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source: lmdz_wrf/trunk/tools/diagnostics.py @ 2344

Last change on this file since 2344 was 2285, checked in by lfita, 6 years ago
Fixing `compute_cellbnds', right values at the x-axis borders
File size: 84.3 KB

Rev	Line
[1675]	1	# Python script to comput diagnostics
[1908]	2	# From L. Fita work in different places: CCRC (Australia), LMD (France)
	3	# More information at: http://www.xn--llusfb-5va.cat/python/PyNCplot
	4	#
	5	# pyNCplot and its component nc_var.py comes with ABSOLUTELY NO WARRANTY.
	6	# This work is licendes under a Creative Commons
	7	# Attribution-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-sa/4.0)
	8	#
	9	# L. Fita, CIMA. CONICET-UBA, CNRS UMI-IFAECI, C.A. Buenos Aires, Argentina
[365]	10	# File diagnostics.inf provides the combination of variables to get the desired diagnostic
[772]	11	# To be used with module_ForDiagnostics.F90, module_ForDiagnosticsVars.F90, module_generic.F90
[1150]	12	# foudre: f2py -m module_ForDiagnostics --f90exec=/usr/bin/gfortran-4.7 -c module_generic.F90 module_ForDiagnosticsVars.F90 module_ForDiagnostics.F90 >& run_f2py.log
	13	# ciclad: f2py --f90flags="-fPIC" --f90exec=/usr/bin/gfortran -L/opt/canopy-1.3.0/Canopy_64bit/System/lib/ -L/usr/lib64/ -L/opt/canopy-1.3.0/Canopy_64bit/System/lib/ -m module_ForDiagnostics -c module_generic.F90 module_ForDiagnosticsVars.F90 module_ForDiagnostics.F90 >& run_f2py.log
[1149]	14
[2095]	15	## e.g. # diagnostics.py -d 'Time@WRFtime,bottom_top@ZNU,south_north@XLAT,west_east@XLONG' -v 'clt\|CLDFRA,cllmh\|CLDFRA@WRFp,RAINTOT\|RAINC@RAINNC@RAINSH@XTIME' -f WRF_LMDZ/NPv31/wrfout_d01_1980-03-01_00:00:00
[413]	16	## e.g. # diagnostics.py -f /home/lluis/PY/diagnostics.inf -d variable_combo -v WRFprc
[365]	17
[1675]	18	# Available general pupose diagnostics (model independent) providing (varv1, varv2, ..., dimns, dimvns)
	19	# compute_accum: Function to compute the accumulation of a variable
	20	# compute_cllmh: Function to compute cllmh: low/medium/hight cloud fraction following
	21	# newmicro.F90 from LMDZ compute_clt(cldfra, pres, dimns, dimvns)
	22	# compute_clt: Function to compute the total cloud fraction following 'newmicro.F90' from LMDZ
	23	# compute_clivi: Function to compute cloud-ice water path (clivi)
	24	# compute_clwvl: Function to compute condensed water path (clwvl)
	25	# compute_deaccum: Function to compute the deaccumulation of a variable
	26	# compute_mslp: Function to compute mslp: mean sea level pressure following p_interp.F90 from WRF
	27	# compute_OMEGAw: Function to transform OMEGA [Pas-1] to velocities [ms-1]
	28	# compute_prw: Function to compute water vapour path (prw)
[2209]	29	# compute_range_faces: Function to compute faces [uphill, valley, downhill] of sections of a mountain
	30	# range, along a given face
[1675]	31	# compute_rh: Function to compute relative humidity following 'Tetens' equation (T,P) ...'
	32	# compute_td: Function to compute the dew point temperature
	33	# compute_turbulence: Function to compute the rubulence term of the Taylor's decomposition ...'
	34	# compute_wds: Function to compute the wind direction
	35	# compute_wss: Function to compute the wind speed
	36	# compute_WRFuava: Function to compute geographical rotated WRF 3D winds
	37	# compute_WRFuasvas: Fucntion to compute geographical rotated WRF 2-meter winds
	38	# derivate_centered: Function to compute the centered derivate of a given field
	39	# def Forcompute_cllmh: Function to compute cllmh: low/medium/hight cloud fraction following newmicro.F90 from LMDZ via Fortran subroutine
	40	# Forcompute_clt: Function to compute the total cloud fraction following 'newmicro.F90' from LMDZ via a Fortran module
[1758]	41	# Forcompute_psl_ptarget: Function to compute the sea-level pressure following target_pressure value found in `p_interp.F'
[1675]	42
	43	# Others just providing variable values
	44	# var_cllmh: Fcuntion to compute cllmh on a 1D column
	45	# var_clt: Function to compute the total cloud fraction following 'newmicro.F90' from LMDZ using 1D vertical column values
	46	# var_mslp: Fcuntion to compute mean sea-level pressure
	47	# var_virtualTemp: This function returns virtual temperature in K,
	48	# var_WRFtime: Function to copmute CFtimes from WRFtime variable
	49	# rotational_z: z-component of the rotatinoal of horizontal vectorial field
	50	# turbulence_var: Function to compute the Taylor's decomposition turbulence term from a a given variable
[2138]	51	# timeoverthres: When a given variable [varname] overpass a given [value]. Being [CFvarn] the name of the diagnostics in
	52	# variables_values.dat
[2141]	53	# timemax ([varname], time). When a given variable [varname] got its maximum
[1675]	54
[365]	55	from optparse import OptionParser
	56	import numpy as np
	57	from netCDF4 import Dataset as NetCDFFile
	58	import os
	59	import re
	60	import nc_var_tools as ncvar
[756]	61	import generic_tools as gen
[654]	62	import datetime as dtime
[1163]	63	import module_ForDiag as fdin
[1942]	64	import module_ForDef as fdef
[1675]	65	import diag_tools as diag
[365]	66
	67	main = 'diagnostics.py'
	68	errormsg = 'ERROR -- error -- ERROR -- error'
	69	warnmsg = 'WARNING -- warning -- WARNING -- warning'
	70
[654]	71	# Constants
	72	grav = 9.81
	73
[365]	74
	75	####### ###### ##### #### ### ## #
	76	comboinf="\nIF -d 'variable_combo', provides information of the combination to obtain -v [varn] with the ASCII file with the combinations as -f [combofile]"
	77
	78	parser = OptionParser()
	79	parser.add_option("-f", "--netCDF_file", dest="ncfile", help="file to use", metavar="FILE")
	80	parser.add_option("-d", "--dimensions", dest="dimns",
[1761]	81	help="[dimtn]@[dtvn],[dimzn]@[dzvn],[...,[dimxn]@[dxvn]], ',' list with the couples [dimDn]@[dDvn], [dimDn], name of the dimension D and name of the variable [dDvn] with the values of the dimension ('WRFtime', for WRF time copmutation). NOTE: same order as in file!!!!" + comboinf,
[365]	82	metavar="LABELS")
	83	parser.add_option("-v", "--variables", dest="varns",
	84	help=" [varn1]\|[var11]@[...[varN1]],[...,[varnM]\|[var1M]@[...[varLM]]] ',' list of variables to compute [varnK] and its necessary ones [var1K]...[varPK]", metavar="VALUES")
	85
	86	(opts, args) = parser.parse_args()
	87
	88	####### #######
	89	## MAIN
	90	#######
[2100]	91	availdiags = ['ACRAINTOT', 'accum', 'clt', 'cllmh', 'convini', 'deaccum', 'fog_K84', \
[2209]	92	'fog_RUC', 'LMDZrh', 'mslp', 'OMEGAw', 'RAINTOT', 'range_faces', \
[2141]	93	'rvors', 'td', 'timemax', 'timeoverthres', 'turbulence', 'uavaFROMwswd', \
[2274]	94	'WRFbnds', 'WRFcape_afwa', 'WRFclivi', 'WRFclwvi', 'WRF_denszint', 'WRFgeop', \
[2206]	95	'WRFmrso', 'WRFmrsos', 'WRFpotevap_orPM', 'WRFp', 'WRFpsl_ecmwf', \
[1762]	96	'WRFpsl_ptarget', 'WRFrvors', 'WRFslw', 'ws', 'wds', 'wss', 'WRFheight', \
[1966]	97	'WRFheightrel', 'WRFtda', 'WRFtdas', 'WRFua', 'WRFva', 'WRFzwind', 'WRFzwind_log', \
[1942]	98	'WRFzwindMO']
[365]	99
[649]	100	methods = ['accum', 'deaccum']
	101
[365]	102	# Variables not to check
[2277]	103	NONcheckingvars = ['accum', 'cllmh', 'deaccum', 'face', 'LONLATdxdy', \
	104	'reglonlatbnds', 'TSrhs', 'TStd', 'TSwds', 'TSwss', \
[2274]	105	'WRFbils', 'WRFbnds', \
[2257]	106	'WRFclivi', 'WRFclwvi', 'WRFdens', 'WRFdx', 'WRFdxdy', 'WRFdxdywps', 'WRFdy', \
	107	'WRFgeop', 'WRFp', 'WRFtd', \
[1809]	108	'WRFpos', 'WRFprc', 'WRFprls', 'WRFrh', 'LMDZrh', 'LMDZrhs', \
[1806]	109	'WRFrhs', 'WRFrvors', \
[2215]	110	'WRFt', 'WRFtime', 'WRFua', 'WRFva', 'WRFwds', 'WRFwss', 'WRFheight', 'WRFz', \
	111	'WRFzg']
[365]	112
[1809]	113	# diagnostics not to check their dependeny
[2138]	114	NONcheckdepvars = ['accum', 'deaccum', 'timeoverthres', 'WRF_denszint', \
	115	'WRFzwind_log', 'WRFzwind', 'WRFzwindMO']
[1809]	116
[1351]	117	NONchkvardims = ['WRFtime']
	118
[365]	119	ofile = 'diagnostics.nc'
	120
	121	dimns = opts.dimns
	122	varns = opts.varns
	123
	124	# Special method. knowing variable combination
	125	##
	126	if opts.dimns == 'variable_combo':
	127	print warnmsg
	128	print ' ' + main + ': knowing variable combination !!!'
	129	combination = variable_combo(opts.varns,opts.ncfile)
	130	print ' COMBO: ' + combination
	131	quit(-1)
	132
[1833]	133	if opts.ncfile is None:
	134	print errormsg
	135	print ' ' + main + ": No file provided !!"
	136	print ' is mandatory to provide a file -f [filename]'
	137	quit(-1)
	138
	139	if opts.dimns is None:
	140	print errormsg
	141	print ' ' + main + ": No description of dimensions are provided !!"
	142	print ' is mandatory to provide description of dimensions as -d [dimn]@[vardimname],... '
	143	quit(-1)
	144
	145	if opts.varns is None:
	146	print errormsg
	147	print ' ' + main + ": No variable to diagnose is provided !!"
	148	print ' is mandatory to provide a variable to diagnose as -v [diagn]\|[varn1]@... '
	149	quit(-1)
	150
[365]	151	if not os.path.isfile(opts.ncfile):
	152	print errormsg
	153	print ' ' + main + ": file '" + opts.ncfile + "' does not exist !!"
	154	quit(-1)
	155
	156	ncobj = NetCDFFile(opts.ncfile, 'r')
	157
[1351]	158	# Looking for specific variables that might be use in more than one diagnostic
	159	WRFgeop_compute = False
	160	WRFp_compute = False
	161	WRFt_compute = False
	162	WRFrh_compute = False
	163	WRFght_compute = False
	164	WRFdens_compute = False
	165	WRFpos_compute = False
	166	WRFtime_compute = False
[1777]	167	WRFz_compute = False
[2215]	168	WRFdxdy_compute = False
[2257]	169	WRFdxdywps_compute = False
[2222]	170	LONLATdxdy_compute = False
[1351]	171
[365]	172	# File creation
	173	newnc = NetCDFFile(ofile,'w')
	174
	175	# dimensions
	176	dimvalues = dimns.split(',')
	177	dnames = []
	178	dvnames = []
	179
	180	for dimval in dimvalues:
[1351]	181	dn = dimval.split('@')[0]
	182	dnv = dimval.split('@')[1]
	183	dnames.append(dn)
	184	dvnames.append(dnv)
	185	# Is there any dimension-variable which should be computed?
