def main():
file_list = parser.parse_args().input_file
cwd = os.getcwd()
path2data = os.getcwd()
if parser.parse_args().fv3 and parser.parse_args().combine:
prRed('Use --fv3 and --combine sequentially to avoid ambiguity ')
exit()
#=======Convert to FV3================
if parser.parse_args().fv3:
for irequest in parser.parse_args().fv3:
if irequest not in ['fixed', 'average', 'daily', 'diurn']:
prRed(
irequest +
""" is not available, select 'fixed', 'average', 'daily', or 'diurn'"""
)
#argument definitions:
do_multi = False
do_1year = False #Used with LegacyGCM_1year.nc'
#Get files to process
histlist = []
for filei in file_list:
if not ('/' in filei):
histlist.append(path2data + '/' + filei)
else:
histlist.append(filei)
fnum = len(histlist)
if fnum >= 0: do_multi = True #TODO why not 1?
try:
hist1year = path2data + '/LegacyGCM_1year.nc'
file1year = Dataset(hist1year, 'r', format='NETCDF4_CLASSIC')
do_1year = True
except:
hist1year = None
do_1year = False
lsmin = None
lsmax = None
if do_multi:
for f in histlist:
histname = os.path.basename(f)
ls_l = histname[-12:-9]
ls_r = histname[-6:-3]
if lsmin is None:
lsmin = ls_l
else:
lsmin = str(min(int(lsmin), int(ls_l))).zfill(3)
if lsmax is None:
lsmax = ls_r
else:
lsmax = str(max(int(lsmax), int(ls_r))).zfill(3)
a = make_FV3_files(f, parser.parse_args().fv3, True, cwd)
elif parser.parse_args().combine:
#TODO Use ncks if it is available (not tested yet)
if cat_method == 'ncks':
subprocess.check_call('ncks --version',
shell=True,
stdout=open(os.devnull, "w"),
stderr=open(os.devnull, "w"))
#now cat together the files
newfavg = "Ls" + lsmin + "_Ls" + lsmax + ".atmos_average.nc"
newfdai = "Ls" + lsmin + "_Ls" + lsmax + ".atmos_daily.nc"
newfdiu = "Ls" + lsmin + "_Ls" + lsmax + ".atmos_diurn.nc"
tempdir = os.path.join(cwd, 'temp')
os.makedirs(tempdir, exist_ok=True)
os.chdir(tempdir)
catavg = "ncrcat ../*.atmos_average.nc " + "00000.atmos_average.nc"
catdai = "ncrcat ../*.atmos_daily.nc " + "00000.atmos_daily.nc"
catdiu = "ncrcat ../*.atmos_diurn.nc " + "00000.atmos_diurn.nc"
p = subprocess.Popen(catavg, universal_newlines=True, shell=True)
p.wait()
p = subprocess.Popen(catdai, universal_newlines=True, shell=True)
p.wait()
p = subprocess.Popen(catdiu, universal_newlines=True, shell=True)
p.wait()
os.chdir(cwd)
p = subprocess.run('rm -f Ls*.nc',
universal_newlines=True,
shell=True)
p = subprocess.run('mv temp/*.nc .',
universal_newlines=True,
shell=True)
p = subprocess.run('rm -rf temp/',
universal_newlines=True,
shell=True)
if do_1year:
a = make_FV3_files(hist1year, cwd)
#=================================
elif cat_method == 'internal':
#Get files to process
histlist = []
for filei in file_list:
#Add path unless full path is provided
if not ('/' in filei):
histlist.append(path2data + '/' + filei)
else:
histlist.append(filei)
fnum = len(histlist)
#Easy case: merging *****.fixed.nc means delete all but the first file:
if file_list[0][5:] == '.fixed.nc' and fnum >= 2:
rm_cmd = 'rm -f '
for i in range(1, fnum):
rm_cmd += ' ' + histlist[i]
p = subprocess.run(rm_cmd, universal_newlines=True, shell=True)
prCyan('Cleaned all but ' + file_list[0])
exit()
#=========
fnum = len(histlist)
prCyan('Merging %i files, starting with %s ...' %
(fnum, file_list[0]))
#this is a temporaty file ***_tmp.nc
file_tmp = histlist[0][:-3] + '_tmp' + '.nc'
