I tried redoing the internal logic for example by using the where function but I can't seem to work out how to match up the logic. For example (note slightly different from above). If I change the main loop to
lst = np.where((data > -900.0) & (lst < -900.0), data, lst) lst = np.where((data > -900.0) & (lst > -900.0), 5.0, lst) If I then had a data array value of 10.0 and lst array value of -999.0. In this scenario the first statement would set the LST value to 10.0. However when you run the second statement, data is still bigger than the undefined (-999.0) but now so is the LST, hence the lst is set to 5.0 This doesn't match with the logic of if data[i,j] > -900.: if lst[i,j] < -900.: lst[i,j] = data[i,j] elif lst[i,j] > -900.: lst[i,j] = 5.0 as it would never get to the second branch under this logic. Does anyone have any suggestions on how to match up the logic? mdekauwe wrote: > > Hi I have written some code and I would appreciate any suggestions to make > better use of the numpy arrays functions to make it a bit more efficient > and less of a port from C. Any tricks are thoughts would be much > appreciated. > > The code reads in a series of images, collects a running total if the > value is valid and averages everything every 8 images. > > Code below... > > Thanks in advance... > > #!/usr/bin/env python > > """ > Average the daily LST values to make an 8 day product... > > Martin De Kauwe > 18th November 2009 > """ > import sys, os, glob > import numpy as np > import matplotlib.pyplot as plt > > > def averageEightDays(files, lst, count, numrows, numcols): > > day_count = 0 > # starting day - tag for output file > doy = 122 > > # loop over all the images and average all the information > # every 8 days... > for fname in glob.glob(os.path.join(path, files)): > current_file = fname.split('/')[8] > year = current_file.split('_')[2][0:4] > > try: > f = open(fname, 'rb') > except IOError: > print "Cannot open outfile for read", fname > sys.exit(1) > > data = np.fromfile(f, dtype=np.float32).reshape(numrows, numcols) > f.close() > > # if it is day 1 then we need to fill up the holding array... > # copy the first file into the array... > if day_count == 0: > lst = data > for i in xrange(numrows): > for j in xrange(numcols): > # increase the pixel count if we got vaild data > (undefined = -999.0 > if lst[i,j] > -900.: > count[i,j] = 1 > day_count += 1 > > # keep a running total of valid lst values in an 8 day sequence > elif day_count > 0 and day_count <= 7: > for i in xrange(numrows): > for j in xrange(numcols): > # lst valid pixel? > if data[i,j] > -900.: > # was the existing pixel valid? > if lst[i,j] < -900.: > lst[i,j] = data[i,j] > count[i,j] = 1 > else: > lst[i,j] += data[i,j] > count[i,j] += 1 > day_count += 1 > > # need to average previous 8 days and write to a file... > if day_count == 8: > for i in xrange(numrows): > for j in xrange(numcols): > if count[i,j] > 0: > lst[i,j] = lst[i,j] / count[i,j] > else: > lst[i,j] = -999.0 > > day_count = 0 > doy += 8 > > lst, count = write_outputs(lst, count, year, doy) > > # it is possible we didn't have enough slices to do the last 8day > avg... > # but if we have more than one day we shall use it > # need to average previous 8 days and write to a file... > if day_count > 1: > for i in xrange(numrows): > for j in xrange(numcols): > if count[i,j] > 0: > lst[i,j] = lst[i,j] / count[i,j] > else: > lst[i,j] = -999.0 > > day_count = 0 > doy += 8 > > lst, count = write_outputs(lst, count, year, doy) > > def write_outputs(lst, count, year, doy): > path = "/users/eow/mgdk/research/HOFF_plots/LST/8dayLST" > outfile = "lst_8day1030am_" + str(year) + str(doy) + ".gra" > > try: > of = open(os.path.join(path, outfile), 'wb') > except IOError: > print "Cannot open outfile for write", outfile > sys.exit(1) > > outfile2 = "pixelcount_8day1030am_" + str(year) + str(doy) + ".gra" > try: > of2 = open(os.path.join(path, outfile2), 'wb') > except IOError: > print "Cannot open outfile for write", outfile2 > sys.exit(1) > > # empty stuff and zero 8day counts > lst.tofile(of) > count.tofile(of2) > of.close() > of2.close() > lst = 0.0 > count = 0.0 > > return lst, count > > > if __name__ == "__main__": > > numrows = 332 > numcols = 667 > > path = "/users/eow/mgdk/research/HOFF_plots/LST/gridded_03/" > lst = np.zeros((numrows, numcols), dtype=np.float32) > count = np.zeros((numrows, numcols), dtype=np.int) > averageEightDays('lst_scr_2006*.gra', lst, count, numrows, numcols) > > > lst = 0.0 > count = 0.0 > averageEightDays('lst_scr_2007*.gra', lst, count, numrows, numcols) > > > > -- View this message in context: http://old.nabble.com/Help-making-better-use-of-numpy-array-functions-tp26503657p26520383.html Sent from the Numpy-discussion mailing list archive at Nabble.com. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion