schain Commit - r1459:52714d4d854d · Jicamarca Repository

HDFWriter writes standard Weather parameters/Now we can run a type OTHER Operation even if flagNoData is True

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schainpy/model/io/jroIO_digitalRF.py +4 0

             '''
             Created on Jul 3, 2014
             @author: roj-idl71
             '''
             # SUBCHANNELS EN VEZ DE CHANNELS
             # BENCHMARKS -> PROBLEMAS CON ARCHIVOS GRANDES -> INCONSTANTE EN EL TIEMPO
             # ACTUALIZACION DE VERSION
             # HEADERS
             # MODULO DE ESCRITURA
             # METADATA
             import os
             import time
             import datetime
             import numpy
             import timeit
             from fractions import Fraction
             from time import time
             from time import sleep
             import schainpy.admin
             from schainpy.model.data.jroheaderIO import RadarControllerHeader, SystemHeader
             from schainpy.model.data.jrodata import Voltage
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             import pickle
             try:
                 import digital_rf
             except:
                 pass
             class DigitalRFReader(ProcessingUnit):
                 '''
                 classdocs
                 '''
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     ProcessingUnit.__init__(self)
                     self.dataOut                  = Voltage()
                     self.__printInfo              = True
                     self.__flagDiscontinuousBlock = False
                     self.__bufferIndex = 9999999
                     self.__codeType    = 0
                     self.__ippKm       = None
                     self.__nCode       = None
                     self.__nBaud       = None
                     self.__code        = None
                     self.dtype         = None
                     self.oldAverage    = None
                     self.path          = None
                 def close(self):
                     print('Average of writing to digital rf format is ', self.oldAverage * 1000)
                     return
                 def __getCurrentSecond(self):
                     return self.__thisUnixSample / self.__sample_rate
                 thisSecond = property(__getCurrentSecond, "I'm the 'thisSecond' property.")
                 def __setFileHeader(self):
                     '''
                     In this method will be initialized every parameter of dataOut object (header, no data)
                     '''
                     ippSeconds = 1.0 * self.__nSamples / self.__sample_rate
                     if not self.getByBlock:
                         nProfiles = 1.0 / ippSeconds  # Number of profiles in one second
                     else:
                         nProfiles = self.nProfileBlocks # Number of profiles in one block
                     try:
                         self.dataOut.radarControllerHeaderObj = RadarControllerHeader(
                             self.__radarControllerHeader)
                     except:
                         self.dataOut.radarControllerHeaderObj = RadarControllerHeader(
                             txA=0,
                             txB=0,
                             nWindows=1,
                             nHeights=self.__nSamples,
                             firstHeight=self.__firstHeigth,
                             deltaHeight=self.__deltaHeigth,
                             codeType=self.__codeType,
                             nCode=self.__nCode, nBaud=self.__nBaud,
                             code=self.__code)
                     try:
                         self.dataOut.systemHeaderObj = SystemHeader(self.__systemHeader)
                     except:
                         self.dataOut.systemHeaderObj = SystemHeader(nSamples=self.__nSamples,
                                                                     nProfiles=nProfiles,
                                                                     nChannels=len(
                                                                         self.__channelList),
                                                                     adcResolution=14)
                     self.dataOut.type  = "Voltage"
                     self.dataOut.data  = None
                     self.dataOut.dtype = self.dtype
                     # self.dataOut.nChannels = 0
                     # self.dataOut.nHeights = 0
                     self.dataOut.nProfiles   = int(nProfiles)
                     self.dataOut.heightList  = self.__firstHeigth + \
                         numpy.arange(self.__nSamples, dtype=numpy.float) * \
                         self.__deltaHeigth
                     #self.dataOut.channelList = list(range(self.__num_subchannels))
                     self.dataOut.channelList = list(range(len(self.__channelList)))
                     if not self.getByBlock:
                         self.dataOut.blocksize   = self.dataOut.nChannels * self.dataOut.nHeights
                     else:
                         self.dataOut.blocksize   = self.dataOut.nChannels * self.dataOut.nHeights*self.nProfileBlocks
                     # self.dataOut.channelIndexList = None
                     self.dataOut.flagNoData      = True
                     if not self.getByBlock:
                         self.dataOut.flagDataAsBlock = False
                     else:
                         self.dataOut.flagDataAsBlock = True
                     # Set to TRUE if the data is discontinuous
                     self.dataOut.flagDiscontinuousBlock = False
                     self.dataOut.utctime     = None
                     # timezone like jroheader, difference in minutes between UTC and localtime
                     self.dataOut.timeZone    = self.__timezone / 60
                     self.dataOut.dstFlag     = 0
                     self.dataOut.errorCount  = 0
                     try:
                         self.dataOut.nCohInt = self.fixed_metadata_dict.get(
                             'nCohInt', self.nCohInt)
                         # asumo que la data esta decodificada
                         self.dataOut.flagDecodeData = self.fixed_metadata_dict.get(
                             'flagDecodeData', self.flagDecodeData)
                         # asumo que la data esta sin flip
                         self.dataOut.flagDeflipData = self.fixed_metadata_dict['flagDeflipData']
                         self.dataOut.flagShiftFFT   = self.fixed_metadata_dict['flagShiftFFT']
                         self.dataOut.useLocalTime   = self.fixed_metadata_dict['useLocalTime']
                     except:
                         pass
                     self.dataOut.ippSeconds = ippSeconds
                     # Time interval between profiles
                     # self.dataOut.timeInterval = self.dataOut.ippSeconds * self.dataOut.nCohInt
                     self.dataOut.frequency  = self.__frequency
                     self.dataOut.realtime   = self.__online
                 def findDatafiles(self, path, startDate=None, endDate=None):
                     if not os.path.isdir(path):
                         return []
                     try:
                         digitalReadObj = digital_rf.DigitalRFReader(
                             path, load_all_metadata=True)
                     except:
                         digitalReadObj = digital_rf.DigitalRFReader(path)
                     channelNameList    = digitalReadObj.get_channels()
                     if not channelNameList:
                         return []
                     metadata_dict      = digitalReadObj.get_rf_file_metadata(channelNameList[0])
                     sample_rate        = metadata_dict['sample_rate'][0]
                     this_metadata_file = digitalReadObj.get_metadata(channelNameList[0])
                     try:
                         timezone       = this_metadata_file['timezone'].value
                     except:
                         timezone       = 0
                     startUTCSecond, endUTCSecond = digitalReadObj.get_bounds(
                         channelNameList[0]) / sample_rate - timezone
                     startDatetime      = datetime.datetime.utcfromtimestamp(startUTCSecond)
                     endDatatime        = datetime.datetime.utcfromtimestamp(endUTCSecond)
                     if not startDate:
                         startDate      = startDatetime.date()
                     if not endDate:
                         endDate        = endDatatime.date()
                     dateList           = []
                     thisDatetime       = startDatetime
                     while(thisDatetime <= endDatatime):
                         thisDate        = thisDatetime.date()
                         if thisDate     < startDate:
                             continue
                         if thisDate     > endDate:
                             break
                         dateList.append(thisDate)
                         thisDatetime += datetime.timedelta(1)
                     return dateList
                 def setup(self, path=None,
                           startDate=None,
                           endDate=None,
                           startTime=datetime.time(0, 0, 0),
                           endTime=datetime.time(23, 59, 59),
                           channelList=None,
                           nSamples=None,
                           online=False,
                           delay=60,
                           buffer_size=1024,
                           ippKm=None,
                           nCohInt=1,
                           nCode=1,
                           nBaud=1,
                           flagDecodeData=False,
                           code=numpy.ones((1, 1), dtype=numpy.int),
                           getByBlock=0,
                           nProfileBlocks=1,
                           **kwargs):
                     '''
                     In this method we should set all initial parameters.
                     Inputs:
                         path
                         startDate
                         endDate
                         startTime
                         endTime
                         set
                         expLabel
                         ext
                         online
                         delay
                     '''
                     self.path           = path
                     self.nCohInt        = nCohInt
                     self.flagDecodeData = flagDecodeData
                     self.i              = 0
                     self.getByBlock     = getByBlock
                     self.nProfileBlocks = nProfileBlocks
                     if not os.path.isdir(path):
                         raise ValueError("[Reading] Directory %s does not exist" % path)
                     try:
                         self.digitalReadObj = digital_rf.DigitalRFReader(
                             path, load_all_metadata=True)
                     except:
                         self.digitalReadObj = digital_rf.DigitalRFReader(path)
                     channelNameList         = self.digitalReadObj.get_channels()
                     if not channelNameList:
                         raise ValueError("[Reading] Directory %s does not have any files" % path)
                     if not channelList:
                         channelList = list(range(len(channelNameList)))
                     ##########  Reading metadata ######################
                     top_properties           = self.digitalReadObj.get_properties(
                         channelNameList[channelList[0]])
                     self.__num_subchannels   = top_properties['num_subchannels']
                     self.__sample_rate       = 1.0 * \
                         top_properties['sample_rate_numerator'] / \
                         top_properties['sample_rate_denominator']
                     # self.__samples_per_file = top_properties['samples_per_file'][0]
                     self.__deltaHeigth       = 1e6 * 0.15 / self.__sample_rate  # why 0.15?
                     this_metadata_file       = self.digitalReadObj.get_digital_metadata(
                         channelNameList[channelList[0]])
                     metadata_bounds          = this_metadata_file.get_bounds()
                     self.fixed_metadata_dict = this_metadata_file.read(
                         metadata_bounds[0])[metadata_bounds[0]]  # GET FIRST HEADER
                     try:
                         self.__processingHeader      = self.fixed_metadata_dict['processingHeader']
                         self.__radarControllerHeader = self.fixed_metadata_dict['radarControllerHeader']
                         self.__systemHeader          = self.fixed_metadata_dict['systemHeader']
                         self.dtype                   = pickle.loads(self.fixed_metadata_dict['dtype'])
                     except:
                         pass
                     self.__frequency = None
                     self.__frequency = self.fixed_metadata_dict.get('frequency', 1)
                     self.__timezone = self.fixed_metadata_dict.get('timezone', 18000)
                     try:
                         nSamples = self.fixed_metadata_dict['nSamples']
                     except:
                         nSamples = None
                     self.__firstHeigth = 0
                     try:
                         codeType       = self.__radarControllerHeader['codeType']
                     except:
                         codeType       = 0
                     try:
                         if codeType:
                             nCode = self.__radarControllerHeader['nCode']
                             nBaud = self.__radarControllerHeader['nBaud']
                             code  = self.__radarControllerHeader['code']
                     except:
                         pass
                     if not ippKm:
                         try:
                             # seconds to km
                             ippKm = self.__radarControllerHeader['ipp']
                         except:
                             ippKm = None
                     ####################################################
                     self.__ippKm   = ippKm
                     startUTCSecond = None
                     endUTCSecond   = None
                     if startDate:
                         startDatetime  = datetime.datetime.combine(startDate, startTime)
                         startUTCSecond = (
                             startDatetime - datetime.datetime(1970, 1, 1)).total_seconds() + self.__timezone
                     if endDate:
                         endDatetime   = datetime.datetime.combine(endDate, endTime)
                         endUTCSecond  = (endDatetime - datetime.datetime(1970,
 , 1)).total_seconds() + self.__timezone
                     #print(startUTCSecond,endUTCSecond)
                     start_index, end_index = self.digitalReadObj.get_bounds(
                         channelNameList[channelList[0]])
                     #print("*****",start_index,end_index)
                     if not startUTCSecond:
                         startUTCSecond = start_index / self.__sample_rate
                     if start_index     > startUTCSecond * self.__sample_rate:
                         startUTCSecond = start_index / self.__sample_rate
                     if not endUTCSecond:
                         endUTCSecond   = end_index / self.__sample_rate
                     if end_index       < endUTCSecond * self.__sample_rate:
                         endUTCSecond   = end_index / self.__sample_rate #Check UTC and LT time
                     if not nSamples:
                         if not ippKm:
                             raise ValueError("[Reading] nSamples or ippKm should be defined")
                         nSamples            = int(ippKm / (1e6 * 0.15 / self.__sample_rate))
                     channelBoundList        = []
                     channelNameListFiltered = []
                     for thisIndexChannel in channelList:
                         thisChannelName        = channelNameList[thisIndexChannel]
                         start_index, end_index = self.digitalReadObj.get_bounds(
                             thisChannelName)
                         channelBoundList.append((start_index, end_index))
                         channelNameListFiltered.append(thisChannelName)
                     self.profileIndex = 0
                     self.i            = 0
                     self.__delay      = delay
                     self.__codeType   = codeType
                     self.__nCode      = nCode
                     self.__nBaud      = nBaud
                     self.__code       = code
                     self.__datapath         = path
                     self.__online           = online
                     self.__channelList      = channelList
                     self.__channelNameList  = channelNameListFiltered
                     self.__channelBoundList = channelBoundList
                     self.__nSamples         = nSamples
                     if self.getByBlock:
                         nSamples = nSamples*nProfileBlocks
                     self.__samples_to_read  = int(nSamples)  # FIJO: AHORA 40
+                    #self.__samples_to_read  = int(1000000)  # FIJO: AHORA 40
                     self.__nChannels        = len(self.__channelList)
                     #print("------------------------------------------")
                     #print("self.__samples_to_read",self.__samples_to_read)
                     #print("self.__nSamples",self.__nSamples)
                     # son iguales y el buffer_index da 0
                     self.__startUTCSecond   = startUTCSecond
                     self.__endUTCSecond     = endUTCSecond
                     self.__timeInterval     = 1.0 * self.__samples_to_read / \
                         self.__sample_rate  # Time interval
                     if online:
                         # self.__thisUnixSample = int(endUTCSecond*self.__sample_rate - 4*self.__samples_to_read)
                         startUTCSecond = numpy.floor(endUTCSecond)
                     # por que en el otro metodo lo primero q se hace es sumar samplestoread
                     self.__thisUnixSample = int(startUTCSecond * self.__sample_rate) - self.__samples_to_read
                     #self.__data_buffer    = numpy.zeros(
                     #    (self.__num_subchannels, self.__samples_to_read), dtype=numpy.complex)
                     self.__data_buffer    = numpy.zeros((int(len(channelList)), self.__samples_to_read), dtype=numpy.complex)
                     self.__setFileHeader()
                     self.isConfig = True
                     print("[Reading] Digital RF Data was found from %s to %s " % (
                         datetime.datetime.utcfromtimestamp(
                             self.__startUTCSecond - self.__timezone),
                         datetime.datetime.utcfromtimestamp(
                             self.__endUTCSecond - self.__timezone)
                     ))
                     print("[Reading] Starting process from %s to %s" % (datetime.datetime.utcfromtimestamp(startUTCSecond - self.__timezone),
                                                                         datetime.datetime.utcfromtimestamp(
                         endUTCSecond - self.__timezone)
                     ))
                     self.oldAverage    = None
                     self.count         = 0
                     self.executionTime = 0
                 def __reload(self):
                     #         print
                     #         print "%s not in range [%s, %s]" %(
                     #                                           datetime.datetime.utcfromtimestamp(self.thisSecond - self.__timezone),
                     #                                           datetime.datetime.utcfromtimestamp(self.__startUTCSecond - self.__timezone),
                     #                                           datetime.datetime.utcfromtimestamp(self.__endUTCSecond - self.__timezone)
                     #                                           )
                     print("[Reading] reloading metadata ...")
                     try:
                         self.digitalReadObj.reload(complete_update=True)
                     except:
                         self.digitalReadObj = digital_rf.DigitalRFReader(self.path)
                     start_index, end_index  = self.digitalReadObj.get_bounds(
                         self.__channelNameList[self.__channelList[0]])
                     if start_index          > self.__startUTCSecond * self.__sample_rate:
                         self.__startUTCSecond = 1.0 * start_index / self.__sample_rate
                     if end_index            > self.__endUTCSecond * self.__sample_rate:
                         self.__endUTCSecond = 1.0 * end_index / self.__sample_rate
                         print()
                         print("[Reading] New timerange found [%s, %s] " % (
                             datetime.datetime.utcfromtimestamp(
                                 self.__startUTCSecond - self.__timezone),
                             datetime.datetime.utcfromtimestamp(
                                 self.__endUTCSecond - self.__timezone)
                         ))
                         return True
                     return False
                 def timeit(self, toExecute):
                     t0                  = time.time()
                     toExecute()
                     self.executionTime  = time.time() - t0
                     if self.oldAverage is None:
                         self.oldAverage = self.executionTime
                     self.oldAverage     = (self.executionTime + self.count *
                                        self.oldAverage) / (self.count + 1.0)
                     self.count          = self.count + 1.0
                     return
                 def __readNextBlock(self, seconds=30, volt_scale=1):
                     '''
                     '''
                     # Set the next data
                     self.__flagDiscontinuousBlock = False
                     self.__thisUnixSample        += self.__samples_to_read
                     if self.__thisUnixSample + 2 * self.__samples_to_read > self.__endUTCSecond * self.__sample_rate:
                         print ("[Reading] There are no more data into selected time-range")
                         if self.__online:
                             sleep(3)
                             self.__reload()
                         else:
                             return False
                         if self.__thisUnixSample + 2 * self.__samples_to_read > self.__endUTCSecond * self.__sample_rate:
                             return False
                             self.__thisUnixSample -= self.__samples_to_read
                     indexChannel = 0
                     dataOk = False
                     for thisChannelName in self.__channelNameList:  # TODO VARIOS CHANNELS?
                         for indexSubchannel in range(self.__num_subchannels):
                             try:
                                 t0     = time()
+                                #print("Unitindex",self.__thisUnixSample)
+                                #print("__samples_to_read",self.__samples_to_read)
                                 result = self.digitalReadObj.read_vector_c81d(self.__thisUnixSample,
                                                                               self.__samples_to_read,
                                                                               thisChannelName, sub_channel=indexSubchannel)
                                 self.executionTime  = time() - t0
                                 if self.oldAverage is None:
                                     self.oldAverage = self.executionTime
                                 self.oldAverage     = (
                                     self.executionTime + self.count * self.oldAverage) / (self.count + 1.0)
                                 self.count = self.count + 1.0
                             except IOError as e:
                                 # read next profile
                                 self.__flagDiscontinuousBlock = True
                                 print("[Reading] %s" % datetime.datetime.utcfromtimestamp(self.thisSecond - self.__timezone), e)
                                 break
                             if result.shape[0] != self.__samples_to_read:
                                 self.__flagDiscontinuousBlock = True
                                 print("[Reading] %s: Too few samples were found, just %d/%d  samples" % (datetime.datetime.utcfromtimestamp(self.thisSecond - self.__timezone),
                                                                                                          result.shape[0],
                                                                                                          self.__samples_to_read))
                                 break
                             self.__data_buffer[indexChannel, :] = result * volt_scale
                             indexChannel+=1
                             dataOk       = True
                     self.__utctime       = self.__thisUnixSample / self.__sample_rate
                     if not dataOk:
                         return False
                     print("[Reading] %s: %d samples <> %f sec" % (datetime.datetime.utcfromtimestamp(self.thisSecond - self.__timezone),
                                                                   self.__samples_to_read,
                                                                   self.__timeInterval))
                     self.__bufferIndex   = 0
                     return True
                 def __isBufferEmpty(self):
                     return self.__bufferIndex > self.__samples_to_read - self.__nSamples  # 40960 - 40
                 def getData(self, seconds=30, nTries=5):
                     '''
                         This method gets the data from files and put the data into the dataOut object
                         In addition, increase el the buffer counter in one.
                         Return:
                             data    :    retorna un perfil de voltages (alturas * canales) copiados desde el
                                         buffer. Si no hay mas archivos a leer retorna None.
                         Affected:
                             self.dataOut
                             self.profileIndex
                             self.flagDiscontinuousBlock
                             self.flagIsNewBlock
                     '''
                     #print("getdata")
                     err_counter = 0
                     self.dataOut.flagNoData = True
                     if self.__isBufferEmpty():
                         #print("hi")
                         self.__flagDiscontinuousBlock = False
                         while True:
                             if self.__readNextBlock():
                                 break
                             if self.__thisUnixSample > self.__endUTCSecond * self.__sample_rate:
                                 raise schainpy.admin.SchainError('Error')
                                 return
                             if self.__flagDiscontinuousBlock:
                                 raise schainpy.admin.SchainError('discontinuous block found')
                                 return
                             if not self.__online:
                                 raise schainpy.admin.SchainError('Online?')
                                 return
                             err_counter += 1
                             if err_counter > nTries:
                                 raise schainpy.admin.SchainError('Max retrys reach')
                                 return
                             print('[Reading] waiting %d seconds to read a new block' % seconds)
                             sleep(seconds)
                         if not self.getByBlock:
                             #print("self.__bufferIndex",self.__bufferIndex)# este valor siempre es cero aparentemente
                             self.dataOut.data = self.__data_buffer[:, self.__bufferIndex:self.__bufferIndex + self.__nSamples]
                             self.dataOut.utctime = ( self.__thisUnixSample + self.__bufferIndex) / self.__sample_rate
                             self.dataOut.flagNoData = False
                             self.dataOut.flagDiscontinuousBlock = self.__flagDiscontinuousBlock
                             self.dataOut.profileIndex = self.profileIndex
                             self.__bufferIndex += self.__nSamples
                             self.profileIndex  += 1
                             if self.profileIndex == self.dataOut.nProfiles:
                                 self.profileIndex = 0
                         else:
                             # ojo debo anadir el readNextBLock y el  __isBufferEmpty(
                             self.dataOut.flagNoData             = False
                             buffer = self.__data_buffer[:,self.__bufferIndex:self.__bufferIndex + self.__samples_to_read]
+                            #print("test",self.__bufferIndex)
                             buffer = buffer.reshape((self.__nChannels, self.nProfileBlocks, int(self.__samples_to_read/self.nProfileBlocks)))
                             self.dataOut.nProfileBlocks = self.nProfileBlocks
                             self.dataOut.data = buffer
                             self.dataOut.utctime = ( self.__thisUnixSample + self.__bufferIndex) / self.__sample_rate
                             self.profileIndex  += self.__samples_to_read
                             self.__bufferIndex += self.__samples_to_read
                             self.dataOut.flagDiscontinuousBlock = self.__flagDiscontinuousBlock
                         return True
                 def printInfo(self):
                     '''
                     '''
                     if self.__printInfo == False:
                         return
                     # self.systemHeaderObj.printInfo()
                     # self.radarControllerHeaderObj.printInfo()
                     self.__printInfo = False
                 def printNumberOfBlock(self):
                     '''
                     '''
                     return
                     # print self.profileIndex
                 def run(self, **kwargs):
                     '''
                     This method will be called many times so here you should put all your code
                     '''
                     if not self.isConfig:
                         self.setup(**kwargs)
                     self.getData(seconds=self.__delay)
                     return
             @MPDecorator
             class DigitalRFWriter(Operation):
                 '''
                 classdocs
                 '''
                 def __init__(self, **kwargs):
                     '''
                     Constructor
                     '''
                     Operation.__init__(self, **kwargs)
                     self.metadata_dict = {}
                     self.dataOut       = None
                     self.dtype         = None
                     self.oldAverage    = 0
                 def setHeader(self):
                     self.metadata_dict['frequency']      = self.dataOut.frequency
                     self.metadata_dict['timezone']       = self.dataOut.timeZone
                     self.metadata_dict['dtype']          = pickle.dumps(self.dataOut.dtype)
                     self.metadata_dict['nProfiles']      = self.dataOut.nProfiles
                     self.metadata_dict['heightList']     = self.dataOut.heightList
                     self.metadata_dict['channelList']    = self.dataOut.channelList
                     self.metadata_dict['flagDecodeData'] = self.dataOut.flagDecodeData
                     self.metadata_dict['flagDeflipData'] = self.dataOut.flagDeflipData
                     self.metadata_dict['flagShiftFFT']   = self.dataOut.flagShiftFFT
                     self.metadata_dict['useLocalTime']   = self.dataOut.useLocalTime
                     self.metadata_dict['nCohInt']        = self.dataOut.nCohInt
                     self.metadata_dict['type']           = self.dataOut.type
                     self.metadata_dict['flagDataAsBlock']= getattr(
                         self.dataOut, 'flagDataAsBlock', None)  # chequear
                 def setup(self, dataOut, path, frequency, fileCadence, dirCadence, metadataCadence, set=0, metadataFile='metadata', ext='.h5'):
                     '''
                     In this method we should set all initial parameters.
