Modified algorithm for ionospheric phase estimation (polar regions)

.circleci/config.yml

@@ -72,7 +72,7 @@ jobs:
               set -ex
               pwd
               . /opt/conda/bin/activate root
-              export ISCE_HOME=/root/project/install/isce
+              ISCE_HOME=/root/project/install/isce
               export PATH="$ISCE_HOME/bin:$ISCE_HOME/applications:/opt/conda/bin:$PATH"
               export PYTHONPATH="/root/project/install:$PYTHONPATH"
               export LD_LIBRARY_PATH="/opt/conda/lib:$LD_LIBRARY_PATH"

SConstruct

@@ -216,43 +216,12 @@ else:
 ### End of GPU branch-specific modifications
 
 
-file = '__init__.py'
+env.Install(inst, '__init__.py')
-if not os.path.exists(file):
+env.Install(inst, 'release_history.py')
-    fout = open(file,"w")
-    fout.write("#!/usr/bin/env python3")
-    fout.close()
-
-env.Install(inst,file)
-try:
-    from subprocess import check_output
-    svn_revision = check_output('svnversion').strip() or 'Unknown'
-    if sys.version_info[0] == 3:
-        svn_revision = svn_revision.decode('utf-8')
-except ImportError:
-    try:
-        import popen2
-        stdout, stdin, stderr = popen2.popen3('svnversion')
-        svn_revision = stdout.read().strip()
-        if stderr.read():
-            raise Exception
-    except Exception:
-        svn_revision = 'Unknown'
-except OSError:
-    svn_revision = 'Unknown'
 
 if not os.path.exists(inst):
     os.makedirs(inst)
 
-fvers = open(os.path.join(inst,'version.py'),'w')
-
-from release_history import release_version, release_svn_revision, release_date
-fvers_lines = ["release_version = '"+release_version+"'\n",
-               "release_svn_revision = '"+release_svn_revision+"'\n",
-               "release_date = '"+release_date+"'\n",
-               "svn_revision = '"+svn_revision+"'\n\n"]
-
-fvers.write(''.join(fvers_lines))
-fvers.close()
 v = 0
 if isrerun == 'no':
     cmd = 'scons -Q install --isrerun=yes'

__init__.py

@@ -25,18 +25,19 @@
 # Author: Giangi Sacco
 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-
+from .release_history import release_version, release_svn_revision, release_date
-
+svn_revision = release_svn_revision
-
+version = release_history # compatibility alias
-from __future__ import print_function
-
-from .version import release_version, release_svn_revision, release_date
-from .version import svn_revision
 
 __version__ = release_version
 
 import sys, os
-isce_path = os.path.split(os.path.abspath(__file__))[0]
+isce_path = os.path.dirname(os.path.abspath(__file__))
+
+import logging
+from logging.config import fileConfig as _fc
+_fc(os.path.join(isce_path, 'defaults', 'logging', 'logging.conf'))
+
 sys.path.insert(1,isce_path)
 sys.path.insert(1,os.path.join(isce_path,'applications'))
 sys.path.insert(1,os.path.join(isce_path,'components'))

applications/CalculatePegPoint.py

@@ -31,12 +31,8 @@
 
 
 
-import os
 import math
-import logging
+from isce import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 from iscesys.Compatibility import Compatibility
 Compatibility.checkPythonVersion()
 from isceobj.Location.Peg import Peg

applications/calculateBaseline.py

@@ -30,11 +30,7 @@
 
 
 
-import os
+from isce import logging
-import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 from iscesys.Compatibility import Compatibility
 Compatibility.checkPythonVersion()
 from iscesys.Component.FactoryInit import FactoryInit

applications/createGeneric.py

@@ -30,11 +30,7 @@
 
 
 
-import os
+from isce import logging
-import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 import isceobj
 from iscesys.Component.FactoryInit import FactoryInit
 

applications/extractHDROrbit.py

@@ -30,12 +30,8 @@
 
 
 
-import os
 import datetime
-import logging
+from isce import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 from iscesys.Compatibility import Compatibility
 Compatibility.checkPythonVersion()
 from iscesys.Component.FactoryInit import FactoryInit

applications/focus.py

@@ -30,12 +30,8 @@
 
 
 
-import os
 import math
-import logging
+from isce import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 import isceobj
 from iscesys.Component.FactoryInit import FactoryInit
 from iscesys.DateTimeUtil.DateTimeUtil import DateTimeUtil as DTU

applications/insarApp.py

@@ -34,8 +34,7 @@ from __future__ import print_function
 import time
 import os
 import sys
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -46,11 +45,6 @@ from iscesys.Component.Configurable import SELF
 import isceobj.InsarProc as InsarProc
 from isceobj.Scene.Frame import FrameMixin
 
-logging.config.fileConfig(
-    os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-        'logging.conf')
-)
-
 logger = logging.getLogger('isce.insar')
 
 

applications/isceApp.py

@@ -41,8 +41,7 @@ import datetime
 import os
 import sys
 import math
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -1438,11 +1437,6 @@ class IsceApp(Application, FrameMixin):
             sys.exit("Could not find the output directory: %s" % self.outputDir)
         os.chdir(self.outputDir) ##change working directory to given output directory
 
-        ##read configfile only here so that log path is in output directory
-        logging.config.fileConfig(
-            os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-                'logging.conf')
-        )
         logger = logging.getLogger('isce.isceProc')
         logger.info(self.intromsg)
         self._isce.dataDirectory = self.outputDir

applications/make_raw.py

@@ -27,16 +27,8 @@
 # Author: Walter Szeliga
 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-
-
-
-import os
-import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
-
 import isce
+from isce import logging
 from iscesys.Compatibility import Compatibility
 from iscesys.Component.Component import Component, Port
 from isceobj.Planet.Ellipsoid import Ellipsoid

applications/rtcApp.py

@@ -30,10 +30,8 @@
 
 
 import time
-import os
 import sys
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -44,11 +42,6 @@ from iscesys.Component.Configurable import SELF
 from isceobj import RtcProc
 from isceobj.Util.decorators import use_api
 
-logging.config.fileConfig(
-    os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-        'logging.conf')
-)
-
 logger = logging.getLogger('isce.grdsar')
 
 

applications/scansarApp.py

@@ -27,13 +27,9 @@
 # Authors: Giangi Sacco, Eric Gurrola
 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-
-
 import time
-import os
 import sys
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -43,11 +39,6 @@ from iscesys.Compatibility import Compatibility
 from iscesys.Component.Configurable import SELF
 from isceobj import ScansarProc
 
-logging.config.fileConfig(
-    os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-        'logging.conf')
-)
-
 logger = logging.getLogger('isce.insar')
 
 

applications/stripmapApp.py

@@ -35,10 +35,8 @@
 
 from __future__ import print_function
 import time
-import os
 import sys
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -50,11 +48,6 @@ import isceobj.StripmapProc as StripmapProc
 from isceobj.Scene.Frame import FrameMixin
 from isceobj.Util.decorators import use_api
 
-logging.config.fileConfig(
-    os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-        'logging.conf')
-)
-
 logger = logging.getLogger('isce.insar')
 
 
@@ -265,7 +258,7 @@ RUBBERSHEET_SNR_THRESHOLD = Application.Parameter('rubberSheetSNRThreshold',
 
 RUBBERSHEET_FILTER_SIZE = Application.Parameter('rubberSheetFilterSize',
                                       public_name='rubber sheet filter size',
-                                      default = 8,
+                                      default = 9,
                                       type = int,
                                       mandatory = False,
                                       doc = '')

applications/topsApp.py

@@ -34,10 +34,8 @@
 
 
 import time
-import os
 import sys
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -47,11 +45,6 @@ from iscesys.Compatibility import Compatibility
 from iscesys.Component.Configurable import SELF
 from isceobj import TopsProc
 
-logging.config.fileConfig(
-    os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-        'logging.conf')
-)
-
 logger = logging.getLogger('isce.insar')
 
 

applications/topsOffsetApp.py

@@ -30,10 +30,8 @@
 
 
 import time
-import os
 import sys
-import logging
+from isce import logging
-import logging.config
 
 import isce
 import isceobj
@@ -42,11 +40,6 @@ from isce.applications.topsApp import TopsInSAR
 from iscesys.Component.Application import Application
 from isceobj.Util.decorators import use_api
 
-logging.config.fileConfig(
-    os.path.join(os.environ['ISCE_HOME'], 'defaults', 'logging',
-        'logging.conf')
-)
-
 logger = logging.getLogger('isce.insar')
 
 WINDOW_SIZE_WIDTH = Application.Parameter(

applications/viewMetadata.py

@@ -27,14 +27,7 @@
 # Author: Walter Szeliga
 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-
+from isce import logging
-
-
-import os
-import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 from iscesys.Compatibility import Compatibility
 Compatibility.checkPythonVersion()
 from iscesys.Component.FactoryInit import FactoryInit

components/isceobj/Location/Offset.py

@@ -29,11 +29,7 @@
 
 
 import math
-import os
+from isce import logging
-import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 
 from isceobj.Util.decorators import type_check, force, pickled, logged
 import numpy as np

components/isceobj/Orbit/Orbit.py

@@ -1061,7 +1061,7 @@ class Orbit(Component):
         ###This wont break the old interface but could cause 
         ###issues at midnight crossing
         if reference is None:
-            reference = self.minTime()
+            reference = self.minTime
 
         refEpoch = reference.replace(hour=0, minute=0, second=0, microsecond=0)
 

components/isceobj/Scene/test/testTrack.py

@@ -27,14 +27,7 @@
 # Author: Walter Szeliga
 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-
+from isce import logging
-
-
-import os
-import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 from isceobj.Sensor.ERS import ERS
 from isceobj.Scene.Track import Track
 logger = logging.getLogger("testTrack")

components/isceobj/StripmapProc/runDenseOffsets.py

@@ -75,11 +75,11 @@ def estimateOffsetField(master, slave, denseOffsetFileName,
 
 def runDenseOffsets(self):
 
-    if self.doDenseOffsets or self.doRubbersheeting:
+    if self.doDenseOffsets or self.doRubbersheetingAzimuth:
         if self.doDenseOffsets:
             print('Dense offsets explicitly requested')
 
-        if self.doRubbersheeting:
+        if self.doRubbersheetingAzimuth:
             print('Generating offsets as rubber sheeting requested')
     else:
         return

components/isceobj/StripmapProc/runDispersive.py

@@ -8,10 +8,13 @@ import isceobj
 from isceobj.Constants import SPEED_OF_LIGHT
 import numpy as np
 import gdal
+<<<<<<< HEAD
 from scipy.ndimage import median_filter
 from astropy.convolution import convolve
 from scipy import ndimage
 import numpy as np
+=======
+>>>>>>> upstream/master
 
 try:
     import cv2
@@ -299,6 +302,8 @@ def fill(data, invalid=None):
     Output:
         Return a filled array.
     """
+    from scipy import ndimage
+
     if invalid is None: invalid = np.isnan(data)
 
     ind = ndimage.distance_transform_edt(invalid,

components/isceobj/StripmapProc/runInterferogram.py

@@ -56,7 +56,7 @@ def compute_FlatEarth(self,ifgFilename,width,length,radarWavelength):
     
     # Open the interferogram
     #ifgFilename= os.path.join(self.insar.ifgDirname, self.insar.ifgFilename)
-    intf = np.memmap(ifgFilename+'.full',dtype=np.complex64,mode='r+',shape=(length,width))
+    intf = np.memmap(ifgFilename,dtype=np.complex64,mode='r+',shape=(length,width))
    
     for ll in range(length):
         intf[ll,:] *= np.exp(cJ*fact*rng2[ll,:])
@@ -155,10 +155,13 @@ def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks,radarW
     else:
         resampAmp += '.amp'
 
+    if not self.doRubbersheetingRange:
         resampInt = resampName
+    else:
+        resampInt = resampName + ".full"
 
     objInt = isceobj.createIntImage()
-    objInt.setFilename(resampInt+'.full')
+    objInt.setFilename(resampInt)
     objInt.setWidth(intWidth)
     imageInt = isceobj.createIntImage()
     IU.copyAttributes(objInt, imageInt)
@@ -166,7 +169,7 @@ def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks,radarW
     objInt.createImage()
 
     objAmp = isceobj.createAmpImage()
-    objAmp.setFilename(resampAmp+'.full')
+    objAmp.setFilename(resampAmp)
     objAmp.setWidth(intWidth)
     imageAmp = isceobj.createAmpImage()
     IU.copyAttributes(objAmp, imageAmp)
@@ -196,8 +199,8 @@ def generateIgram(self,imageSlc1, imageSlc2, resampName, azLooks, rgLooks,radarW
        compute_FlatEarth(self,resampInt,intWidth,lines,radarWavelength)
        
        # Perform Multilook
-       multilook(resampInt+'.full', outname=resampInt, alks=azLooks, rlks=rgLooks)  #takeLooks(objAmp,azLooks,rgLooks)
+       multilook(resampInt, outname=resampName, alks=azLooks, rlks=rgLooks)  #takeLooks(objAmp,azLooks,rgLooks)
-       multilook(resampAmp+'.full', outname=resampAmp, alks=azLooks, rlks=rgLooks)  #takeLooks(objInt,azLooks,rgLooks)
+       multilook(resampAmp, outname=resampAmp.replace(".full",""), alks=azLooks, rlks=rgLooks)  #takeLooks(objInt,azLooks,rgLooks)
        
        #os.system('rm ' + resampInt+'.full* ' + resampAmp + '.full* ')
        # End of modification 

components/isceobj/StripmapProc/runResampleSlc.py

@@ -75,6 +75,7 @@ def runResampleSlc(self, kind='coarse'):
     if kind in ['coarse', 'refined']:
         azname = os.path.join(offsetsDir, self.insar.azimuthOffsetFilename)
         rgname = os.path.join(offsetsDir, self.insar.rangeOffsetFilename)
+        flatten = True
     else:
         azname = os.path.join(offsetsDir, self.insar.azimuthRubbersheetFilename)
         if self.doRubbersheetingRange:

components/isceobj/StripmapProc/runRubbersheet.py

@@ -6,7 +6,6 @@
 import isce
 import isceobj
 from osgeo import gdal
-from scipy import ndimage
 import numpy as np
 import os
 
@@ -24,6 +23,9 @@ def fill(data, invalid=None):
     Output:
         Return a filled array.
     """
+
+    from scipy import ndimage
+
     if invalid is None: invalid = np.isnan(data)
 
     ind = ndimage.distance_transform_edt(invalid,
@@ -35,6 +37,8 @@ def fill(data, invalid=None):
 def mask_filter(denseOffsetFile, snrFile, band, snrThreshold, filterSize, outName):
     #masking and Filtering
 
+    from scipy import ndimage
+
     ##Read in the offset file
     ds = gdal.Open(denseOffsetFile + '.vrt', gdal.GA_ReadOnly)
     Offset = ds.GetRasterBand(1).ReadAsArray()
@@ -140,7 +144,7 @@ def resampleOffset(maskedFiltOffset, geometryOffset, outName):
 
 def runRubbersheet(self):
 
-    if not self.doRubbersheeting:
+    if not self.doRubbersheetingAzimuth:
         print('Rubber sheeting not requested ... skipping')
         return
 
@@ -170,5 +174,3 @@ def runRubbersheet(self):
 
     print("I'm here")
     return None
-
-

components/isceobj/StripmapProc/runRubbersheetAzimuth.py

@@ -9,14 +9,14 @@
 import isce
 import isceobj
 from osgeo import gdal
-from scipy import ndimage
-from astropy.convolution import convolve
 import numpy as np
 import os
 
 def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
     # Masking the offsets with a data-based approach
 
+    from scipy import ndimage
+
     # Open the offsets
     ds = gdal.Open(denseOffsetFile+'.vrt',gdal.GA_ReadOnly)
     off_az = ds.GetRasterBand(1).ReadAsArray()
@@ -79,6 +79,9 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
 
 
 def off_masking(off,filterSize,thre=2):
+
+    from scipy import ndimage
+
     # Define the mask to fill the offsets
     vram = ndimage.median_filter(off.real, filterSize)
     vazm = ndimage.median_filter(off.imag, filterSize)
@@ -101,6 +104,8 @@ def fill(data, invalid=None):
     Output:
         Return a filled array.
     """
+    from scipy import ndimage
+
     if invalid is None: invalid = np.isnan(data)
 
     ind = ndimage.distance_transform_edt(invalid,
@@ -112,6 +117,8 @@ def fill(data, invalid=None):
 def mask_filter(denseOffsetFile, snrFile, band, snrThreshold, filterSize, outName):
     #masking and Filtering
 
+    from scipy import ndimage
+
     ##Read in the offset file
     ds = gdal.Open(denseOffsetFile + '.vrt', gdal.GA_ReadOnly)
     Offset = ds.GetRasterBand(band).ReadAsArray()
@@ -155,6 +162,8 @@ def mask_filter(denseOffsetFile, snrFile, band, snrThreshold, filterSize, outNam
 
 def fill_with_smoothed(off,filterSize):
 
+    from astropy.convolution import convolve
+
     off_2filt=np.copy(off)
     kernel = np.ones((filterSize,filterSize),np.float32)/(filterSize*filterSize)
     loop = 0
@@ -272,5 +281,3 @@ def runRubbersheetAzimuth(self):
     resampleOffset(filtAzOffsetFile, geometryAzimuthOffset, sheetOffset)
 
     return None
-
-

components/isceobj/StripmapProc/runRubbersheetRange.py

@@ -9,15 +9,14 @@
 import isce
 import isceobj
 from osgeo import gdal
-from scipy import ndimage
 import numpy as np
 import os
-from astropy.convolution import convolve
-
 
 def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
     # Masking the offsets with a data-based approach
 
+    from scipy import ndimage
+
     # Open the offsets
     ds = gdal.Open(denseOffsetFile+'.vrt',gdal.GA_ReadOnly)
     off_az = ds.GetRasterBand(1).ReadAsArray()
@@ -78,6 +77,9 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
     return 
 
 def off_masking(off,filterSize,thre=2):
+
+    from scipy import ndimage
+
     vram = ndimage.median_filter(off.real, filterSize)
     vazm = ndimage.median_filter(off.imag, filterSize)
 
@@ -100,6 +102,8 @@ def fill(data, invalid=None):
     Output:
         Return a filled array.
     """
+    from scipy import ndimage
+
     if invalid is None: invalid = np.isnan(data)
 
     ind = ndimage.distance_transform_edt(invalid,
@@ -109,6 +113,8 @@ def fill(data, invalid=None):
 
 def fill_with_smoothed(off,filterSize):
 
+    from astropy.convolution import convolve
+
     off_2filt=np.copy(off)
     kernel = np.ones((filterSize,filterSize),np.float32)/(filterSize*filterSize)
     loop = 0
@@ -131,6 +137,8 @@ def fill_with_smoothed(off,filterSize):
 def mask_filter(denseOffsetFile, snrFile, band, snrThreshold, filterSize, outName):
     #masking and Filtering
 
+    from scipy import ndimage
+
     ##Read in the offset file
     ds = gdal.Open(denseOffsetFile + '.vrt', gdal.GA_ReadOnly)
     Offset = ds.GetRasterBand(band).ReadAsArray()
@@ -236,6 +244,8 @@ def resampleOffset(maskedFiltOffset, geometryOffset, outName):
 
 def runRubbersheetRange(self):
 
+    from scipy import ndimage
+
     if not self.doRubbersheetingRange:
         print('Rubber sheeting in azimuth not requested ... skipping')
         return

components/isceobj/TopsProc/runIon.py

@@ -9,9 +9,6 @@ import shutil
 import datetime
 import numpy as np
 import numpy.matlib
-import scipy.signal as ss
-from scipy import interpolate
-from scipy.interpolate import interp1d
 
 import isceobj
 import logging
@@ -638,6 +635,7 @@ def cal_coherence(inf, win=5, edge=0):
 
           4: keep all samples
     '''
+    import scipy.signal as ss
 
     if win % 2 != 1:
         raise Exception('window size must be odd!')
@@ -1682,6 +1680,9 @@ def computeDopplerOffset(burst, firstline, lastline, firstcolumn, lastcolumn, nr
 
     output: first lines > 0, last lines < 0
     '''
+    from scipy import interpolate
+    from scipy.interpolate import interp1d
+
     Vs = np.linalg.norm(burst.orbit.interpolateOrbit(burst.sensingMid, method='hermite').getVelocity())
     Ks =   2 * Vs * burst.azimuthSteeringRate / burst.radarWavelength 
 
@@ -1830,6 +1831,7 @@ def adaptive_gaussian(ionos, wgt, size_max, size_min):
     size_max: maximum window size
     size_min: minimum window size
     '''
+    import scipy.signal as ss
 
     length = (ionos.shape)[0]
     width = (ionos.shape)[1]
@@ -1892,6 +1894,8 @@ def filt_gaussian(self, ionParam):
     currently not implemented.
     a less accurate method is to use ionsphere without any projection
     '''
+    from scipy import interpolate
+    from scipy.interpolate import interp1d
 
     #################################################
     #SET PARAMETERS HERE
@@ -2659,5 +2663,3 @@ def runIon(self):
     #esd_noion(self, ionParam)
 
     return
-
-    

components/isceobj/TopsProc/runOffsetFilter.py

@@ -3,7 +3,6 @@
 # Copyright 2016
 #
 
-from scipy.ndimage.filters import median_filter
 import numpy as np
 import isce
 import isceobj
@@ -20,6 +19,8 @@ def runOffsetFilter(self):
     if not self.doDenseOffsets:
         return
 