Log = Ncdf(file_tmp, 'Merged file')
Log.merge_files_from_list(histlist)
Log.close()
#=====Delete files that have been combined====
#Rename merged file LegacyGCM_LsINI_LsEND.nc or first files of the list (e.g 00010.atmos_average.nc)
if file_list[0][:12] == 'LegacyGCM_Ls':
ls_ini = file_list[0][12:15]
ls_end = file_list[-1][18:21]
fileout = 'LegacyGCM_Ls%s_Ls%s.nc' % (ls_ini, ls_end)
else:
fileout = histlist[0]
#---Assemble 'remove' and 'move' commands to execute-----
rm_cmd = 'rm -f '
for ifile in histlist:
rm_cmd += ' ' + ifile
cmd_txt = 'mv ' + file_tmp + ' ' + fileout
p = subprocess.run(rm_cmd, universal_newlines=True, shell=True)
p = subprocess.run(cmd_txt, universal_newlines=True, shell=True)
prCyan(fileout + ' was merged')
#=========== Tshift implemation by Victoria!! ===========================
elif parser.parse_args().tshift:
#Get files to process
histlist = []
for filei in file_list:
#Add path unless full path is provided
if not ('/' in filei):
fullnameIN = path2data + '/' + filei
else:
fullnameIN = filei
fullnameOUT = fullnameIN[:-3] + '_T' + '.nc'
fdiurn = Dataset(fullnameIN, 'r', format='NETCDF4_CLASSIC')
fnew = Ncdf(fullnameOUT
) # define a Ncdf object from the Ncdf wrapper module
#Copy some dimensions from the old file to the new file
fnew.copy_all_dims_from_Ncfile(fdiurn)
#find time of day variable name
tod_name = find_tod_in_diurn(fdiurn)
# find vertical dimension variable name
if filei[:-3].endswith('_pstd'):
zaxis = 'pstd'
elif filei[:3].endswith('_zagl'):
zaxis = 'zagl'
elif filei[:3].endswith('_zstd'):
zaxis = 'zstd'
else:
zaxis = 'pfull'
# Copy some variables from the old file to the new file
fnew.copy_Ncaxis_with_content(fdiurn.variables['lon'])
fnew.copy_Ncaxis_with_content(fdiurn.variables['lat'])
#Only create a vertical axis if the original file contains 3D fields
if zaxis in fdiurn.dimensions.keys():
fnew.copy_Ncaxis_with_content(fdiurn.variables[zaxis])
fnew.copy_Ncaxis_with_content(fdiurn.variables['time'])
fnew.copy_Ncaxis_with_content(fdiurn.variables[tod_name])
#Only copy areo if existing in the original file:
if 'areo' in fdiurn.variables.keys():
fnew.copy_Ncvar(fdiurn.variables['areo'])
# read 4D field and do time shift
tod_in = np.array(fdiurn.variables[tod_name])
longitude = np.array(fdiurn.variables['lon'])
var_list = fdiurn.variables.keys(
) # get all variables from old file
for ivar in var_list:
varIN = fdiurn.variables[ivar][:]
vkeys = fdiurn.variables[ivar].dimensions
if (len(vkeys) == 4):
print(ivar)
ilat = vkeys.index('lat')
ilon = vkeys.index('lon')
itime = vkeys.index('time')
itod = vkeys.index(tod_name)
newvar = np.transpose(varIN, (ilon, ilat, itime, itod))
newvarOUT = tshift(newvar, lon=longitude, timex=tod_in)
varOUT = np.transpose(newvarOUT, (2, 3, 1, 0))
fnew.log_variable(ivar, varOUT,
['time', tod_name, 'lat', 'lon'],
fdiurn.variables[ivar].long_name,
fdiurn.variables[ivar].units)
if (len(vkeys) == 5):
print(ivar)
ilat = vkeys.index('lat')
ilon = vkeys.index('lon')
iz = vkeys.index(zaxis)
itime = vkeys.index('time')
itod = vkeys.index(tod_name)
newvar = np.transpose(varIN, (ilon, ilat, iz, itime, itod))
newvarOUT = tshift(newvar, lon=longitude, timex=tod_in)
varOUT = np.transpose(newvarOUT, (3, 4, 2, 1, 0))
fnew.log_variable(ivar, varOUT,
['time', tod_name, zaxis, 'lat', 'lon'],