                     Input:
                         dataOut: Input data will also be outputa data
                     '''
                     self.setHeader()
                     self.__ippSeconds  = dataOut.ippSeconds
                     self.__deltaH      = dataOut.getDeltaH()
                     self.__sample_rate = 1e6 * 0.15 / self.__deltaH
                     self.__dtype       = dataOut.dtype
                     if len(dataOut.dtype) == 2:
                         self.__dtype = dataOut.dtype[0]
                     self.__nSamples  = dataOut.systemHeaderObj.nSamples
                     self.__nProfiles = dataOut.nProfiles
                     if self.dataOut.type != 'Voltage':
                         raise 'Digital RF cannot be used with this data type'
                         self.arr_data = numpy.ones((1, dataOut.nFFTPoints * len(
                             self.dataOut.channelList)), dtype=[('r', self.__dtype), ('i', self.__dtype)])
                     else:
                         self.arr_data = numpy.ones((self.__nSamples, len(
                             self.dataOut.channelList)), dtype=[('r', self.__dtype), ('i', self.__dtype)])
                     file_cadence_millisecs  = 1000
                     sample_rate_fraction    = Fraction(self.__sample_rate).limit_denominator()
                     sample_rate_numerator   = int(sample_rate_fraction.numerator)
                     sample_rate_denominator = int(sample_rate_fraction.denominator)
                     start_global_index      = dataOut.utctime * self.__sample_rate
                     uuid              = 'prueba'
                     compression_level = 0
                     checksum          = False
                     is_complex        = True
                     num_subchannels   = len(dataOut.channelList)
                     is_continuous     = True
                     marching_periods  = False
                     self.digitalWriteObj = digital_rf.DigitalRFWriter(path, self.__dtype, dirCadence,
                                                                       fileCadence, start_global_index,
                                                                       sample_rate_numerator, sample_rate_denominator, uuid, compression_level, checksum,
                                                                       is_complex, num_subchannels, is_continuous, marching_periods)
                     metadata_dir         = os.path.join(path, 'metadata')
                     os.system('mkdir %s' % (metadata_dir))
                     self.digitalMetadataWriteObj = digital_rf.DigitalMetadataWriter(metadata_dir, dirCadence, 1,  # 236, file_cadence_millisecs / 1000
                                                                                     sample_rate_numerator, sample_rate_denominator,
                                                                                     metadataFile)
                     self.isConfig      = True
                     self.currentSample = 0
                     self.oldAverage    = 0
                     self.count         = 0
                     return
                 def writeMetadata(self):
                     start_idx                                   = self.__sample_rate * self.dataOut.utctime
                     self.metadata_dict['processingHeader']      = self.dataOut.processingHeaderObj.getAsDict(
                     )
                     self.metadata_dict['radarControllerHeader'] = self.dataOut.radarControllerHeaderObj.getAsDict(
                     )
                     self.metadata_dict['systemHeader']          = self.dataOut.systemHeaderObj.getAsDict(
                     )
                     self.digitalMetadataWriteObj.write(start_idx, self.metadata_dict)
                     return
                 def timeit(self, toExecute):
                     t0 = time()
                     toExecute()
                     self.executionTime  = time() - t0
                     if self.oldAverage is None:
                         self.oldAverage = self.executionTime
                     self.oldAverage     = (self.executionTime + self.count *
                                        self.oldAverage) / (self.count + 1.0)
                     self.count          = self.count + 1.0
                     return
                 def writeData(self):
                     if self.dataOut.type != 'Voltage':
                         raise 'Digital RF cannot be used with this data type'
                         for channel in self.dataOut.channelList:
                             for i in range(self.dataOut.nFFTPoints):
                                 self.arr_data[1][channel * self.dataOut.nFFTPoints +
                                                  i]['r'] = self.dataOut.data[channel][i].real
                                 self.arr_data[1][channel * self.dataOut.nFFTPoints +
                                                  i]['i'] = self.dataOut.data[channel][i].imag
                     else:
                         for i in range(self.dataOut.systemHeaderObj.nSamples):
                             for channel in self.dataOut.channelList:
                                 self.arr_data[i][channel]['r'] = self.dataOut.data[channel][i].real
                                 self.arr_data[i][channel]['i'] = self.dataOut.data[channel][i].imag
                     def f(): return self.digitalWriteObj.rf_write(self.arr_data)
                     self.timeit(f)
                     return
                 def run(self, dataOut, frequency=49.92e6, path=None, fileCadence=1000, dirCadence=36000, metadataCadence=1, **kwargs):
                     '''
                     This method will be called many times so here you should put all your code
                     Inputs:
                         dataOut: object with the data
                     '''
                     # print dataOut.__dict__
                     self.dataOut = dataOut
                     if not self.isConfig:
                         self.setup(dataOut, path, frequency, fileCadence,
                                    dirCadence, metadataCadence, **kwargs)
                         self.writeMetadata()
                     self.writeData()
                     ## self.currentSample += 1
                     # if self.dataOut.flagDataAsBlock or self.currentSample == 1:
                     # self.writeMetadata()
                     ## if self.currentSample == self.__nProfiles: self.currentSample = 0
                     return dataOut# en la version 2.7 no aparece este return
                 def close(self):
                     print('[Writing] - Closing files ')
                     print('Average of writing to digital rf format is ', self.oldAverage * 1000)
                     try:
                         self.digitalWriteObj.close()
                     except:
                         pass

schainpy/model/io/jroIO_param.py +36 -19

             import os
             import time
             import datetime
             import numpy
             import h5py
             import schainpy.admin
             from schainpy.model.data.jrodata import *
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.io.jroIO_base import *
             from schainpy.utils import log
             class HDFReader(Reader, ProcessingUnit):
                 """Processing unit to read HDF5 format files
                 This unit reads HDF5 files created with `HDFWriter` operation contains
                 by default two groups Data and Metadata all variables would be saved as `dataOut`
                 attributes.
                 It is possible to read any HDF5 file by given the structure in the `description`
                 parameter, also you can add extra values to metadata with the parameter `extras`.
                 Parameters:
                 -----------
                 path : str
                     Path where files are located.
                 startDate : date
                     Start date of the files
                 endDate : list
                     End date of the files
                 startTime : time
                     Start time of the files
                 endTime : time
                     End time of the files
                 description : dict, optional
                     Dictionary with the description of the HDF5 file
                 extras : dict, optional
                     Dictionary with extra metadata to be be added to `dataOut`
                 Examples
                 --------
                 desc = {
                     'Data': {
                         'data_output': ['u', 'v', 'w'],
                         'utctime': 'timestamps',
                     }  ,
                     'Metadata': {
                         'heightList': 'heights'
                     }
                 }
                 desc = {
                     'Data': {
                         'data_output': 'winds',
                         'utctime': 'timestamps'
                     },
                     'Metadata': {
                         'heightList': 'heights'
                     }
                 }
                 extras = {
                     'timeZone': 300
                 }
                 reader = project.addReadUnit(
                     name='HDFReader',
                     path='/path/to/files',
                     startDate='2019/01/01',
                     endDate='2019/01/31',
                     startTime='00:00:00',
                     endTime='23:59:59',
                     # description=json.dumps(desc),
                     # extras=json.dumps(extras),
                     )
                 """
                 __attrs__ = ['path', 'startDate', 'endDate', 'startTime', 'endTime', 'description', 'extras']
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Parameters()
                     self.ext = ".hdf5"
                     self.optchar = "D"
                     self.meta = {}
                     self.data = {}
                     self.open_file = h5py.File
                     self.open_mode = 'r'
                     self.description = {}
                     self.extras = {}
                     self.filefmt = "*%Y%j***"
                     self.folderfmt = "*%Y%j"
                     self.utcoffset = 0
                 def setup(self, **kwargs):
                     self.set_kwargs(**kwargs)
                     if not self.ext.startswith('.'):
                         self.ext = '.{}'.format(self.ext)
                     if self.online:
                         log.log("Searching files in online mode...", self.name)
                         for nTries in range(self.nTries):
                             fullpath = self.searchFilesOnLine(self.path, self.startDate,
                                 self.endDate, self.expLabel, self.ext, self.walk,
                                 self.filefmt, self.folderfmt)
                             try:
                                 fullpath = next(fullpath)
                             except:
                                 fullpath = None
                             if fullpath:
                                 break
                             log.warning(
                                 'Waiting {} sec for a valid file in {}: try {} ...'.format(
                                     self.delay, self.path, nTries + 1),
                                 self.name)
                             time.sleep(self.delay)
                         if not(fullpath):
                             raise schainpy.admin.SchainError(
                                 'There isn\'t any valid file in {}'.format(self.path))
                         pathname, filename = os.path.split(fullpath)
                         self.year = int(filename[1:5])
                         self.doy = int(filename[5:8])
                         self.set = int(filename[8:11]) - 1
                     else:
                         log.log("Searching files in {}".format(self.path), self.name)
                         self.filenameList = self.searchFilesOffLine(self.path, self.startDate,
                             self.endDate, self.expLabel, self.ext, self.walk, self.filefmt, self.folderfmt)
                     self.setNextFile()
                     return
                 def readFirstHeader(self):
                     '''Read metadata and data'''
                     self.__readMetadata()
                     self.__readData()
                     self.__setBlockList()
                     if 'type' in self.meta:
                         self.dataOut = eval(self.meta['type'])()
                     for attr in self.meta:
                         setattr(self.dataOut, attr, self.meta[attr])
                     self.blockIndex = 0
                     return
                 def __setBlockList(self):
                     '''
                     Selects the data within the times defined
                     self.fp
                     self.startTime
                     self.endTime
                     self.blockList
                     self.blocksPerFile
                     '''
                     startTime = self.startTime
                     endTime = self.endTime
                     thisUtcTime = self.data['utctime'] + self.utcoffset
                     self.interval = numpy.min(thisUtcTime[1:] - thisUtcTime[:-1])
                     thisDatetime = datetime.datetime.utcfromtimestamp(thisUtcTime[0])
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     startUtcTime = (datetime.datetime.combine(thisDate, startTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     endUtcTime = (datetime.datetime.combine(thisDate, endTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     ind = numpy.where(numpy.logical_and(thisUtcTime >= startUtcTime, thisUtcTime < endUtcTime))[0]
                     self.blockList = ind
                     self.blocksPerFile = len(ind)
                     return
                 def __readMetadata(self):
                     '''
                     Reads Metadata
                     '''
                     meta = {}
                     if self.description:
                         for key, value in self.description['Metadata'].items():
                             meta[key] = self.fp[value][()]
                     else:
                         grp = self.fp['Metadata']
                         for name in grp:
                             meta[name] = grp[name][()]
                     if self.extras:
                         for key, value in self.extras.items():
                             meta[key] = value
                     self.meta = meta
                     return
                 def __readData(self):
                     data = {}
                     if self.description:
                         for key, value in self.description['Data'].items():
                             if isinstance(value, str):
                                 if isinstance(self.fp[value], h5py.Dataset):
                                     data[key] = self.fp[value][()]
                                 elif isinstance(self.fp[value], h5py.Group):
                                     array = []
                                     for ch in self.fp[value]:
                                         array.append(self.fp[value][ch][()])
                                     data[key] = numpy.array(array)
                             elif isinstance(value, list):
                                 array = []
                                 for ch in value:
                                     array.append(self.fp[ch][()])
                                 data[key] = numpy.array(array)
                     else:
                         grp = self.fp['Data']
                         for name in grp:
                             if isinstance(grp[name], h5py.Dataset):
                                 array = grp[name][()]
                             elif isinstance(grp[name], h5py.Group):
                                 array = []
                                 for ch in grp[name]:
                                     array.append(grp[name][ch][()])
                                 array = numpy.array(array)
                             else:
                                 log.warning('Unknown type: {}'.format(name))
                             if name in self.description:
                                 key = self.description[name]
                             else:
                                 key = name
                             data[key] = array
                     self.data = data
                     return
                 def getData(self):
                     for attr in self.data:
                         if self.data[attr].ndim == 1:
                             setattr(self.dataOut, attr, self.data[attr][self.blockIndex])
                         else:
                             setattr(self.dataOut, attr, self.data[attr][:, self.blockIndex])
                     self.dataOut.flagNoData = False
                     self.blockIndex += 1
                     log.log("Block No. {}/{} -> {}".format(
                         self.blockIndex,
                         self.blocksPerFile,
                         self.dataOut.datatime.ctime()), self.name)
                     return
                 def run(self, **kwargs):
                     if not(self.isConfig):
                         self.setup(**kwargs)
                         self.isConfig = True
                     if self.blockIndex == self.blocksPerFile:
                         self.setNextFile()
                     self.getData()
                     return
             @MPDecorator
             class HDFWriter(Operation):
                 """Operation to write HDF5 files.
