def getLevs(dat, zmin=0, zmax=100000, convertPressureUnit=None):
"""
TBD
"""
from Scientific.IO.NetCDF import NetCDFFile as ncf
filename = cfile(dat)
fileobj = ncf(filename)
min_lev = zmin
max_lev = zmax
my_levs = None
levname = None
for varname in fileobj.variables:
if varname in [
'level', 'levels', 'lev', 'levs', 'depth', 'deptht', 'DEPTH',
'DEPTHT', 'plev'
]:
levname = varname
levunits = fileobj.variables[levname].units
for lev in fileobj.variables[levname].getValue():
#print lev
if min_lev <= lev <= max_lev:
if convertPressureUnit:
if convertPressureUnit == 'hPaToPa':
lev = lev * 100
if convertPressureUnit == 'PaTohPa':
lev = lev / 100
if my_levs:
my_levs = my_levs + ',' + str(int(lev))
else:
my_levs = str(int(lev))
return my_levs
def getLevs(dat, zmin, zmax, convertPressureUnit=None):
from Scientific.IO.NetCDF import NetCDFFile as ncf
filename = dat.baseFiles()
fileobj = ncf(filename)
min_lev = zmin
max_lev = zmax
my_levs = None
levname = None
for varname in fileobj.variables:
if varname in ["level", "levels", "lev", "levs", "depth", "deptht", "DEPTH", "DEPTHT", "plev"]:
levname = varname
for lev in fileobj.variables[levname].getValue():
# print lev
if min_lev <= lev <= max_lev:
if convertPressureUnit:
if convertPressureUnit == "hPaToPa":
lev = lev * 100
if convertPressureUnit == "PaTohPa":
lev = lev / 100
if my_levs:
my_levs = my_levs + "," + str(int(lev))
else:
my_levs = str(int(lev))
return my_levs
def fileHasVar(filename,varname):
"""
returns True if FILENAME has variable VARNAME
"""
from Scientific.IO.NetCDF import NetCDFFile as ncf
rep=False
clogger.debug("opening "+filename)
try :
fileobj=ncf(filename)
except:
clogger.error("Issue opening file "+filename)
return False
for filevar in fileobj.variables :
if filevar == varname :
rep=True
break
fileobj.close()
return(rep)
def varOfFile(filename) :
"""
returns the name of the unique non-dimension variable in
NetCDF file FILENAME, or None if it is not unique
"""
from Scientific.IO.NetCDF import NetCDFFile as ncf
varname=None
fileobj=ncf(filename)
#import NetCDF4
#fileobj=netCDF4.Dataset(filename)
for filevar in fileobj.variables :
if ((filevar not in fileobj.dimensions) and
not re.findall("^time_",filevar) and
not re.findall("_bnds$",filevar) ):
if varname is None :
varname=filevar
else :
clogger.debug("Got at least two variables (%s and %s) "
"and no direction to choose - File is %s"%\
(varname,filevar,filename))
return(None)
fileobj.close()
return(varname)
def cread(datafile,varname=None):
import re
if not datafile : return(None)
if re.findall(".png$",datafile) :
subprocess.Popen(["display",datafile,"&"])
elif re.findall(".nc$",datafile) :
clogger.debug("reading NetCDF file %s"%datafile)
if varname is None: varname=varOfFile(datafile)
if varname is None: return(None)
from Scientific.IO.NetCDF import NetCDFFile as ncf
fileobj=ncf(datafile)
#import netCDF4
#fileobj=netCDF4.Dataset(datafile)
# Note taken from the CDOpy developper : .data is not backwards
# compatible to old scipy versions, [:] is
data=fileobj.variables[varname][:]
fillv=fileobj.variables[varname]._FillValue
import numpy.ma
rep= numpy.ma.array(data,mask = data==fillv)
fileobj.close()
return(rep)
else :
clogger.error("cannot yet handle %s"%datafile)
return None
fname = sys.argv[4+fnum]
m = rcmre.search(fname)
if m:
label = m.group(1)
year0 = int(m.group(2))
year1 = int(m.group(3))
elif fname.startswith('ERAINT'):
label = 'ERAINT'
else:
label = 'CRU'
CRUnum = fnum
if not omitcru or label != 'CRU':
labels.append(label)
file = ncf(fname,'r')
var = file.variables[varname]
vardata = var.getValue()
if label == 'regcm411' and varname!='RT':
vardata = var[:,0]
else:
vardata = var.getValue()
if hasattr(var,'missing_value'):
fillval = var.missing_value
maskeddata = ma.masked_where(vardata==fillval,vardata)
elif hasattr(var,'_FillValue'):