	186	if dnv == 'WRFgeop':WRFgeop_compute = True
	187	if dnv == 'WRFp': WRFp_compute = True
	188	if dnv == 'WRFt': WRFt_compute = True
	189	if dnv == 'WRFrh': WRFrh_compute = True
	190	if dnv == 'WRFght': WRFght_compute = True
	191	if dnv == 'WRFdens': WRFdens_compute = True
	192	if dnv == 'WRFpos': WRFpos_compute = True
	193	if dnv == 'WRFtime': WRFtime_compute = True
[1777]	194	if dnv == 'WRFz':WRFz_compute = True
[2215]	195	if dnv == 'WRFdxdy':WRFdxdy_compute = True
[2257]	196	if dnv == 'WRFdxdywps':WRFdxdywps_compute = True
[2222]	197	if dnv == 'LONLATdxdy':LONLATdxdy_compute = True
[365]	198
	199	# diagnostics to compute
	200	diags = varns.split(',')
	201	Ndiags = len(diags)
	202
	203	for idiag in range(Ndiags):
	204	if diags[idiag].split('\|')[1].find('@') == -1:
	205	depvars = diags[idiag].split('\|')[1]
[654]	206	if depvars == 'WRFgeop':WRFgeop_compute = True
[365]	207	if depvars == 'WRFp': WRFp_compute = True
	208	if depvars == 'WRFt': WRFt_compute = True
	209	if depvars == 'WRFrh': WRFrh_compute = True
	210	if depvars == 'WRFght': WRFght_compute = True
	211	if depvars == 'WRFdens': WRFdens_compute = True
	212	if depvars == 'WRFpos': WRFpos_compute = True
[654]	213	if depvars == 'WRFtime': WRFtime_compute = True
[1777]	214	if depvars == 'WRFz': WRFz_compute = True
[365]	215	else:
	216	depvars = diags[idiag].split('\|')[1].split('@')
[756]	217	if gen.searchInlist(depvars, 'WRFgeop'): WRFgeop_compute = True
	218	if gen.searchInlist(depvars, 'WRFp'): WRFp_compute = True
	219	if gen.searchInlist(depvars, 'WRFt'): WRFt_compute = True
	220	if gen.searchInlist(depvars, 'WRFrh'): WRFrh_compute = True
	221	if gen.searchInlist(depvars, 'WRFght'): WRFght_compute = True
	222	if gen.searchInlist(depvars, 'WRFdens'): WRFdens_compute = True
	223	if gen.searchInlist(depvars, 'WRFpos'): WRFpos_compute = True
	224	if gen.searchInlist(depvars, 'WRFtime'): WRFtime_compute = True
[1777]	225	if gen.searchInlist(depvars, 'WRFz'): WRFz_compute = True
[2215]	226	if gen.searchInlist(depvars, 'WRFdxdy'): WRFdxdy_compute = True
[2257]	227	if gen.searchInlist(depvars, 'WRFdxdywps'): WRFdxdywps_compute = True
[2222]	228	if gen.searchInlist(depvars, 'LONLATdxdy'): LONLATdxdy_compute = True
[365]	229
[1351]	230	# Dictionary with the new computed variables to be able to add them
	231	dictcompvars = {}
[654]	232	if WRFgeop_compute:
	233	print ' ' + main + ': Retrieving geopotential value from WRF as PH + PHB'
	234	dimv = ncobj.variables['PH'].shape
	235	WRFgeop = ncobj.variables['PH'][:] + ncobj.variables['PHB'][:]
	236
[1351]	237	# Attributes of the variable
[1412]	238	Vvals = gen.variables_values('WRFgeop')
[1351]	239	dictcompvars['WRFgeop'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	240	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	241
[365]	242	if WRFp_compute:
	243	print ' ' + main + ': Retrieving pressure value from WRF as P + PB'
	244	dimv = ncobj.variables['P'].shape
	245	WRFp = ncobj.variables['P'][:] + ncobj.variables['PB'][:]
	246
[1351]	247	# Attributes of the variable
	248	Vvals = gen.variables_values('WRFp')
	249	dictcompvars['WRFgeop'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	250	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	251
[365]	252	if WRFght_compute:
	253	print ' ' + main + ': computing geopotential height from WRF as PH + PHB ...'
	254	WRFght = ncobj.variables['PH'][:] + ncobj.variables['PHB'][:]
	255
[1351]	256	# Attributes of the variable
	257	Vvals = gen.variables_values('WRFght')
	258	dictcompvars['WRFgeop'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	259	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	260
[365]	261	if WRFrh_compute:
	262	print ' ' + main + ": computing relative humidity from WRF as 'Tetens'" + \
	263	' equation (T,P) ...'
	264	p0=100000.
	265	p=ncobj.variables['P'][:] + ncobj.variables['PB'][:]
	266	tk = (ncobj.variables['T'][:] + 300.)(p/p0)*(2./7.)
	267	qv = ncobj.variables['QVAPOR'][:]
	268
	269	data1 = 10.0.6112np.exp(17.67*(tk-273.16)/(tk-29.65))
	270	data2 = 0.622data1/(0.01p-(1.-0.622)*data1)
	271
	272	WRFrh = qv/data2
	273
[1351]	274	# Attributes of the variable
	275	Vvals = gen.variables_values('WRFrh')
	276	dictcompvars['WRFrh'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	277	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	278
[365]	279	if WRFt_compute:
	280	print ' ' + main + ': computing temperature from WRF as inv_potT(T + 300) ...'
	281	p0=100000.
	282	p=ncobj.variables['P'][:] + ncobj.variables['PB'][:]
	283
	284	WRFt = (ncobj.variables['T'][:] + 300.)(p/p0)*(2./7.)
	285
[1351]	286	# Attributes of the variable
	287	Vvals = gen.variables_values('WRFt')
	288	dictcompvars['WRFt'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	289	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	290
[365]	291	if WRFdens_compute:
	292	print ' ' + main + ': computing air density from WRF as ((MU + MUB) * ' + \
	293	'DNW)/g ...'
	294
	295	# Just we need in in absolute values: Size of the central grid cell
	296	## dxval = ncobj.getncattr('DX')
	297	## dyval = ncobj.getncattr('DY')
	298	## mapfac = ncobj.variables['MAPFAC_M'][:]
	299	## area = dxvaldyvalmapfac
	300
	301	mu = (ncobj.variables['MU'][:] + ncobj.variables['MUB'][:])
	302	dnw = ncobj.variables['DNW'][:]
	303
	304	WRFdens = np.zeros((mu.shape[0], dnw.shape[1], mu.shape[1], mu.shape[2]), \
	305	dtype=np.float)
	306	levval = np.zeros((mu.shape[1], mu.shape[2]), dtype=np.float)
	307
	308	for it in range(mu.shape[0]):
	309	for iz in range(dnw.shape[1]):
	310	levval.fill(np.abs(dnw[it,iz]))
	311	WRFdens[it,iz,:,:] = levval
	312	WRFdens[it,iz,:,:] = mu[it,:,:]*WRFdens[it,iz,:,:]/grav
	313
[1351]	314	# Attributes of the variable
	315	Vvals = gen.variables_values('WRFdens')
	316	dictcompvars['WRFdens'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	317	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	318
[365]	319	if WRFpos_compute:
	320	# WRF positions from the lowest-leftest corner of the matrix
	321	print ' ' + main + ': computing position from MAPFAC_M as sqrt(DYj*2 + ' + \
	322	'DXx2)MAPFAC_M ...'
	323
	324	mapfac = ncobj.variables['MAPFAC_M'][:]
	325
	326	distx = np.float(ncobj.getncattr('DX'))
	327	disty = np.float(ncobj.getncattr('DY'))
	328
	329	print 'distx:',distx,'disty:',disty
	330
	331	dx = mapfac.shape[2]
	332	dy = mapfac.shape[1]
	333	dt = mapfac.shape[0]
	334
	335	WRFpos = np.zeros((dt, dy, dx), dtype=np.float)
	336
	337	for i in range(1,dx):
	338	WRFpos[0,0,i] = distx*i/mapfac[0,0,i]
	339	for j in range(1,dy):
	340	i=0
	341	WRFpos[0,j,i] = WRFpos[0,j-1,i] + disty/mapfac[0,j,i]
	342	for i in range(1,dx):
	343	# WRFpos[0,j,i] = np.sqrt((distyj)2. + (distxi)**2.)/mapfac[0,j,i]
	344	# WRFpos[0,j,i] = np.sqrt((distyj)2. + (distxi)**2.)
	345	WRFpos[0,j,i] = WRFpos[0,j,i-1] + distx/mapfac[0,j,i]
	346
	347	for it in range(1,dt):
	348	WRFpos[it,:,:] = WRFpos[0,:,:]
	349
[654]	350	if WRFtime_compute:
	351	print ' ' + main + ': computing time from WRF as CFtime(Times) ...'
	352
	353	refdate='19491201000000'
	354	tunitsval='minutes'
	355
	356	timeobj = ncobj.variables['Times']
	357	timewrfv = timeobj[:]
	358
	359	yrref=refdate[0:4]
	360	monref=refdate[4:6]
	361	dayref=refdate[6:8]
	362	horref=refdate[8:10]
	363	minref=refdate[10:12]
	364	secref=refdate[12:14]
	365
	366	refdateS = yrref + '-' + monref + '-' + dayref + ' ' + horref + ':' + minref + \
	367	':' + secref
	368
[2065]	369
	370	if len(timeobj.shape) == 2:
	371	dt = timeobj.shape[0]
	372	else:
	373	dt = 1
[654]	374	WRFtime = np.zeros((dt), dtype=np.float)
	375
[2065]	376	if len(timeobj.shape) == 2:
	377	for it in range(dt):
	378	wrfdates = gen.datetimeStr_conversion(timewrfv[it,:],'WRFdatetime', \
	379	'matYmdHMS')
	380	WRFtime[it] = gen.realdatetime1_CFcompilant(wrfdates, refdate, tunitsval)
	381	else:
	382	wrfdates = gen.datetimeStr_conversion(timewrfv[:],'WRFdatetime', \
	383	'matYmdHMS')
[2072]	384	WRFtime[0] = gen.realdatetime1_CFcompilant(wrfdates, refdate, tunitsval)
[654]	385
	386	tunits = tunitsval + ' since ' + refdateS
	387
[1351]	388	# Attributes of the variable
	389	dictcompvars['WRFtime'] = {'name': 'time', 'standard_name': 'time', \
	390	'long_name': 'time', 'units': tunits, 'calendar': 'gregorian'}
	391
[1777]	392	if WRFz_compute:
	393	print ' ' + main + ': Retrieving z: height above surface value from WRF as ' + \
	394	'unstagger(PH + PHB)/9.8-hgt'
	395	dimv = ncobj.variables['PH'].shape
	396	WRFzg = (ncobj.variables['PH'][:] + ncobj.variables['PHB'][:])/9.8
	397
	398	unzgd = (dimv[0], dimv[1]-1, dimv[2], dimv[3])
	399	unzg = np.zeros(unzgd, dtype=np.float)
	400	unzg = 0.5*(WRFzg[:,0:dimv[1]-1,:,:] + WRFzg[:,1:dimv[1],:,:])
	401
	402	WRFz = np.zeros(unzgd, dtype=np.float)
	403	for iz in range(dimv[1]-1):
	404	WRFz[:,iz,:,:] = unzg[:,iz,:,:] - ncobj.variables['HGT'][:]
	405
	406	# Attributes of the variable
	407	Vvals = gen.variables_values('WRFz')
[2215]	408	dictcompvars['WRFz'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
[1777]	409	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	410
[2215]	411	if WRFdxdy_compute:
	412	print ' ' + main + ': Retrieving dxdy: real distance between grid points ' + \
	413	'from WRF as dx=(XLONG(i+1)-XLONG(i))DX/MAPFAC_M, dy=(XLAT(j+1)-XLAT(i))DY/'+\
	414	'MAPFAC_M, ds=sqrt(dx2+dy2)'
	415	dimv = ncobj.variables['XLONG'].shape
	416	WRFlon = ncobj.variables['XLONG'][0,:,:]
	417	WRFlat = ncobj.variables['XLAT'][0,:,:]
	418	WRFmapfac_m = ncobj.variables['MAPFAC_M'][0,:,:]
	419	DX = ncobj.DX
	420	DY = ncobj.DY
	421
	422	dimx = dimv[2]
	423	dimy = dimv[1]
	424
	425	WRFdx = np.zeros((dimy,dimx), dtype=np.float)
	426	WRFdy = np.zeros((dimy,dimx), dtype=np.float)
	427
	428	WRFdx[:,0:dimx-1]=(WRFlon[:,1:dimx]-WRFlon[:,0:dimx-1])*DX/WRFmapfac_m[:,0:dimx-1]
	429	WRFdy[0:dimy-1,:]=(WRFlat[1:dimy,:]-WRFlat[0:dimy-1,:])*DY/WRFmapfac_m[0:dimy-1,:]
	430	WRFds = np.sqrt(WRFdx2 + WRFdy2)
	431
	432	# Attributes of the variable
	433	Vvals = gen.variables_values('WRFdx')
	434	dictcompvars['WRFdx'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	435	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	436	Vvals = gen.variables_values('WRFdy')
	437	dictcompvars['WRFdy'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	438	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	439	Vvals = gen.variables_values('WRFds')
[2222]	440	dictcompvars['WRFds'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	441	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	442
[2257]	443	if WRFdxdywps_compute:
	444	print ' ' + main + ': Retrieving dxdy: real distance between grid points ' + \
	445	'from wpsWRF as dx=(XLONG_M(i+1)-XLONG_M(i))*DX/MAPFAC_M, ' + \
	446	'dy=(XLAT_M(j+1)-XLAT_M(i))DY/MAPFAC_M, ds=sqrt(dx2+dy*2)'
	447	dimv = ncobj.variables['XLONG_M'].shape
	448	WRFlon = ncobj.variables['XLONG_M'][0,:,:]
	449	WRFlat = ncobj.variables['XLAT_M'][0,:,:]
	450	WRFmapfac_m = ncobj.variables['MAPFAC_M'][0,:,:]
	451	DX = ncobj.DX
	452	DY = ncobj.DY
	453
	454	dimx = dimv[2]
	455	dimy = dimv[1]
	456
	457	WRFdx = np.zeros((dimy,dimx), dtype=np.float)
	458	WRFdy = np.zeros((dimy,dimx), dtype=np.float)
	459
	460	WRFdx[:,0:dimx-1]=(WRFlon[:,1:dimx]-WRFlon[:,0:dimx-1])*DX/WRFmapfac_m[:,0:dimx-1]
	461	WRFdy[0:dimy-1,:]=(WRFlat[1:dimy,:]-WRFlat[0:dimy-1,:])*DY/WRFmapfac_m[0:dimy-1,:]
	462	WRFds = np.sqrt(WRFdx2 + WRFdy2)
	463
	464	# Attributes of the variable
	465	Vvals = gen.variables_values('WRFdx')
	466	dictcompvars['WRFdx'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	467	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	468	Vvals = gen.variables_values('WRFdy')
	469	dictcompvars['WRFdy'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	470	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	471	Vvals = gen.variables_values('WRFds')
	472	dictcompvars['WRFds'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	473	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	474
[2222]	475	if LONLATdxdy_compute:
	476	print ' ' + main + ': Retrieving dxdy: real distance between grid points ' + \
	477	'from a regular lonlat projection as dx=(lon[i+1]-lon[i])raddegRearth*' + \
	478	'cos(abs(lat[i])); dy=(lat[j+1]-lat[i])raddegRearth; ds=sqrt(dx2+dy2); '+\
	479	'raddeg = pi/180; Rearth=6370.0e03'
	480	dimv = ncobj.variables['lon'].shape
	481	lon = ncobj.variables['lon'][:]
	482	lat = ncobj.variables['lat'][:]
	483
	484	WRFlon, WRFlat = gen.lonlat2D(lon,lat)
	485
	486	dimx = WRFlon.shape[1]
	487	dimy = WRFlon.shape[0]
	488
	489	WRFdx = np.zeros((dimy,dimx), dtype=np.float)
	490	WRFdy = np.zeros((dimy,dimx), dtype=np.float)
	491
	492	raddeg = np.pi/180.
