = sys.stdin
else:
modelFile = open(modelName)
try:
model = loadModel(modelFormat, modelFile)
finally:
if modelName != "-":
modelFile.close()
errors = []
warnings = []
validator = ModelValidator(model)
lock = validator.beginValidation(modelType, errors, warnings)
if lock == None:
print 'Model %s is of an unknown type.' % modelName
print ''
return
while True:
sleep(0.1)
if not lock.locked():
break
pruneErrors(errors)
pruneErrors(warnings)
for i in errors + warnings:
for j in i[1]:
if j[:4] == 'path' and i[1][j] != None:
i[1][j] = [str(k) for k in i[1][j]]
if (len(errors) == 0 and len(warnings) == 0):
print 'Model %s is valid.' % modelName
else:
if (len(errors) > 0):
print 'Errors in model %s:\n' % modelName +\
str([(i[0], ModelValidator.defaultErrorMessages[i[0]] % i[1]) for i in errors])
if (len(warnings) > 0):
print 'Warnings in model %s:\n' % modelName +\
str([(i[0], ModelValidator.defaultErrorMessages[i[0]] % i[1]) for i in warnings])
print ''
def validateModel(modelName,modelFormat,modelType):
if not modelFormat:
modelFormat = getModelType(modelName)
if modelType:
modelType = eval("ModelValidator.%s" % modelType.upper())
else:
modelFormats = [ "mdm","lsts" ]
for format in modelFormats:
if modelName.endswith(".refined.%s" % format ):
modelType = ModelValidator.REFINED_MACHINE
elif modelName.endswith("-im.%s" % format ):
modelType = ModelValidator.INITIALIZATION_MACHINE
elif modelName.endswith("-lm.%s" % format ):
modelType = ModelValidator.LAUNCH_MACHINE
elif modelName.endswith("-rm.%s" % format ):
modelType = ModelValidator.REFINEMENT_MACHINE
elif modelName.endswith(".%s" % format ):
modelType = ModelValidator.ACTION_MACHINE
elif modelName.endswith(".ext") or modelName.endswith(".parallellsts") or modelName.endswith(".parallel"):
modelType = ModelValidator.COMPOSED_MACHINE
if modelType is not None:
break
else:
print 'File %s is in unknown format' % modelName
print ''
return
model = None
if modelName == "-":
modelFile = sys.stdin
else:
modelFile = open(modelName)
try:
model = loadModel(modelFormat,modelFile)
finally:
if modelName != "-":
modelFile.close()
errors = []
warnings = []
validator = ModelValidator(model)
lock = validator.beginValidation(modelType, errors, warnings)
if lock == None:
print 'Model %s is of an unknown type.' % modelName
print ''
return
while True:
sleep(0.1)
if not lock.locked():
break
pruneErrors(errors)
pruneErrors(warnings)
for i in errors + warnings:
for j in i[1]:
if j[:4] == 'path' and i[1][j] != None:
i[1][j] = [str(k) for k in i[1][j]]
if (len(errors) == 0 and len(warnings) == 0):
print 'Model %s is valid.' % modelName
else:
if (len(errors) > 0):
print 'Errors in model %s:\n' % modelName +\
str([(i[0], ModelValidator.defaultErrorMessages[i[0]] % i[1]) for i in errors])
if (len(warnings) > 0):
print 'Warnings in model %s:\n' % modelName +\
str([(i[0], ModelValidator.defaultErrorMessages[i[0]] % i[1]) for i in warnings])
print ''
