class COSMO_SkyMed(Sensor):
"""
A class to parse COSMO-SkyMed metadata
"""
parameter_list = (HDF5, ) + Sensor.parameter_list
logging_name = "isce.sensor.COSMO_SkyMed"
family = 'cosmo_skymed'
def __init__(self, family='', name=''):
super().__init__(family if family else self.__class__.family,
name=name)
self.hdf5 = None
#used to allow refactoring on tkfunc
self._imageFileList = None
###Specific doppler functions for CSK
self.dopplerRangeTime = []
self.dopplerAzimuthTime = []
self.azimuthRefTime = None
self.rangeRefTime = None
self.rangeFirstTime = None
self.rangeLastTime = None
## make this a class attribute, and a Sensor.Constant--not a dictionary.
self.constants = {'iBias': 127.5, 'qBias': 127.5}
return None
## Note: this breaks the ISCE convention of getters.
def getFrame(self):
return self.frame
#jng parse or parse_context never used
def parse(self):
try:
fp = h5py.File(self.hdf5, 'r')
except Exception as strerror:
self.logger.error("IOError: %s\n" % strerror)
return None
self.populateMetadata(file=fp)
fp.close()
## Use h5's context management-- TODO: debug and install as 'parse'
def parse_context(self):
try:
with h5py.File(self.hdf5, 'r') as fp:
self.populateMetadata(file=fp)
except Exception as strerror:
self.logger.error("IOError: %s\n" % strerror)
return None
def _populatePlatform(self, file=None):
platform = self.frame.getInstrument().getPlatform()
if np.isnan(file['S01'].attrs['Equivalent First Column Time']) and (
len(file['S01/B001'].attrs['Range First Times']) > 1):
raise NotImplementedError(
'Current CSK reader does not handle RAW data not adjusted for SWST shifts'
)
platform.setMission(
file.attrs['Satellite ID']) # Could use Mission ID as well
platform.setPlanet(Planet(pname="Earth"))
platform.setPointingDirection(
self.lookMap[file.attrs['Look Side'].decode('utf-8')])
platform.setAntennaLength(file.attrs['Antenna Length'])
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
rangePixelSize = Const.c / (2 * file['S01'].attrs['Sampling Rate'])
instrument.setRadarWavelength(file.attrs['Radar Wavelength'])
instrument.setPulseRepetitionFrequency(file['S01'].attrs['PRF'])
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(file['S01'].attrs['Range Chirp Length'])
instrument.setChirpSlope(file['S01'].attrs['Range Chirp Rate'])
instrument.setRangeSamplingRate(file['S01'].attrs['Sampling Rate'])
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
instrument.setBeamNumber(file.attrs['Multi-Beam ID'])
def _populateFrame(self, file):
rft = file['S01']['B001'].attrs['Range First Times'][0]
slantRange = rft * Const.c / 2.0
sensingStart = self._parseNanoSecondTimeStamp(
file.attrs['Scene Sensing Start UTC'])
sensingStop = self._parseNanoSecondTimeStamp(
file.attrs['Scene Sensing Stop UTC'])
centerTime = DTUtil.timeDeltaToSeconds(sensingStop -
sensingStart) / 2.0
sensingMid = sensingStart + datetime.timedelta(
microseconds=int(centerTime * 1e6))
self.frame.setStartingRange(slantRange)
self.frame.setPassDirection(file.attrs['Orbit Direction'])
self.frame.setOrbitNumber(file.attrs['Orbit Number'])
self.frame.setProcessingFacility(file.attrs['Processing Centre'])
self.frame.setProcessingSoftwareVersion(
file.attrs['L0 Software Version'])
self.frame.setPolarization(file['S01'].attrs['Polarisation'])
self.frame.setNumberOfLines(file['S01']['B001'].shape[0])
self.frame.setNumberOfSamples(file['S01']['B001'].shape[1])
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = slantRange + self.frame.getNumberOfSamples() * rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self, file):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
t0 = datetime.datetime.strptime(
file.attrs['Reference UTC'].decode('utf-8'),
'%Y-%m-%d %H:%M:%S.%f000')
t = file.attrs['State Vectors Times']
position = file.attrs['ECEF Satellite Position']
velocity = file.attrs['ECEF Satellite Velocity']
for i in range(len(position)):
vec = StateVector()
dt = t0 + datetime.timedelta(seconds=t[i])
vec.setTime(dt)
vec.setPosition([position[i, 0], position[i, 1], position[i, 2]])
vec.setVelocity([velocity[i, 0], velocity[i, 1], velocity[i, 2]])
orbit.addStateVector(vec)
def populateImage(self, filename):
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setFilename(filename)
rawImage.setAccessMode('read')
rawImage.setWidth(2 * self.frame.getNumberOfSamples())
rawImage.setXmax(2 * self.frame.getNumberOfSamples())
rawImage.setXmin(0)
self.getFrame().setImage(rawImage)
def _populateExtras(self, file):
"""
Populate some extra fields.
"""
self.dopplerRangeTime = file.attrs['Centroid vs Range Time Polynomial']
self.dopplerAzimuthTime = file.attrs[
'Centroid vs Azimuth Time Polynomial']
self.rangeRefTime = file.attrs['Range Polynomial Reference Time']
self.azimuthRefTime = file.attrs['Azimuth Polynomial Reference Time']
self.rangeFirstTime = file['S01']['B001'].attrs['Range First Times'][0]
self.rangeLastTime = self.rangeFirstTime + (
self.frame.getNumberOfSamples() -
1) / self.frame.instrument.getRangeSamplingRate()
def extractImage(self):
"""Extract the raw image data"""
import os
from ctypes import cdll, c_char_p
extract_csk = cdll.LoadLibrary(os.path.dirname(__file__) + '/csk.so')
# Prepare and run the C-based extractor
for i in range(len(self.hdf5FileList)):
#need to create a new instance every time
self.frame = Frame()
self.frame.configure()
appendStr = '_' + str(i)
# if more than one file to contatenate that create different outputs
# but suffixing _i
if (len(self.hdf5FileList) == 1):
appendStr = ''
outputNow = self.output + appendStr
self.hdf5 = self.hdf5FileList[i]
inFile_c = c_char_p(bytes(self.hdf5, 'utf-8'))
outFile_c = c_char_p(bytes(outputNow, 'utf-8'))
extract_csk.extract_csk(inFile_c, outFile_c)
# Now, populate the metadata
try:
fp = h5py.File(self.hdf5, 'r')
except Exception as strerror:
self.logger.error("IOError: %s\n" % strerror)
return
self.populateMetadata(file=fp)
self.populateImage(outputNow)
self._populateExtras(fp)
fp.close()
self.frameList.append(self.frame)
createAuxFile(self.frame, outputNow + '.aux')
self._imageFileList = self.hdf5FileList
return tkfunc(self)
def _parseNanoSecondTimeStamp(self, timestamp):
"""Parse a date-time string with nanosecond precision and return a
datetime object
"""
dateTime, nanoSeconds = timestamp.decode('utf-8').split('.')
microsec = float(nanoSeconds) * 1e-3
dt = datetime.datetime.strptime(dateTime, '%Y-%m-%d %H:%M:%S')
dt = dt + datetime.timedelta(microseconds=microsec)
return dt
def extractDoppler(self):
"""
Return the doppler centroid as defined in the HDF5 file.
"""
quadratic = {}
midtime = (self.rangeLastTime +
self.rangeFirstTime) * 0.5 - self.rangeRefTime
fd_mid = 0.0
x = 1.0
for ind, coeff in enumerate(self.dopplerRangeTime):
fd_mid += coeff * x
x *= midtime
####insarApp style
quadratic['a'] = fd_mid / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
###For roiApp more accurate
####Convert stuff to pixel wise coefficients
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5 * Const.c / dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append(val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs) - 1)
poly.setMean((rref - r0) / dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(coeffs) + 1)
evals = poly(pix)
fit = np.polyfit(pix, evals, len(coeffs) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class EnviSAT_SLC(Sensor):
parameter_list = (ORBIT_DIRECTORY, ORBITFILE, INSTRUMENTFILE,
INSTRUMENT_DIRECTORY, IMAGEFILE) + Sensor.parameter_list
"""
A Class for parsing EnviSAT instrument and imagery files
"""
family = 'envisat'
def __init__(self, family='', name=''):
super(EnviSAT_SLC,
self).__init__(family if family else self.__class__.family,
name=name)
self._imageFile = None
self._instrumentFileData = None
self._imageryFileData = None
self.dopplerRangeTime = None
self.rangeRefTime = None
self.logger = logging.getLogger("isce.sensor.EnviSAT_SLC")
self.frame = None
self.frameList = []
self.constants = {'antennaLength': 10.0, 'iBias': 128, 'qBias': 128}
def getFrame(self):
return self.frame
def parse(self):
"""
Parse both imagery and instrument files and create
objects representing the platform, instrument and scene
"""
self.frame = Frame()
self.frame.configure()
self._imageFile = ImageryFile(fileName=self._imageFileName)
self._imageryFileData = self._imageFile.parse()
if self.instrumentFile in [None, '']:
self.findInstrumentFile()
instrumentFileParser = InstrumentFile(fileName=self.instrumentFile)
self._instrumentFileData = instrumentFileParser.parse()
self.populateMetadata()
def populateMetadata(self):
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
self._populateOrbit()
self.dopplerRangeTime = self._imageryFileData['doppler']
self.rangeRefTime = self._imageryFileData['dopplerOrigin'][0] * 1.0e-9
# print('Doppler confidence: ', 100.0 * self._imageryFileData['dopplerConfidence'][0])
def _populatePlatform(self):
"""Populate the platform object with metadata"""
platform = self.frame.getInstrument().getPlatform()
# Populate the Platform and Scene objects
platform.setMission("Envisat")
platform.setPointingDirection(-1)
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPlanet(Planet(pname="Earth"))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
rangeSampleSpacing = Const.c / (
2 * self._imageryFileData['rangeSamplingRate'])
pri = self._imageryFileData['pri']
####These shouldnt matter for SLC data since data is already focused.