+    from scipy.ndimage.filters import median_filter
+
     offsetfile = os.path.join(self._insar.mergedDirname, self._insar.offsetfile) 
     snrfile = os.path.join(self._insar.mergedDirname, self._insar.snrfile)
     print('\n======================================')

components/isceobj/TopsProc/runPrepESD.py

@@ -8,7 +8,6 @@ import numpy as np
 import os
 import isceobj
 import logging
-import scipy.signal as SS
 from isceobj.Util.ImageUtil import ImageLib as IML
 import datetime
 import pprint
@@ -177,6 +176,7 @@ def createCoherence(intfile, win=5):
     '''
     Compute coherence using scipy convolve 2D.
     '''
+    import scipy.signal as SS
 
     corfile = os.path.splitext(intfile)[0] + '.cor'
     filt = np.ones((win,win))/ (1.0*win*win)

components/isceobj/Unwrap/snaphu.py

@@ -54,7 +54,7 @@ class snaphu(Component):
         self.azimuthLooks = obj.insar.topo.numberAzimuthLooks
 
         azres = obj.insar.masterFrame.platform.antennaLength/2.0
-        azfact = obj.insar.topo.numberAzimuthLooks *azres / obj.insar.topo.azimuthSpacing
+        azfact = azres / obj.insar.topo.azimuthSpacing
 
         rBW = obj.insar.masterFrame.instrument.pulseLength * obj.insar.masterFrame.instrument.chirpSlope
         rgres = abs(SPEED_OF_LIGHT / (2.0 * rBW))

components/isceobj/Unwrap/snaphu_mcf.py

@@ -54,7 +54,7 @@ class snaphu_mcf(Component):
         self.azimuthLooks = obj.insar.topo.numberAzimuthLooks
 
         azres = obj.insar.masterFrame.platform.antennaLength/2.0
-        azfact = obj.insar.topo.numberAzimuthLooks *azres / obj.insar.topo.azimuthSpacing
+        azfact = azres / obj.insar.topo.azimuthSpacing
 
         rBW = obj.insar.masterFrame.instrument.pulseLength * obj.insar.masterFrame.instrument.chirpSlope
         rgres = abs(SPEED_OF_LIGHT / (2.0 * rBW))

components/isceobj/Util/geo/__init__.py

@@ -45,10 +45,6 @@ ellipsoid        oblate ellipsoid of revolution (e.g, WGS84) with all the
   See mainpage.txt for a complete dump of geo's philosophy-- otherwise,
   use the docstrings.
 """
-import os
-isce_path  = os.getenv("ISCE_HOME")
 
 ## \namespace geo  Vector- and Affine-spaces, on Earth
 __all__ = ['euclid', 'coordinates', 'ellipsoid', 'charts', 'affine', 'motion']
-
-

components/iscesys/Component/Configurable.py

@@ -32,10 +32,7 @@ from __future__ import print_function
 import os
 import sys
 import operator
-import logging
+from isce import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 from iscesys.DictUtils.DictUtils import DictUtils as DU
 from iscesys.Compatibility import Compatibility
 Compatibility.checkPythonVersion()

components/iscesys/DataRetriever/DataRetriever.py

@@ -37,8 +37,7 @@ import isce
 import zipfile
 import os
 import sys
-import logging
+from isce import logging
-import logging.config
 from iscesys.Component.Component import Component
 import shutil
 from urllib import request
@@ -325,8 +324,4 @@ class DataRetriever(Component):
         # logger not defined until baseclass is called
 
         if not self.logger:
-            logging.config.fileConfig(
-                os.path.join(os.environ['ISCE_HOME'], 'defaults',
-                'logging', 'logging.conf')
-            )
             self.logger = logging.getLogger('isce.iscesys.DataRetriever')

components/stdproc/alosreformat/ALOS_lib/src/cfft1d_fftpack.c

@@ -1,7 +1,6 @@
 #include <stdio.h>
 #include <stdlib.h>
 #include <complex.h>
-#include <malloc.h>
 /************************************************************************
 * cfft1d is a subroutine used to call and initialize perflib Fortran FFT *
 * routines.                                                             *

components/stdproc/orbit/orbitLib/CalcSchHeightVel.py

@@ -29,10 +29,8 @@
 
 
 
-import os
 import logging
 import math
-import logging.config
 
 from iscesys.Compatibility import Compatibility
 
@@ -40,9 +38,6 @@ from isceobj.Planet import Planet
 from isceobj import Constants as CN
 from iscesys.Component.Component import Component, Port
 
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
-
 RANGE_SAMPLING_RATE = Component.Parameter('rangeSamplingRate',
                                           public_name='range sampling rate',
                                           type=float,

components/zerodop/GPUampcor/cuda/SConscript

@@ -49,7 +49,7 @@ if envGPUampcor['GPU_ACC_ENABLED']:
         build_base += "-ccbin " + envGPUampcor['NVCC_CCBIN'] + " "
     else:
         print('Assuming default system compiler for nvcc.')
-    build_base += "-arch=sm_35 -shared -Xcompiler -fPIC -O3 "
+    build_base += "-shared -Xcompiler -fPIC -O3 "
     build_cmd = build_base + "-dc -m64 -o $TARGET -c $SOURCE"
     built_path = os.path.join(build, 'gpu-ampcor.o')
     linked_path = os.path.join(build, 'gpu-ampcor-linked.o')

components/zerodop/GPUtopozero/cuda/compilation

@@ -1,2 +1,2 @@
-nvcc -arch=sm_35 -Xcompiler -fPIC -o gpu-topo.o -c Topo.cu
+nvcc -Xcompiler -fPIC -o gpu-topo.o -c Topo.cu
 cp -f gpu-topo.o ..

contrib/PyCuAmpcor/SConscript

@@ -1,4 +1,4 @@
-#!/usr/bin/env python
+#!/usr/bin/env python3
 
 import os
 
@@ -28,7 +28,7 @@ if envPyCuAmpcor['GPU_ACC_ENABLED']:
 
     if not os.path.exists(initFile):
         with open(initFile, 'w') as fout:
-            fout.write("#!/usr/bin/env python")
+            fout.write("#!/usr/bin/env python3")
 
     listFiles = [initFile]
     envPyCuAmpcor.Install(install, listFiles)

contrib/PyCuAmpcor/examples/GeoTiffSample.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python3
+#
+# Test program to run ampcor with GPU
+# For two GeoTiff images
+#
+
+import argparse
+import numpy as np
+from PyCuAmpcor import PyCuAmpcor
+
+
+def main():
+    '''
+    main program
+    '''
+
+    objOffset = PyCuAmpcor() # create the processor
+
+    objOffset.algorithm = 0 # cross-correlation method 0=freq 1=time
+    objOffset.deviceID = 0  # GPU device id to be used
+    objOffset.nStreams = 2  # cudaStreams; multiple streams to overlap data transfer with gpu calculations
+    objOffset.masterImageName = "master.tif"
+    objOffset.masterImageHeight = 16480 # RasterYSize
+    objOffset.masterImageWidth = 17000 # RasterXSize
+    objOffset.slaveImageName = "slave.tif"
+    objOffset.slaveImageHeight = 16480
+    objOffset.slaveImageWidth = 17000
+    objOffset.windowSizeWidth = 64 # template window size
+    objOffset.windowSizeHeight = 64
+    objOffset.halfSearchRangeDown = 20 # search range
+    objOffset.halfSearchRangeAcross = 20
+    objOffset.derampMethod = 1 # deramping for complex signal, set to 1 for real images
+
+    objOffset.skipSampleDown = 128 # strides between windows
+    objOffset.skipSampleAcross = 64
+    # gpu processes several windows in one batch/Chunk
+    # total windows in Chunk = numberWindowDownInChunk*numberWindowAcrossInChunk
+    # the max number of windows depending on gpu memory and type
+    objOffset.numberWindowDownInChunk = 1
+    objOffset.numberWindowAcrossInChunk = 10
+    objOffset.corrSurfaceOverSamplingFactor = 8 # oversampling factor for correlation surface
+    objOffset.corrSurfaceZoomInWindow = 16  # area in correlation surface to be oversampled
+    objOffset.corrSufaceOverSamplingMethod = 1 # fft or sinc oversampler
+    objOffset.useMmap = 1 # default using memory map as buffer, if having troubles, set to 0
+    objOffset.mmapSize = 1 # mmap or buffer size used for transferring data from file to gpu, in GB
+
+    objOffset.numberWindowDown = 40 # number of windows to be processed
+    objOffset.numberWindowAcross = 100
+    # if to process the whole image; some math needs to be done
+    # margin = 0 # margins to be neglected
+    #objOffset.numberWindowDown = (objOffset.slaveImageHeight - 2*margin - 2*objOffset.halfSearchRangeDown - objOffset.windowSizeHeight) // objOffset.skipSampleDown
+    #objOffset.numberWindowAcross = (objOffset.slaveImageWidth - 2*margin - 2*objOffset.halfSearchRangeAcross - objOffset.windowSizeWidth) // objOffset.skipSampleAcross
+
+    objOffset.setupParams()
+    objOffset.masterStartPixelDownStatic = objOffset.halfSearchRangeDown # starting pixel offset
+    objOffset.masterStartPixelAcrossStatic = objOffset.halfSearchRangeDown
+    objOffset.setConstantGrossOffset(0, 0) # gross offset between master and slave images
+    objOffset.checkPixelInImageRange() # check whether there is something wrong with
+    objOffset.runAmpcor()
+
+
+if __name__ == '__main__':
+

contrib/PyCuAmpcor/examples/glacierSample.py

@@ -7,8 +7,8 @@
 
 import argparse
 import numpy as np
-#from PyCuAmpcor import PyCuAmpcor
+from PyCuAmpcor import PyCuAmpcor
-from isce.components.contrib.PyCuAmpcor import PyCuAmpcor
+
 
 def main():
     '''
@@ -20,10 +20,10 @@ def main():
     objOffset.algorithm = 0
     objOffset.deviceID = 0  # -1:let system find the best GPU
     objOffset.nStreams = 2  #cudaStreams
-    objOffset.masterImageName = "master.slc"
+    objOffset.masterImageName = "20131213.slc.vrt"
     objOffset.masterImageHeight = 43008
     objOffset.masterImageWidth = 24320
-    objOffset.slaveImageName = "slave.slc"
+    objOffset.slaveImageName = "20131221.slc.vrt"
     objOffset.slaveImageHeight = 43008
     objOffset.slaveImageWidth = 24320
     objOffset.windowSizeWidth = 64
@@ -40,6 +40,7 @@ def main():
     objOffset.corrSurfaceOverSamplingFactor = 8
     objOffset.corrSurfaceZoomInWindow = 16
     objOffset.corrSufaceOverSamplingMethod = 1
+    objOffset.useMmap = 1
     objOffset.mmapSize = 8
 
     objOffset.setupParams()

contrib/PyCuAmpcor/examples/varyGrossOffsetSample.py

@@ -11,10 +11,10 @@ def main():
     objOffset = PyCuAmpcor()
 
     #step 1 set constant parameters
-    objOffset.masterImageName = "master.slc"
+    objOffset.masterImageName = "master.slc.vrt"
     objOffset.masterImageHeight = 128
     objOffset.masterImageWidth = 128
-    objOffset.slaveImageName = "slave.slc"
+    objOffset.slaveImageName = "slave.slc.vrt"
     objOffset.masterImageHeight = 128
     objOffset.masterImageWidth = 128
     objOffset.skipSampleDown = 2

contrib/PyCuAmpcor/src/GDALImage.cu

@@ -0,0 +1,154 @@
+#include "GDALImage.h"
+#include <iostream>
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <unistd.h>
+#include <fcntl.h>
+#include <assert.h>
+#include <cublas_v2.h>
+#include "cudaError.h"
+#include <errno.h>
+#include <unistd.h>
+
+
+/**
+ * \brief Constructor
+ *
+ * @param filename a std::string with the raster image file name
+ */
+
+GDALImage::GDALImage(std::string filename, int band, int cacheSizeInGB, int useMmap)
+   : _useMmap(useMmap)
+{
+    // open the file as dataset
+    _poDataset = (GDALDataset *) GDALOpen(filename.c_str(), GA_ReadOnly );
+    // if something is wrong, throw an exception
+    // GDAL reports the error message
+    if(!_poDataset)
+        throw;
+
+    // check the band info
+    int count = _poDataset->GetRasterCount();
+    if(band > count)
+    {
+        std::cout << "The desired band " << band << " is greated than " << count << " bands available";
+        throw;
+    }
+
+    // get the desired band
+    _poBand = _poDataset->GetRasterBand(band);
+    if(!_poBand)
+        throw;
+
+     // get the width(x), and height(y)
+    _width = _poBand->GetXSize();
+    _height = _poBand->GetYSize();
+
+    _dataType = _poBand->GetRasterDataType();
+    // determine the image type
+    _isComplex = GDALDataTypeIsComplex(_dataType);
+    // determine the pixel size in bytes
+    _pixelSize = GDALGetDataTypeSize(_dataType);
+
+    _bufferSize = 1024*1024*cacheSizeInGB;
+
+    // checking whether using memory map
+    if(_useMmap) {
+
+       char **papszOptions = NULL;
+        // if cacheSizeInGB = 0, use default
+        // else set the option
+        if(cacheSizeInGB > 0)
+            papszOptions = CSLSetNameValue( papszOptions,
+                "CACHE_SIZE",
+		        std::to_string(_bufferSize).c_str());
+
+        // space between two lines
+	    GIntBig pnLineSpace;
+        // set up the virtual mem buffer
+        _poBandVirtualMem =  GDALGetVirtualMemAuto(
+            static_cast<GDALRasterBandH>(_poBand),
+		    GF_Read,
+		    &_pixelSize,
+		    &pnLineSpace,
+		    papszOptions);
+
+        // check it
+        if(!_poBandVirtualMem)
+            throw;
+
+        // get the starting pointer
+        _memPtr = CPLVirtualMemGetAddr(_poBandVirtualMem);
+    }
+    else { // use a buffer
+        checkCudaErrors(cudaMallocHost((void **)&_memPtr, _bufferSize));
+    }
+
+    // make sure memPtr is not Null
+    if (!_memPtr)
+        throw;
+
+    // all done
+}
+
+
+/// load a tile of data h_tile x w_tile from CPU (mmap) to GPU
+/// @param dArray pointer for array in device memory
+/// @param h_offset Down/Height offset
+/// @param w_offset Across/Width offset
+/// @param h_tile Down/Height tile size
+/// @param w_tile Across/Width tile size
+/// @param stream CUDA stream for copying
+void GDALImage::loadToDevice(void *dArray, size_t h_offset, size_t w_offset, size_t h_tile, size_t w_tile, cudaStream_t stream)
+{
+    size_t tileStartOffset = (h_offset*_width + w_offset)*_pixelSize;
+
+    char * startPtr = (char *)_memPtr ;
+    startPtr += tileStartOffset;
+
+    // @note
+    // We assume down/across directions as rows/cols. Therefore, SLC mmap and device array are both row major.
+    // cuBlas assumes both source and target arrays are column major.
+    // To use cublasSetMatrix, we need to switch w_tile/h_tile for rows/cols
+    // checkCudaErrors(cublasSetMatrixAsync(w_tile, h_tile, sizeof(float2), startPtr, width, dArray, w_tile, stream));
+    if (_useMmap)
+        checkCudaErrors(cudaMemcpy2DAsync(dArray, w_tile*_pixelSize, startPtr, _width*_pixelSize,
+                                      w_tile*_pixelSize, h_tile, cudaMemcpyHostToDevice,stream));
+    else {
+        // get the total tile size in bytes
+        size_t tileSize = h_tile*w_tile*_pixelSize;
+        // if the size is bigger than existing buffer, reallocate
+        if (tileSize > _bufferSize) {
+            // maybe we need to make it to fit the pagesize
+            _bufferSize = tileSize;
+            checkCudaErrors(cudaFree(_memPtr));
+            checkCudaErrors(cudaMallocHost((void **)&_memPtr, _bufferSize));
+        }
+        // copy from file to buffer
+        CPLErr err = _poBand->RasterIO(GF_Read, //eRWFlag
+            w_offset, h_offset,  //nXOff, nYOff
+            w_tile, h_tile,  // nXSize, nYSize
+            _memPtr, // pData
+            w_tile*h_tile, 1, // nBufXSize, nBufYSize
+            _dataType, //eBufType
+            0, 0, //nPixelSpace, nLineSpace in pData
+            NULL //psExtraArg extra resampling callback
+            );
+
+        if(err != CE_None)
+            throw;
+        // copy from buffer to gpu
+        checkCudaErrors(cudaMemcpyAsync(dArray, _memPtr, tileSize, cudaMemcpyHostToDevice, stream));
+    }
+}
+
+GDALImage::~GDALImage()
+{
+    // free the virtual memory
+    CPLVirtualMemFree(_poBandVirtualMem),
+    // free the GDAL Dataset, close the file
+    delete _poDataset;
+}
+
+// end of file

contrib/PyCuAmpcor/src/GDALImage.h

@@ -0,0 +1,79 @@
+// -*- c++ -*-
+/**
+ * \brief Class for an image described GDAL vrt
+ *
+ * only complex (pixelOffset=8) or real(pixelOffset=4) images are supported, such as SLC and single-precision TIFF
+ */
+
+#ifndef __GDALIMAGE_H
+#define __GDALIMAGE_H
+
+#include <cublas_v2.h>
+#include <string>
+#include <gdal/gdal_priv.h>
+#include <gdal/cpl_conv.h>
+
+class GDALImage{
+
+public:
+    using size_t = std::size_t;
+
+private:
+    size_t _fileSize;
+    int _height;
+    int _width;
+
+    // buffer pointer
+    void * _memPtr = NULL;
+
+    int _pixelSize; //in bytes
+
+    int _isComplex;
+
+    size_t _bufferSize;
+    int _useMmap;
+
+    GDALDataType _dataType;
+    CPLVirtualMem * _poBandVirtualMem = NULL;
+    GDALDataset * _poDataset = NULL;
+    GDALRasterBand * _poBand = NULL;
+
+public:
+    GDALImage() = delete;
+    GDALImage(std::string fn, int band=1, int cacheSizeInGB=0, int useMmap=1);
+
+    void * getmemPtr()
+    {
+        return(_memPtr);
+    }
+
+    size_t getFileSize()
+    {
+        return (_fileSize);
+    }
+
+    size_t getHeight() {
+        return (_height);
+    }
+
+    size_t getWidth()
+    {
+        return (_width);
+    }
+
+    int getPixelSize()
+    {
+        return _pixelSize;
+    }
+
+    bool isComplex()
+    {
+        return _isComplex;
+    }
+
+    void loadToDevice(void *dArray, size_t h_offset, size_t w_offset, size_t h_tile, size_t w_tile, cudaStream_t stream);
+    ~GDALImage();
+
+};
+
+#endif //__GDALIMAGE_H

contrib/PyCuAmpcor/src/Makefile

@@ -4,22 +4,23 @@ LDFLAGS =  -lcuda -lcudart -lcufft -lcublas
 CXXFLAGS = -std=c++11 -fpermissive -fPIC -shared
 NVCCFLAGS = -ccbin g++ -m64 \
     -gencode arch=compute_35,code=sm_35 \
+	-gencode arch=compute_60,code=sm_60 \
     -Xcompiler -fPIC -shared -Wno-deprecated-gpu-targets \
     -ftz=false -prec-div=true -prec-sqrt=true
 
 CXX=g++
 NVCC=nvcc
 
-DEPS = cudaUtil.h cudaError.h cuArrays.h SlcImage.h cuAmpcorParameter.h
+DEPS = cudaUtil.h cudaError.h cuArrays.h GDALImage.h cuAmpcorParameter.h
-OBJS =  SlcImage.o cuArrays.o cuArraysCopy.o cuArraysPadding.o cuOverSampler.o \
+OBJS =  GDALImage.o cuArrays.o cuArraysCopy.o cuArraysPadding.o cuOverSampler.o \
 	    cuSincOverSampler.o cuDeramp.o cuOffset.o \
         cuCorrNormalization.o cuAmpcorParameter.o cuCorrTimeDomain.o cuCorrFrequency.o \
         cuAmpcorChunk.o cuAmpcorController.o cuEstimateStats.o
 
-all: cuampcor 
+all: pyampcor
 
-SlcImage.o: SlcImage.cu $(DEPS)
+GDALImage.o: GDALImage.cu $(DEPS)
-	$(NVCC) $(NVCCFLAGS) -c -o $@ SlcImage.cu
+	$(NVCC) $(NVCCFLAGS) -c -o $@ GDALImage.cu
 
 cuArrays.o: cuArrays.cu $(DEPS)
 	$(NVCC) $(NVCCFLAGS) -c -o $@ cuArrays.cu
@@ -64,7 +65,7 @@ cuEstimateStats.o: cuEstimateStats.cu
 	$(NVCC) $(NVCCFLAGS) -c -o $@ cuEstimateStats.cu
 
 
-cuampcor: $(OBJS)
+pyampcor: $(OBJS)
 	rm -f PyCuAmpcor.cpp && python3 setup.py build_ext --inplace
 
 clean:

contrib/PyCuAmpcor/src/PyCuAmpcor.pyx

@@ -62,7 +62,8 @@ cdef extern from "cuAmpcorParameter.h":
         int slaveImageHeight            	## slave image height
         int slaveImageWidth            		## slave image width
 