	493
	494	Rearth = fdef.module_definitions.earthradii
	495
	496	WRFdx[:,0:dimx-1]=(WRFlon[:,1:dimx]-WRFlon[:,0:dimx-1])raddegRearth* \
	497	np.cos(np.abs(WRFlat[:,0:dimx-1]*raddeg))
	498	WRFdy[0:dimy-1,:]=(WRFlat[1:dimy,:]-WRFlat[0:dimy-1,:])raddegRearth
	499	WRFds = np.sqrt(WRFdx2 + WRFdy2)
	500
	501	# Attributes of the variable
	502	Vvals = gen.variables_values('WRFdx')
	503	dictcompvars['WRFdx'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	504	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	505	Vvals = gen.variables_values('WRFdy')
	506	dictcompvars['WRFdy'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	507	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	508	Vvals = gen.variables_values('WRFds')
[2215]	509	dictcompvars['WRFds'] = {'name': Vvals[0], 'standard_name': Vvals[1], \
	510	'long_name': Vvals[4].replace('\|',' '), 'units': Vvals[5]}
	511
[365]	512	### ## #
	513	# Going for the diagnostics
	514	### ## #
	515	print ' ' + main + ' ...'
[1404]	516	varsadd = []
[365]	517
	518	for idiag in range(Ndiags):
	519	print ' diagnostic:',diags[idiag]
[1758]	520	diagn = diags[idiag].split('\|')[0]
[365]	521	depvars = diags[idiag].split('\|')[1].split('@')
[1809]	522	if not gen.searchInlist(NONcheckdepvars, diagn):
	523	if diags[idiag].split('\|')[1].find('@') != -1:
	524	depvars = diags[idiag].split('\|')[1].split('@')
	525	if depvars[0] == 'deaccum': diagn='deaccum'
	526	if depvars[0] == 'accum': diagn='accum'
	527	for depv in depvars:
[2212]	528	# Checking without extra arguments of a depending variable (':', separated)
	529	if depv.find(':') != -1: depv=depv.split(':')[0]
[1809]	530	if not ncobj.variables.has_key(depv) and not \
	531	gen.searchInlist(NONcheckingvars, depv) and \
	532	not gen.searchInlist(methods, depv) and not depvars[0] == 'deaccum'\
	533	and not depvars[0] == 'accum' and not depv[0:2] == 'z=':
	534	print errormsg
	535	print ' ' + main + ": file '" + opts.ncfile + \
	536	"' does not have variable '" + depv + "' !!"
	537	quit(-1)
	538	else:
	539	depvars = diags[idiag].split('\|')[1]
	540	if not ncobj.variables.has_key(depvars) and not \
	541	gen.searchInlist(NONcheckingvars, depvars) and \
	542	not gen.searchInlist(methods, depvars):
[365]	543	print errormsg
	544	print ' ' + main + ": file '" + opts.ncfile + \
[1809]	545	"' does not have variable '" + depvars + "' !!"
[365]	546	quit(-1)
	547
[1758]	548	print "\n Computing '" + diagn + "' from: ", depvars, '...'
[365]	549
[2095]	550	# acraintot: accumulated total precipitation from WRF RAINC, RAINNC, RAINSH
[1758]	551	if diagn == 'ACRAINTOT':
[365]	552
	553	var0 = ncobj.variables[depvars[0]]
	554	var1 = ncobj.variables[depvars[1]]
[2095]	555	var2 = ncobj.variables[depvars[2]]
[365]	556
[2095]	557	diagout = var0[:] + var1[:] + var2[:]
	558
[365]	559	dnamesvar = var0.dimensions
	560	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	561
[1647]	562	# Removing the nonChecking variable-dimensions from the initial list
	563	varsadd = []
	564	for nonvd in NONchkvardims:
	565	if gen.searchInlist(dvnamesvar,nonvd): dvnamesvar.remove(nonvd)
	566	varsadd.append(nonvd)
	567
[649]	568	ncvar.insert_variable(ncobj, 'pracc', diagout, dnamesvar, dvnamesvar, newnc)
[365]	569
[649]	570	# accum: acumulation of any variable as (Variable, time [as [tunits]
	571	# from/since ....], newvarname)
[1758]	572	elif diagn == 'accum':
[649]	573
	574	var0 = ncobj.variables[depvars[0]]
	575	var1 = ncobj.variables[depvars[1]]
	576
	577	dnamesvar = var0.dimensions
	578	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	579
[1675]	580	diagout, diagoutd, diagoutvd = diag.compute_accum(var0,dnamesvar,dvnamesvar)
[1825]	581	# Removing the nonChecking variable-dimensions from the initial list
	582	varsadd = []
	583	diagoutvd = list(dvnames)
	584	for nonvd in NONchkvardims:
	585	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	586	varsadd.append(nonvd)
[649]	587
	588	CFvarn = ncvar.variables_values(depvars[0])[0]
	589
	590	# Removing the flux
	591	if depvars[1] == 'XTIME':
	592	dtimeunits = var1.getncattr('description')
	593	tunits = dtimeunits.split(' ')[0]
	594	else:
	595	dtimeunits = var1.getncattr('units')
	596	tunits = dtimeunits.split(' ')[0]
	597
[1825]	598	dtime = (var1[1] - var1[0])*diag.timeunits_seconds(tunits)
[649]	599
	600	ncvar.insert_variable(ncobj, CFvarn + 'acc', diagout*dtime, diagoutd, diagoutvd, newnc)
	601
[365]	602	# cllmh with cldfra, pres
[1758]	603	elif diagn == 'cllmh':
[365]	604
	605	var0 = ncobj.variables[depvars[0]]
	606	if depvars[1] == 'WRFp':
	607	var1 = WRFp
	608	else:
	609	var01 = ncobj.variables[depvars[1]]
	610	if len(size(var1.shape)) < len(size(var0.shape)):
	611	var1 = np.brodcast_arrays(var01,var0)[0]
	612	else:
	613	var1 = var01
	614
[1675]	615	diagout, diagoutd, diagoutvd = diag.Forcompute_cllmh(var0,var1,dnames,dvnames)
[772]	616
[1351]	617	# Removing the nonChecking variable-dimensions from the initial list
	618	varsadd = []
	619	for nonvd in NONchkvardims:
	620	if gen.searchInlist(diagoutvd,nonvd): diagoutvd.remove(nonvd)
	621	varsadd.append(nonvd)
	622
[365]	623	ncvar.insert_variable(ncobj, 'cll', diagout[0,:], diagoutd, diagoutvd, newnc)
	624	ncvar.insert_variable(ncobj, 'clm', diagout[1,:], diagoutd, diagoutvd, newnc)
	625	ncvar.insert_variable(ncobj, 'clh', diagout[2,:], diagoutd, diagoutvd, newnc)
	626
	627	# clt with cldfra
[1758]	628	elif diagn == 'clt':
[365]	629
	630	var0 = ncobj.variables[depvars]
[1675]	631	diagout, diagoutd, diagoutvd = diag.Forcompute_clt(var0,dnames,dvnames)
[1351]	632
	633	# Removing the nonChecking variable-dimensions from the initial list
	634	varsadd = []
	635	for nonvd in NONchkvardims:
	636	if gen.searchInlist(diagoutvd,nonvd): diagoutvd.remove(nonvd)
	637	varsadd.append(nonvd)
	638
[365]	639	ncvar.insert_variable(ncobj, 'clt', diagout, diagoutd, diagoutvd, newnc)
	640
[2100]	641	# convini (pr, time)
	642	elif diagn == 'convini':
	643
	644	var0 = ncobj.variables[depvars[0]][:]
	645	var1 = ncobj.variables[depvars[1]][:]
	646	otime = ncobj.variables[depvars[1]]
	647
	648	dnamesvar = ncobj.variables[depvars[0]].dimensions
	649	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	650
	651	diagout, diagoutd, diagoutvd = diag.var_convini(var0, var1, dnames, dvnames)
	652
	653	ncvar.insert_variable(ncobj, 'convini', diagout, diagoutd, diagoutvd, newnc, \
	654	fill=gen.fillValueF)
	655	# Getting the right units
	656	ovar = newnc.variables['convini']
	657	if gen.searchInlist(otime.ncattrs(), 'units'):
	658	tunits = otime.getncattr('units')
	659	ncvar.set_attribute(ovar, 'units', tunits)
	660	newnc.sync()
	661
[365]	662	# deaccum: deacumulation of any variable as (Variable, time [as [tunits]
	663	# from/since ....], newvarname)
[1758]	664	elif diagn == 'deaccum':
[365]	665
[1825]	666	var0 = ncobj.variables[depvars[0]]
	667	var1 = ncobj.variables[depvars[1]]
[365]	668
	669	dnamesvar = var0.dimensions
	670	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	671
[1675]	672	diagout, diagoutd, diagoutvd = diag.compute_deaccum(var0,dnamesvar,dvnamesvar)
[1825]	673	# Removing the nonChecking variable-dimensions from the initial list
	674	varsadd = []
	675	diagoutvd = list(dvnames)
	676	for nonvd in NONchkvardims:
	677	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	678	varsadd.append(nonvd)
[365]	679
	680	# Transforming to a flux
[1825]	681	if depvars[1] == 'XTIME':
[365]	682	dtimeunits = var1.getncattr('description')
	683	tunits = dtimeunits.split(' ')[0]
	684	else:
	685	dtimeunits = var1.getncattr('units')
	686	tunits = dtimeunits.split(' ')[0]
	687
[1825]	688	dtime = (var1[1] - var1[0])*diag.timeunits_seconds(tunits)
[1908]	689	ncvar.insert_variable(ncobj, depvars[2], diagout/dtime, diagoutd, diagoutvd, \
	690	newnc)
[365]	691
[1909]	692	# fog_K84: Computation of fog and visibility following Kunkel, (1984) as QCLOUD, QICE
[1908]	693	elif diagn == 'fog_K84':
	694
	695	var0 = ncobj.variables[depvars[0]]
	696	var1 = ncobj.variables[depvars[1]]
	697
	698	dnamesvar = list(var0.dimensions)
	699	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	700
	701	diag1, diag2, diagoutd, diagoutvd = diag.Forcompute_fog_K84(var0, var1, \
	702	dnamesvar, dvnamesvar)
	703	# Removing the nonChecking variable-dimensions from the initial list
	704	varsadd = []
	705	diagoutvd = list(dvnames)
	706	for nonvd in NONchkvardims:
	707	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	708	varsadd.append(nonvd)
	709	ncvar.insert_variable(ncobj, 'fog', diag1, diagoutd, diagoutvd, newnc)
	710	ncvar.insert_variable(ncobj, 'fogvisblty', diag2, diagoutd, diagoutvd, newnc)
	711
[1909]	712	# fog_RUC: Computation of fog and visibility following Kunkel, (1984) as QVAPOR,
	713	# WRFt, WRFp or Q2, T2, PSFC
[1908]	714	elif diagn == 'fog_RUC':
	715
	716	var0 = ncobj.variables[depvars[0]]
[1909]	717	print gen.infmsg
	718	if depvars[1] == 'WRFt':
	719	print ' ' + main + ": computing '" + diagn + "' using 3D variables !!"
	720	var1 = WRFt
	721	var2 = WRFp
	722	else:
	723	print ' ' + main + ": computing '" + diagn + "' using 2D variables !!"
	724	var1 = ncobj.variables[depvars[1]]
	725	var2 = ncobj.variables[depvars[2]]
[1908]	726
	727	dnamesvar = list(var0.dimensions)
	728	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	729
[1909]	730	diag1, diag2, diagoutd, diagoutvd = diag.Forcompute_fog_RUC(var0, var1, var2,\
[1908]	731	dnamesvar, dvnamesvar)
	732	# Removing the nonChecking variable-dimensions from the initial list
	733	varsadd = []
	734	diagoutvd = list(dvnames)
	735	for nonvd in NONchkvardims:
	736	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	737	varsadd.append(nonvd)
	738	ncvar.insert_variable(ncobj, 'fog', diag1, diagoutd, diagoutvd, newnc)
	739	ncvar.insert_variable(ncobj, 'fogvisblty', diag2, diagoutd, diagoutvd, newnc)
	740
[1909]	741	# fog_FRAML50: Computation of fog and visibility following Gultepe, I. and
	742	# J.A. Milbrandt, 2010 as QVAPOR, WRFt, WRFp or Q2, T2, PSFC
	743	elif diagn == 'fog_FRAML50':
	744
	745	var0 = ncobj.variables[depvars[0]]
	746	print gen.infmsg
	747	if depvars[1] == 'WRFt':
	748	print ' ' + main + ": computing '" + diagn + "' using 3D variables !!"
	749	var1 = WRFt
	750	var2 = WRFp
	751	else:
	752	print ' ' + main + ": computing '" + diagn + "' using 2D variables !!"