txPulseLength = 512 / 19207680.000000
chirpPulseBandwidth = 16.0e6
chirpSlope = chirpPulseBandwidth / txPulseLength
instrument.setRangePixelSize(rangeSampleSpacing)
instrument.setPulseLength(txPulseLength)
#instrument.setSwath(imageryFileData['SWATH'])
instrument.setRadarFrequency(self._instrumentFileData['frequency'])
instrument.setChirpSlope(chirpSlope)
instrument.setRangeSamplingRate(
self._imageryFileData['rangeSamplingRate'])
instrument.setPulseRepetitionFrequency(1.0 / pri)
#instrument.setRangeBias(rangeBias)
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
def _populateFrame(self):
"""Populate the scene object with metadata"""
numberOfLines = self._imageryFileData['numLines']
numberOfSamples = self._imageryFileData['numSamples']
pri = self._imageryFileData['pri']
startingRange = Const.c * float(
self._imageryFileData['timeToFirstSample']) * 1.0e-9 / 2.0
rangeSampleSpacing = Const.c / (
2 * self._imageryFileData['rangeSamplingRate'])
farRange = startingRange + numberOfSamples * rangeSampleSpacing
first_line_utc = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
center_line_utc = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
last_line_utc = datetime.datetime.strptime(
self._imageryFileData['LAST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
centerTime = DTUtil.timeDeltaToSeconds(last_line_utc -
first_line_utc) / 2.0
center_line_utc = center_line_utc + datetime.timedelta(
microseconds=int(centerTime * 1e6))
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(farRange)
self.frame.setProcessingFacility(self._imageryFileData['PROC_CENTER'])
self.frame.setProcessingSystem(self._imageryFileData['SOFTWARE_VER'])
self.frame.setTrackNumber(int(self._imageryFileData['REL_ORBIT']))
self.frame.setOrbitNumber(int(self._imageryFileData['ABS_ORBIT']))
self.frame.setPolarization(self._imageryFileData['MDS1_TX_RX_POLAR'])
self.frame.setNumberOfSamples(numberOfSamples)
self.frame.setNumberOfLines(numberOfLines)
self.frame.setSensingStart(first_line_utc)
self.frame.setSensingMid(center_line_utc)
self.frame.setSensingStop(last_line_utc)
def _populateOrbit(self):
if self.orbitFile in [None, '']:
self.findOrbitFile()
dorParser = DOR(fileName=self.orbitFile)
dorParser.parse()
startTime = self.frame.getSensingStart() - datetime.timedelta(
minutes=5)
stopTime = self.frame.getSensingStop() + datetime.timedelta(minutes=5)
self.frame.setOrbit(dorParser.orbit.trimOrbit(startTime, stopTime))
def _populateImage(self, outname, width, length):
#farRange = self.frame.getStartingRange() + width*self.frame.getInstrument().getRangeSamplingRate()
# Update the NumberOfSamples and NumberOfLines in the Frame object
self.frame.setNumberOfSamples(width)
self.frame.setNumberOfLines(length)
#self.frame.setFarRange(farRange)
# Create a RawImage object
rawImage = createSlcImage()
rawImage.setFilename(outname)
rawImage.setAccessMode('read')
rawImage.setByteOrder('l')
rawImage.setXmin(0)
rawImage.setXmax(width)
rawImage.setWidth(width)
self.frame.setImage(rawImage)
def extractImage(self):
from datetime import datetime as dt
import tempfile as tf
self.parse()
width = self._imageryFileData['numSamples']
length = self._imageryFileData['numLines']
self._imageFile.extractImage(self.output, width, length)
self._populateImage(self.output, width, length)
pass
def findOrbitFile(self):
datefmt = '%Y%m%d%H%M%S'
# sensingStart = self.frame.getSensingStart()
sensingStart = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
outFile = None
if self.orbitDir in [None, '']:
raise Exception(
'No Envisat Orbit File or Orbit Directory specified')
try:
for fname in os.listdir(self.orbitDir):
if not os.path.isfile(os.path.join(self.orbitDir, fname)):
continue
if not fname.startswith('DOR'):
continue
fields = fname.split('_')
procdate = datetime.datetime.strptime(
fields[-6][-8:] + fields[-5], datefmt)
startdate = datetime.datetime.strptime(fields[-4] + fields[-3],
datefmt)
enddate = datetime.datetime.strptime(fields[-2] + fields[-1],
datefmt)
if (sensingStart > startdate) and (sensingStart < enddate):
outFile = os.path.join(self.orbitDir, fname)
break
except:
raise Exception(
'Error occured when trying to find orbit file in %s' %
(self.orbitDir))
if not outFile:
raise Exception('Envisat orbit file could not be found in %s' %
(self.orbitDir))
self.orbitFile = outFile
return
def findInstrumentFile(self):
datefmt = '%Y%m%d%H%M%S'
sensingStart = datetime.datetime.strptime(
self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
print('sens: ', sensingStart)
outFile = None
if self.instrumentDir in [None, '']:
raise Exception(
'No Envisat Instrument File or Instrument Directory specified')
try:
for fname in os.listdir(self.instrumentDir):
if not os.path.isfile(os.path.join(self.instrumentDir, fname)):
continue
if not fname.startswith('ASA_INS'):
continue
fields = fname.split('_')
procdate = datetime.datetime.strptime(
fields[-6][-8:] + fields[-5], datefmt)
startdate = datetime.datetime.strptime(fields[-4] + fields[-3],
datefmt)
enddate = datetime.datetime.strptime(fields[-2] + fields[-1],
datefmt)
if (sensingStart > startdate) and (sensingStart < enddate):
outFile = os.path.join(self.instrumentDir, fname)
break
except:
raise Exception(
'Error occured when trying to find instrument file in %s' %
(self.instrumentDir))
if not outFile:
raise Exception(
'Envisat instrument file could not be found in %s' %
(self.instrumentDir))
self.instrumentFile = outFile
return
def extractDoppler(self):
"""
Return the doppler centroid as defined in the ASAR file.
"""
quadratic = {}
r0 = self.frame.getStartingRange()
dr = self.frame.instrument.getRangePixelSize()
width = self.frame.getNumberOfSamples()
midr = r0 + (width / 2.0) * dr
midtime = 2 * midr / Const.c - self.rangeRefTime
fd_mid = 0.0
tpow = midtime
for kk in self.dopplerRangeTime:
fd_mid += kk * tpow
tpow *= midtime
####For insarApp
quadratic['a'] = fd_mid / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5 * Const.c / dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append(val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs) - 1)
poly.setMean((rref - r0) / dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(coeffs) + 1)
evals = poly(pix)
fit = np.polyfit(pix, evals, len(coeffs) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class Radarsat2(Sensor):
"""
A Class representing RADARSAT 2 data
"""
family = 'radarsat2'
parameter_list = (XML, TIFF) + Sensor.parameter_list
def __init__(self, family='', name=''):
super().__init__(family if family else self.__class__.family,
name=name)
self.product = _Product()
self.frame = Frame()
self.frame.configure()
def getFrame(self):
return self.frame
def parse(self):
try:
fp = open(self.xml, 'r')
except IOError as strerr:
print("IOError: %s" % strerr)
return
self._xml_root = ElementTree(file=fp).getroot()
self.product.set_from_etnode(self._xml_root)
self.populateMetadata()
fp.close()
def populateMetadata(self):
"""
Create metadata objects from the metadata files
"""
mission = self.product.sourceAttributes.satellite
swath = self.product.sourceAttributes.radarParameters.beams
frequency = self.product.sourceAttributes.radarParameters.radarCenterFrequency
orig_prf = self.product.sourceAttributes.radarParameters.prf # original PRF not necessarily effective PRF
rangePixelSize = self.product.imageAttributes.rasterAttributes.sampledPixelSpacing
rangeSamplingRate = Const.c / (2 * rangePixelSize)
pulseLength = self.product.sourceAttributes.radarParameters.pulseLengths[
0]
pulseBandwidth = self.product.sourceAttributes.radarParameters.pulseBandwidths[
0]
polarization = self.product.sourceAttributes.radarParameters.polarizations
lookSide = lookMap[self.product.sourceAttributes.radarParameters.
antennaPointing.upper()]
facility = self.product.imageGenerationParameters.generalProcessingInformation._processingFacility
version = self.product.imageGenerationParameters.generalProcessingInformation.softwareVersion
lines = self.product.imageAttributes.rasterAttributes.numberOfLines
samples = self.product.imageAttributes.rasterAttributes.numberOfSamplesPerLine
startingRange = self.product.imageGenerationParameters.slantRangeToGroundRange.slantRangeTimeToFirstRangeSample * (
Const.c / 2)
incidenceAngle = (self.product.imageGenerationParameters.
sarProcessingInformation.incidenceAngleNearRange +
self.product.imageGenerationParameters.
sarProcessingInformation.incidenceAngleFarRange) / 2
# some RS2 scenes have oversampled SLC images because processed azimuth bandwidth larger than PRF EJF 2015/08/15
azimuthPixelSize = self.product.imageAttributes.rasterAttributes.sampledLineSpacing # ground spacing in meters
totalProcessedAzimuthBandwidth = self.product.imageGenerationParameters.sarProcessingInformation.totalProcessedAzimuthBandwidth
prf = orig_prf * np.ceil(
totalProcessedAzimuthBandwidth / orig_prf
) # effective PRF can be double original, suggested by Piyush
print("effective PRF %f, original PRF %f" % (prf, orig_prf))
lineFlip = (self.product.imageAttributes.rasterAttributes.
lineTimeOrdering.upper() == 'DECREASING')
if lineFlip:
dataStopTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeFirstLine
dataStartTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeLastLine
else:
dataStartTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeFirstLine
dataStopTime = self.product.imageGenerationParameters.sarProcessingInformation.zeroDopplerTimeLastLine
passDirection = self.product.sourceAttributes.orbitAndAttitude.orbitInformation.passDirection
height = self.product.imageGenerationParameters.sarProcessingInformation._satelliteHeight
####Populate platform
platform = self.frame.getInstrument().getPlatform()
platform.setPlanet(Planet(pname="Earth"))
platform.setMission(mission)
platform.setPointingDirection(lookSide)
platform.setAntennaLength(15.0)
####Populate instrument
instrument = self.frame.getInstrument()
instrument.setRadarFrequency(frequency)
instrument.setPulseRepetitionFrequency(prf)
instrument.setPulseLength(pulseLength)
instrument.setChirpSlope(pulseBandwidth / pulseLength)
instrument.setIncidenceAngle(incidenceAngle)
#self.frame.getInstrument().setRangeBias(0)
instrument.setRangePixelSize(rangePixelSize)
instrument.setRangeSamplingRate(rangeSamplingRate)
instrument.setBeamNumber(swath)
instrument.setPulseLength(pulseLength)
#Populate Frame
#self.frame.setSatelliteHeight(height)
self.frame.setSensingStart(dataStartTime)
self.frame.setSensingStop(dataStopTime)
diffTime = DTUtil.timeDeltaToSeconds(dataStopTime -
dataStartTime) / 2.0
sensingMid = dataStartTime + datetime.timedelta(
microseconds=int(diffTime * 1e6))
self.frame.setSensingMid(sensingMid)
self.frame.setPassDirection(passDirection)
self.frame.setPolarization(polarization)
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(startingRange + (samples - 1) * rangePixelSize)
self.frame.setNumberOfLines(lines)
self.frame.setNumberOfSamples(samples)
self.frame.setProcessingFacility(facility)
self.frame.setProcessingSoftwareVersion(version)
# Initialize orbit objects
# Read into temp orbit first.
# Radarsat 2 needs orbit extensions.
tempOrbit = Orbit()
self.frame.getOrbit().setOrbitSource(
'Header: ' + self.product.sourceAttributes.orbitAndAttitude.