fdiurn.variables[ivar].long_name,
fdiurn.variables[ivar].units)
fnew.close()
fdiurn.close()
else:
prRed(
"""Error: no action requested: use 'MarsFiles *nc --fv3 --combine, or --tshift'"""
)
def main():
start_time = time.time()
debug = parser.parse_args().debug
#load all the .nc files
file_list = parser.parse_args().input_file
interp_type = parser.parse_args().type #e.g. 'pstd'
custom_level = parser.parse_args().level #e.g. 'p44'
#The fixed file is needed if pk, bk are not available in the requested file, or
# to load the topography is zstd output is requested
name_fixed = filepath + '/' + file_list[0][0:5] + '.fixed.nc'
# PRELIMINARY DEFINITIONS
#===========================pstd============================================
if interp_type == 'pstd':
longname_txt = 'standard pressure'
units_txt = 'Pa'
need_to_reverse = False
interp_technic = 'log'
if custom_level:
content_txt = section_content_amesgcm_profile(
'Pressure definitions for pstd')
#print(content_txt)
exec(content_txt) #load all variables in that section
lev_in = eval('np.array(' + custom_level +
')') #copy requested variable
else:
#Default levels, this is size 36
lev_in = np.array([
1.0e+03, 9.5e+02, 9.0e+02, 8.5e+02, 8.0e+02, 7.5e+02, 7.0e+02,
6.5e+02, 6.0e+02, 5.5e+02, 5.0e+02, 4.5e+02, 4.0e+02, 3.5e+02,
3.0e+02, 2.5e+02, 2.0e+02, 1.5e+02, 1.0e+02, 7.0e+01, 5.0e+01,
3.0e+01, 2.0e+01, 1.0e+01, 7.0e+00, 5.0e+00, 3.0e+00, 2.0e+00,
1.0e+00, 5.0e-01, 3.0e-01, 2.0e-01, 1.0e-01, 5.0e-02, 3.0e-02,
1.0e-02
])
#===========================zstd============================================
elif interp_type == 'zstd':
longname_txt = 'standard altitude'
units_txt = 'm'
need_to_reverse = True
interp_technic = 'lin'
if custom_level:
content_txt = section_content_amesgcm_profile(
'Altitude definitions for zstd')
exec(content_txt) #load all variables in that section
lev_in = eval('np.array(' + custom_level +
')') #copy requested variable
else:
#Default levels, this is size 45
lev_in = np.array([
-7000, -6000, -5000, -4500, -4000, -3500, -3000, -2500, -2000,
-1500, -1000, -500, 0, 500, 1000, 1500, 2000, 2500, 3000, 3500,
4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 12000, 14000,
16000, 18000, 20000, 25000, 30000, 35000, 40000, 45000, 50000,
55000, 60000, 70000, 80000, 90000, 100000
])
try:
f_fixed = Dataset(name_fixed, 'r')
zsurf = f_fixed.variables['zsurf'][:]
f_fixed.close()
except FileNotFoundError:
prRed(
'***Error*** Topography is needed for zstd interpolation, however'
)
prRed('file %s not found' % (name_fixed))
exit()
#===========================zagl============================================
elif interp_type == 'zagl':
longname_txt = 'altitude above ground level'
units_txt = 'm'
need_to_reverse = True
interp_technic = 'lin'
if custom_level:
content_txt = section_content_amesgcm_profile(
'Altitude definitions for zagl')
#print(content_txt)
exec(content_txt) #load all variables in that section
lev_in = eval('np.array(' + custom_level +
')') #copy requested variable
else:
#Default levels, this is size 45
lev_in = np.array([
-7000, -6000, -5000, -4500, -4000, -3500, -3000, -2500, -2000,
-1500, -1000, -500, 0, 500, 1000, 1500, 2000, 2500, 3000, 3500,
4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 12000, 14000,
16000, 18000, 20000, 25000, 30000, 35000, 40000, 45000, 50000,
55000, 60000, 70000, 80000, 90000, 100000
