def StatsImage(self):
#Input files
source = os.path.join(self.Folder,"*.tif")
output = self.OutImage
listImages = glob.glob(source)
NumberOfImages = len(listImages)
#Get properties images
Type = gdal.GDT_Float32
driver = gdal.GetDriverByName('GTiff')
setup = gdal.Open(listImages[0],gdal.GA_ReadOnly)
Xsize = setup.RasterXSize
YSize = setup.RasterYSize
proj = setup.GetProjection()
geo = setup.GetGeoTransform()
#Create output image
ImageOut = driver.Create(output,Xsize,YSize,1,Type,['COMPRESS=LZW'])
ImageOut.SetProjection(proj)
ImageOut.SetGeoTransform(geo)
#Create log error file
LogFolder = os.path.join(os.path.dirname(output),"Log.txt",)
LogError = open(LogFolder,'w')
BadImages = utils.verifyImageDimension(listImages)
typeSt = self.Stats
if BadImages == 0:
for i in xrange(YSize):
aCom = numpy.zeros((NumberOfImages,1,Xsize))
for j in xrange(len(listImages)):
GetImages = gdal.Open(listImages[j],gdal.GA_ReadOnly)
band = GetImages.GetRasterBand(1).ReadAsArray(0,i,Xsize,1).astype(numpy.float16)
#Crop Nodata Values
if type(self.NoData) is float:
band = numpy.where(band == self.NoData,None,band)
aCom[j] = band
band = None
StatsBand = self.CalcStats(self.Stats,aCom)
ImageOut.GetRasterBand(1).WriteArray(StatsBand,0,i)
if not self.NoData == '':
ImageOut.GetRasterBand(1).SetNoDataValue(self.NoData)
aCom = None
StatsBand = None
perc = int(100.00*(float(i+1)/float(YSize)))
self.progress.emit(perc)
self.finished.emit(BadImages)
else:
self.finished.emit(BadImages)
def SavitzkyGolayFilter(self):
#Input files
source = os.path.join(self.inFolder, "*.tif")
desti = self.outFolder
listImages = sorted(glob.glob(source))
NumberOfImages = len(listImages)
#Get properties images
Type = gdal.GDT_Float32
driver = gdal.GetDriverByName('GTiff')
setup = gdal.Open(listImages[0], gdal.GA_ReadOnly)
Xsize = setup.RasterXSize
YSize = setup.RasterYSize
proj = setup.GetProjection()
geo = setup.GetGeoTransform()
listImageOut = []
#Create output's images
for li in listImages:
output = os.path.join(self.outFolder, os.path.basename(li))
imageOut = driver.Create(output, Xsize, YSize, 1, Type,
['COMPRESS=LZW'])
imageOut.SetProjection(proj)
imageOut.SetGeoTransform(geo)
listImageOut.append(imageOut)
BadImages = utils.verifyImageDimension(listImages)
if BadImages == 0:
for i in xrange(YSize):
print i
aCom = numpy.zeros((NumberOfImages, 1, Xsize), numpy.float32)
for j in xrange(len(listImages)):
GetImages = gdal.Open(listImages[j], gdal.GA_ReadOnly)
aCom[j] = GetImages.GetRasterBand(1).ReadAsArray(
0, i, Xsize, 1)
for k in xrange(Xsize):
signal = aCom[numpy.array(range(NumberOfImages)), 0, k]
if numpy.max(signal) != numpy.min(signal):
savGol = savgol_filter(signal, self.WindowSize,
self.Polynomial)
aCom[numpy.array(range(NumberOfImages)), 0, k] = savGol
for l in xrange(len(listImages)):
listImageOut[l].GetRasterBand(1).WriteArray(aCom[l], 0, i)
perc = int(100.00 * (float(i + 1) / float(YSize)))
aCom = None
self.progress.emit(perc)
self.finished.emit(0)
else:
self.finished.emit(BadImages)
def SavitzkyGolayFilter(self):
#Input files
source = os.path.join(self.inFolder,"*.tif")
desti = self.outFolder
listImages = sorted(glob.glob(source))
NumberOfImages = len(listImages)
#Get properties images
Type = gdal.GDT_Float32
driver = gdal.GetDriverByName('GTiff')
setup = gdal.Open(listImages[0],gdal.GA_ReadOnly)
Xsize = setup.RasterXSize
YSize = setup.RasterYSize
proj = setup.GetProjection()
geo = setup.GetGeoTransform()
listImageOut = []
#Create output's images
for li in listImages:
output = os.path.join(self.outFolder,os.path.basename(li))
imageOut = driver.Create(output,Xsize,YSize,1,Type,['COMPRESS=LZW'])
imageOut.SetProjection(proj)
imageOut.SetGeoTransform(geo)
listImageOut.append(imageOut)
BadImages = utils.verifyImageDimension(listImages)
if BadImages == 0:
for i in xrange(YSize):
print i
aCom = numpy.zeros((NumberOfImages,1,Xsize),numpy.float32)
for j in xrange(len(listImages)):
GetImages = gdal.Open(listImages[j],gdal.GA_ReadOnly)
aCom[j] = GetImages.GetRasterBand(1).ReadAsArray(0,i,Xsize,1)
for k in xrange(Xsize):
signal = aCom[numpy.array(range(NumberOfImages)),0,k]
if numpy.max(signal) != numpy.min(signal):
savGol = savgol_filter(signal,self.WindowSize,self.Polynomial)
aCom[numpy.array(range(NumberOfImages)),0,k] = savGol
for l in xrange(len(listImages)):
listImageOut[l].GetRasterBand(1).WriteArray(aCom[l],0,i)
