370 lines
11 KiB
Python
370 lines
11 KiB
Python
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#!/usr/bin/env python3
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#Author: Heresh Fattahi
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import os, imp, sys, glob
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import argparse
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import configparser
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import datetime
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import time
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import numpy as np
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import shelve
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import isce
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import isceobj
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from isceobj.Util.Poly2D import Poly2D
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import h5py
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from insarPair import insarPair
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from insarStack import insarStack
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import gdal
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#################################################################
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def createParser():
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'''
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Create command line parser.
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'''
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parser = argparse.ArgumentParser( description='extracts the overlap geometry between master bursts')
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parser.add_argument('-i', '--input', type=str, dest='input', required=True,
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help='Directory with the pair directories that includes dense offsets for each pair')
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parser.add_argument('-o', '--output', type=str, dest='output', required=True,
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help='output directory to save dense-offsets for each date with respect to the stack Master date')
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return parser
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def cmdLineParse(iargs = None):
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'''
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Command line parser.
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'''
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parser = createParser()
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inps = parser.parse_args(args=iargs)
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return inps
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def write2h5(inps):
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# dumping all offset files to an h5 file
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dirs = glob.glob(os.path.join(inps.input,'*'))
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pairsDict = {}
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for dir in dirs:
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#Assuming the directory name for a pair is master_slave dates (eg: 20100506_20101112)
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d12 = os.path.basename(dir)
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#if os.path.exists(os.path.join(dir,d12+'.bil')):
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if os.path.exists(os.path.join(dir,'filtAzimuth.off')):
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obsDict = {'offset-azimuth':os.path.join(dir,'filtAzimuth.off')}
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#qualityDict = {'offset-snr':os.path.join(dir,d12+'_snr.bil')}
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dates = os.path.basename(dir).split('_')
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t1 = time.strptime(dates[0],'%Y%m%d')
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Time1 = datetime.datetime(t1.tm_year,t1.tm_mon,t1.tm_mday)
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t2 = time.strptime(dates[1],'%Y%m%d')
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Time2 = datetime.datetime(t2.tm_year,t2.tm_mon,t2.tm_mday)
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metadataDict = {'platform' : 'platform' , 'processor' : 'ISCE' }
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pairObj = insarPair(dates=(Time1 , Time2) ,observation = obsDict, metadata=metadataDict)
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#pairObj = insarPair(dates=(Time1 , Time2) ,observation = obsDict, quality = qualityDict, metadata=metadataDict)
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pairObj.get_metadata('offset-azimuth')
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pairsDict[(Time1,Time2)] = pairObj
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############################################
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stackObj = insarStack(pairsDict = pairsDict)
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stackObj.get_platform_tracks()
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outFile = os.path.join(inps.input,'offsets.h5')
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stackObj.save2h5(output = outFile)
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return outFile
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def date_list(h5file):
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h5=h5py.File(h5file,'r')
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ds = h5['/platform-track/observations'].get('pairs_idx')
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pairs = ds[:,:]
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numPiars = pairs.shape[0]
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dateList = []
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tbase = []
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masters = [None]*numPiars
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slaves = [None]*numPiars
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for i in range(numPiars):
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master = pairs[i,0].decode("utf-8")
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slave = pairs[i,1].decode("utf-8")
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if master not in dateList: dateList.append(master)
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if slave not in dateList: dateList.append(slave)
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masters[i]=master
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slaves[i]=slave
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dateList.sort()
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d1 = datetime.datetime(*time.strptime(dateList[0],"%Y-%m-%d %H:%M:%S")[0:6])
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for ni in range(len(dateList)):
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d2 = datetime.datetime(*time.strptime(dateList[ni],"%Y-%m-%d %H:%M:%S")[0:6])
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diff = d2-d1
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tbase.append(diff.days)
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dateDict = {}
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for i in range(len(dateList)): dateDict[dateList[i]] = tbase[i]
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return tbase,dateList,dateDict, masters, slaves
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#####################################
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def design_matrix(h5File):
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tbase,dateList,dateDict, masters, slaves = date_list(h5File)
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numDates = len(dateDict)
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numPairs = len(masters)
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A = np.zeros((numPairs,numDates))
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B = np.zeros_like(A)