                 The HDF5 file contains by default two groups Data and Metadata where
                 you can save any `dataOut` attribute specified by `dataList` and `metadataList`
                 parameters, data attributes are normaly time dependent where the metadata
                 are not.
                 It is possible to customize the structure of the HDF5 file with the
                 optional description parameter see the examples.
                 Parameters:
                 -----------
                 path : str
                     Path where files will be saved.
                 blocksPerFile : int
                     Number of blocks per file
                 metadataList : list
                     List of the dataOut attributes that will be saved as metadata
                 dataList : int
                     List of the dataOut attributes that will be saved as data
                 setType : bool
                     If True the name of the files corresponds to the timestamp of the data
                 description : dict, optional
                     Dictionary with the desired description of the HDF5 file
                 Examples
                 --------
                 desc = {
                     'data_output': {'winds': ['z', 'w', 'v']},
                     'utctime': 'timestamps',
                     'heightList': 'heights'
                 }
                 desc = {
                     'data_output': ['z', 'w', 'v'],
                     'utctime': 'timestamps',
                     'heightList': 'heights'
                 }
                 desc = {
                     'Data': {
                         'data_output': 'winds',
                         'utctime': 'timestamps'
                     },
                     'Metadata': {
                         'heightList': 'heights'
                     }
                 }
                 writer = proc_unit.addOperation(name='HDFWriter')
                 writer.addParameter(name='path', value='/path/to/file')
                 writer.addParameter(name='blocksPerFile', value='32')
                 writer.addParameter(name='metadataList', value='heightList,timeZone')
                 writer.addParameter(name='dataList',value='data_output,utctime')
                 # writer.addParameter(name='description',value=json.dumps(desc))
                 """
                 ext = ".hdf5"
                 optchar = "D"
                 filename = None
                 path = None
                 setFile = None
                 fp = None
                 firsttime = True
                 #Configurations
                 blocksPerFile = None
                 blockIndex = None
                 dataOut = None
                 #Data Arrays
                 dataList = None
                 metadataList = None
                 currentDay = None
                 lastTime = None
                 last_Azipos = None
                 last_Elepos = None
                 mode       = None
                 #-----------------------
                 Typename = None
                 def __init__(self):
                     Operation.__init__(self)
                     return
                 def set_kwargs(self, **kwargs):
                     for key, value in kwargs.items():
                         setattr(self, key, value)
                 def set_kwargs_obj(self,obj, **kwargs):
                     for key, value in kwargs.items():
                         setattr(obj, key, value)
                 def generalFlag(self):
                     ####rint("GENERALFLAG")
                     if self.mode== "weather":
                         if self.last_Azipos == None:
                             tmp = self.dataOut.azimuth
                             ####print("ang azimuth writer",tmp)
                             self.last_Azipos = tmp
                             flag = False
                             return flag
                         ####print("ang_azimuth writer",self.dataOut.azimuth)
                         result = self.dataOut.azimuth - self.last_Azipos
                         self.last_Azipos = self.dataOut.azimuth
                         if result<0:
                             flag = True
                             return flag
                 def generalFlag_vRF(self):
                     ####rint("GENERALFLAG")
                     try:
                         self.dataOut.flagBlock360Done
                         return self.dataOut.flagBlock360Done
                     except:
                         return 0
                 def setup(self, path=None, blocksPerFile=10, metadataList=None, dataList=None, setType=None, description=None,type_data=None,**kwargs):
                     self.path = path
                     self.blocksPerFile = blocksPerFile
                     self.metadataList = metadataList
                     self.dataList = [s.strip() for s in dataList]
                     self.setType = setType
                     if self.mode == "weather":
                         self.setType = "weather"
                         self.set_kwargs(**kwargs)
                         self.set_kwargs_obj(self.dataOut,**kwargs)
                     self.description = description
                     self.type_data=type_data
                     if self.metadataList is None:
                         self.metadataList = self.dataOut.metadata_list
                     tableList = []
                     dsList = []
                     for i in range(len(self.dataList)):
                         dsDict = {}
                         if hasattr(self.dataOut, self.dataList[i]):
                             dataAux = getattr(self.dataOut, self.dataList[i])
                             dsDict['variable'] = self.dataList[i]
                         else:
                             log.warning('Attribute {} not found in dataOut', self.name)
                             continue
                         if dataAux is None:
                             continue
                         elif isinstance(dataAux, (int, float, numpy.integer, numpy.float)):
                             dsDict['nDim'] = 0
                         else:
                             dsDict['nDim'] = len(dataAux.shape)
                             dsDict['shape'] = dataAux.shape
                             dsDict['dsNumber'] = dataAux.shape[0]
                             dsDict['dtype'] = dataAux.dtype
                         dsList.append(dsDict)
                     self.dsList = dsList
                     self.currentDay = self.dataOut.datatime.date()
                 def timeFlag(self):
                     currentTime = self.dataOut.utctime
                     timeTuple = time.localtime(currentTime)
                     dataDay = timeTuple.tm_yday
                     if self.lastTime is None:
                         self.lastTime = currentTime
                         self.currentDay = dataDay
                         return False
                     timeDiff = currentTime - self.lastTime
                     #Si el dia es diferente o si la diferencia entre un dato y otro supera la hora
                     if dataDay != self.currentDay:
                         self.currentDay = dataDay
                         return True
                     elif timeDiff > 3*60*60:
                         self.lastTime = currentTime
                         return True
                     else:
                         self.lastTime = currentTime
                         return False
                 def run(self, dataOut, path, blocksPerFile=10, metadataList=None,
                         dataList=[], setType=None, description={},mode= None,type_data=None,Reset = False,**kwargs):
                     if Reset:
                         self.isConfig = False
                         self.closeFile()
                         self.lastTime = None
                         self.blockIndex = 0
                     self.dataOut = dataOut
                     self.mode    = mode
+                    self.var = dataList[0]
                     if not(self.isConfig):
                         self.setup(path=path, blocksPerFile=blocksPerFile,
                                    metadataList=metadataList, dataList=dataList,
                                    setType=setType, description=description,type_data=type_data,**kwargs)
                         self.isConfig = True
                         self.setNextFile()
                     self.putData()
                     return
                 def setNextFile(self):
                     ###print("HELLO WORLD--------------------------------")
                     ext = self.ext
                     path = self.path
                     setFile = self.setFile
                     type_data = self.type_data
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join(path, subfolder)
                     if os.path.exists(fullpath):
                         filesList = os.listdir(fullpath)
                         filesList = [k for k in filesList if k.startswith(self.optchar)]
                         if len( filesList ) > 0:
                             filesList = sorted(filesList, key=str.lower)
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber(filen[8:11]):
                                 setFile = int(filen[8:11]) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 setFile = -1
                         else:
                             setFile = -1 #inicializo mi contador de seteo
                     else:
                         os.makedirs(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     ###print("**************************",self.setType)
                     if self.setType is None:
                         setFile += 1
                         file = '%s%4.4d%3.3d%03d%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     elif self.setType == "weather":
-                          print("HOLA AMIGOS")
-                          wr_exp = self.dataOut.wr_exp
-                          if wr_exp== "PPI":
-                              wr_type = 'E'
-                              ang_    = numpy.mean(self.dataOut.elevation)
-                          else:
-                              wr_type = 'A'
-                              ang_    = numpy.mean(self.dataOut.azimuth)
-                          wr_writer = '%s%s%2.1f%s'%('-',
+                        if self.var.lower() == 'Zdb'.lower():
-                                                     wr_type,
+                            wr_type = 'Z'
+                        elif self.var.lower() == 'Zdb_D'.lower():
+                            wr_type = 'D'
+                        elif self.var.lower() == 'PhiD_P'.lower():
+                            wr_type = 'P'
+                        elif self.var.lower() == 'RhoHV_R'.lower():
+                            wr_type = 'R'
+                        elif self.var.lower() == 'velRadial_V'.lower():
+                            wr_type = 'V'
+                        elif self.var.lower() == 'Sigmav_W'.lower():
+                            wr_type = 'S'
+                        elif self.var.lower() == 'dataPP_POWER'.lower():
+                            wr_type = 'Pow'
+                        elif self.var.lower() == 'dataPP_DOP'.lower():
+                            wr_type = 'Dop'
+                        #Z_SOPHy_El10.0_20200505_14:02:15.h5
+                        #Z_SOPHy_Az40.0_20200505_14:02:15.h5
+                        if self.dataOut.flagMode == 1: #'AZI' #PPI
+                            ang_type = 'El'
+                            ang_    = round(numpy.mean(self.dataOut.data_ele),1)
+                        elif self.dataOut.flagMode == 0: #'ELE' #RHI
+                            ang_type = 'Az'
+                            ang_    = round(numpy.mean(self.dataOut.data_azi),1)
+                        file = '%s%s%s%2.1f%s%2.2d%2.2d%2.2d%s%2.2d%2.2d%2.2d%s' % (wr_type,
+                                                       '_SOPHy_',
+                                                       ang_type,
                                                        ang_,
-                                                     '-')
+                                                       '_',
-                          ###print("wr_writer********************",wr_writer)
-                          file = '%s%4.4d%2.2d%2.2d%s%2.2d%2.2d%2.2d%s%s%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_mon,
                                                        timeTuple.tm_mday,
-                                                           '-',
+                                                       '_',
                                                        timeTuple.tm_hour,
                                                        timeTuple.tm_min,
                                                        timeTuple.tm_sec,
-                                                           wr_writer,
-                                                           type_data,
                                                        ext )
-                          ###print("FILENAME", file)
                     else:
                         setFile = timeTuple.tm_hour*60+timeTuple.tm_min
                         file = '%s%4.4d%3.3d%04d%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     self.filename = os.path.join( path, subfolder, file )
                     #Setting HDF5 File
+                    print("filename",self.filename)
                     self.fp = h5py.File(self.filename, 'w')
                     #write metadata
                     self.writeMetadata(self.fp)
                     #Write data
                     self.writeData(self.fp)
                 def getLabel(self, name, x=None):
                     if x is None:
                         if 'Data' in self.description:
                             data = self.description['Data']
                             if 'Metadata' in self.description:
                                 data.update(self.description['Metadata'])
                         else:
                             data = self.description
                         if name in data:
                             if isinstance(data[name], str):
                                 return data[name]
                             elif isinstance(data[name], list):
                                 return None
                             elif isinstance(data[name], dict):
                                 for key, value in data[name].items():
                                     return key
                         return name
                     else:
                         if 'Metadata' in self.description:
                             meta = self.description['Metadata']
                         else:
                             meta = self.description
                         if name in meta:
                             if isinstance(meta[name], list):
                                 return meta[name][x]
                             elif isinstance(meta[name], dict):
                                 for key, value in meta[name].items():
                                     return value[x]
                         if 'cspc' in name:
                             return 'pair{:02d}'.format(x)
                         else:
                             return 'channel{:02d}'.format(x)
                 def writeMetadata(self, fp):
                     if self.description:
                         if 'Metadata' in self.description:
                             grp = fp.create_group('Metadata')
                         else:
                             grp = fp
                     else:
                         grp = fp.create_group('Metadata')
                     for i in range(len(self.metadataList)):
                         if not hasattr(self.dataOut, self.metadataList[i]):
                             log.warning('Metadata: `{}` not found'.format(self.metadataList[i]), self.name)
                             continue
                         value = getattr(self.dataOut, self.metadataList[i])
                         if isinstance(value, bool):
                             if value is True:
                                 value = 1
                             else:
                                 value = 0
                         grp.create_dataset(self.getLabel(self.metadataList[i]), data=value)
                     return
                 def writeData(self, fp):
                     if self.description:
                         if 'Data' in self.description:
                             grp = fp.create_group('Data')
                         else:
                             grp = fp
                     else:
                         grp = fp.create_group('Data')
                     dtsets = []
                     data = []
                     for dsInfo in self.dsList:
                         if dsInfo['nDim'] == 0:
                             ds = grp.create_dataset(
                                 self.getLabel(dsInfo['variable']),
                                 (self.blocksPerFile, ),
                                 chunks=True,
                                 dtype=numpy.float64)
                             dtsets.append(ds)
                             data.append((dsInfo['variable'], -1))
                         else:
                             label = self.getLabel(dsInfo['variable'])
                             if label is not None:
                                 sgrp = grp.create_group(label)
                             else:
                                 sgrp = grp
                             for i in range(dsInfo['dsNumber']):
                                 ds = sgrp.create_dataset(
                                     self.getLabel(dsInfo['variable'], i),
                                     (self.blocksPerFile, ) + dsInfo['shape'][1:],
                                     chunks=True,
                                     dtype=dsInfo['dtype'])
                                 dtsets.append(ds)
                                 data.append((dsInfo['variable'], i))
                     fp.flush()
                     log.log('Creating file: {}'.format(fp.filename), self.name)
                     self.ds = dtsets
                     self.data = data
                     self.firsttime = True
                     self.blockIndex = 0
                     return
                 def putData(self):
                     if (self.blockIndex == self.blocksPerFile) or self.timeFlag():# or self.generalFlag_vRF():
                         self.closeFile()
                         self.setNextFile()
                     for i, ds in enumerate(self.ds):
                         attr, ch = self.data[i]
                         if ch == -1:
                             ds[self.blockIndex] = getattr(self.dataOut, attr)
                         else:
                             ds[self.blockIndex] = getattr(self.dataOut, attr)[ch]
                     self.fp.flush()
                     self.blockIndex += 1
                     log.log('Block No. {}/{}'.format(self.blockIndex, self.blocksPerFile), self.name)
                     return
                 def closeFile(self):
                     if self.blockIndex != self.blocksPerFile:
                         for ds in self.ds:
                             ds.resize(self.blockIndex, axis=0)
                     if self.fp:
                         self.fp.flush()
                         self.fp.close()
                 def close(self):
                     self.closeFile()

schainpy/model/proc/jroproc_base.py +11 -1

             '''
             Base clases to create Processing units and operations, the MPDecorator
             must be used in plotting and writing operations to allow to run as an
             external process.
