Update runRubbersheetAzimuth.py

Add "from scipy import ndimage"

components/isceobj/StripmapProc/runRubbersheetAzimuth.py

@@ -22,39 +22,39 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
     off_az = ds.GetRasterBand(1).ReadAsArray()
     off_rg = ds.GetRasterBand(2).ReadAsArray()
     ds = None
-    
+
-    # Remove missing values from ampcor 
+    # Remove missing values from ampcor
     off_rg[np.where(off_rg < -9999)]=0
     off_az[np.where(off_az < -9999)]=0
-    
+
-    
+
     # Store the offsets in a complex variable
     off = off_rg + 1j*off_az
 
     # Mask the azimuth offsets based on the MAD
-    mask = off_masking(off,filterSize,thre=3) 
+    mask = off_masking(off,filterSize,thre=3)
-    
+
     xoff_masked = np.ma.array(off.real,mask=mask)
     yoff_masked = np.ma.array(off.imag,mask=mask)
-    
+
     # Delete unused variables
     mask = None
     off = None
-    
+
     # Remove residual noisy spots with a median filter on the azimuth offmap
     yoff_masked.mask = yoff_masked.mask | \
             (ndimage.median_filter(xoff_masked.filled(fill_value=0),3) == 0) | \
             (ndimage.median_filter(yoff_masked.filled(fill_value=0),3) == 0)
-    
+
-    # Fill the data by iteratively using smoothed values    
+    # Fill the data by iteratively using smoothed values
     data = yoff_masked.data
     data[yoff_masked.mask]=np.nan
-    
+
     off_az_filled = fill_with_smoothed(data,filterSize)
-    
+
     # Apply median filter to smooth the azimuth offset map
     off_az_filled = ndimage.median_filter(off_az_filled,filterSize)
-    
+
     # Save the filtered offsets
     length, width = off_az_filled.shape
 
@@ -74,8 +74,8 @@ def mask_filterNoSNR(denseOffsetFile,filterSize,outName):
     img.scheme = 'BIP'
     img.renderHdr()
 
-    
+
-    return 
+    return
 
 
 def off_masking(off,filterSize,thre=2):
@@ -94,16 +94,18 @@ def fill(data, invalid=None):
     """
     Replace the value of invalid 'data' cells (indicated by 'invalid')
     by the value of the nearest valid data cell
-    
+
     Input:
         data:    numpy array of any dimension
         invalid: a binary array of same shape as 'data'.
                  data value are replaced where invalid is True
                  If None (default), use: invalid  = np.isnan(data)
-       
+
     Output:
         Return a filled array.
     """
+    from scipy import ndimage
+
     if invalid is None: invalid = np.isnan(data)
 
     ind = ndimage.distance_transform_edt(invalid,
@@ -166,7 +168,7 @@ def fill_with_smoothed(off,filterSize):
     kernel = np.ones((filterSize,filterSize),np.float32)/(filterSize*filterSize)
     loop = 0
     cnt2=1
-    
+
     while (cnt2!=0 & loop<100):
        loop += 1
        idx2= np.isnan(off_2filt)
@@ -178,9 +180,9 @@ def fill_with_smoothed(off,filterSize):
           idx3 = np.where(off_filt == 0)
           off_2filt[idx3]=np.nan
           off_filt=None
-    
+
     return off_2filt
-    
+
 def resampleOffset(maskedFiltOffset, geometryOffset, outName):
     '''
     Oversample offset and add.
@@ -198,7 +200,7 @@ def resampleOffset(maskedFiltOffset, geometryOffset, outName):
     ###Currently making the assumption that top left of dense offsets and interfeorgrams are the same.
     ###This is not true for now. We need to update DenseOffsets to have the ability to have same top left
     ###As the input images. Once that is implemente, the math here should all be consistent.
-    ###However, this is not too far off since the skip for doing dense offsets is generally large. 
+    ###However, this is not too far off since the skip for doing dense offsets is generally large.
     ###The offset is not too large to worry about right now. If the skip is decreased, this could be an issue.
 
     print('oversampling the filtered and masked offsets to the width and length:', width, ' ', length )
@@ -226,7 +228,7 @@ def resampleOffset(maskedFiltOffset, geometryOffset, outName):
     for ll in range(length):
         val = geomoff.bands[0][ll,:] + osoff.bands[0][ll,:]
         val.tofile(fid)
-    
+
     fid.close()
 
     img = isceobj.createImage()
@@ -239,7 +241,7 @@ def resampleOffset(maskedFiltOffset, geometryOffset, outName):
     img.scheme = 'BIP'
     img.renderHdr()
 
-    
+
 
     return None
 
@@ -264,7 +266,7 @@ def runRubbersheetAzimuth(self):
     if not self.doRubbersheetingRange:
        print('Rubber sheeting in range is off, filtering the offsets with a SNR-based mask')
        mask_filter(denseOffsetFile, snrFile, band[0], snrThreshold, filterSize, filtAzOffsetFile)
-    else: 
+    else:
        print('Rubber sheeting in range is on, filtering the offsets with data-based mask')
        mask_filterNoSNR(denseOffsetFile, filterSize, filtAzOffsetFile)
 
@@ -274,10 +276,8 @@ def runRubbersheetAzimuth(self):
     sheetOffset = os.path.join(offsetsDir, self.insar.azimuthRubbersheetFilename)
 
     # oversampling the filtAzOffsetFile to the same size of geometryAzimuthOffset
-    # and then update the geometryAzimuthOffset by adding the oversampled 
+    # and then update the geometryAzimuthOffset by adding the oversampled
     # filtAzOffsetFile to it.
     resampleOffset(filtAzOffsetFile, geometryAzimuthOffset, sheetOffset)
 
     return None
-
-