])
else:
prRed(
"Interpolation type '%s' is not supported, use 'pstd','zstd' or 'zagl'"
% (interp_type))
exit()
#For all the files
for ifile in file_list:
#First check if file is present on the disk (Lou only)
check_file_tape(ifile)
newname = filepath + '/' + ifile[:-3] + '_' + interp_type + '.nc'
#=================================================================
#=======================Interpolate action========================
#=================================================================
fNcdf = Dataset(ifile, 'r', format='NETCDF4_CLASSIC')
# Load pk and bk and ps for 3D pressure field calculation.
# We will read the pk and bk for each file in case the vertical resolution is changed.
try:
#First try to read pk and bk in the file
pk = np.array(fNcdf.variables['pk'])
bk = np.array(fNcdf.variables['bk'])
except:
#If pk and bk are not available in the file, try the matching XXXXX.fixed.nc
name_fixed = filepath + '/' + ifile[0:5] + '.fixed.nc'
f_fixed = Dataset(name_fixed, 'r', format='NETCDF4_CLASSIC')
pk = np.array(f_fixed.variables['pk'])
bk = np.array(f_fixed.variables['bk'])
f_fixed.close()
ps = np.array(fNcdf.variables['ps'])
if len(ps.shape) == 3:
do_diurn = False
tod_name = 'not_used'
permut = [
1, 0, 2, 3
] # Put vertical axis first for 4D variable, e.g (time,lev,lat,lon) >>> (lev,time,lat,lon)
# ( 0 1 2 3 ) >>> ( 1 0 2 3 )
elif len(ps.shape) == 4:
do_diurn = True
#find time of day variable name
tod_name = find_tod_in_diurn(fNcdf)
permut = [
2, 1, 0, 3, 4
] #Same for diun files, e.g (time,time_of_day_XX,lev,lat,lon) >>> (lev,time_of_day_XX,time,lat,lon)
# ( 0 1 2 3 4) >>> ( 2 1 0 3 4 )
#== Compute levels in the file, these are permutted arrays
# Suppress divided by zero error ==
with np.errstate(divide='ignore', invalid='ignore'):
if interp_type == 'pstd':
L_3D_P = fms_press_calc(
ps, pk, bk,
lev_type='full') #permuted by default, e.g lev is first
elif interp_type == 'zagl':
temp = fNcdf.variables['temp'][:]
L_3D_P = fms_Z_calc(ps,
pk,
bk,
temp.transpose(permut),
topo=0.,
lev_type='full')
elif interp_type == 'zstd':
temp = fNcdf.variables['temp'][:]
#Expend the zsurf array to the time dimension
zflat = np.repeat(zsurf[np.newaxis, :], ps.shape[0], axis=0)
if do_diurn:
zflat = np.repeat(zflat[:, np.newaxis, :, :],
ps.shape[1],
axis=1)
L_3D_P = fms_Z_calc(ps,
pk,
bk,
temp.transpose(permut),
topo=zflat,
lev_type='full')
fnew = Ncdf(newname, 'Pressure interpolation using MarsInterp.py')
#=========== Replicate existing DIMENSIONS but pfull =================
#get all variables in file:
var_list = fNcdf.variables.keys()
fnew.copy_all_dims_from_Ncfile(fNcdf, exclude_dim=['pfull'])
fnew.add_dim_with_content(interp_type, lev_in, longname_txt,
units_txt) #Add new vertical dimension
fnew.copy_Ncaxis_with_content(fNcdf.variables['lon'])
fnew.copy_Ncaxis_with_content(fNcdf.variables['lat'])
fnew.copy_Ncaxis_with_content(fNcdf.variables['time'])
if do_diurn: fnew.copy_Ncaxis_with_content(fNcdf.variables[tod_name])
#We will re-use the indices for each files, this speeds-up the calculation
compute_indices = True
for ivar in var_list:
if (fNcdf.variables[ivar].dimensions
== ('time', 'pfull', 'lat', 'lon')
or fNcdf.variables[ivar].dimensions
== ('time', tod_name, 'pfull', 'lat', 'lon')):
if compute_indices:
prCyan("Computing indices ...")