             '''
             import os
             import inspect
             import zmq
             import time
             import pickle
             import traceback
             from threading import Thread
             from multiprocessing import Process, Queue
             from schainpy.utils import log
             QUEUE_SIZE = int(os.environ.get('QUEUE_MAX_SIZE', '10'))
             class ProcessingUnit(object):
                 '''
                 Base class to create Signal Chain Units
                 '''
                 proc_type = 'processing'
                 def __init__(self):
                     self.dataIn = None
                     self.dataOut = None
                     self.isConfig = False
                     self.operations = []
                     self.name = 'Test'
                     self.inputs = []
                 def setInput(self, unit):
                     attr = 'dataIn'
                     for i, u in enumerate(unit):
                         if i==0:
                             self.dataIn = u.dataOut
                             self.inputs.append('dataIn')
                         else:
                             setattr(self, 'dataIn{}'.format(i), u.dataOut)
                             self.inputs.append('dataIn{}'.format(i))
                 def getAllowedArgs(self):
                     if hasattr(self, '__attrs__'):
                         return self.__attrs__
                     else:
                         return inspect.getargspec(self.run).args
                 def addOperation(self, conf, operation):
                     '''
                     '''
                     self.operations.append((operation, conf.type, conf.getKwargs()))
                 def getOperationObj(self, objId):
                     if objId not in list(self.operations.keys()):
                         return None
                     return self.operations[objId]
                 def call(self, **kwargs):
                     '''
                     '''
                     try:
                         if self.dataIn is not None and self.dataIn.flagNoData and not self.dataIn.error:
                             return self.dataIn.isReady()
                         elif self.dataIn is None or not self.dataIn.error:
                             self.run(**kwargs)
                         elif self.dataIn.error:
                             self.dataOut.error = self.dataIn.error
                             self.dataOut.flagNoData = True
                     except:
                         err = traceback.format_exc()
                         if 'SchainWarning' in err:
                             log.warning(err.split('SchainWarning:')[-1].split('\n')[0].strip(), self.name)
                         elif 'SchainError' in err:
                             log.error(err.split('SchainError:')[-1].split('\n')[0].strip(), self.name)
                         else:
                             log.error(err, self.name)
                         self.dataOut.error = True
                     ##### correcion de la declaracion Out
                     for op, optype, opkwargs in self.operations:
                         aux = self.dataOut.copy()
-                        if optype == 'other' and not self.dataOut.flagNoData:
+                        '''
+                        print("op",op)
+                        try:
+                            print("runNextOp",self.dataOut.runNextOp)
+                        except:
+                            pass
+                            '''
+                        if not hasattr(self.dataOut, 'runNextOp'):
+                            self.dataOut.runNextOp = False
+                        if optype == 'other' and (not self.dataOut.flagNoData or self.dataOut.runNextOp):
+                        #if optype == 'other' and not self.dataOut.flagNoData:
                             self.dataOut = op.run(self.dataOut, **opkwargs)
                         elif optype == 'external' and not self.dataOut.flagNoData:
                             #op.queue.put(self.dataOut)
                             op.queue.put(aux)
                         elif optype == 'external' and self.dataOut.error:
                             #op.queue.put(self.dataOut)
                             op.queue.put(aux)
                     try:
                         if self.dataOut.runNextUnit:
                             runNextUnit = self.dataOut.runNextUnit
                         else:
                             runNextUnit = self.dataOut.isReady()
                     except:
                         runNextUnit = self.dataOut.isReady()
                     return 'Error' if self.dataOut.error else runNextUnit
                 def setup(self):
                     raise NotImplementedError
                 def run(self):
                     raise NotImplementedError
                 def close(self):
                     return
             class Operation(object):
                 '''
                 '''
                 proc_type = 'operation'
                 def __init__(self):
                     self.id = None
                     self.isConfig = False
                     if not hasattr(self, 'name'):
                         self.name = self.__class__.__name__
                 def getAllowedArgs(self):
                     if hasattr(self, '__attrs__'):
                         return self.__attrs__
                     else:
                         return inspect.getargspec(self.run).args
                 def setup(self):
                     self.isConfig = True
                     raise NotImplementedError
                 def run(self, dataIn, **kwargs):
                     """
                     Realiza las operaciones necesarias sobre la dataIn.data y actualiza los
                     atributos del objeto dataIn.
                     Input:
                         dataIn    :    objeto del tipo JROData
                     Return:
                         None
                     Affected:
                         __buffer    :    buffer de recepcion de datos.
                     """
                     if not self.isConfig:
                         self.setup(**kwargs)
                     raise NotImplementedError
                 def close(self):
                     return
             def MPDecorator(BaseClass):
                 """
                 Multiprocessing class decorator
                 This function add multiprocessing features to a BaseClass.
                 """
                 class MPClass(BaseClass, Process):
                     def __init__(self, *args, **kwargs):
                         super(MPClass, self).__init__()
                         Process.__init__(self)
                         self.args = args
                         self.kwargs = kwargs
                         self.t = time.time()
                         self.op_type = 'external'
                         self.name = BaseClass.__name__
                         self.__doc__ = BaseClass.__doc__
                         if 'plot' in self.name.lower() and not self.name.endswith('_'):
                             self.name = '{}{}'.format(self.CODE.upper(), 'Plot')
                         self.start_time = time.time()
                         self.err_queue = args[3]
                         self.queue = Queue(maxsize=QUEUE_SIZE)
                         self.myrun = BaseClass.run
                     def run(self):
                         while True:
                             dataOut = self.queue.get()
                             if not dataOut.error:
                                 try:
                                     BaseClass.run(self, dataOut, **self.kwargs)
                                 except:
                                     err = traceback.format_exc()
                                     log.error(err, self.name)
                             else:
                                 break
                         self.close()
                     def close(self):
                         BaseClass.close(self)
                         log.success('Done...(Time:{:4.2f} secs)'.format(time.time()-self.start_time), self.name)
                 return MPClass

schainpy/model/proc/jroproc_parameters.py 0 0

	1	NO CONTENT: modified file			NO CONTENT: modified file
The requested commit or file is too big and content was truncated. Show full diff

schainpy/model/proc/jroproc_voltage.py +3 -2

             import sys
             import numpy,math
             from scipy import interpolate
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon
             from schainpy.utils import log
             from time import time
             class VoltageProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Voltage()
                     self.flip = 1
                     self.setupReq = False
                 def run(self):
                     if self.dataIn.type == 'AMISR':
                         self.__updateObjFromAmisrInput()
                     if self.dataIn.type == 'Voltage':
                         self.dataOut.copy(self.dataIn)
                 def __updateObjFromAmisrInput(self):
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.dstFlag = self.dataIn.dstFlag
                     self.dataOut.errorCount = self.dataIn.errorCount
                     self.dataOut.useLocalTime = self.dataIn.useLocalTime
                     self.dataOut.flagNoData = self.dataIn.flagNoData
                     self.dataOut.data = self.dataIn.data
                     self.dataOut.utctime = self.dataIn.utctime
                     self.dataOut.channelList = self.dataIn.channelList
                     #self.dataOut.timeInterval = self.dataIn.timeInterval
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.nProfiles = self.dataIn.nProfiles
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.azimuth = self.dataIn.azimuth
                     self.dataOut.zenith = self.dataIn.zenith
                     self.dataOut.beam.codeList = self.dataIn.beam.codeList
                     self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
                     self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
             class selectChannels(Operation):
                 def run(self, dataOut, channelList):
                     channelIndexList = []
                     self.dataOut = dataOut
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList)))
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                     return self.dataOut
                 def selectChannelsByIndex(self, channelIndexList):
                     """
                     Selecciona un bloque de datos en base a canales segun el channelIndexList
                     Input:
                         channelIndexList    :    lista sencilla de canales a seleccionar por ej. [2,3,7]
                     Affected:
                         self.dataOut.data
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                         self.dataOut.m_ProcessingHeader.totalSpectra
                         self.dataOut.systemHeaderObj.numChannels
                         self.dataOut.m_ProcessingHeader.blockSize
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError("The value %d in channelIndexList is not valid" %channelIndex)
                     if self.dataOut.type == 'Voltage':
                         if self.dataOut.flagDataAsBlock:
                             """
                             Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                             """
                             data = self.dataOut.data[channelIndexList,:,:]
                         else:
                             data = self.dataOut.data[channelIndexList,:]
                         self.dataOut.data = data
                         # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                         self.dataOut.channelList = range(len(channelIndexList))
                     elif self.dataOut.type == 'Spectra':
                         data_spc = self.dataOut.data_spc[channelIndexList, :]
                         data_dc = self.dataOut.data_dc[channelIndexList, :]
                         self.dataOut.data_spc = data_spc
                         self.dataOut.data_dc = data_dc
                         # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                         self.dataOut.channelList = range(len(channelIndexList))
                         self.__selectPairsByChannel(channelIndexList)
                     return 1
                 def __selectPairsByChannel(self, channelList=None):
                     if channelList == None:
                         return
                     pairsIndexListSelected = []
                     for pairIndex in self.dataOut.pairsIndexList:
                         # First pair
                         if self.dataOut.pairsList[pairIndex][0] not in channelList:
                             continue
                         # Second pair
                         if self.dataOut.pairsList[pairIndex][1] not in channelList:
                             continue
                         pairsIndexListSelected.append(pairIndex)
                     if not pairsIndexListSelected:
                         self.dataOut.data_cspc = None
                         self.dataOut.pairsList = []
                         return
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
                     self.dataOut.pairsList = [self.dataOut.pairsList[i]
                                               for i in pairsIndexListSelected]
                     return
             class selectHeights(Operation):
                 def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     self.dataOut = dataOut
                     if minHei and maxHei:
                         if (minHei < self.dataOut.heightList[0]):
                             minHei = self.dataOut.heightList[0]
                         if (maxHei > self.dataOut.heightList[-1]):
                             maxHei = self.dataOut.heightList[-1]
                         minIndex = 0
                         maxIndex = 0
                         heights = self.dataOut.heightList
                         inda = numpy.where(heights >= minHei)
                         indb = numpy.where(heights <= maxHei)
                         try:
                             minIndex = inda[0][0]
                         except:
                             minIndex = 0
                         try:
                             maxIndex = indb[0][-1]
                         except:
                             maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return self.dataOut
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if self.dataOut.type == 'Voltage':
                         if (minIndex < 0) or (minIndex > maxIndex):
                             raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex))
                         if (maxIndex >= self.dataOut.nHeights):
                             maxIndex = self.dataOut.nHeights
                         #print("shapeeee",self.dataOut.data.shape)
                         #voltage
                         if self.dataOut.flagDataAsBlock:
                             """
                             Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                             """
                             data = self.dataOut.data[:,:, minIndex:maxIndex]
                         else:
                             data = self.dataOut.data[:, minIndex:maxIndex]
                         #         firstHeight = self.dataOut.heightList[minIndex]
                         self.dataOut.data = data
                         self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex]
                         if self.dataOut.nHeights <= 1:
                             raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights))
                     elif self.dataOut.type == 'Spectra':
                         if (minIndex < 0) or (minIndex > maxIndex):
                             raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (
                                 minIndex, maxIndex))
                         if (maxIndex >= self.dataOut.nHeights):
                             maxIndex = self.dataOut.nHeights - 1
                         # Spectra
                         data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1]
                         data_cspc = None
                         if self.dataOut.data_cspc is not None:
                             data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1]
                         data_dc = None
                         if self.dataOut.data_dc is not None:
                             data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1]
                         self.dataOut.data_spc = data_spc
                         self.dataOut.data_cspc = data_cspc
                         self.dataOut.data_dc = data_dc
                         self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1]
                     return 1
             class filterByHeights(Operation):
                 def run(self, dataOut, window):
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     if window == None:
                         window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
                     newdelta = deltaHeight * window
                     r = dataOut.nHeights % window
                     newheights = (dataOut.nHeights-r)/window
                     if newheights <= 1:
                         raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window))
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)]
                         buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window)
                         buffer = numpy.sum(buffer,3)
                     else:
                         buffer = dataOut.data[:,0:int(dataOut.nHeights-r)]
                         buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window))
                         buffer = numpy.sum(buffer,2)
                     dataOut.data = buffer
                     dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta
                     dataOut.windowOfFilter = window
                     return dataOut
             class setH0(Operation):
                 def run(self, dataOut, h0, deltaHeight = None):
                     if not deltaHeight:
                         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     nHeights = dataOut.nHeights
                     newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight
                     dataOut.heightList = newHeiRange
                     return dataOut
             class deFlip(Operation):
                 def run(self, dataOut, channelList = []):
                     data = dataOut.data.copy()
                     if dataOut.flagDataAsBlock:
                         flip = self.flip
                         profileList = list(range(dataOut.nProfiles))
                         if not channelList:
                             for thisProfile in profileList:
                                 data[:,thisProfile,:] = data[:,thisProfile,:]*flip
                                 flip *= -1.0
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in dataOut.channelList:
                                     continue
                                 for thisProfile in profileList:
                                     data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip
                                     flip *= -1.0
                         self.flip = flip
                     else:
                         if not channelList:
                             data[:,:] = data[:,:]*self.flip
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in dataOut.channelList:
                                     continue
                                 data[thisChannel,:] = data[thisChannel,:]*self.flip
                         self.flip *= -1.
