# -*- coding: iso-8859-15 -*- # Generic program to transfrom ASCII observational data in columns to a netcdf # L. Fita, LMD February 2015 ## e.g. # create_OBSnetcdf.py -c '#' -d ACAR/description.dat -e space -f ACAR/2012/10/ACAR_121018.asc -g true -t 19491201000000,seconds -k trajectory import numpy as np from netCDF4 import Dataset as NetCDFFile import os import re from optparse import OptionParser # version version=1.2 # Filling values for floats, integer and string fillValueF = 1.e20 fillValueI = -99999 fillValueS = '---' # Length of the string variables StringLength = 200 # Size of the map for the complementary variables/maps Ndim2D = 100 main = 'create_OBSnetcdf.py' errormsg = 'ERROR -- error -- ERROR -- error' warnmsg = 'WARNING -- warning -- WARNING -- warning' fillValue = 1.e20 def searchInlist(listname, nameFind): """ Function to search a value within a list listname = list nameFind = value to find >>> searInlist(['1', '2', '3', '5'], '5') True """ for x in listname: if x == nameFind: return True return False def typemod(value, typeval): """ Function to give back a value in a given dtype >>> print(typemod(8.2223, 'np.float64')) >>> print(typemod(8.2223, 'tuple')) """ fname='typemod' if typeval == 'int' or typeval == 'I': return int(value) elif typeval == 'long': return long(value) elif typeval == 'float' or typeval == 'F' or typeval == 'R': return float(value) elif typeval == 'complex': return complex(value) elif typeval == 'str' or typeval == 'S': return str(value) elif typeval == 'bool': return bool(value) elif typeval == 'B': return Str_Bool(value) elif typeval == 'list': newval = [] newval.append(value) return newval elif typeval == 'dic': newval = {} newval[value] = value return newval elif typeval == 'tuple': newv = [] newv.append(value) newval = tuple(newv) return newval elif typeval == 'np.int8': return np.int8(value) elif typeval == 'np.int16': return np.int16(value) elif typeval == 'np.int32': return np.int32(value) elif typeval == 'np.int64': return np.int64(value) elif typeval == 'np.uint8': return np.uint8(value) elif typeval == 'np.uint16': return np.uint16(value) elif typeval == 'np.np.uint32': return np.uint32(value) elif typeval == 'np.uint64': return np.uint64(value) elif typeval == 'np.float' or typeval == 'R': return np.float(value) elif typeval == 'np.float16': return np.float16(value) elif typeval == 'np.float32': return np.float32(value) elif typeval == 'float32': return np.float32(value) elif typeval == 'np.float64' or typeval == 'D': return np.float64(value) elif typeval == 'float64': return np.float64(value) elif typeval == 'np.complex': return np.complex(value) elif typeval == 'np.complex64': return np.complex64(value) elif typeval == 'np.complex128': return np.complex128(value) else: print errormsg print fname + ': data type "' + typeval + '" is not ready !' print errormsg quit(-1) return def str_list_k(string, cdiv, kind): """ Function to obtain a list of types of values from a string giving a split character string= String from which to obtain a list ('None' for None) cdiv= character to use to split the string kind= kind of desired value (as string like: 'np.float', 'int', 'np.float64', ....) >>> str_list_k('1:@#:$:56', ':', 'S') ['1', '@#', '$', '56'] >>> str_list_k('1:3.4:12.3', ':', 'np.float64') [1.0, 3.3999999999999999, 12.300000000000001] """ fname = 'str_list' if string.find(cdiv) != -1: listv = string.split(cdiv) else: if string == 'None': listv = None else: listv = [string] if listv is not None: finalist = [] for lv in listv: finalist.append(typemod(lv, kind)) else: finalist = None return finalist def set_attribute(ncvar, attrname, attrvalue): """ Sets a value of an attribute of a netCDF variable. Removes previous attribute value if exists ncvar = object netcdf variable attrname = name of the attribute attrvalue = value of the attribute """ import numpy as np from netCDF4 import Dataset as NetCDFFile attvar = ncvar.ncattrs() if searchInlist(attvar, attrname): attr = ncvar.delncattr(attrname) attr = ncvar.setncattr(attrname, attrvalue) return ncvar def set_attributek(ncv, attrname, attrval, attrkind): """ Sets a value of an attribute of a netCDF variable with a kind. Removes previous attribute value if exists ncvar = object netcdf variable attrname = name of the attribute attrvalue = value of the attribute atrtrkind = kind of attribute: 'S', string ('!' as spaces); 'U', unicode ('!' as spaces); 'I', integer; 'Inp32', numpy integer 32; 'R', ot 'F' real; ' npfloat', np.float; 'D', np.float64 """ fname = 'set_attributek' validk = {'S': 'string', 'U': 'unicode', 'I': 'integer', \ 'Inp32': 'integer long (np.int32)', 'F': 'float', 'R': 'float', \ 'npfloat': 'np.float', 'D': 'float long (np.float64)'} if type(attrkind) == type('s'): if attrkind == 'S': attrvalue = str(attrval.replace('!', ' ')) elif attrkind == 'U': attrvalue = unicode(attrval.replace('!',' ')) elif attrkind == 'I': attrvalue = np.int(attrval) elif attrkind == 'R' or attrkind == 'F' : attrvalue = float(attrval) elif attrkind == 'npfloat': attrvalue = np.float(attrval) elif attrkind == 'D': attrvalue = np.float64(attrval) else: print errormsg print ' ' + fname + ": '" + attrkind + "' kind of attribute is not ready!" print ' valid values: _______' for key in validk.keys(): print ' ', key,':', validk[key] quit(-1) else: if attrkind == type(str('a')): attrvalue = str(attrval.replace('!', ' ')) elif attrkind == type(unicode('a')): attrvalue = unicode(attrval.replace('!',' ')) elif attrkind == type(np.int(1)): attrvalue = np.int(attrval) elif attrkind == np.dtype('i'): attrvalue = np.int32(attrval) elif attrkind == type(float(1.)): attrvalue = float(attrval) elif attrkind == type(np.float(1.)): attrvalue = np.float(attrval) elif attrkind == np.dtype('float32'): attrvalue = np.array(attrval, dtype='f') elif attrkind == type(np.float32(1.)): attrvalue = np.float32(attrval) elif attrkind == type(np.float64(1.)): attrvalue = np.float64(attrval) elif attrkind == type(np.array([1.,2.])): attrvalue = attrval else: print errormsg print ' ' + fname + ": '" + attrkind + "' kind of attribute is not ready!" print ' valid values: _______' for key in validk.keys(): print ' ', key,':', validk[key] quit(-1) attvar = ncv.ncattrs() if searchInlist(attvar, attrname): attr = ncv.delncattr(attrname) if attrname == 'original_subroutines_author': attrvalue = 'Cindy Bruyere' attr = ncv.setncattr(attrname, attrvalue) return attr def basicvardef(varobj, vstname, vlname, vunits): """ Function to give the basic attributes to a variable varobj= netCDF variable object vstname= standard name of the variable vlname= long name of the variable vunits= units of the variable """ attr = varobj.setncattr('standard_name', vstname) attr = varobj.setncattr('long_name', vlname) attr = varobj.setncattr('units', vunits) return def remove_NONascii(string): """ Function to remove that characters which are not in the standard 127 ASCII string= string to transform >>> remove_NONascii('Lluís') Lluis """ fname = 'remove_NONascii' newstring = string RTFchar= ['á', 'é', 'í', 'ó', 'ú', 'à', 'è', 'ì', 'ò', 'ù', 'â', 'ê', 'î', 'ô', \ 'û', 'ä', 'ë', 'ï', 'ö', 'ü', 'ç', 'ñ','æ', 'œ', 'Á', 'É', 'Í', 'Ó', 'Ú', 'À', \ 'È', 'Ì', 'Ò', 'Ù', 'Â', 'Ê', 'Î', 'Ô', 'Û', 'Ä', 'Ë', 'Ï', 'Ö', 'Ü', 'Ç', 'Ñ',\ 'Æ', 'Œ', '\n', '\t'] ASCchar= ['a', 'e', 'i', 'o', 'u', 'a', 'e', 'i', 'o', 'u', 'a', 'e', 'i', 'o', \ 'u', 'a', 'e', 'i', 'o', 'u', 'c', 'n','ae', 'oe', 'A', 'E', 'I', 'O', 'U', 'A', \ 'E', 'I', 'O', 'U', 'A', 'E', 'I', 'O', 'U', 'A', 'E', 'I', 'O', 'U', 'C', 'N',\ 'AE', 'OE', '', ' '] Nchars = len(RTFchar) for ichar in range(Nchars): foundchar = string.find(RTFchar[ichar]) if foundchar != -1: newstring = newstring.replace(RTFchar[ichar], ASCchar[ichar]) return newstring def read_description(fdobs, dbg): """ reads the description file of the observational data-set fdobs= descriptive observational data-set dbg= boolean argument for debugging * Each station should have a 'description.dat' file with: institution=Institution who creates the data department=Department within the institution scientists=names of the data producers contact=contact of the data producers description=description of the observations acknowledgement=sentence of acknowlegement comment=comment for the measurements MissingValue='|' list of ASCII values for missing values within the data (as they appear!, 'empty' for no value at all) comment=comments varN='|' list of variable names varLN='|' list of long variable names varU='|' list units of the variables varBUFR='|' list BUFR code of the variables varTYPE='|' list of variable types ('D', 'F', 'I', 'I64', 'S') varOPER='|' list of operations to do to the variables to meet their units ([oper],[val]) [oper]: -, nothing sumc, add [val] subc, rest [val] mulc, multiply by [val] divc, divide by [val] rmchar,[val],[pos], remove [val] characters from [pos]='B', beginning, 'E', end NAMElon=name of the variable with the longitude (x position) NAMElat=name of the variable with the latitude (y position) NAMEheight=ind_alt NAMEtime=name of the varibale with the time FMTtime=format of the time (as in 'C', 'CFtime' for already CF-like time) """ fname = 'read_description' descobj = open(fdobs, 'r') desc = {} namevalues = [] for line in descobj: if line[0:1] != '#' and len(line) > 1 : descn = remove_NONascii(line.split('=')[0]) descv = remove_NONascii(line.split('=')[1]) namevalues.append(descn) if descn[0:3] != 'var': if descn != 'MissingValue': desc[descn] = descv else: desc[descn] = [] for dn in descv.split('|'): desc[descn].append(dn) print ' ' + fname + ': missing values found:',desc[descn] elif descn[0:3] == 'var': desc[descn] = descv.split('|') elif descn[0:4] == 'NAME': desc[descn] = descv elif descn[0:3] == 'FMT': desc[descn] = descv if not desc.has_key('varOPER'): desc['varOPER'] = None if dbg: Nvars = len(desc['varN']) print ' ' + fname + ": description content of '" + fdobs + "'______________" for varn in namevalues: if varn[0:3] != 'var': print ' ' + varn + ':',desc[varn] elif varn == 'varN': print ' * Variables:' for ivar in range(Nvars): varname = desc['varN'][ivar] varLname = desc['varLN'][ivar] varunits = desc['varU'][ivar] if desc.has_key('varBUFR'): varbufr = desc['varBUFR'][ivar] else: varbufr = None if desc['varOPER'] is not None: opv = desc['varOPER'][ivar] else: opv = None print ' ', ivar, varname+':',varLname,'[',varunits, \ ']','bufr code:',varbufr,'oper:',opv descobj.close() return desc def value_fmt(val, miss, op, fmt): """ Function to transform an ASCII value to a given format val= value to transform miss= list of possible missing values op= operation to perform to the value fmt= format to take: 'D': float double precission 'F': float 'I': integer 'I64': 64-bits integer 'S': string >>> value_fmt('9876.12', '-999', 'F') 9876.12 """ fname = 'value_fmt' aopers = ['sumc','subc','mulc','divc', 'rmchar'] fmts = ['D', 'F', 'I', 'I64', 'S'] Nfmts = len(fmts) if not searchInlist(miss,val): if searchInlist(miss,'empty') and len(val) == 0: newval = None else: if op != '-': opern = op.split(',')[0] operv = op.split(',')[1] if not searchInlist(aopers,opern): print errormsg print ' ' + fname + ": operation '" + opern + "' not ready!!" print ' availables:',aopers quit(-1) else: opern = 'sumc' operv = '0' if not searchInlist(fmts, fmt): print errormsg print ' ' + fname + ": format '" + fmt + "' not ready !!" quit(-1) else: if fmt == 'D': opv = np.float32(operv) if opern == 'sumc': newval = np.float32(val) + opv elif opern == 'subc': newval = np.float32(val) - opv elif opern == 'mulc': newval = np.float32(val) * opv elif opern == 'divc': newval = np.float32(val) / opv elif opern == 'rmchar': opv = int(operv) Lval = len(val) if op.split(',')[2] == 'B': newval = np.float32(val[opv:Lval+1]) elif op.split(',')[2] == 'E': newval = np.float32(val[Lval-opv:Lval]) else: print errormsg print ' ' + fname + ": operation '" + opern + "' not " +\ " work with '" + op.split(',')[2] + "' !!" quit(-1) elif fmt == 'F': opv = np.float(operv) if opern == 'sumc': newval = np.float(val) + opv elif opern == 'subc': newval = np.float(val) - opv elif opern == 'mulc': newval = np.float(val) * opv elif opern == 'divc': newval = np.float(val) / opv elif opern == 'rmchar': opv = int(operv) Lval = len(val) if op.split(',')[2] == 'B': newval = np.float(val[opv:Lval+1]) elif op.split(',')[2] == 'E': newval = np.float(val[0:Lval-opv]) else: print errormsg print ' ' + fname + ": operation '" + opern + "' not " +\ " work with '" + op.split(',')[2] + "' !!" quit(-1) elif fmt == 'I': opv = int(operv) if opern == 'sumc': newval = int(val) + opv elif opern == 'subc': newval = int(val) - opv elif opern == 'mulc': newval = int(val) * opv elif opern == 'divc': newval = int(val) / opv elif opern == 'rmchar': opv = int(operv) Lval = len(val) if op.split(',')[2] == 'B': newval = int(val[opv:Lval+1]) elif op.split(',')[2] == 'E': newval = int(val[0:Lval-opv]) else: print errormsg print ' ' + fname + ": operation '" + opern + "' not " +\ " work with '" + op.split(',')[2] + "' !!" quit(-1) elif fmt == 'I64': opv = np.int64(operv) if opern == 'sumc': newval = np.int64(val) + opv elif opern == 'subc': newval = np.int64(val) - opv elif opern == 'mulc': newval = np.int64(val) * opv elif opern == 'divc': newval = np.int64(val) / opv elif opern == 'rmchar': opv = int(operv) Lval = len(val) if op.split(',')[2] == 'B': newval = np.int64(val[opv:Lval+1]) elif op.split(',')[2] == 'E': newval = np.int64(val[0:Lval-opv]) else: print errormsg print ' ' + fname + ": operation '" + opern + "' not " +\ " work with '" + op.split(',')[2] + "' !!" quit(-1) elif fmt == 'S': if opern == 'rmchar': opv = int(operv) Lval = len(val) if op.split(',')[2] == 'B': newval = val[opv:Lval+1] elif op.split(',')[2] == 'E': newval = val[0:Lval-opv] else: print errormsg print ' ' + fname + ": operation '" + opern + "' not " +\ " work with '" + op.split(',')[2] + "' !!" quit(-1) else: newval = val else: newval = None return newval def getting_fixedline(line, cuts, types, dbg=False): """ Function to get the values from a line of text with fixed lenght of different values line: line with values cuts: character number where a value ends types: consecutive type of values 'I': integer 'R': real 'D': float64 'S': string 'B': boolean dbg: debug mode (default False) >>> Sline=' 87007 03012015 25.6 6.4 9.4 5 15' >>> getting_fixedline(Sline, [8, 17, 23, 29, 36, 40, 45, 50], ['I', 'R', 'R', 'R', 'I', 'R', 'R', 'R']) [87007, 3012015.0, 25.6, 6.4, -99999, -99999, 9.4, 5.0, 15.0] """ fname = 'getting_fixedline' if len(cuts) + 1 != len(types): print errormsg print ' ' + fname + ': The number of types :', len(types), 'must be +1', \ 'number of cuts:', len(cuts) quit(-1) values = [] val = line[0:cuts[0]] if len(val.replace(' ','')) >= 1: values.append(typemod(val, types[0])) else: if types[0] == 'I': values.append(fillValueI) elif types[0] == 'R': values.append(fillValueF) elif types[0] == 'D': values.append(fillValueF) elif types[0] == 'S': values.append(fillValueS) elif types[0] == 'B': values.append(fillValueB) Ncuts = len(cuts) for ic in range(1,Ncuts): val = line[cuts[ic-1]:cuts[ic]] if dbg: print ic, ':', val, '-->', types[ic] if len(val.replace(' ','')) >= 1: values.append(typemod(val, types[ic])) else: if types[ic] == 'I': values.append(fillValueI) elif types[ic] == 'R': values.append(fillValueF) elif types[ic] == 'D': values.append(fillValueF) elif types[ic] == 'S': values.append(fillValueS) elif types[ic] == 'B': values.append(fillValueB) # Last value Lline = len(line) val = line[cuts[Ncuts-1]:Lline] if len(val.replace(' ','')) >= 1: values.append(typemod(val, types[Ncuts])) else: if types[Ncuts] == 'I': values.append(fillValueI) elif types[Ncuts] == 'R': values.append(fillValueF) elif types[Ncuts] == 'D': values.append(fillValueF) elif types[Ncuts] == 'S': values.append(fillValueS) elif types[Ncuts] == 'B': values.append(fillValueB) return values def getting_fixedline_NOk(line, cuts, miss, dbg=False): """ Function to get the values from a line of text with fixed lenght of different values without types line: line with values cuts: character number where a value ends miss: character form issed values dbg: debug mode (default False) >>> Sline=' 87007 03012015 25.6 6.4 9.4 5 15' >>> getting_fixedline_NOk(Sline, [8, 17, 23, 29, 36, 40, 45, 50], '#') ['87007', '03012015', '25.6', '6.4', '#', '#', '9.4', '5', '15'] """ fname = 'getting_fixedline_NOk' values = [] val = line[0:cuts[0]] if len(val.replace(' ','')) >= 1: values.append(val.replace(' ','')) else: values.append(miss) Ncuts = len(cuts) for ic in range(1,Ncuts): val = line[cuts[ic-1]:cuts[ic]] if dbg: print ic, ':', val if len(val.replace(' ','')) >= 1: values.append(val.replace(' ','')) else: values.append(miss) # Last value Lline = len(line) val = line[cuts[Ncuts-1]:Lline] if len(val.replace(' ','')) >= 1: values.append(val.replace(' ','')) else: values.append(miss) return values def read_datavalues(dataf, comchar, colchar, fmt, oper, miss, varns, dbg): """ Function to read from an ASCII file values in column dataf= data file comchar= list