-        int mmapSizeInGB                    ## mmap buffer size in unit of Gigabytes
+        int useMmap                         ## whether to use mmap
+        int mmapSizeInGB                    ## mmap buffer size in unit of Gigabytes (if not mmmap, the buffer size)
 
         ## total number of chips/windows
         int numberWindowDown            	## number of total windows (down)
@@ -103,6 +104,7 @@ cdef extern from "cuAmpcorParameter.h":
         string grossOffsetImageName
         string offsetImageName     ## Output Offset fields filename
         string snrImageName        ## Output SNR filename
+        string covImageName        ## Output COV filename
         void setStartPixels(int*, int*, int*, int*)
         void setStartPixels(int, int, int*, int*)
         void setStartPixels(int, int, int, int)
@@ -143,6 +145,12 @@ cdef class PyCuAmpcor(object):
     def nStreams(self, int a):
         self.c_cuAmpcor.param.nStreams = a
     @property
+    def useMmap(self):
+        return self.c_cuAmpcor.param.useMmap
+    @useMmap.setter
+    def useMmap(self, int a):
+        self.c_cuAmpcor.param.useMmap = a
+    @property
     def mmapSize(self):
         return self.c_cuAmpcor.param.mmapSizeInGB
     @mmapSize.setter
@@ -324,6 +332,7 @@ cdef class PyCuAmpcor(object):
     @offsetImageName.setter
     def offsetImageName(self, str a):
         self.c_cuAmpcor.param.offsetImageName = <string> a.encode()
+
     @property
     def snrImageName(self):
         return self.c_cuAmpcor.param.snrImageName
@@ -331,6 +340,13 @@ cdef class PyCuAmpcor(object):
     def snrImageName(self, str a):
         self.c_cuAmpcor.param.snrImageName = <string> a.encode()
 
+    @property
+    def covImageName(self):
+        return self.c_cuAmpcor.param.covImageName
+    @covImageName.setter
+    def covImageName(self, str a):
+        self.c_cuAmpcor.param.covImageName = <string> a.encode()
+
     @property
     def masterStartPixelDownStatic(self):
         return self.c_cuAmpcor.param.masterStartPixelDown0

contrib/PyCuAmpcor/src/SConscript

@@ -6,7 +6,7 @@ package = envPyCuAmpcor['PACKAGE']
 project = envPyCuAmpcor['PROJECT']
 build = envPyCuAmpcor['PRJ_LIB_DIR']
 install = envPyCuAmpcor['PRJ_SCONS_INSTALL'] + '/' + package + '/' + project
-listFiles = ['SlcImage.cu', 'cuArrays.cu', 'cuArraysCopy.cu',
+listFiles = ['GDALImage.cu', 'cuArrays.cu', 'cuArraysCopy.cu',
              'cuArraysPadding.cu', 'cuOverSampler.cu',
              'cuSincOverSampler.cu', 'cuDeramp.cu',
              'cuOffset.cu', 'cuCorrNormalization.cu',

contrib/PyCuAmpcor/src/cuAmpcorChunk.cu

@@ -33,22 +33,38 @@ void cuAmpcorChunk::run(int idxDown_, int idxAcross_)
         cuCorrTimeDomain(r_masterBatchRaw, r_slaveBatchRaw, r_corrBatchRaw, stream); //time domain cross correlation
     }
     cuCorrNormalize(r_masterBatchRaw, r_slaveBatchRaw, r_corrBatchRaw, stream);
+
+
     // find the maximum location of none-oversampled correlation
-    cuArraysMaxloc2D(r_corrBatchRaw, offsetInit, stream);
+    // 41 x 41, if halfsearchrange=20
+    //cuArraysMaxloc2D(r_corrBatchRaw, offsetInit, stream);
+    cuArraysMaxloc2D(r_corrBatchRaw, offsetInit, r_maxval, stream);
 
-// Estimate SNR (Minyan Zhong)
+    offsetInit->outputToFile("offsetInit1", stream);
 
-    //std::cout<< "flag stats 1" <<std::endl; 
+    // Estimation of statistics
-    //cuArraysCopyExtractCorr(r_corrBatchRaw, r_corrBatchZoomIn, i_corrBatchZoomInValid, offsetInit, stream);
+    // Author: Minyan Zhong
+    // Extraction of correlation surface around the peak
+    cuArraysCopyExtractCorr(r_corrBatchRaw, r_corrBatchRawZoomIn, i_corrBatchZoomInValid, offsetInit, stream);
 
-    //std::cout<< "flag stats 2" <<std::endl;
+    cudaDeviceSynchronize();
-    //cuArraysSumCorr(r_corrBatchZoomIn, i_corrBatchZoomInValid, r_corrBatchSum, i_corrBatchValidCount, stream);
 
-    //std::cout<< "flag stats 3" <<std::endl;
+    // debug: output the intermediate results
-    //cuEstimateSnr(r_corrBatchSum, i_corrBatchValidCount, r_maxval, r_snrValue, stream);
+    r_maxval->outputToFile("r_maxval",stream);
+    r_corrBatchRaw->outputToFile("r_corrBatchRaw",stream);
+    r_corrBatchRawZoomIn->outputToFile("r_corrBatchRawZoomIn",stream);
+    i_corrBatchZoomInValid->outputToFile("i_corrBatchZoomInValid",stream);
 
-//
+    // Summation of correlation and data point values
+    cuArraysSumCorr(r_corrBatchRawZoomIn, i_corrBatchZoomInValid, r_corrBatchSum, i_corrBatchValidCount, stream);
 
+    // SNR
+    cuEstimateSnr(r_corrBatchSum, i_corrBatchValidCount, r_maxval, r_snrValue, stream);
+
+    // Variance
+    // cuEstimateVariance(r_corrBatchRaw, offsetInit, r_maxval, r_covValue, stream);
+
+    // Using the approximate estimation to adjust slave image (half search window size becomes only 4 pixels)
     //offsetInit->debuginfo(stream);
     // determine the starting pixel to extract slave images around the max location
     cuDetermineSlaveExtractOffset(offsetInit,
@@ -109,12 +125,21 @@ void cuAmpcorChunk::run(int idxDown_, int idxAcross_)
     //offsetZoomIn->debuginfo(stream);
     //offsetFinal->debuginfo(stream);
 
+    // Do insertion.
+    // Offsetfields.
     cuArraysCopyInsert(offsetFinal, offsetImage, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);
 
-    // Minyan Zhong
+    // Debugging matrix.
-    //cuArraysCopyInsert(corrMaxValue, snrImage, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);    
+    cuArraysCopyInsert(r_corrBatchSum, floatImage1, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);
-    //cuArraysCopyInsert(r_snrValue, snrImage, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);    
+    cuArraysCopyInsert(i_corrBatchValidCount, intImage1, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);
 
+    // Old: save max correlation coefficients.
+    //cuArraysCopyInsert(corrMaxValue, snrImage, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);
+    // New: save SNR
+    cuArraysCopyInsert(r_snrValue, snrImage, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);
+
+    // Variance.
+    cuArraysCopyInsert(r_covValue, covImage, idxDown_*param->numberWindowDownInChunk, idxAcross_*param->numberWindowAcrossInChunk,stream);
 }
 
 void cuAmpcorChunk::setIndex(int idxDown_, int idxAcross_)
@@ -162,19 +187,37 @@ void cuAmpcorChunk::getRelativeOffset(int *rStartPixel, const int *oStartPixel,
 
 void cuAmpcorChunk::loadMasterChunk()
 {
-    //load a chunk from mmap to gpu
+
-    int startD = param->masterChunkStartPixelDown[idxChunk];
+    // we first load the whole chunk of image from cpu to a gpu buffer c(r)_masterChunkRaw
-    int startA = param->masterChunkStartPixelAcross[idxChunk];
+    // then copy to a batch of windows with (nImages, height, width) (leading dimension on the right)
-    int height =  param->masterChunkHeight[idxChunk];
+
-    int width = param->masterChunkWidth[idxChunk];
+    // get the chunk size to be loaded to gpu
-    masterImage->loadToDevice(c_masterChunkRaw->devData, startD, startA, height, width, stream);
+    int startD = param->masterChunkStartPixelDown[idxChunk]; //start pixel down (along height)
-    std::cout << "debug load master: " << startD << " " <<  startA << " " <<  height << " "  << width << "\n";
+    int startA = param->masterChunkStartPixelAcross[idxChunk]; // start pixel across (along width)
-    //copy the chunk to a batch of images format (nImages, height, width) 
+    int height =  param->masterChunkHeight[idxChunk]; // number of pixels along height
-    //use cpu for some simple math  
+    int width = param->masterChunkWidth[idxChunk];  // number of pixels along width
+
+    //use cpu to compute the starting positions for each window
     getRelativeOffset(ChunkOffsetDown->hostData, param->masterStartPixelDown, param->masterChunkStartPixelDown[idxChunk]);
+    // copy the positions to gpu
     ChunkOffsetDown->copyToDevice(stream);
+    // same for the across direction
     getRelativeOffset(ChunkOffsetAcross->hostData, param->masterStartPixelAcross, param->masterChunkStartPixelAcross[idxChunk]);
     ChunkOffsetAcross->copyToDevice(stream);
+
+    // check whether the image is complex (e.g., SLC) or real( e.g. TIFF)
+    if(masterImage->isComplex())
+    {
+        // allocate a gpu buffer to load data from cpu/file
+        // try allocate/deallocate the buffer on the fly to save gpu memory 07/09/19
+        c_masterChunkRaw = new cuArrays<float2> (param->maxMasterChunkHeight, param->maxMasterChunkWidth);
+        c_masterChunkRaw->allocate();
+
+        // load the data from cpu
+        masterImage->loadToDevice((void *)c_masterChunkRaw->devData, startD, startA, height, width, stream);
+        //std::cout << "debug load master: " << startD << " " <<  startA << " " <<  height << " "  << width << "\n";
+
+        //copy the chunk to a batch format (nImages, height, width)
         // if derampMethod = 0 (no deramp), take amplitudes; otherwise, copy complex data
         if(param->derampMethod == 0) {
             cuArraysCopyToBatchAbsWithOffset(c_masterChunkRaw, param->masterChunkWidth[idxChunk],
@@ -184,10 +227,41 @@ void cuAmpcorChunk::loadMasterChunk()
             cuArraysCopyToBatchWithOffset(c_masterChunkRaw, param->masterChunkWidth[idxChunk],
                 c_masterBatchRaw, ChunkOffsetDown->devData, ChunkOffsetAcross->devData, stream);
         }
+        // deallocate the gpu buffer
+        delete c_masterChunkRaw;
+    }
+    // if the image is real
+    else {
+        r_masterChunkRaw = new cuArrays<float> (param->maxMasterChunkHeight, param->maxMasterChunkWidth);
+        r_masterChunkRaw->allocate();
+
+        // load the data from cpu
+        masterImage->loadToDevice((void *)r_masterChunkRaw->devData, startD, startA, height, width, stream);
+
+        // copy the chunk (real) to a batch format (complex)
+        cuArraysCopyToBatchWithOffsetR2C(r_masterChunkRaw, param->masterChunkWidth[idxChunk],
+                c_masterBatchRaw, ChunkOffsetDown->devData, ChunkOffsetAcross->devData, stream);
+        // deallocate the gpu buffer
+        delete r_masterChunkRaw;
+    }
+
+
 }
 
 void cuAmpcorChunk::loadSlaveChunk()
 {
+
+    //copy to a batch format (nImages, height, width)
+    getRelativeOffset(ChunkOffsetDown->hostData, param->slaveStartPixelDown, param->slaveChunkStartPixelDown[idxChunk]);
+    ChunkOffsetDown->copyToDevice(stream);
+    getRelativeOffset(ChunkOffsetAcross->hostData, param->slaveStartPixelAcross, param->slaveChunkStartPixelAcross[idxChunk]);
+    ChunkOffsetAcross->copyToDevice(stream);
+
+    if(slaveImage->isComplex())
+    {
+        c_slaveChunkRaw = new cuArrays<float2> (param->maxSlaveChunkHeight, param->maxSlaveChunkWidth);
+        c_slaveChunkRaw->allocate();
+
         //load a chunk from mmap to gpu
         slaveImage->loadToDevice(c_slaveChunkRaw->devData,
             param->slaveChunkStartPixelDown[idxChunk],
@@ -195,38 +269,60 @@ void cuAmpcorChunk::loadSlaveChunk()
             param->slaveChunkHeight[idxChunk],
             param->slaveChunkWidth[idxChunk],
             stream);
-    //copy to a batch format (nImages, height, width)
+
-    getRelativeOffset(ChunkOffsetDown->hostData, param->slaveStartPixelDown, param->slaveChunkStartPixelDown[idxChunk]);
-    ChunkOffsetDown->copyToDevice(stream);
-    getRelativeOffset(ChunkOffsetAcross->hostData, param->slaveStartPixelAcross, param->slaveChunkStartPixelAcross[idxChunk]);
-    ChunkOffsetAcross->copyToDevice(stream);
         if(param->derampMethod == 0) {
             cuArraysCopyToBatchAbsWithOffset(c_slaveChunkRaw, param->slaveChunkWidth[idxChunk],
                 c_slaveBatchRaw, ChunkOffsetDown->devData, ChunkOffsetAcross->devData, stream);
         }
-    else
+        else {
-    {
            cuArraysCopyToBatchWithOffset(c_slaveChunkRaw, param->slaveChunkWidth[idxChunk],
                 c_slaveBatchRaw, ChunkOffsetDown->devData, ChunkOffsetAcross->devData, stream);
         }
+        delete c_slaveChunkRaw;
+    }
+    else { //real image
+        //allocate the gpu buffer
+        r_slaveChunkRaw = new cuArrays<float> (param->maxSlaveChunkHeight, param->maxSlaveChunkWidth);
+        r_slaveChunkRaw->allocate();
+
+        //load a chunk from mmap to gpu
+        slaveImage->loadToDevice(r_slaveChunkRaw->devData,
+            param->slaveChunkStartPixelDown[idxChunk],
+            param->slaveChunkStartPixelAcross[idxChunk],
+            param->slaveChunkHeight[idxChunk],
+            param->slaveChunkWidth[idxChunk],
+            stream);
+
+        // convert to the batch format
+        cuArraysCopyToBatchWithOffsetR2C(r_slaveChunkRaw, param->slaveChunkWidth[idxChunk],
+                c_slaveBatchRaw, ChunkOffsetDown->devData, ChunkOffsetAcross->devData, stream);
+        delete r_slaveChunkRaw;
+    }
 }
 
-cuAmpcorChunk::cuAmpcorChunk(cuAmpcorParameter *param_, SlcImage *master_, SlcImage *slave_, 
+cuAmpcorChunk::cuAmpcorChunk(cuAmpcorParameter *param_, GDALImage *master_, GDALImage *slave_,
-    cuArrays<float2> *offsetImage_, cuArrays<float> *snrImage_, cudaStream_t stream_)
+    cuArrays<float2> *offsetImage_, cuArrays<float> *snrImage_, cuArrays<float3> *covImage_, cuArrays<int> *intImage1_, cuArrays<float> *floatImage1_, cudaStream_t stream_)
+
 {
     param = param_;
     masterImage = master_;
     slaveImage = slave_;
     offsetImage = offsetImage_;
     snrImage = snrImage_;
+    covImage = covImage_;
+
+    intImage1 = intImage1_;
+    floatImage1 = floatImage1_;
+
     stream = stream_;
 
-    std::cout << "debug Chunk creator " << param->maxMasterChunkHeight << " " << param->maxMasterChunkWidth << "\n";
+    // std::cout << "debug Chunk creator " << param->maxMasterChunkHeight << " " << param->maxMasterChunkWidth << "\n";
-    c_masterChunkRaw = new cuArrays<float2> (param->maxMasterChunkHeight, param->maxMasterChunkWidth); 
+    // try allocate/deallocate on the fly to save gpu memory 07/09/19
-    c_masterChunkRaw->allocate();
+    // c_masterChunkRaw = new cuArrays<float2> (param->maxMasterChunkHeight, param->maxMasterChunkWidth);
+    // c_masterChunkRaw->allocate();
 
-    c_slaveChunkRaw = new cuArrays<float2> (param->maxSlaveChunkHeight, param->maxSlaveChunkWidth); 
+    // c_slaveChunkRaw = new cuArrays<float2> (param->maxSlaveChunkHeight, param->maxSlaveChunkWidth);
-    c_slaveChunkRaw->allocate();
+    // c_slaveChunkRaw->allocate();
 
     ChunkOffsetDown = new cuArrays<int> (param->numberWindowDownInChunk, param->numberWindowAcrossInChunk);
     ChunkOffsetDown->allocate();
@@ -329,6 +425,54 @@ cuAmpcorChunk::cuAmpcorChunk(cuAmpcorParameter *param_, SlcImage *master_, SlcIm
     corrMaxValue = new cuArrays<float> (param->numberWindowDownInChunk, param->numberWindowAcrossInChunk);
     corrMaxValue->allocate();
 
+
+    // new arrays due to snr estimation
+    std::cout<< "corrRawZoomInHeight: " << param->corrRawZoomInHeight << "\n";
+    std::cout<< "corrRawZoomInWidth: " << param->corrRawZoomInWidth << "\n";
+
+    r_corrBatchRawZoomIn = new cuArrays<float> (
+			param->corrRawZoomInHeight,
+			param->corrRawZoomInWidth,
+			param->numberWindowDownInChunk,
+			param->numberWindowAcrossInChunk);
+    r_corrBatchRawZoomIn->allocate();
+
+    i_corrBatchZoomInValid = new cuArrays<int> (
+			param->corrRawZoomInHeight,
+			param->corrRawZoomInWidth,
+			param->numberWindowDownInChunk,
+			param->numberWindowAcrossInChunk);
+    i_corrBatchZoomInValid->allocate();
+
+
+    r_corrBatchSum = new cuArrays<float> (
+                    param->numberWindowDownInChunk,
+                    param->numberWindowAcrossInChunk);
+    r_corrBatchSum->allocate();
+
+    i_corrBatchValidCount = new cuArrays<int> (
+                        param->numberWindowDownInChunk,
+                        param->numberWindowAcrossInChunk);
+    i_corrBatchValidCount->allocate();
+
+    i_maxloc = new cuArrays<int2> (param->numberWindowDownInChunk, param->numberWindowAcrossInChunk);
+
+    i_maxloc->allocate();
+
+    r_maxval = new cuArrays<float> (param->numberWindowDownInChunk, param->numberWindowAcrossInChunk);
+
+    r_maxval->allocate();
+
+    r_snrValue = new cuArrays<float> (param->numberWindowDownInChunk, param->numberWindowAcrossInChunk);
+
+    r_snrValue->allocate();
+
+    r_covValue = new cuArrays<float3> (param->numberWindowDownInChunk, param->numberWindowAcrossInChunk);
+
+    r_covValue->allocate();
+
+    // end of new arrays
+
     if(param->oversamplingMethod) {
         corrSincOverSampler = new cuSincOverSamplerR2R(param->zoomWindowSize, param->oversamplingFactor, stream);
     }

contrib/PyCuAmpcor/src/cuAmpcorChunk.h

@@ -6,7 +6,7 @@
 #ifndef __CUAMPCORCHUNK_H
 #define __CUAMPCORCHUNK_H
 
-#include "SlcImage.h"
+#include "GDALImage.h"
 #include "cuArrays.h"
 #include "cuAmpcorParameter.h"
 #include "cuOverSampler.h"
@@ -24,15 +24,26 @@ private:
 	int devId;
 	cudaStream_t stream;
 
-	SlcImage *masterImage;
+	GDALImage *masterImage;
-	SlcImage *slaveImage;
+	GDALImage *slaveImage;
 	cuAmpcorParameter *param;
 	cuArrays<float2> *offsetImage;
 	cuArrays<float> *snrImage;
+	cuArrays<float3> *covImage;
 
+	// added for test
+    cuArrays<int> *intImage1;
+    cuArrays<float> *floatImage1;
+
+    // gpu buffer
 	cuArrays<float2> * c_masterChunkRaw, * c_slaveChunkRaw;
+	cuArrays<float> * r_masterChunkRaw, * r_slaveChunkRaw;
+
+	// gpu windows raw data
     cuArrays<float2> * c_masterBatchRaw, * c_slaveBatchRaw, * c_slaveBatchZoomIn;
     cuArrays<float> * r_masterBatchRaw, * r_slaveBatchRaw;
+
+    // gpu windows oversampled data
     cuArrays<float2> * c_masterBatchOverSampled, * c_slaveBatchOverSampled;
     cuArrays<float> * r_masterBatchOverSampled, * r_slaveBatchOverSampled;
     cuArrays<float> * r_corrBatchRaw, * r_corrBatchZoomIn, * r_corrBatchZoomInOverSampled, * r_corrBatchZoomInAdjust;
@@ -50,26 +61,32 @@ private:
 	cuArrays<int2> *offsetInit;
 	cuArrays<int2> *offsetZoomIn;
 	cuArrays<float2> *offsetFinal;
+    cuArrays<float> *corrMaxValue;
 
-        //corr statistics
-    cuArrays<int2> *i_maxloc;
-    cuArrays<float> *r_maxval;
 
+    //SNR estimation
+
+    cuArrays<float> *r_corrBatchRawZoomIn;
     cuArrays<float> *r_corrBatchSum;
     cuArrays<int> *i_corrBatchZoomInValid, *i_corrBatchValidCount;
 