index = find_n(L_3D_P,
lev_in,
reverse_input=need_to_reverse)
compute_indices = False
prCyan("Interpolating: %s ..." % (ivar))
varIN = fNcdf.variables[ivar][:]
#==This with loop suppresses divided by zero errors==
with np.errstate(divide='ignore', invalid='ignore'):
varOUT = vinterp(varIN.transpose(permut),
L_3D_P,
lev_in,
type=interp_technic,
reverse_input=need_to_reverse,
masktop=True,
index=index).transpose(permut)
if not do_diurn:
fnew.log_variable(ivar, varOUT,
('time', interp_type, 'lat', 'lon'),
fNcdf.variables[ivar].long_name,
fNcdf.variables[ivar].units)
else:
fnew.log_variable(
ivar, varOUT,
('time', tod_name, interp_type, 'lat', 'lon'),
fNcdf.variables[ivar].long_name,
fNcdf.variables[ivar].units)
else:
if ivar not in [
'time', 'pfull', 'lat', 'lon', 'phalf', 'pk', 'bk',
'pstd', 'zstd', 'zagl', tod_name
]:
#print("\r Copying over: %s..."%(ivar), end='')
prCyan("Copying over: %s..." % (ivar))
fnew.copy_Ncvar(fNcdf.variables[ivar])
print('\r ', end='')
fNcdf.close()
fnew.close()
print("Completed in %.3f sec" % (time.time() - start_time))
def main():
#load all the .nc files
file_list = parser.parse_args().input_file
add_list = parser.parse_args().add
zdiff_list = parser.parse_args().zdiff
col_list = parser.parse_args().col
remove_list = parser.parse_args().remove
debug = parser.parse_args().debug
#Check if an operation is requested, otherwise print file content.
if not (add_list or zdiff_list or remove_list or col_list):
print_fileContent(file_list[0])
prYellow(
''' ***Notice*** No operation requested, use '-add var', '-zdiff var', '-col var', '-rm var' '''
)
exit() #Exit cleanly
#For all the files
for ifile in file_list:
#First check if file is present on the disk (Lou only)
check_file_tape(ifile)
#=================================================================
#====================Remove action================================
#=================================================================
if remove_list:
cmd_txt = 'ncks --version'
try:
#If ncks is available, use it:--
subprocess.check_call(cmd_txt,
shell=True,
stdout=open(os.devnull, "w"),
stderr=open(os.devnull, "w"))
for ivar in remove_list:
print('Creating new file %s without %s:' % (ifile, ivar))
cmd_txt = 'ncks -C -O -x -v %s %s %s' % (ivar, ifile,
ifile)
try:
subprocess.check_call(cmd_txt,
shell=True,
stdout=open(os.devnull, "w"),
stderr=open(os.devnull, "w"))
except Exception as exception:
print(exception.__class__.__name__ + ": " +
exception.message)
#ncks is not available, we use internal method.