of the characters indicating comment in the file colchar= character which indicate end of value in the column dbg= debug mode or not fmt= list of kind of values to be found oper= list of operations to perform miss= missing value varns= list of name of the variables to find """ fname = 'read_datavalues' ofile = open(dataf, 'r') Nvals = len(fmt) if oper is None: opers = [] for ioper in range(Nvals): opers.append('-') else: opers = oper finalvalues = {} iline = 0 for line in ofile: line = line.replace('\n','').replace(chr(13),'') if not searchInlist(comchar,line[0:1]) and len(line) > 1: # Getting values if colchar[0:4] != 'None': values0 = line.split(colchar) else: ltypes=str_list_k(colchar[5:len(colchar)+1],',','I') values0 = getting_fixedline_NOk(line, ltypes, miss[0], dbg=dbg) # Removing no-value columns values = [] for iv in values0: if len(iv) > 0: values.append(iv) Nvalues = len(values) # Checkings for wierd characters at the end of lines (use it to check) # if values[Nvalues-1][0:4] == '-999': # print line,'last v:',values[Nvalues-1],'len:',len(values[Nvalues-1]) # for ic in range(len(values[Nvalues-1])): # print ic,ord(values[Nvalues-1][ic:ic+1]) # quit() if len(values[Nvalues-1]) == 0: Nvalues = Nvalues - 1 if Nvalues != Nvals: print warnmsg print ' ' + fname + ': number of formats:',Nvals,' and number of ', \ 'values:',Nvalues,' with split character *' + colchar + \ '* does not coincide!!' print ' * what is found is ________' if Nvalues > Nvals: Nshow = Nvals for ivar in range(Nshow): print ' ',varns[ivar],'fmt:',fmt[ivar],'value:',values[ivar] print ' missing formats for:',values[Nshow:Nvalues+1] print ' values not considered, continue' else: Nshow = Nvalues for ivar in range(Nshow): print ' ',varns[ivar],'fmt:',fmt[ivar],'value:',values[ivar] print ' excess of formats:',fmt[Nshow:Nvals+1] quit(-1) # Reading and transforming values if dbg: print ' ' + fname + ': values found _________' for ivar in range(Nvals): if dbg: print iline, varns[ivar],'value:',values[ivar],miss,opers[ivar], \ fmt[ivar] if iline == 0: listvals = [] listvals.append(value_fmt(values[ivar], miss, opers[ivar], \ fmt[ivar])) finalvalues[varns[ivar]] = listvals else: listvals = finalvalues[varns[ivar]] listvals.append(value_fmt(values[ivar], miss, opers[ivar], \ fmt[ivar])) finalvalues[varns[ivar]] = listvals else: # First line without values if iline == 0: iline = -1 iline = iline + 1 ofile.close() return finalvalues def writing_str_nc(varo, values, Lchar): """ Function to write string values in a netCDF variable as a chain of 1char values varo= netCDF variable object values = list of values to introduce Lchar = length of the string in the netCDF file """ Nvals = len(values) for iv in range(Nvals): stringv=values[iv] charvals = np.chararray(Lchar) Lstr = len(stringv) charvals[Lstr:Lchar] = '' for ich in range(Lstr): charvals[ich] = stringv[ich:ich+1] varo[iv,:] = charvals return def Stringtimes_CF(tvals, fmt, Srefdate, tunits, dbg): """ Function to transform a given data in String formats to a CF date tvals= string temporal values fmt= format of the the time values Srefdate= reference date in [YYYY][MM][DD][HH][MI][SS] format tunits= units to use ('weeks', 'days', 'hours', 'minutes', 'seconds') dbg= debug >>> Stringtimes_CF(['19760217082712','20150213101837'], '%Y%m%d%H%M%S', '19491201000000', 'hours', False) [229784.45333333 571570.31027778] """ import datetime as dt fname = 'Stringtimes' dimt = len(tvals) yrref = int(Srefdate[0:4]) monref = int(Srefdate[4:6]) dayref = int(Srefdate[6:8]) horref = int(Srefdate[8:10]) minref = int(Srefdate[10:12]) secref = int(Srefdate[12:14]) refdate = dt.datetime( yrref, monref, dayref, horref, minref, secref) cftimes = np.zeros((dimt), dtype=np.float) Nfmt=len(fmt.split('%')) if dbg: print ' ' + fname + ': fmt=',fmt,'refdate:',Srefdate,'uits:',tunits, \ 'date dt_days dt_time deltaseconds CFtime _______' for it in range(dimt): # Removing excess of mili-seconds (up to 6 decimals) if fmt.split('%')[Nfmt-1] == 'f': tpoints = tvals[it].split('.') if len(tpoints[len(tpoints)-1]) > 6: milisec = '{0:.6f}'.format(np.float('0.'+tpoints[len(tpoints)-1]))[0:7] newtval = '' for ipt in range(len(tpoints)-1): newtval = newtval + tpoints[ipt] + '.' newtval = newtval + str(milisec)[2:len(milisec)+1] else: newtval = tvals[it] tval = dt.datetime.strptime(newtval, fmt) else: tval = dt.datetime.strptime(tvals[it], fmt) deltatime = tval - refdate deltaseconds = deltatime.days*24.*3600. + deltatime.seconds + \ deltatime.microseconds/100000. if tunits == 'weeks': deltat = 7.*24.*3600. elif tunits == 'days': deltat = 24.*3600. elif tunits == 'hours': deltat = 3600. elif tunits == 'minutes': deltat = 60. elif tunits == 'seconds': deltat = 1. else: print errormsg print ' ' + fname + ": time units '" + tunits + "' not ready !!" quit(-1) cftimes[it] = deltaseconds / deltat if dbg: print ' ' + tvals[it], deltatime, deltaseconds, cftimes[it] return cftimes def adding_complementary(onc, dscn, okind, dvalues, tvals, refCFt, CFtu, Nd, dbg): """ Function to add complementary variables as function of the observational type onc= netcdf objecto file to add the variables dscn= description dictionary okind= observational kind dvalues= values tvals= CF time values refCFt= reference time of CF time (in [YYYY][MM][DD][HH][MI][SS]) CFtu= CF time units Nd= size of the domain dbg= debugging flag """ import numpy.ma as ma fname = 'adding_complementary' # Kind of observations which require de integer lon/lat (for the 2D map) map2D=['multi-points', 'trajectory'] SrefCFt = refCFt[0:4] +'-'+ refCFt[4:6] +'-'+ refCFt[6:8] + ' ' + refCFt[8:10] + \ ':'+ refCFt[10:12] +':'+ refCFt[12:14] if dscn['NAMElon'] == '-' or