[Numpy-discussion] Help making better use of numpy array functions
josef.pktd at gmail.com
josef.pktd at gmail.com
Wed Nov 25 16:22:34 EST 2009
On Wed, Nov 25, 2009 at 4:13 PM, mdekauwe <mdekauwe at gmail.com> wrote:
>
> 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)
does an intermediate array help?
lst2 = np.where((data > -900.0) & (lst < -900.0), data, lst)
lst = np.where((data > -900.0) & (lst > -900.0), 5.0, lst2)
I didn't read through all the loops to see what would be a better way to do it.
Josef
>
> 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)
>>
>>
>>
>>
>
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