	753	var1 = ncobj.variables[depvars[1]]
	754	var2 = ncobj.variables[depvars[2]]
	755
	756	dnamesvar = list(var0.dimensions)
	757	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	758
	759	diag1, diag2, diagoutd, diagoutvd = diag.Forcompute_fog_FRAML50(var0, var1, \
	760	var2, dnamesvar, dvnamesvar)
	761	# Removing the nonChecking variable-dimensions from the initial list
	762	varsadd = []
	763	diagoutvd = list(dvnames)
	764	for nonvd in NONchkvardims:
	765	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	766	varsadd.append(nonvd)
	767	ncvar.insert_variable(ncobj, 'fog', diag1, diagoutd, diagoutvd, newnc)
	768	ncvar.insert_variable(ncobj, 'fogvisblty', diag2, diagoutd, diagoutvd, newnc)
	769
[365]	770	# LMDZrh (pres, t, r)
[1758]	771	elif diagn == 'LMDZrh':
[365]	772
	773	var0 = ncobj.variables[depvars[0]][:]
	774	var1 = ncobj.variables[depvars[1]][:]
	775	var2 = ncobj.variables[depvars[2]][:]
	776
[1675]	777	diagout, diagoutd, diagoutvd = diag.compute_rh(var0,var1,var2,dnames,dvnames)
[1079]	778	ncvar.insert_variable(ncobj, 'hur', diagout, diagoutd, diagoutvd, newnc)
[365]	779
	780	# LMDZrhs (psol, t2m, q2m)
[1758]	781	elif diagn == 'LMDZrhs':
[365]	782
	783	var0 = ncobj.variables[depvars[0]][:]
	784	var1 = ncobj.variables[depvars[1]][:]
	785	var2 = ncobj.variables[depvars[2]][:]
	786
	787	dnamesvar = ncobj.variables[depvars[0]].dimensions
	788	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	789
[1675]	790	diagout, diagoutd, diagoutvd = diag.compute_rh(var0,var1,var2,dnamesvar,dvnamesvar)
[365]	791
[1079]	792	ncvar.insert_variable(ncobj, 'hurs', diagout, diagoutd, diagoutvd, newnc)
[365]	793
[2215]	794	# range_faces: LON, LAT, HGT, WRFdxdy, 'face:['WE'/'SN']:[dsfilt]:[dsnewrange]:[hvalleyrange]'
[2208]	795	elif diagn == 'range_faces':
	796
	797	var0 = ncobj.variables[depvars[0]][:]
	798	var1 = ncobj.variables[depvars[1]][:]
	799	var2 = ncobj.variables[depvars[2]][:]
[2215]	800	face = depvars[4].split(':')[1]
	801	dsfilt = np.float(depvars[4].split(':')[2])
	802	dsnewrange = np.float(depvars[4].split(':')[3])
	803	hvalleyrange = np.float(depvars[4].split(':')[4])
[2208]	804
[2222]	805	dnamesvar = list(ncobj.variables[depvars[2]].dimensions)
[2212]	806	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
[2209]	807	lon, lat = gen.lonlat2D(var0, var1)
	808	if len(var2.shape) == 3:
	809	print warnmsg
	810	print ' ' + diagn + ": shapping to 2D variable '" + depvars[2] + "' !!"
	811	hgt = var2[0,:,:]
[2212]	812	dnamesvar.pop(0)
	813	dvnamesvar.pop(0)
[2209]	814	else:
	815	hgt = var2[:]
	816
[2213]	817	orogmax, ptorogmax, dhgt, peaks, valleys, origfaces, diagout, diagoutd, \
[2223]	818	diagoutvd, rng, rngorogmax, ptrngorogmax= diag.Forcompute_range_faces(lon, \
[2260]	819	lat, hgt, WRFdx, WRFdy, WRFds, face, dsfilt, dsnewrange, hvalleyrange, \
	820	dnamesvar, dvnamesvar)
[2208]	821
	822	# Removing the nonChecking variable-dimensions from the initial list
	823	varsadd = []
	824	diagoutvd = list(dvnames)
	825	for nonvd in NONchkvardims:
	826	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	827	varsadd.append(nonvd)
[2212]	828
[2215]	829	ncvar.insert_variable(ncobj, 'dx', WRFdx, diagoutd, diagoutvd, newnc)
	830	ncvar.insert_variable(ncobj, 'dy', WRFdy, diagoutd, diagoutvd, newnc)
	831	ncvar.insert_variable(ncobj, 'ds', WRFds, diagoutd, diagoutvd, newnc)
	832
[2213]	833	# adding variables to output file
	834	if face == 'WE': axis = 'lon'
	835	elif face == 'SN': axis = 'lat'
	836
[2223]	837	ncvar.insert_variable(ncobj, 'range', rng, diagoutd, diagoutvd, newnc, \
	838	fill=gen.fillValueI)
	839	ovar = newnc.variables['range']
	840	ncvar.set_attribute(ovar, 'deriv', axis)
	841
[2214]	842	ncvar.insert_variable(ncobj, 'orogmax', rngorogmax, diagoutd, diagoutvd, \
[2222]	843	newnc, fill=gen.fillValueF)
[2214]	844	newnc.renameVariable('orogmax', 'rangeorogmax')
	845	ovar = newnc.variables['rangeorogmax']
	846	ncvar.set_attribute(ovar, 'deriv', axis)
	847	stdn = ovar.standard_name
	848	ncvar.set_attribute(ovar, 'standard_name', 'range_' + stdn)
	849	Ln = ovar.long_name
	850	ncvar.set_attribute(ovar, 'long_name', 'range ' + stdn)
	851
	852	ncvar.insert_variable(ncobj, 'ptorogmax', ptrngorogmax, diagoutd, diagoutvd, \
	853	newnc)
	854	newnc.renameVariable('ptorogmax', 'rangeptorogmax')
	855	ovar = newnc.variables['rangeptorogmax']
	856	ncvar.set_attribute(ovar, 'deriv', axis)
	857	stdn = ovar.standard_name
	858	ncvar.set_attribute(ovar, 'standard_name', 'range_' + stdn)
	859	Ln = ovar.long_name
	860	ncvar.set_attribute(ovar, 'long_name', 'range ' + stdn)
	861
[2213]	862	ncvar.insert_variable(ncobj, 'orogmax', orogmax, diagoutd, diagoutvd, \
	863	newnc)
	864	ovar = newnc.variables['orogmax']
	865	ncvar.set_attribute(ovar, 'deriv', axis)
	866
	867	ncvar.insert_variable(ncobj, 'ptorogmax', ptorogmax, diagoutd, diagoutvd, \
	868	newnc)
	869	ovar = newnc.variables['ptorogmax']
	870	ncvar.set_attribute(ovar, 'deriv', axis)
	871
[2215]	872	ncvar.insert_variable(ncobj, 'orogderiv', dhgt, diagoutd, diagoutvd, newnc)
	873	ovar = newnc.variables['orogderiv']
[2212]	874	ncvar.set_attribute(ovar, 'deriv', axis)
[2208]	875
[2212]	876	ncvar.insert_variable(ncobj, 'peak', peaks, diagoutd, diagoutvd, newnc)
	877	ncvar.insert_variable(ncobj, 'valley', valleys, diagoutd, diagoutvd, newnc)
	878
	879	ncvar.insert_variable(ncobj, 'rangefaces', diagout, diagoutd, diagoutvd, \
	880	newnc)
	881	newnc.renameVariable('rangefaces', 'rangefacesfilt')
	882	ovar = newnc.variables['rangefacesfilt']
	883	ncvar.set_attribute(ovar, 'face', face)
[2215]	884	ncvar.set_attributek(ovar, 'dist_filter', dsfilt, 'F')
[2212]	885
	886	ncvar.insert_variable(ncobj, 'rangefaces', origfaces, diagoutd, diagoutvd, \
[2215]	887	newnc, fill=gen.fillValueI)
[2212]	888	ovar = newnc.variables['rangefaces']
	889	ncvar.set_attribute(ovar, 'face', face)
[2215]	890	ncvar.set_attributek(ovar, 'dist_newrange', dsnewrange, 'F')
	891	ncvar.set_attributek(ovar, 'h_valley_newrange', hvalleyrange, 'F')
[2212]	892
[2277]	893	# cell_bnds: grid cell bounds from lon, lat from a reglar lon/lat projection as
	894	# intersection of their related parallels and meridians
	895	elif diagn == 'reglonlatbnds':
	896
	897	var00 = ncobj.variables[depvars[0]][:]
	898	var01 = ncobj.variables[depvars[1]][:]
	899
	900	var0, var1 = gen.lonlat2D(var00,var01)
	901
	902	dnamesvar = []
	903	dnamesvar.append('bnds')
	904	if (len(var00.shape) == 3):
	905	dnamesvar.append(ncobj.variables[depvars[0]].dimensions[1])
	906	dnamesvar.append(ncobj.variables[depvars[0]].dimensions[2])
	907	elif (len(var00.shape) == 2):
	908	dnamesvar.append(ncobj.variables[depvars[0]].dimensions[0])
	909	dnamesvar.append(ncobj.variables[depvars[0]].dimensions[1])
	910	elif (len(var00.shape) == 1):
	911	dnamesvar.append(ncobj.variables[depvars[0]].dimensions[0])
	912	dnamesvar.append(ncobj.variables[depvars[1]].dimensions[0])
	913	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	914
	915	cellbndsx, cellbndsy, diagoutd, diagoutvd = diag.Forcompute_cellbndsreg(var0,\
	916	var1, dnamesvar, dvnamesvar)
	917
	918	# Removing the nonChecking variable-dimensions from the initial list
	919	varsadd = []
	920	diagoutvd = list(dvnames)
	921	for nonvd in NONchkvardims:
	922	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	923	varsadd.append(nonvd)
	924	# creation of bounds dimension
	925	newdim = newnc.createDimension('bnds', 4)
	926
	927	ncvar.insert_variable(ncobj, 'lon_bnds', cellbndsx, diagoutd, diagoutvd, newnc)
	928	ncvar.insert_variable(ncobj, 'lat_bnds', cellbndsy, diagoutd, diagoutvd, newnc)
	929
[2274]	930	# cell_bnds: grid cell bounds from XLONG_U, XLAT_U, XLONG_V, XLAT_V as intersection
	931	# of their related parallels and meridians
	932	elif diagn == 'WRFbnds':
	933
	934	var0 = ncobj.variables[depvars[0]][0,:,:]
	935	var1 = ncobj.variables[depvars[1]][0,:,:]
	936	var2 = ncobj.variables[depvars[2]][0,:,:]
	937	var3 = ncobj.variables[depvars[3]][0,:,:]
	938
	939	dnamesvar = []
[2276]	940	dnamesvar.append('bnds')
	941	dnamesvar.append(ncobj.variables[depvars[0]].dimensions[1])
[2274]	942	dnamesvar.append(ncobj.variables[depvars[2]].dimensions[2])
	943	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	944
	945	cellbndsx, cellbndsy, diagoutd, diagoutvd = diag.Forcompute_cellbnds(var0, \
	946	var1, var2, var3, dnamesvar, dvnamesvar)
	947
	948	# Removing the nonChecking variable-dimensions from the initial list
	949	varsadd = []
	950	diagoutvd = list(dvnames)
	951	for nonvd in NONchkvardims:
	952	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	953	varsadd.append(nonvd)
	954	# creation of bounds dimension
	955	newdim = newnc.createDimension('bnds', 4)
	956
	957	ncvar.insert_variable(ncobj, 'lon_bnds', cellbndsx, diagoutd, diagoutvd, newnc)
[2285]	958	newnc.sync()
[2274]	959	ncvar.insert_variable(ncobj, 'lat_bnds', cellbndsy, diagoutd, diagoutvd, newnc)
[2285]	960	newnc.sync()
[2274]	961
[2283]	962	ovar = newnc.variables['XLONG']
[2285]	963	ovar.setncattr('bounds', 'lon_bnds lat_bnds')
[2283]	964	ovar = newnc.variables['XLAT']
[2285]	965	ovar.setncattr('bounds', 'lon_bnds lat_bnds')
[2283]	966
[1762]	967	# mrso: total soil moisture SMOIS, DZS
	968	elif diagn == 'WRFmrso':
	969
	970	var0 = ncobj.variables[depvars[0]][:]
	971	var10 = ncobj.variables[depvars[1]][:]
	972	dnamesvar = list(ncobj.variables[depvars[0]].dimensions)
	973	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	974
	975	var1 = var0.copy()*0.
	976	var2 = var0.copy()*0.+1.
	977	# Must be a better way....
	978	for j in range(var0.shape[2]):
	979	for i in range(var0.shape[3]):
	980	var1[:,:,j,i] = var10
	981
	982	diagout, diagoutd, diagoutvd = diag.Forcompute_zint(var0, var1, var2, \
	983	dnamesvar, dvnamesvar)
	984
	985	# Removing the nonChecking variable-dimensions from the initial list
	986	varsadd = []
	987	diagoutvd = list(dvnames)
	988	for nonvd in NONchkvardims:
	989	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	990	varsadd.append(nonvd)
	991	ncvar.insert_variable(ncobj, 'mrso', diagout, diagoutd, diagoutvd, newnc)
	992
[2206]	993	# mrsos: First layer soil moisture SMOIS, DZS
	994	elif diagn == 'WRFmrsos':
	995
	996	var0 = ncobj.variables[depvars[0]][:]
	997	var1 = ncobj.variables[depvars[1]][:]
	998	diagoutd = list(ncobj.variables[depvars[0]].dimensions)
	999	diagoutvd = ncvar.var_dim_dimv(diagoutd,dnames,dvnames)
	1000
	1001	diagoutd.pop(1)
	1002	diagoutvd.pop(1)
	1003
	1004	diagout= np.zeros((var0.shape[0],var0.shape[2],var0.shape[3]), dtype=np.float)
	1005
	1006	# Must be a better way....
