def _loadAlgorithms(self):
folder = ModelerUtils.modelsFolder()
for descriptionFile in os.listdir(folder):
if descriptionFile.endswith("model"):
try:
alg = ModelerAlgorithm()
fullpath = os.path.join(ModelerUtils.modelsFolder(),descriptionFile)
alg.openModel(fullpath)
if alg.name.strip() != "":
alg.provider = self
self.algs.append(alg)
except WrongModelException,e:
SextanteLog.addToLog(SextanteLog.LOG_ERROR,"Could not load model " + descriptionFile + "\n" + e.msg)
def _loadAlgorithms(self):
folder = ModelerUtils.modelsFolder()
for descriptionFile in os.listdir(folder):
if descriptionFile.endswith("model"):
try:
alg = ModelerAlgorithm()
fullpath = os.path.join(ModelerUtils.modelsFolder(),descriptionFile)
alg.openModel(fullpath)
if alg.name.strip() != "":
alg.provider = self
self.algs.append(alg)
except WrongModelException,e:
SextanteLog.addToLog(SextanteLog.LOG_ERROR,"Could not load model " + descriptionFile + "\n" + e.msg)
def openModel(self, filename):
self.algPos = []
self.paramPos = []
self.algs = []
self.algParameters = []
self.algOutputs = []
self.paramValues = {}
self.dependencies = []
self.descriptionFile = filename
lines = codecs.open(filename, "r", encoding='utf-8')
line = lines.readline().strip("\n")
iAlg = 0
try:
while line != "":
if line.startswith("PARAMETER:"):
paramLine = line[len("PARAMETER:"):]
param = ParameterFactory.getFromString(paramLine)
if param:
self.parameters.append(param)
else:
raise WrongModelException("Error in line: " + line)
line = lines.readline().strip("\n")
tokens = line.split(",")
self.paramPos.append(QtCore.QPointF(float(tokens[0]), float(tokens[1])))
elif line.startswith("VALUE:"):
valueLine = line[len("VALUE:"):]
tokens = valueLine.split("===")
self.paramValues[tokens[0]] = tokens[1].replace(ModelerAlgorithm.LINE_BREAK_STRING, '\n')
elif line.startswith("NAME:"):
self.name = line[len("NAME:"):]
elif line.startswith("GROUP:"):
self.group = line[len("GROUP:"):]
elif line.startswith("ALGORITHM:"):
algParams={}
algOutputs={}
algLine = line[len("ALGORITHM:"):]
alg = ModelerUtils.getAlgorithm(algLine)
if alg:
posline = lines.readline().strip("\n")
tokens = posline.split(",")
self.algPos.append(QtCore.QPointF(float(tokens[0]), float(tokens[1])))
self.algs.append(alg)
dependenceline = lines.readline().strip("\n")
dependencies = [];
if dependenceline != str(None):
for index in dependenceline.split(","):
dependencies.append(int(index))
for param in alg.parameters:
line = lines.readline().strip("\n")
if line==str(None):
algParams[param.name] = None
else:
tokens = line.split("|")
algParams[param.name] = AlgorithmAndParameter(int(tokens[0]), tokens[1])
for out in alg.outputs:
line = lines.readline().strip("\n")
if str(None)!=line:
algOutputs[out.name] = line
#we add the output to the algorithm, with a name indicating where it comes from
#that guarantees that the name is unique
output = copy.deepcopy(out)
output.description = line
output.name = self.getSafeNameForOutput(iAlg, output)
self.addOutput(output)
else:
algOutputs[out.name] = None
self.algOutputs.append(algOutputs)
self.algParameters.append(algParams)
self.dependencies.append(dependencies)
iAlg += 1
else:
raise WrongModelException("Error in line: " + line)
line = lines.readline().strip("\n")
except:
raise WrongModelException("Error in line: " + line)
def openModel(self, filename):
self.algPos = []
self.paramPos = []
self.algs = []
self.algParameters = []
self.algOutputs = []
self.paramValues = {}
self.descriptionFile = filename
lines = codecs.open(filename, "r", encoding='utf-8')
line = lines.readline().strip("\n")
iAlg = 0
try:
while line != "":
if line.startswith("PARAMETER:"):
paramLine = line[len("PARAMETER:"):]
param = ParameterFactory.getFromString(paramLine)
if param:
self.parameters.append(param)
else:
raise WrongModelException("Error in line: " + line)
line = lines.readline().strip("\n")
tokens = line.split(",")
self.paramPos.append(
QtCore.QPointF(float(tokens[0]), float(tokens[1])))
elif line.startswith("VALUE:"):
valueLine = line[len("VALUE:"):]
tokens = valueLine.split("=")
self.paramValues[tokens[0]] = tokens[1]
elif line.startswith("NAME:"):
self.name = line[len("NAME:"):]
elif line.startswith("GROUP:"):
self.group = line[len("GROUP:"):]
elif line.startswith("ALGORITHM:"):
algParams = {}
algOutputs = {}
algLine = line[len("ALGORITHM:"):]
alg = ModelerUtils.getAlgorithm(algLine)
if alg:
posline = lines.readline().strip("\n")
tokens = posline.split(",")
self.algPos.append(
QtCore.QPointF(float(tokens[0]), float(tokens[1])))