orbitInformation.orbitDataFile)
self.frame.setPassDirection(passDirection)
stateVectors = self.product.sourceAttributes.orbitAndAttitude.orbitInformation.stateVectors
for i in range(len(stateVectors)):
position = [
stateVectors[i].xPosition, stateVectors[i].yPosition,
stateVectors[i].zPosition
]
velocity = [
stateVectors[i].xVelocity, stateVectors[i].yVelocity,
stateVectors[i].zVelocity
]
vec = StateVector()
vec.setTime(stateVectors[i].timeStamp)
vec.setPosition(position)
vec.setVelocity(velocity)
tempOrbit.addStateVector(vec)
planet = self.frame.instrument.platform.planet
orbExt = OrbitExtender(planet=planet)
orbExt.configure()
newOrb = orbExt.extendOrbit(tempOrbit)
for sv in newOrb:
self.frame.getOrbit().addStateVector(sv)
# save the Doppler centroid coefficients, converting units from product.xml file
# units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2)
# ISCE expects Hz, Hz/(range sample), Hz((range sample)^2
# note that RS2 Doppler values are estimated at time dc.dopplerCentroidReferenceTime,
# so the values might need to be adjusted for ISCE usage
# added EJF 2015/08/17
dc = self.product.imageGenerationParameters.dopplerCentroid
poly = dc.dopplerCentroidCoefficients
# need to convert units
poly[1] = poly[1] / rangeSamplingRate
poly[2] = poly[2] / rangeSamplingRate**2
self.doppler_coeff = poly
# similarly save Doppler azimuth fm rate values, converting units
# units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2)
# Guessing that ISCE expects Hz, Hz/(range sample), Hz((range sample)^2
# note that RS2 Doppler values are estimated at time dc.dopplerRateReferenceTime,
# so the values might need to be adjusted for ISCE usage
# added EJF 2015/08/17
dr = self.product.imageGenerationParameters.dopplerRateValues
fmpoly = dr.dopplerRateValuesCoefficients
# need to convert units
fmpoly[1] = fmpoly[1] / rangeSamplingRate
fmpoly[2] = fmpoly[2] / rangeSamplingRate**2
self.azfmrate_coeff = fmpoly
# now calculate effective PRF from the azimuth line spacing after we have the orbit info EJF 2015/08/15
# this does not work because azimuth spacing is on ground. Instead use bandwidth ratio calculated above EJF
# SCHvelocity = self.frame.getSchVelocity()
# SCHvelocity = 7550.75 # hard code orbit velocity for now m/s
# prf = SCHvelocity/azimuthPixelSize
# instrument.setPulseRepetitionFrequency(prf)
def extractImage(self, verbose=True):
'''
Use gdal to extract the slc.
'''
try:
from osgeo import gdal
except ImportError:
raise Exception(
'GDAL python bindings not found. Need this for RSAT2 / TandemX / Sentinel1A.'
)
self.parse()
width = self.frame.getNumberOfSamples()
lgth = self.frame.getNumberOfLines()
lineFlip = (self.product.imageAttributes.rasterAttributes.
lineTimeOrdering.upper() == 'DECREASING')
pixFlip = (self.product.imageAttributes.rasterAttributes.
pixelTimeOrdering.upper() == 'DECREASING')
src = gdal.Open(self.tiff.strip(), gdal.GA_ReadOnly)
cJ = np.complex64(1.0j)
####Images are small enough that we can do it all in one go - Piyush
real = src.GetRasterBand(1).ReadAsArray(0, 0, width, lgth)
imag = src.GetRasterBand(2).ReadAsArray(0, 0, width, lgth)
if (real is None) or (imag is None):
raise Exception(
'Input Radarsat2 SLC seems to not be a 2 band Int16 image.')
data = real + cJ * imag
real = None
imag = None
src = None
if lineFlip:
if verbose:
print('Vertically Flipping data')
data = np.flipud(data)
if pixFlip:
if verbose:
print('Horizontally Flipping data')
data = np.fliplr(data)
data.tofile(self.output)
####
slcImage = isceobj.createSlcImage()
slcImage.setByteOrder('l')
slcImage.setFilename(self.output)
slcImage.setAccessMode('read')
slcImage.setWidth(width)
slcImage.setLength(lgth)
slcImage.setXmin(0)
slcImage.setXmax(width)
# slcImage.renderHdr()
self.frame.setImage(slcImage)
def extractDoppler(self):
'''
self.parse()
Extract doppler information as needed by mocomp
'''
ins = self.frame.getInstrument()
dc = self.product.imageGenerationParameters.dopplerCentroid
quadratic = {}
r0 = self.frame.startingRange
fs = ins.getRangeSamplingRate()
tNear = 2 * r0 / Const.c
tMid = tNear + 0.5 * self.frame.getNumberOfSamples() / fs
t0 = dc.dopplerCentroidReferenceTime
poly = dc.dopplerCentroidCoefficients
fd_mid = 0.0
for kk in range(len(poly)):
fd_mid += poly[kk] * (tMid - t0)**kk
####For insarApp
quadratic['a'] = fd_mid / ins.getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
from isceobj.Util import Poly1D
coeffs = poly
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * t0
r0 = self.frame.getStartingRange()
norm = 0.5 * Const.c / dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append(val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs) - 1)
poly.setMean((rref - r0) / dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(coeffs) + 1)
evals = poly(pix)
fit = np.polyfit(pix, evals, len(coeffs) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class Radarsat1(Sensor):
"""
Code to read CEOSFormat leader files for Radarsat-1 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.
"""
family = 'radarsat1'
logging_name = 'isce.sensor.radarsat1'
parameter_list = (LEADERFILE, IMAGEFILE, PARFILE) + Sensor.parameter_list
auxLength = 50
@logged
def __init__(self, name=''):
super().__init__(family=self.__class__.family, name=name)
self.imageFile = None
self.leaderFile = None
#####Soecific doppler functions for RSAT1
self.doppler_ref_range = None
self.doppler_ref_azi = None
self.doppler_predict = None
self.doppler_DAR = None
self.doppler_coeff = None
self.frame = Frame()
self.frame.configure()
self.constants = {'polarization': 'HH', 'antennaLength': 15}
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(self, file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self, file=self._imageFile)
self.imageFile.parse()
self.populateMetadata()
if self._parFile:
self.parseParFile()
else:
self.populateCEOSOrbit()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.
metadata['Scene reference number'])
try:
rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord.
metadata['Range sampling rate'] * 1e6)
except ZeroDivisionError:
rangePixelSize = 0
ins = self.frame.getInstrument()
platform = ins.getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.
metadata['Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(-1)
platform.setPlanet(Planet(pname='Earth'))
ins.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.
metadata['Incidence angle at scene centre'])
##RSAT-1 does not have PRF for raw data in leader file.
# self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency'])
ins.setRangePixelSize(rangePixelSize)
ins.setPulseLength(
self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] *
1e-6)
chirpPulseBandwidth = 15.50829e6 # Is this really not in the CEOSFormat Header?
ins.setChirpSlope(
chirpPulseBandwidth /
(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] *
1e-6))
ins.setInPhaseValue(7.5)
ins.setQuadratureValue(7.5)
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(
self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
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.imageFDR.metadata['Number of lines per data set'])
self.frame.setNumberOfSamples(
self.imageFile.imageFDR.
metadata['Number of pixels per line per SAR channel'])
self.frame.getOrbit().setOrbitSource('Header')
self.frame.getOrbit().setOrbitQuality(
self.leaderFile.platformPositionRecord.
metadata['Orbital elements designator'])
def populateCEOSOrbit(self):
from isceobj.Orbit.Inertial import ECI2ECR
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(
seconds=self.leaderFile.platformPositionRecord.
metadata['Seconds of day'])
#####Read in orbit in inertial coordinates
orb = Orbit()
for i in range(self.leaderFile.platformPositionRecord.
metadata['Number of data points']):
vec = StateVector()
t = t0 + datetime.timedelta(
seconds=(i * self.leaderFile.platformPositionRecord.
metadata['Time interval between DATA points']))
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'] / 1000.,
dataPoints['Velocity vector Y'] / 1000.,
dataPoints['Velocity vector Z'] / 1000.
])
orb.addStateVector(vec)
#####Convert orbits from ECI to ECEF frame.
t0 = orb._stateVectors[0]._time
ang = self.leaderFile.platformPositionRecord.metadata[
'Greenwich mean hour angle']
cOrb = ECI2ECR(orb, GAST=ang, epoch=t0)
wgsorb = cOrb.convert()
orb = self.frame.getOrbit()
for sv in wgsorb:
orb.addStateVector(sv)
print(sv)
def extractImage(self):
import isceobj
if (self.imageFile is None) or (self.leaderFile is None):
self.parse()
try:
out = open(self.output, 'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
self.imageFile.extractImage(output=out)
out.close()
####RSAT1 is weird. Contains all useful info in RAW data and not leader.
ins = self.frame.getInstrument()
ins.setPulseRepetitionFrequency(self.imageFile.prf)
ins.setPulseLength(self.imageFile.pulseLength)
ins.setRangeSamplingRate(self.imageFile.rangeSamplingRate)
ins.setRangePixelSize(Const.c / (2 * self.imageFile.rangeSamplingRate))
ins.setChirpSlope(self.imageFile.chirpSlope)
######
self.frame.setSensingStart(self.imageFile.sensingStart)
sensingStop = self.imageFile.sensingStart + datetime.timedelta(
seconds=((self.frame.getNumberOfLines() - 1) / self.imageFile.prf))
sensingMid = self.imageFile.sensingStart + datetime.timedelta(
seconds=0.5 *
(sensingStop - self.imageFile.sensingStart).total_seconds())
self.frame.setSensingStop(sensingStop)
self.frame.setSensingMid(sensingMid)
self.frame.setNumberOfSamples(self.imageFile.width)
self.frame.setStartingRange(self.imageFile.startingRange)
farRange = self.imageFile.startingRange + ins.getRangePixelSize(
) * self.imageFile.width * 0.5
self.frame.setFarRange(farRange)
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
rawImage.renderHdr()
self.frame.setImage(rawImage)
def parseParFile(self):
'''Parse the par file if any is available.'''
if self._parFile not in (None, ''):
par = ParFile(self._parFile)
####Update orbit
svs = par['prep_block']['sensor']['ephemeris']['sv_block'][
'state_vector']
datefmt = '%Y%m%d%H%M%S%f'
for entry in svs:
sv = StateVector()
sv.setPosition(
[float(entry['x']),
float(entry['y']),
float(entry['z'])])
sv.setVelocity([
float(entry['xv']),
float(entry['yv']),
float(entry['zv'])
])
sv.setTime(datetime.datetime.strptime(entry['Date'], datefmt))
self.frame.orbit.addStateVector(sv)
self.frame.orbit._stateVectors = sorted(
self.frame.orbit._stateVectors, key=lambda x: x.getTime())
doppinfo = par['prep_block']['sensor']['beam'][
'DopplerCentroidParameters']
#######Selectively update some values.
