# [SciPy-User] How to ignore NaN values and -32767 in numpy array

questions anon questions.anon@gmail....
Wed Aug 17 01:17:26 CDT 2011

I am trying to run simple stats on a bunch of monthly netcdfs files with
hourly temperature data. With help from this list I am able to loop through
a calculate the mean, but in doing this I have discovered that there are a
some hours that have no values or -32767. I am sure there are some cases
where I could slice out the section (if I know where they are) but is there
a way I could just ignore these hours and calculate the mean?
I have found something called "numpy.isnan" but this does not seem to work.

from netCDF4 import Dataset
import matplotlib.pyplot as plt
import numpy as N
from mpl_toolkits.basemap import Basemap
import os

MainFolder=r"E:/temp_samples/"

all_TSFC=[]
for (path, dirs, files) in os.walk(MainFolder):
for dir in dirs:
print dir
path=path+'/'
for ncfile in files:
if ncfile[-3:]=='.nc':
ncfile=os.path.join(path,ncfile)
ncfile=Dataset(ncfile, 'r+', 'NETCDF4')
TSFC=ncfile.variables['T_SFC'][:]
LAT=ncfile.variables['latitude'][:]
LON=ncfile.variables['longitude'][:]
TIME=ncfile.variables['time'][:]
fillvalue=ncfile.variables['T_SFC']._FillValue
ncfile.close()

#combine all TSFC to make one array for analyses
all_TSFC.append(TSFC)

big_array=N.concatenate(all_TSFC)
Mean=big_array.mean(axis=0)
print "the mean is", Mean

#plot output summary stats
map = Basemap(projection='merc',llcrnrlat=-40,urcrnrlat=-33,

llcrnrlon=139.0,urcrnrlon=151.0,lat_ts=0,resolution='i')
x,y=map(*N.meshgrid(LON,LAT))
CS = map.contourf(x,y,Mean, cmap=plt.cm.jet)
l,b,w,h =0.1,0.1,0.8,0.8
cax = plt.axes([l+w+0.025, b, 0.025, h])
plt.colorbar(CS,cax=cax, drawedges=True)

plt.show()
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