-        cuArrays<float> *corrMaxValue;
     cuArrays<float> *r_snrValue;
 
+    cuArrays<int2> *i_maxloc;
+    cuArrays<float> *r_maxval;
+
+    // Varince estimation.
+    cuArrays<float3> *r_covValue;
+
 public:
 	cuAmpcorChunk()	{}
 	//cuAmpcorChunk(cuAmpcorParameter *param_, SlcImage *master_, SlcImage *slave_);
 
 	void setIndex(int idxDown_, int idxAcross_);
 
+	cuAmpcorChunk(cuAmpcorParameter *param_, GDALImage *master_, GDALImage *slave_, cuArrays<float2> *offsetImage_,
+	            cuArrays<float> *snrImage_, cuArrays<float3> *covImage_, cuArrays<int> *intImage1_, cuArrays<float> *floatImage1_, cudaStream_t stream_);
 
-	cuAmpcorChunk(cuAmpcorParameter *param_, SlcImage *master_, SlcImage *slave_, cuArrays<float2> *offsetImage_, 
-	            cuArrays<float> *snrImage_, cudaStream_t stream_);
 
     void loadMasterChunk();
     void loadSlaveChunk();

contrib/PyCuAmpcor/src/cuAmpcorController.cu

@@ -1,7 +1,7 @@
 // Implementation of cuAmpcorController
 
 #include "cuAmpcorController.h"
-#include "SlcImage.h"
+#include "GDALImage.h"
 #include "cuArrays.h"
 #include "cudaUtil.h"
 #include "cuAmpcorChunk.h"
@@ -13,19 +13,22 @@ cuAmpcorController::~cuAmpcorController() { delete param; }
 
 void cuAmpcorController::runAmpcor() {
 
+    // set the gpu id
     param->deviceID = gpuDeviceInit(param->deviceID);
-    SlcImage *masterImage;
+    // initialize the gdal driver
-    SlcImage *slaveImage;
+    GDALAllRegister();
+    // master and slave images; use band=1 as default
+    // TODO: selecting band
+    GDALImage *masterImage = new GDALImage(param->masterImageName, 1, param->mmapSizeInGB);
+    GDALImage *slaveImage = new GDALImage(param->slaveImageName, 1, param->mmapSizeInGB);
 
     cuArrays<float2> *offsetImage, *offsetImageRun;
     cuArrays<float> *snrImage, *snrImageRun;
+    cuArrays<float3> *covImage, *covImageRun;
 
-    
+    // For debugging.
-//    cuArrays<float> *floatImage;
+    cuArrays<int> *intImage1;
-//    cuArrays<int> *intImage;
+    cuArrays<float> *floatImage1;
-
-    masterImage = new SlcImage(param->masterImageName, param->masterImageHeight, param->masterImageWidth, param->mmapSizeInGB);
-    slaveImage = new SlcImage(param->slaveImageName, param->slaveImageHeight, param->slaveImageWidth, param->mmapSizeInGB);
 
     int nWindowsDownRun = param->numberChunkDown * param->numberWindowDownInChunk;
     int nWindowsAcrossRun = param->numberChunkAcross * param->numberWindowAcrossInChunk;
@@ -33,28 +36,41 @@ void cuAmpcorController::runAmpcor() {
     std::cout << "Debug " << nWindowsDownRun << " " << param->numberWindowDown << "\n";
 
     offsetImageRun = new cuArrays<float2>(nWindowsDownRun, nWindowsAcrossRun);
-    snrImageRun = new cuArrays<float>(nWindowsDownRun, nWindowsAcrossRun);
     offsetImageRun->allocate();
+
+    snrImageRun = new cuArrays<float>(nWindowsDownRun, nWindowsAcrossRun);
     snrImageRun->allocate();
 
+    covImageRun = new cuArrays<float3>(nWindowsDownRun, nWindowsAcrossRun);
+    covImageRun->allocate();
+
+    // intImage 1 and floatImage 1 are added for debugging issues
+
+    intImage1 = new cuArrays<int>(nWindowsDownRun, nWindowsAcrossRun);
+    intImage1->allocate();
+
+    floatImage1 = new cuArrays<float>(nWindowsDownRun, nWindowsAcrossRun);
+    floatImage1->allocate();
+
+    // Offsetfields.
     offsetImage = new cuArrays<float2>(param->numberWindowDown, param->numberWindowAcross);
-    snrImage = new cuArrays<float>(param->numberWindowDown, param->numberWindowAcross);
     offsetImage->allocate();
+
+    // SNR.
+    snrImage = new cuArrays<float>(param->numberWindowDown, param->numberWindowAcross);
     snrImage->allocate();
 
-// Minyan Zhong
+    // Variance.
-//    floatImage = new cuArrays<float>(param->numberWindowDown, param->numberWindowAcross);
+    covImage = new cuArrays<float3>(param->numberWindowDown, param->numberWindowAcross);
-//    intImage = new cuArrays<int>(param->numberWindowDown, param->numberWindowAcross);
+    covImage->allocate();
 
-//    floatImage->allocate();
-//    intImage->allocate();
-// 
     cudaStream_t streams[param->nStreams];
     cuAmpcorChunk *chunk[param->nStreams];
     for(int ist=0; ist<param->nStreams; ist++)
     {
         cudaStreamCreate(&streams[ist]);
-        chunk[ist]= new cuAmpcorChunk(param, masterImage, slaveImage, offsetImageRun, snrImageRun, streams[ist]);
+        chunk[ist]= new cuAmpcorChunk(param, masterImage, slaveImage, offsetImageRun, snrImageRun, covImageRun, intImage1, floatImage1, streams[ist]);
+
     }
 
     int nChunksDown = param->numberChunkDown;
@@ -63,7 +79,7 @@ void cuAmpcorController::runAmpcor() {
     std::cout << "Total number of windows (azimuth x range):  " <<param->numberWindowDown << " x " << param->numberWindowAcross  << std::endl;
     std::cout << "to be processed in the number of chunks: " <<nChunksDown << " x " << nChunksAcross  << std::endl;
 
-    for(int i = 60; i<nChunksDown; i++)
+    for(int i = 0; i<nChunksDown; i++)
     {
         std::cout << "Processing chunk (" << i <<", x" << ")" << std::endl;
         for(int j=0; j<nChunksAcross; j+=param->nStreams)
@@ -81,26 +97,39 @@ void cuAmpcorController::runAmpcor() {
 
     cudaDeviceSynchronize();
 
+    // Do extraction.
     cuArraysCopyExtract(offsetImageRun, offsetImage, make_int2(0,0), streams[0]);
     cuArraysCopyExtract(snrImageRun, snrImage, make_int2(0,0), streams[0]);
+    cuArraysCopyExtract(covImageRun, covImage, make_int2(0,0), streams[0]);
 
     offsetImage->outputToFile(param->offsetImageName, streams[0]);
     snrImage->outputToFile(param->snrImageName, streams[0]);
+    covImage->outputToFile(param->covImageName, streams[0]);
 
-// Minyan Zhong
+    // Output debugging arrays.
-//    floatImage->allocate();
+    intImage1->outputToFile("intImage1", streams[0]);
-//    intImage->allocate();
+    floatImage1->outputToFile("floatImage1", streams[0]);
-//
 
     outputGrossOffsets();
+
+    // Delete arrays.
     delete offsetImage;
     delete snrImage;
+    delete covImage;
+
+    delete intImage1;
+    delete floatImage1;
+
     delete offsetImageRun;
     delete snrImageRun;
+    delete covImageRun;
+
     for (int ist=0; ist<param->nStreams; ist++)
         delete chunk[ist];
+
     delete masterImage;
     delete slaveImage;
+
 }
 
 void cuAmpcorController::outputGrossOffsets()

contrib/PyCuAmpcor/src/cuAmpcorParameter.cu

@@ -17,6 +17,8 @@
 
 cuAmpcorParameter::cuAmpcorParameter()
 {
+    // default settings
+    // will be changed if they are set by python scripts
     algorithm = 0; //0 freq; 1 time
     deviceID = 0;
     nStreams = 1;
@@ -43,6 +45,7 @@ cuAmpcorParameter::cuAmpcorParameter()
     offsetImageName = "DenseOffset.off";
     grossOffsetImageName = "GrossOffset.off";
     snrImageName = "snr.snr";
+    covImageName = "cov.cov";
     numberWindowDown =  1;
     numberWindowAcross = 1;
     numberWindowDownInChunk = 1;
@@ -50,6 +53,13 @@ cuAmpcorParameter::cuAmpcorParameter()
 
     masterStartPixelDown0 = 0;
     masterStartPixelAcross0 = 0;
+
+    corrRawZoomInHeight = 17; // 8*2+1
+    corrRawZoomInWidth = 17;
+
+    useMmap = 1; // use mmap
+    mmapSizeInGB = 1;
+
 }
 
 /**

contrib/PyCuAmpcor/src/cuAmpcorParameter.h

@@ -50,6 +50,8 @@ public:
     int searchWindowSizeHeightRawZoomIn;
     int searchWindowSizeWidthRawZoomIn;
 
+    int corrRawZoomInHeight;  // window to estimate snr
+    int corrRawZoomInWidth;
 
     // chip or window size after oversampling
     int rawDataOversamplingFactor;  /// Raw data overampling factor (from original size to oversampled size)
@@ -101,7 +103,8 @@ public:
     int numberChunkAcross;          /// number of chunks (across)
     int numberChunks;
 
-    int mmapSizeInGB;
+    int useMmap;                    /// whether to use mmap 0=not 1=yes (default = 0)
+    int mmapSizeInGB;               /// size for mmap buffer(useMmap=1) or a cpu memory buffer (useMmap=0)
 
     int masterStartPixelDown0;
     int masterStartPixelAcross0;
@@ -128,6 +131,7 @@ public:
     std::string grossOffsetImageName;
     std::string offsetImageName;    /// Output Offset fields filename
     std::string snrImageName;       /// Output SNR filename
+    std::string covImageName;
 
     cuAmpcorParameter();  /// Class constructor and default parameters setter
     ~cuAmpcorParameter(); /// Class descontructor

contrib/PyCuAmpcor/src/cuAmpcorUtil.h

@@ -22,16 +22,23 @@ void cuArraysCopyToBatchWithOffset(cuArrays<float2> *image1, const int lda1, cuA
 	const int *offsetH, const int* offsetW, cudaStream_t stream);
 void cuArraysCopyToBatchAbsWithOffset(cuArrays<float2> *image1, const int lda1, cuArrays<float2> *image2,
 	const int *offsetH, const int* offsetW, cudaStream_t stream);
+void cuArraysCopyToBatchWithOffsetR2C(cuArrays<float> *image1, const int lda1, cuArrays<float2> *image2,
+	const int *offsetH, const int* offsetW, cudaStream_t stream);
 void cuArraysCopyC2R(cuArrays<float2> *image1, cuArrays<float> *image2, int strideH, int strideW, cudaStream_t stream);
 
+// same routine name overloaded for different data type
 void cuArraysCopyExtract(cuArrays<float> *imagesIn, cuArrays<float> *imagesOut, cuArrays<int2> *offset, cudaStream_t stream);
 void cuArraysCopyExtract(cuArrays<float> *imagesIn, cuArrays<float> *imagesOut, int2 offset, cudaStream_t stream);
 void cuArraysCopyExtract(cuArrays<float2> *imagesIn, cuArrays<float> *imagesOut, int2 offset, cudaStream_t stream);
 void cuArraysCopyExtract(cuArrays<float2> *imagesIn, cuArrays<float2> *imagesOut, int2 offset, cudaStream_t stream);
 void cuArraysCopyExtract(cuArrays<float2> *imagesIn, cuArrays<float2> *imagesOut, cuArrays<int2> *offsets, cudaStream_t stream);
+void cuArraysCopyExtract(cuArrays<float3> *imagesIn, cuArrays<float3> *imagesOut, int2 offset, cudaStream_t stream);
 
 void cuArraysCopyInsert(cuArrays<float2> *imageIn, cuArrays<float2> *imageOut, int offsetX, int offersetY, cudaStream_t stream);
+void cuArraysCopyInsert(cuArrays<float3> *imageIn, cuArrays<float3> *imageOut, int offsetX, int offersetY, cudaStream_t stream);
 void cuArraysCopyInsert(cuArrays<float> *imageIn, cuArrays<float> *imageOut, int offsetX, int offsetY, cudaStream_t stream);
+void cuArraysCopyInsert(cuArrays<int> *imageIn, cuArrays<int> *imageOut, int offsetX, int offersetY, cudaStream_t stream);
+
 void cuArraysCopyInversePadded(cuArrays<float> *imageIn, cuArrays<float> *imageOut,cudaStream_t stream);
 
 void cuArraysCopyPadded(cuArrays<float> *imageIn, cuArrays<float> *imageOut,cudaStream_t stream);
@@ -80,7 +87,11 @@ void cuArraysElementMultiplyConjugate(cuArrays<float2> *image1, cuArrays<float2>
 void cuArraysCopyExtractCorr(cuArrays<float> *imagesIn, cuArrays<float> *imagesOut, cuArrays<int> *imagesValid, cuArrays<int2> *maxloc, cudaStream_t stream);
 // implemented in cuCorrNormalization.cu
 void cuArraysSumCorr(cuArrays<float> *images, cuArrays<int> *imagesValid, cuArrays<float> *imagesSum, cuArrays<int> *imagesValidCount, cudaStream_t stream);
+
 // implemented in cuEstimateStats.cu
 void cuEstimateSnr(cuArrays<float> *corrSum, cuArrays<int> *corrValidCount, cuArrays<float> *maxval, cuArrays<float> *snrValue, cudaStream_t stream);
 
+// implemented in cuEstimateStats.cu
+void cuEstimateVariance(cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream);
+
 #endif

contrib/PyCuAmpcor/src/cuArrays.cu

@@ -155,7 +155,20 @@
 		file.close();
 	}
 
+	template<>
+	void cuArrays<float3>::outputToFile(std::string fn, cudaStream_t stream)
+	{
+		float *data;
+		data = (float *)malloc(size*count*sizeof(float3));
+		checkCudaErrors(cudaMemcpyAsync(data, devData, size*count*sizeof(float3), cudaMemcpyDeviceToHost, stream));
+		std::ofstream file;  
+		file.open(fn.c_str(),  std::ios_base::binary);
+		file.write((char *)data, size*count*sizeof(float3));
+		file.close();
+	}
+	
 	template class cuArrays<float>;
 	template class cuArrays<float2>;
+    template class cuArrays<float3>;
 	template class cuArrays<int2>;
     template class cuArrays<int>;

contrib/PyCuAmpcor/src/cuArraysCopy.cu

@@ -16,7 +16,7 @@ inline __device__ float cuAbs(float2 a)
 	return sqrtf(a.x*a.x+a.y*a.y);
 }*/
 
-//copy a chunk into a series of chips
+// copy a chunk into a batch of chips for a given stride
 __global__ void cuArraysCopyToBatch_kernel(const float2 *imageIn, const int inNX, const int inNY,
     float2 *imageOut, const int outNX, const int outNY,
     const int nImagesX, const int nImagesY,
@@ -33,7 +33,6 @@ __global__ void cuArraysCopyToBatch_kernel(const float2 *imageIn, const int inNX
 	imageOut[idxOut] = imageIn[idxIn];
 }
 
-//tested
 void cuArraysCopyToBatch(cuArrays<float2> *image1, cuArrays<float2> *image2,
 	int strideH, int strideW, cudaStream_t stream)
 {
@@ -48,6 +47,8 @@ void cuArraysCopyToBatch(cuArrays<float2> *image1, cuArrays<float2> *image2,
 	getLastCudaError("cuArraysCopyToBatch_kernel");
 }
 
+
+// copy a chunk into a batch of chips for a set of offsets (varying strides), from complex to complex
 __global__ void cuArraysCopyToBatchWithOffset_kernel(const float2 *imageIn, const int inNY,
     float2 *imageOut, const int outNX, const int outNY, const int nImages,
 	const int *offsetX, const int *offsetY)
@@ -61,10 +62,7 @@ __global__ void cuArraysCopyToBatchWithOffset_kernel(const float2 *imageIn, cons
 	imageOut[idxOut] = imageIn[idxIn];
 }
 
-/// @param[in] image1 input image in a large chunk
+// lda1 (inNY) is the leading dimension of image1, usually, its width
-/// @param[in] lda1 width of image 1
-/// @param[out] image2 output image with a batch of small windows
-
 void cuArraysCopyToBatchWithOffset(cuArrays<float2> *image1, const int lda1, cuArrays<float2> *image2,
 	const int *offsetH, const int* offsetW, cudaStream_t stream)
 {
@@ -79,6 +77,7 @@ void cuArraysCopyToBatchWithOffset(cuArrays<float2> *image1, const int lda1, cuA
 	getLastCudaError("cuArraysCopyToBatchAbsWithOffset_kernel");
 }
 
+// copy a chunk into a batch of chips for a set of offsets (varying strides), from complex to real(take amplitudes)
 __global__ void cuArraysCopyToBatchAbsWithOffset_kernel(const float2 *imageIn, const int inNY,
     float2 *imageOut, const int outNX, const int outNY, const int nImages,
 	const int *offsetX, const int *offsetY)
@@ -106,6 +105,34 @@ void cuArraysCopyToBatchAbsWithOffset(cuArrays<float2> *image1, const int lda1,
 	getLastCudaError("cuArraysCopyToBatchAbsWithOffset_kernel");
 }
 
+// copy a chunk into a batch of chips for a set of offsets (varying strides), from real to complex(to real part)
+__global__ void cuArraysCopyToBatchWithOffsetR2C_kernel(const float *imageIn, const int inNY,
+    float2 *imageOut, const int outNX, const int outNY, const int nImages,
+	const int *offsetX, const int *offsetY)
+{
+	int idxImage = blockIdx.z;
+	int outx = threadIdx.x + blockDim.x*blockIdx.x;
+	int outy = threadIdx.y + blockDim.y*blockIdx.y;
+	if(idxImage>=nImages || outx >= outNX || outy >= outNY) return;
+	int idxOut = idxImage*outNX*outNY + outx*outNY + outy;
+	int idxIn = (offsetX[idxImage]+outx)*inNY + offsetY[idxImage] + outy;
+	imageOut[idxOut] = make_float2(imageIn[idxIn], 0.0f);
+}
+
+void cuArraysCopyToBatchWithOffsetR2C(cuArrays<float> *image1, const int lda1, cuArrays<float2> *image2,
+	const int *offsetH, const int* offsetW, cudaStream_t stream)
+{
+	const int nthreads = 16;
+	dim3 blockSize(nthreads, nthreads, 1);
+	dim3 gridSize(IDIVUP(image2->height,nthreads), IDIVUP(image2->width,nthreads), image2->count);
+    //fprintf(stderr, "copy tile to batch, %d %d\n", lda1, image2->count);
+	cuArraysCopyToBatchWithOffsetR2C_kernel<<<gridSize,blockSize, 0 , stream>>> (
+		image1->devData, lda1,
+		image2->devData, image2->height, image2->width, image2->count,
+		offsetH, offsetW);
+	getLastCudaError("cuArraysCopyToBatchWithOffsetR2C_kernel");
+}
+
 //copy a chunk into a series of chips
 __global__ void cuArraysCopyC2R_kernel(const float2 *imageIn, const int inNX, const int inNY,
     float *imageOut, const int outNX, const int outNY,
@@ -208,14 +235,17 @@ __global__ void cuArraysCopyExtractVaryingOffsetCorr(const float *imageIn, const
 
         int idxImage = blockIdx.z;
 
+        // One thread per out point. Find the coordinates within the current image.
         int outx = threadIdx.x + blockDim.x*blockIdx.x;
         int outy = threadIdx.y + blockDim.y*blockIdx.y;
 
+        // Find the correponding input.
         int inx = outx + maxloc[idxImage].x - outNX/2;
         int iny = outy + maxloc[idxImage].y - outNY/2;
 
         if (outx < outNX && outy < outNY)
         {
+                // Find the location in full array.
                 int idxOut = ( blockIdx.z * outNX + outx ) * outNY + outy;
 
                 int idxIn = ( blockIdx.z * inNX + inx ) * inNY + iny;
@@ -284,6 +314,7 @@ void cuArraysCopyExtract(cuArrays<float> *imagesIn, cuArrays<float> *imagesOut,
 	getLastCudaError("cuArraysCopyExtract error");
 }
 
