Excellent, thank you.
I just realised this does not work with my data because of the extra
dimension.
I have a mask that matches my 2-dimensional array but my data is for every
hour over a month so the arrays do not match. Is there a way to make them
match or mask each time?
thanks again
This is some of my code:
for ncfile in files:
if ncfile[-3:]=='.nc':
print "dealing with ncfiles:",
path+ncfile
ncfile=os.path.join(path,ncfile)
ncfile=Dataset(ncfile, 'r+', 'NETCDF4')
TSFC=ncfile.variables['T_SFC'][:]
TIME=ncfile.variables['time'][:]
fillvalue=ncfile.variables['T_SFC']._FillValue
TSFC=MA.masked_values(TSFC, fillvalue)
ncfile.close()
TSFC=MA.masked_array(TSFC,
mask=newmask.mask)
On Tue, Nov 22, 2011 at 11:21 AM, Olivier Delalleau
If your new array is x, you can use:
numpy.ma.masked_array(x, mask=mask.mask)
-=- Olivier
2011/11/21 questions anon
I am trying to mask one array using another array.
I have created a masked array using mask=MA.masked_equal(myarray, 0), that looks something like: [1 - - 1, 1 1 - 1, 1 1 1 1, - 1 - 1]
I have an array of values that I want to mask whereever my mask has a a '-'. how do I do this? I have looked at http://www.cawcr.gov.au/bmrc/climdyn/staff/lih/pubs/docs/masks.pdf but the command:
d = array(a, mask=c.mask()
results in this error: TypeError: 'numpy.ndarray' object is not callable
I basically want to do exactly what that article does in that equation.
Any feedback will be greatly appreciated.
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