                     dataOut.data = data
                     return dataOut
             class setAttribute(Operation):
                 '''
                 Set an arbitrary attribute(s) to dataOut
                 '''
                 def __init__(self):
                     Operation.__init__(self)
                     self._ready = False
                 def run(self, dataOut, **kwargs):
                     for key, value in kwargs.items():
                         setattr(dataOut, key, value)
                     return dataOut
             @MPDecorator
             class printAttribute(Operation):
                 '''
                 Print an arbitrary attribute of dataOut
                 '''
                 def __init__(self):
                     Operation.__init__(self)
                 def run(self, dataOut, attributes):
                     if isinstance(attributes, str):
                         attributes = [attributes]
                     for attr in attributes:
                         if hasattr(dataOut, attr):
                             log.log(getattr(dataOut, attr), attr)
             class interpolateHeights(Operation):
                 def run(self, dataOut, topLim, botLim):
                     #69 al 72 para julia
                     #82-84 para meteoros
                     if len(numpy.shape(dataOut.data))==2:
                         sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2
                         sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1)))
                         #dataOut.data[:,botLim:limSup+1] = sampInterp
                         dataOut.data[:,botLim:topLim+1] = sampInterp
                     else:
                         nHeights = dataOut.data.shape[2]
                         x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights)))
                         y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))]
                         f = interpolate.interp1d(x, y, axis = 2)
                         xnew = numpy.arange(botLim,topLim+1)
                         ynew = f(xnew)
                         dataOut.data[:,:,botLim:topLim+1]  = ynew
                     return dataOut
             class CohInt(Operation):
                 isConfig = False
                 __profIndex = 0
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __bufferStride = []
                 __dataReady = False
                 __profIndexStride = 0
                 __dataToPutStride = False
                 n = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n               :    Number of coherent integrations
                         timeInterval    :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping     :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer = None
                     self.__dataReady = False
                     self.byblock = byblock
                     self.stride = stride
                     if n == None and timeInterval == None:
                         raise ValueError("n or timeInterval should be specified ...")
                     if n != None:
                         self.n = n
                         self.__byTime = False
                     else:
                         self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverlapping = True
                         self.__buffer = None
                     else:
                         self.__withOverlapping = False
                         self.__buffer = 0
                     self.__profIndex = 0
                 def putData(self, data):
                     """
                     Add a profile to the __buffer and increase in one the __profileIndex
                     """
                     if not self.__withOverlapping:
                         self.__buffer += data.copy()
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nHeis = data.shape
                     data = numpy.reshape(data, (1, nChannels, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer is None:
                         self.__buffer = data
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer = numpy.vstack((self.__buffer, data))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
                     self.__buffer[self.n-1] = data
                     self.__profIndex = self.n
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     if not self.__withOverlapping:
                         data = self.__buffer
                         n = self.__profIndex
                         self.__buffer = 0
                         self.__profIndex = 0
                         return data, n
                     #Integration with Overlapping
                     data = numpy.sum(self.__buffer, axis=0)
                     # print data
                     # raise
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
                     #         n = None
                     # print data
                     # raise
                     self.putData(data)
                     if self.__profIndex == self.n:
                         avgdata, n = self.pushData()
                         self.__dataReady = True
                     return avgdata
                 def byTime(self, data, datatime):
                     self.__dataReady = False
                     avgdata = None
                     n = None
                     self.putData(data)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata
                 def integrateByStride(self, data, datatime):
                     # print data
                     if self.__profIndex == 0:
                         self.__buffer = [[data.copy(), datatime]]
                     else:
                         self.__buffer.append([data.copy(),datatime])
                     self.__profIndex += 1
                     self.__dataReady = False
                     if self.__profIndex == self.n * self.stride :
                         self.__dataToPutStride = True
                         self.__profIndexStride = 0
                         self.__profIndex = 0
                         self.__bufferStride = []
                         for i in range(self.stride):
                             current = self.__buffer[i::self.stride]
                             data = numpy.sum([t[0] for t in current], axis=0)
                             avgdatatime = numpy.average([t[1] for t in current])
                             # print data
                             self.__bufferStride.append((data, avgdatatime))
                     if self.__dataToPutStride:
                         self.__dataReady = True
                         self.__profIndexStride += 1
                         if self.__profIndexStride == self.stride:
                             self.__dataToPutStride = False
                         # print self.__bufferStride[self.__profIndexStride - 1]
                         # raise
                         return self.__bufferStride[self.__profIndexStride - 1]
                     return None, None
                 def integrate(self, data, datatime=None):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata = self.byTime(data, datatime)
                     else:
                         avgdata = self.byProfiles(data)
                     self.__lastdatatime = datatime
                     if avgdata is None:
                         return None, None
                     avgdatatime = self.__initime
                     deltatime = datatime - self.__lastdatatime
                     if not self.__withOverlapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdata, avgdatatime
                 def integrateByBlock(self, dataOut):
                     times = int(dataOut.data.shape[1]/self.n)
                     avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex)
                     id_min = 0
                     id_max = self.n
                     for i in range(times):
                         junk = dataOut.data[:,id_min:id_max,:]
                         avgdata[:,i,:] = junk.sum(axis=1)
                         id_min += self.n
                         id_max += self.n
                     timeInterval = dataOut.ippSeconds*self.n
                     avgdatatime = (times - 1) * timeInterval + dataOut.utctime
                     self.__dataReady = True
                     return avgdata, avgdatatime
                 def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs):
                     if not self.isConfig:
                         self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         avgdata, avgdatatime = self.integrateByBlock(dataOut)
                         dataOut.nProfiles /= self.n
                     else:
                         if stride is None:
                             avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
                         else:
                             avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime)
                     #   dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         if not dataOut.flagCohInt:
                             dataOut.nCohInt *= self.n
                             dataOut.flagCohInt = True
-                        dataOut.utctime = avgdatatime
+                        ####################################dataOut.utctime = avgdatatime
                         # print avgdata, avgdatatime
                         # raise
                         #   dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
                     return dataOut
             class Decoder(Operation):
                 isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.times = None
                     self.osamp = None
                 #         self.__setValues = False
                     self.isConfig = False
                     self.setupReq = False
                 def setup(self, code, osamp, dataOut):
                     self.__profIndex = 0
                     self.code = code
                     self.nCode = len(code)
                     self.nBaud = len(code[0])
                     if (osamp != None) and (osamp >1):
                         self.osamp = osamp
                         self.code = numpy.repeat(code, repeats=self.osamp, axis=1)
                         self.nBaud = self.nBaud*self.osamp
                     self.__nChannels = dataOut.nChannels
                     self.__nProfiles = dataOut.nProfiles
                     self.__nHeis = dataOut.nHeights
                     if self.__nHeis < self.nBaud:
                         raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud))
                     #Frequency
                     __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex)
                     __codeBuffer[:,0:self.nBaud] = self.code
                     self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1))
                     if dataOut.flagDataAsBlock:
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex)
                     else:
                         #Time
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex)
                 def __convolutionInFreq(self, data):
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=1)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=1)
                     return data
                 def __convolutionInFreqOpt(self, data):
                     raise NotImplementedError
                 def __convolutionInTime(self, data):
                     code = self.code[self.__profIndex]
                     for i in range(self.__nChannels):
                         self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInTime(self, data):
                     repetitions = int(self.__nProfiles / self.nCode)
                     junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize))
                     junk = junk.flatten()
                     code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud))
                     profilesList = range(self.__nProfiles)
                     for i in range(self.__nChannels):
                         for j in profilesList:
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInFreq(self, data):
                     raise NotImplementedError("Decoder by frequency fro Blocks not implemented")
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=2)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=2)
                     return data
                 def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None):
                     if dataOut.flagDecodeData:
                         print("This data is already decoded, recoding again ...")
                     if not self.isConfig:
                         if code is None:
                             if dataOut.code is None:
                                 raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type)
                             code = dataOut.code
                         else:
                             code = numpy.array(code).reshape(nCode,nBaud)
                         self.setup(code, osamp, dataOut)
                         self.isConfig = True
                         if mode == 3:
                             sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode)
                         if times != None:
                             sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n")
                     if self.code is None:
                         print("Fail decoding: Code is not defined.")