#######Currently used only for doppler centroids.
self.doppler_ref_range = float(doppinfo['reference_range'])
self.doppler_ref_azi = datetime.datetime.strptime(
doppinfo['reference_date'], '%Y%m%d%H%M%S%f')
self.doppler_predict = float(doppinfo['Predict_doppler'])
self.doppler_DAR = float(doppinfo['DAR_doppler'])
coeff = doppinfo['doppler_centroid_coefficients']
rngOrder = int(coeff['number_of_coefficients_first_dimension']) - 1
azOrder = int(coeff['number_of_coefficients_second_dimension']) - 1
self.doppler_coeff = Poly2D.Poly2D()
self.doppler_coeff.initPoly(rangeOrder=rngOrder,
azimuthOrder=azOrder)
self.doppler_coeff.setMeanRange(self.doppler_ref_range)
self.doppler_coeff.setMeanAzimuth(
secondsSinceMidnight(self.doppler_ref_azi))
parms = []
for ii in range(azOrder + 1):
row = []
for jj in range(rngOrder + 1):
key = 'a%d%d' % (ii, jj)
val = float(coeff[key])
row.append(val)
parms.append(row)
self.doppler_coeff.setCoeffs(parms)
def extractDoppler(self):
'''
Evaluate the doppler polynomial and return the average value for now.
'''
rmin = self.frame.getStartingRange()
rmax = self.frame.getFarRange()
rmid = 0.5 * (rmin + rmax)
delr = Const.c / (2 * self.frame.instrument.rangeSamplingRate)
azmid = secondsSinceMidnight(self.frame.getSensingMid())
print(rmid, self.doppler_coeff.getMeanRange())
print(azmid, self.doppler_coeff.getMeanAzimuth())
if self.doppler_coeff is None:
raise Exception(
'ASF PARFILE was not provided. Cannot determine default doppler.'
)
dopav = self.doppler_coeff(azmid, rmid)
prf = self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic = {}
quadratic['a'] = dopav / prf
quadratic['b'] = 0.
quadratic['c'] = 0.
######Set up the doppler centroid computation just like CSK at mid azimuth
order = self.doppler_coeff._rangeOrder
rng = np.linspace(rmin, rmax, num=(order + 2))
pix = (rng - rmin) / delr
val = [self.doppler_coeff(azmid, x) for x in rng]
print(rng, val)
print(delr, pix)
fit = np.polyfit(pix, val, order)
self.frame._dopplerVsPixel = list(fit[::-1])
# self.frame._dopplerVsPixel = [dopav,0.,0.,0.]
return quadratic
def _decodeSceneReferenceNumber(self, referenceNumber):
return referenceNumber
class ERS_EnviSAT_SLC(Sensor):
parameter_list = (ORBIT_TYPE,
ORBIT_DIRECTORY,
ORBITFILE,
IMAGEFILE) + Sensor.parameter_list
"""
A Class for parsing ERS instrument and imagery files (Envisat format)
"""
family = 'ers'
logging_name = 'isce.sensor.ers_envisat_slc'
def __init__(self,family='',name=''):
super(ERS_EnviSAT_SLC, self).__init__(family if family else self.__class__.family, name=name)
self._imageFile = None
#self._instrumentFileData = None #none for ERS
self._imageryFileData = None
self.dopplerRangeTime = None
self.rangeRefTime = None
self.logger = logging.getLogger("isce.sensor.ERS_EnviSAT_SLC")
self.frame = None
self.frameList = []
#NOTE: copied from ERS_SLC.py... only antennaLength used? -SH
# 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}
def getFrame(self):
return self.frame
def parse(self):
"""
Parse both imagery and create
objects representing the platform, instrument and scene
"""
self.frame = Frame()
self.frame.configure()
self._imageFile = ImageryFile(fileName=self._imageFileName)
self._imageryFileData = self._imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
#self._populateOrbit()
if (self._orbitType == 'ODR'):
self._populateDelftOrbits()
elif (self._orbitType == 'PRC'):
self._populatePRCOrbits()
elif (self._orbitType == 'PDS'):
self._populatePDSOrbits()
#else:
# self._populateHeaderOrbit() #NOTE: No leader file
#NOTE: remove?
self.dopplerRangeTime = self._imageryFileData['doppler']
self.rangeRefTime = self._imageryFileData['dopplerOrigin'][0] * 1.0e-9
# print('Doppler confidence: ', 100.0 * self._imageryFileData['dopplerConfidence'][0])
def _populatePlatform(self):
"""Populate the platform object with metadata"""
platform = self.frame.getInstrument().getPlatform()
# Populate the Platform and Scene objects
platform.setMission("ERS")
platform.setPointingDirection(-1)
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPlanet(Planet(pname="Earth"))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
rangeSampleSpacing = Const.c/(2*self._imageryFileData['rangeSamplingRate'])
pri = self._imageryFileData['pri']
####These shouldnt matter for SLC data since data is already focused.
txPulseLength = 512 / 19207680.000000
chirpPulseBandwidth = 16.0e6
chirpSlope = chirpPulseBandwidth/txPulseLength
instrument.setRangePixelSize(rangeSampleSpacing)
instrument.setPulseLength(txPulseLength)
#instrument.setSwath(imageryFileData['SWATH'])
instrument.setRadarFrequency(self._imageryFileData['radarFrequency'])
instrument.setChirpSlope(chirpSlope)
instrument.setRangeSamplingRate(self._imageryFileData['rangeSamplingRate'])
instrument.setPulseRepetitionFrequency(1.0/pri)
#instrument.setRangeBias(rangeBias)
instrument.setInPhaseValue(self.constants['iBias'])
instrument.setQuadratureValue(self.constants['qBias'])
def _populateFrame(self):
"""Populate the scene object with metadata"""
numberOfLines = self._imageryFileData['numLines']
numberOfSamples = self._imageryFileData['numSamples']
pri = self._imageryFileData['pri']
startingRange = Const.c * float(self._imageryFileData['timeToFirstSample']) * 1.0e-9 / 2.0
rangeSampleSpacing = Const.c/(2*self._imageryFileData['rangeSamplingRate'])
farRange = startingRange + numberOfSamples*rangeSampleSpacing
first_line_utc = datetime.datetime.strptime(self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
center_line_utc = datetime.datetime.strptime(self._imageryFileData['FIRST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
last_line_utc = datetime.datetime.strptime(self._imageryFileData['LAST_LINE_TIME'], '%d-%b-%Y %H:%M:%S.%f')
centerTime = DTUtil.timeDeltaToSeconds(last_line_utc-first_line_utc)/2.0
center_line_utc = center_line_utc + datetime.timedelta(microseconds=int(centerTime*1e6))
self.frame.setStartingRange(startingRange)
self.frame.setFarRange(farRange)
self.frame.setProcessingFacility(self._imageryFileData['PROC_CENTER'])
self.frame.setProcessingSystem(self._imageryFileData['SOFTWARE_VER'])
self.frame.setTrackNumber(int(self._imageryFileData['REL_ORBIT']))
self.frame.setOrbitNumber(int(self._imageryFileData['ABS_ORBIT']))
self.frame.setPolarization(self._imageryFileData['MDS1_TX_RX_POLAR'])
self.frame.setNumberOfSamples(numberOfSamples)
self.frame.setNumberOfLines(numberOfLines)
self.frame.setSensingStart(first_line_utc)
self.frame.setSensingMid(center_line_utc)
self.frame.setSensingStop(last_line_utc)
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()
print(self.frame.getSensingStart())
print(arclist)
orbitFile = arclist.getOrbitFile(self.frame.getSensingStart())
#print(orbitFile)
odr = ODR(file=os.path.join(self._orbitDir,orbitFile))
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 _populateImage(self,outname,width,length):
#farRange = self.frame.getStartingRange() + width*self.frame.getInstrument().getRangeSamplingRate()
# Update the NumberOfSamples and NumberOfLines in the Frame object
self.frame.setNumberOfSamples(width)
self.frame.setNumberOfLines(length)
#self.frame.setFarRange(farRange)
# Create a RawImage object
rawImage = createSlcImage()
rawImage.setFilename(outname)
rawImage.setAccessMode('read')
rawImage.setByteOrder('l')
rawImage.setXmin(0)
rawImage.setXmax(width)
rawImage.setWidth(width)
self.frame.setImage(rawImage)
def extractImage(self):
from datetime import datetime as dt
import tempfile as tf
self.parse()
width = self._imageryFileData['numSamples']
length = self._imageryFileData['numLines']
self._imageFile.extractImage(self.output, width, length)
self._populateImage(self.output, width, length)
pass
def extractDoppler(self):
"""
Return the doppler centroid as defined in the ASAR file.
