Merge pull request #82 from rtburns-jpl/hide-imports

Hide rubbersheeting scipy/astropy imports

components/isceobj/StripmapProc/runDispersive.py

@@ -9,7 +9,6 @@ from isceobj.Constants import SPEED_OF_LIGHT
 import numpy as np
 import gdal
 
-from scipy import ndimage
 try:
     import cv2
 except ImportError:
@@ -296,6 +295,8 @@ 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/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()

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)
@@ -112,6 +115,8 @@ 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()
@@ -154,7 +159,9 @@ def mask_filter(denseOffsetFile, snrFile, band, snrThreshold, filterSize, outNam
     return 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

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,
@@ -108,7 +112,9 @@ def fill(data, invalid=None):
     return data[tuple(ind)]
 
 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)