+//
 
 __global__ void cuArraysCopyExtract_C2C_FixedOffset(const float2 *imageIn, const int inNX, const int inNY,
      float2 *imageOut, const int outNX, const int outNY, const int nImages,
@@ -315,6 +346,42 @@ void cuArraysCopyExtract(cuArrays<float2> *imagesIn, cuArrays<float2> *imagesOut
 	    imagesOut->devData, imagesOut->height, imagesOut->width, imagesOut->count, offset.x, offset.y);
 	getLastCudaError("cuArraysCopyExtractC2C error");
 }
+//
+
+// float3
+__global__ void cuArraysCopyExtract_C2C_FixedOffset(const float3 *imageIn, const int inNX, const int inNY,
+     float3 *imageOut, const int outNX, const int outNY, const int nImages,
+     const int offsetX, const int offsetY)
+{
+	int outx = threadIdx.x + blockDim.x*blockIdx.x;
+	int outy = threadIdx.y + blockDim.y*blockIdx.y;
+
+	if(outx < outNX && outy < outNY)
+	{
+		int idxOut = (blockIdx.z * outNX + outx)*outNY+outy;
+		int idxIn = (blockIdx.z*inNX + outx + offsetX)*inNY + outy + offsetY;
+		imageOut[idxOut] = imageIn[idxIn];
+	}
+}
+
+
+void cuArraysCopyExtract(cuArrays<float3> *imagesIn, cuArrays<float3> *imagesOut, int2 offset, cudaStream_t stream)
+{
+	//assert(imagesIn->height >= imagesOut && inNY >= outNY);
+	const int nthreads = NTHREADS2D;
+	dim3 threadsperblock(nthreads, nthreads,1);
+	dim3 blockspergrid(IDIVUP(imagesOut->height,nthreads), IDIVUP(imagesOut->width,nthreads), imagesOut->count);
+    //std::cout << "debug copyExtract" << imagesOut->width << imagesOut->height << "\n";
+    //imagesIn->debuginfo(stream);
+    //imagesOut->debuginfo(stream);
+	cuArraysCopyExtract_C2C_FixedOffset<<<blockspergrid, threadsperblock,0, stream>>>
+        (imagesIn->devData, imagesIn->height, imagesIn->width,
+	    imagesOut->devData, imagesOut->height, imagesOut->width, imagesOut->count, offset.x, offset.y);
+	getLastCudaError("cuArraysCopyExtractFloat3 error");
+}
+
+//
+
 
 __global__ void cuArraysCopyExtract_C2R_FixedOffset(const float2 *imageIn, const int inNX, const int inNY,
      float *imageOut, const int outNX, const int outNY, const int nImages,
@@ -332,6 +399,7 @@ __global__ void cuArraysCopyExtract_C2R_FixedOffset(const float2 *imageIn, const
 }
 
 
+
 void cuArraysCopyExtract(cuArrays<float2> *imagesIn, cuArrays<float> *imagesOut, int2 offset, cudaStream_t stream)
 {
 	//assert(imagesIn->height >= imagesOut && inNY >= outNY);
@@ -343,7 +411,7 @@ void cuArraysCopyExtract(cuArrays<float2> *imagesIn, cuArrays<float> *imagesOut,
 	    imagesOut->devData, imagesOut->height, imagesOut->width, imagesOut->count, offset.x, offset.y);
 	getLastCudaError("cuArraysCopyExtractC2C error");
 }
-
+//
 
 __global__ void cuArraysCopyInsert_kernel(const float2* imageIn, const int inNX, const int inNY,
    float2* imageOut, const int outNY, const int offsetX, const int offsetY)
@@ -367,7 +435,31 @@ void cuArraysCopyInsert(cuArrays<float2> *imageIn, cuArrays<float2> *imageOut, i
 	       imageOut->devData,  imageOut->width, offsetX, offsetY);
 	getLastCudaError("cuArraysCopyInsert error");
 }
+//
+// float3
+__global__ void cuArraysCopyInsert_kernel(const float3* imageIn, const int inNX, const int inNY,
+   float3* imageOut, const int outNY, const int offsetX, const int offsetY)
+{
+	int inx = threadIdx.x + blockDim.x*blockIdx.x;
+	int iny = threadIdx.y + blockDim.y*blockIdx.y;
+	if(inx < inNX && iny < inNY) {
+		int idxOut = IDX2R(inx+offsetX, iny+offsetY, outNY);
+		int idxIn = IDX2R(inx, iny, inNY);
+		imageOut[idxOut] = make_float3(imageIn[idxIn].x, imageIn[idxIn].y, imageIn[idxIn].z);
+	}
+}
 
+void cuArraysCopyInsert(cuArrays<float3> *imageIn, cuArrays<float3> *imageOut, int offsetX, int offsetY, cudaStream_t stream)
+{
+	const int nthreads = 16;
+	dim3 threadsperblock(nthreads, nthreads);
+	dim3 blockspergrid(IDIVUP(imageIn->height,nthreads), IDIVUP(imageIn->width,nthreads));
+	cuArraysCopyInsert_kernel<<<blockspergrid, threadsperblock,0, stream>>>(imageIn->devData, imageIn->height, imageIn->width,
+	       imageOut->devData,  imageOut->width, offsetX, offsetY);
+	getLastCudaError("cuArraysCopyInsert error");
+}
+
+//
 
 __global__ void cuArraysCopyInsert_kernel(const float* imageIn, const int inNX, const int inNY,
    float* imageOut, const int outNY, const int offsetX, const int offsetY)
@@ -392,6 +484,32 @@ void cuArraysCopyInsert(cuArrays<float> *imageIn, cuArrays<float> *imageOut, int
 	getLastCudaError("cuArraysCopyInsert Float error");
 }
 
+//
+
+__global__ void cuArraysCopyInsert_kernel(const int* imageIn, const int inNX, const int inNY,
+   int* imageOut, const int outNY, const int offsetX, const int offsetY)
+{
+	int inx = threadIdx.x + blockDim.x*blockIdx.x;
+	int iny = threadIdx.y + blockDim.y*blockIdx.y;
+	if(inx < inNX && iny < inNY) {
+		int idxOut = IDX2R(inx+offsetX, iny+offsetY, outNY);
+		int idxIn = IDX2R(inx, iny, inNY);
+		imageOut[idxOut] = imageIn[idxIn];
+	}
+}
+
+
+void cuArraysCopyInsert(cuArrays<int> *imageIn, cuArrays<int> *imageOut, int offsetX, int offsetY, cudaStream_t stream)
+{
+	const int nthreads = 16;
+	dim3 threadsperblock(nthreads, nthreads);
+	dim3 blockspergrid(IDIVUP(imageIn->height,nthreads), IDIVUP(imageIn->width,nthreads));
+	cuArraysCopyInsert_kernel<<<blockspergrid, threadsperblock,0, stream>>>(imageIn->devData, imageIn->height, imageIn->width,
+	       imageOut->devData,  imageOut->width, offsetX, offsetY);
+	getLastCudaError("cuArraysCopyInsert Integer error");
+}
+//
+
 
 __global__ void cuArraysCopyInversePadded_kernel(float *imageIn, int inNX, int inNY, int sizeIn,
     float *imageOut, int outNX, int outNY, int sizeOut, int nImages)

contrib/PyCuAmpcor/src/cuCorrNormalization.cu

@@ -195,7 +195,6 @@ __device__ float2 partialSums(const float v, volatile float* shmem, const int st
     return make_float2(Sum, Sum2);
 } 
 
-__forceinline__ __device__ int __mul(const int a, const int b) { return a*b; }
 
 template<const int Nthreads2>
 __global__ void cuCorrNormalize_kernel(
@@ -232,7 +231,7 @@ __global__ void cuCorrNormalize_kernel(
         templateSum += templateD[i];
     }
     templateSum = sumReduceBlock<Nthreads>(templateSum, shmem);
-
+    __syncthreads();
     
     float templateSum2 = 0.0f;
     for (int i = tid; i < templateSize; i += Nthreads)
@@ -241,11 +240,12 @@ __global__ void cuCorrNormalize_kernel(
             templateSum2 += t*t;
         }
     templateSum2 = sumReduceBlock<Nthreads>(templateSum2, shmem);
+    __syncthreads();
 
     //if(tid ==0) printf("template sum %d %g %g \n", imageIdx, templateSum, templateSum2);
     /*********/
 
-    shmem[tid] = shmem[tid + Nthreads] = 0.0f;
+    shmem[tid] = shmem[tid + Nthreads] = shmem[tid + 2*Nthreads] = 0.0f;
     __syncthreads();
     
     float imageSum  = 0.0f;
@@ -281,7 +281,7 @@ __global__ void cuCorrNormalize_kernel(
         if (tid < resultNY)
         {
             const int         ix = iaddr/imageNY;
-            const int       addr = __mul(ix-templateNX, resultNY);
+            const int       addr = (ix-templateNX)*resultNY;
             
             //printf("test norm %d %d %d %d %f\n", tid, ix, addr, addr+tid, resultD[addr + tid]);
             

contrib/PyCuAmpcor/src/cuEstimateStats.cu

@@ -25,7 +25,7 @@ __global__ void cudaKernel_estimateSnr(const float* corrSum, const int* corrVali
 
     float mean = (corrSum[idx] - maxval[idx] * maxval[idx]) / (corrValidCount[idx] - 1);
 
-    snrValue[idx] = maxval[idx] / mean;
+    snrValue[idx] = maxval[idx] * maxval[idx] / mean;
 }
 
 void cuEstimateSnr(cuArrays<float> *corrSum, cuArrays<int> *corrValidCount, cuArrays<float> *maxval, cuArrays<float> *snrValue, cudaStream_t stream)
@@ -68,3 +68,80 @@ void cuEstimateSnr(cuArrays<float> *corrSum, cuArrays<int> *corrValidCount, cuAr
 
     getLastCudaError("cuda kernel estimate stats error\n");
 }
+
+
+template <const int BLOCKSIZE> // number of threads per block.
+__global__ void cudaKernel_estimateVar(const float* corrBatchRaw, const int NX, const int NY, const int2* maxloc, const float* maxval, float3* covValue, const int size)
+{
+
+    // Find image id.
+    int idxImage = threadIdx.x + blockDim.x*blockIdx.x;
+
+    if (idxImage >= size) return;
+
+    // Preparation.
+    int px = maxloc[idxImage].x;
+    int py = maxloc[idxImage].y;
+    float peak = maxval[idxImage];
+
+    // Check if maxval is on the margin.
+    if (px-1 < 0 || py-1 <0 || px + 1 >=NX || py+1 >=NY)  {
+
+        covValue[idxImage] = make_float3(99.0, 99.0, 99.0);
+
+    }
+    else {
+        int offset = NX * NY * idxImage;
+        int idx00 = offset + (px - 1) * NY + py - 1;
+        int idx01 = offset + (px - 1) * NY + py    ;
+        int idx02 = offset + (px - 1) * NY + py + 1;
+        int idx10 = offset + (px    ) * NY + py - 1;
+        int idx11 = offset + (px    ) * NY + py    ;
+        int idx12 = offset + (px    ) * NY + py + 1;
+        int idx20 = offset + (px + 1) * NY + py - 1;
+        int idx21 = offset + (px + 1) * NY + py    ;
+        int idx22 = offset + (px + 1) * NY + py + 1;
+
+        float dxx = - ( corrBatchRaw[idx21] + corrBatchRaw[idx01] - 2*corrBatchRaw[idx11] ) * 0.5;
+        float dyy = - ( corrBatchRaw[idx12] + corrBatchRaw[idx10] - 2*corrBatchRaw[idx11] ) * 0.5;
+        float dxy = - ( corrBatchRaw[idx22] + corrBatchRaw[idx00] - corrBatchRaw[idx20] - corrBatchRaw[idx02] ) *0.25;
+
+        float n2 = fmaxf(1 - peak, 0.0);
+
+        int winSize = NX*NY;
+
+        dxx = dxx * winSize;
+        dyy = dyy * winSize;
+        dxy = dxy * winSize;
+
+        float n4 = n2*n2;
+        n2 = n2 * 2;
+        n4 = n4 * 0.5 * winSize;
+
+        float u = dxy * dxy - dxx * dyy;
+        float u2 = u*u;
+
+        if (fabsf(u) < 1e-2) {
+
+            covValue[idxImage] = make_float3(99.0, 99.0, 99.0);
+
+        }
+        else {
+                float cov_xx = (- n2 * u * dyy + n4 * ( dyy*dyy + dxy*dxy) ) / u2;
+                float cov_yy = (- n2 * u * dxx + n4 * ( dxx*dxx + dxy*dxy) ) / u2;
+                float cov_xy = (  n2 * u * dxy - n4 * ( dxx + dyy ) * dxy ) / u2;
+                covValue[idxImage] = make_float3(cov_xx, cov_yy, cov_xy);
+        }
+    }
+}
+
+void cuEstimateVariance(cuArrays<float> *corrBatchRaw, cuArrays<int2> *maxloc, cuArrays<float> *maxval, cuArrays<float3> *covValue, cudaStream_t stream)
+{
+
+    int size = corrBatchRaw->count;
+
+    // One dimensional launching parameters to loop over every correlation surface.
+    cudaKernel_estimateVar<NTHREADS><<< IDIVUP(size, NTHREADS), NTHREADS, 0, stream>>>
+        (corrBatchRaw->devData, corrBatchRaw->height, corrBatchRaw->width, maxloc->devData, maxval->devData, covValue->devData, size);
+    getLastCudaError("cudaKernel_estimateVar error\n");
+}

contrib/PyCuAmpcor/src/setup.py

@@ -7,20 +7,21 @@
 from distutils.core import setup
 from distutils.extension import Extension
 from Cython.Build import cythonize
-import os
 
-os.environ["CC"] = "g++"
+import numpy
 
 setup(  name = 'PyCuAmpcor',
         ext_modules = cythonize(Extension(
         "PyCuAmpcor",
         sources=['PyCuAmpcor.pyx'],
-        include_dirs=['/usr/local/cuda/include'], # REPLACE WITH YOUR PATH TO YOUR CUDA LIBRARY HEADERS
+        include_dirs=['/usr/local/cuda/include', numpy.get_include()], # REPLACE WITH YOUR PATH TO YOUR CUDA LIBRARY HEADERS
         extra_compile_args=['-fPIC','-fpermissive'],
-        extra_objects=['SlcImage.o','cuAmpcorChunk.o','cuAmpcorParameter.o','cuCorrFrequency.o',
+        extra_objects=['GDALImage.o','cuAmpcorChunk.o','cuAmpcorParameter.o','cuCorrFrequency.o',
                        'cuCorrNormalization.o','cuCorrTimeDomain.o','cuArraysCopy.o',
                        'cuArrays.o','cuArraysPadding.o','cuOffset.o','cuOverSampler.o',
-                       'cuSincOverSampler.o', 'cuDeramp.o','cuAmpcorController.o'],
+                       'cuSincOverSampler.o', 'cuDeramp.o','cuAmpcorController.o','cuEstimateStats.o'],
-        extra_link_args=['-L/usr/local/cuda/lib64','-lcuda','-lcudart','-lcufft','-lcublas'], # REPLACE FIRST PATH WITH YOUR PATH TO YOUR CUDA LIBRARIES
+        extra_link_args=['-L/usr/local/cuda/lib64',
+                        '-L/usr/lib64/nvidia',
+                        '-lcuda','-lcudart','-lcufft','-lcublas','-lgdal'], # REPLACE FIRST PATH WITH YOUR PATH TO YOUR CUDA LIBRARIES
         language='c++'
     )))

contrib/SConscript

@@ -78,3 +78,6 @@ SConscript(rfi)
 SConscript('PyCuAmpcor/SConscript')
 SConscript('splitSpectrum/SConscript')
 SConscript('alos2proc/SConscript')
+
+if os.path.exists('geo_autoRIFT'):
+    SConscript('geo_autoRIFT/SConscript')

contrib/demUtils/demstitcher/DemStitcher.py

@@ -43,8 +43,7 @@ import os
 import sys
 import math
 import urllib.request, urllib.parse, urllib.error
-import logging
+from isce import logging
-import logging.config
 from iscesys.Component.Component import Component
 
 import xml.etree.ElementTree as ET
@@ -1013,10 +1012,6 @@ class DemStitcher(Component):
         # logger not defined until baseclass is called
 
         if not self.logger:
-            logging.config.fileConfig(
-                os.path.join(os.environ['ISCE_HOME'], 'defaults',
-                'logging', 'logging.conf')
-            )
             self.logger = logging.getLogger('isce.contrib.demUtils.DemStitcher')
 
     url = property(getUrl,setUrl)

contrib/demUtils/demstitcher/DemStitcherV3.py

@@ -39,8 +39,7 @@ from ctypes import cdll
 import os
 import sys
 import urllib.request, urllib.error, urllib.parse
-import logging
+from isce import logging
-import logging.config
 from iscesys.Component.Component import Component
 from contrib.demUtils.DemStitcher import DemStitcher as DS
 #Parameters definitions
@@ -291,7 +290,4 @@ class DemStitcher(DS):
         #it's /srtm/version2_1/SRTM(1,3)
         self._remove = ['.jpg','.xml']
         if not self.logger:
-            logging.config.fileConfig(
-            os.environ['ISCE_HOME'] + '/library/applications/logging.conf'
-            )
             self.logger = logging.getLogger('isce.contrib.demUtils.DemStitcherV3')

contrib/demUtils/swbdstitcher/SWBDStitcher.py

@@ -39,9 +39,8 @@ from ctypes import cdll
 import numpy as np
 import os
 import sys
-import logging
+from isce import logging
 import math
-import logging.config
 import urllib.request, urllib.parse, urllib.error
 from iscesys.Component.Component import Component
 from contrib.demUtils.DemStitcher import DemStitcher
@@ -315,9 +314,6 @@ class SWBDStitcher(DemStitcher):
         #it's /srtm/version2_1/SRTM(1,3)
         self._remove = ['.jpg','.xml']
         if not self.logger:
-            logging.config.fileConfig(
-            os.environ['ISCE_HOME'] + '/library/applications/logging.conf'
-            )
             self.logger = logging.getLogger('isce.contrib.demUtils.SWBDStitcher')
 
         self.parameter_list = self.parameter_list + super(DemStitcher,self).parameter_list

contrib/demUtils/watermask/WaterMask.py

@@ -35,8 +35,7 @@ import sys
 import math
 from html.parser import HTMLParser
 import urllib.request, urllib.parse, urllib.error
-import logging
+from isce import logging
-import logging.config
 from iscesys.Component.Component import Component
 import zipfile
 import os
@@ -979,10 +978,6 @@ class MaskStitcher(Component):
         # logger not defined until baseclass is called
 
         if not self.logger:
-            logging.config.fileConfig(
-                os.path.join(os.environ['ISCE_HOME'], 'defaults',
-                'logging', 'logging.conf')
-            )
             self.logger = logging.getLogger('isce.contrib.demUtils.MaskStitcher')
 
     utl = property(getUrl,setUrl)

contrib/issi/applications/ISSI.py

@@ -32,10 +32,7 @@
 
 import os
 import math
-import logging
+from isce import logging
-import logging.config
-logging.config.fileConfig(os.path.join(os.environ['ISCE_HOME'], 'defaults',
-    'logging', 'logging.conf'))
 
 import isce
 from iscesys.Component.FactoryInit import FactoryInit

contrib/stack/INSTALL.txt

@@ -1,17 +0,0 @@
-To use the TOPS or Stripmap stack processors you need to:
-
-1- Install ISCE as usual
-2- Depending on which stack processor you need to try, add the path of the folder containing the python scripts to your $PATH environment variable as follows:
-   - to use the topsStack for processing a stack of Sentinel-1 tops data add the full path of your "contrib/stack/topsStack" to your $PATH environemnt variable
-   - to use the stripmapStack for processing a stack of Stripmap data, add the full path of your "contrib/stack/stripmapStack" to your $PATH environemnt variableu 
-
-NOTE:
-
-   The stack processors do not show up in the install directory of your isce software. They can be found in the isce source directory. 
-
-Important Note:
-
-   There might be conflicts between topsStack and stripmapStack scripts (due to comman names of different scripts). Therefore users MUST only have the path of one stack processor in their $PATH environment at a time, to avoid conflicts between the two stack processors.
-
-
-

contrib/stack/README.md

@@ -0,0 +1,34 @@
+## Stack Processors
+
+Read the document for each stack processor for details.
+
++ [stripmapStack](./stripmapStack/README.md)
++ [topsStack](./topsStack/README.md)
+
+### Installation
+
+To use the TOPS or Stripmap stack processors you need to:
+
+1. Install ISCE as usual
+
+2. Depending on which stack processor you need to try, add the path of the folder containing the python scripts to your `$PATH` environment variable as follows:
+   - add the full path of your **contrib/stack/topsStack** to `$PATH` to use the topsStack for processing a stack of Sentinel-1 TOPS data
+   - add the full path of your **contrib/stack/stripmapStack** to `$PATH` to use the stripmapStack for processing a stack of StripMap data
+
+Note: The stack processors do not show up in the install directory of your isce software. They can be found in the isce source directory. 
+
+#### Important Note: ####
+
+There might be conflicts between topsStack and stripmapStack scripts (due to comman names of different scripts). Therefore users **MUST only** have the path of **one stack processor in their $PATH environment at a time**, to avoid conflicts between the two stack processors.
+
+### References
+
+Users who use the stack processors may refer to the following literatures:
+
+For StripMap stack processor and ionospheric phase estimation:
+
++ H. Fattahi, M. Simons, and P. Agram, "InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique", IEEE Trans. Geosci. Remote Sens., vol. 55, no. 10, 5984-5996, 2017. (https://ieeexplore.ieee.org/abstract/document/7987747/)
+
+For TOPS stack processing:
+
++ H. Fattahi, P. Agram, and M. Simons, “A network-based enhanced spectral diversity approach for TOPS time-series analysis,” IEEE Trans. Geosci. Remote Sens., vol. 55, no. 2, pp. 777–786, Feb. 2017. (https://ieeexplore.ieee.org/abstract/document/7637021/)

