#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Copyright 2010 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # United States Government Sponsorship acknowledged. This software is subject to # U.S. export control laws and regulations and has been classified as 'EAR99 NLR' # (No [Export] License Required except when exporting to an embargoed country, # end user, or in support of a prohibited end use). By downloading this software, # the user agrees to comply with all applicable U.S. export laws and regulations. # The user has the responsibility to obtain export licenses, or other export # authority as may be required before exporting this software to any 'EAR99' # embargoed foreign country or citizen of those countries. # # Author: Walter Szeliga #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import os import math import array import string import random import logging import datetime import isceobj from . import CEOS from isceobj.Scene.Track import Track from isceobj.Scene.Frame import Frame from isceobj.Planet.Planet import Planet from isceobj.Planet.AstronomicalHandbook import Const from isceobj.Orbit.Orbit import StateVector from iscesys.Component.Component import Component from iscesys.DateTimeUtil.DateTimeUtil import DateTimeUtil as DTU #from Sensor.ReadOrbitPulseERS import ReadOrbitPulseERS from isceobj.Sensor import xmlPrefix from isceobj.Util.decorators import pickled, logged LEADERFILE = Component.Parameter('_leaderFileList', public_name='LEADERFILE', default = '', container=list, type=str, mandatory=True, doc="List of names of ALOS Leaderfile" ) IMAGEFILE = Component.Parameter('_imageFileList', public_name='IMAGEFILE', default = '', container=list, type=str, mandatory=True, doc="List of names of ALOS Imagefile" ) ORBIT_TYPE = Component.Parameter('_orbitType', public_name='ORBIT_TYPE', default='', type=str, mandatory=True, doc="Options: ODR, PRC, PDS" ) ORBIT_DIRECTORY = Component.Parameter('_orbitDir', public_name='ORBIT_DIRECTORY', default='', type=str, mandatory=False, doc="Path to the directory containing the orbit files." ) ORBIT_FILE = Component.Parameter('_orbitFile', public_name='ORBIT_FILE', default='', type=str, mandatory=False, doc='Only used with PDS ORBIT_TYPE' ) ## # Code to read CEOSFormat leader files for ERS-1/2 SAR data. The tables used # to create this parser are based on document number ER-IS-EPO-GS-5902.1 from # the European Space Agency. from .Sensor import Sensor class ERS(Sensor): family = 'ers' logging_name = 'isce.sensor.ers' parameter_list = (IMAGEFILE, LEADERFILE, ORBIT_TYPE, ORBIT_DIRECTORY, ORBIT_FILE) + Sensor.parameter_list @logged def __init__(self, name=''): super().__init__(family=self.__class__.family, name=name) self._leaderFile = None self._imageFile = None self.frameList = [] self.frame = Frame() self.frame.configure() # Constants are from # J. J. Mohr and S. N. Madsen. Geometric calibration of ERS satellite # SAR images. IEEE T. Geosci. Remote, 39(4):842-850, Apr. 2001. self.constants = {'polarization': 'VV', 'antennaLength': 10, 'lookDirection': 'RIGHT', 'chirpPulseBandwidth': 15.50829e6, 'rangeSamplingRate': 18.962468e6, 'delayTime':6.622e-6, 'iBias': 15.5, 'qBias': 15.5} return None def getFrame(self): return self.frame def parse(self): self.leaderFile = LeaderFile(file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self) self.imageFile.parse() self.populateMetadata() def populateMetadata(self): """ Create the appropriate metadata objects from our CEOSFormat metadata """ self._populatePlatform() self._populateInstrument() self._populateFrame() if (self._orbitType == 'ODR'): self._populateDelftOrbits() elif (self._orbitType == 'PRC'): self._populatePRCOrbits() elif (self._orbitType == 'PDS'): self._populatePDSOrbits() else: self._populateHeaderOrbit() def _populatePlatform(self): """ Populate the platform object with metadata """ platform = self.frame.getInstrument().getPlatform() platform.setMission(self.leaderFile.sceneHeaderRecord.metadata[ 'Sensor platform mission identifier']) platform.setAntennaLength(self.constants['antennaLength']) platform.setPointingDirection(-1) platform.setPlanet(Planet(pname='Earth')) def _populateInstrument(self): """Populate the instrument object with metadata""" instrument = self.frame.getInstrument() pri = self.imageFile.firstPri rangeSamplingRate = self.constants['rangeSamplingRate'] #rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata[ # 'Range sampling rate']*1e6 rangePixelSize = Const.c/(2.0*rangeSamplingRate) pulseInterval = 4.0/rangeSamplingRate*(pri+2.0) prf = 1.0/pulseInterval instrument.setRadarWavelength( self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength']) instrument.setIncidenceAngle( self.leaderFile.sceneHeaderRecord.metadata[ 'Incidence angle at scene centre']) instrument.setPulseRepetitionFrequency(prf) instrument.setRangeSamplingRate(rangeSamplingRate) instrument.setRangePixelSize(rangePixelSize) instrument.setPulseLength(self.leaderFile.sceneHeaderRecord.metadata[ 'Range pulse length']*1e-6) instrument.setChirpSlope(self.constants['chirpPulseBandwidth']/ (self.leaderFile.sceneHeaderRecord.metadata['Range pulse length']* 1e-6)) instrument.setInPhaseValue(self.constants['iBias']) instrument.setQuadratureValue(self.constants['qBias']) def _populateFrame(self): """Populate the scene object with metadata""" rangeSamplingRate = self.constants['rangeSamplingRate'] #rangeSamplingRate = self.leaderFile.sceneHeaderRecord.metadata[ # 'Range sampling rate']*1e6 rangePixelSize = Const.c/(2.0*rangeSamplingRate) pulseInterval = 1.0/self.frame.getInstrument().getPulseRepetitionFrequency() frame = self._decodeSceneReferenceNumber( self.leaderFile.sceneHeaderRecord.metadata[ 'Scene reference number']) startingRange = (9*pulseInterval + self.imageFile.minSwst*4/rangeSamplingRate-self.constants['delayTime'])*Const.c/2.0 farRange = startingRange + self.imageFile.width*rangePixelSize # Use the Scene center time to get the date, then use the ICU on board time from the image for the rest centerLineTime = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Scene centre time'],"%Y%m%d%H%M%S%f") first_line_utc = datetime.datetime(year=centerLineTime.year, month=centerLineTime.month, day=centerLineTime.day) if(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'] in ('CRDC_SARDPF','GTS - ERS')): first_line_utc = first_line_utc + datetime.timedelta(milliseconds=self.imageFile.startTime) else: deltaSeconds = (self.imageFile.startTime - self.leaderFile.sceneHeaderRecord.metadata['Satellite encoded binary time code'])* 1/256.0 # Sometimes, the ICU on board clock is corrupt, if the time suggested by the on board clock is more than # 5 days from the satellite clock time, assume its bogus and use the low-precision scene centre time if (math.fabs(deltaSeconds) > 5*86400): self.logger.warning("ICU on board time appears to be corrupt, resorting to low precision clock") first_line_utc = centerLineTime - datetime.timedelta(microseconds=pulseInterval*(self.imageFile.length/2.0)*1e6) else: satelliteClockTime = datetime.datetime.strptime(self.leaderFile.sceneHeaderRecord.metadata['Satellite clock time'],"%Y%m%d%H%M%S%f") first_line_utc = satelliteClockTime + datetime.timedelta(microseconds=int(deltaSeconds*1e6)) mid_line_utc = first_line_utc + datetime.timedelta(microseconds=pulseInterval*(self.imageFile.length/2.0)*1e6) last_line_utc = first_line_utc + datetime.timedelta(microseconds=pulseInterval*self.imageFile.length*1e6) self.logger.debug("Frame UTC start, mid, end times: %s %s %s" % (first_line_utc,mid_line_utc,last_line_utc)) self.frame.setFrameNumber(frame) self.frame.setOrbitNumber(self.leaderFile.sceneHeaderRecord.metadata['Orbit number']) self.frame.setStartingRange(startingRange) self.frame.setFarRange(farRange) self.frame.setProcessingFacility(self.