dscn['NAMElat'] == '-': print errormsg print ' ' + fname + ": to complement a '" + okind + "' observation kind " + \ " a given longitude ('NAMElon':",dscn['NAMElon'],") and latitude ('" + \ "'NAMElat:'", dscn['NAMElat'],') from the data has to be provided and ' + \ 'any are given !!' quit(-1) if not dvalues.has_key(dscn['NAMElon']) or not dvalues.has_key(dscn['NAMElat']): print errormsg print ' ' + fname + ": observations do not have 'NAMElon':", \ dscn['NAMElon'],"and/or 'NAMElat:'", dscn['NAMElat'],' !!' print ' available data:',dvalues.keys() quit(-1) if okind == 'trajectory': if dscn['NAMEheight'] == '-': print warnmsg print ' ' + fname + ": to complement a '" + okind + "' observation " + \ "kind a given height ('NAMEheight':",dscn['NAMEheight'],"') might " + \ 'be provided and any is given !!' quit(-1) if not dvalues.has_key(dscn['NAMEheight']): print errormsg print ' ' + fname + ": observations do not have 'NAMEtime':", \ dscn['NAMEtime'],' !!' print ' available data:',dvalues.keys() quit(-1) if searchInlist(map2D, okind): # A new 2D map with the number of observation will be added for that 'NAMElon' # and 'NAMElat' are necessary. A NdxNd domain space size will be used. objfile.createDimension('lon2D',Nd) objfile.createDimension('lat2D',Nd) lonvals = ma.masked_equal(dvalues[dscn['NAMElon']], None) latvals = ma.masked_equal(dvalues[dscn['NAMElat']], None) minlon = min(lonvals) maxlon = max(lonvals) minlat = min(latvals) maxlat = max(latvals) blon = (maxlon - minlon)/(Nd-1) blat = (maxlat - minlat)/(Nd-1) newvar = onc.createVariable( 'lon2D', 'f8', ('lon2D')) basicvardef(newvar, 'longitude', 'longitude map observations','degrees_East') newvar[:] = minlon + np.arange(Nd)*blon newattr = set_attribute(newvar, 'axis', 'X') newvar = onc.createVariable( 'lat2D', 'f8', ('lat2D')) basicvardef(newvar, 'latitude', 'latitude map observations', 'degrees_North') newvar[:] = minlat + np.arange(Nd)*blat newattr = set_attribute(newvar, 'axis', 'Y') if dbg: print ' ' + fname + ': minlon=',minlon,'maxlon=',maxlon print ' ' + fname + ': minlat=',minlat,'maxlat=',maxlat print ' ' + fname + ': precission on x-axis=', blon*(Nd-1), 'y-axis=', \ blat*(Nd-1) if okind == 'multi-points': map2D = np.ones((Nd, Nd), dtype=np.float)*fillValueI dimt = len(tvals) Nlost = 0 for it in range(dimt): lon = dvalues[dscn['NAMElon']][it] lat = dvalues[dscn['NAMElat']][it] if lon is not None and lat is not None: ilon = int((Nd-1)*(lon - minlon)/(maxlon - minlon)) ilat = int((Nd-1)*(lat - minlat)/(maxlat - minlat)) if map2D[ilat,ilon] == fillValueI: map2D[ilat,ilon] = 1 else: map2D[ilat,ilon] = map2D[ilat,ilon] + 1 if dbg: print it, lon, lat, ilon, ilat, map2D[ilat,ilon] newvar = onc.createVariable( 'mapobs', 'f4', ('lat2D', 'lon2D'), \ fill_value = fillValueI) basicvardef(newvar, 'map_observations', 'number of observations', '-') newvar[:] = map2D newattr = set_attribute(newvar, 'coordinates', 'lon2D lat2D') elif okind == 'trajectory': # A new 2D map with the trajectory 'NAMElon' and 'NAMElat' and maybe 'NAMEheight' # are necessary. A NdxNdxNd domain space size will be used. Using time as # reference variable if dscn['NAMEheight'] == '-': # No height map2D = np.ones((Nd, Nd), dtype=np.float)*fillValueI dimt = len(tvals) Nlost = 0 if dbg: print ' time-step lon lat ix iy passes _______' for it in range(dimt): lon = dvalues[dscn['NAMElon']][it] lat = dvalues[dscn['NAMElat']][it] if lon is not None and lat is not None: ilon = int((Nd-1)*(lon - minlon)/(maxlon - minlon)) ilat = int((Nd-1)*(lat - minlat)/(maxlat - minlat)) if map2D[ilat,ilon] == fillValueI: map2D[ilat,ilon] = 1 else: map2D[ilat,ilon] = map2D[ilat,ilon] + 1 if dbg: print it, lon, lat, ilon, ilat, map2D[ilat,ilon] newvar = onc.createVariable( 'trjobs', 'i', ('lat2D', 'lon2D'), \ fill_value = fillValueI) basicvardef(newvar, 'trajectory_observations', 'number of passes', '-' ) newvar[:] = map2D newattr = set_attribute(newvar, 'coordinates', 'lon2D lat2D') else: ivn = 0 for vn in dscn['varN']: if vn == dscn['NAMEheight']: zu = dscn['varU'][ivn] break ivn = ivn + 1 objfile.createDimension('z2D',Nd) zvals = ma.masked_equal(dvalues[dscn['NAMEheight']], None) minz = min(zvals) maxz = max(zvals) bz = (maxz - minz)/(Nd-1) newvar = onc.createVariable( 'z2D', 'f8', ('z2D')) basicvardef(newvar, 'z2D', 'z-coordinate map observations', zu) newvar[:] = minz + np.arange(Nd)*bz newattr = set_attribute(newvar, 'axis', 'Z') if dbg: print ' ' + fname + ': zmin=',minz,zu,'zmax=',maxz,zu print ' ' + fname + ': precission on z-axis=', bz*(Nd-1), zu map3D = np.ones((Nd, Nd, Nd), dtype=int)*fillValueI dimt = len(tvals) Nlost = 0 if dbg: print ' time-step lon lat z ix iy iz passes _______' for it in range(dimt): lon = dvalues[dscn['NAMElon']][it] lat = dvalues[dscn['NAMElat']][it] z = dvalues[dscn['NAMEheight']][it] if lon is not None and lat is not None and z is not None: ilon = int((Nd-1)*(lon - minlon)/(maxlon - minlon)) ilat = int((Nd-1)*(lat - minlat)/(maxlat - minlat)) iz = int((Nd-1)*(z - minz)/(maxz - minz)) if map3D[iz,ilat,ilon] == fillValueI: map3D[iz,ilat,ilon] = 1 else: map3D[iz,ilat,ilon] = map3D[iz,ilat,ilon] + 1 if dbg: print it, lon, lat, z, ilon, ilat, iz, map3D[iz,ilat,ilon] newvar = onc.createVariable( 'trjobs', 'i', ('z2D', 'lat2D', 'lon2D'), \ fill_value = fillValueI) basicvardef(newvar, 'trajectory_observations', 'number of passes', '-') newvar[:] = map3D newattr = set_attribute(newvar, 'coordinates', 'lon2D lat2D z2D') onc.sync() return def adding_station_desc(onc,stdesc): """ Function to add a station description in a netCDF file onc= netCDF object stdesc= station description name, lon, lat, height """ fname = 'adding_station_desc' newdim = onc.createDimension('nst',1) newvar = objfile.createVariable( 'station', 'c', ('nst','StrLength')) writing_str_nc(newvar, [stdesc[0].replace('!', ' ')], StringLength) newvar = objfile.createVariable( 'lonstGDM', 'c', ('nst','StrLength')) Gv = int(stdesc[1]) Dv = int((stdesc[1] - Gv)*60.) Mv = int((stdesc[1] - Gv - Dv/60.)