except subprocess.CalledProcessError:
f_IN = Dataset(ifile, 'r', format='NETCDF4_CLASSIC')
ifile_tmp = ifile[:-3] + '_tmp' + '.nc'
Log = Ncdf(ifile_tmp, 'Edited in postprocessing')
Log.copy_all_dims_from_Ncfile(f_IN)
Log.copy_all_vars_from_Ncfile(f_IN, remove_list)
f_IN.close()
Log.close()
cmd_txt = 'mv ' + ifile_tmp + ' ' + ifile
p = subprocess.run(cmd_txt,
universal_newlines=True,
shell=True)
prCyan(ifile + ' was updated')
#=================================================================
#=======================Add action================================
#=================================================================
#If the list is not empty, load ak and bk for pressure calculation, those are always needed.
if add_list:
name_fixed = ifile[0:5] + '.fixed.nc'
f_fixed = Dataset(name_fixed, 'r', format='NETCDF4_CLASSIC')
variableNames = f_fixed.variables.keys()
ak = np.array(f_fixed.variables['pk'])
bk = np.array(f_fixed.variables['bk'])
f_fixed.close()
#----
#----Check if the variable is currently supported---
for ivar in add_list:
if ivar not in VAR.keys():
prRed("Variable '%s' is not supported" % (ivar))
else:
print('Processing: %s...' % (ivar))
try:
fileNC = Dataset(ifile, 'a', format='NETCDF4_CLASSIC')
#---temp and ps are always needed---
dim_out = fileNC.variables[
'temp'].dimensions #get dimension
temp = fileNC.variables['temp'][:]
shape_out = temp.shape
ps = fileNC.variables['ps'][:]
p_3D = compute_p_3D(ps, ak, bk, shape_out)
#----
if ivar == 'pfull3D': OUT = p_3D
if ivar == 'rho':
OUT = compute_rho(p_3D, temp)
if ivar == 'theta':
OUT = compute_theta(p_3D, ps, temp)
if ivar == 'w':
omega = fileNC.variables['omega'][:]
rho = compute_rho(p_3D, temp)
OUT = compute_w(rho, omega)
if ivar == 'zfull':
OUT = compute_zfull(ps, ak, bk,
temp) #TODO not with _pstd
if ivar == 'wspeed' or ivar == 'wdir':
ucomp = fileNC.variables['ucomp'][:]
vcomp = fileNC.variables['vcomp'][:]
theta, mag = cart_to_azimut_TR(ucomp,
vcomp,
mode='from')
if ivar == 'wdir': OUT = theta
if ivar == 'wspeed': OUT = mag
if ivar == 'N':
theta = compute_theta(p_3D, ps, temp)
zfull = compute_zfull(ps, ak, bk,
temp) #TODO not with _pstd
OUT = compute_N(theta, zfull)
if ivar == 'Ri':
theta = compute_theta(p_3D, ps, temp)
zfull = compute_zfull(ps, ak, bk,
temp) #TODO not with _pstd
N = compute_N(theta, zfull)
ucomp = fileNC.variables['ucomp'][:]
vcomp = fileNC.variables['vcomp'][:]
du_dz = dvar_dh(ucomp.transpose([1, 0, 2, 3]),
zfull.transpose([1, 0, 2,
3])).transpose(
[1, 0, 2, 3])
dv_dz = dvar_dh(vcomp.transpose([1, 0, 2, 3]),
zfull.transpose([1, 0, 2,
3])).transpose(
[1, 0, 2, 3])
OUT = N**2 / (du_dz**2 + dv_dz**2)
if ivar == 'Tco2': OUT = compute_Tco2(p_3D, temp)
if ivar == 'scorer_wl':
ucomp = fileNC.variables['ucomp'][:]
theta = compute_theta(p_3D, ps, temp)
zfull = compute_zfull(ps, ak, bk, temp)
N = compute_N(theta, zfull)
OUT = compute_scorer(N, ucomp, zfull)
#filter nan
OUT[np.isnan(OUT)] = fill_value
#Log the variable
var_Ncdf = fileNC.createVariable(ivar, 'f4', dim_out)
var_Ncdf.long_name = VAR[ivar][0]
var_Ncdf.units = VAR[ivar][1]
var_Ncdf[:] = OUT
fileNC.close()
print('%s: \033[92mDone\033[00m' % (ivar))
except Exception as exception:
if debug: raise
if str(exception) == 'NetCDF: String match to name in use':
