genericValidation.GenericValidationData Class Reference

Inheritance diagram for genericValidation.GenericValidationData:

Public Member Functions
def	__init__
def	createCrabCfg
Public Member Functions inherited from genericValidation.GenericValidation
def	__init__
def	createConfiguration
def	createCrabCfg
def	createFiles
def	createScript
def	getCompareStrings
def	getRepMap

Public Attributes
	crabWorkingDir
	dataset
	jobmode
Public Attributes inherited from genericValidation.GenericValidation
	alignmentToValidate
	config
	configFiles
	crabConfigFiles
	filesToCompare
	general
	jobmode
	name
	randomWorkdirPart
	scriptFiles

Additional Inherited Members
Static Public Attributes inherited from genericValidation.GenericValidation
string	defaultReferenceName = "DEFAULT"

Detailed Description

Subclass of `GenericValidation` which is the base for validations using
datasets.

Definition at line 104 of file genericValidation.py.

Constructor & Destructor Documentation

def genericValidation.GenericValidationData.__init__	(		self,
			valName,
			alignment,
			config,
			valType,
			addDefaults = {},
			addMandatories = []
	)

This method adds additional items to the `self.general` dictionary
which are only needed for validations using datasets.

Arguments:
- `valName`: String which identifies individual validation instances
- `alignment`: `Alignment` instance to validate
- `config`: `BetterConfigParser` instance which includes the
    configuration of the validations
- `valType`: String which specifies the type of validation
- `addDefaults`: Dictionary which contains default values for individual
         validations in addition to the general default values
- `addMandatories`: List which contains mandatory parameters for
            individual validations in addition to the general
            mandatory parameters
            (currently there are no general mandatories)

Definition at line 111 of file genericValidation.py.

References genericValidation.GenericValidation.jobmode, entry.name, genericValidation.GenericValidation.name, alignment.Alignment.name, MuonGeometrySanityCheckPoint.name, and plotscripts.SawTeethFunction.name.

                 addDefaults = {}, addMandatories=[]):
        """
        This method adds additional items to the `self.general` dictionary
        which are only needed for validations using datasets.
        
        Arguments:
        - `valName`: String which identifies individual validation instances
        - `alignment`: `Alignment` instance to validate
        - `config`: `BetterConfigParser` instance which includes the
                    configuration of the validations
        - `valType`: String which specifies the type of validation
        - `addDefaults`: Dictionary which contains default values for individual
                         validations in addition to the general default values
        - `addMandatories`: List which contains mandatory parameters for
                            individual validations in addition to the general
                            mandatory parameters
                            (currently there are no general mandatories)
        """

        GenericValidation.__init__(self, valName, alignment, config)
        defaults = {"jobmode": self.jobmode,
                    "runRange": "",
                    "firstRun": "",
                    "lastRun": "",
                    "begin": "",
                    "end": "",
                    "JSON": ""
                    }
        defaults.update(addDefaults)
        mandatories = []
        mandatories += addMandatories
        theUpdate = config.getResultingSection(valType+":"+self.name,
                                               defaultDict = defaults,
                                               demandPars = mandatories)
        self.general.update(theUpdate)
        self.jobmode = self.general["jobmode"]

        knownOpts = defaults.keys()+mandatories
        ignoreOpts = []
        if self.jobmode.split(",")[0] == "crab" \
                or self.__class__.__name__=="OfflineValidationParallel":
            knownOpts.append("parallelJobs")
        else:
            ignoreOpts.append("parallelJobs")
        config.checkInput(valType+":"+self.name,
                          knownSimpleOptions = knownOpts,
                          ignoreOptions = ignoreOpts)

        if self.general["dataset"] not in globalDictionaries.usedDatasets:
            globalDictionaries.usedDatasets[self.general["dataset"]] = Dataset(
                self.general["dataset"] )
        self.dataset = globalDictionaries.usedDatasets[self.general["dataset"]]
        
        if not self.jobmode.split( ',' )[0] == "crab":
            try:
                self.general["datasetDefinition"] = self.dataset.datasetSnippet(
                    jsonPath = self.general["JSON"],
                    nEvents = self.general["maxevents"],
                    firstRun = self.general["firstRun"],
                    lastRun = self.general["lastRun"],
                    begin = self.general["begin"],
                    end = self.general["end"] )
            except AllInOneError, e:
                msg = "In section [%s:%s]: "%(valType, self.name)
                msg += str(e)
                raise AllInOneError(msg)
        else:
            if self.dataset.predefined():
                msg = ("For jobmode 'crab' you cannot use predefined datasets "
                       "(in your case: '%s')."%( self.dataset.name() ))
                raise AllInOneError( msg )
            try:
                theUpdate = config.getResultingSection(valType+":"+self.name,
                                                       demandPars = ["parallelJobs"])
            except AllInOneError, e:
                msg = str(e)[:-1]+" when using 'jobmode: crab'."
                raise AllInOneError(msg)
            self.general.update(theUpdate)
            if self.general["begin"] or self.general["end"]:
                ( self.general["begin"],
                  self.general["end"],
                  self.general["firstRun"],
                  self.general["lastRun"] ) = self.dataset.convertTimeToRun(
                    firstRun = self.general["firstRun"],
                    lastRun = self.general["lastRun"],
                    begin = self.general["begin"],
                    end = self.general["end"],
                    shortTuple = False)
                if self.general["begin"] == None:
                    self.general["begin"] = ""
                if self.general["end"] == None:
                    self.general["end"] = ""
                self.general["firstRun"] = str( self.general["firstRun"] )
                self.general["lastRun"] = str( self.general["lastRun"] )
            if ( not self.general["firstRun"] ) and \
                   ( self.general["end"] or self.general["lastRun"] ):
                self.general["firstRun"] = str(
                    self.dataset.runList()[0]["run_number"])
            if ( not self.general["lastRun"] ) and \
                   ( self.general["begin"] or self.general["firstRun"] ):
                self.general["lastRun"] = str(
                    self.dataset.runList()[-1]["run_number"])
            if self.general["firstRun"] and self.general["lastRun"]:
                if int(self.general["firstRun"]) > int(self.general["lastRun"]):
                    msg = ( "The lower time/runrange limit ('begin'/'firstRun') "
                            "chosen is greater than the upper time/runrange limit "
                            "('end'/'lastRun').")
                    raise AllInOneError( msg )
                self.general["runRange"] = (self.general["firstRun"]
                                            + '-' + self.general["lastRun"])
            try:
                self.general["datasetDefinition"] = self.dataset.datasetSnippet(
                    jsonPath = self.general["JSON"],
                    nEvents = self.general["maxevents"],
                    firstRun = self.general["firstRun"],
                    lastRun = self.general["lastRun"],
                    begin = self.general["begin"],
                    end = self.general["end"],
                    crab = True )
            except AllInOneError, e:
                msg = "In section [%s:%s]: "%(valType, self.name)
                msg += str( e )
                raise AllInOneError( msg )