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)
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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