[Numpy-discussion] Find Daily max - create lists using date and add hourly data to that list for the day

questions anon questions.anon at gmail.com
Wed May 21 20:27:26 EDT 2014


I have hourly 2D temperature data in a monthly netcdf and I would like to
find the daily maximum temperature. The shape of the netcdf is (744, 106,
193)

I would like to use the year-month-day as a new list name (i.e. 2009-03-01,
2009-03-02....2009-03-31) and then add each of the hours worth of
temperature data to each corresponding list. Therefore each new list should
contain 24 hours worth of data and the shape should be (24,106,193) . This
is the part I cannot seem to get to work. I am using datetime and then
groupby to group by date but I am not sure how to use the output to make a
new list name and then add the data for that day into that list. see below
and attached for my latest attempt.  Any feedback will be greatly
appreciated.



from netCDF4 import Dataset

import numpy as np

import matplotlib.pyplot as plt

from mpl_toolkits.basemap import Basemap

from netcdftime import utime

from datetime import datetime as dt

import os

import gc

from numpy import *

import pytz

from itertools import groupby


MainFolder=r"/DATA/2009/03"

dailydate=[]

alltime=[]

lists={}



ncvariablename='T_SFC'


for (path, dirs, files) in os.walk(MainFolder):

for ncfile in files:

print ncfile

fileext='.nc'

if ncfile.endswith(ncvariablename+'.nc'):

print "dealing with ncfiles:", path+ncfile

ncfile=os.path.join(path,ncfile)

ncfile=Dataset(ncfile, 'r+', 'NETCDF4')

variable=ncfile.variables[ncvariablename][:,:,:]

TIME=ncfile.variables['time'][:]

ncfile.close()

 for temp, time in zip((variable[:]),(TIME[:])):

cdftime=utime('seconds since 1970-01-01 00:00:00')

ncfiletime=cdftime.num2date(time)

timestr=str(ncfiletime)

utc_dt = dt.strptime(timestr, '%Y-%m-%d %H:%M:%S')

au_tz = pytz.timezone('Australia/Sydney')

local_dt = utc_dt.replace(tzinfo=pytz.utc).astimezone(au_tz)

alltime.append(local_dt)

 for k, g in groupby(alltime, key=lambda d: d.date()):

kstrp_local=k.strftime('%Y-%m-%d_%H')

klocal_date=k.strftime('%Y-%m-%d')

dailydate.append(klocal_date)

for n in dailydate:

lists[n]=[]

lists[n].append(temp)


  big_array=np.ma.concatenate(lists[n])

DailyTemp=big_array.max(axis=0)
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