                         return
                     self.__nProfiles = dataOut.nProfiles
                     datadec = None
                     if mode == 3:
                         mode = 0
                     if dataOut.flagDataAsBlock:
                         """
                         Decoding when data have been read as block,
                         """
                         if mode == 0:
                             datadec = self.__convolutionByBlockInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionByBlockInFreq(dataOut.data)
                     else:
                         """
                         Decoding when data have been read profile by profile
                         """
                         if mode == 0:
                             datadec = self.__convolutionInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionInFreq(dataOut.data)
                         if mode == 2:
                             datadec = self.__convolutionInFreqOpt(dataOut.data)
                     if datadec is None:
                         raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode)
                     dataOut.code = self.code
                     dataOut.nCode = self.nCode
                     dataOut.nBaud = self.nBaud
                     dataOut.data = datadec
                     dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]]
                     dataOut.flagDecodeData = True #asumo q la data esta decodificada
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return dataOut
                     self.__profIndex += 1
                     return dataOut
                 #        dataOut.flagDeflipData = True #asumo q la data no esta sin flip
             class ProfileConcat(Operation):
                 isConfig = False
                 buffer = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def reset(self):
                     self.buffer = numpy.zeros_like(self.buffer)
                     self.start_index = 0
                     self.times = 1
                 def setup(self, data, m, n=1):
                     self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0]))
                     self.nHeights = data.shape[1]#.nHeights
                     self.start_index = 0
                     self.times = 1
                 def concat(self, data):
                     self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy()
                     self.start_index = self.start_index + self.nHeights
                 def run(self, dataOut, m):
                     dataOut.flagNoData = True
                     if not self.isConfig:
                         self.setup(dataOut.data, m, 1)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False")
                     else:
                         self.concat(dataOut.data)
                         self.times += 1
                         if self.times > m:
                             dataOut.data = self.buffer
                             self.reset()
                             dataOut.flagNoData = False
                             # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas
                             deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                             xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m
                             dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
                             dataOut.ippSeconds *= m
                     return dataOut
             class ProfileSelector(Operation):
                 profileIndex = None
                 # Tamanho total de los perfiles
                 nProfiles = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def incProfileIndex(self):
                     self.profileIndex += 1
                     if self.profileIndex >= self.nProfiles:
                         self.profileIndex = 0
                 def isThisProfileInRange(self, profileIndex, minIndex, maxIndex):
                     if profileIndex < minIndex:
                         return False
                     if profileIndex > maxIndex:
                         return False
                     return True
                 def isThisProfileInList(self, profileIndex, profileList):
                     if profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None):
                     #print("before",dataOut.data.shape)
                     """
                     ProfileSelector:
                     Inputs:
                         profileList        :    Index of profiles selected. Example: profileList = (0,1,2,7,8)
                         profileRangeList    :    Minimum and maximum profile indexes. Example: profileRangeList = (4, 30)
                         rangeList            :    List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256))
                     """
                     if rangeList is not None:
                         if type(rangeList[0]) not in (tuple, list):
                             rangeList = [rangeList]
                     dataOut.flagNoData = True
                     if dataOut.flagDataAsBlock:
                         """
                         data dimension  = [nChannels, nProfiles, nHeis]
                         """
                         if profileList != None:
                             dataOut.data = dataOut.data[:,profileList,:]
                         if profileRangeList != None:
                             minIndex = profileRangeList[0]
                             maxIndex = profileRangeList[1]
                             profileList = list(range(minIndex, maxIndex+1))
                             dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:]
                         if rangeList != None:
                             profileList = []
                             for thisRange in rangeList:
                                 minIndex = thisRange[0]
                                 maxIndex = thisRange[1]
                                 profileList.extend(list(range(minIndex, maxIndex+1)))
                             dataOut.data = dataOut.data[:,profileList,:]
                         dataOut.nProfiles = len(profileList)
                         dataOut.profileIndex = dataOut.nProfiles - 1
                         dataOut.flagNoData = False
                         #print(dataOut.data.shape)
                         return dataOut
                     """
                     data dimension  = [nChannels, nHeis]
                     """
                     if profileList != None:
                         if self.isThisProfileInList(dataOut.profileIndex, profileList):
                             self.nProfiles = len(profileList)
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if profileRangeList != None:
                         minIndex = profileRangeList[0]
                         maxIndex = profileRangeList[1]
                         if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                             self.nProfiles = maxIndex - minIndex + 1
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if rangeList != None:
                         nProfiles = 0
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             nProfiles += maxIndex - minIndex + 1
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                                 self.nProfiles = nProfiles
                                 dataOut.nProfiles = self.nProfiles
                                 dataOut.profileIndex = self.profileIndex
                                 dataOut.flagNoData = False
                                 self.incProfileIndex()
                                 break
                         return dataOut
                     if beam != None: #beam is only for AMISR data
                         if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]):
                             dataOut.flagNoData = False
                             dataOut.profileIndex = self.profileIndex
                             self.incProfileIndex()
                         return dataOut
                     raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter")
             class Reshaper(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__buffer = None
                     self.__nitems = 0
                 def __appendProfile(self, dataOut, nTxs):
                     if self.__buffer is None:
                         shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) )
                         self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype)
                     ini = dataOut.nHeights * self.__nitems
                     end = ini + dataOut.nHeights
                     self.__buffer[:, ini:end] = dataOut.data
                     self.__nitems += 1
                     return int(self.__nitems*nTxs)
                 def __getBuffer(self):
                     if self.__nitems == int(1./self.__nTxs):
                         self.__nitems = 0
                         return self.__buffer.copy()
                     return None
                 def __checkInputs(self, dataOut, shape, nTxs):
                     if shape is None and nTxs is None:
                         raise ValueError("Reshaper: shape of factor should be defined")
                     if nTxs:
                         if nTxs < 0:
                             raise ValueError("nTxs should be greater than 0")
                         if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0:
                             raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)))
                         shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs]
                         return shape, nTxs
                     if len(shape) != 2 and len(shape) !=  3:
                         raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights))
                     if len(shape) == 2:
                         shape_tuple = [dataOut.nChannels]
                         shape_tuple.extend(shape)
                     else:
                         shape_tuple = list(shape)
                     nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles
                     return shape_tuple, nTxs
                 def run(self, dataOut, shape=None, nTxs=None):
                     shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs)
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         dataOut.data = numpy.reshape(dataOut.data, shape_tuple)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1
                     else:
                         if self.__nTxs < 1:
                             self.__appendProfile(dataOut, self.__nTxs)
                             new_data = self.__getBuffer()
                             if new_data is not None:
                                 dataOut.data = new_data
                                 dataOut.flagNoData = False
                                 profileIndex = dataOut.profileIndex*nTxs
                         else:
                             raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= self.__nTxs
                     return dataOut
             class SplitProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         if shape[2] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]))
                         new_shape = shape[0], shape[1]*n, int(shape[2]/n)
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles/n) - 1
                     else:
                         raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= n
                     return dataOut
             class CombineProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__remData = None
                     self.__profileIndex = 0
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         new_shape = shape[0], shape[1]/n, shape[2]*n
                         if shape[1] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]))
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*n) - 1
                     else:
                         #nchannels, nsamples
                         if self.__remData is None:
                             newData = dataOut.data
                         else:
                             newData = numpy.concatenate((self.__remData, dataOut.data), axis=1)
                         self.__profileIndex += 1
                         if self.__profileIndex < n:
                             self.__remData = newData
                             #continue
                             return
                         self.__profileIndex = 0
                         self.__remData = None
                         dataOut.data = newData
                         dataOut.flagNoData = False
                         profileIndex = dataOut.profileIndex/n
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles/n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds *= n
                     return dataOut
             class PulsePair(Operation):
                 '''
                 Function PulsePair(Signal Power, Velocity)
                 The real component of Lag[0] provides Intensity Information
                 The imag component of Lag[1] Phase provides Velocity Information
                 Configuration Parameters:
                 nPRF = Number of Several PRF
                 theta = Degree Azimuth angel Boundaries
                 Input:
                       self.dataOut
                       lag[N]
                 Affected:
                       self.dataOut.spc
                 '''
                 isConfig       = False
                 __profIndex    = 0
                 __initime      = None
                 __lastdatatime = None
                 __buffer       = None
                 noise          = None
                 __dataReady    = False
                 n              = None
                 __nch          = 0
                 __nHeis        = 0
                 removeDC       = False
                 ipp            = None
                 lambda_        = 0
                 def __init__(self,**kwargs):
                     Operation.__init__(self,**kwargs)
                 def setup(self, dataOut, n = None, removeDC=False):
                     '''
                     n= Numero de PRF's de entrada
                     '''
                     self.__initime        = None
                     ####print("[INICIO]-setup  del METODO PULSE PAIR")
                     self.__lastdatatime   = 0
                     self.__dataReady      = False
                     self.__buffer         = 0
                     self.__profIndex      = 0
                     self.noise            = None
                     self.__nch            = dataOut.nChannels
                     self.__nHeis          = dataOut.nHeights
                     self.removeDC         = removeDC
                     self.lambda_          = 3.0e8/(9345.0e6)
                     self.ippSec           = dataOut.ippSeconds
                     self.nCohInt          = dataOut.nCohInt
                     ####print("IPPseconds",dataOut.ippSeconds)
                     ####print("ELVALOR DE n es:", n)
                     if n == None:
                         raise ValueError("n should be specified.")
                     if n != None:
                         if n<2:
                             raise ValueError("n should be greater than 2")
                     self.n       = n
                     self.__nProf = n
                     self.__buffer = numpy.zeros((dataOut.nChannels,
                                                        n,
                                                        dataOut.nHeights),
                                                       dtype='complex')
                 def putData(self,data):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:,self.__profIndex,:]= data
                     self.__profIndex      += 1
                     return
                 def pushData(self,dataOut):
                     '''
                     Return the PULSEPAIR and the profiles used in the operation
                     Affected :  self.__profileIndex
                     '''
                     #----------------- Remove DC-----------------------------------
                     if self.removeDC==True:
                         mean    = numpy.mean(self.__buffer,1)
                         tmp     = mean.reshape(self.__nch,1,self.__nHeis)
                         dc= numpy.tile(tmp,[1,self.__nProf,1])
                         self.__buffer = self.__buffer -  dc
                     #------------------Calculo de Potencia ------------------------
                     pair0       = self.__buffer*numpy.conj(self.__buffer)
                     pair0       = pair0.real
                     lag_0       = numpy.sum(pair0,1)
                     #-----------------Calculo de Cscp------------------------------ New
                     cspc_pair01 = self.__buffer[0]*self.__buffer[1]
                     #------------------Calculo de Ruido x canal--------------------
                     self.noise  = numpy.zeros(self.__nch)
                     for i in range(self.__nch):
                         daux         = numpy.sort(pair0[i,:,:],axis= None)
                         self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt)
                     self.noise       = self.noise.reshape(self.__nch,1)
                     self.noise       = numpy.tile(self.noise,[1,self.__nHeis])
                     noise_buffer     = self.noise.reshape(self.__nch,1,self.__nHeis)
                     noise_buffer     = numpy.tile(noise_buffer,[1,self.__nProf,1])
                     #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N--
                     #------------------   P= S+N  ,P=lag_0/N ---------------------------------
                     #-------------------- Power --------------------------------------------------
                     data_power       = lag_0/(self.n*self.nCohInt)
                     #--------------------CCF------------------------------------------------------
                     data_ccf         =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt)
                     #------------------  Senal  --------------------------------------------------
                     data_intensity   = pair0 - noise_buffer
                     data_intensity   = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt)
                     #data_intensity   = (lag_0-self.noise*self.n)*(self.n*self.nCohInt)
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_intensity[i][j]  < 0:
                                 data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j]))
                     #----------------- Calculo de Frecuencia y Velocidad doppler--------
                     pair1            = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:])
                     lag_1            = numpy.sum(pair1,1)
                     data_freq        = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1)
                     data_velocity    = (self.lambda_/2.0)*data_freq
                     #---------------- Potencia promedio estimada de la Senal-----------
                     lag_0            = lag_0/self.n
                     S                = lag_0-self.noise
                     #---------------- Frecuencia Doppler promedio ---------------------
                     lag_1            = lag_1/(self.n-1)
                     R1               = numpy.abs(lag_1)
                     #---------------- Calculo del SNR----------------------------------
                     data_snrPP       = S/self.noise
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_snrPP[i][j]  < 1.e-20:
                                 data_snrPP[i][j] = 1.e-20
                     #----------------- Calculo del ancho espectral ----------------------
                     L                = S/R1
                     L                = numpy.where(L<0,1,L)
                     L                = numpy.log(L)
                     tmp              = numpy.sqrt(numpy.absolute(L))
                     data_specwidth   = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L)
                     n                = self.__profIndex
                     self.__buffer    = numpy.zeros((self.__nch, self.__nProf,self.__nHeis),  dtype='complex')
                     self.__profIndex = 0
                     return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n
                 def pulsePairbyProfiles(self,dataOut):
                     self.__dataReady     =  False
                     data_power           =  None
                     data_intensity       =  None
                     data_velocity        =  None
                     data_specwidth       =  None
                     data_snrPP           =  None
                     data_ccf             =  None
                     self.putData(data=dataOut.data)
                     if self.__profIndex  == self.n:
                         data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n   = self.pushData(dataOut=dataOut)
                         self.__dataReady                   = True
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf
                 def pulsePairOp(self, dataOut, datatime= None):
                     if self.__initime == None:
                         self.__initime = datatime
                     data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut)
                     self.__lastdatatime           = datatime
                     if data_power is None:
                         return None, None, None,None,None,None,None
                     avgdatatime    = self.__initime
                     deltatime      = datatime - self.__lastdatatime
                     self.__initime = datatime
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime
                 def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs):
                     #print("hey")
                     #print(dataOut.data.shape)
                     #exit(1)
                     #print(self.__profIndex)
                     if not self.isConfig:
                         self.setup(dataOut = dataOut, n    = n , removeDC=removeDC , **kwargs)
                         self.isConfig   = True
                     data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime)
                     dataOut.flagNoData                         = True
                     if self.__dataReady:
                         ###print("READY ----------------------------------")
                         dataOut.nCohInt        *= self.n
                         dataOut.dataPP_POW      = data_intensity # S
                         dataOut.dataPP_POWER    = data_power     # P valor que corresponde a POTENCIA MOMENTO
                         dataOut.dataPP_DOP      = data_velocity
                         dataOut.dataPP_SNR      = data_snrPP
                         dataOut.dataPP_WIDTH    = data_specwidth
                         dataOut.dataPP_CCF      = data_ccf
                         dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
                         dataOut.nProfiles       = int(dataOut.nProfiles/n)
                         dataOut.utctime         = avgdatatime
                         dataOut.flagNoData      = False
                     return dataOut
             class PulsePair_vRF(Operation):
                 '''
                 Function PulsePair(Signal Power, Velocity)
                 The real component of Lag[0] provides Intensity Information
                 The imag component of Lag[1] Phase provides Velocity Information
                 Configuration Parameters:
                 nPRF = Number of Several PRF
                 theta = Degree Azimuth angel Boundaries
                 Input:
                       self.dataOut
                       lag[N]
                 Affected:
                       self.dataOut.spc
                 '''
                 isConfig       = False
                 __profIndex    = 0
                 __initime      = None
                 __lastdatatime = None
                 __buffer       = None
                 noise          = None
                 __dataReady    = False
                 n              = None
                 __nch          = 0
                 __nHeis        = 0
                 removeDC       = False
                 ipp            = None
                 lambda_        = 0
                 def __init__(self,**kwargs):
                     Operation.__init__(self,**kwargs)
                 def setup(self, dataOut, n = None, removeDC=False):
                     '''
                     n= Numero de PRF's de entrada
                     '''
                     self.__initime        = None
                     ####print("[INICIO]-setup  del METODO PULSE PAIR")
                     self.__lastdatatime   = 0
                     self.__dataReady      = False
                     self.__buffer         = 0
                     self.__profIndex      = 0
                     self.noise            = None
                     self.__nch            = dataOut.nChannels
                     self.__nHeis          = dataOut.nHeights
                     self.removeDC         = removeDC
                     self.lambda_          = 3.0e8/(9345.0e6)
                     self.ippSec           = dataOut.ippSeconds
                     self.nCohInt          = dataOut.nCohInt
                     ####print("IPPseconds",dataOut.ippSeconds)
                     ####print("ELVALOR DE n es:", n)
                     if n == None:
                         raise ValueError("n should be specified.")
