Python Base.exists方法代碼示例

# 需要導入模塊: from PyDbLite import Base [as 別名]
# 或者: from PyDbLite.Base import exists [as 別名]
    def __init__(self, sID, onePiece):
        today = datetime.date.today()
        self.sID = sID
        self.opp = onePiece
        self.historyDB = Base("F://alfStock//"+"alf123"+'.history')
        self.currentDB = Base("F://alfStock//"+"alf123"+'.current')
        self.historyDB.open()
        self.currentDB.open()
        db = Base("F://alfStock//"+str(today)+'.db')
        impactDB = Base("F://alfStock//"+str(today)+'.yv')
        if db.exists():
            db.open()

            recs = [ r for r in db if r['sid'] == self.sID ]
            if len(recs) > 0:

                self.history = recs[0]['history']
                self.sCurrent = recs[0]['current']
            else:
                print "already existed:  ", len(db)
                self.insertHistory(db)
        else:
            db.create('sid','history', 'current')
            self.insertHistory(db)

        if impactDB.exists():
            self.idb = impactDB
        else:
            impactDB.create('sid','UpOrDown')# U:up; D:down
            impactDB.open()
            impactDB.commit()
            self.idb = impactDB

# 需要導入模塊: from PyDbLite import Base [as 別名]
# 或者: from PyDbLite.Base import exists [as 別名]
class doAnalysis:
    
    #What do we need in init now? Ah, the analysis cache DB
    def __init__(self):
        
        self.AnalysisResults = Base('AnalysisResults/AnalysisResults.pdl')
        
        #check if the DB exists. If Yes, open, if not
        #create it:
        if not self.AnalysisResults.exists():
            self.genPDL()
        else:
            self.AnalysisResults.open()
        
        self.PassportOffice = EventPassport.EventPassportOffice()
        self.LoadWaveform = WaveformLoader.LoadWave()
        self.AcousticAnalysis = AnalysisTools.AcousticsAnalysis()
        
        self.SignalManip = SignalManip.SignalManip()
        
        
    #If DB doesnt exist, make it!
    def genPDL(self):
        #Create the PDL file for database
        self.AnalysisResults.create('EventID','PVar', mode = "open")
    
    #Gen PVAr of the Signals!
    def genPVAR(self):
        
        '''
        Filter Params.
        
        doFilter -> Filter on or OFF
        lowfreq_HP -> Low frequency High Pass
        highFreq_LP -> High Frequency low pass
        
        Set both for a band pass filter.
        
        Filter Types:
        ApplyFiltersWall -> Boxcar window
        ApplyFiltersFIR -> Kaiser Window
        '''
        
        doFilter = True
        lowFreq_HP = 3000
        highFreq_LP = None
        
        
        ####Neutron Data#####
        #get the list of events
        PVar_Neutron_List = []
        EventList = self.PassportOffice.CheckPassport_Runtype("Neutron")
        
        #For every Event
        for Event in EventList:
            
            #Load Raw data
            raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
            
            #Apply filter. See the docstring
            #for options
            if doFilter:
                filtered_data = self.AcousticAnalysis.ApplyFiltersWall(raw_data[0], lowFreq=lowFreq_HP, highFreq=highFreq_LP)
            else:
                filtered_data = raw_data[0]
            
            #Calculate PVAR
            PVar = self.AcousticAnalysis.calculatePVar(filtered_data)
            
            #PVAr > 25 were observed for events from the wall from 1 specific run!
            #We dont know what to do with those yet.
            
            #if PVar<20:
            PVar_Neutron_List.append(PVar)
                
        ##########Plotting#########
        hist_bins = numpy.arange(10,13.0,0.1)
        #hist_bins=20
        plt.hist(PVar_Neutron_List, bins=hist_bins, normed=True, facecolor='green', alpha=0.75)
        plt.grid(True)
        plt.xlabel("PVar")
        plt.ylabel("Count")
        plt.title("PVar of Entire Dataset")
        
        
        #### ALPHA DATA ####
        PVar_Alpha_List = []
        EventList = self.PassportOffice.CheckPassport_Runtype("Alpha")
        for Event in EventList:
            #get raw data
            raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
            #Apply filter. See the docstring
            #for options
            if doFilter:
                filtered_data = self.AcousticAnalysis.ApplyFiltersWall(raw_data[0], lowFreq=lowFreq_HP, highFreq=highFreq_LP)
            else:
                filtered_data = raw_data[0]
            PVar = self.AcousticAnalysis.calculatePVar(filtered_data)
            PVar_Alpha_List.append(PVar)
        
#.........這裏部分代碼省略.........

