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Hide scipy imports for stripmapapp

LT1AB
Ryan Burns 2019-12-16 10:22:01 -08:00
parent 537bae03d9
commit e2a81bbd6a
4 changed files with 12 additions and 8 deletions
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3
components/isceobj/StripmapProc/runDispersive.py
View File

@ -9,7 +9,6 @@ from isceobj.Constants import SPEED_OF_LIGHT
import numpy as np import numpy as np
import gdal import gdal
from scipy import ndimage
try: try:
import cv2 import cv2
except ImportError: except ImportError:
@ -296,6 +295,8 @@ def fill(data, invalid=None):
Output: Output:
Return a filled array. Return a filled array.
""" """
from scipy import ndimage
if invalid is None: invalid = np.isnan(data) if invalid is None: invalid = np.isnan(data)
ind = ndimage.distance_transform_edt(invalid, ind = ndimage.distance_transform_edt(invalid,

12
components/isceobj/TopsProc/runIon.py
View File

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

3
components/isceobj/TopsProc/runOffsetFilter.py
View File

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

2
components/isceobj/TopsProc/runPrepESD.py
View File

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