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier']) self.frame.setProcessingSystem(self.leaderFile.sceneHeaderRecord.metadata['Processing system identifier']) self.frame.setProcessingSoftwareVersion(self.leaderFile.sceneHeaderRecord.metadata['Processing version identifier']) self.frame.setPolarization(self.constants['polarization']) self.frame.setNumberOfLines(self.imageFile.length) self.frame.setNumberOfSamples(self.imageFile.width) self.frame.setSensingStart(first_line_utc) self.frame.setSensingMid(mid_line_utc) self.frame.setSensingStop(last_line_utc) def _populateHeaderOrbit(self): """Populate an orbit object with the header orbits""" self.logger.info("Using Header Orbits") orbit = self.frame.getOrbit() orbit.setOrbitSource('Header') orbit.setOrbitQuality('Unknown') t0 = datetime.datetime(year=self.leaderFile.platformPositionRecord.metadata['Year of data point'], month=self.leaderFile.platformPositionRecord.metadata['Month of data point'], day=self.leaderFile.platformPositionRecord.metadata['Day of data point']) t0 = t0 + datetime.timedelta(microseconds=self.leaderFile.platformPositionRecord.metadata['Seconds of day']*1e6) for i in range(self.leaderFile.platformPositionRecord.metadata['Number of data points']): vec = StateVector() deltaT = self.leaderFile.platformPositionRecord.metadata['Time interval between DATA points'] t = t0 + datetime.timedelta(microseconds=i*deltaT*1e6) vec.setTime(t) dataPoints = self.leaderFile.platformPositionRecord.metadata['Positional Data Points'][i] vec.setPosition([dataPoints['Position vector X'], dataPoints['Position vector Y'], dataPoints['Position vector Z']]) vec.setVelocity([dataPoints['Velocity vector X'], dataPoints['Velocity vector Y'], dataPoints['Velocity vector Z']]) orbit.addStateVector(vec) def _populateDelftOrbits(self): """Populate an orbit object with the Delft orbits""" from isceobj.Orbit.ODR import ODR, Arclist self.logger.info("Using Delft Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) self.logger.info('Using ODR file: ' + orbitFile) odr = ODR(file=os.path.join(self._orbitDir,orbitFile)) #jng it seem that for this tipe of orbit points are separated by 60 sec. In ODR at least 9 state vectors are needed to compute the velocities. add # extra time before and after to allow interpolation, but do not do it for all data points. too slow startTimePreInterp = self.frame.getSensingStart() - datetime.timedelta(minutes=60) stopTimePreInterp = self.frame.getSensingStop() + datetime.timedelta(minutes=60) odr.parseHeader(startTimePreInterp,stopTimePreInterp) startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) orbit = odr.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePRCOrbits(self): """Populate an orbit object the D-PAF PRC orbits""" from isceobj.Orbit.PRC import PRC, Arclist self.logger.info("Using PRC Orbits") arclist = Arclist(os.path.join(self._orbitDir,'arclist')) arclist.parse() orbitFile = arclist.getOrbitFile(self.frame.getSensingStart()) self.logger.debug("Using file %s" % (orbitFile)) prc = PRC(file=os.path.join(self._orbitDir,orbitFile)) prc.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = prc.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def _populatePDSOrbits(self): """ Populate an orbit object using the ERS-2 PDS format """ from isceobj.Orbit.PDS import PDS self.logger.info("Using PDS Orbits") pds = PDS(file=self._orbitFile) pds.parse() startTime = self.frame.getSensingStart() - datetime.timedelta(minutes=5) stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5) self.logger.debug("Extracting orbits between %s and %s" % (startTime,stopTime)) fullOrbit = pds.getOrbit() orbit = fullOrbit.trimOrbit(startTime,stopTime) self.frame.setOrbit(orbit) def extractImage(self): import array import math if(len(self._imageFileList) != len(self._leaderFileList)): self.logger.error("Number of leader files different from number of image files.") raise Exception self.frameList = [] for i in range(len(self._imageFileList)): appendStr = "_" + str(i) #if only one file don't change the name if(len(self._imageFileList) == 1): appendStr = '' self.frame = Frame() self.frame.configure() self._leaderFile = self._leaderFileList[i] self._imageFile = self._imageFileList[i] self.leaderFile = LeaderFile(file=self._leaderFile) self.leaderFile.parse() self.imageFile = ImageFile(self) try: outputNow = self.output + appendStr out = open(outputNow,'wb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) return self.imageFile.extractImage(output=out) out.close() rawImage = isceobj.createRawImage() rawImage.setByteOrder('l') rawImage.setAccessMode('read') rawImage.setFilename(outputNow) rawImage.setWidth(self.imageFile.width) rawImage.setXmin(0) rawImage.setXmax(self.imageFile.width) self.frame.setImage(rawImage) self.populateMetadata() self.frameList.append(self.frame) #jng Howard Z at this point adjusts the sampling starting time for imagery generated from CRDC_SARDPF facility. # for now create the orbit aux file based in starting time and prf prf = self.frame.getInstrument().getPulseRepetitionFrequency() senStart = self.frame.getSensingStart() numPulses = int(math.ceil(DTU.timeDeltaToSeconds(self.frame.getSensingStop()-senStart)*prf)) # the aux files has two entries per line. day of the year and microseconds in the day musec0 = (senStart.hour*3600 + senStart.minute*60 + senStart.second)*10**6 + senStart.microsecond maxMusec = (24*3600)*10**6#use it to check if we went across a day. very rare day0 = (datetime.datetime(senStart.year,senStart.month,senStart.day) - datetime.datetime(senStart.year,1,1)).days + 1 outputArray = array.array('d',[0]*2*numPulses) self.frame.auxFile = outputNow + '.aux' fp = open(self.frame.auxFile,'wb') j = -1 for i1 in range(numPulses): j += 1 musec = round((j/prf)*10**6) + musec0 if musec >= maxMusec: day0 += 1 musec0 = musec%maxMusec musec = musec0 j = 0 outputArray[2*i1] = day0 outputArray[2*i1+1] = musec outputArray.tofile(fp) fp.close() tk = Track() if(len(self._imageFileList) > 1): self.frame = tk.combineFrames(self.output,self.frameList) for i in range(len(self._imageFileList)): try: os.remove(self.output + "_" + str(i)) except OSError: print("Error. Cannot remove temporary file",self.output + "_" + str(i)) raise OSError def _decodeSceneReferenceNumber(self,referenceNumber): frameNumber = referenceNumber.split('=') if (len(frameNumber) > 2): frameNumber = frameNumber[2].strip() else: frameNumber = frameNumber[0] return frameNumber class LeaderFile(object): def __init__(self,file=None): self.file = file self.leaderFDR = None self.sceneHeaderRecord = None self.platformPositionRecord = None self.facilityRecord = None self.facilityPCSRecord = None self.logger = logging.getLogger('isce.sensor.ers') def parse(self): """ Parse the leader file to create a header object """ try: fp = open(self.file,'rb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) return # Leader record self.leaderFDR = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/leader_file.xml'),dataFile=fp) self.leaderFDR.parse() fp.seek(self.leaderFDR.getEndOfRecordPosition()) if (self.leaderFDR.metadata['Number of data set summary records'] > 0): # Scene Header self.sceneHeaderRecord = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/scene_record.xml'),dataFile=fp) self.sceneHeaderRecord.parse() fp.seek(self.sceneHeaderRecord.getEndOfRecordPosition()) if (self.leaderFDR.metadata['Number of platform pos. data records'] > 0): # Platform Position self.platformPositionRecord = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/platform_position_record.xml'),dataFile=fp) self.platformPositionRecord.parse() fp.seek(self.platformPositionRecord.getEndOfRecordPosition()) if (self.leaderFDR.metadata['Number of facility data records'] > 0): # Facility Record self.facilityRecord = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/facility_record.xml'), dataFile=fp) self.facilityRecord.parse() fp.seek(self.facilityRecord.getEndOfRecordPosition()) # Facility PCS Record self.facilityPCSRecord = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/facility_related_pcs_record.xml'), dataFile=fp) self.facilityPCSRecord.parse() fp.seek(self.facilityPCSRecord.getEndOfRecordPosition()) fp.close() class VolumeDirectoryFile(object): def __init__(self,file=None): self.file = file self.metadata = {} self.logger = logging.getLogger('isce.sensor.ers') def parse(self): try: fp = open(self.file,'r') except IOError as strerr: self.logger.error("IOError: %s" % strerr) return volumeFDR = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/volume_descriptor.xml'),dataFile=fp) volumeFDR.parse() fp.seek(volumeFDR.getEndOfRecordPosition()) fp.close() import pprint pp = pprint.PrettyPrinter() pp.pprint(volumeFDR.metadata) class ImageFile(object): def __init__(self,parent): self.parent = parent self.width = None self.length = None self.minSwst = None self.maxSwst = None self.firstPri = None self.startTime = None self.imageFDR = None self.logger = logging.getLogger('isce.sensor.ers') self.image_record = os.path.join(xmlPrefix,'ers/image_record.xml') facility = self.parent.