*3600.) writing_str_nc(newvar, [str(Gv)+"d" + str(Dv)+"m" + str(Mv)+'s'], StringLength) if onc.variables.has_key('lon'): print warnmsg print ' ' + fname + ": variable 'lon' already exist !!" print " renaming it as 'lonst'" lonname = 'lonst' else: lonname = 'lon' newvar = objfile.createVariable( lonname, 'f4', ('nst')) basicvardef(newvar, lonname, 'longitude', 'degrees_West' ) newvar[:] = stdesc[1] newvar = objfile.createVariable( 'latstGDM', 'c', ('nst','StrLength')) Gv = int(stdesc[2]) Dv = int((stdesc[2] - Gv)*60.) Mv = int((stdesc[2] - Gv - Dv/60.)*3600.) writing_str_nc(newvar, [str(Gv)+"d" + str(Dv)+"m" + str(Mv)+'s'], StringLength) if onc.variables.has_key('lat'): print warnmsg print ' ' + fname + ": variable 'lat' already exist !!" print " renaming it as 'latst'" latname = 'latst' else: latname = 'lat' newvar = objfile.createVariable( latname, 'f4', ('nst')) basicvardef(newvar, lonname, 'latitude', 'degrees_North' ) newvar[:] = stdesc[2] if onc.variables.has_key('height'): print warnmsg print ' ' + fname + ": variable 'height' already exist !!" print " renaming it as 'heightst'" heightname = 'heightst' else: heightname = 'height' newvar = objfile.createVariable( heightname, 'f4', ('nst')) basicvardef(newvar, heightname, 'height above sea level', 'm' ) newvar[:] = stdesc[3] return def oper_values(dvals, opers): """ Function to operate the values according to given parameters dvals= datavalues opers= operations """ fname = 'oper_values' newdvals = {} varnames = dvals.keys() aopers = ['sumc','subc','mulc','divc'] Nopers = len(opers) for iop in range(Nopers): vn = varnames[iop] print vn,'oper:',opers[iop] if opers[iop] != '-': opern = opers[iop].split(',')[0] operv = np.float(opers[iop].split(',')[1]) vvals = np.array(dvals[vn]) if opern == 'sumc': newvals = np.where(vvals is None, None, vvals+operv) elif opern == 'subc': newvals = np.where(vvals is None, None, vvals-operv) elif opern == 'mulc': newvals = np.where(vvals is None, None, vvals*operv) elif opern == 'divc': newvals = np.where(vvals is None, None, vvals/operv) else: print errormsg print ' ' + fname + ": operation '" + opern + "' not ready!!" print ' availables:',aopers quit(-1) newdvals[vn] = list(newvals) else: newdvals[vn] = dvals[vn] return newdvals def WMOcodevar(unitsn, onc, Lstrcode=1024): """ Function to add a variabe providing description of a units based on WMO code unitsn= name of the units (all WMO codes derived units must be labelled as 'wmo_code_[num]' associated to a file valled wmo_[num].code) onc= netCDF object file to add the description Lstrcode= length of description of codes wmo_[num].code must have the structure: ('#' for comments) reference|web page, document reference with the code short_description|main description of the code long_description|long description of the code codeTYPE|type of the code (andy of 'D', 'F', 'I', 'S') @| Values line giving the start of the values [val1]|[meaning of first value] (...) [valN]|[meaning of last value] """ fname = 'WMOcodevar' # From http://stackoverflow.com/questions/4934806/how-can-i-find-scripts-directory-with-python folder = os.path.dirname(os.path.realpath(__file__)) code = unitsn.split('_')[2] infile = folder + '/wmo_' + code +'.code' if not os.path.isfile(infile): print warnmsg print ' ' + fname + ": WMO code file '" + infile + "' does not exist !!" return # main expected values descvals = ['wmo_code', 'reference', 'short_description', 'long_description', \ 'codeTYPE', '@'] availcodetype = ['D', 'F', 'I', 'S'] codevalues = {} ocode = open(infile, 'r') inivals = False codvals = [] codmeanings = [] for line in ocode: if len(line) > 1 and line[0:1] != '#': linev = line.replace('\n','').replace('\t',' ').replace('\r','') if not inivals: Sv = linev.split('|')[0] Vv = linev.split('|')[1] if searchInlist(descvals, Sv): if Sv != '@': codevalues[Sv] = Vv else: inivals = True else: Svv = linev.split('|')[0] Vvv = linev.split('|')[1] codvals.append(Svv) codmeanings.append(Vvv) # Creating variable if not searchInlist(onc.dimensions, 'Lstringcode'): print ' ' + fname + ": Adding string length dimension 'Lstringcode' for " + \ " code descriptions" newdim = onc.createDimension('Lstringcode', Lstrcode) Ncodes = len(codvals) codedimn = 'wmo_code_' + str(code) if not searchInlist(onc.dimensions, codedimn): print ' ' + fname + ": Adding '" + codedimn + "' dimension for code " + \ "description" newdim = onc.createDimension(codedimn, Ncodes) onc.sync() # Variable with the value of the code if not onc.variables.has_key(codedimn): if codevalues['codeTYPE'] == 'D': newvar = onc.createVariable(codedimn, 'f8', (codedimn)) for iv in range(Ncodes): newvar[iv] = np.float64(codvals[iv]) elif codevalues['codeTYPE'] == 'F': newvar = onc.createVariable(codedimn, 'f', (codedimn)) for iv in range(Ncodes): newvar[iv] = np.float(codvals[iv]) elif codevalues['codeTYPE'] == 'I': newvar = onc.createVariable(codedimn, 'i', (codedimn)) for iv in range(Ncodes): newvar[iv] = int(codvals[iv]) elif codevalues['codeTYPE'] == 'S': newvar = onc.createVariable(codedimn, 'c', (codedimn, 'Lstringcode')) writing_str_nc(newvar, codvals, Lstrcode) else: print errormsg print ' ' + fname + ": codeTYPE '" + codevalues['codeTYPE'] + "' not" + \ " ready !!" print ' available ones:', availcodetype quit(-1) for descv in descvals: if descv != '@' and descv != 'codeTYPE': newvar.setncattr(descv, codevalues[descv]) # Variable