                     if n != None:
                         if n<2:
                             raise ValueError("n should be greater than 2")
                     self.n       = n
                     self.__nProf = n
                     self.__buffer = numpy.zeros((dataOut.nChannels,
                                                        n,
                                                        dataOut.nHeights),
                                                       dtype='complex')
                 def putData(self,data):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:,self.__profIndex,:]= data
                     self.__profIndex      += 1
                     return
                 def putDataByBlock(self,data,n):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:]= data
                     self.__profIndex      = n
                     return
                 def pushData(self,dataOut):
                     '''
                     Return the PULSEPAIR and the profiles used in the operation
                     Affected :  self.__profileIndex
                     '''
                     #----------------- Remove DC-----------------------------------
                     if self.removeDC==True:
                         mean    = numpy.mean(self.__buffer,1)
                         tmp     = mean.reshape(self.__nch,1,self.__nHeis)
                         dc= numpy.tile(tmp,[1,self.__nProf,1])
                         self.__buffer = self.__buffer -  dc
                     #------------------Calculo de Potencia ------------------------
                     pair0       = self.__buffer*numpy.conj(self.__buffer)
                     pair0       = pair0.real
                     lag_0       = numpy.sum(pair0,1)
                     #-----------------Calculo de Cscp------------------------------ New
                     cspc_pair01 = self.__buffer[0]*self.__buffer[1]
                     #------------------Calculo de Ruido x canal--------------------
                     self.noise  = numpy.zeros(self.__nch)
                     for i in range(self.__nch):
                         daux         = numpy.sort(pair0[i,:,:],axis= None)
                         self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt)
                     self.noise       = self.noise.reshape(self.__nch,1)
                     self.noise       = numpy.tile(self.noise,[1,self.__nHeis])
                     noise_buffer     = self.noise.reshape(self.__nch,1,self.__nHeis)
                     noise_buffer     = numpy.tile(noise_buffer,[1,self.__nProf,1])
                     #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N--
                     #------------------   P= S+N  ,P=lag_0/N ---------------------------------
                     #-------------------- Power --------------------------------------------------
                     data_power       = lag_0/(self.n*self.nCohInt)
                     #--------------------CCF------------------------------------------------------
                     data_ccf         =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt)
                     #------------------  Senal  --------------------------------------------------
                     data_intensity   = pair0 - noise_buffer
                     data_intensity   = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt)
                     #data_intensity   = (lag_0-self.noise*self.n)*(self.n*self.nCohInt)
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_intensity[i][j]  < 0:
                                 data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j]))
                     #----------------- Calculo de Frecuencia y Velocidad doppler--------
                     pair1            = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:])
                     lag_1            = numpy.sum(pair1,1)
                     data_freq        = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1)
                     data_velocity    = (self.lambda_/2.0)*data_freq
                     #---------------- Potencia promedio estimada de la Senal-----------
                     lag_0            = lag_0/self.n
                     S                = lag_0-self.noise
                     #---------------- Frecuencia Doppler promedio ---------------------
                     lag_1            = lag_1/(self.n-1)
                     R1               = numpy.abs(lag_1)
                     #---------------- Calculo del SNR----------------------------------
                     data_snrPP       = S/self.noise
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_snrPP[i][j]  < 1.e-20:
                                 data_snrPP[i][j] = 1.e-20
                     #----------------- Calculo del ancho espectral ----------------------
                     L                = S/R1
                     L                = numpy.where(L<0,1,L)
                     L                = numpy.log(L)
                     tmp              = numpy.sqrt(numpy.absolute(L))
                     data_specwidth   = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L)
                     n                = self.__profIndex
                     self.__buffer    = numpy.zeros((self.__nch, self.__nProf,self.__nHeis),  dtype='complex')
                     self.__profIndex = 0
                     return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n
                 def pulsePairbyProfiles(self,dataOut,n):
                     self.__dataReady     =  False
                     data_power           =  None
                     data_intensity       =  None
                     data_velocity        =  None
                     data_specwidth       =  None
                     data_snrPP           =  None
                     data_ccf             =  None
                     if dataOut.flagDataAsBlock:
                         self.putDataByBlock(data=dataOut.data,n=n)
                     else:
                         self.putData(data=dataOut.data)
                     if self.__profIndex  == self.n:
                         data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n   = self.pushData(dataOut=dataOut)
                         self.__dataReady                   = True
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf
                 def pulsePairOp(self, dataOut, n, datatime= None):
                     if self.__initime == None:
                         self.__initime = datatime
                     data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut,n)
                     self.__lastdatatime           = datatime
                     if data_power is None:
                         return None, None, None,None,None,None,None
                     avgdatatime    = self.__initime
                     deltatime      = datatime - self.__lastdatatime
                     self.__initime = datatime
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime
                 def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs):
                     if dataOut.flagDataAsBlock:
-                        n = dataOut.nProfiles
+                        n = int(dataOut.nProfiles)
+                        #print("n",n)
                     if not self.isConfig:
                         self.setup(dataOut = dataOut, n    = n , removeDC=removeDC , **kwargs)
                         self.isConfig   = True
                     data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime)
                     dataOut.flagNoData                         = True
                     if self.__dataReady:
                         ###print("READY ----------------------------------")
                         dataOut.nCohInt        *= self.n
                         dataOut.dataPP_POW      = data_intensity # S
                         dataOut.dataPP_POWER    = data_power     # P valor que corresponde a POTENCIA MOMENTO
                         dataOut.dataPP_DOP      = data_velocity
                         dataOut.dataPP_SNR      = data_snrPP
                         dataOut.dataPP_WIDTH    = data_specwidth
                         dataOut.dataPP_CCF      = data_ccf
                         dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
                         dataOut.nProfiles       = int(dataOut.nProfiles/n)
                         dataOut.utctime         = avgdatatime
                         dataOut.flagNoData      = False
                     return dataOut
             # import collections
             # from scipy.stats import mode
             #
             # class Synchronize(Operation):
             #
             #     isConfig = False
             #     __profIndex = 0
             #
             #     def __init__(self, **kwargs):
             #
             #         Operation.__init__(self, **kwargs)
             # #         self.isConfig = False
             #         self.__powBuffer = None
             #         self.__startIndex = 0
             #         self.__pulseFound = False
             #
             #     def __findTxPulse(self, dataOut, channel=0, pulse_with = None):
             #
             #         #Read data
             #
             #         powerdB = dataOut.getPower(channel = channel)
             #         noisedB = dataOut.getNoise(channel = channel)[0]
             #
             #         self.__powBuffer.extend(powerdB.flatten())
             #
             #         dataArray = numpy.array(self.__powBuffer)
             #
             #         filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same")
             #
             #         maxValue = numpy.nanmax(filteredPower)
             #
             #         if maxValue < noisedB + 10:
             #             #No se encuentra ningun pulso de transmision
             #             return None
             #
             #         maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0]
             #
             #         if len(maxValuesIndex) < 2:
             #             #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX
             #             return None
             #
             #         phasedMaxValuesIndex = maxValuesIndex - self.__nSamples
             #
             #         #Seleccionar solo valores con un espaciamiento de nSamples
             #         pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex)
             #
             #         if len(pulseIndex) < 2:
             #             #Solo se encontro un pulso de transmision con ancho mayor a 1
             #             return None
             #
             #         spacing = pulseIndex[1:] - pulseIndex[:-1]
             #
             #         #remover senales que se distancien menos de 10 unidades o muestras
             #         #(No deberian existir IPP menor a 10 unidades)
             #
             #         realIndex = numpy.where(spacing > 10 )[0]
             #
             #         if len(realIndex) < 2:
             #             #Solo se encontro un pulso de transmision con ancho mayor a 1
             #             return None
             #
             #         #Eliminar pulsos anchos (deja solo la diferencia entre IPPs)
             #         realPulseIndex = pulseIndex[realIndex]
             #
             #         period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0]
             #
             #         print "IPP = %d samples" %period
             #
             #         self.__newNSamples = dataOut.nHeights #int(period)
             #         self.__startIndex = int(realPulseIndex[0])
             #
             #         return 1
             #
             #
             #     def setup(self, nSamples, nChannels, buffer_size = 4):
             #
             #         self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float),
             #                                           maxlen = buffer_size*nSamples)
             #
             #         bufferList = []
             #
             #         for i in range(nChannels):
             #             bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) +  numpy.NAN,
             #                                           maxlen = buffer_size*nSamples)
             #
             #             bufferList.append(bufferByChannel)
             #
             #         self.__nSamples = nSamples
             #         self.__nChannels = nChannels
             #         self.__bufferList = bufferList
             #
             #     def run(self, dataOut, channel = 0):
             #
             #         if not self.isConfig:
             #             nSamples = dataOut.nHeights
             #             nChannels = dataOut.nChannels
             #             self.setup(nSamples, nChannels)
             #             self.isConfig = True
             #
             #         #Append new data to internal buffer
             #         for thisChannel in range(self.__nChannels):
             #             bufferByChannel = self.__bufferList[thisChannel]
             #             bufferByChannel.extend(dataOut.data[thisChannel])
             #
             #         if self.__pulseFound:
             #             self.__startIndex -= self.__nSamples
             #
             #         #Finding Tx Pulse
             #         if not self.__pulseFound:
             #             indexFound = self.__findTxPulse(dataOut, channel)
             #
             #             if indexFound == None:
             #                 dataOut.flagNoData = True
             #                 return
             #
             #             self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex)
             #             self.__pulseFound = True
             #             self.__startIndex = indexFound
             #
             #         #If pulse was found ...
             #         for thisChannel in range(self.__nChannels):
             #             bufferByChannel = self.__bufferList[thisChannel]
             #             #print self.__startIndex
             #             x = numpy.array(bufferByChannel)
             #             self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples]
             #
             #         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
             #         dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight
             # #             dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6
             #
             #         dataOut.data = self.__arrayBuffer
             #
             #         self.__startIndex += self.__newNSamples
             #
             #         return

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