	1007	for j in range(var0.shape[2]):
	1008	for i in range(var0.shape[3]):
	1009	diagout[:,j,i] = var0[:,0,j,i]*var1[:,0]
	1010
	1011	# Removing the nonChecking variable-dimensions from the initial list
	1012	varsadd = []
	1013	diagoutvd = list(dvnames)
	1014	for nonvd in NONchkvardims:
	1015	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1016	varsadd.append(nonvd)
	1017	ncvar.insert_variable(ncobj, 'mrsos', diagout, diagoutd, diagoutvd, newnc)
	1018
[365]	1019	# mslp: mean sea level pressure (pres, psfc, terrain, temp, qv)
[1758]	1020	elif diagn == 'mslp' or diagn == 'WRFmslp':
[365]	1021
	1022	var1 = ncobj.variables[depvars[1]][:]
	1023	var2 = ncobj.variables[depvars[2]][:]
	1024	var4 = ncobj.variables[depvars[4]][:]
	1025
[1758]	1026	if diagn == 'WRFmslp':
[365]	1027	var0 = WRFp
	1028	var3 = WRFt
	1029	dnamesvar = ncobj.variables['P'].dimensions
	1030	else:
	1031	var0 = ncobj.variables[depvars[0]][:]
	1032	var3 = ncobj.variables[depvars[3]][:]
	1033	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1034
	1035	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1036
[1675]	1037	diagout, diagoutd, diagoutvd = diag.compute_mslp(var0, var1, var2, var3, var4, \
[365]	1038	dnamesvar, dvnamesvar)
	1039
[1581]	1040	# Removing the nonChecking variable-dimensions from the initial list
	1041	varsadd = []
	1042	diagoutvd = list(dvnames)
	1043	for nonvd in NONchkvardims:
	1044	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1045	varsadd.append(nonvd)
[365]	1046	ncvar.insert_variable(ncobj, 'psl', diagout, diagoutd, diagoutvd, newnc)
	1047
[642]	1048	# OMEGAw (omega, p, t) from NCL formulation (https://www.ncl.ucar.edu/Document/Functions/Contributed/omega_to_w.shtml)
[1758]	1049	elif diagn == 'OMEGAw':
[642]	1050
	1051	var0 = ncobj.variables[depvars[0]][:]
	1052	var1 = ncobj.variables[depvars[1]][:]
[643]	1053	var2 = ncobj.variables[depvars[2]][:]
[642]	1054
	1055	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1056	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1057
[1675]	1058	diagout, diagoutd, diagoutvd = diag.compute_OMEGAw(var0,var1,var2,dnamesvar,dvnamesvar)
[642]	1059
	1060	ncvar.insert_variable(ncobj, 'wa', diagout, diagoutd, diagoutvd, newnc)
	1061
[2095]	1062	# raintot: instantaneous total precipitation from WRF as (RAINC + RAINC + RAINSH) / dTime
[1758]	1063	elif diagn == 'RAINTOT':
[365]	1064
	1065	var0 = ncobj.variables[depvars[0]]
	1066	var1 = ncobj.variables[depvars[1]]
[2095]	1067	var2 = ncobj.variables[depvars[2]]
	1068
	1069	if depvars[3] != 'WRFtime':
	1070	var3 = ncobj.variables[depvars[3]]
[654]	1071	else:
[2095]	1072	var3 = np.arange(var0.shape[0], dtype=int)
[365]	1073
[2095]	1074	var = var0[:] + var1[:] + var2[:]
[365]	1075
	1076	dnamesvar = var0.dimensions
	1077	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1078
[1675]	1079	diagout, diagoutd, diagoutvd = diag.compute_deaccum(var,dnamesvar,dvnamesvar)
[365]	1080
	1081	# Transforming to a flux
[2095]	1082	if var3.shape[0] > 1:
	1083	if depvars[3] != 'WRFtime':
	1084	dtimeunits = var3.getncattr('units')
[600]	1085	tunits = dtimeunits.split(' ')[0]
	1086
[2095]	1087	dtime = (var3[1] - var3[0])*diag.timeunits_seconds(tunits)
[600]	1088	else:
[2095]	1089	var3 = ncobj.variables['Times']
	1090	time1 = var3[0,:]
	1091	time2 = var3[1,:]
[600]	1092	tmf1 = ''
	1093	tmf2 = ''
	1094	for ic in range(len(time1)):
	1095	tmf1 = tmf1 + time1[ic]
	1096	tmf2 = tmf2 + time2[ic]
[654]	1097	dtdate1 = dtime.datetime.strptime(tmf1,"%Y-%m-%d_%H:%M:%S")
	1098	dtdate2 = dtime.datetime.strptime(tmf2,"%Y-%m-%d_%H:%M:%S")
[600]	1099	diffdate12 = dtdate2 - dtdate1
	1100	dtime = diffdate12.total_seconds()
	1101	print 'dtime:',dtime
[442]	1102	else:
[600]	1103	print warnmsg
[1645]	1104	print ' ' + main + ": only 1 time-step for '" + diag + "' !!"
[600]	1105	print ' leaving a zero value!'
[1646]	1106	diagout = var0[:]*0.
[600]	1107	dtime=1.
[442]	1108
[1644]	1109	# Removing the nonChecking variable-dimensions from the initial list
	1110	varsadd = []
	1111	for nonvd in NONchkvardims:
	1112	if gen.searchInlist(diagoutvd,nonvd): diagoutvd.remove(nonvd)
	1113	varsadd.append(nonvd)
	1114
[365]	1115	ncvar.insert_variable(ncobj, 'pr', diagout/dtime, diagoutd, diagoutvd, newnc)
	1116
[2140]	1117	# timemax ([varname], time). When a given variable [varname] got its maximum
	1118	elif diagn == 'timemax':
	1119
	1120	var0 = ncobj.variables[depvars[0]][:]
	1121	var1 = ncobj.variables[depvars[1]][:]
	1122
	1123	otime = ncobj.variables[depvars[1]]
	1124
	1125	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1126	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1127
	1128	diagout, diagoutd, diagoutvd = diag.var_timemax(var0, var1, dnames, \
	1129	dvnames)
	1130
	1131	ncvar.insert_variable(ncobj, 'timemax', diagout, diagoutd, diagoutvd, newnc, \
	1132	fill=gen.fillValueF)
	1133	# Getting the right units
	1134	ovar = newnc.variables['timemax']
	1135	if gen.searchInlist(otime.ncattrs(), 'units'):
	1136	tunits = otime.getncattr('units')
	1137	ncvar.set_attribute(ovar, 'units', tunits)
	1138	newnc.sync()
	1139	ncvar.set_attribute(ovar, 'variable', depvars[0])
	1140
[2138]	1141	# timeoverthres ([varname], time, [value], [CFvarn]). When a given variable [varname]
	1142	# overpass a given [value]. Being [CFvarn] the name of the diagnostics in
	1143	# variables_values.dat
	1144	elif diagn == 'timeoverthres':
	1145
	1146	var0 = ncobj.variables[depvars[0]][:]
	1147	var1 = ncobj.variables[depvars[1]][:]
	1148	var2 = np.float(depvars[2])
	1149	var3 = depvars[3]
	1150
	1151	otime = ncobj.variables[depvars[1]]
	1152
	1153	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1154	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1155
	1156	diagout, diagoutd, diagoutvd = diag.var_timeoverthres(var0, var1, var2, \
	1157	dnames, dvnames)
	1158
	1159	ncvar.insert_variable(ncobj, var3, diagout, diagoutd, diagoutvd, newnc, \
	1160	fill=gen.fillValueF)
	1161	# Getting the right units
	1162	ovar = newnc.variables[var3]
	1163	if gen.searchInlist(otime.ncattrs(), 'units'):
	1164	tunits = otime.getncattr('units')
	1165	ncvar.set_attribute(ovar, 'units', tunits)
	1166	newnc.sync()
	1167	ncvar.set_attribute(ovar, 'overpassed_threshold', var2)
	1168
[612]	1169	# rhs (psfc, t, q) from TimeSeries files
[1758]	1170	elif diagn == 'TSrhs':
[612]	1171
	1172	p0=100000.
	1173	var0 = ncobj.variables[depvars[0]][:]
	1174	var1 = (ncobj.variables[depvars[1]][:])(var0/p0)*(2./7.)
	1175	var2 = ncobj.variables[depvars[2]][:]
	1176
	1177	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1178	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1179
[1675]	1180	diagout, diagoutd, diagoutvd = diag.compute_rh(var0,var1,var2,dnamesvar,dvnamesvar)
[612]	1181
[1079]	1182	ncvar.insert_variable(ncobj, 'hurs', diagout, diagoutd, diagoutvd, newnc)
[612]	1183
[1762]	1184	# slw: total soil liquid water SH2O, DZS
	1185	elif diagn == 'WRFslw':
	1186
	1187	var0 = ncobj.variables[depvars[0]][:]
	1188	var10 = ncobj.variables[depvars[1]][:]
	1189	dnamesvar = list(ncobj.variables[depvars[0]].dimensions)
	1190	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1191
	1192	var1 = var0.copy()*0.
	1193	var2 = var0.copy()*0.+1.
	1194	# Must be a better way....
	1195	for j in range(var0.shape[2]):
	1196	for i in range(var0.shape[3]):
	1197	var1[:,:,j,i] = var10
	1198
	1199	diagout, diagoutd, diagoutvd = diag.Forcompute_zint(var0, var1, var2, \
	1200	dnamesvar, dvnamesvar)
	1201
	1202	# Removing the nonChecking variable-dimensions from the initial list
	1203	varsadd = []
	1204	diagoutvd = list(dvnames)
	1205	for nonvd in NONchkvardims:
	1206	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1207	varsadd.append(nonvd)
	1208	ncvar.insert_variable(ncobj, 'slw', diagout, diagoutd, diagoutvd, newnc)
	1209
[612]	1210	# td (psfc, t, q) from TimeSeries files
[1758]	1211	elif diagn == 'TStd' or diagn == 'td':
[612]	1212
	1213	var0 = ncobj.variables[depvars[0]][:]
	1214	var1 = ncobj.variables[depvars[1]][:] - 273.15
	1215	var2 = ncobj.variables[depvars[2]][:]
	1216
	1217	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1218	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1219
[1675]	1220	diagout, diagoutd, diagoutvd = diag.compute_td(var0,var1,var2,dnamesvar,dvnamesvar)
[612]	1221
[1966]	1222	ncvar.insert_variable(ncobj, 'tdas', diagout, diagoutd, diagoutvd, newnc)
[612]	1223
	1224	# td (psfc, t, q) from TimeSeries files
[1758]	1225	elif diagn == 'TStdC' or diagn == 'tdC':
[612]	1226
	1227	var0 = ncobj.variables[depvars[0]][:]
	1228	# Temperature is already in degrees Celsius
	1229	var1 = ncobj.variables[depvars[1]][:]
	1230	var2 = ncobj.variables[depvars[2]][:]
	1231
	1232	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1233	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1234
[1675]	1235	diagout, diagoutd, diagoutvd = diag.compute_td(var0,var1,var2,dnamesvar,dvnamesvar)
[612]	1236
[1999]	1237	# Removing the nonChecking variable-dimensions from the initial list
	1238	varsadd = []
	1239	for nonvd in NONchkvardims:
	1240	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1241	varsadd.append(nonvd)
	1242
[1966]	1243	ncvar.insert_variable(ncobj, 'tdas', diagout, diagoutd, diagoutvd, newnc)
[612]	1244
	1245	# wds (u, v)
[1758]	1246	elif diagn == 'TSwds' or diagn == 'wds' :
[612]	1247
	1248	var0 = ncobj.variables[depvars[0]][:]
	1249	var1 = ncobj.variables[depvars[1]][:]
	1250
	1251	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1252	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1253
[1675]	1254	diagout, diagoutd, diagoutvd = diag.compute_wds(var0,var1,dnamesvar,dvnamesvar)
[612]	1255
[1999]	1256	# Removing the nonChecking variable-dimensions from the initial list
	1257	varsadd = []
	1258	for nonvd in NONchkvardims:
	1259	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1260	varsadd.append(nonvd)
	1261
[612]	1262	ncvar.insert_variable(ncobj, 'wds', diagout, diagoutd, diagoutvd, newnc)
	1263
	1264	# wss (u, v)
[1758]	1265	elif diagn == 'TSwss' or diagn == 'wss':
[612]	1266
	1267	var0 = ncobj.variables[depvars[0]][:]
	1268	var1 = ncobj.variables[depvars[1]][:]
	1269
	1270	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1271	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1272
[1675]	1273	diagout, diagoutd, diagoutvd = diag.compute_wss(var0,var1,dnamesvar,dvnamesvar)
[612]	1274
[1999]	1275	# Removing the nonChecking variable-dimensions from the initial list
	1276	varsadd = []
	1277	for nonvd in NONchkvardims:
	1278	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1279	varsadd.append(nonvd)
	1280
[612]	1281	ncvar.insert_variable(ncobj, 'wss', diagout, diagoutd, diagoutvd, newnc)
	1282
[365]	1283	# turbulence (var)
[1758]	1284	elif diagn == 'turbulence':
[365]	1285
	1286	var0 = ncobj.variables[depvars][:]
	1287
	1288	dnamesvar = list(ncobj.variables[depvars].dimensions)
	1289	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1290
[1675]	1291	diagout, diagoutd, diagoutvd = diag.compute_turbulence(var0,dnamesvar,dvnamesvar)
[959]	1292	valsvar = gen.variables_values(depvars)
[365]	1293
[959]	1294	newvarn = depvars + 'turb'
	1295	ncvar.insert_variable(ncobj, newvarn, diagout, diagoutd,
[365]	1296	diagoutvd, newnc)
[959]	1297	varobj = newnc.variables[newvarn]
[365]	1298	attrv = varobj.long_name
	1299	attr = varobj.delncattr('long_name')
	1300	newattr = ncvar.set_attribute(varobj, 'long_name', attrv + \
	1301	" Taylor decomposition turbulence term")
	1302
[1927]	1303	# ua va from ws wd (deg)
	1304	elif diagn == 'uavaFROMwswd':
	1305
	1306	var0 = ncobj.variables[depvars[0]][:]
	1307	var1 = ncobj.variables[depvars[1]][:]
	1308
	1309	ua = var0np.cos(var1np.pi/180.)
	1310	va = var0np.sin(var1np.pi/180.)
	1311
	1312	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1313	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1314
	1315	ncvar.insert_variable(ncobj, 'ua', ua, dnamesvar, dvnamesvar, newnc)
	1316	ncvar.insert_variable(ncobj, 'va', va, dnamesvar, dvnamesvar, newnc)
	1317
[2033]	1318	# ua va from obs ws wd (deg)
	1319	elif diagn == 'uavaFROMobswswd':
	1320
	1321	var0 = ncobj.variables[depvars[0]][:]
	1322	var1 = ncobj.variables[depvars[1]][:]
[1927]	1323
[2033]	1324	ua = var0np.cos((var1+180.)np.pi/180.)