with the meaning of the code if not onc.variables.has_key(codedimn+'_meaning'): print ' '+fname+": Adding '" + codedimn + "_meaning' variable for code " + \ "description" newvar = onc.createVariable(codedimn+'_meaning','c',(codedimn,'Lstringcode')) writing_str_nc(newvar, codmeanings, Lstrcode) newvar.setncattr('description', 'meaning of WMO code ' + str(code)) onc.sync() return def add_global_PyNCplot(ObjFile, pyscript, funcname, version): """ Function to add global attributes from 'PyNCplot' to a given netCDF ObjFile= netCDF file object to which add the global attributes funcname= name of the function from which file comes from version= version of the function """ fname = 'add_global_PyNCplot' # Global values ObjFile.setncattr('author', 'L. Fita') newattr = set_attributek(ObjFile, 'institution', unicode('Centro de ' + \ 'Investigaciones del Mar y la Atm' + unichr(243) + 'sfera (CIMA)'), 'U') newattr = set_attributek(ObjFile, 'institution2', unicode('Instituto Franco-' + \ 'Argentino sobre Estudios de Clima y sus Impactos (CNRS, UMI-3351-IFAECI'), 'U') newattr = set_attributek(ObjFile, 'center', unicode('Consejo Nacional de ' + \ 'Investigaciones Cient' + unichr(237) + 'ficas y T' + unichr(233) + \ 'cnicas (CONICET)'), 'U') ObjFile.setncattr('university', 'Universidad de Buenos Aires (UBA)') ObjFile.setncattr('city', 'Buenos Aires') ObjFile.setncattr('country', 'Argentina') ObjFile.setncattr('tool', 'PyNCplot') ObjFile.setncattr('url', 'http://www.xn--llusfb-5va.cat/python/PyNCplot') ObjFile.setncattr('script', pyscript) if funcname is not None: ObjFile.setncattr('function', funcname) ObjFile.setncattr('version', version) ObjFile.sync() return ####### ###### ##### #### ### ## # strCFt="Refdate,tunits (CF reference date [YYYY][MM][DD][HH][MI][SS] format and " + \ " and time units: 'weeks', 'days', 'hours', 'miuntes', 'seconds')" kindobs=['stations-map','multi-points', 'single-station', 'trajectory'] strkObs="kind of observations; 'multi-points': multiple individual punctual obs " + \ "(e.g., lightning strikes), 'single-station': single station on a fixed position,"+\ "'trajectory': following a trajectory" parser = OptionParser() parser.add_option("-c", "--comments", dest="charcom", help="':', list of characters used for comments", metavar="VALUES") parser.add_option("-d", "--descriptionfile", dest="fdesc", help="description file to use" + read_description.__doc__, metavar="FILE") parser.add_option("-e", "--end_column", dest="endcol", help="character to indicate end of the column ('space', for ' ', or 'None,[fixcoljumps]' for fixed size columns with [fixcoljumps]: ',' separated list of positions of column ends within line)", metavar="VALUE") parser.add_option("-f", "--file", dest="obsfile", help="observational file to use", metavar="FILE") parser.add_option("-g", "--debug", dest="debug", help="whther debug is required ('false', 'true')", metavar="VALUE") parser.add_option("-k", "--kindObs", dest="obskind", type='choice', choices=kindobs, help=strkObs, metavar="VALUE") parser.add_option("-s", "--stationLocation", dest="stloc", help="name ('!' for spaces), longitude, latitude and height of the station (only for 'single-station')", metavar="FILE") parser.add_option("-t", "--CFtime", dest="CFtime", help=strCFt, metavar="VALUE") (opts, args) = parser.parse_args() ####### ####### ## MAIN ####### ofile='OBSnetcdf.nc' if opts.charcom is None: print warnmsg print ' ' + main + ': No list of comment characters provided!!' print ' assuming no need!' charcomments = [] else: charcomments = opts.charcom.split(':') if opts.fdesc is None: print errormsg print ' ' + main + ': No description file for the observtional data provided!!' quit(-1) if opts.endcol is None: print warnmsg print ' ' + main + ': No list of comment characters provided!!' print " assuming 'space'" endcol = ' ' else: if opts.endcol == 'space': endcol = ' ' else: endcol = opts.endcol if opts.obsfile is None: print errormsg print ' ' + main + ': No observations file provided!!' quit(-1) if opts.debug is None: print warnmsg print ' ' + main + ': No debug provided!!' print " assuming 'False'" debug = False else: if opts.debug == 'true': debug = True else: debug = False if not os.path.isfile(opts.fdesc): print errormsg print ' ' + main + ": description file '" + opts.fdesc + "' does not exist !!" quit(-1) if not os.path.isfile(opts.obsfile): print errormsg print ' ' + main + ": observational file '" + opts.obsfile + "' does not exist !!" quit(-1) if opts.CFtime is None: print warnmsg print ' ' + main + ': No CFtime criteria are provided !!' print " either time is already in CF-format ('timeFMT=CFtime') in '" + \ opts.fdesc + "'" print " or assuming refdate: '19491201000000' and time units: 'hours'" referencedate = '19491201000000' timeunits = 'hours' else: referencedate = opts.CFtime.split(',')[0] timeunits = opts.CFtime.split(',')[1] if opts.obskind is None: print warnmsg print ' ' + main + ': No kind of observations provided !!' print " assuming 'single-station': single station on a fixed position at 0,0,0" obskind = 'single-station' stationdesc = [0.0, 0.0, 0.0, 0.0] else: obskind = opts.obskind if obskind == 'single-station': if opts.stloc is None: print errornmsg print ' ' + main + ': No station location provided !!' quit(-1) else: stvals = opts.stloc.split(',') stationdesc = [stvals[0], np.float(stvals[1]), np.float(stvals[2]), \ np.float(stvals[3])] else: obskind = opts.obskind # Reading description file ## description = read_description(opts.fdesc, debug) Nvariables=len(description['varN']) formats = description['varTYPE'] if len(formats) != Nvariables: print errormsg print ' ' + main + ': number of formats:',len(formats),' and number