contrib/stack/README_stripmapStack.txt

@@ -1,64 +0,0 @@
-
-The detailed algorithms for stack processing of stripmap data can be found here:
-
-H. Fattahi, M. Simons, and P. Agram, "InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique", IEEE Trans. Geosci. Remote Sens., vol. 55, no. 10, 5984-5996, 2017. (https://ieeexplore.ieee.org/abstract/document/7987747/)
-
-
------------------------------------
-
-Notes on stripmap stack processor:
-
-Here are some notes to get started with processing stacks of stripmap data with ISCE. 
-
-
-1- create a folder somewhere for your project
-
-mkdir MauleT111
-cd MauleT111
-
-2- create a DEM:
-
-dem.py -a stitch -b -37 -31 -72 -69 -r -s 1 -c
-
-3- Keep only ".dem.wgs84", ".dem.wgs84.vrt" and ".dem.wgs84.xml" and remove unnecessary files
-
-4- fix the path of the file in the xml file of the DEM by using this command:
-
-fixImageXml.py -f -i demLat_S37_S31_Lon_W072_W069.dem.wgs84
-
-5- create a folder to download the ALOS-1 data from ASF:
-
-mkdir download 
-cd download
-
-6- Download the data that that you want to process to the downlowd directory.
-
-7- once all data have been downloaded, we need to unzip them and move them to different folders and getting ready for unpacking and then SLC generation. 
-This can be done by running the following command in a directory above "download":
-
-prepRawALOS.py -i download/ -o SLC
-
-This command generates an empty SLC folder and a run file called: "run_unPackALOS". 
-You could also run prepRawSensor.py which aims to recognize the sensor data automatically followed by running the sensor specific preparation script. For now we include support for ALOS and CSK raw data, but it is trivial to expand and include other sensors as unpacking routines are already included in the distribution.
-
-prepRawSensor.py -i download/ -o SLC
-
-8- execute the commands inside run_unPackALOS file. If you have a cluster that you can submit jobs, you can submit each line of command to a processor. The commands are independent and can be run in parallel.
-
-9- After successfully running the previous step, you should see acquisition dates in the SLC folder and the ".raw" files for each acquisition
-
-Note: For ALOS-1, If there is an acquisition that does not include .raw file, this is most likely due to PRF change between frames and can not be currently handled by ISCE. You have to ignore those.
-
-10- run stackStripmap.py which will generate many config and run files that need to be executed. Here is an example:
-
-stackStripMap.py -s SLC/ -d demLat_S37_S31_Lon_W072_W069.dem.wgs84 -t 250 -b 1000 -a 14 -r 4 -u snaphu
-
-This will produce:
-a) baseline folder, which contains baseline information
-b) pairs.png which is a baseline-time plot of the network of interferograms
-c) configs: which contains the configuration parameter to run different InSAR processing steps
-d) run_files: a folder that includes several run and job files that needs to be run in order
-
-11- execute the commands in run files (run_1, run_2, etc) in the run_files folder
-
-

contrib/stack/README_topsStack.txt

@@ -1,117 +0,0 @@
-The detailed algorithm for stack processing of TOPS data can be find here:
-
-H. Fattahi, P. Agram, and M. Simons, “A network-based enhanced spectral diversity approach for TOPS time-series analysis,” IEEE Trans. Geosci. Remote Sens., vol. 55, no. 2, pp. 777–786, Feb. 2017. (https://ieeexplore.ieee.org/abstract/document/7637021/)
-
-<<<<<< Sentinel-1 TOPS stack processor >>>>>>
-
-
-To use the sentinel stack processor, make sure to add the path of your "contrib/stack/topsStack" folder to your $PATH environment varibale. 
-
-
-The scripts provides support for Sentinel-1 TOPS stack processing. Currently supported workflows include a coregistered stack of SLC, interferograms, offsets, and coherence. 
-
-stackSentinel.py generates all configuration and run files required to be executed on a stack of Sentinel-1 TOPS data. When stackSentinel.py is executed for a given workflow (-W option) a “configs” and “run_files” folder is generated. No processing is performed at this stage. Within the “run_files” folder different run_#_description files are contained which are to be executed as shell scripts in the run number order. Each of these run scripts call specific configure files contained in the “configs” folder which call ISCE in a modular fashion. The configure and run files will change depending on the selected workflow. To make run_# files executable, change the file permission accordingly (e.g., chmod +x run_1_unpack_slc).
-
-To see workflow examples, type “stackSentinel.py -H”
-To get an overview of all the configurable parameters, type “stackSentinel.py -h”
-
-Required parameters of stackSentinel.py include:
--s SLC_DIRNAME	A folder with downloaded Sentinel-1 SLC’s. 
--o ORBIT_DIRNAME	A folder containing the Sentinel-1 orbits.
-Missing orbit files will be downloaded automatically
--a AUX_DIRNAME 	A folder containing the Sentinel-1 Auxiliary files
--d DEM 		A DEM (Digital Elevation Model) referenced to wgs84
-
-
-In the following, different workflow examples are provided. Note that stackSentinel.py only generates the run and configure files. To perform the actual processing, the user will need to execute each run file in their numbered order.
-
-In all workflows, coregistration (-C option) can be done using only geometry (set option = geometry) or with geometry plus refined azimuth offsets through NESD (set option = NESD) approach, the latter being the default. For the NESD coregistrstion the user can control the ESD coherence threshold (-e option) and the number of overlap interferograms (-O) to be used in NESD estimation.
-
------------------------------- Example 1: Coregistered stack of SLC ----------------------------
-Generate the run and configure files needed to generate a coregistered stack of SLCs. 
-In this example, a pre-defined bounding box is specified. Note, if the bounding box is not provided it is set by default to the common SLC area among all SLCs. We recommend that user always set the processing bounding box. Since ESA does not have a fixed frame definition, we suggest to download data for a larger bounding box compared to the actual bounding box used in stackSentinel.py. This way user can ensure to have required data to cover the region of interest. Here is an example command to create configuration files for a stack of SLCs:
-
-stackSentinel.py -s ../SLC/ -d ../DEM/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -a ../../AuxDir/ -o ../../Orbits -b '19 20 -99.5 -98.5' -W slc
-by running the command above, the configs and run_files folders are created. User needs to execute each run file in order. The order is specified by the index number of the run file name. For the example above, the run_files folder includes the following files:
--	run_1_unpack_slc_topo_master
--	run_2_average_baseline
--	run_3_extract_burst_overlaps
--	run_4_overlap_geo2rdr_resample
--	run_5_pairs_misreg
--	run_6_timeseries_misreg
--	run_7_geo2rdr_resample
--	run_8_extract_stack_valid_region
--	run_9_merge
--	run_10_grid_baseline
-
-The generated run files are self descriptive. Below is a short explanation on what each run_file does:
-
-***run_1_unpack_slc_topo_master:***
-Includes commands to unpack Sentinel-1 TOPS SLCs using ISCE readers. For older SLCs which need antenna elevation pattern correction, the file is extracted and written to disk. For newer version of SLCs which don’t need the elevation antenna pattern correction, only a gdal virtual “vrt” file (and isce xml file) is generated. The “.vrt” file points to the Sentinel SLC file and reads them whenever required during the processing. If a user wants to write the “.vrt” SLC file to disk, it can be done easily using gdal_translate (e.g. gdal_translate –of ENVI File.vrt File.slc). 
-The “run_1_unpack_slc_topo_master” also includes a command that refers to the config file of the stack master, which includes configuration for running topo for the stack master. Note that in the pair-wise processing strategy one should run topo (mapping from range-Doppler to geo coordinate) for all pairs. However, with stackSentinel, topo needs to be run only one time for the master in the stack. 
-
-***run_2_average_baseline: ***
-Computes average baseline for the stack. These baselines are not used for processing anywhere. They are only an approximation and can be used for plotting purposes. A more precise baseline grid is estimated later in run_10.
-
-***run_3_extract_burst_overlaps: ***
-Burst overlaps are extracted for estimating azimuth misregistration using NESD technique. If coregistration method is chosen to be “geometry”, then this run file won’t exist and the overlaps are not extracted.
-
-***run_4_overlap_geo2rdr_resample: ***
-Running geo2rdr to estimate geometrical offsets between slave burst overlaps and the stack master burst overlaps. The slave burst overlaps are then resampled to the stack master burst overlaps. 
-
-***run_5_pairs_misreg: ***
-Using the coregistered stack burst overlaps generated from the previous step, differential overlap interferograms are generated and are used for estimating azimuth misregistration using Enhanced Spectral Diversity (ESD) technique. 
-
-***run_6_timeseries_misreg: ***
-A time-series of azimuth and range misregistration is estimated with respect to the stack master. The time-series is a least squares esatimation from the pair misregistration from the previous step.
-
-***run_7_geo2rdr_resample: ***
-Using orbit and DEM, geometrical offsets among all slave SLCs and the stack master is computed. The goometrical offsets, together with the misregistration time-series (from previous step) are used for precise coregistration of each burst SLC. 
-
-***run_8_extract_stack_valid_region: ***
-The valid region between burst SLCs at the overlap area of the bursts slightly changes for different acquisitions. Therefore we need to keep track of these overlaps which will be used during merging bursts. Without these knowledge, lines of invalid data may appear in the merged products at the burst overlaps.
-
-***run_9_merge: ***
-Merges all bursts for the master and coregistered SLCs. The geometry files are also merged including longitude, latitude, shadow and layer mask, line-of-sight files, etc. .
-
-***run_10_grid_baseline: ***
-A coarse grid of baselines between each slave SLC and the stack master is generated. This is not used in any computation.
-
-
--------- Example 2: Coregistered stack of SLC with modified parameters -----------
-In the following example, the same stack generation is requested but where the threshold of the default coregistration approach (NESD) is relaxed from its default 0.85 value 0.7.
-
-stackSentinel.py -s ../SLC/ -d ../DEM/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -a ../../AuxDir/ -o ../../Orbits -b '19 20 -99.5 -98.5' -W slc -e 0.7
-
-When running all the run files, the final products are located in the merge folder which has subdirectories “geom_master”, “baselines” and “SLC”. The “geom_master” folder contains geometry products such as longitude, latitude, height, local incidence angle, look angle, heading, and shadowing/layover mask files. The “baselines” folder contains sparse grids of the perpendicular baseline for each acquisition, while the “SLC” folder contains the coregistered SLCs
-
-
------------------------------- Example 3: Stack of interferograms  ------------------------------
-Generate the run and configure files needed to generate a stack of interferograms.
-In this example, a stack of interferograms is requested for which up to 2 nearest neighbor connections are included.
-
-stackSentinel.py -s ../SLC/ -d ../../MexicoCity/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -b '19 20 -99.5 -98.5' -a ../../AuxDir/ -o ../../Orbits -c 2
-
-In the following example, all possible interferograms are being generated and in which the coregistration approach is set to use geometry and not the default NESD. 
-
-stackSentinel.py -s ../SLC/ -d ../../MexicoCity/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -b '19 20 -99.5 -98.5' -a ../../AuxDir/ -o ../../Orbits -C geometry -c all
-
-When executing all the run files, a coregistered stack of slcs are produced, the burst interferograms are generated and then merged. Merged interferograms are multilooked, filtered and unwrapped. Geocoding is not applied. If users need to geocode any product, they can use the geocodeGdal.py script.
-
-
--------------------- Example 4:  Correlation stack example ----------------------------
-Generate the run and configure files needed to generate a stack of coherence.
-In this example, a correlation stack is requested considering all possible coherence pairs and where the coregistration approach is done using geometry only.
-
-stackSentinel.py -s ../SLC/ -d ../../MexicoCity/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -b '19 20 -99.5 -98.5' -a ../../AuxDir/ -o ../../Orbits -C geometry -c all -W correlation
-
-This workflow is basically similar to the previous one. The difference is that the interferograms are not unwrapped.
-
-
------------------------------------ DEM download example -----------------------------------
-Download of DEM (need to use wgs84 version) using the ISCE DEM download script.
-dem.py -a stitch -b 18 20 -100 -97 -r -s 1 –c
-
-Updating DEM’s wgs84 xml to include full path to the DEM
-fixImageXml.py -f -i demLat_N18_N20_Lon_W100_W097.dem.wgs84
-

contrib/stack/References.txt

@@ -1,11 +0,0 @@
-Users who use the stack processors may refer to the following literatures:
-
-for stripmap stack processor and ionospheric phase estimation:
-
-H. Fattahi, M. Simons, and P. Agram, "InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique", IEEE Trans. Geosci. Remote Sens., vol. 55, no. 10, 5984-5996, 2017. (https://ieeexplore.ieee.org/abstract/document/7987747/)
-
-For TOPS stack processing:
-
-H. Fattahi, P. Agram, and M. Simons, “A network-based enhanced spectral diversity approach for TOPS time-series analysis,” IEEE Trans. Geosci. Remote Sens., vol. 55, no. 2, pp. 777–786, Feb. 2017. (https://ieeexplore.ieee.org/abstract/document/7637021/)
-
-

contrib/stack/stripmapStack/README.md

@@ -0,0 +1,85 @@
+## StripMap stack processor
+
+The detailed algorithms and workflow for stack processing of stripmap SAR data can be found here:
+
++ Fattahi, H., M. Simons, and P. Agram (2017), InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique, IEEE Transactions on Geoscience and Remote Sensing, 55(10), 5984-5996, doi:[10.1109/TGRS.2017.2718566](https://ieeexplore.ieee.org/abstract/document/7987747/).
+
+-----------------------------------
+
+To use the stripmap stack processor, make sure to add the path of your `contrib/stack/stripmapStack` folder to your `$PATH` environment varibale. 
+
+Currently supported workflows include a coregistered stack of SLC, interferograms, ionospheric delays. 
+
+Here are some notes to get started with processing stacks of stripmap data with ISCE. 
+
+#### 1. Create your project folder somewhere   
+
+```
+mkdir MauleAlosDT111
+cd MauleAlosDT111
+```
+
+#### 2. Prepare DEM    
+a) create a folder for DEM;    
+b) create a DEM using dem.py with SNWE of your study area in integer;   
+d) Keep only ".dem.wgs84", ".dem.wgs84.vrt" and ".dem.wgs84.xml" and remove unnecessary files;    
+d) fix the path of the file in the xml file of the DEM by using fixImageXml.py.   
+
+```
+mkdir DEM; cd DEM
+dem.py -a stitch -b -37 -31 -72 -69 -r -s 1 -c
+rm demLat*.dem demLat*.dem.xml demLat*.dem.vrt
+fixImageXml.py -f -i demLat*.dem.wgs84
+cd ..
+```
+
+#### 3. Download data    
+
+##### 3.1 create a folder to download SAR data (i.e. ALOS-1 data from ASF)   
+
+```
+mkdir download 
+cd download
+```
+
+##### 3.2 Download the data that that you want to process to the "downlowd" directory   
+
+#### 4. Prepare SAR data    
+    
+Once all data have been downloaded, we need to unzip them and move them to different folders and getting ready for unpacking and then SLC generation. This can be done by running the following command in a directory above "download":
+      
+```
+prepRawALOS.py -i download/ -o SLC
+```
+
+This command generates an empty SLC folder and a run file called: "run_unPackALOS".    
+
+You could also run prepRawSensor.py which aims to recognize the sensor data automatically followed by running the sensor specific preparation script. For now we include support for ALOS and CSK raw data, but it is trivial to expand and include other sensors as unpacking routines are already included in the distribution.
+
+```
+prepRawSensor.py -i download/ -o SLC
+```
+
+#### 5. Execute the commands in "run_unPackALOS" file   
+
+If you have a cluster that you can submit jobs, you can submit each line of command to a processor. The commands are independent and can be run in parallel.    
+
+After successfully running the previous step, you should see acquisition dates in the SLC folder and the ".raw" files for each acquisition.    
+
+Note: For ALOS-1, If there is an acquisition that does not include .raw file, this is most likely due to PRF change between frames and can not be currently handled by ISCE. You have to ignore those.    
+
+#### 6. Run "stackStripmap.py"   
+
+This will generate many config and run files that need to be executed. Here is an example:    
+
+```
+stackStripMap.py -s SLC/ -d DEM/demLat*.dem.wgs84 -t 250 -b 1000 -a 14 -r 4 -u snaphu
+```
+
+This will produce:    
+a) baseline folder, which contains baseline information   
+b) pairs.png which is a baseline-time plot of the network of interferograms      
+c) configs: which contains the configuration parameter to run different InSAR processing steps   
+d) run_files: a folder that includes several run and job files that needs to be run in order    
+
+#### 7. Execute the commands in run files (run_1*, run_2*, etc) in the "run_files" folder   

contrib/stack/stripmapStack/README.txt

@@ -1,64 +0,0 @@
-
-The detailed algorithms for stack processing of stripmap data can be found here:
-
-H. Fattahi, M. Simons, and P. Agram, "InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique", IEEE Trans. Geosci. Remote Sens., vol. 55, no. 10, 5984-5996, 2017. (https://ieeexplore.ieee.org/abstract/document/7987747/)
-
-
------------------------------------
-
-Notes on stripmap stack processor:
-
-Here are some notes to get started with processing stacks of stripmap data with ISCE. 
-
-
-1- create a folder somewhere for your project
-
-mkdir MauleT111
-cd MauleT111
-
-2- create a DEM:
-
-dem.py -a stitch -b -37 -31 -72 -69 -r -s 1 -c
-
-3- Keep only ".dem.wgs84", ".dem.wgs84.vrt" and ".dem.wgs84.xml" and remove unnecessary files
-
-4- fix the path of the file in the xml file of the DEM by using this command:
-
-fixImageXml.py -f -i demLat_S37_S31_Lon_W072_W069.dem.wgs84
-
-5- create a folder to download the ALOS-1 data from ASF:
-
-mkdir download 
-cd download
-
-6- Download the data that that you want to process to the downlowd directory.
-
-7- once all data have been downloaded, we need to unzip them and move them to different folders and getting ready for unpacking and then SLC generation. 
-This can be done by running the following command in a directory above "download":
-
-prepRawALOS.py -i download/ -o SLC
-
-This command generates an empty SLC folder and a run file called: "run_unPackALOS". 
-You could also run prepRawSensor.py which aims to recognize the sensor data automatically followed by running the sensor specific preparation script. For now we include support for ALOS and CSK raw data, but it is trivial to expand and include other sensors as unpacking routines are already included in the distribution.
-
-prepRawSensor.py -i download/ -o SLC
-
-8- execute the commands inside run_unPackALOS file. If you have a cluster that you can submit jobs, you can submit each line of command to a processor. The commands are independent and can be run in parallel.
-
-9- After successfully running the previous step, you should see acquisition dates in the SLC folder and the ".raw" files for each acquisition
-
-Note: For ALOS-1, If there is an acquisition that does not include .raw file, this is most likely due to PRF change between frames and can not be currently handled by ISCE. You have to ignore those.
-
-10- run stackStripmap.py which will generate many config and run files that need to be executed. Here is an example:
-
-stackStripMap.py -s SLC/ -d demLat_S37_S31_Lon_W072_W069.dem.wgs84 -t 250 -b 1000 -a 14 -r 4 -u snaphu
-
-This will produce:
-a) baseline folder, which contains baseline information
-b) pairs.png which is a baseline-time plot of the network of interferograms
-c) configs: which contains the configuration parameter to run different InSAR processing steps
-d) run_files: a folder that includes several run and job files that needs to be run in order
-
-11- execute the commands in run files (run_1, run_2, etc) in the run_files folder
-
-

contrib/stack/stripmapStack/Stack.py

@@ -65,6 +65,8 @@ class config(object):
         self.f.write('master : ' + self.slcDir +'\n')
         self.f.write('dem : ' + self.dem +'\n')
         self.f.write('output : ' + self.geometryDir +'\n')
+        self.f.write('alks : ' + self.alks +'\n')
+        self.f.write('rlks : ' + self.rlks +'\n')
         if self.nativeDoppler:
             self.f.write('native : True\n')
         if self.useGPU:
@@ -73,6 +75,17 @@ class config(object):
             self.f.write('useGPU : False\n')
         self.f.write('##########################'+'\n')
 
+    def createWaterMask(self, function):
+
+        self.f.write('##########################'+'\n')
+        self.f.write(function+'\n')
+        self.f.write('createWaterMask : '+'\n')
+        self.f.write('dem_file : ' + self.dem +'\n')
+        self.f.write('lat_file : ' + self.latFile +'\n')
+        self.f.write('lon_file : ' + self.lonFile +'\n')
+        self.f.write('output : ' + self.waterMaskFile + '\n')
+        self.f.write('##########################'+'\n')
+
     def geo2rdr(self, function):
 
         self.f.write('##########################'+'\n')
@@ -197,6 +210,8 @@ class config(object):
         self.f.write('nomcf : ' + self.noMCF + '\n')
         self.f.write('master : ' + self.master + '\n')
         self.f.write('defomax : ' + self.defoMax + '\n')
+        self.f.write('alks : ' + self.alks + '\n')
+        self.f.write('rlks : ' + self.rlks + '\n')
         self.f.write('method : ' + self.unwMethod + '\n')
         self.f.write('##########################'+'\n')
 