	1325	va = var0np.sin((var1+180.)np.pi/180.)
	1326
	1327	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1328	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1329
	1330	ncvar.insert_variable(ncobj, 'ua', ua, dnamesvar, dvnamesvar, newnc)
	1331	ncvar.insert_variable(ncobj, 'va', va, dnamesvar, dvnamesvar, newnc)
	1332
[390]	1333	# WRFbils fom WRF as HFX + LH
[1758]	1334	elif diagn == 'WRFbils':
[390]	1335
	1336	var0 = ncobj.variables[depvars[0]][:]
	1337	var1 = ncobj.variables[depvars[1]][:]
	1338
	1339	diagout = var0 + var1
[867]	1340	dnamesvar = list(ncobj.variables[depvars[0]].dimensions)
	1341	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
[390]	1342
[867]	1343	ncvar.insert_variable(ncobj, 'bils', diagout, dnamesvar, dvnamesvar, newnc)
[390]	1344
[1759]	1345	# WRFcape_afwa CAPE, CIN, ZLFC, PLFC, LI following WRF 'phys/module_diaf_afwa.F'
	1346	# methodology as WRFt, WRFrh, WRFp, WRFgeop, HGT
	1347	elif diagn == 'WRFcape_afwa':
	1348	var0 = WRFt
	1349	var1 = WRFrh
	1350	var2 = WRFp
	1351	dz = WRFgeop.shape[1]
	1352	# de-staggering
[1833]	1353	var3 = 0.5*(WRFgeop[:,0:dz-1,:,:]+WRFgeop[:,1:dz,:,:])/9.8
[1759]	1354	var4 = ncobj.variables[depvars[4]][0,:,:]
	1355
	1356	dnamesvar = list(ncobj.variables['T'].dimensions)
	1357	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1358
	1359	diagout = np.zeros(var0.shape, dtype=np.float)
	1360	diagout1, diagout2, diagout3, diagout4, diagout5, diagoutd, diagoutvd = \
	1361	diag.Forcompute_cape_afwa(var0, var1, var2, var3, var4, 3, dnamesvar, \
	1362	dvnamesvar)
	1363
	1364	# Removing the nonChecking variable-dimensions from the initial list
	1365	varsadd = []
	1366	for nonvd in NONchkvardims:
	1367	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1368	varsadd.append(nonvd)
	1369
	1370	ncvar.insert_variable(ncobj, 'cape', diagout1, diagoutd, diagoutvd, newnc)
	1371	ncvar.insert_variable(ncobj, 'cin', diagout2, diagoutd, diagoutvd, newnc)
	1372	ncvar.insert_variable(ncobj, 'zlfc', diagout3, diagoutd, diagoutvd, newnc)
	1373	ncvar.insert_variable(ncobj, 'plfc', diagout4, diagoutd, diagoutvd, newnc)
	1374	ncvar.insert_variable(ncobj, 'li', diagout5, diagoutd, diagoutvd, newnc)
	1375
[1581]	1376	# WRFclivi WRF water vapour path WRFdens, QICE, QGRAUPEL, QHAIL
[1758]	1377	elif diagn == 'WRFclivi':
[1581]	1378
	1379	var0 = WRFdens
	1380	qtot = ncobj.variables[depvars[1]]
	1381	qtotv = qtot[:]
	1382	Nspecies = len(depvars) - 2
	1383	for iv in range(Nspecies):
[1585]	1384	if ncobj.variables.has_key(depvars[iv+2]):
	1385	var1 = ncobj.variables[depvars[iv+2]][:]
	1386	qtotv = qtotv + var1
[1581]	1387
	1388	dnamesvar = list(qtot.dimensions)
	1389	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1390
[1675]	1391	diagout, diagoutd, diagoutvd = diag.compute_clivi(var0, qtotv, dnamesvar,dvnamesvar)
[1581]	1392
	1393	# Removing the nonChecking variable-dimensions from the initial list
	1394	varsadd = []
	1395	diagoutvd = list(dvnames)
	1396	for nonvd in NONchkvardims:
	1397	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1398	varsadd.append(nonvd)
	1399	ncvar.insert_variable(ncobj, 'clivi', diagout, diagoutd, diagoutvd, newnc)
	1400
[1803]	1401	# WRFclwvi WRF water cloud-condensed path WRFdens, QCLOUD, QICE, QGRAUPEL, QHAIL
	1402	elif diagn == 'WRFclwvi':
[1581]	1403
	1404	var0 = WRFdens
	1405	qtot = ncobj.variables[depvars[1]]
	1406	qtotv = ncobj.variables[depvars[1]]
	1407	Nspecies = len(depvars) - 2
	1408	for iv in range(Nspecies):
[1585]	1409	if ncobj.variables.has_key(depvars[iv+2]):
	1410	var1 = ncobj.variables[depvars[iv+2]]
	1411	qtotv = qtotv + var1[:]
[1581]	1412
	1413	dnamesvar = list(qtot.dimensions)
	1414	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1415
[1675]	1416	diagout, diagoutd, diagoutvd = diag.compute_clwvl(var0, qtotv, dnamesvar,dvnamesvar)
[1581]	1417
	1418	# Removing the nonChecking variable-dimensions from the initial list
	1419	varsadd = []
	1420	diagoutvd = list(dvnames)
	1421	for nonvd in NONchkvardims:
	1422	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1423	varsadd.append(nonvd)
[1803]	1424	ncvar.insert_variable(ncobj, 'clwvi', diagout, diagoutd, diagoutvd, newnc)
[1581]	1425
[1809]	1426	# WRF_denszint WRF vertical integration as WRFdens, sum(Q[water species1], ..., Q[water speciesN]), varn=[varN]
	1427	elif diagn == 'WRF_denszint':
	1428
	1429	var0 = WRFdens
	1430	varn = depvars[1].split('=')[1]
	1431	qtot = ncobj.variables[depvars[2]]
	1432	qtotv = ncobj.variables[depvars[2]]
	1433	Nspecies = len(depvars) - 2
	1434	for iv in range(Nspecies):
	1435	if ncobj.variables.has_key(depvars[iv+2]):
	1436	var1 = ncobj.variables[depvars[iv+2]]
	1437	qtotv = qtotv + var1[:]
	1438
	1439	dnamesvar = list(qtot.dimensions)
	1440	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1441
	1442	diagout, diagoutd, diagoutvd = diag.compute_clwvl(var0, qtotv, dnamesvar,dvnamesvar)
	1443
	1444	# Removing the nonChecking variable-dimensions from the initial list
	1445	varsadd = []
	1446	diagoutvd = list(dvnames)
	1447	for nonvd in NONchkvardims:
	1448	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1449	varsadd.append(nonvd)
	1450	ncvar.insert_variable(ncobj, varn, diagout, diagoutd, diagoutvd, newnc)
	1451
[654]	1452	# WRFgeop geopotential from WRF as PH + PHB
[1758]	1453	elif diagn == 'WRFgeop':
[1382]	1454	var0 = ncobj.variables[depvars[0]][:]
	1455	var1 = ncobj.variables[depvars[1]][:]
[654]	1456
[1382]	1457	# de-staggering geopotential
	1458	diagout0 = var0 + var1
	1459	dt = diagout0.shape[0]
	1460	dz = diagout0.shape[1]
	1461	dy = diagout0.shape[2]
	1462	dx = diagout0.shape[3]
	1463
	1464	diagout = np.zeros((dt,dz-1,dy,dx), dtype=np.float)
	1465	diagout = 0.5*(diagout0[:,1:dz,:,:]+diagout0[:,0:dz-1,:,:])
	1466
	1467	# Removing the nonChecking variable-dimensions from the initial list
	1468	varsadd = []
[1389]	1469	diagoutvd = list(dvnames)
[1382]	1470	for nonvd in NONchkvardims:
[1389]	1471	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
[1382]	1472	varsadd.append(nonvd)
	1473
[1389]	1474	ncvar.insert_variable(ncobj, 'zg', diagout, dnames, diagoutvd, newnc)
[654]	1475
[1804]	1476	# WRFpotevap_orPM potential evapotranspiration following Penman-Monteith formulation
[1833]	1477	# implemented in ORCHIDEE (in src_sechiba/enerbil.f90) as: WRFdens, UST, U10, V10, T2, PSFC, QVAPOR
[1804]	1478	elif diagn == 'WRFpotevap_orPM':
	1479	var0 = WRFdens[:,0,:,:]
	1480	var1 = ncobj.variables[depvars[1]][:]
	1481	var2 = ncobj.variables[depvars[2]][:]
	1482	var3 = ncobj.variables[depvars[3]][:]
	1483	var4 = ncobj.variables[depvars[4]][:]
	1484	var5 = ncobj.variables[depvars[5]][:]
	1485	var6 = ncobj.variables[depvars[6]][:,0,:,:]
	1486
	1487	dnamesvar = list(ncobj.variables[depvars[1]].dimensions)
	1488	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1489
	1490	diagout = np.zeros(var1.shape, dtype=np.float)
	1491	diagout, diagoutd, diagoutvd = diag.Forcompute_potevap_orPM(var0, var1, var2,\
	1492	var3, var4, var5, var6, dnamesvar, dvnamesvar)
	1493
	1494	# Removing the nonChecking variable-dimensions from the initial list
	1495	varsadd = []
	1496	for nonvd in NONchkvardims:
	1497	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1498	varsadd.append(nonvd)
	1499
	1500	ncvar.insert_variable(ncobj, 'evspsblpot', diagout, diagoutd, diagoutvd, newnc)
	1501
[1795]	1502	# WRFmslp_ptarget sea-level pressure following ECMWF method as PSFC, HGT, WRFt, WRFp, ZNU, ZNW
	1503	elif diagn == 'WRFpsl_ecmwf':
	1504	var0 = ncobj.variables[depvars[0]][:]
	1505	var1 = ncobj.variables[depvars[1]][0,:,:]
	1506	var2 = WRFt[:,0,:,:]
	1507	var4 = WRFp[:,0,:,:]
	1508	var5 = ncobj.variables[depvars[4]][0,:]
	1509	var6 = ncobj.variables[depvars[5]][0,:]
	1510
	1511	# This is quite too appriximate!! passing pressure at half-levels to 2nd full
	1512	# level, using eta values at full (ZNW) and half (ZNU) mass levels
	1513	var3 = WRFp[:,0,:,:] + (var6[1] - var5[0])*(WRFp[:,1,:,:] - WRFp[:,0,:,:])/ \
	1514	(var5[1]-var5[0])
	1515
	1516	dnamesvar = list(ncobj.variables[depvars[0]].dimensions)
	1517	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1518
	1519	diagout = np.zeros(var0.shape, dtype=np.float)
	1520	diagout, diagoutd, diagoutvd = diag.Forcompute_psl_ecmwf(var0, var1, var2, \
	1521	var3, var4, dnamesvar, dvnamesvar)
	1522
	1523	# Removing the nonChecking variable-dimensions from the initial list
	1524	varsadd = []
	1525	for nonvd in NONchkvardims:
	1526	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1527	varsadd.append(nonvd)
	1528
	1529	ncvar.insert_variable(ncobj, 'psl', diagout, diagoutd, diagoutvd, newnc)
	1530
[1758]	1531	# WRFmslp_ptarget sea-level pressure following ptarget method as WRFp, PSFC, WRFt, HGT, QVAPOR
	1532	elif diagn == 'WRFpsl_ptarget':
	1533	var0 = WRFp
	1534	var1 = ncobj.variables[depvars[1]][:]
	1535	var2 = WRFt
	1536	var3 = ncobj.variables[depvars[3]][0,:,:]
	1537	var4 = ncobj.variables[depvars[4]][:]
	1538
	1539	dnamesvar = list(ncobj.variables[depvars[4]].dimensions)
	1540	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1541
	1542	diagout = np.zeros(var0.shape, dtype=np.float)
	1543	diagout, diagoutd, diagoutvd = diag.Forcompute_psl_ptarget(var0, var1, var2, \
	1544	var3, var4, 700000., dnamesvar, dvnamesvar)
	1545
	1546	# Removing the nonChecking variable-dimensions from the initial list
	1547	varsadd = []
	1548	for nonvd in NONchkvardims:
	1549	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1550	varsadd.append(nonvd)
	1551
	1552	ncvar.insert_variable(ncobj, 'psl', diagout, diagoutd, diagoutvd, newnc)
	1553
[390]	1554	# WRFp pressure from WRF as P + PB
[1758]	1555	elif diagn == 'WRFp':
[1944]	1556	var0 = ncobj.variables[depvars[0]][:]
	1557	var1 = ncobj.variables[depvars[1]][:]
[365]	1558
[1944]	1559	diagout = var0 + var1
[1999]	1560	diagoutd = list(ncobj.variables[depvars[0]].dimensions)
	1561	diagoutvd = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
[365]	1562
[1999]	1563	# Removing the nonChecking variable-dimensions from the initial list
	1564	varsadd = []
	1565	for nonvd in NONchkvardims:
	1566	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1567	varsadd.append(nonvd)
[365]	1568
[1999]	1569	ncvar.insert_variable(ncobj, 'pres', diagout, diagoutd, diagoutvd, newnc)
	1570
[365]	1571	# WRFpos
[1758]	1572	elif diagn == 'WRFpos':
[365]	1573
	1574	dnamesvar = ncobj.variables['MAPFAC_M'].dimensions
	1575	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1576
	1577	ncvar.insert_variable(ncobj, 'WRFpos', WRFpos, dnamesvar, dvnamesvar, newnc)
	1578
	1579	# WRFprw WRF water vapour path WRFdens, QVAPOR
[1758]	1580	elif diagn == 'WRFprw':
[365]	1581
	1582	var0 = WRFdens
	1583	var1 = ncobj.variables[depvars[1]]
	1584
	1585	dnamesvar = list(var1.dimensions)
	1586	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1587
[1675]	1588	diagout, diagoutd, diagoutvd = diag.compute_prw(var0, var1, dnamesvar,dvnamesvar)
[365]	1589
[1586]	1590	# Removing the nonChecking variable-dimensions from the initial list
	1591	varsadd = []
	1592	diagoutvd = list(dvnames)
	1593	for nonvd in NONchkvardims:
	1594	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1595	varsadd.append(nonvd)
[365]	1596	ncvar.insert_variable(ncobj, 'prw', diagout, diagoutd, diagoutvd, newnc)
	1597
	1598	# WRFrh (P, T, QVAPOR)
[1758]	1599	elif diagn == 'WRFrh':
[365]	1600
	1601	dnamesvar = list(ncobj.variables[depvars[2]].dimensions)
	1602	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1603
[878]	1604	ncvar.insert_variable(ncobj, 'hur', WRFrh, dnames, dvnames, newnc)
[365]	1605
	1606	# WRFrhs (PSFC, T2, Q2)
[1758]	1607	elif diagn == 'WRFrhs':
[365]	1608
	1609	var0 = ncobj.variables[depvars[0]][:]
	1610	var1 = ncobj.variables[depvars[1]][:]
	1611	var2 = ncobj.variables[depvars[2]][:]
	1612
	1613	dnamesvar = list(ncobj.variables[depvars[2]].dimensions)
	1614	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1615
[1675]	1616	diagout, diagoutd, diagoutvd = diag.compute_rh(var0,var1,var2,dnamesvar,dvnamesvar)
[878]	1617	ncvar.insert_variable(ncobj, 'hurs', diagout, diagoutd, diagoutvd, newnc)
[365]	1618
	1619	# rvors (u10, v10, WRFpos)
[1758]	1620	elif diagn == 'WRFrvors':
[365]	1621
	1622	var0 = ncobj.variables[depvars[0]]
	1623	var1 = ncobj.variables[depvars[1]]
	1624
	1625	diagout = rotational_z(var0, var1, distx)
	1626
	1627	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1628	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1629
	1630	ncvar.insert_variable(ncobj, 'rvors', diagout, dnamesvar, dvnamesvar, newnc)
	1631
[884]	1632	# WRFt (T, P, PB)
[1758]	1633	elif diagn == 'WRFt':
[884]	1634	var0 = ncobj.variables[depvars[0]][:]
	1635	var1 = ncobj.variables[depvars[1]][:]
	1636	var2 = ncobj.variables[depvars[2]][:]
[654]	1637
[884]	1638	p0=100000.