of ' + \ 'variables', Nvariables,' does not coincide!!' print ' * what is found is _______' if Nvariables > len(formats): Nshow = len(formats) for ivar in range(Nshow): print ' ',description['varN'][ivar],':', description['varLN'][ivar],\ '[', description['varU'][ivar], '] fmt:', formats[ivar] print ' missing values for:', description['varN'][Nshow:Nvariables+1] else: Nshow = Nvariables for ivar in range(Nshow): print ' ',description['varN'][ivar],':', description['varLN'][ivar],\ '[', description['varU'][ivar], '] fmt:', formats[ivar] print ' excess of formats for:', formats[Nshow:len(formats)+1] # quit(-1) # Reading values ## datavalues = read_datavalues(opts.obsfile, charcomments, endcol, formats, description['varOPER'], description['MissingValue'], description['varN'], debug) # Total number of values Ntvalues = len(datavalues[description['varN'][0]]) if obskind == 'stations-map': print main + ': total values found:',Ntvalues else: print main + ': total temporal values found:',Ntvalues objfile = NetCDFFile(ofile, 'w') # Creation of dimensions ## if obskind == 'stations-map': rowsdim = 'Npoints' dimlength = Ntvalues else: rowsdim = 'time' dimlength = None objfile.createDimension(rowsdim,dimlength) objfile.createDimension('StrLength',StringLength) # Creation of variables ## for ivar in range(Nvariables): varn = description['varN'][ivar] print " including: '" + varn + "' ... .. ." if formats[ivar] == 'D': newvar = objfile.createVariable(varn, 'f32', (rowsdim), fill_value=fillValueF) basicvardef(newvar, varn, description['varLN'][ivar], \ description['varU'][ivar]) newvar[:] = np.where(datavalues[varn] is None, fillValueF, datavalues[varn]) elif formats[ivar] == 'F': newvar = objfile.createVariable(varn, 'f', (rowsdim), fill_value=fillValueF) basicvardef(newvar, varn, description['varLN'][ivar], \ description['varU'][ivar]) newvar[:] = np.where(datavalues[varn] is None, fillValueF, datavalues[varn]) elif formats[ivar] == 'I': newvar = objfile.createVariable(varn, 'i', (rowsdim), fill_value=fillValueI) basicvardef(newvar, varn, description['varLN'][ivar], \ description['varU'][ivar]) # Why is not wotking with integers? vals = np.array(datavalues[varn]) for iv in range(Ntvalues): if vals[iv] is None: vals[iv] = fillValueI newvar[:] = vals elif formats[ivar] == 'S': newvar = objfile.createVariable(varn, 'c', (rowsdim,'StrLength')) basicvardef(newvar, varn, description['varLN'][ivar], \ description['varU'][ivar]) vals = datavalues[varn] for iv in range(Ntvalues): if vals[iv] is None: vals[iv] = fillValueS writing_str_nc(newvar, vals, StringLength) # Getting new variables to describe certain units as codeWMO_[num] from an # external file if description['varU'][ivar][0:8] == 'wmo_code': WMOcodevar(description['varU'][ivar], objfile) # Extra variable descriptions/attributes if description.has_key('varBUFR'): set_attribute(newvar,'bufr_code',description['varBUFR'][ivar]) objfile.sync() # Time variable in CF format ## if description['FMTtime'] == 'CFtime': timevals = datavalues[description['NAMEtime']] iv = 0 for ivn in description['varN']: if ivn == description['NAMEtime']: tunits = description['varU'][iv] break iv = iv + 1 else: # Time as a composition of different columns tcomposite = description['NAMEtime'].find('@') if tcomposite != -1: timevars = description['NAMEtime'].split('@') print warnmsg print ' ' + main + ': time values as combination of different columns!' print ' combining:',timevars,' with a final format: ',description['FMTtime'] timeSvals = [] if debug: print ' ' + main + ': creating times _______' for it in range(Ntvalues): tSvals = '' for tvar in timevars: tSvals = tSvals + datavalues[tvar][it] + ' ' timeSvals.append(tSvals[0:len(tSvals)-1]) if debug: print it, '*' + timeSvals[it] + '*' timevals = Stringtimes_CF(timeSvals, description['FMTtime'].replace('@',' '),\ referencedate, timeunits, debug) else: timevals = Stringtimes_CF(datavalues[description['NAMEtime']], \ description['FMTtime'], referencedate, timeunits, debug) CFtimeRef = referencedate[0:4] +'-'+ referencedate[4:6] +'-'+ referencedate[6:8] + \ ' ' + referencedate[8:10] +':'+ referencedate[10:12] +':'+ referencedate[12:14] tunits = timeunits + ' since ' + CFtimeRef if objfile.variables.has_key('time'): print warnmsg print ' ' + main + ": variable 'time' already exist !!" print " renaming it as 'CFtime'" timeCFname = 'CFtime' newdim = objfile.renameDimension('time','CFtime') newvar = objfile.createVariable( timeCFname, 'f8', ('CFtime')) basicvardef(newvar, timeCFname, 'time', tunits ) else: if not searchInlist(objfile.dimensions, 'time'): newdim = objfile.createDimension('time',None) timeCFname = 'time' newvar = objfile.createVariable( timeCFname, 'f8', ('time')) newvar[:] = np.zeros(timevals.shape[0]) basicvardef(newvar, timeCFname, 'time', tunits ) set_attribute(newvar, 'calendar', 'standard') if obskind == 'stations-map': newvar[:] = timevals[0] else: newvar[:] = timevals # Global attributes ## for descn in description.keys(): if descn[0:3] != 'var' and descn[0:4] != 'NAME' and descn[0:3] != 'FMT': set_attribute(objfile, descn, description[descn]) add_global_PyNCplot(objfile, main, 'main', version) objfile.sync() # Adding new variables as function of the observational type ## 'multi-points', 'single-station', 'trajectory' if obskind != 'single-station': adding_complementary(objfile, description, obskind, datavalues, timevals, \ referencedate, timeunits, Ndim2D, debug) else: # Adding three variables with the station location, longitude, latitude and height adding_station_desc(objfile,stationdesc) objfile.sync() objfile.close() print main + ": Successfull generation of netcdf observational file '" + ofile + "' !!"