prYellow("""***Error*** Variable already exists""")
prYellow(
"""Delete existing variables %s with 'MarsVars.py %s -rm %s'"""
% (ivar, ifile, ivar))
#=================================================================
#=============Vertical Differentiation action=====================
#=================================================================
#ak and bk are needed to derive the distance between layer pfull
if zdiff_list:
name_fixed = ifile[0:5] + '.fixed.nc'
f_fixed = Dataset(name_fixed, 'r', format='NETCDF4_CLASSIC')
variableNames = f_fixed.variables.keys()
ak = np.array(f_fixed.variables['pk'])
bk = np.array(f_fixed.variables['bk'])
f_fixed.close()
for idiff in zdiff_list:
fileNC = Dataset(ifile, 'a', format='NETCDF4_CLASSIC')
if idiff not in fileNC.variables.keys():
prRed("zdiff error: variable '%s' is not present in %s" %
(idiff, ifile))
fileNC.close()
else:
print('Differentiating: %s...' % (idiff))
try:
var = fileNC.variables[idiff][:, :, :, :]
newUnits = fileNC.variables[
idiff].units[:-2] + '/m]' #remove the last ']' to update units, e.g turn '[kg]' to '[kg/m]'
newLong_name = 'vertical gradient of ' + fileNC.variables[
idiff].long_name
#---temp and ps are always needed---
dim_out = fileNC.variables[
'temp'].dimensions #get dimension
temp = fileNC.variables['temp'][:]
ps = fileNC.variables['ps'][:]
zfull = fms_Z_calc(ps,
ak,
bk,
temp.transpose([1, 0, 2, 3]),
topo=0.,
lev_type='full') #z is first axis
#differentiate the variable zith respect to z:
darr_dz = dvar_dh(var.transpose([1, 0, 2, 3]),
zfull).transpose([1, 0, 2, 3])
#Log the variable
var_Ncdf = fileNC.createVariable('d_dz_' + idiff, 'f4',
dim_out)
var_Ncdf.long_name = newLong_name
var_Ncdf.units = newUnits
var_Ncdf[:] = darr_dz
fileNC.close()
print('%s: \033[92mDone\033[00m' % ('d_dz_' + idiff))
except Exception as exception:
if debug: raise
if str(exception) == 'NetCDF: String match to name in use':
prYellow("""***Error*** Variable already exists""")
prYellow(
"""Delete existing variable %s with 'MarsVars %s -rm %s'"""
% ('d_dz_' + idiff, ifile, 'd_dz_' + idiff))
#=================================================================
#============= Column integration ============================
#=================================================================
#ak and bk are needed to derive the distance between layer pfull
if col_list:
name_fixed = ifile[0:5] + '.fixed.nc'
f_fixed = Dataset(name_fixed, 'r', format='NETCDF4_CLASSIC')
variableNames = f_fixed.variables.keys()
ak = np.array(f_fixed.variables['pk'])
bk = np.array(f_fixed.variables['bk'])
f_fixed.close()
for icol in col_list:
fileNC = Dataset(ifile, 'a') #, format='NETCDF4_CLASSIC
if icol not in fileNC.variables.keys():
prRed(
"column integration error: variable '%s' is not present in %s"
% (icol, ifile))
fileNC.close()
else:
print('Performing colum integration: %s...' % (icol))
try:
var = fileNC.variables[icol][:]
#prRed(fileNC.variables[icol].units+'|')
newUnits = fileNC.variables[
icol].units[:-3] + '/m2' # turn 'kg/kg'> to 'kg/m2'
newLong_name = 'column integration of ' + fileNC.variables[
icol].long_name
#---temp and ps are always needed---
dim_in = fileNC.variables[
'temp'].dimensions #get dimension
shape_in = fileNC.variables['temp'].shape