@@ -307,8 +322,7 @@ class run(object):
              self.runf.write(self.text_cmd+'stripmapWrapper.py -c '+ configName+'\n')
  
     def master_focus_split_geometry(self, stackMaster, config_prefix, split=False, focus=True, native=True):
-  	########
+        """focusing master and producing geometry files"""
-  	# focusing master and producing geometry files
         configName = os.path.join(self.configDir, config_prefix + stackMaster)
         configObj = config(configName)
         configObj.configure(self)
@@ -329,6 +343,14 @@ class run(object):
             configObj.outDir = configObj.slcDir
             configObj.shelve = os.path.join(configObj.slcDir, 'data')
             configObj.splitRangeSpectrum('[Function-{0}]'.format(counter))
+            counter += 1
+
+        # generate water mask in radar coordinates
+        configObj.latFile = os.path.join(self.workDir, 'geom_master/lat.rdr')
+        configObj.lonFile = os.path.join(self.workDir, 'geom_master/lon.rdr')
+        configObj.waterMaskFile = os.path.join(self.workDir, 'geom_master/waterMask.rdr')
+        configObj.createWaterMask('[Function-{0}]'.format(counter))
+        counter += 1
 
         configObj.finalize()
         del configObj

contrib/stack/stripmapStack/createWaterMask.py

@@ -2,30 +2,45 @@
 
 #Author: Heresh Fattahi
 
-import isce
+import os
-import isceobj
-from contrib.demUtils.SWBDStitcher import SWBDStitcher
-from iscesys.DataManager import createManager
 import argparse
 import configparser
-from numpy import round
+import numpy as np
+import isce
+import isceobj
+from iscesys.DataManager import createManager
+from contrib.demUtils.SWBDStitcher import SWBDStitcher
+
+
+EXAMPLE = """example:
+  createWaterMask.py -b 31 33 130 132
+  createWaterMask.py -b 31 33 130 132 -l lat.rdr -L lon.rdr -o waterMask.rdr
+  createWaterMask.py -d ../DEM/demLat_N31_N33_Lon_E130_E132.dem.wgs84 -l lat.rdr -L lon.rdr -o waterMask.rdr
+"""
 
 def createParser():
     '''
     Create command line parser.
     '''
     
-    parser = argparse.ArgumentParser( description='extracts the overlap geometry between master bursts')
+    parser = argparse.ArgumentParser(description='Create water body mask in geo and/or radar coordinates',
-   # parser.add_argument('-b', '--bbox', dest='bbox', type=str, default=None, 
+                                     formatter_class=argparse.RawTextHelpFormatter,
-    #                  help='Lat/Lon Bounding SNWE')
+                                     epilog=EXAMPLE)
-    parser.add_argument('-b', '--bbox', type = int, default = None, nargs = '+', dest = 'bbox', help = 'Defines the spatial region in the format south north west east.\
+    parser.add_argument('-b', '--bbox', dest='bbox', type=int, default=None, nargs=4, metavar=('S','N','W','E'), 
-                        The values should be integers from (-90,90) for latitudes and (0,360) or (-180,180) for longitudes.')
+                      help = 'Defines the spatial region in the format south north west east.\n'
+                             'The values should be integers from (-90,90) for latitudes '
+                             'and (0,360) or (-180,180) for longitudes.')
+    parser.add_argument('-d','--dem_file', dest='demName', type=str, default=None,
+                      help='DEM file in geo coordinates, i.e. demLat*.dem.wgs84.')
     parser.add_argument('-l', '--lat_file', dest='latName', type=str, default=None, 
                       help='pixel by pixel lat file in radar coordinate')
     parser.add_argument('-L', '--lon_file', dest='lonName', type=str, default=None, 
                       help='pixel by pixel lat file in radar coordinate')
+    parser.add_argument('-o', '--output', dest='outfile', type=str,
+                      help='output filename of water mask in radar coordinates')
     return parser
 
+
 def cmdLineParse(iargs = None):
     '''
     Command line parser.
@@ -33,37 +48,69 @@ def cmdLineParse(iargs = None):
 
     parser = createParser()
     inps = parser.parse_args(args=iargs)
-    #inps.bbox = [int(round(val)) for val in inps.bbox.split()]
+
+    if not inps.bbox and not inps.demName:
+        parser.print_usage()
+        raise SystemExit('ERROR: no --bbox/--dem_file input, at least one is required.')
+
+    if not inps.outfile and (inps.latName and inps.lonName):
+        inps.outfile = os.path.join(os.path.dirname(inps.latName), 'waterMask.rdr')
+
     return inps
 
 
-def download_waterMask(inps):
+def dem2bbox(dem_file):
+    """Grab bbox from DEM file in geo coordinates"""
+    demImage = isceobj.createDemImage()
+    demImage.load(dem_file + '.xml')
+    demImage.setAccessMode('read')
+    N = demImage.getFirstLatitude()
+    W = demImage.getFirstLongitude()
+    S = N + demImage.getDeltaLatitude() * demImage.getLength()
+    E = W + demImage.getDeltaLongitude() * demImage.getWidth()
+    bbox = [np.floor(S).astype(int), np.ceil(N).astype(int),
+            np.floor(W).astype(int), np.ceil(E).astype(int)]
+    return bbox
+
+
+def download_waterMask(bbox, dem_file):
+    out_dir = os.getcwd()
+    # update out_dir and/or bbox if dem_file is input
+    if dem_file:
+        out_dir = os.path.dirname(dem_file)
+        if not bbox:
+            bbox = dem2bbox(dem_file)
 
     sw = createManager('wbd')
     sw.configure()
-    inps.waterBodyGeo = sw.defaultName(inps.bbox)
+    #inps.waterBodyGeo = sw.defaultName(inps.bbox)
+    sw.outputFile = os.path.join(out_dir, sw.defaultName(bbox))
     sw._noFilling = False
-    #sw._fillingValue = -1.0
+    sw._fillingValue = -1.0    #fill pixels without DEM data with value of -1, same as water body
-    sw._fillingValue = 0.0
+    #sw._fillingValue = 0.0
-    sw.stitch(inps.bbox[0:2],inps.bbox[2:])
+    sw.stitch(bbox[0:2], bbox[2:])
+    return sw.outputFile
 
-    return inps
 
-def geo2radar(inps):
+def geo2radar(geo_file, rdr_file, lat_file, lon_file):
-    inps.waterBodyRadar = inps.waterBodyGeo + '.rdr'
+    #inps.waterBodyRadar = inps.waterBodyGeo + '.rdr'
     sw = SWBDStitcher()
-    sw.toRadar(inps.waterBodyGeo, inps.latName, inps.lonName, inps.waterBodyRadar)
+    sw.toRadar(geo_file, lat_file, lon_file, rdr_file)
+    return rdr_file
 
 #looks.py -i watermask.msk -r 4 -a 14 -o 'waterMask.14alks_4rlks.msk'
 
 #imageMath.py -e='a*b' --a=filt_20100911_20101027.int --b=watermask.14alks_4rlks.msk -o filt_20100911_20101027_masked.int -t cfloat -s BIL
 
+
 def main(iargs=None):
 
     inps = cmdLineParse(iargs)
-  inps = download_waterMask(inps)    
+    geo_file = download_waterMask(inps.bbox, inps.demName)    
     if inps.latName and inps.lonName:
-     inps = geo2radar(inps)
+        geo2radar(geo_file, inps.outfile, inps.latName, inps.lonName)
+    return
+
 
 if __name__ == '__main__' :
   ''' 

contrib/stack/stripmapStack/stackStripMap.py

@@ -20,7 +20,7 @@ defoMax = '2'
 maxNodes = 72
 
 def createParser():
-    parser = argparse.ArgumentParser( description='Preparing the directory structure and config files for stack processing of Sentinel data')
+    parser = argparse.ArgumentParser( description='Preparing the directory structure and config files for stack processing of StripMap data')
 
     parser.add_argument('-s', '--slc_directory', dest='slcDir', type=str, required=True,
             help='Directory with all stripmap SLCs')
@@ -31,7 +31,7 @@ def createParser():
             help='Working directory ')
 
     parser.add_argument('-d', '--dem', dest='dem', type=str, required=True,
-            help='Directory with the DEM (.xml and .vrt files)')
+            help='DEM file (with .xml and .vrt files)')
 
     parser.add_argument('-m', '--master_date', dest='masterDate', type=str, default=None,
             help='Directory with master acquisition')
@@ -43,47 +43,54 @@ def createParser():
             help='Baseline threshold (max bperp in meters)')
 
     parser.add_argument('-a', '--azimuth_looks', dest='alks', type=str, default='10',
-            help='Number of looks in azimuth (automaticly computed as AspectR*looks when "S" or "sensor" is defined to give approximately square multi-look pixels)')
+            help='Number of looks in azimuth (automaticly computed as AspectR*looks when '
+                 '"S" or "sensor" is defined to give approximately square multi-look pixels)')
     parser.add_argument('-r', '--range_looks', dest='rlks', type=str, default='10',
             help='Number of looks in range')
     parser.add_argument('-S', '--sensor', dest='sensor', type=str, required=False,
             help='SAR sensor used to define square multi-look pixels')
-    parser.add_argument('-L', '--low_band_frequency', dest='fL', type=str, default=None,
+
-            help='low band frequency')
+    parser.add_argument('-u', '--unw_method', dest='unwMethod', type=str, default='snaphu', 
-    parser.add_argument('-H', '--high_band_frequency', dest='fH', type=str, default=None,
+            help='unwrapping method (icu, snaphu, or snaphu2stage)')
-            help='high band frequency')
-    parser.add_argument('-B', '--subband_bandwidth ', dest='bandWidth', type=str, default=None,
-            help='sub-band band width')
-    parser.add_argument('-u', '--unw_method', dest='unwMethod', type=str, default='snaphu'
-       , help='unwrapping method (icu, snaphu, or snaphu2stage)')
 
     parser.add_argument('-f','--filter_strength', dest='filtStrength', type=str, default=filtStrength,
             help='strength of Goldstein filter applied to the wrapped phase before spatial coherence estimation.'
                  ' Default: {}'.format(filtStrength))
 
-    parser.add_argument('--filter_sigma_x', dest='filterSigmaX', type=str, default='100'
+    iono = parser.add_argument_group('Ionosphere', 'Configurationas for ionospheric correction')
-       , help='filter sigma for gaussian filtering the dispersive and nonDispersive phase')
+    iono.add_argument('-L', '--low_band_frequency', dest='fL', type=str, default=None,
+            help='low band frequency')
+    iono.add_argument('-H', '--high_band_frequency', dest='fH', type=str, default=None,
+            help='high band frequency')
+    iono.add_argument('-B', '--subband_bandwidth ', dest='bandWidth', type=str, default=None,
+            help='sub-band band width')
 
-    parser.add_argument('--filter_sigma_y', dest='filterSigmaY', type=str, default='100.0',
+    iono.add_argument('--filter_sigma_x', dest='filterSigmaX', type=str, default='100', 
+            help='filter sigma for gaussian filtering the dispersive and nonDispersive phase')
+
+    iono.add_argument('--filter_sigma_y', dest='filterSigmaY', type=str, default='100.0',
             help='sigma of the gaussian filter in Y direction, default=100')
 
-    parser.add_argument('--filter_size_x', dest='filterSizeX', type=str, default='800.0',
+    iono.add_argument('--filter_size_x', dest='filterSizeX', type=str, default='800.0',
             help='size of the gaussian kernel in X direction, default = 800')
 
-    parser.add_argument('--filter_size_y', dest='filterSizeY', type=str, default='800.0',
+    iono.add_argument('--filter_size_y', dest='filterSizeY', type=str, default='800.0',
             help='size of the gaussian kernel in Y direction, default=800')
 
-    parser.add_argument('--filter_kernel_rotation', dest='filterKernelRotation', type=str, default='0.0',
+    iono.add_argument('--filter_kernel_rotation', dest='filterKernelRotation', type=str, default='0.0',
             help='rotation angle of the filter kernel in degrees (default = 0.0)')
 
-    parser.add_argument('-W', '--workflow', dest='workflow', type=str, default='slc'
+    parser.add_argument('-W', '--workflow', dest='workflow', type=str, default='slc', 
-       , help='The InSAR processing workflow : (slc, interferogram, ionosphere)')
+            help='The InSAR processing workflow : (slc, interferogram, ionosphere)')
 
-    parser.add_argument('-z', '--zero', dest='zerodop', action='store_true', default=False, help='Use zero doppler geometry for processing - Default : No')
+    parser.add_argument('-z', '--zero', dest='zerodop', action='store_true', default=False, 
-    parser.add_argument('--nofocus', dest='nofocus', action='store_true', default=False, help='If input data is already focused to SLCs - Default : do focus')
+            help='Use zero doppler geometry for processing - Default : No')
-    parser.add_argument('-c', '--text_cmd', dest='text_cmd', type=str, default=''
+    parser.add_argument('--nofocus', dest='nofocus', action='store_true', default=False, 
-       , help='text command to be added to the beginning of each line of the run files. Example : source ~/.bash_profile;')
+            help='If input data is already focused to SLCs - Default : do focus')
-    parser.add_argument('-useGPU', '--useGPU', dest='useGPU',action='store_true', default=False, help='Allow App to use GPU when available')
+    parser.add_argument('-c', '--text_cmd', dest='text_cmd', type=str, default='', 
+            help='text command to be added to the beginning of each line of the run files. Example : source ~/.bash_profile;')
+    parser.add_argument('-useGPU', '--useGPU', dest='useGPU',action='store_true', default=False,
+             help='Allow App to use GPU when available')
 
     parser.add_argument('--summary', dest='summary', action='store_true', default=False, help='Show summary only')
     return parser

contrib/stack/stripmapStack/topo.py

@@ -1,13 +1,16 @@
 #!/usr/bin/env python3
+
+import os
 import argparse
+import shelve
+import datetime
+import shutil
+import numpy as np
 import isce
 import isceobj
-import numpy as np
-import shelve
-import os
-import datetime 
 from isceobj.Constants import SPEED_OF_LIGHT
 from isceobj.Util.Poly2D import Poly2D
+from mroipac.looks.Looks import Looks
 
 def createParser():
     '''
@@ -328,6 +331,7 @@ def runTopoCPU(info, demImage, dop=None,
     topo.topo()
     return
 
+
 def runSimamp(outdir, hname='z.rdr'):
     from iscesys.StdOEL.StdOELPy import create_writer
 
@@ -354,6 +358,86 @@ def runSimamp(outdir, hname='z.rdr'):
     simImage.renderHdr()
     hgtImage.finalizeImage()
     simImage.finalizeImage()
+    return
+
+
+def runMultilook(in_dir, out_dir, alks, rlks):
+    print('generate multilooked geometry files with alks={} and rlks={}'.format(alks, rlks))
+    from iscesys.Parsers.FileParserFactory import createFileParser
+    FP = createFileParser('xml')
+
+    if not os.path.isdir(out_dir):
+        os.makedirs(out_dir)
+        print('create directory: {}'.format(out_dir))
+
+    for fbase in ['hgt', 'incLocal', 'lat', 'lon', 'los', 'shadowMask', 'waterMask']:
+        fname = '{}.rdr'.format(fbase)
+        in_file = os.path.join(in_dir, fname)
+        out_file = os.path.join(out_dir, fname)
+
+        if os.path.isfile(in_file):
+            xmlProp = FP.parse(in_file+'.xml')[0]
+            if('image_type' in xmlProp and xmlProp['image_type'] == 'dem'):
+                inImage = isceobj.createDemImage()
+            else:
+                inImage = isceobj.createImage()
+
+            inImage.load(in_file+'.xml')
+            inImage.filename = in_file
+
+            lkObj = Looks()
+            lkObj.setDownLooks(alks)
+            lkObj.setAcrossLooks(rlks)
+            lkObj.setInputImage(inImage)
+            lkObj.setOutputFilename(out_file)
+            lkObj.looks()
+
+            # copy the full resolution xml/vrt file from ./merged/geom_master to ./geom_master
+            # to facilitate the number of looks extraction
+            # the file path inside .xml file is not, but should, updated
+            shutil.copy(in_file+'.xml', out_file+'.full.xml')
+            shutil.copy(in_file+'.vrt', out_file+'.full.vrt')
+
+    return out_dir
+
+
+def runMultilookGdal(in_dir, out_dir, alks, rlks):
+    print('generate multilooked geometry files with alks={} and rlks={}'.format(alks, rlks))
+    import gdal
+
+    # create 'geom_master' directory
+    if not os.path.isdir(out_dir):
+        os.makedirs(out_dir)
+        print('create directory: {}'.format(out_dir))
+
+    # multilook files one by one
+    for fbase in ['hgt', 'incLocal', 'lat', 'lon', 'los', 'shadowMask', 'waterMask']:
+        fname = '{}.rdr'.format(fbase)
+        in_file = os.path.join(in_dir, fname)
+        out_file = os.path.join(out_dir, fname)
+
+        if os.path.isfile(in_file):
+            ds = gdal.Open(in_file, gdal.GA_ReadOnly)
+            in_wid = ds.RasterXSize
+            in_len = ds.RasterYSize
+
+            out_wid = int(in_wid / rlks)
+            out_len = int(in_len / alks)
+            src_wid = out_wid * rlks
+            src_len = out_len * alks
+
+            cmd = 'gdal_translate -of ENVI -a_nodata 0 -outsize {ox} {oy} '.format(ox=out_wid, oy=out_len)
+            cmd += ' -srcwin 0 0 {sx} {sy} {fi} {fo} '.format(sx=src_wid, sy=src_len, fi=in_file, fo=out_file)
+            print(cmd)
+            os.system(cmd)
+
+            # copy the full resolution xml/vrt file from ./merged/geom_master to ./geom_master
+            # to facilitate the number of looks extraction
+            # the file path inside .xml file is not, but should, updated
+            shutil.copy(in_file+'.xml', out_file+'.full.xml')
+            shutil.copy(in_file+'.vrt', out_file+'.full.vrt')
+
+    return out_dir
 
 
 def extractInfo(frame, inps):
@@ -369,8 +453,8 @@ def extractInfo(frame, inps):
 
     info.lookSide = frame.instrument.platform.pointingDirection
     info.rangeFirstSample = frame.startingRange
-    info.numberRangeLooks = inps.rlks
+    info.numberRangeLooks = 1 #inps.rlks
-    info.numberAzimuthLooks = inps.alks
+    info.numberAzimuthLooks = 1 #inps.alks
 
     fsamp = frame.rangeSamplingRate
 
@@ -419,11 +503,9 @@ def main(iargs=None):
         doppler = db['doppler']
     except:
         doppler = frame._dopplerVsPixel
-
     db.close()
 
 
-
     ####Setup dem
     demImage = isceobj.createDemImage()
     demImage.load(inps.dem + '.xml')
@@ -439,14 +521,20 @@ def main(iargs=None):
     info.incFilename = os.path.join(info.outdir, 'incLocal.rdr')
     info.maskFilename = os.path.join(info.outdir, 'shadowMask.rdr')
 
-
     runTopo(info,demImage,dop=doppler,nativedop=inps.nativedop, legendre=inps.legendre)
     runSimamp(os.path.dirname(info.heightFilename),os.path.basename(info.heightFilename))
 
+    # write multilooked geometry files in "geom_master" directory, same level as "Igrams"
+    if inps.rlks * inps.rlks > 1:
+        out_dir = os.path.join(os.path.dirname(os.path.dirname(info.outdir)), 'geom_master')
+        runMultilookGdal(in_dir=info.outdir, out_dir=out_dir, alks=inps.alks, rlks=inps.rlks)
+        #runMultilook(in_dir=info.outdir, out_dir=out_dir, alks=inps.alks, rlks=inps.rlks)
+
+    return
+
 
 if __name__ == '__main__':
     '''
     Main driver.
     '''
     main()
-

contrib/stack/stripmapStack/trackCRs.py

@@ -73,8 +73,7 @@ def makeOnePlot(filename, pos):
     minx = np.clip(np.min(pos[:,2])-win, 0, npix-1)
     maxx = np.clip(np.max(pos[:,2])+win, 0, npix-1)
 
-
+    box = np.power(np.abs(data[int(miny):int(maxy), int(minx):int(maxx)]), 0.4)
-    box = np.power(np.abs(data[miny:maxy, minx:maxx]), 0.4)
 
     plt.figure('CR analysis')
 
@@ -104,7 +103,7 @@ def getAzRg(frame,llh):
     pol._normRange = frame.instrument.rangePixelSize
     pol.initPoly(azimuthOrder=0, rangeOrder=len(coeffs)-1, coeffs=[coeffs])
 
-    taz, rgm = frame.orbit.geo2rdr(list(llh), side=frame.instrument.platform.pointingDirection, 
+    taz, rgm = frame.orbit.geo2rdr(list(llh)[1:], side=frame.instrument.platform.pointingDirection,
                 doppler=pol, wvl=frame.instrument.getRadarWavelength())
 
     line = (taz - frame.sensingStart).total_seconds() * frame.PRF 
@@ -145,7 +144,7 @@ if __name__ == '__main__':
 #    frame.startingRange = frame.startingRange + 100.0
 
     ###Load CRS positions
-    llhs = np.loadtxt(inps.posfile)
+    llhs = np.loadtxt(inps.posfile, delimiter=',')
 
 
     crs = []

contrib/stack/stripmapStack/unwrap.py

@@ -113,9 +113,19 @@ def extractInfoFromPickle(pckfile, inps):
     data['earthRadius'] = elp.local_radius_of_curvature(llh.lat, hdg)
     
     #azspacing  = burst.azimuthTimeInterval * sv.getScalarVelocity()
-    azres = 20.0 
+    #azres = 20.0 
+    azspacing = sv.getScalarVelocity() / burst.PRF
+    azres = burst.platform.antennaLength / 2.0
+    azfact = azres / azspacing
+
+    burst.getInstrument()
+    rgBandwidth = burst.instrument.pulseLength * burst.instrument.chirpSlope
+    rgres = abs(SPEED_OF_LIGHT / (2.0 * rgBandwidth))
+    rgspacing = burst.instrument.rangePixelSize
+    rgfact = rgres / rgspacing
 