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'] version = self.parent.leaderFile.sceneHeaderRecord.metadata['Processing system identifier'] self.parent.logger.debug("Processing Facility: " + facility ) self.parent.logger.debug("Processing System: " + version) if(facility in ('CRDC_SARDPF','GTS - ERS')): self.image_record = os.path.join(xmlPrefix,'ers/crdc-sardpf_image_record.xml') elif((facility == 'D-PAF') and (version=='MSAR')): self.image_record = os.path.join(xmlPrefix, 'ers/new-d-paf_image_record.xml') def parse(self): try: fp = open(self.parent._imageFile,'rb') except IOError as strerr: self.logger.error("IOError: %s" % strerr) return self.imageFDR = CEOS.CEOSDB(xml=os.path.join(xmlPrefix,'ers/image_file.xml'), dataFile=fp) self.imageFDR.parse() fp.seek(self.imageFDR.getEndOfRecordPosition()) self._calculateRawDimensions(fp) fp.close() def extractImage(self,output=None): """ Extract the I and Q channels from the image file """ if (not self.imageFDR): self.parse() try: fp = open(self.parent._imageFile,'rb') except IOError as strerr: self.logger.error("IOError %s" % strerr) return (maxSwst,minSwst) = self._calculateRawDimensions(fp) lines = self.imageFDR.metadata['Number of SAR DATA records'] pixelCount = self.imageFDR.metadata['Number of left border pixels per line'] + \ self.imageFDR.metadata['Number of pixels per line per SAR channel'] + \ self.imageFDR.metadata['Number of right border pixels per line'] suffixSize = self.imageFDR.metadata['Number of bytes of suffix data per record'] fp.seek(self.imageFDR.getEndOfRecordPosition(),os.SEEK_SET) lastSwst = 0 lastLineCounter = 0 lineGap = 0 # Extract the I and Q channels imageData = CEOS.CEOSDB(xml=self.image_record,dataFile=fp) #jng use this line as a template IQLine = array.array('B',[random.randint(15,16)*x for x in [1]*self.width]) IQ = array.array('B',[x for x in [0]*self.width]) IQFile = array.array('B',[x for x in [0]*2*pixelCount]) for line in range(lines): if ((line%1000) == 0): self.logger.debug("Extracting line %s" % line) imageData.parseFast() # Find missing range values currentSwst = imageData.metadata['Sampling window start time'] if ((currentSwst>500) and (currentSwst<1500) and (currentSwst-minSwst)%22 == 0): lastSwst = currentSwst leftPad = (lastSwst - minSwst)*8 rightPad = self.width - leftPad - 2*pixelCount # Find missing lines lineCounter = imageData.metadata['Image format counter'] if (lineCounter == 0): self.logger.warning("Zero line counter at line %s" % (line+1)) lastLineCounter += 1 continue # Initialize the line counter if (line == 0): lastLineCounter = lineCounter-1 lineGap = lineCounter - lastLineCounter-1 #self.logger.debug("Line Counter: %s Last Line Counter: %s Line Gap: %s line: %s" % (lineCounter,lastLineCounter,lineGap,line)) skipLine = False if (lineGap > 0): if (lineGap > 30000): self.logger.warn("Bad Line Counter on line %s, Gap length too large (%s)" % (line+1,lineGap)) fp.seek((2*pixelCount+suffixSize),os.SEEK_CUR) lastLineCounter += 1 continue self.logger.debug("Gap of length %s at line %s" % (lineGap,(line+1))) #jng just put a predefine sequence af random values. randint very slow #IQ = array.array('B',[random.randint(15,16)*x for x in [1]*(leftPad+2*pixelCount+rightPad)]) IQ = array.array('B',[IQLine[i] for i in range(self.width)]) for i in range(lineGap): IQ.tofile(output) # It may be better to fill missing lines with random 15's and 16's rather than copying the last good line lastLineCounter += 1 elif (lineGap == -1): skipLine = True elif (lineGap < 0): self.logger.warn("Unusual Line Gap %s at line %s" % (lineGap,(line+1))) raise IndexError #self.logger.debug("Extracting line %s" % (line+1)) # Pad data with random integers around the I and Q bias of 15.5 on the left #jng just put a predefine sequence af random values. randint very