#TODO edged cases where time =1
dim_out = tuple([dim_in[0], dim_in[2], dim_in[3]])
ps = fileNC.variables['ps'][:, :, :]
DP = compute_DP_3D(ps, ak, bk, shape_in)
out = np.sum(var * DP / g, axis=1)
#Log the variable
var_Ncdf = fileNC.createVariable(icol + '_col', 'f4',
dim_out)
var_Ncdf.long_name = newLong_name
var_Ncdf.units = newUnits
var_Ncdf[:] = out
fileNC.close()
print('%s: \033[92mDone\033[00m' % (icol + '_col'))
except Exception as exception:
if debug: raise
if str(exception) == 'NetCDF: String match to name in use':
prYellow("""***Error*** Variable already exists""")
prYellow(
"""Delete existing variable %s with 'MarsVars %s -rm %s'"""
% (icol + '_col', ifile, icol + '_col'))
from amesgcm.Script_utils import check_file_tape, prYellow, prRed, prCyan, prGreen, prPurple, print_fileContent
from amesgcm.Script_utils import section_content_amesgcm_profile, find_tod_in_diurn
from amesgcm.Ncdf_wrapper import Ncdf
#=====Attempt to import specific scientic modules one may not find in the default python on NAS ====
try:
import matplotlib
matplotlib.use('Agg') # Force matplotlib to not use any Xwindows backend.
import numpy as np
from netCDF4 import Dataset, MFDataset
except ImportError as error_msg:
prYellow("Error while importing modules")
prYellow('Your are using python ' + str(sys.version_info[0:3]))
prYellow('Please, source your virtual environment')
prCyan(' source envPython3.7/bin/activate.csh \n')
print("Error was: " + error_msg.message)
exit()
except Exception as exception:
# Output unexpected Exceptions.
print(exception, False)
print(exception.__class__.__name__ + ": " + exception.message)
exit()
#======================================================
# ARGUMENTS PARSER
#======================================================
parser = argparse.ArgumentParser(
description=
"""\033[93m MarsInterp, pressure interpolation on fixed layers\n \033[00m""",
formatter_class=argparse.RawTextHelpFormatter)
from amesgcm.FV3_utils import fms_press_calc, fms_Z_calc, dvar_dh, cart_to_azimut_TR
from amesgcm.Script_utils import check_file_tape, prYellow, prRed, prCyan, prGreen, prPurple, print_fileContent
from amesgcm.Ncdf_wrapper import Ncdf
#=====Attempt to import specific scientic modules one may not find in the default python on NAS ====
try:
import matplotlib
matplotlib.use('Agg') # Force matplotlib to not use any Xwindows backend.
import numpy as np
from netCDF4 import Dataset, MFDataset
except ImportError as error_msg:
prYellow("Error while importing modules")
prYellow('Your are using python ' + str(sys.version_info[0:3]))
prYellow('Please, source your virtual environment')
prCyan(' source amesGCM3/bin/activate \n')
print("Error was: " + error_msg.message)
exit()
except Exception as exception:
# Output unexpected Exceptions.
print(exception, False)
print(exception.__class__.__name__ + ": " + exception.message)
exit()
#======================================================
# ARGUMENTS PARSER
#======================================================
parser = argparse.ArgumentParser(
description=
"""\033[93m MarsVars, variable manager, utility to add or remove variables to the diagnostic files\n Use MarsFiles ****.atmos.average.nc to view file content \033[00m""",