# 需要導入模塊: from PyDbLite import Base [as 別名]
# 或者: from PyDbLite.Base import exists [as 別名]
class EventPassportOffice:
    
    #what do we need in init?
    #pressure run ID number
    #acoustic ID number
    #(btw marking those separate is a bad idea on the operators part)
    def __init__(self):
        self.EventPassport = Base('EventPassport/EventPassport.pdl')
        #check if the DB exists. If Yes, open, if not
        #create it:
        if not self.EventPassport.exists():
            self.genPDL()
        else:
            self.EventPassport.open()
        
        self.CleanEvents = CleanEvents.CleanData()
        
        
    
    def genPDL(self):
        #Create the PDL file for database
        self.EventPassport.create('EventID','Temperature','Pressure','Time', 'RunNumber','Path', 'RunType', mode = "open")
        #RunNumber is defined as RunNumberAcoustic
        #Runtype can be neutron or alpha
    
    def genPassport(self, Path, RunNumberAcoustic, RunNumberPressure, RunType_WS):
        FilteredData = self.CleanEvents.MatchEvent_PressurePiezo(Path, str(RunNumberAcoustic), str(RunNumberPressure))
        
        #Get the last EventID
        recs = [ Record['EventID'] for Record in self.EventPassport if Record['RunNumber'] == RunNumberAcoustic]
        if len(recs) == 0:
            EID = str(RunNumberAcoustic)+"0001"
            EID = int(EID)
        else:
            EID = max(recs)+1
        
        #check if we have a duplicate!
        for DataPoint in FilteredData:
            timestamp =  DataPoint[1]
            #Check if we have a dupe/conflict
            x = [Event for Event in self.EventPassport if Event['Time']-timedelta(seconds=2)<=timestamp<=Event['Time']+timedelta(seconds=2)]
            if len(x) == 0:
                self.EventPassport.insert(EventID = EID ,Temperature = DataPoint[3],Pressure = DataPoint[2],Time = DataPoint[1], RunNumber = RunNumberAcoustic, Path = DataPoint[0], RunType = RunType_WS)
                EID += 1
                print("Inserting Entry ...")
            else:
                print "Duplicate entry found at: "+str(DataPoint[1])+" Event ID: "+str(x[0]['EventID'])
        
        self.EventPassport.commit()
        
    def CheckPassport_RunNumber(self, RunNumberQry):
        return self.EventPassport(RunNumber = RunNumberQry)
    def CheckPassport_Temperature(self, HighTemp, LowTemp):
        return self.EventPassport(HighTemp>Temperature>LowTemp)
    def CheckPassport_Time(self, fromTime, toTime):
        recs = [ r for r in self.EventPassport if fromTime < r['Time'] < toTime]
        return recs
    def SizeofPassportDB(self):
        return len(self.EventPassport)
    def CheckPassport_Runtype(self, runtype_WS):
        return self.EventPassport(RunType = runtype_WS)
    def CheckPassport_eventID(self, EventID_WS):
        return self.EventPassport(EventID = EventID_WS)
    def _deleteEvent(self, RecID_WS):
        del self.EventPassport[RecID_WS]
        self.EventPassport.commit()

# 需要導入模塊: from PyDbLite import Base [as 別名]
# 或者: from PyDbLite.Base import exists [as 別名]
class SignalManip:
    
    #usual stuff in init
    def __init__(self):
        self.AnalysisResults = Base('AnalysisResults/AnalysisResults.pdl')
        
        #check if the DB exists. If Yes, open, if not
        #create it:
        if not self.AnalysisResults.exists():
            self.genPDL()
        else:
            self.AnalysisResults.open()
        
        self.PassportOffice = EventPassport.EventPassportOffice()
        self.LoadWaveform = WaveformLoader.LoadWave()
        self.AcousticAnalysis = AnalysisTools.AcousticsAnalysis()
        
        
    #If DB doesnt exist, make it!
    def genPDL(self):
        #Create the PDL file for database
        self.AnalysisResults.create('EventID','PVar', mode = "open")
    
    #Function to generate signal average
    def genSignalAverage(self, EventType = "Neutron"):
        #get all Events of type EventType
        EventList = []
        EventList = self.PassportOffice.CheckPassport_Runtype(EventType)
        
        SignalAvgMem = numpy.zeros((50000))
        
        for Event in EventList:
            #Load Raw data
            raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
            SignalAvgMem += raw_data[0]
        
        SignalAvgMem /= len(EventList)
        
        ####Storage#####
        Storage = open("AnalysisResults/signalAvg."+EventType+".binary", "wb")
        SignalAvgMem.tofile(Storage, format="%f")
        Storage.close()
        
        return SignalAvgMem
    
    #function to generate FFT avergae
    def genFFTAverage(self, EventType="Neutron", doWin = False, winStart=10000, winEnd=30000, Fs = 1250000.0):
        #get all Events of type EventType
        EventList = []
        EventList = self.PassportOffice.CheckPassport_Runtype(EventType)
        
        
        
        
        FFTAvgMem = numpy.zeros((50000))
        FFTAvgBins = numpy.fft.fftfreq(len(FFTAvgMem), 1.0/Fs)
        
        
        for Event in EventList:
            #Load Raw data
            raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
            
            
             