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tbase = np.array(tbase)
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for ni in range(numPairs):
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ndxt1 = dateList.index(masters[ni])
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ndxt2 = dateList.index(slaves[ni])
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A[ni,ndxt1] = -1
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A[ni,ndxt2] = 1
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B[ni,ndxt1:ndxt2] = tbase[ndxt1+1:ndxt2+1]-tbase[ndxt1:ndxt2]
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#print('A',A)
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#print('%%%%%%%%%%%%%%% %%%%%')
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A = A[:,1:]
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B = B[:,:-1]
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return A, B
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def invert_wlq(inps,h5File):
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tbase,dateList,dateDict, masters, slaves = date_list(h5File)
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numPairs = len(masters)
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A,B = design_matrix(h5File)
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h5 = h5py.File(h5File,'r')
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data = h5['/platform-track/observations'].get('offset-azimuth')
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snr = h5['/platform-track/quality'].get('offset-snr')
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Nz, Ny, Nx = data.shape
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Npar = A.shape[1]
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A1 = np.linalg.pinv(A)
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A1 = np.array(A1,np.float32)
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##########
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outName = os.path.join(inps.output,'timeseries.h5')
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h5out = h5py.File(outName,'w')
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ds = h5out.create_dataset('offsets',shape=(len(dateList),Ny,Nx),dtype=np.float32)
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dsq = h5out.create_dataset('quality',shape=(len(dateList),Ny,Nx),dtype=np.float32)
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I = np.eye(Nx)
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#Ak = np.kron(I,A)
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for j in range(Ny):
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print(j, 'out of ',Ny)
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L = data[:,j,:]
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Lsnr = snr[:,j,:]
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mask = np.prod(Lsnr,0)
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ind = mask>0.0
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NumValidPixels = np.sum(ind)
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if NumValidPixels>0:
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Lsnr = Lsnr[:,ind].flatten(1)
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L = L[:,ind].flatten(1)
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Lsnr = Lsnr/np.sum(Lsnr)
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W = np.diag(Lsnr)
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I = np.eye(NumValidPixels)
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Ak = np.kron(I,A)
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Cm = np.linalg.inv(np.dot(np.dot(Ak.T, W),Ak))
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B = np.dot(np.dot(np.linalg.inv(np.dot(np.dot(Ak.T, W),Ak)),Ak.T),W)
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ts = np.dot(B,L)
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Cm = np.sqrt(Cm[range(NumValidPixels*Npar),range(NumValidPixels*Npar)]).reshape([NumValidPixels,Npar]).T
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#Cm = np.vstack((np.zeros((1,ts.shape[1]), dtype=np.float32), ts))
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ts = ts.reshape([NumValidPixels,Npar]).T
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#ts = np.vstack((np.zeros((1,ts.shape[1]), dtype=np.float32), ts))
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ds[1:,j,ind] = ts
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dsq[1:,j,ind] = Cm
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dateListE = [d.encode("ascii", "ignore") for d in dateList]
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dateListE = np.array(dateListE)
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dsDateList = h5out.create_dataset('dateList', data=dateListE, dtype=dateListE.dtype)
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h5out.close()
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h5.close()
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return outName
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##########
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#def invert_old():
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'''
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for j in range(Ny):
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print(j, 'out of ',Ny)
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L = np.empty((Nz*Nx,1))
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L[:,0] = data[:,j,:].flatten(1)[:]
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Lsnr = snr[:,j,:].flatten(1)
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Lsnr = Lsnr/np.sum(Lsnr)
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W = np.diag(Lsnr)
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#W = np.eye(Nz*Nx)
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B = np.dot(np.dot(np.linalg.inv(np.dot(np.dot(Ak.T, W),Ak)),Ak.T),W)
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ts = np.dot(B,L)
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ts = ts.reshape([Nx,Npar]).T
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ts = np.vstack((np.zeros((1,ts.shape[1]), dtype=np.float32), ts))
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ds[:,j,:] = ts
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'''
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##########
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'''
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for j in range(Ny):
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print(j, 'out of ',Ny)
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for i in range(Nx):
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L = np.empty((Nz,1))
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L[:,0] = data[:,j,i]
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Lsnr = snr[:,j,i]
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Lsnr = Lsnr/np.sum(Lsnr)
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W = np.diag(Lsnr)
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#print('W',W)
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B = np.dot(np.dot(np.linalg.inv(np.dot(np.dot(A.T, W),A)),A.T),W)
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B = np.array(B,np.float32)
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ts = np.dot(B,L)
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ts = np.vstack((np.zeros((1,ts.shape[1]), dtype=np.float32), ts))
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ds[:,j,i] = ts[:,0]
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'''
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def invert(inps,h5File):
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tbase,dateList,dateDict, masters, slaves = date_list(h5File)
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numPairs = len(masters)
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A,B = design_matrix(h5File)
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h5 = h5py.File(h5File,'r')
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data = h5['/platform-track/observations'].get('offset-azimuth')
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Nz, Ny, Nx = data.shape
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Npar = A.shape[1]
