Hello all, I have netcdf files that contain hourly rainfall data. Each netcdf file includes one months worth of hours and I have 10 years worth of data. I would like to calculate the sum of each month and then the mean of these summed months across all of the years. I have no problem firstly calculating the sum of each month but then I come up with a mask-size error when I try to calculate the mean of those months. So somehow I am not combining my summed months correctly? Below is the code I am using (focusing on just january at this stage) and below that is the error. Any feedback will be greatly appreciated. from netCDF4 import Dataset import numpy as N import matplotlib.pyplot as plt from mpl_toolkits.basemap import Basemap import os shapefile1="/Users/REGIONS" OutputFolder=r"/Users/rainmonthlysummarystats/" fileforlatlon=Dataset("/Users/WRFsample/IDV71000_VIC_T_SFC.nc", 'r+', 'NETCDF4') LAT=fileforlatlon.variables['latitude'][:] LON=fileforlatlon.variables['longitude'][:] def summaryplots(variable): if variable=='RAIN': ncvariablename='PCP_SFC' MainFolder=r"/Data/WRFmonthly/" ticks=[0, 25, 50, 75, 100, 125, 150, 175, 200] cmap=plt.cm.jet Jan="01" monthseason="Jan" summonthlyrain_all=[] all_variabledata=[] for (path, dirs, files) in os.walk(MainFolder): if os.path.basename(path)==Jan: for ncfile in files: fileext=ncvariablename+'.nc' if ncfile.endswith(fileext): print "dealing with ncfiles:", path+ncfile ncfile=os.path.join(path,ncfile) ncfile=Dataset(ncfile, 'r+', 'NETCDF4') variable=ncfile.variables[ncvariablename][:,:,:] ncfile.close() all_variabledata.append(variable) #combine all data from the chosen variable to make one array for analyses big_array=N.ma.concatenate(all_variabledata) SUM=big_array.sum(axis=0) summonthlyrain_all.append(SUM) del all_variabledata[:] big_array_sumrain=N.ma.concatenate(summonthlyrain_all) MEAN=big_array_sumrain.mean(axis=0) #plot output summary stats map = Basemap(projection='merc',llcrnrlat=-40,urcrnrlat=-33, llcrnrlon=139.0,urcrnrlon=151.0,lat_ts=0,resolution='i') map.drawcoastlines() map.drawstates() map.readshapefile(shapefile1, 'DSE_REGIONS') x,y=map(*N.meshgrid(LON,LAT)) plottitle=ncvariablename+'_mean_'+monthseason plt.title(plottitle) CS = map.contourf(x,y,MEAN, ticks, cmap=cmap) 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.savefig((os.path.join(OutputFolder, plottitle+'.png'))) plt.show() plt.close() summaryplots('RAIN') MaskError Traceback (most recent call last) /Applications/Canopy.app/appdata/canopy-1.3.0.1715.macosx-x86_64/Canopy.app/Contents/lib/python2.7/site-packages/IPython/utils/py3compat.pyc in execfile(fname, *where) 202 else: 203 filename = fname --> 204 __builtin__.execfile(filename, *where) /Users/slburns/Dropbox/Python_code/WRFoutputs/plot_variable_sum_monthlyrain_percentiles_test.py in <module>() 71 72 ---> 73 summaryplots('RAIN') 74 75 /Users/slburns/Dropbox/Python_code/WRFoutputs/plot_variable_sum_monthlyrain_percentiles_test.py in summaryplots(variable) 62 plottitle=ncvariablename+'_mean_'+monthseason 63 plt.title(plottitle) ---> 64 CS = map.contourf(x,y,MEAN, ticks, cmap=cmap) 65 l,b,w,h =0.1,0.1,0.8,0.8 66 cax = plt.axes([l+w+0.025, b, 0.025, h]) /Users/slburns/Applications/User/lib/python2.7/site-packages/mpl_toolkits/basemap/__init__.pyc in with_transform(self, x, y, data, *args, **kwargs) 519 # convert lat/lon coords to map projection coords. 520 x, y = self(x,y) --> 521 return plotfunc(self,x,y,data,*args,**kwargs) 522 return with_transform 523 /Users/slburns/Applications/User/lib/python2.7/site-packages/mpl_toolkits/basemap/__init__.pyc in contourf(self, x, y, data, *args, **kwargs) 3670 # combine with data mask. 3671 mask = np.logical_or(ma.getmaskarray(data),xymask) -> 3672 data = ma.masked_array(data,mask=mask) 3673 CS = ax.contourf(x,y,data,*args,**kwargs) 3674 except: /Users/slburns/Applications/User/lib/python2.7/site-packages/numpy/ma/core.pyc in __new__(cls, data, mask, dtype, copy, subok, ndmin, fill_value, keep_mask, hard_mask, shrink, **options) 2708 msg = "Mask and data not compatible: data size is %i, " + 2709 "mask size is %i." -> 2710 raise MaskError(msg % (nd, nm)) 2711 copy = True 2712 # Set the mask to the new value MaskError: Mask and data not compatible: data size is 193, mask size is 20458.