"""
quadratic = {}
r0 = self.frame.getStartingRange()
dr = self.frame.instrument.getRangePixelSize()
width = self.frame.getNumberOfSamples()
midr = r0 + (width/2.0) * dr
midtime = 2 * midr/ Const.c - self.rangeRefTime
fd_mid = 0.0
tpow = midtime
for kk in self.dopplerRangeTime:
fd_mid += kk * tpow
tpow *= midtime
####For insarApp
quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5*Const.c/dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append( val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs)-1)
poly.setMean( (rref - r0)/dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs)+1)
evals = poly(pix)
fit = np.polyfit(pix,evals, len(coeffs)-1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class Generic(Component):
"""
A class to parse generic SAR data stored in the HDF5 format
"""
logging_name = 'isce.sensor.Generic'
def __init__(self):
super(Generic, self).__init__()
self._hdf5File = None
self.output = None
self.frame = Frame()
self.frame.configure()
self.logger = logging.getLogger('isce.sensor.Generic')
self.descriptionOfVariables = {}
self.dictionaryOfVariables = {
'HDF5': ['self._hdf5File', 'str', 'mandatory'],
'OUTPUT': ['self.output', 'str', 'optional']
}
return None
def getFrame(self):
return self.frame
def parse(self):
try:
fp = h5py.File(self._hdf5File, 'r')
except Exception as strerror:
self.logger.error("IOError: %s" % strerror)
return
self.populateMetadata(fp)
fp.close()
def populateMetadata(self, file):
"""
Create the appropriate metadata objects from our HDF5 file
"""
self._populatePlatform(file)
self._populateInstrument(file)
self._populateFrame(file)
self._populateOrbit(file)
def _populatePlatform(self, file):
platform = self.frame.getInstrument().getPlatform()
platform.setMission(file['Platform'].attrs['Mission'])
platform.setPlanet(Planet(pname='Earth'))
platform.setAntennaLength(file['Platform'].attrs['Antenna Length'])
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
instrument.setRadarWavelength(file['Instrument'].attrs['Wavelength'])
instrument.setPulseRepetitionFrequency(
file['Instrument'].attrs['Pulse Repetition Frequency'])
instrument.setRangePixelSize(
file['Instrument'].attrs['Range Pixel Size'])
instrument.setPulseLength(file['Instrument'].attrs['Pulse Length'])
instrument.setChirpSlope(file['Instrument'].attrs['Chirp Slope'])
instrument.setRangeSamplingRate(
file['Instrument'].attrs['Range Sampling Frequency'])
instrument.setInPhaseValue(file['Frame'].attrs['In Phase Bias'])
instrument.setQuadratureValue(file['Frame'].attrs['Quadrature Bias'])
def _populateFrame(self, file):
size = file['Frame'].shape
start = DTU.parseIsoDateTime(file['Frame'].attrs['Sensing Start'])
stop = DTU.parseIsoDateTime(file['Frame'].attrs['Sensing Stop'])
deltaT = DTU.timeDeltaToSeconds(stop - start)
mid = start + datetime.timedelta(microseconds=int(deltaT / 2.0 * 1e6))
startingRange = file['Frame'].attrs['Starting Range']
rangePixelSize = file['Instrument'].attrs['Range Pixel Size']
farRange = startingRange + size[1] * rangePixelSize
self.frame.setStartingRange(file['Frame'].attrs['Starting Range'])
self.frame.setFarRange(farRange)
self.frame.setNumberOfLines(size[0])
self.frame.setNumberOfSamples(2 * size[1])
self.frame.setSensingStart(start)
self.frame.setSensingMid(mid)
self.frame.setSensingStop(stop)
def _populateOrbit(self, file):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource(file['Orbit'].attrs['Source'])
for i in range(len(file['Orbit']['Time'])):
vec = StateVector()
time = DTU.parseIsoDateTime(file['Orbit']['Time'][i])
vec.setTime(time)
vec.setPosition(list(file['Orbit']['Position'][i]))
vec.setVelocity(list(file['Orbit']['Velocity'][i]))
orbit.addStateVector(vec)
def extractImage(self):
try:
file = h5py.File(self._hdf5File, 'r')
except Exception as strerror:
self.logger.error("IOError: %s" % strerror)
return
size = file['Frame'].shape
dtype = self._translateDataType(file['Frame'].attrs['Image Type'])
length = size[0]
width = size[1]
data = numpy.memmap(self.output,
dtype=dtype,
mode='w+',
shape=(length, width, 2))
data[:, :, :] = file['Frame'][:, :, :]
del data
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('r')
rawImage.setFilename(self.output)
rawImage.setWidth(2 * width)
rawImage.setXmin(0)
rawImage.setXmax(2 * width)
self.frame.setImage(rawImage)
self.populateMetadata(file)
file.close()
def write(self, output, compression=None):
"""
Given a frame object (appropriately populated) and an image, create
an HDF5 from those objects.
"""
if (not self.frame):
self.logger.error("Frame not set")
raise AttributeError("Frame not set")
h5file = h5py.File(output, 'w')
self._writeMetadata(h5file, compression)
def _writeMetadata(self, h5file, compression=None):
self._writePlatform(h5file)
self._writeInstrument(h5file)
self._writeFrame(h5file, compression)
self._writeOrbit(h5file)
def _writePlatform(self, h5file):
platform = self.frame.getInstrument().getPlatform()
if (not platform):
self.logger.error("Platform not set")
raise AttributeError("Platform not set")
group = h5file.create_group('Platform')
group.attrs['Mission'] = platform.getMission()
group.attrs['Planet'] = platform.getPlanet().name
group.attrs['Antenna Length'] = platform.getAntennaLength()
def _writeInstrument(self, h5file):
instrument = self.frame.getInstrument()
if (not instrument):
self.logger.error("Instrument not set")
raise AttributeError("Instrument not set")
group = h5file.create_group('Instrument')
group.attrs['Wavelength'] = instrument.getRadarWavelength()
group.attrs[
'Pulse Repetition Frequency'] = instrument.getPulseRepetitionFrequency(
)
group.attrs['Range Pixel Size'] = instrument.getRangePixelSize()
group.attrs['Pulse Length'] = instrument.getPulseLength()
group.attrs['Chirp Slope'] = instrument.getChirpSlope()
group.attrs[
'Range Sampling Frequency'] = instrument.getRangeSamplingRate()
group.attrs['In Phase Bias'] = instrument.getInPhaseValue()
group.attrs['Quadrature Bias'] = instrument.getQuadratureValue()
def _writeFrame(self, h5file, compression=None):
group = self._writeImage(h5file, compression)
group.attrs['Starting Range'] = self.frame.getStartingRange()
group.attrs['Sensing Start'] = self.frame.getSensingStart().isoformat()
group.attrs['Sensing Stop'] = self.frame.getSensingStop().isoformat()
def _writeImage(self, h5file, compression=None):
image = self.frame.getImage()
if (not image):
self.logger.error("Image not set")
raise AttributeError("Image not set")
filename = image.getFilename()
length = image.getLength()
width = image.getWidth()
dtype = self._translateDataType(image.dataType)
if (image.dataType == 'BYTE'):
width = int(width / 2)
self.logger.debug("Width: %s" % (width))
self.logger.debug("Length: %s" % (length))
data = numpy.memmap(filename,
dtype=dtype,
mode='r',
shape=(length, 2 * width))
dset = h5file.create_dataset("Frame", (length, width, 2),
dtype=dtype,
compression=compression)
dset.attrs['Image Type'] = image.dataType
dset[:, :, 0] = data[:, ::2]
dset[:, :, 1] = data[:, 1::2]
del data
return dset
def _writeOrbit(self, h5file):
# Add orbit information
(time, position, velocity) = self._orbitToArray()
group = h5file.create_group("Orbit")
group.attrs['Source'] = self.frame.getOrbit().getOrbitSource()
group.attrs['Reference Frame'] = self.frame.getOrbit(
).getReferenceFrame()
timedset = h5file.create_dataset("Orbit/Time",
time.shape,
dtype=time.dtype)
posdset = h5file.create_dataset("Orbit/Position",
position.shape,
dtype=numpy.float64)
veldset = h5file.create_dataset("Orbit/Velocity",
velocity.shape,
dtype=numpy.float64)
timedset[...] = time
posdset[...] = position
veldset[...] = velocity
def _orbitToArray(self):
orbit = self.frame.getOrbit()
if (not orbit):
self.logger.error("Orbit not set")
raise AttributeError("Orbit not set")
time = []
position = []
velocity = []
for sv in orbit:
timeString = sv.getTime().isoformat()
time.append(timeString)
position.append(sv.getPosition())
velocity.append(sv.getVelocity())
return numpy.array(time), numpy.array(position), numpy.array(velocity)
def _translateDataType(self, imageType):
dtype = ''
if (imageType == 'BYTE'):
dtype = 'int8'
elif (imageType == 'CFLOAT'):
dtype = 'float32'
elif (imageType == 'SHORT'):
dtype = 'int16'
else:
self.logger.error("Unknown data type %s" % (imageType))
raise ValueError("Unknown data type %s" % (imageType))
return dtype
class Radarsat1(Component):
"""
Code to read CEOSFormat leader files for Radarsat-1 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.
"""
auxLength = 50
def __init__(self):
Component.__init__(self)
self._leaderFile = None
self._imageFile = None
self._parFile = None
self.output = None
self.imageFile = None
self.leaderFile = None
#####Soecific doppler functions for RSAT1
self.doppler_ref_range = None
self.doppler_ref_azi = None
self.doppler_predict = None
self.doppler_DAR = None
self.doppler_coeff = None
self.frame = Frame()
self.frame.configure()
self.constants = {'polarization': 'HH', 'antennaLength': 15}
self.descriptionOfVariables = {}
self.dictionaryOfVariables = {
'LEADERFILE': ['self._leaderFile', 'str', 'mandatory'],
'IMAGEFILE': ['self._imageFile', 'str', 'mandatory'],
'PARFILE': ['self._parFile', 'str', 'optional'],
'OUTPUT': ['self.output', 'str', 'optional']
}
def getFrame(self):
return self.frame
def parse(self):
self.leaderFile = LeaderFile(self, file=self._leaderFile)
self.leaderFile.parse()
self.imageFile = ImageFile(self, file=self._imageFile)
self.imageFile.parse()
self.populateMetadata()
def populateMetadata(self):
"""
Create the appropriate metadata objects from our CEOSFormat metadata
"""
frame = self._decodeSceneReferenceNumber(
self.leaderFile.sceneHeaderRecord.
metadata['Scene reference number'])
try:
rangePixelSize = Const.c / (2 * self.leaderFile.sceneHeaderRecord.
metadata['Range sampling rate'] * 1e6)
except ZeroDivisionError:
rangePixelSize = 0
ins = self.frame.getInstrument()
platform = ins.getPlatform()
platform.setMission(self.leaderFile.sceneHeaderRecord.
metadata['Sensor platform mission identifier'])
platform.setAntennaLength(self.constants['antennaLength'])
platform.setPointingDirection(-1)
platform.setPlanet(Planet('Earth'))
ins.setRadarWavelength(
self.leaderFile.sceneHeaderRecord.metadata['Radar wavelength'])
ins.setIncidenceAngle(self.leaderFile.sceneHeaderRecord.
metadata['Incidence angle at scene centre'])
##RSAT-1 does not have PRF for raw data in leader file.