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A1 = np.linalg.pinv(A)
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A1 = np.array(A1,np.float32)
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##########
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outName = os.path.join(inps.output,'timeseries.h5')
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h5out = h5py.File(outName,'w')
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ds = h5out.create_dataset('offsets',shape=(len(dateList),Ny,Nx),dtype=np.float32)
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#dsq = h5out.create_dataset('quality',shape=(len(dateList),Ny,Nx),dtype=np.float32)
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h5tempCoh = h5py.File(os.path.join(inps.output,'temporal_coherence.h5'),'w')
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dst = h5tempCoh.create_dataset('temporal_coherence', shape=(Ny,Nx),dtype=np.float32)
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for i in range(Ny):
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print(i, 'out of ',Ny)
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L = data[:,i,:]
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ts = np.dot(A1, L)
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L_residual = L - np.dot(A,ts)
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#dsr[:,i,:] = L_residual
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dst[i,:] = np.absolute(np.sum(np.exp(1j*L_residual),0))/Nz
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ts = np.vstack((np.zeros((1,ts.shape[1]), dtype=np.float32), ts))
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ds[:,i,:] = ts
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dateListE = [d.encode("ascii", "ignore") for d in dateList]
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dateListE = np.array(dateListE)
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dsDateList = h5out.create_dataset('dateList', data=dateListE, dtype=dateListE.dtype)
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h5out.close()
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h5tempCoh.close()
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h5.close()
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return outName
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def writeDateOffsets(inps, h5File):
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h5=h5py.File(h5File, 'r')
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ds = h5.get('offsets')
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# dsq = h5.get('quality')
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dsDates = h5.get('dateList')
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dateList = list(dsDates[:])
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print (dateList)
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for i in range(len(dateList)):
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print(dateList[i])
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d = dateList[i].decode("utf-8")
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d = datetime.datetime(*time.strptime(d,"%Y-%m-%d %H:%M:%S")[0:6]).strftime('%Y%m%d')
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outDir = os.path.join(inps.output, d)
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if not os.path.exists(outDir):
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os.makedirs(outDir)
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outName = os.path.join(outDir , d + '.bil')
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write(ds[i,:,:], outName, 1, 6)
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# outName = os.path.join(outDir , d + '_snr.bil')
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# write(dsq[i,:,:], outName, 1, 6)
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def write(raster, fileName, nbands, bandType):
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############
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# Create the file
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length, width = raster.shape
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driver = gdal.GetDriverByName( 'ENVI' )
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dst_ds = driver.Create(fileName, raster.shape[1], raster.shape[0], nbands, bandType )
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dst_ds.GetRasterBand(1).WriteArray( raster, 0 ,0 )
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dst_ds = None
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img = isceobj.createImage()
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img.setFilename(fileName)
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img.setWidth(width)
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img.setLength(length)
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img.setAccessMode('READ')
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img.bands = 1
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img.dataType = 'FLOAT'
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img.scheme = 'BIP'
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img.renderHdr()
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img.renderVRT()
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'''
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chunks = getChunks(Ny,Nx, 128, 128)
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print(chunks)
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start = time.time()
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for cnk in chunks:
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ss = np.zeros((128,128))
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for ii in range(numPairs):
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line = data[ii,cnk[0],cnk[1]]
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print(line.shape)
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print(np.mean(line))
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#ss += line
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end = time.time()
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print('3D chunked chunk-by-slice: ', end-start)
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h5.close()
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'''
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def getChunks(Ny,Nx, chunk_y, chunk_x):
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# First determine the number of chunks in each dimension
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Ny_chunk = int(Ny // chunk_y)
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Nx_chunk = int(Nx // chunk_x)
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if Ny % chunk_y != 0:
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Ny_chunk += 1
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if Nx % chunk_x != 0:
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Nx_chunk += 1
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# Now construct chunk bounds
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chunks = []
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for i in range(Ny_chunk):
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if i == Ny_chunk - 1:
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nrows = Ny - chunk_y * i
|
||
|
|
else:
|
||
|
|
nrows = chunk_y
|
||
|
|
istart = chunk_y * i
|
||
|
|
iend = istart + nrows
|
||
|
|
for j in range(Nx_chunk):
|
||
|
|
if j == Nx_chunk - 1:
|
||
|
|
ncols = Nx - chunk_x * j
|
||
|
|
else:
|
||
|
|
ncols = chunk_x
|
||
|
|
jstart = chunk_x * j
|
||
|
|
jend = jstart + ncols
|
||
|
|
chunks.append([slice(istart,iend), slice(jstart,jend)])
|
||
|
|
|
||
|
|
return chunks
|
||
|
|
|
||
|
|
def main(iargs=None):
|
||
|
|
|
||
|
|
inps = cmdLineParse(iargs)
|
||
|
|
if not os.path.exists(inps.output):
|
||
|
|
os.makedirs(inps.output)
|
||
|
|
|
||
|
|
h5File = write2h5(inps)
|
||
|
|
|
||
|
|
h5Timeseries = invert(inps, h5File)
|
||
|
|
|
||
|
|
writeDateOffsets(inps, h5Timeseries)
|
||
|
|
|
||
|
|
if __name__ == '__main__' :
|
||
|
|
'''
|
||
|
|
invert a network of the pair's mis-registrations to
|
||
|
|
estimate the mis-registrations wrt the Master date.
|
||
|
|
'''
|
||
|
|
|
||
|
|
main()
|