self.algs.append(alg)
for param in alg.parameters:
line = lines.readline().strip("\n")
if line == str(None):
algParams[param.name] = None
else:
tokens = line.split("|")
algParams[param.name] = AlgorithmAndParameter(
int(tokens[0]), tokens[1])
for out in alg.outputs:
line = lines.readline().strip("\n")
if str(None) != line:
algOutputs[out.name] = line
#we add the output to the algorithm, with a name indicating where it comes from
#that guarantees that the name is unique
output = copy.deepcopy(out)
output.description = line
output.name = self.getSafeNameForOutput(
iAlg, output)
self.addOutput(output)
else:
algOutputs[out.name] = None
self.algOutputs.append(algOutputs)
self.algParameters.append(algParams)
iAlg += 1
else:
raise WrongModelException("Error in line: " + line)
line = lines.readline().strip("\n")
except WrongModelException:
raise WrongModelException(line)
def openModel(self, filename):
self.algPos = []
self.paramPos = []
self.algs = []
self.algParameters = []
self.algOutputs = []
self.paramValues = {}
self.dependencies = []
self.descriptionFile = filename
lines = codecs.open(filename, "r", encoding='utf-8')
line = lines.readline().strip("\n").strip("\r")
iAlg = 0
try:
while line != "":
if line.startswith("PARAMETER:"):
paramLine = line[len("PARAMETER:"):]
param = ParameterFactory.getFromString(paramLine)
if param:
self.parameters.append(param)
else:
raise WrongModelException("Error in parameter line: " +
line)
line = lines.readline().strip("\n")
tokens = line.split(",")
self.paramPos.append(
QtCore.QPointF(float(tokens[0]), float(tokens[1])))
elif line.startswith("VALUE:"):
valueLine = line[len("VALUE:"):]
tokens = valueLine.split("===")
self.paramValues[tokens[0]] = tokens[1].replace(
ModelerAlgorithm.LINE_BREAK_STRING, '\n')
elif line.startswith("NAME:"):
self.name = line[len("NAME:"):]
elif line.startswith("GROUP:"):
self.group = line[len("GROUP:"):]
elif line.startswith("ALGORITHM:"):
algParams = {}
algOutputs = {}
algLine = line[len("ALGORITHM:"):]
alg = ModelerUtils.getAlgorithm(algLine)
if alg is not None:
posline = lines.readline().strip("\n").strip("\r")
tokens = posline.split(",")
self.algPos.append(
QtCore.QPointF(float(tokens[0]), float(tokens[1])))
self.algs.append(alg)
dependenceline = lines.readline().strip("\n").strip(
"\r")
dependencies = []
if dependenceline != str(None):
for index in dependenceline.split(","):
try:
dependencies.append(int(index))
except:
pass #a quick fix fwhile I figure out how to solve problems when parsing this
for param in alg.parameters:
line = lines.readline().strip("\n").strip("\r")
if line == str(None):
algParams[param.name] = None
else:
tokens = line.split("|")
algParams[param.name] = AlgorithmAndParameter(
int(tokens[0]), tokens[1])
for out in alg.outputs:
line = lines.readline().strip("\n").strip("\r")
if str(None) != line:
algOutputs[out.name] = line
#we add the output to the algorithm, with a name indicating where it comes from
#that guarantees that the name is unique
output = copy.deepcopy(out)
output.description = line
output.name = self.getSafeNameForOutput(
iAlg, output)
self.addOutput(output)
else:
algOutputs[out.name] = None
self.algOutputs.append(algOutputs)
self.algParameters.append(algParams)
self.dependencies.append(dependencies)
iAlg += 1
else:
raise WrongModelException("Error in algorithm name: " +
algLine)
line = lines.readline().strip("\n").strip("\r")
except Exception, e:
if isinstance(e, WrongModelException):
raise e
else:
raise WrongModelException("Error in model definition line:" +
line.strip() + " : " +
traceback.format_exc())
def _loadAlgorithms(self):
folder = ModelerUtils.modelsFolder()
self.loadFromFolder(folder)
folder = os.path.join(os.path.dirname(__file__), "models")
self.loadFromFolder(folder)
def modelsFolder(self):
return ModelerUtils.modelsFolder()
def initializeSettings(self):
AlgorithmProvider.initializeSettings(self)
SextanteConfig.addSetting(
Setting(self.getDescription(), ModelerUtils.MODELS_FOLDER,
"Models folder", ModelerUtils.modelsFolder()))
def _loadAlgorithms(self):
folder = ModelerUtils.modelsFolder()
self.loadFromFolder(folder)
folder = os.path.join(os.path.dirname(__file__), "models")
self.loadFromFolder(folder)
def modelsFolder(self):
return ModelerUtils.modelsFolder()
def initializeSettings(self):
AlgorithmProvider.initializeSettings(self)
SextanteConfig.addSetting(Setting(self.getDescription(), ModelerUtils.MODELS_FOLDER, "Models folder", ModelerUtils.modelsFolder()))