            
            ####SignalWindow####
            if doWin:
                print "is it"
                TempSigMem = numpy.zeros((50000))
                TempSigMem[winStart:winEnd] = raw_data[0][winStart:winEnd]
                R_data = TempSigMem
            else:
                R_data = raw_data[0]
            
            #
            
            FFTs = numpy.fft.fft(R_data)
            
            #for i in range(5000,6000):
            #pwrspec = abs(numpy.mean(FFTs[5000:6000]))
            #if pwrspec>10:
            #    print pwrspec, Event
            
            
            FFTAvgMem += FFTs
        
        
        
        FFTAvgMem /= len(EventList)
        
        
        
        ####Storage#####
        #FFT#
        Storage = open("AnalysisResults/FFTAvg."+EventType+"win"+str(doWin)+".binary", "wb")
        FFTAvgMem.tofile(Storage, format="%f")
        Storage.close()
        #FFT FREQS#
        Storage = open("AnalysisResults/FFTAvgBins."+EventType+"win"+str(doWin)+".binary", "wb")
        FFTAvgBins.tofile(Storage, format="%f")
#.........這裏部分代碼省略.........

# 需要導入模塊: from PyDbLite import Base [as 別名]
# 或者: from PyDbLite.Base import exists [as 別名]
class PressureVeto:
    
    #We need the run number for init. We will use PyDBLite
    #so we need to gen the db first. There will be another
    #function for that. The reason we use this is because
    #of native python compatibility
    
    def __init__(self, RunNumber):
        #property self.RunNumber assigned.
        #This is typecasted to string for manipulation
        self.RunNumber = str(RunNumber)
        #property self.PyDB -> Database for pressures
        self.PyDB = Base('pressures/'+self.RunNumber+'.dbl')
        #check if the DB exists. If Yes, open, if not
        #create it:
        if not self.PyDB.exists():
            self.genPDL()
        else:
            self.PyDB.open()
            
        #Define the time iteration between bubbles minimum threshold
        #Remember, each iteration is 1/10th second!
        #Iter must be integer!
        minSecondsBetweenBubbles = 4
        self.minIterBetweenBubbles = int(minSecondsBetweenBubbles*10)
        
        
        
    #Funtion to generate PyDBLite database
    #I will deliberately not give this MySQL abilities
    #since I dont want my data wiped out by "mistake"
    #The human veto has to be in here somewhere.
    def genPDL(self):
    
        #Create the PDL file for database
        self.PyDB.create('id','temp','pressure','time', mode = "override")
        
        #import CSV for CSV file ops. Import ONLY if needed, so its here.
        import csv
        #filename in CSV file. Assumption -> RunID.csv
        fname_csv = self.RunNumber+".csv"
        PTcsv = csv.reader(open(fname_csv))
        
        #convert CSV to PyDB line by line
        for line in PTcsv:
            self.PyDB.insert(id = int(line[0]),temp=float(line[1]), pressure=float(line[2]), time=datetime.strptime(line[3], "%Y-%m-%d %H:%M:%S"))
        #Commit the database
        self.PyDB.commit()
        #Print a confirmation
        print "Creating PyDB complete."
    
    #this function finds the "peaks" in the pressures.
    #Criterion: Peaks are above 30 PSI
    
    def findBubbleTimings(self):
        '''Finds the bubble timings
        In -> Pressure data
        Out -> Timings (datetime.datetime)
        Assumptions -> Bubble PSI > 30 PSI
        '''
        
        #Select records with pressure > 30.0 PSI
        recs = [r for r in self.PyDB]
        #Make an iterator of this list
        RecIter = itertools.islice(recs, None)
        
        #Declare memory space for:
        #Valid Bubbles
        #Temporary Storage
        #Last Record's ID (to stop Iterator)
        ValidBubbles = []
        _VBubbleAmpTemporaryStorage = []
        RecLastID = recs[-1:][0]['__id__']
        
        #Go record by record:
        for record in RecIter:
            #If pressure > 30:
            if record['pressure'] >= 30.0:
                #Assign the temporary memory with present pressure, time
                _VBubbleAmpTemporaryStorage = [record['pressure'], record['time'], record['temp']]
                #Number of steps to iter so we dont go beyond the last rec
                stepsTillLastRec = RecLastID - record['__id__']
                stepsIter = self.minIterBetweenBubbles if ( stepsTillLastRec > self.minIterBetweenBubbles) else stepsTillLastRec
                #Investigate for next minIterBetweenBubbles for a maxima
                for i in xrange(stepsIter):
                    #Progress iterator by 1
                    record = RecIter.next()
                    #is present iteration > memory stored variable? Yes: Store it, No: Continue
                    _VBubbleAmpTemporaryStorage = [record['pressure'], record['time'], record['temp']] if record['pressure']>=_VBubbleAmpTemporaryStorage else _VBubbleAmpTemporaryStorage
                #The local maxima is found, store it as good data, continue searching
                ValidBubbles.append(_VBubbleAmpTemporaryStorage)
                #clear the temporary space
                _VBubbleAmpTemporaryStorage = []
        
        #Return the time cut!
        return ValidBubbles