[Numpy-discussion] numpy sum each month and then numpy mean of all months

[questions anon]

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.
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