# self.frame.getInstrument().setPulseRepetitionFrequency(self.leaderFile.sceneHeaderRecord.metadata['Pulse Repetition Frequency'])
ins.setRangePixelSize(rangePixelSize)
ins.setPulseLength(
self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] *
1e-6)
chirpPulseBandwidth = 15.50829e6 # Is this really not in the CEOSFormat Header?
ins.setChirpSlope(
chirpPulseBandwidth /
(self.leaderFile.sceneHeaderRecord.metadata['Range pulse length'] *
1e-6))
ins.setInPhaseValue(7.5)
ins.setQuadratureValue(7.5)
self.frame.setFrameNumber(frame)
self.frame.setOrbitNumber(
self.leaderFile.sceneHeaderRecord.metadata['Orbit number'])
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.imageFDR.metadata['Number of lines per data set'])
self.frame.setNumberOfSamples(
self.imageFile.imageFDR.
metadata['Number of pixels per line per SAR channel'])
self.frame.getOrbit().setOrbitSource('Header')
self.frame.getOrbit().setOrbitQuality(
self.leaderFile.platformPositionRecord.
metadata['Orbital elements designator'])
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(
seconds=self.leaderFile.platformPositionRecord.
metadata['Seconds of day'])
#####Read in orbit in inertial coordinates
orb = Orbit()
for i in range(self.leaderFile.platformPositionRecord.
metadata['Number of data points']):
vec = StateVector()
t = t0 + datetime.timedelta(
seconds=(i * self.leaderFile.platformPositionRecord.
metadata['Time interval between DATA points']))
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'] / 1000.,
dataPoints['Velocity vector Y'] / 1000.,
dataPoints['Velocity vector Z'] / 1000.
])
orb.addStateVector(vec)
#####Convert orbits from ECI to ECEF frame.
convOrb = ECI2ECEF(orb, eci='ECI_TOD')
wgsorb = convOrb.convert()
orb = self.frame.getOrbit()
for sv in wgsorb:
orb.addStateVector(sv)
self.parseParFile()
def extractImage(self):
import isceobj
if (self.imageFile is None) or (self.leaderFile is None):
self.parse()
try:
out = open(self.output, 'wb')
except IOError as strerr:
self.logger.error("IOError: %s" % strerr)
self.imageFile.extractImage(output=out)
out.close()
####RSAT1 is weird. Contains all useful info in RAW data and not leader.
ins = self.frame.getInstrument()
ins.setPulseRepetitionFrequency(self.imageFile.prf)
ins.setPulseLength(self.imageFile.pulseLength)
ins.setRangeSamplingRate(self.imageFile.rangeSamplingRate)
ins.setRangePixelSize(Const.c / (2 * self.imageFile.rangeSamplingRate))
ins.setChirpSlope(self.imageFile.chirpSlope)
######
self.frame.setSensingStart(self.imageFile.sensingStart)
sensingStop = self.imageFile.sensingStart + datetime.timedelta(
seconds=((self.frame.getNumberOfLines() - 1) / self.imageFile.prf))
sensingMid = self.imageFile.sensingStart + datetime.timedelta(
seconds=0.5 *
(sensingStop - self.imageFile.sensingStart).total_seconds())
self.frame.setSensingStop(sensingStop)
self.frame.setSensingMid(sensingMid)
self.frame.setNumberOfSamples(self.imageFile.width)
self.frame.setStartingRange(self.imageFile.startingRange)
farRange = self.imageFile.startingRange + ins.getRangePixelSize(
) * self.imageFile.width * 0.5
self.frame.setFarRange(farRange)
rawImage = isceobj.createRawImage()
rawImage.setByteOrder('l')
rawImage.setAccessMode('read')
rawImage.setFilename(self.output)
rawImage.setWidth(self.imageFile.width)
rawImage.setXmin(0)
rawImage.setXmax(self.imageFile.width)
rawImage.renderHdr()
self.frame.setImage(rawImage)
def parseParFile(self):
'''Parse the par file if any is available.'''
if self._parFile not in (None, ''):
par = ParFile(self._parFile)
doppinfo = par['prep_block']['sensor']['beam'][
'DopplerCentroidParameters']
#######Selectively update some values.
#######Currently used only for doppler centroids.
self.doppler_ref_range = float(doppinfo['reference_range'])
self.doppler_ref_azi = datetime.datetime.strptime(
doppinfo['reference_date'], '%Y%m%d%H%M%S%f')
self.doppler_predict = float(doppinfo['Predict_doppler'])
self.doppler_DAR = float(doppinfo['DAR_doppler'])
coeff = doppinfo['doppler_centroid_coefficients']
rngOrder = int(coeff['number_of_coefficients_first_dimension'])
azOrder = int(coeff['number_of_coefficients_second_dimension'])
self.doppler_coeff = Polynomial(rangeOrder=rngOrder,
azimuthOrder=azOrder)
self.doppler_coeff.setMeanRange(self.doppler_ref_range)
self.doppler_coeff.setMeanAzimuth(
secondsSinceMidnight(self.doppler_ref_azi))
for ii in range(azOrder):
for jj in range(rngOrder):
key = 'a%d%d' % (ii, jj)
val = float(coeff[key])
self.doppler_coeff.setCoeff(ii, jj, val)
def extractDoppler(self):
'''
Evaluate the doppler polynomial and return the average value for now.
'''
rmin = self.frame.getStartingRange()
rmax = self.frame.getFarRange()
rmid = 0.5 * (rmin + rmax)
azmid = secondsSinceMidnight(self.frame.getSensingMid())
print(rmid, self.doppler_coeff.getMeanRange())
print(azmid, self.doppler_coeff.getMeanAzimuth())
if self.doppler_coeff is None:
raise Exception(
'ASF PARFILE was not provided. Cannot determine default doppler.'
)
dopav = self.doppler_coeff(azmid, rmid)
prf = self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic = {}
quadratic['a'] = dopav / prf
quadratic['b'] = 0.
quadratic['c'] = 0.
return quadratic
def _decodeSceneReferenceNumber(self, referenceNumber):
return referenceNumber
class SAOCOM_SLC(Sensor):
parameter_list = (IMAGEFILE,
XEMTFILE,
XMLFILE) + Sensor.parameter_list
"""
A Class for parsing SAOCOM instrument and imagery files
"""
family = 'saocom_slc'
def __init__(self,family='',name=''):
super(SAOCOM_SLC, self).__init__(family if family else self.__class__.family, name=name)
self._imageFile = None
self._xemtFileParser = None
self._xmlFileParser = None
self._instrumentFileData = None
self._imageryFileData = None
self.dopplerRangeTime = None
self.rangeRefTime = None
self.azimuthRefTime = None
self.rangeFirstTime = None
self.rangeLastTime = None
self.logger = logging.getLogger("isce.sensor.SAOCOM_SLC")
self.frame = None
self.frameList = []
self.lookMap = {'RIGHT': -1,
'LEFT': 1}
self.nearIncidenceAngle = {'S1DP': 20.7,
'S2DP': 24.9,
'S3DP': 29.1,
'S4DP': 33.7,
'S5DP': 38.2,
'S6DP': 41.3,
'S7DP': 44.6,
'S8DP': 47.2,
'S9DP': 48.8,
'S1QP': 17.6,
'S2QP': 19.5,
'S3QP': 21.4,
'S4QP': 23.2,
'S5QP': 25.3,
'S6QP': 27.2,
'S7QP': 29.6,
'S8QP': 31.2,
'S9QP': 33.0,
'S10QP': 34.6}
self.farIncidenceAngle = {'S1DP': 25.0,
'S2DP': 29.2,
'S3DP': 33.8,
'S4DP': 38.3,
'S5DP': 41.3,
'S6DP': 44.5,
'S7DP': 47.1,
'S8DP': 48.7,
'S9DP': 50.2,
'S1QP': 19.6,
'S2QP': 21.5,
'S3QP': 23.3,
'S4QP': 25.4,
'S5QP': 27.3,
'S6QP': 29.6,
'S7QP': 31.2,
'S8QP': 33.0,
'S9QP': 34.6,
'S10QP': 35.5}
def parse(self):
"""
Parse both imagery and instrument files and create
objects representing the platform, instrument and scene
"""
self.frame = Frame()
self.frame.configure()
self._xemtFileParser = XEMTFile(fileName=self.xemtFile)
self._xemtFileParser.parse()
self._xmlFileParser = XMLFile(fileName=self.xmlFile)
self._xmlFileParser.parse()
self.populateMetadata()
def populateMetadata(self):
self._populatePlatform()
self._populateInstrument()
self._populateFrame()
self._populateOrbit()
self._populateExtras()
def _populatePlatform(self):
"""Populate the platform object with metadata"""
platform = self.frame.getInstrument().getPlatform()
# Populate the Platform and Scene objects
platform.setMission(self._xmlFileParser.sensorName)
platform.setPointingDirection(self.lookMap[self._xmlFileParser.sideLooking])
platform.setAntennaLength(9.968)
platform.setPlanet(Planet(pname="Earth"))
def _populateInstrument(self):
"""Populate the instrument object with metadata"""
instrument = self.frame.getInstrument()
rangePixelSize = self._xmlFileParser.PSRng
azimuthPixelSize = self._xmlFileParser.PSAz
radarWavelength = Const.c/float(self._xmlFileParser.fc_hz)
instrument.setRadarWavelength(radarWavelength)
instrument.setPulseRepetitionFrequency(self._xmlFileParser.prf)
instrument.setRangePixelSize(rangePixelSize)
instrument.setAzimuthPixelSize(azimuthPixelSize)
instrument.setPulseLength(self._xmlFileParser.pulseLength)
instrument.setChirpSlope(float(self._xmlFileParser.pulseBandwidth)/float(self._xmlFileParser.pulseLength))
instrument.setRangeSamplingRate(self._xmlFileParser.frg)
incAngle = 0.5*(self.nearIncidenceAngle[self._xemtFileParser.beamID] + self.farIncidenceAngle[self._xemtFileParser.beamID])
instrument.setIncidenceAngle(incAngle)
def _populateFrame(self):
"""Populate the scene object with metadata"""
rft = self._xmlFileParser.rangeStartTime
slantRange = float(rft)*Const.c/2.0
self.frame.setStartingRange(slantRange)
sensingStart = self._parseNanoSecondTimeStamp(self._xmlFileParser.azimuthStartTime)
sensingTime = self._xmlFileParser.lines/self._xmlFileParser.prf
sensingStop = sensingStart + datetime.timedelta(seconds=sensingTime)
sensingMid = sensingStart + datetime.timedelta(seconds=0.5*sensingTime)
self.frame.setPassDirection(self._xmlFileParser.orbitDirection)
self.frame.setProcessingFacility(self._xemtFileParser.facilityID)
self.frame.setProcessingSoftwareVersion(self._xemtFileParser.softVersion)
self.frame.setPolarization(self._xmlFileParser.polarization)
self.frame.setNumberOfLines(self._xmlFileParser.lines)
self.frame.setNumberOfSamples(self._xmlFileParser.samples)
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = slantRange + (self.frame.getNumberOfSamples()-1)*rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
t0 = self._parseNanoSecondTimeStamp(self._xmlFileParser.orbitStartTime)
t = np.arange(self._xmlFileParser.numberSV)*self._xmlFileParser.deltaTimeSV
position = self._xmlFileParser.orbitPositionXYZ
velocity = self._xmlFileParser.orbitVelocityXYZ
for i in range(0,self._xmlFileParser.numberSV):
vec = StateVector()
dt = t0 + datetime.timedelta(seconds=t[i])
vec.setTime(dt)
vec.setPosition([position[i*3],position[i*3+1],position[i*3+2]])
vec.setVelocity([velocity[i*3],velocity[i*3+1],velocity[i*3+2]])
orbit.addStateVector(vec)
print("valor "+str(i)+": "+str(dt))
def _populateExtras(self):
from isceobj.Doppler.Doppler import Doppler
self.dopplerRangeTime = self._xmlFileParser.dopRngTime
self.rangeRefTime = self._xmlFileParser.trg
self.rangeFirstTime = self._xmlFileParser.rangeStartTime
def extractImage(self):
"""
Exports GeoTiff to ISCE format.