fillval = var._FillValue
maskeddata = ma.masked_where(vardata==fillval,vardata)
if label == 'CRU':
globalmask = maskeddata.mask
levels={
'eur': {'t2avg':np.arange(-5,6,0.5), 't2max':np.arange(-5,6,0.5), 't2min':np.arange(-5,6,0.5),'pcpavg':np.arange(-5,6,0.5)},
# 'eur': {'t2avg':np.arange(-2.5,2.6,0.5), 't2max':np.arange(-2.5,2.6,0.5), 't2min':np.arange(-2.5,2.6,0.5),'pcpavg':np.arange(-5,6,0.5)},
'ce': {'t2avg':np.arange(-5,6,0.5), 't2max':np.arange(-5,6,0.5), 't2min':np.arange(-5,6,0.5),'pcpavg':np.arange(-5,6,0.5)}
}[sys.argv[1]]
bufferzonewidth={'ce':55,'eur':20}[sys.argv[1]]
outpostfix=sys.argv[1]
parallelsdis={'ce':5.,'eur':10}[sys.argv[1]]
meridiansdis={'ce':5.,'eur':10}[sys.argv[1]]
if year1==year2:
headerfilename='%s.%d.%s.%s.nc' % (inprefix, year1, ncvars[0], timespan)
else:
headerfilename='%s.%d-%d.%s.%s.nc' % (inprefix, year1, year2, ncvars[0], timespan)
ff = ncf(headerfilename,'r')
"""
xlon = headerfile.variables['longitude'].getValue()
xlat = headerfile.variables['latitude'].getValue()
m = Basemap(projection='cyl',llcrnrlat=xlat[0], urcrnrlat=xlat[-1], llcrnrlon=xlon[0], urcrnrlon=xlon[-1], resolution='l')
"""
lat_0 = float(ff.latitude_of_projection_origin)
lon_0 = float(ff.longitude_of_projection_origin)
lat_1 = float(ff.standard_parallel[0])
lat_2 = float(ff.standard_parallel[1])
grdis = float(ff.grid_size_in_meters)
nx = int(ff.dimensions['x'])
inprefix='CORDEX-Africa-sec-noemiss-CRU-af'
year1=1990
year2=1990
timespan='yseasavg'
seasons = ('DJF','MAM','JJA','SON')
levels={
'eur': {'t2avg':range(-10,11), 't2max':range(-10,11), 't2min':range(-10,11),'pcpavg':range(-10,10)},
# 'eur': {'t2avg':np.arange(-2.5,2.6,0.5), 't2max':np.arange(-2.5,2.6,0.5), 't2min':np.arange(-2.5,2.6,0.5),'pcpavg':np.arange(-5,6,0.5)},
'ce': {'t2avg':range(-5,6), 't2max':range(-8,9), 't2min':range(-5,6),'pcpavg':range(-3,4)}
}[sys.argv[1]]
bufferzonewidth={'ce':55,'eur':12}[sys.argv[1]]
outpostfix=sys.argv[1]
parallelsdis={'ce':5.,'eur':10}[sys.argv[1]]
meridiansdis={'ce':5.,'eur':10}[sys.argv[1]]
headerfile = ncf(sys.argv[2],'r')
xlon = headerfile.variables['lon'].getValue()
xlat = headerfile.variables['lat'].getValue()
m = Basemap(projection='cyl',llcrnrlat=xlat[0], urcrnrlat=xlat[-1], llcrnrlon=xlon[0], urcrnrlon=xlon[-1], resolution='l')
x,y = m(xlon,xlat)
for v in ncvars:
if year1==year2:
infilename='%s.%d.%s.%s' % (inprefix, year1, v, timespan)
else:
infilename='%s.%d-%d.%s.%s' % (inprefix, year1, year2, v, timespan)
if v == 'RT':
infilename += '.perc.nc'
else:
infilename += '.nc'
#!/usr/bin/env python
from Scientific.IO.NetCDF import NetCDFFile as ncf
import sys
from datetime import date
refdate = date(1949,12,1)
year1=int(sys.argv[2])
year2=int(sys.argv[3])
print year1, year2
ff = ncf(sys.argv[1],'a')
ff.createDimension('bnds',2)
tb = ff.createVariable('time_bnds','d',('time','bnds'))
t = ff.variables['time']
tbdata = []
tdata = []
for y in range(year1,year2+1):
for m in range(1,13):
mp = (m+1)%12
yp = y
if mp == 0:
mp = 12
if mp == 1:
yp += 1
_date1 = date(y,m,1)
_date2 = date(yp,mp,1)
def zonmean_interpolation(dat1,
dat2=None,
vertical_levels=None,
cdo_horizontal_grid='r1x90'):
"""
Interpolates the zonal mean field dat1 via two possible ways:
- either by providing a target zonal field dat2 => dat1 is regridded both horizontally and vertically on dat2
- or by providing a list of vertical levels => dat1 is regridded horizontally on the cdo_horizontal_grid
(default='r1x90'), and vertically on the list of vertical levels
The user can provide the vertical levels (in Pa) like this:
vertical_levels=[100000,85000,50000,20000,...] # or
vertical_levels='100000,85000,50000,20000'
Before the computations, the function checks the unit of the vertical axis;
it is converted to Pa if necessary directly in the netcdf file(s) corresponding to dat1(2).