	1639	p=var1 + var2
	1640
	1641	WRFt = (var0 + 300.)(p/p0)*(2./7.)
	1642
	1643	dnamesvar = list(ncobj.variables[depvars[0]].dimensions)
	1644	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1645
[1382]	1646	# Removing the nonChecking variable-dimensions from the initial list
	1647	varsadd = []
[1389]	1648	diagoutvd = list(dvnames)
[1382]	1649	for nonvd in NONchkvardims:
[1389]	1650	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
[1382]	1651	varsadd.append(nonvd)
	1652
[1389]	1653	ncvar.insert_variable(ncobj, 'ta', WRFt, dnames, diagoutvd, newnc)
[884]	1654
[1942]	1655	# WRFtda (WRFrh, WRFt)
	1656	elif diagn == 'WRFtda':
	1657	ARM2 = fdef.module_definitions.arm2
	1658	ARM3 = fdef.module_definitions.arm3
	1659
	1660	gammatarh = np.log(WRFrh) + ARM2*(WRFt-273.15)/((WRFt-273.15)+ARM3)
[1943]	1661	td = ARM3*gammatarh/(ARM2-gammatarh)
[1942]	1662
	1663	dnamesvar = list(ncobj.variables['T'].dimensions)
	1664	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1665
	1666	# Removing the nonChecking variable-dimensions from the initial list
	1667	varsadd = []
	1668	diagoutvd = list(dvnames)
	1669	for nonvd in NONchkvardims:
	1670	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1671	varsadd.append(nonvd)
	1672
	1673	ncvar.insert_variable(ncobj, 'tda', td, dnames, diagoutvd, newnc)
	1674
[1966]	1675	# WRFtdas (PSFC, T2, Q2)
	1676	elif diagn == 'WRFtdas':
[1962]	1677	ARM2 = fdef.module_definitions.arm2
	1678	ARM3 = fdef.module_definitions.arm3
	1679
	1680	var0 = ncobj.variables[depvars[0]][:]
	1681	var1 = ncobj.variables[depvars[1]][:]
	1682	var2 = ncobj.variables[depvars[2]][:]
	1683
	1684	dnamesvar = list(ncobj.variables[depvars[1]].dimensions)
	1685	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1686
	1687	rhs, diagoutd, diagoutvd = diag.compute_rh(var0,var1,var2,dnamesvar,dvnamesvar)
	1688
	1689	gammatarhs = np.log(rhs) + ARM2*(var1-273.15)/((var1-273.15)+ARM3)
[1970]	1690	tdas = ARM3*gammatarhs/(ARM2-gammatarhs) + 273.15
[1962]	1691
	1692	# Removing the nonChecking variable-dimensions from the initial list
	1693	varsadd = []
	1694	diagoutvd = list(dvnames)
	1695	for nonvd in NONchkvardims:
	1696	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1697	varsadd.append(nonvd)
	1698
[1966]	1699	ncvar.insert_variable(ncobj, 'tdas', tdas, dnames, diagoutvd, newnc)
[1962]	1700
[914]	1701	# WRFua (U, V, SINALPHA, COSALPHA) to be rotated !!
[1758]	1702	elif diagn == 'WRFua':
[914]	1703	var0 = ncobj.variables[depvars[0]][:]
	1704	var1 = ncobj.variables[depvars[1]][:]
	1705	var2 = ncobj.variables[depvars[2]][:]
	1706	var3 = ncobj.variables[depvars[3]][:]
	1707
	1708	# un-staggering variables
[1999]	1709	if len(var0.shape) == 4:
	1710	unstgdims = [var0.shape[0], var0.shape[1], var0.shape[2], var0.shape[3]-1]
	1711	elif len(var0.shape) == 3:
	1712	# Asuming sunding point (dimt, dimz, dimstgx)
	1713	unstgdims = [var0.shape[0], var0.shape[1]]
	1714
[914]	1715	ua = np.zeros(tuple(unstgdims), dtype=np.float)
	1716	unstgvar0 = np.zeros(tuple(unstgdims), dtype=np.float)
	1717	unstgvar1 = np.zeros(tuple(unstgdims), dtype=np.float)
	1718
[1999]	1719	if len(var0.shape) == 4:
	1720	unstgvar0 = 0.5*(var0[:,:,:,0:var0.shape[3]-1] + var0[:,:,:,1:var0.shape[3]])
	1721	unstgvar1 = 0.5*(var1[:,:,0:var1.shape[2]-1,:] + var1[:,:,1:var1.shape[2],:])
[914]	1722
[1999]	1723	for iz in range(var0.shape[1]):
	1724	ua[:,iz,:,:] = unstgvar0[:,iz,:,:]var3 - unstgvar1[:,iz,:,:]var2
	1725
	1726	dnamesvar = ['Time','bottom_top','south_north','west_east']
	1727
	1728	elif len(var0.shape) == 3:
	1729	unstgvar0 = 0.5*(var0[:,:,0] + var0[:,:,1])
	1730	unstgvar1 = 0.5*(var1[:,:,0] + var1[:,:,1])
	1731	for iz in range(var0.shape[1]):
	1732	ua[:,iz] = unstgvar0[:,iz]var3 - unstgvar1[:,iz]var2
	1733
	1734	dnamesvar = ['Time','bottom_top']
	1735
[914]	1736	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1737
[1404]	1738	# Removing the nonChecking variable-dimensions from the initial list
	1739	varsadd = []
	1740	diagoutvd = list(dvnames)
	1741	for nonvd in NONchkvardims:
	1742	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1743	varsadd.append(nonvd)
[914]	1744
[1404]	1745	ncvar.insert_variable(ncobj, 'ua', ua, dnames, diagoutvd, newnc)
	1746
[914]	1747	# WRFua (U, V, SINALPHA, COSALPHA) to be rotated !!
[1758]	1748	elif diagn == 'WRFva':
[914]	1749	var0 = ncobj.variables[depvars[0]][:]
	1750	var1 = ncobj.variables[depvars[1]][:]
	1751	var2 = ncobj.variables[depvars[2]][:]
	1752	var3 = ncobj.variables[depvars[3]][:]
	1753
	1754	# un-staggering variables
[1999]	1755	if len(var0.shape) == 4:
	1756	unstgdims = [var0.shape[0], var0.shape[1], var0.shape[2], var0.shape[3]-1]
	1757	elif len(var0.shape) == 3:
	1758	# Asuming sunding point (dimt, dimz, dimstgx)
	1759	unstgdims = [var0.shape[0], var0.shape[1]]
	1760
[914]	1761	va = np.zeros(tuple(unstgdims), dtype=np.float)
	1762	unstgvar0 = np.zeros(tuple(unstgdims), dtype=np.float)
	1763	unstgvar1 = np.zeros(tuple(unstgdims), dtype=np.float)
	1764
[1999]	1765	if len(var0.shape) == 4:
	1766	unstgvar0 = 0.5*(var0[:,:,:,0:var0.shape[3]-1] + var0[:,:,:,1:var0.shape[3]])
	1767	unstgvar1 = 0.5*(var1[:,:,0:var1.shape[2]-1,:] + var1[:,:,1:var1.shape[2],:])
	1768
	1769	for iz in range(var0.shape[1]):
	1770	va[:,iz,:,:] = unstgvar0[:,iz,:,:]var2 + unstgvar1[:,iz,:,:]var3
	1771
	1772	dnamesvar = ['Time','bottom_top','south_north','west_east']
	1773
	1774	elif len(var0.shape) == 3:
	1775	unstgvar0 = 0.5*(var0[:,:,0] + var0[:,:,1])
	1776	unstgvar1 = 0.5*(var1[:,:,0] + var1[:,:,1])
	1777	for iz in range(var0.shape[1]):
	1778	va[:,iz] = unstgvar0[:,iz]var2 + unstgvar1[:,iz]var3
	1779
	1780	dnamesvar = ['Time','bottom_top']
	1781
[914]	1782	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1783
[1404]	1784	# Removing the nonChecking variable-dimensions from the initial list
	1785	varsadd = []
	1786	diagoutvd = list(dvnames)
	1787	for nonvd in NONchkvardims:
	1788	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1789	varsadd.append(nonvd)
	1790	ncvar.insert_variable(ncobj, 'va', va, dnames, diagoutvd, newnc)
[914]	1791
[1980]	1792
	1793	# WRFwd (U, V, SINALPHA, COSALPHA) to be rotated !!