"""
from osgeo import gdal
ds = gdal.Open(self._imageFileName)
metadata = ds.GetMetadata()
geoTs = ds.GetGeoTransform() #GeoTransform
prj = ds.GetProjection() #Projection
dataType = ds.GetRasterBand(1).DataType
gcps = ds.GetGCPs()
sds = ds.ReadAsArray()
# Output raster array to ISCE file
driver = gdal.GetDriverByName('ISCE')
export = driver.Create(self.output, ds.RasterXSize, ds.RasterYSize, 1, dataType)
band = export.GetRasterBand(1)
band.WriteArray(sds)
export.SetGeoTransform(geoTs)
export.SetMetadata(metadata)
export.SetProjection(prj)
export.SetGCPs(gcps,prj)
band.FlushCache()
export.FlushCache()
self.parse()
slcImage = isceobj.createSlcImage()
slcImage.setFilename(self.output)
slcImage.setXmin(0)
slcImage.setXmax(self.frame.getNumberOfSamples())
slcImage.setWidth(self.frame.getNumberOfSamples())
slcImage.setAccessMode('r')
self.frame.setImage(slcImage)
def _parseNanoSecondTimeStamp(self,timestamp):
"""
Parse a date-time string with microsecond precision and return a datetime object
"""
dateTime,decSeconds = timestamp.split('.')
microsec = float("0."+decSeconds)*1e6
dt = datetime.datetime.strptime(dateTime,'%d-%b-%Y %H:%M:%S')
dt = dt + datetime.timedelta(microseconds=microsec)
return dt
def extractDoppler(self):
"""
Return the doppler centroid.
"""
quadratic = {}
r0 = self.frame.getStartingRange()
dr = self.frame.instrument.getRangePixelSize()
width = self.frame.getNumberOfSamples()
midr = r0 + (width/2.0) * dr
midtime = 2 * midr/ Const.c - self.rangeRefTime
fd_mid = 0.0
tpow = midtime
for kk in self.dopplerRangeTime:
fd_mid += kk * tpow
tpow *= midtime
####For insarApp
quadratic['a'] = fd_mid/self.frame.getInstrument().getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp
####More accurate
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5*Const.c/dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append( val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs)-1)
poly.setMean( (rref - r0)/dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0, self.frame.getNumberOfSamples(), num=len(coeffs)+1)
evals = poly(pix)
fit = np.polyfit(pix,evals, len(coeffs)-1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
return quadratic
class COSMO_SkyMed_SLC(Sensor):
"""
A class representing a Level1Product meta data.
Level1Product(hdf5=h5filename) will parse the hdf5
file and produce an object with attributes for metadata.
"""
parameter_list = (HDF5, ) + Sensor.parameter_list
logging_name = 'isce.Sensor.COSMO_SkyMed_SLC'
family = 'cosmo_skymed_slc'
def __init__(self, family='', name=''):
super(COSMO_SkyMed_SLC,
self).__init__(family if family else self.__class__.family,
name=name)
self.frame = Frame()
self.frame.configure()
# Some extra processing parameters unique to CSK SLC (currently)
self.dopplerRangeTime = []
self.dopplerAzimuthTime = []
self.azimuthRefTime = None
self.rangeRefTime = None
self.rangeFirstTime = None
self.rangeLastTime = None
self.lookMap = {'RIGHT': -1, 'LEFT': 1}
return
def __getstate__(self):
d = dict(self.__dict__)
del d['logger']
return d
def __setstate__(self, d):
self.__dict__.update(d)
self.logger = logging.getLogger('isce.Sensor.COSMO_SkyMed_SLC')
return
def getFrame(self):
return self.frame
def parse(self):
try:
fp = h5py.File(self.hdf5, 'r')
except Exception as strerr:
self.logger.error("IOError: %s" % strerr)
return None
self.populateMetadata(fp)
fp.close()
def populateMetadata(self, file):
"""
Populate our Metadata objects
"""
self._populatePlatform(file)
self._populateInstrument(file)
self._populateFrame(file)
self._populateOrbit(file)
self._populateExtras(file)
def _populatePlatform(self, file):
platform = self.frame.getInstrument().getPlatform()
platform.setMission(file.attrs['Satellite ID'])
platform.setPointingDirection(
self.lookMap[file.attrs['Look Side'].decode('utf-8')])
platform.setPlanet(Planet(pname="Earth"))
####This is an approximation for spotlight mode
####In spotlight mode, antenna length changes with azimuth position
platform.setAntennaLength(file.attrs['Antenna Length'])
try:
if file.attrs['Multi-Beam ID'].startswith('ES'):
platform.setAntennaLength(
16000.0 / file['S01/SBI'].attrs['Line Time Interval'])
except:
pass
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
# rangePixelSize = Const.c/(2*file['S01'].attrs['Sampling Rate'])
rangePixelSize = file['S01/SBI'].attrs['Column Spacing']
instrument.setRadarWavelength(file.attrs['Radar Wavelength'])
# instrument.setPulseRepetitionFrequency(file['S01'].attrs['PRF'])
instrument.setPulseRepetitionFrequency(
1.0 / file['S01/SBI'].attrs['Line Time Interval'])
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(file['S01'].attrs['Range Chirp Length'])
instrument.setChirpSlope(file['S01'].attrs['Range Chirp Rate'])
# instrument.setRangeSamplingRate(file['S01'].attrs['Sampling Rate'])
instrument.setRangeSamplingRate(
1.0 / file['S01/SBI'].attrs['Column Time Interval'])
incangle = 0.5 * (file['S01/SBI'].attrs['Far Incidence Angle'] +
file['S01/SBI'].attrs['Near Incidence Angle'])
instrument.setIncidenceAngle(incangle)
def _populateFrame(self, file):
rft = file['S01/SBI'].attrs['Zero Doppler Range First Time']
slantRange = rft * Const.c / 2.0
self.frame.setStartingRange(slantRange)
referenceUTC = self._parseNanoSecondTimeStamp(
file.attrs['Reference UTC'])
relStart = file['S01/SBI'].attrs['Zero Doppler Azimuth First Time']
relEnd = file['S01/SBI'].attrs['Zero Doppler Azimuth Last Time']
relMid = 0.5 * (relStart + relEnd)
sensingStart = self._combineDateTime(referenceUTC, relStart)
sensingStop = self._combineDateTime(referenceUTC, relEnd)
sensingMid = self._combineDateTime(referenceUTC, relMid)
self.frame.setPassDirection(file.attrs['Orbit Direction'])
self.frame.setOrbitNumber(file.attrs['Orbit Number'])
self.frame.setProcessingFacility(file.attrs['Processing Centre'])
self.frame.setProcessingSoftwareVersion(
file.attrs['L0 Software Version'])
self.frame.setPolarization(file['S01'].attrs['Polarisation'])
self.frame.setNumberOfLines(file['S01/SBI'].shape[0])
self.frame.setNumberOfSamples(file['S01/SBI'].shape[1])
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = slantRange + (self.frame.getNumberOfSamples() -
1) * rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self, file):
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
t0 = datetime.datetime.strptime(
file.attrs['Reference UTC'].decode('utf-8'),
'%Y-%m-%d %H:%M:%S.%f000')
t = file.attrs['State Vectors Times']
position = file.attrs['ECEF Satellite Position']
velocity = file.attrs['ECEF Satellite Velocity']
for i in range(len(position)):
vec = StateVector()
dt = t0 + datetime.timedelta(seconds=t[i])
vec.setTime(dt)
vec.setPosition([position[i, 0], position[i, 1], position[i, 2]])
vec.setVelocity([velocity[i, 0], velocity[i, 1], velocity[i, 2]])
orbit.addStateVector(vec)
def _populateExtras(self, file):
"""
Populate some of the extra fields unique to processing TSX data.
In the future, other sensors may need this information as well,
and a re-organization may be necessary.
"""
from isceobj.Doppler.Doppler import Doppler
self.dopplerRangeTime = file.attrs['Centroid vs Range Time Polynomial']
self.dopplerAzimuthTime = file.attrs[
'Centroid vs Azimuth Time Polynomial']
self.rangeRefTime = file.attrs['Range Polynomial Reference Time']
self.azimuthRefTime = file.attrs['Azimuth Polynomial Reference Time']
self.rangeFirstTime = file['S01/SBI'].attrs[
'Zero Doppler Range First Time']
self.rangeLastTime = file['S01/SBI'].attrs[
'Zero Doppler Range Last Time']
# get Doppler rate information, vs. azimuth first EJF 2015/00/05
# guessing that same scale applies as for Doppler centroid
self.dopplerRateCoeffs = file.attrs[
'Doppler Rate vs Azimuth Time Polynomial']
def extractImage(self):
import os
from ctypes import cdll, c_char_p
extract_csk = cdll.LoadLibrary(os.path.dirname(__file__) + '/csk.so')
inFile_c = c_char_p(bytes(self.hdf5, 'utf-8'))
outFile_c = c_char_p(bytes(self.output, 'utf-8'))
extract_csk.extract_csk_slc(inFile_c, outFile_c)
self.parse()
slcImage = isceobj.createSlcImage()
slcImage.setFilename(self.output)
slcImage.setXmin(0)
slcImage.setXmax(self.frame.getNumberOfSamples())
slcImage.setWidth(self.frame.getNumberOfSamples())
slcImage.setAccessMode('r')
self.frame.setImage(slcImage)
def _parseNanoSecondTimeStamp(self, timestamp):
"""
Parse a date-time string with nanosecond precision and return a datetime object
"""
dateTime, nanoSeconds = timestamp.decode('utf-8').split('.')
microsec = float(nanoSeconds) * 1e-3
dt = datetime.datetime.strptime(dateTime, '%Y-%m-%d %H:%M:%S')
dt = dt + datetime.timedelta(microseconds=microsec)
return dt
def _combineDateTime(self, dobj, secsstr):
'''Takes the date from dobj and time from secs to spit out a date time object.
'''
sec = float(secsstr)
dt = datetime.timedelta(seconds=sec)
return datetime.datetime.combine(dobj.date(), datetime.time(0, 0)) + dt
def extractDoppler(self):
"""
Return the doppler centroid as defined in the HDF5 file.