>>> dat = ds(project='CMIP5',model='IPSL-CM5A-LR',variable='ua',period='1980-1985',
experiment='historical',table='Amon')
>>> ref = ds(project='ref_pcmdi',variable='ua',product='ERAINT')
>>> zonmean_dat = zonmean(time_average(dat))
>>> zonmean_ref = zonmean(time_average(ref))
>>> dat_interpolated_on_ref = zonmean_interpolation(zonmean_dat,zonmean_ref)
>>> dat_interpolated_on_list_of_levels = zonmean_interpolation(zonmean_dat,vertical_levels='100000,85000,50000,20000,10000,5000,2000,1000')
"""
from climaf.anynetcdf import ncf
file1 = cfile(dat1)
ncfile1 = ncf(file1)
# -- First, we check the unit of the vertical dimension of file1
levname1 = None
for varname in ncfile1.variables:
if varname.lower() in [
'level', 'levels', 'lev', 'levs', 'depth', 'deptht', 'plev'
]:
levname1 = varname
if not levname1:
print 'Name of the vertical axis not found for dat1'
levunits1 = ncfile1.variables[levname1].units
if levunits1.lower() in ['hpa', 'millibar', 'mbar', 'hectopascal']:
# -- Multiplier par 100
cmd1 = 'ncap2 -As "' + levname1 + '=' + levname1 + '*100" ' + file1 + ' ' + file1
cmd2 = 'ncatted -O -a units,' + levname1 + ',o,c,Pa ' + file1
print cmd1
print cmd2
os.system(cmd1)
os.system(cmd2)
# -> The vertical axis of file1 is now set to Pa
#
# -- Second, we check the unit of the vertical dimension of file2
if dat2:
file2 = cfile(dat2)
ncfile2 = ncf(file2)
levname2 = None
for varname in ncfile2.variables:
if varname.lower() in [
'level', 'levels', 'lev', 'levs', 'depth', 'deptht', 'plev'
]:
levname2 = varname
if not levname2:
print 'Name of the vertical axis not found for dat2'
levunits2 = ncfile2.variables[levname2].units
levValues2 = ncfile2.variables[levname2].getValue()
if levunits2.lower() in ['hpa', 'millibar', 'mbar', 'hectopascal']:
# -- Multiplier par 100
cmd1 = 'ncap2 -As "' + levname2 + '=' + levname2 + '*100" ' + file2 + ' ' + file2
cmd2 = 'ncatted -O -a units,' + levname2 + ',o,c,Pa ' + file2
print cmd1
print cmd2
os.system(cmd1)
os.system(cmd2)
# -> The vertical axis of file2 is now set to Pa in the netcdf file
scale = 100.0
else:
scale = 1.0
#
# --> We get the values of the vertical levels of dat2 (from the original file, that's why we apply a scale)
levels = ''
for lev in levValues2:
levels = levels + ',' + str(lev * scale)
#
# --> We can now interpolate dat1 on dat2 verticaly and horizontally
print levels
regridded_dat1 = ccdo(regrid(dat1, dat2), operator='intlevel' + levels)
else:
if vertical_levels:
if isinstance(vertical_levels, list):
levels = ''
for lev in vertical_levels:
levels = levels + ',' + str(lev)
else:
levels = ',' + vertical_levels
regridded_dat1 = ccdo(regridn(dat1, cdogrid=cdo_horizontal_grid),
operator='intlevel' + levels)
else:
print '--> Provide a list of vertical levels with vertical_levels'
return regridded_dat1
