def build_multiband_image(rootDIR, outName, newfoldername, find, drivercode, ndvalue):
outdir = create_output_dir(rootDIR, newfoldername)
print "\nOutputting files to : {0}".format(outdir)
print "\nFinding HDF files in directory/subfolders: {0}".format(rootDIR)
hdfs = find_files(rootDIR, ".hdf")
print "\tFound {0} files.".format(len(hdfs))
print "\nGetting images to process of type {0}...".format(find)
toprocess = []
for hdf in hdfs:
sds = get_hdf_subdatasets(hdf)
for ds in sds:
if find.upper() in ds[1].upper():
toprocess.append(ds[0])
print "\t\t{0}".format(ds[0])
bands = len(toprocess)
print "\tFound {0} images of type {1}.".format(bands, find)
print "\nGetting output parameters..."
rows, cols, datatype, geotransform, projection = open_image(toprocess[0])
print "\tParameters: rows: {0}, cols: {1}, datatype: {2}, projection: {3}.".format(rows, cols, datatype, projection)
outfile = os.path.join(outdir, outName) + ".tif"
print "\nOutput file is: {0}".format(outfile)
outds = create_output_raster(outfile, cols, rows, bands, datatype, drivername=drivercode)
print "\tCreated output file."
print"\nAdding bands to output file..."
for i in range(0, bands):
print "\tProcessing band {0} of {1}...".format(i + 1, bands)
image = gdal.Open(toprocess[i])
band = image.GetRasterBand(1)
outband = outds.GetRasterBand(i + 1)
print "\t\tReading band data to array..."
data = band.ReadAsArray(0, 0, cols, rows)
print "\t\tWriting band data to output band..."
outband.WriteArray(data, 0, 0)
outband.SetNoDataValue(ndvalue)
outband.FlushCache()
del data, outband
image = ""
print "\tFinished adding bands to output file."
print "\nSetting transform and projection..."
outds.SetGeoTransform(geotransform)
outds.SetProjection(projection)
outDS = ""
print "\nProcess completed."
def get_incorrect_px_curves(inputpath, referencepath, vitimeseriespath, startdoy, interval, outputpath=None, nodata=None):
if not outputpath:
root = os.path.dirname(inputpath)
outputpath = create_output_dir(root, "plots")
#Open images
inputimage = build_multiband_image.open_image(inputpath, returnimage=True)
referenceimage = build_multiband_image.open_image(referencepath, returnimage=True)
timeseries = build_multiband_image.open_image(vitimeseriespath, returnimage=True)
#Get band 1 of input and reference images and read as arrays
inband = inputimage[5].GetRasterBand(1)
inarray = inband.ReadAsArray(0, 0, inputimage[0], inputimage[1])
inband = ""
refband = referenceimage[5].GetRasterBand(1)
refarray = refband.ReadAsArray(0, 0, referenceimage[0], referenceimage[1])
refband = ""
#Close in and ref images
#Find unique values in the input image
uniquevals = set(np.unique(inarray).tolist())
uniquevals.remove(nodata)
print uniquevals
#Iterate through pixels in images, comparing arrays for each value in input image, making note of tested values and excluding them from comparison with 0 value in input image
#Return pixel coordinates and the identified and true identities of the pixels from the input and reference images
coordinatelist = {}
for value in uniquevals:
coordinatelist[value] = []
numincorrect = 0
for col in range(0, inputimage[0]):
for row in range(0, inputimage[1]):
if (inarray[row, col] != 0) and (inarray[row, col] != refarray[row, col]) and (inarray[row, col] != nodata):
if refarray[row, col] in uniquevals:
coordinatelist[refarray[row, col]].append([col, row, inarray[row, col], refarray[row, col]])
numincorrect += 1
else:
coordinatelist[0].append([col, row, inarray[row, col], refarray[row, col]])
numincorrect += 1
elif (inarray[row,col] == 0) and (refarray[row, col] in uniquevals):
coordinatelist[refarray[row, col]].append([col, row, inarray[row, col], refarray[row, col]])
numincorrect += 1
#For each returned pixel, extract and plot the curve from vitimeseries and export plot as image; be sure to label plot correctly
bandcnt = timeseries[5].RasterCount
arrays = {}
for i in range(1, bandcnt + 1):
band = timeseries[5].GetRasterBand(i)
data = band.ReadAsArray(0, 0, timeseries[0], timeseries[1])
arrays[i] = data
print("Found {0} incorrect pixels to process...".format(numincorrect))
plotvalues = []
i = 0
for group, pixels in coordinatelist.items():
for pixel in pixels:
pxvalues = {}
for key, val in arrays.items():
doy = interval * (key - 1) + startdoy
if doy >= 366:
t = floor((doy - 366)/interval)
doy = interval * t + 366
pxvalues[doy] = val[pixel[1], pixel[0]]
color = color_picker(i)
pixel.append(pxvalues)
pixel.append(color)
plotvalues.append(pixel)
i += 1
pdf = PdfPages(os.path.join(outputpath, "plots.pdf"))
for pixel in plotvalues:
figure = plot_pixel(pixel, outputpath, color=pixel[5])
pdf.savefig()
plt.close(figure)
pdf.close()