"""
import numpy as np
quadratic = {}
midtime = (self.rangeLastTime +
self.rangeFirstTime) * 0.5 - self.rangeRefTime
fd_mid = 0.0
x = 1.0
for ind, coeff in enumerate(self.dopplerRangeTime):
fd_mid += coeff * x
x *= midtime
####insarApp style
quadratic['a'] = fd_mid / self.frame.getInstrument(
).getPulseRepetitionFrequency()
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp more accurate
####Convert stuff to pixel wise coefficients
from isceobj.Util import Poly1D
coeffs = self.dopplerRangeTime
dr = self.frame.getInstrument().getRangePixelSize()
rref = 0.5 * Const.c * self.rangeRefTime
r0 = self.frame.getStartingRange()
norm = 0.5 * Const.c / dr
dcoeffs = []
for ind, val in enumerate(coeffs):
dcoeffs.append(val / (norm**ind))
poly = Poly1D.Poly1D()
poly.initPoly(order=len(coeffs) - 1)
poly.setMean((rref - r0) / dr - 1.0)
poly.setCoeffs(dcoeffs)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(coeffs) + 1)
evals = poly(pix)
fit = np.polyfit(pix, evals, len(coeffs) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', fit[::-1])
#EMG - 20160420 This section was introduced in the populateMetadata method by EJF in r2022
#Its pupose seems to be to set self.doppler_coeff and self.azfmrate_coeff, which don't seem
#to be used anywhere in ISCE. Need to take time to understand the need for this and consult
#with EJF.
#
## save the Doppler centroid coefficients, converting units from .h5 file
## units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2)
## ISCE expects Hz, Hz/(range sample), Hz/(range sample)^2
## note that RS2 Doppler values are estimated at time dc.dopplerCentroidReferenceTime,
## so the values might need to be adjusted for ISCE usage
## adapted from RS2 version EJF 2015/09/05
# poly = self.frame._dopplerVsPixel
# rangeSamplingRate = self.frame.getInstrument().getPulseRepetitionFrequency()
# # need to convert units
# poly[1] = poly[1]/rangeSamplingRate
# poly[2] = poly[2]/rangeSamplingRate**2
# self.doppler_coeff = poly
#
## similarly save Doppler azimuth fm rate values, converting units
## units in the file are quadratic coefficients in Hz, Hz/sec, and Hz/(sec^2)
## units are already converted below
## Guessing that ISCE expects Hz, Hz/(azimuth line), Hz/(azimuth line)^2
## note that RS2 Doppler values are estimated at time dc.dopplerRateReferenceTime,
## so the values might need to be adjusted for ISCE usage
## modified from RS2 version EJF 2015/09/05
## CSK Doppler azimuth FM rate not yet implemented in reading section, set to zero for now
#
# fmpoly = self.dopplerRateCoeffs
# # don't need to convert units
## fmpoly[1] = fmpoly[1]/rangeSamplingRate
## fmpoly[2] = fmpoly[2]/rangeSamplingRate**2
# self.azfmrate_coeff = fmpoly
#EMG - 20160420
return quadratic
class ICEYE_SLC(Sensor):
"""
A class representing a Level1Product meta data.
Level1Product(hdf5=h5filename) will parse the hdf5
file and produce an object with attributes for metadata.
"""
parameter_list = (HDF5, APPLY_SLANT_RANGE_PHASE) + Sensor.parameter_list
logging_name = 'isce.Sensor.ICEYE_SLC'
family = 'iceye_slc'
def __init__(self, family='', name=''):
super(ICEYE_SLC,
self).__init__(family if family else self.__class__.family,
name=name)
self.frame = Frame()
self.frame.configure()
# Some extra processing parameters unique to CSK SLC (currently)
self.dopplerRangeTime = []
self.dopplerAzimuthTime = []
self.azimuthRefTime = None
self.rangeRefTime = None
self.rangeFirstTime = None
self.rangeLastTime = None
self.lookMap = {'RIGHT': -1, 'LEFT': 1}
return
def __getstate__(self):
d = dict(self.__dict__)
del d['logger']
return d
def __setstate__(self, d):
self.__dict__.update(d)
self.logger = logging.getLogger('isce.Sensor.ICEYE_SLC')
return
def getFrame(self):
return self.frame
def parse(self):
try:
fp = h5py.File(self.hdf5, 'r')
except Exception as strerr:
self.logger.error("IOError: %s" % strerr)
return None
self.populateMetadata(fp)
fp.close()
def populateMetadata(self, file):
"""
Populate our Metadata objects
"""
self._populatePlatform(file)
self._populateInstrument(file)
self._populateFrame(file)
self._populateOrbit(file)
self._populateExtras(file)
def _populatePlatform(self, file):
platform = self.frame.getInstrument().getPlatform()
platform.setMission(file['satellite_name'][()])
platform.setPointingDirection(
self.lookMap[file['look_side'][()].upper()])
platform.setPlanet(Planet(pname="Earth"))
####This is an approximation for spotlight mode
####In spotlight mode, antenna length changes with azimuth position
platform.setAntennaLength(2 * file['azimuth_ground_spacing'][()])
assert (file['range_looks'][()] == 1)
assert (file['azimuth_looks'][()] == 1)
def _populateInstrument(self, file):
instrument = self.frame.getInstrument()
rangePixelSize = file['slant_range_spacing'][()]
instrument.setRadarWavelength(Const.c / file['carrier_frequency'][()])
instrument.setPulseRepetitionFrequency(file['processing_prf'][()])
instrument.setRangePixelSize(rangePixelSize)
instrument.setPulseLength(file['chirp_duration'][()])
instrument.setChirpSlope(file['chirp_bandwidth'][()] /
file['chirp_duration'][()])
instrument.setRangeSamplingRate(file['range_sampling_rate'][()])
incangle = file['local_incidence_angle']
instrument.setIncidenceAngle(incangle[incangle.size // 2])
def _populateFrame(self, file):
rft = file['first_pixel_time'][()]
slantRange = rft * Const.c / 2.0
self.frame.setStartingRange(slantRange)
sensingStart = datetime.datetime.strptime(
file['zerodoppler_start_utc'][()].decode('utf-8'),
'%Y-%m-%dT%H:%M:%S.%f')
sensingStop = datetime.datetime.strptime(
file['zerodoppler_end_utc'][()].decode('utf-8'),
'%Y-%m-%dT%H:%M:%S.%f')
sensingMid = sensingStart + 0.5 * (sensingStop - sensingStart)
self.frame.setPassDirection(file['orbit_direction'][()])
self.frame.setOrbitNumber(file['orbit_absolute_number'][()])
self.frame.setProcessingFacility('ICEYE')
self.frame.setProcessingSoftwareVersion(
str(file['processor_version'][()]))
self.frame.setPolarization(file['polarization'][()])
self.frame.setNumberOfLines(file['number_of_azimuth_samples'][()])
self.frame.setNumberOfSamples(file['number_of_range_samples'][()])
self.frame.setSensingStart(sensingStart)
self.frame.setSensingMid(sensingMid)
self.frame.setSensingStop(sensingStop)
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
farRange = slantRange + (self.frame.getNumberOfSamples() -
1) * rangePixelSize
self.frame.setFarRange(farRange)
def _populateOrbit(self, file):
import numpy as np
orbit = self.frame.getOrbit()
orbit.setReferenceFrame('ECR')
orbit.setOrbitSource('Header')
t = file['state_vector_time_utc'][:]
position = np.zeros((t.size, 3))
position[:, 0] = file['posX'][:]
position[:, 1] = file['posY'][:]
position[:, 2] = file['posZ'][:]
velocity = np.zeros((t.size, 3))
velocity[:, 0] = file['velX'][:]
velocity[:, 1] = file['velY'][:]
velocity[:, 2] = file['velZ'][:]
for ii in range(t.size):
vec = StateVector()
vec.setTime(
datetime.datetime.strptime(t[ii][0].decode('utf-8'),
'%Y-%m-%dT%H:%M:%S.%f'))
vec.setPosition(
[position[ii, 0], position[ii, 1], position[ii, 2]])
vec.setVelocity(
[velocity[ii, 0], velocity[ii, 1], velocity[ii, 2]])
orbit.addStateVector(vec)
def _populateExtras(self, file):
"""
Populate some of the extra fields unique to processing TSX data.
In the future, other sensors may need this information as well,
and a re-organization may be necessary.
"""
import numpy as np
self.dcpoly = np.mean(file['dc_estimate_coeffs'][:], axis=0)
def extractImage(self):
import numpy as np
import h5py
self.parse()
fid = h5py.File(self.hdf5, 'r')
si = fid['s_i']
sq = fid['s_q']
nLines = si.shape[0]
spectralShift = 2 * self.frame.getInstrument().getRangePixelSize(
) / self.frame.getInstrument().getRadarWavelength()
spectralShift -= np.floor(spectralShift)
phsShift = np.exp(-1j * 2 * np.pi * spectralShift *
np.arange(si.shape[1]))
with open(self.output, 'wb') as fout:
for ii in range(nLines):
line = (si[ii, :] + 1j * sq[ii, :])
if self.applySlantRangePhase:
line *= phsShift
line.astype(np.complex64).tofile(fout)
fid.close()
slcImage = isceobj.createSlcImage()
slcImage.setFilename(self.output)
slcImage.setXmin(0)
slcImage.setXmax(self.frame.getNumberOfSamples())
slcImage.setWidth(self.frame.getNumberOfSamples())
slcImage.setAccessMode('r')
self.frame.setImage(slcImage)
def extractDoppler(self):
"""
Return the doppler centroid as defined in the HDF5 file.
"""
import numpy as np
quadratic = {}
rangePixelSize = self.frame.getInstrument().getRangePixelSize()
rt0 = self.frame.getStartingRange() / (2 * Const.c)
rt1 = rt0 + ((self.frame.getNumberOfSamples() - 1) *
rangePixelSize) / (2 * Const.c)
####insarApp style
quadratic['a'] = np.polyval(self.dcpoly, 0.5 *
(rt0 + rt1)) / self.frame.PRF
quadratic['b'] = 0.
quadratic['c'] = 0.
####For roiApp more accurate
####Convert stuff to pixel wise coefficients
x = np.linspace(rt0, rt1, num=len(self.dcpoly) + 1)
pix = np.linspace(0,
self.frame.getNumberOfSamples(),
num=len(self.dcpoly) + 1)
evals = np.polyval(self.dcpoly, x)
fit = np.polyfit(pix, evals, len(self.dcpoly) - 1)
self.frame._dopplerVsPixel = list(fit[::-1])
print('Doppler Fit: ', self.frame._dopplerVsPixel)
return quadratic