     #data['corrlooks'] = inps.rglooks * inps.azlooks * azspacing / azres
+    data['corrlooks'] = inps.rglooks * inps.azlooks / (azfact * rgfact)
     data['rglooks'] = inps.rglooks
     data['azlooks'] = inps.azlooks
 
@@ -149,7 +159,7 @@ def runUnwrap(infile, outfile, corfile, config, costMode = None,initMethod = Non
     altitude   = config['altitude']
     rangeLooks = config['rglooks']
     azimuthLooks = config['azlooks']
-    #corrLooks = config['corrlooks']
+    corrLooks = config['corrlooks']
     maxComponents = 20
 
     snp = Snaphu()
@@ -163,7 +173,7 @@ def runUnwrap(infile, outfile, corfile, config, costMode = None,initMethod = Non
     snp.setAltitude(altitude)
     snp.setCorrfile(corfile)
     snp.setInitMethod(initMethod)
-   # snp.setCorrLooks(corrLooks)
+    snp.setCorrLooks(corrLooks)
     snp.setMaxComponents(maxComponents)
     snp.setDefoMaxCycles(defomax)
     snp.setRangeLooks(rangeLooks)
@@ -248,7 +258,8 @@ def runUnwrapIcu(infile, outfile):
     unwImage.finalizeImage()
     unwImage.renderHdr()
 
-def runUnwrap2Stage(unwrappedIntFilename,connectedComponentsFilename,unwrapped2StageFilename, unwrapper_2stage_name=None, solver_2stage=None):                                                                                            
+def runUnwrap2Stage(unwrappedIntFilename,connectedComponentsFilename,unwrapped2StageFilename,
+                    unwrapper_2stage_name=None, solver_2stage=None):
   
     if unwrapper_2stage_name is None:
         unwrapper_2stage_name = 'REDARC0'
@@ -303,6 +314,7 @@ def main(iargs=None):
         pckfile = os.path.join(masterShelveDir,'data')
         print(pckfile)
         metadata = extractInfoFromPickle(pckfile, inps)
+
     ########
     print ('unwrapping method : ' , inps.method)
     if inps.method == 'snaphu':
@@ -311,6 +323,7 @@ def main(iargs=None):
         else:
             fncall = runUnwrapMcf
         fncall(inps.intfile, inps.unwprefix + '_snaphu.unw', inps.cohfile, metadata, defomax=inps.defomax)
+
     elif inps.method == 'snaphu2stage':
         if inps.nomcf: 
             fncall =  runUnwrap
@@ -319,8 +332,9 @@ def main(iargs=None):
         fncall(inps.intfile, inps.unwprefix + '_snaphu.unw', inps.cohfile, metadata, defomax=inps.defomax)
 
         # adding in the two-stage
-        runUnwrap2Stage(inps.unwprefix + '_snaphu.unw', inps.unwprefix + '_snaphu.unw.conncomp',inps.unwprefix + '_snaphu2stage.unw')
+        runUnwrap2Stage(inps.unwprefix + '_snaphu.unw',
-
+                        inps.unwprefix + '_snaphu.unw.conncomp',
+                        inps.unwprefix + '_snaphu2stage.unw')
 
     elif inps.method == 'icu':
         runUnwrapIcu(inps.intfile, inps.unwprefix + '_icu.unw')

contrib/stack/topsStack/README.md

@@ -1,38 +1,80 @@
+## Sentinel-1 TOPS stack processor
+
 The detailed algorithm for stack processing of TOPS data can be find here:
 
-H. Fattahi, P. Agram, and M. Simons, “A network-based enhanced spectral diversity approach for TOPS time-series analysis,” IEEE Trans. Geosci. Remote Sens., vol. 55, no. 2, pp. 777–786, Feb. 2017. (https://ieeexplore.ieee.org/abstract/document/7637021/)
++ Fattahi, H., P. Agram, and M. Simons (2016), A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis, IEEE Transactions on Geoscience and Remote Sensing, 55(2), 777-786, doi:[10.1109/TGRS.2016.2614925](https://ieeexplore.ieee.org/abstract/document/7637021).
 
+-----------------------------------
 
-<<<<<< Sentinel-1 TOPS stack processor >>>>>>
+To use the sentinel stack processor, make sure to add the path of your `contrib/stack/topsStack` folder to your `$PATH` environment varibale. 
-
-To use the sentinel stack processor, make sure to add the path of your "contrib/stack/topsStack" folder to your $PATH environment varibale. 
-
 
 The scripts provides support for Sentinel-1 TOPS stack processing. Currently supported workflows include a coregistered stack of SLC, interferograms, offsets, and coherence. 
 
-stackSentinel.py generates all configuration and run files required to be executed on a stack of Sentinel-1 TOPS data. When stackSentinel.py is executed for a given workflow (-W option) a “configs” and “run_files” folder is generated. No processing is performed at this stage. Within the “run_files” folder different run_#_description files are contained which are to be executed as shell scripts in the run number order. Each of these run scripts call specific configure files contained in the “configs” folder which call ISCE in a modular fashion. The configure and run files will change depending on the selected workflow. To make run_# files executable, change the file permission accordingly (e.g., chmod +x run_1_unpack_slc).
+`stackSentinel.py` generates all configuration and run files required to be executed on a stack of Sentinel-1 TOPS data. When stackSentinel.py is executed for a given workflow (-W option) a **configs** and **run_files** folder is generated. No processing is performed at this stage. Within the run_files folder different run\_#\_description files are contained which are to be executed as shell scripts in the run number order. Each of these run scripts call specific configure files contained in the “configs” folder which call ISCE in a modular fashion. The configure and run files will change depending on the selected workflow. To make run_# files executable, change the file permission accordingly (e.g., `chmod +x run_1_unpack_slc`).
 
-To see workflow examples, type “stackSentinel.py -H”
+```bash
-To get an overview of all the configurable parameters, type “stackSentinel.py -h”
+stackSentinel.py -H     #To see workflow examples,
+stackSentinel.py -h     #To get an overview of all the configurable parameters
+```
 
 Required parameters of stackSentinel.py include:
--s SLC_DIRNAME	A folder with downloaded Sentinel-1 SLC’s. 
--o ORBIT_DIRNAME	A folder containing the Sentinel-1 orbits.
-Missing orbit files will be downloaded automatically
--a AUX_DIRNAME 	A folder containing the Sentinel-1 Auxiliary files
--d DEM 		A DEM (Digital Elevation Model) referenced to wgs84
 
+```cfg
+-s SLC_DIRNAME          #A folder with downloaded Sentinel-1 SLC’s. 
+-o ORBIT_DIRNAME        #A folder containing the Sentinel-1 orbits. Missing orbit files will be downloaded automatically
+-a AUX_DIRNAME          #A folder containing the Sentinel-1 Auxiliary files
+-d DEM_FILENAME         #A DEM (Digital Elevation Model) referenced to wgs84
+```
 
 In the following, different workflow examples are provided. Note that stackSentinel.py only generates the run and configure files. To perform the actual processing, the user will need to execute each run file in their numbered order.
 
 In all workflows, coregistration (-C option) can be done using only geometry (set option = geometry) or with geometry plus refined azimuth offsets through NESD (set option = NESD) approach, the latter being the default. For the NESD coregistrstion the user can control the ESD coherence threshold (-e option) and the number of overlap interferograms (-O) to be used in NESD estimation.
 
------------------------------- Example 1: Coregistered stack of SLC ----------------------------
+#### AUX_CAL file download ####
-Generate the run and configure files needed to generate a coregistered stack of SLCs. 
-In this example, a pre-defined bounding box is specified. Note, if the bounding box is not provided it is set by default to the common SLC area among all SLCs. We recommend that user always set the processing bounding box. Since ESA does not have a fixed frame definition, we suggest to download data for a larger bounding box compared to the actual bounding box used in stackSentinel.py. This way user can ensure to have required data to cover the region of interest. Here is an example command to create configuration files for a stack of SLCs:
 
+The following calibration auxliary (AUX_CAL) file is used for **antenna pattern correction** to compensate the range phase offset of SAFE products with **IPF verison 002.36** (mainly for images acquired before March 2015). If all your SAFE products are from another IPF version, then no AUX files are needed. Check [ESA document](https://earth.esa.int/documents/247904/1653440/Sentinel-1-IPF_EAP_Phase_correction) for details. 
+
+Run the command below to download the AUX_CAL file once and store it somewhere (_i.e._ ~/aux/aux_cal) so that you can use it all the time, for `stackSentinel.py -a` or `auxiliary data directory` in `topsApp.py`.
+
+```
+wget https://qc.sentinel1.eo.esa.int/product/S1A/AUX_CAL/20140908T000000/S1A_AUX_CAL_V20140908T000000_G20190626T100201.SAFE.TGZ
+tar zxvf S1A_AUX_CAL_V20140908T000000_G20190626T100201.SAFE.TGZ
+rm S1A_AUX_CAL_V20140908T000000_G20190626T100201.SAFE.TGZ
+```
+
+#### 1. Create your project folder somewhere ####
+
+```
+mkdir MexicoSenAT72
+cd MexicoSenAT72
+```
+
+#### 2. Prepare DEM ####
+
+Download of DEM (need to use wgs84 version) using the ISCE DEM download script.
+
+```
+mkdir DEM; cd DEM
+dem.py -a stitch -b 18 20 -100 -97 -r -s 1 –c
+rm demLat*.dem demLat*.dem.xml demLat*.dem.vrt
+fixImageXml.py -f -i demLat*.dem.wgs84             #Updating DEM’s wgs84 xml to include full path to the DEM
+cd ..
+```
+
+#### 3. Download Sentinel-1 data to SLC ####
+
+
+
+#### 4.1 Example workflow: Coregistered stack of SLC ####
+
+Generate the run and configure files needed to generate a coregistered stack of SLCs. In this example, a pre-defined bounding box is specified. Note, if the bounding box is not provided it is set by default to the common SLC area among all SLCs. We recommend that user always set the processing bounding box. Since ESA does not have a fixed frame definition, we suggest to download data for a larger bounding box compared to the actual bounding box used in stackSentinel.py. This way user can ensure to have required data to cover the region of interest. Here is an example command to create configuration files for a stack of SLCs:
+
+```
 stackSentinel.py -s ../SLC/ -d ../DEM/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -a ../../AuxDir/ -o ../../Orbits -b '19 20 -99.5 -98.5' -W slc
+```
+
 by running the command above, the configs and run_files folders are created. User needs to execute each run file in order. The order is specified by the index number of the run file name. For the example above, the run_files folder includes the following files:
+
 -	run_1_unpack_slc_topo_master
 -	run_2_average_baseline
 -	run_3_extract_burst_overlaps
@@ -46,72 +88,83 @@ by running the command above, the configs and run_files folders are created. Use
 
 The generated run files are self descriptive. Below is a short explanation on what each run_file does:
 
-***run_1_unpack_slc_topo_master:***
+**run_1_unpack_slc_topo_master:**
+
 Includes commands to unpack Sentinel-1 TOPS SLCs using ISCE readers. For older SLCs which need antenna elevation pattern correction, the file is extracted and written to disk. For newer version of SLCs which don’t need the elevation antenna pattern correction, only a gdal virtual “vrt” file (and isce xml file) is generated. The “.vrt” file points to the Sentinel SLC file and reads them whenever required during the processing. If a user wants to write the “.vrt” SLC file to disk, it can be done easily using gdal_translate (e.g. gdal_translate –of ENVI File.vrt File.slc). 
 The “run_1_unpack_slc_topo_master” also includes a command that refers to the config file of the stack master, which includes configuration for running topo for the stack master. Note that in the pair-wise processing strategy one should run topo (mapping from range-Doppler to geo coordinate) for all pairs. However, with stackSentinel, topo needs to be run only one time for the master in the stack. 
 
-***run_2_average_baseline: ***
+**run_2_average_baseline:**
+
 Computes average baseline for the stack. These baselines are not used for processing anywhere. They are only an approximation and can be used for plotting purposes. A more precise baseline grid is estimated later in run_10.
 
-***run_3_extract_burst_overlaps: ***
+**run_3_extract_burst_overlaps:**
+
 Burst overlaps are extracted for estimating azimuth misregistration using NESD technique. If coregistration method is chosen to be “geometry”, then this run file won’t exist and the overlaps are not extracted.
 
-***run_4_overlap_geo2rdr_resample: ***
+**run_4_overlap_geo2rdr_resample:***
+
 Running geo2rdr to estimate geometrical offsets between slave burst overlaps and the stack master burst overlaps. The slave burst overlaps are then resampled to the stack master burst overlaps. 
 
-***run_5_pairs_misreg: ***
+**run_5_pairs_misreg:**
+
 Using the coregistered stack burst overlaps generated from the previous step, differential overlap interferograms are generated and are used for estimating azimuth misregistration using Enhanced Spectral Diversity (ESD) technique. 
 
-***run_6_timeseries_misreg: ***
+**run_6_timeseries_misreg:**
+
 A time-series of azimuth and range misregistration is estimated with respect to the stack master. The time-series is a least squares esatimation from the pair misregistration from the previous step.
 
-***run_7_geo2rdr_resample: ***
+**run_7_geo2rdr_resample:**
+
 Using orbit and DEM, geometrical offsets among all slave SLCs and the stack master is computed. The goometrical offsets, together with the misregistration time-series (from previous step) are used for precise coregistration of each burst SLC. 
 
-***run_8_extract_stack_valid_region: ***
+**run_8_extract_stack_valid_region:**
+
 The valid region between burst SLCs at the overlap area of the bursts slightly changes for different acquisitions. Therefore we need to keep track of these overlaps which will be used during merging bursts. Without these knowledge, lines of invalid data may appear in the merged products at the burst overlaps.
 
-***run_9_merge: ***
+**run_9_merge:**
+
 Merges all bursts for the master and coregistered SLCs. The geometry files are also merged including longitude, latitude, shadow and layer mask, line-of-sight files, etc. .
 
-***run_10_grid_baseline: ***
+**run_10_grid_baseline:**
+
 A coarse grid of baselines between each slave SLC and the stack master is generated. This is not used in any computation.
 
+#### 4.2 Example workflow: Coregistered stack of SLC with modified parameters ####
 
--------- Example 2: Coregistered stack of SLC with modified parameters -----------
 In the following example, the same stack generation is requested but where the threshold of the default coregistration approach (NESD) is relaxed from its default 0.85 value 0.7.
 
+```
 stackSentinel.py -s ../SLC/ -d ../DEM/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -a ../../AuxDir/ -o ../../Orbits -b '19 20 -99.5 -98.5' -W slc -e 0.7
+```
 
-When running all the run files, the final products are located in the merge folder which has subdirectories “geom_master”, “baselines” and “SLC”. The “geom_master” folder contains geometry products such as longitude, latitude, height, local incidence angle, look angle, heading, and shadowing/layover mask files. The “baselines” folder contains sparse grids of the perpendicular baseline for each acquisition, while the “SLC” folder contains the coregistered SLCs
+When running all the run files, the final products are located in the merge folder which has subdirectories **geom_master**, **baselines** and **SLC**. The **geom_master** folder contains geometry products such as longitude, latitude, height, local incidence angle, look angle, heading, and shadowing/layover mask files. The **baselines** folder contains sparse grids of the perpendicular baseline for each acquisition, while the **SLC** folder contains the coregistered SLCs
 
+#### 4.3 Example workflow: Stack of interferograms ####
 
------------------------------- Example 3: Stack of interferograms  ------------------------------
 Generate the run and configure files needed to generate a stack of interferograms.
 In this example, a stack of interferograms is requested for which up to 2 nearest neighbor connections are included.
 
+```
 stackSentinel.py -s ../SLC/ -d ../../MexicoCity/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -b '19 20 -99.5 -98.5' -a ../../AuxDir/ -o ../../Orbits -c 2
+```
 
 In the following example, all possible interferograms are being generated and in which the coregistration approach is set to use geometry and not the default NESD. 
 
+```
 stackSentinel.py -s ../SLC/ -d ../../MexicoCity/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -b '19 20 -99.5 -98.5' -a ../../AuxDir/ -o ../../Orbits -C geometry -c all
+```
 
 When executing all the run files, a coregistered stack of slcs are produced, the burst interferograms are generated and then merged. Merged interferograms are multilooked, filtered and unwrapped. Geocoding is not applied. If users need to geocode any product, they can use the geocodeGdal.py script.
 
+#### 4.4 Example workflow: Stack of correlation ####
 
--------------------- Example 4:  Correlation stack example ----------------------------
 Generate the run and configure files needed to generate a stack of coherence.
 In this example, a correlation stack is requested considering all possible coherence pairs and where the coregistration approach is done using geometry only.
 
+```
 stackSentinel.py -s ../SLC/ -d ../../MexicoCity/demLat_N18_N20_Lon_W100_W097.dem.wgs84 -b '19 20 -99.5 -98.5' -a ../../AuxDir/ -o ../../Orbits -C geometry -c all -W correlation
+```
 
 This workflow is basically similar to the previous one. The difference is that the interferograms are not unwrapped.
 
-
+#### 5. Execute the commands in run files (run_1*, run_2*, etc) in the "run_files" folder ####
------------------------------------ DEM download example -----------------------------------
-Download of DEM (need to use wgs84 version) using the ISCE DEM download script.
-dem.py -a stitch -b 18 20 -100 -97 -r -s 1 –c
-
-Updating DEM’s wgs84 xml to include full path to the DEM
-fixImageXml.py -f -i demLat_N18_N20_Lon_W100_W097.dem.wgs84
-

examples/input_files/stripmapApp.xml

@@ -12,7 +12,8 @@
         <value>/Users/fattahi/process/test_roiApp/Alos_Maule_T116/demLat_S39_S35_Lon_W074_W071.dem.wgs84</value>
     </property>
     <!--
-    <property name="do rubbersheeting">True</property>
+      <property name="do rubbersheetingAzimuth">True</property>
+      <property name="do rubbersheetingRange">False</property>
     -->
     <property name="do denseoffsets">True</property>
     <property name="do split spectrum">True</property>

scons_tools/cuda.py

@@ -52,7 +52,7 @@ def generate(env):
     # default flags for the NVCC compiler
     env['STATICNVCCFLAGS'] = ''
     env['SHAREDNVCCFLAGS'] = ''
-    env['ENABLESHAREDNVCCFLAG'] = '-arch=sm_35 -shared -Xcompiler -fPIC'
+    env['ENABLESHAREDNVCCFLAG'] = '-shared -Xcompiler -fPIC'
 
     # default NVCC commands
     env['STATICNVCCCMD'] = '$NVCC -o $TARGET -c $NVCCFLAGS $STATICNVCCFLAGS $SOURCES'
@@ -153,7 +153,7 @@ def generate(env):
     #env.Append(LIBPATH=[cudaSDKPath + '/lib', cudaSDKPath + '/common/lib' + cudaSDKSubLibDir, cudaToolkitPath + '/lib'])
 
     env.Append(CUDACPPPATH=[cudaToolkitPath + '/include'])
-    env.Append(CUDALIBPATH=[cudaToolkitPath + '/lib', cudaToolkitPath + '/lib64'])
+    env.Append(CUDALIBPATH=[cudaToolkitPath + '/lib', cudaToolkitPath + '/lib64', '/lib64'])
     env.Append(CUDALIBS=['cudart'])
 
 def exists(env):

setup/setup.py

@@ -12,7 +12,7 @@
 from __future__ import print_function
 import sys
 import os
-import urllib2
+import urllib
 import getopt
 import re
 import shutil
@@ -57,7 +57,7 @@ def print2log(msg, withtime=True, cmd=False):
     if withtime:
         now = datetime.datetime.today()
         msg = "%s >> %s" % (now.isoformat(), msg)
-    LOGFILE.write(msg + '\n')
+    LOGFILE.write((msg + '\n').encode('utf-8'))
     LOGFILE.flush()
     os.fsync(LOGFILE)
 
@@ -157,9 +157,9 @@ def downloadfile(url, fname, repeat=1):
     counter = 0
     while counter < repeat:
         try:
-            response = urllib2.urlopen(url)
+            response = urllib.request.urlopen(url)
             break
-        except urllib2.URLError, e:
+        except urllib.request.URLError as e:
             counter += 1
             if hasattr(e, 'reason'):
                 print2log("Failed to reach server. Reason: %s" % e.reason)
@@ -851,7 +851,7 @@ class ISCEDeps(object):
         f = open(self.config, 'rb')
         lines = f.readlines()
         for line in lines:
-            m = re.match("([^#].*?)=([^#]+?)$", line.strip())
+            m = re.match("([^#].*?)=([^#]+?)$", line.strip().decode('utf-8'))
             if m:
                 var = m.group(1).strip()
                 val = m.group(2).strip()
@@ -867,7 +867,7 @@ def readSetupConfig(setup_config):
     f = open(setup_config, 'rb')
     lines = f.readlines()
     for line in lines:
-        m = re.match("([^#].*?)=([^#]+?)$", line.strip())
+        m = re.match("([^#].*?)=([^#]+?)$", line.strip().decode('utf-8'))
         if m:
             var = m.group(1).strip()
             val = m.group(2).strip().replace('"', '')
@@ -885,7 +885,7 @@ def checkArgs(args):
     """
     try:
         opts, args = getopt.getopt(args, "h", ["help", "prefix=", "ping=", "config=", "uname=", "download=", "unpack=", "install=", "gcc=", "gpp=", "verbose"])
-    except getopt.GetoptError, err:
+    except getopt.GetoptError as err:
         print2log("ProgError: %s" % str(err))
         usage()
         sys.exit(2)