perc = int(100.00*(float(i+1)/float(YSize)))
aCom = None
self.progress.emit(perc)
self.finished.emit(0)
else:
self.finished.emit(BadImages)
def HagensFilterCalc(self):
BadImages = utils.verifyImageDimension(self.inFolder)
if BadImages == 0:
#Get properties images
Type = gdal.GDT_Float32
driver = gdal.GetDriverByName('GTiff')
setup = gdal.Open(self.inFolder[0],gdal.GA_ReadOnly)
Xsize = setup.RasterXSize
YSize = setup.RasterYSize
proj = setup.GetProjection()
geo = setup.GetGeoTransform()
listImageOut = []
#Create output's images
for li in self.inFolder:
output = os.path.join(self.outFolder,os.path.basename(li))
imageOut = driver.Create(output,Xsize,YSize,1,Type,['COMPRESS=LZW'])
imageOut.SetProjection(proj)
imageOut.SetGeoTransform(geo)
listImageOut.append(imageOut)
#Create typical year
tYear = os.path.join(self.outFolder,'TypicalYear.tif')
typicalYearImage = driver.Create(tYear,Xsize,YSize,self.Composite,Type,['COMPRESS=LZW'])
typicalYearImage.SetProjection(proj)
typicalYearImage.SetGeoTransform(geo)
#Create images Quality pixels - Used in Create typical year
iQuality = os.path.join(self.outFolder,'QualityTypicalYear.tif')
imageQuality = driver.Create(iQuality,Xsize,YSize,self.Composite,Type,['COMPRESS=LZW'])
imageQuality.SetProjection(proj)
imageQuality.SetGeoTransform(geo)
NumberOfImages = len(self.inFolder)
#Process BIL
for i in xrange(YSize):
iArray = numpy.zeros((NumberOfImages,1,Xsize),numpy.float32)
iFlag = numpy.zeros((NumberOfImages,1,Xsize),numpy.byte)
#Get Values in Image
for j in xrange(len(self.inFolder)):
GetImages = gdal.Open(self.inFolder[j],gdal.GA_ReadOnly)
GetImagesFlags = gdal.Open(self.inFlag[j],gdal.GA_ReadOnly)
iArray[j] = GetImages.GetRasterBand(1).ReadAsArray(0,i,Xsize,1)
iFlag[j] = GetImagesFlags.GetRasterBand(1).ReadAsArray(0,i,Xsize,1)
#Products Hagens Filter
typicalYear = HagensFilter_tools.AveregeYearDoy(iArray,iFlag,self.Composite,0,Xsize)[0]
arrayQA = HagensFilter_tools.AveregeYearDoy(iArray,iFlag,self.Composite,0,Xsize)[1]
devAveregeAnual = HagensFilter_tools.DevAveregeAnual(iArray,iFlag,self.Composite,typicalYear,0,Xsize)
devNeighborhoodDay = HagensFilter_tools.DevNeighborhoodDay(iArray,iFlag,0,Xsize)
devNeighborhoodAnual = HagensFilter_tools.DevNeighborhoodAnual(iArray,iFlag,self.Composite,0,Xsize)
fillGaps = HagensFilter_tools.FillGaps(iArray,iFlag,self.Composite,typicalYear,devAveregeAnual,devNeighborhoodDay,devNeighborhoodAnual,0,Xsize)
#Update Typical Year
for k in xrange(int(self.Composite)):
typicalYearImage.GetRasterBand(k+1).WriteArray(typicalYear[k],0,i)
imageQuality.GetRasterBand(k+1).WriteArray(arrayQA[k],0,i)
#Update Hagens Filter
for l in xrange(len(self.inFolder)):
listImageOut[l].GetRasterBand(1).WriteArray(fillGaps[l],0,i)
perc = int(100.00*(float(i+1)/float(YSize)))
iArray = None
iFlag = None
self.progress.emit(perc)
self.finished.emit(0)
else:
self.finished.emit(BadImages)
def StatsImage(self):
#Input files
source = os.path.join(self.Folder, "*.tif")
output = self.OutImage
listImages = glob.glob(source)
NumberOfImages = len(listImages)
#Get properties images
Type = gdal.GDT_Float32
driver = gdal.GetDriverByName('GTiff')
setup = gdal.Open(listImages[0], gdal.GA_ReadOnly)
Xsize = setup.RasterXSize
YSize = setup.RasterYSize
proj = setup.GetProjection()
geo = setup.GetGeoTransform()
#Create output image
ImageOut = driver.Create(output, Xsize, YSize, 1, Type,
['COMPRESS=LZW'])
ImageOut.SetProjection(proj)
ImageOut.SetGeoTransform(geo)
#Create log error file
LogFolder = os.path.join(
os.path.dirname(output),
"Log.txt",
)
LogError = open(LogFolder, 'w')
BadImages = utils.verifyImageDimension(listImages)
typeSt = self.Stats
if BadImages == 0:
for i in xrange(YSize):
aCom = numpy.zeros((NumberOfImages, 1, Xsize))
for j in xrange(len(listImages)):
GetImages = gdal.Open(listImages[j], gdal.GA_ReadOnly)
band = GetImages.GetRasterBand(1).ReadAsArray(
0, i, Xsize, 1).astype(numpy.float16)
#Crop Nodata Values
if type(self.NoData) is float:
band = numpy.where(band == self.NoData, None, band)
aCom[j] = band
band = None
StatsBand = self.CalcStats(self.Stats, aCom)
ImageOut.GetRasterBand(1).WriteArray(StatsBand, 0, i)
if not self.NoData == '':
ImageOut.GetRasterBand(1).SetNoDataValue(self.NoData)
aCom = None
StatsBand = None
perc = int(100.00 * (float(i + 1) / float(YSize)))
self.progress.emit(perc)
self.finished.emit(BadImages)
else:
self.finished.emit(BadImages)