slow #IQ = array.array('B',[random.randint(15,16)*x for x in [1]*leftPad]) IQ = array.array('B',[IQLine[i] for i in range(leftPad)]) # Read the I and Q values IQ.fromfile(fp,2*pixelCount) fp.seek(suffixSize,os.SEEK_CUR) # Now pad on the right #jng just put a predefine sequence af random values. randint very slow #IQ.extend([random.randint(15,16)*x for x in [1]*rightPad]) IQ.extend([IQLine[i] for i in range(rightPad)]) # Output the padded line if not skipLine: IQ.tofile(output) lastLineCounter += 1 imageData.finalizeParser() fp.close() def _calculateRawDimensions(self,fp): """ Run through the data file once, and calculate the valid sampling window start time range. """ lines = self.imageFDR.metadata['Number of SAR DATA records'] pixelCount = self.imageFDR.metadata['Number of left border pixels per line'] + self.imageFDR.metadata['Number of pixels per line per SAR channel'] + self.imageFDR.metadata['Number of right border pixels per line'] suffixSize = self.imageFDR.metadata['Number of bytes of suffix data per record'] self.length = lines expectedFileSize = self.imageFDR.metadata['Record Length'] + self.imageFDR.metadata['SAR DATA record length']*self.imageFDR.metadata['Number of SAR DATA records'] fp.seek(0,os.SEEK_END) actualSize = fp.tell() if (expectedFileSize != actualSize): self.logger.info("File too short. Expected %s bytes, found %s bytes" % (expectedFileSize,actualSize)) lines = (actualSize - self.imageFDR.metadata['Record Length'])/(12+self.imageFDR.metadata['Number of bytes of prefix data per record']+self.imageFDR.metadata['Number of bytes of SAR data per record']+self.imageFDR.metadata['Number of bytes of suffix data per record']) expectedFileSize = self.imageFDR.metadata['Record Length'] + self.imageFDR.metadata['SAR DATA record length']*lines self.logger.info("%s (%s bytes total) lines of data estimated (%s expected)" % (lines,expectedFileSize,self.length)) fp.seek(self.imageFDR.getEndOfRecordPosition(),os.SEEK_SET) mstime = [] icu = [] swst = [] pri = [] lastLineCounter = None lineGap = 0 # Calculate the minimum and maximum Sampling Window Start Times imageData = CEOS.CEOSDB(xml=self.image_record,dataFile=fp) mstime = [0]*lines icu = [0]*lines pri = [0]*lines swst = [0]*lines i = 0 for line in range(lines): imageData.parseFast() lineCounter = imageData.metadata['Image format counter'] if (not lastLineCounter): lastLineCounter = lineCounter else: lineGap = lineCounter - lastLineCounter-1 lastLineCounter = lineCounter if (lineGap != 0): self.length += lineGap mstime[i] = imageData.metadata['Record time in milliseconds'] icu[i] = imageData.metadata['ICU on board time'] swst[i] = imageData.metadata['Sampling window start time'] pri[i] = imageData.metadata['Pulse repetition interval'] fp.seek(2*pixelCount,os.SEEK_CUR) fp.seek(suffixSize,os.SEEK_CUR) i += 1 imageData.finalizeParser() if(self.parent.leaderFile.sceneHeaderRecord.metadata['Processing facility identifier'] in ('CRDC_SARDPF','GTS - ERS')): self.startTime = mstime[0] else: self.startTime = icu[0] self.firstPri= pri[0] s = swst[:] for val in swst: if ((val<500) or (val>1500) or ((val-swst[0])%22 != 0)): s.remove(val) self.minSwst = min(s) self.maxSwst = max(s) pad = (self.maxSwst - self.minSwst)*8 self.width = 2*pixelCount + pad return self.maxSwst,self.minSwst #Parsers.CEOS.CEOSFormat.ceosTypes['text'] = # {'typeCode': 63, 'subtypeCode': [18,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['leaderFile'] = # {'typeCode': 192, 'subtypeCode': [63,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['dataSetSummary'] = # {'typeCode': 10, 'subtypeCode': [10,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['platformPositionData'] = # {'typeCode': 30, 'subtypeCode': [10,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['facilityData'] = # {'typeCode': 200, 'subtypeCode': [10,31,50]} #Parsers.CEOS.CEOSFormat.ceosTypes['datafileDescriptor'] = # {'typeCode': 192, 'subtypeCode':[63,18,18]} #Parsers.CEOS.CEOSFormat.ceosTypes['signalData'] = # {'typeCode': 10, 'subtypeCode': [50,31,20]} #Parsers.CEOS.CEOSFormat.ceosTypes['nullFileDescriptor'] = # {'typeCode': 192, 'subtypeCode': [192,63,18]}