	1794	elif diagn == 'WRFwd':
	1795	var0 = ncobj.variables[depvars[0]][:]
	1796	var1 = ncobj.variables[depvars[1]][:]
	1797	var2 = ncobj.variables[depvars[2]][:]
	1798	var3 = ncobj.variables[depvars[3]][:]
	1799
	1800	# un-staggering variables
[1999]	1801	if len(var0.shape) == 4:
	1802	unstgdims = [var0.shape[0], var0.shape[1], var0.shape[2], var0.shape[3]-1]
	1803	elif len(var0.shape) == 3:
	1804	# Asuming sunding point (dimt, dimz, dimstgx)
	1805	unstgdims = [var0.shape[0], var0.shape[1]]
	1806
[1980]	1807	ua = np.zeros(tuple(unstgdims), dtype=np.float)
	1808	va = np.zeros(tuple(unstgdims), dtype=np.float)
	1809	unstgvar0 = np.zeros(tuple(unstgdims), dtype=np.float)
	1810	unstgvar1 = np.zeros(tuple(unstgdims), dtype=np.float)
	1811
[1999]	1812	if len(var0.shape) == 4:
	1813	unstgvar0 = 0.5*(var0[:,:,:,0:var0.shape[3]-1] + var0[:,:,:,1:var0.shape[3]])
	1814	unstgvar1 = 0.5*(var1[:,:,0:var1.shape[2]-1,:] + var1[:,:,1:var1.shape[2],:])
[1980]	1815
[1999]	1816	for iz in range(var0.shape[1]):
	1817	ua[:,iz,:,:] = unstgvar0[:,iz,:,:]var3 - unstgvar1[:,iz,:,:]var2
	1818	va[:,iz,:,:] = unstgvar0[:,iz,:,:]var2 + unstgvar1[:,iz,:,:]var3
	1819
	1820	dnamesvar = ['Time','bottom_top','south_north','west_east']
	1821
	1822	elif len(var0.shape) == 3:
	1823	unstgvar0 = 0.5*(var0[:,:,0] + var0[:,:,1])
	1824	unstgvar1 = 0.5*(var1[:,:,0] + var1[:,:,1])
	1825	for iz in range(var0.shape[1]):
	1826	ua[:,iz] = unstgvar0[:,iz]var3 - unstgvar1[:,iz]var2
	1827	va[:,iz] = unstgvar0[:,iz]var2 + unstgvar1[:,iz]var3
	1828
	1829	dnamesvar = ['Time','bottom_top']
	1830
[1980]	1831	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1832
	1833	wd, dnames, dvnames = diag.compute_wd(ua, va, dnamesvar, dvnamesvar)
	1834
	1835	# Removing the nonChecking variable-dimensions from the initial list
	1836	varsadd = []
	1837	diagoutvd = list(dvnames)
	1838	for nonvd in NONchkvardims:
	1839	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1840	varsadd.append(nonvd)
	1841
	1842	ncvar.insert_variable(ncobj, 'wd', wd, dnames, diagoutvd, newnc)
	1843
[914]	1844	# WRFtime
[1758]	1845	elif diagn == 'WRFtime':
[654]	1846
	1847	diagout = WRFtime
	1848
	1849	dnamesvar = ['Time']
	1850	dvnamesvar = ['Times']
	1851
	1852	ncvar.insert_variable(ncobj, 'time', diagout, dnamesvar, dvnamesvar, newnc)
	1853
[959]	1854	# ws (U, V)
[1758]	1855	elif diagn == 'ws':
[959]	1856
	1857	# un-staggering variables
[1999]	1858	if len(var0.shape) == 4:
	1859	unstgdims = [var0.shape[0], var0.shape[1], var0.shape[2], var0.shape[3]-1]
	1860	elif len(var0.shape) == 3:
	1861	# Asuming sunding point (dimt, dimz, dimstgx)
	1862	unstgdims = [var0.shape[0], var0.shape[1]]
	1863
	1864	ua = np.zeros(tuple(unstgdims), dtype=np.float)
[959]	1865	va = np.zeros(tuple(unstgdims), dtype=np.float)
	1866	unstgvar0 = np.zeros(tuple(unstgdims), dtype=np.float)
	1867	unstgvar1 = np.zeros(tuple(unstgdims), dtype=np.float)
	1868
[1999]	1869	if len(var0.shape) == 4:
	1870	unstgvar0 = 0.5*(var0[:,:,:,0:var0.shape[3]-1] + var0[:,:,:,1:var0.shape[3]])
	1871	unstgvar1 = 0.5*(var1[:,:,0:var1.shape[2]-1,:] + var1[:,:,1:var1.shape[2],:])
	1872
	1873	for iz in range(var0.shape[1]):
	1874	ua[:,iz,:,:] = unstgvar0[:,iz,:,:]var3 - unstgvar1[:,iz,:,:]var2
	1875	va[:,iz,:,:] = unstgvar0[:,iz,:,:]var2 + unstgvar1[:,iz,:,:]var3
	1876
	1877	dnamesvar = ['Time','bottom_top','south_north','west_east']
	1878
	1879	elif len(var0.shape) == 3:
	1880	unstgvar0 = 0.5*(var0[:,:,0] + var0[:,:,1])
	1881	unstgvar1 = 0.5*(var1[:,:,0] + var1[:,:,1])
	1882	for iz in range(var0.shape[1]):
	1883	ua[:,iz] = unstgvar0[:,iz]var3 - unstgvar1[:,iz]var2
	1884	va[:,iz] = unstgvar0[:,iz]var2 + unstgvar1[:,iz]var3
	1885
	1886	dnamesvar = ['Time','bottom_top']
	1887
[959]	1888	diagout = np.sqrt(unstgvar0unstgvar0 + unstgvar1unstgvar1)
	1889
	1890	# dnamesvar = ncobj.variables[depvars[0]].dimensions
	1891	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1892
[1408]	1893	# Removing the nonChecking variable-dimensions from the initial list
	1894	varsadd = []
	1895	diagoutvd = list(dvnamesvar)
	1896	for nonvd in NONchkvardims:
	1897	if gen.searchInlist(dvnamesvar,nonvd): diagoutvd.remove(nonvd)
	1898	varsadd.append(nonvd)
	1899	ncvar.insert_variable(ncobj, 'ws', diagout, dnamesvar, diagoutvd, newnc)
[959]	1900
[365]	1901	# wss (u10, v10)
[1758]	1902	elif diagn == 'wss':
[365]	1903
	1904	var0 = ncobj.variables[depvars[0]][:]
	1905	var1 = ncobj.variables[depvars[1]][:]
	1906
	1907	diagout = np.sqrt(var0var0 + var1var1)
	1908
	1909	dnamesvar = ncobj.variables[depvars[0]].dimensions
	1910	dvnamesvar = ncvar.var_dim_dimv(dnamesvar,dnames,dvnames)
	1911
	1912	ncvar.insert_variable(ncobj, 'wss', diagout, dnamesvar, dvnamesvar, newnc)
	1913
[654]	1914	# WRFheight height from WRF geopotential as WRFGeop/g
[1758]	1915	elif diagn == 'WRFheight':
[654]	1916
	1917	diagout = WRFgeop/grav
	1918
[1412]	1919	# Removing the nonChecking variable-dimensions from the initial list
	1920	varsadd = []
	1921	diagoutvd = list(dvnames)
	1922	for nonvd in NONchkvardims:
	1923	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1924	varsadd.append(nonvd)
[654]	1925
[1412]	1926	ncvar.insert_variable(ncobj, 'zhgt', diagout, dnames, diagoutvd, newnc)
	1927
[1413]	1928	# WRFheightrel relative-height from WRF geopotential as WRFgeop(PH + PHB)/g-HGT 'WRFheightrel\|PH@PHB@HGT
[1758]	1929	elif diagn == 'WRFheightrel':
[1413]	1930	var0 = ncobj.variables[depvars[0]][:]
	1931	var1 = ncobj.variables[depvars[1]][:]
	1932	var2 = ncobj.variables[depvars[2]][:]
	1933
	1934	dimz = var0.shape[1]
	1935	diagout = np.zeros(tuple(var0.shape), dtype=np.float)
	1936	for iz in range(dimz):
[1419]	1937	diagout[:,iz,:,:] = (var0[:,iz,:,:]+ var1[:,iz,:,:])/grav - var2
[1413]	1938
	1939	# Removing the nonChecking variable-dimensions from the initial list
	1940	varsadd = []
	1941	diagoutvd = list(dvnames)
	1942	for nonvd in NONchkvardims:
	1943	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1944	varsadd.append(nonvd)
	1945
	1946	ncvar.insert_variable(ncobj, 'zhgtrel', diagout, dnames, diagoutvd, newnc)
	1947
[1773]	1948	# WRFzmla_gen generic boundary layer hieght computation from WRF theta, QVAPOR, WRFgeop, HGT,
	1949	elif diagn == 'WRFzmlagen':
	1950	var0 = ncobj.variables[depvars[0]][:]+300.
	1951	var1 = ncobj.variables[depvars[1]][:]
	1952	dimz = var0.shape[1]
	1953	var2 = WRFgeop[:,1:dimz+1,:,:]/9.8
	1954	var3 = ncobj.variables[depvars[3]][0,:,:]
	1955
	1956	diagout, diagoutd, diagoutvd = diag.Forcompute_zmla_gen(var0,var1,var2,var3, \
	1957	dnames,dvnames)
	1958
	1959	# Removing the nonChecking variable-dimensions from the initial list
	1960	varsadd = []
	1961	for nonvd in NONchkvardims:
	1962	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1963	varsadd.append(nonvd)
	1964
	1965	ncvar.insert_variable(ncobj, 'zmla', diagout, diagoutd, diagoutvd, newnc)
	1966
[1784]	1967	# WRFzwind wind extrapolation at a given height using power law computation from WRF
	1968	# U, V, WRFz, U10, V10, SINALPHA, COSALPHA, z=[zval]
[1776]	1969	elif diagn == 'WRFzwind':
	1970	var0 = ncobj.variables[depvars[0]][:]
	1971	var1 = ncobj.variables[depvars[1]][:]
[1777]	1972	var2 = WRFz
[1776]	1973	var3 = ncobj.variables[depvars[3]][:]
	1974	var4 = ncobj.variables[depvars[4]][:]
	1975	var5 = ncobj.variables[depvars[5]][0,:,:]
	1976	var6 = ncobj.variables[depvars[6]][0,:,:]
[1777]	1977	var7 = np.float(depvars[7].split('=')[1])
[1776]	1978
	1979	# un-staggering 3D winds
	1980	unstgdims = [var0.shape[0], var0.shape[1], var0.shape[2], var0.shape[3]-1]
	1981	va = np.zeros(tuple(unstgdims), dtype=np.float)
	1982	unvar0 = np.zeros(tuple(unstgdims), dtype=np.float)
	1983	unvar1 = np.zeros(tuple(unstgdims), dtype=np.float)
	1984	unvar0 = 0.5*(var0[:,:,:,0:var0.shape[3]-1] + var0[:,:,:,1:var0.shape[3]])
	1985	unvar1 = 0.5*(var1[:,:,0:var1.shape[2]-1,:] + var1[:,:,1:var1.shape[2],:])
	1986
	1987	diagout1, diagout2, diagoutd, diagoutvd = diag.Forcompute_zwind(unvar0, \
[1777]	1988	unvar1, var2, var3, var4, var5, var6, var7, dnames, dvnames)
[1776]	1989
	1990	# Removing the nonChecking variable-dimensions from the initial list
	1991	varsadd = []
	1992	for nonvd in NONchkvardims:
	1993	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	1994	varsadd.append(nonvd)
	1995
	1996	ncvar.insert_variable(ncobj, 'uaz', diagout1, diagoutd, diagoutvd, newnc)
	1997	ncvar.insert_variable(ncobj, 'vaz', diagout2, diagoutd, diagoutvd, newnc)
	1998
[1784]	1999	# WRFzwind wind extrapolation at a given hieght using logarithmic law computation
	2000	# from WRF U, V, WRFz, U10, V10, SINALPHA, COSALPHA, z=[zval]
	2001	elif diagn == 'WRFzwind_log':
	2002	var0 = ncobj.variables[depvars[0]][:]
	2003	var1 = ncobj.variables[depvars[1]][:]
	2004	var2 = WRFz
	2005	var3 = ncobj.variables[depvars[3]][:]
	2006	var4 = ncobj.variables[depvars[4]][:]
	2007	var5 = ncobj.variables[depvars[5]][0,:,:]
	2008	var6 = ncobj.variables[depvars[6]][0,:,:]
	2009	var7 = np.float(depvars[7].split('=')[1])
	2010
	2011	# un-staggering 3D winds
	2012	unstgdims = [var0.shape[0], var0.shape[1], var0.shape[2], var0.shape[3]-1]
	2013	va = np.zeros(tuple(unstgdims), dtype=np.float)
	2014	unvar0 = np.zeros(tuple(unstgdims), dtype=np.float)
	2015	unvar1 = np.zeros(tuple(unstgdims), dtype=np.float)
	2016	unvar0 = 0.5*(var0[:,:,:,0:var0.shape[3]-1] + var0[:,:,:,1:var0.shape[3]])
	2017	unvar1 = 0.5*(var1[:,:,0:var1.shape[2]-1,:] + var1[:,:,1:var1.shape[2],:])
	2018
	2019	diagout1, diagout2, diagoutd, diagoutvd = diag.Forcompute_zwind_log(unvar0, \
	2020	unvar1, var2, var3, var4, var5, var6, var7, dnames, dvnames)
	2021
	2022	# Removing the nonChecking variable-dimensions from the initial list
	2023	varsadd = []
	2024	for nonvd in NONchkvardims:
	2025	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	2026	varsadd.append(nonvd)
	2027
	2028	ncvar.insert_variable(ncobj, 'uaz', diagout1, diagoutd, diagoutvd, newnc)
	2029	ncvar.insert_variable(ncobj, 'vaz', diagout2, diagoutd, diagoutvd, newnc)
	2030
[1783]	2031	# WRFzwindMO wind extrapolation at a given height computation using Monin-Obukhow
	2032	# theory from WRF UST, ZNT, RMOL, U10, V10, SINALPHA, COSALPHA, z=[zval]
[1784]	2033	# NOTE: only useful for [zval] < 80. m
[1783]	2034	elif diagn == 'WRFzwindMO':
	2035	var0 = ncobj.variables[depvars[0]][:]
	2036	var1 = ncobj.variables[depvars[1]][:]
	2037	var2 = ncobj.variables[depvars[2]][:]
	2038	var3 = ncobj.variables[depvars[3]][:]
	2039	var4 = ncobj.variables[depvars[4]][:]
	2040	var5 = ncobj.variables[depvars[5]][0,:,:]
	2041	var6 = ncobj.variables[depvars[6]][0,:,:]
	2042	var7 = np.float(depvars[7].split('=')[1])
	2043
	2044	diagout1, diagout2, diagoutd, diagoutvd = diag.Forcompute_zwindMO(var0, var1,\
	2045	var2, var3, var4, var5, var6, var7, dnames, dvnames)
	2046
	2047	# Removing the nonChecking variable-dimensions from the initial list
	2048	varsadd = []
	2049	for nonvd in NONchkvardims:
	2050	if gen.searchInlist(dvnames,nonvd): diagoutvd.remove(nonvd)
	2051	varsadd.append(nonvd)
	2052
	2053	ncvar.insert_variable(ncobj, 'uaz', diagout1, diagoutd, diagoutvd, newnc)
	2054	ncvar.insert_variable(ncobj, 'vaz', diagout2, diagoutd, diagoutvd, newnc)
	2055
[365]	2056	else:
	2057	print errormsg
[1758]	2058	print ' ' + main + ": diagnostic '" + diagn + "' not ready!!!"
[365]	2059	print ' available diagnostics: ', availdiags
	2060	quit(-1)
	2061
	2062	newnc.sync()
[1351]	2063	# Adding that additional variables required to compute some diagnostics which
	2064	# where not in the original file
[1944]	2065	print ' adding additional variables...'
[1351]	2066	for vadd in varsadd:
[1942]	2067	if not gen.searchInlist(newnc.variables.keys(),vadd) and \
	2068	dictcompvars.has_key(vadd):
[1351]	2069	attrs = dictcompvars[vadd]
	2070	vvn = attrs['name']
	2071	if not gen.searchInlist(newnc.variables.keys(), vvn):
	2072	iidvn = dvnames.index(vadd)
	2073	dnn = dnames[iidvn]
	2074	if vadd == 'WRFtime':
	2075	dvarvals = WRFtime[:]
	2076	newvar = newnc.createVariable(vvn, 'f8', (dnn))
	2077	newvar[:] = dvarvals
	2078	for attn in attrs.keys():
	2079	if attn != 'name':
	2080	attv = attrs[attn]
	2081	ncvar.set_attribute(newvar, attn, attv)
[365]	2082
	2083	# end of diagnostics
	2084
	2085	# Global attributes
	2086	##
[1758]	2087	ncvar.add_global_PyNCplot(newnc, main, None, '2.0')
[365]	2088
	2089	gorigattrs = ncobj.ncattrs()
	2090	for attr in gorigattrs:
	2091	attrv = ncobj.getncattr(attr)
	2092	atvar = ncvar.set_attribute(newnc, attr, attrv)
	2093
	2094	ncobj.close()
	2095	newnc.close()
	2096
	2097	print '\n' + main + ': successfull writting of diagnostics file "' + ofile + '" !!!'

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