def main():
    """
    NAME
    specimens_results_magic.py

    DESCRIPTION
    combines pmag_specimens.txt file with age, location, acceptance criteria and
    outputs pmag_results table along with other MagIC tables necessary for uploading to the database

    SYNTAX
    specimens_results_magic.py [command line options]

    OPTIONS
    -h prints help message and quits
    -usr USER:   identify user, default is ""
    -f: specimen input magic_measurements format file, default is "magic_measurements.txt"
    -fsp: specimen input pmag_specimens format file, default is "pmag_specimens.txt"
    -fsm: sample input er_samples format file, default is "er_samples.txt"
    -fsi: specimen input er_sites format file, default is "er_sites.txt"
    -fla: specify a file with paleolatitudes for calculating VADMs, default is not to calculate VADMS
               format is:  site_name paleolatitude (space delimited file)
    -fa AGES: specify er_ages format file with age information
    -crd [s,g,t,b]:   specify coordinate system
        (s, specimen, g geographic, t, tilt corrected, b, geographic and tilt corrected)
        Default is to assume geographic
        NB: only the tilt corrected data will appear on the results table, if both g and t are selected.
        -cor [AC:CR:NL]: colon delimited list of required data adjustments for all specimens
            included in intensity calculations (anisotropy, cooling rate, non-linear TRM)
            unless specified, corrections will not be applied
        -pri [TRM:ARM] colon delimited list of priorities for anisotropy correction (-cor must also be set to include AC). default is TRM, then ARM
    -age MIN MAX UNITS:   specify age boundaries and units
    -exc:  use exiting selection criteria (in pmag_criteria.txt file), default is default criteria
    -C: no acceptance criteria
    -aD:  average directions per sample, default is NOT
    -aI:  average multiple specimen intensities per sample, default is by site
    -aC:  average all components together, default is NOT
    -pol:  calculate polarity averages
    -sam:  save sample level vgps and v[a]dms, default is by site
    -xSi:  skip the site level intensity calculation
    -p: plot directions and look at intensities by site, default is NOT
        -fmt: specify output for saved images, default is svg (only if -p set)
    -lat: use present latitude for calculating VADMs, default is not to calculate VADMs
    -xD: skip directions
    -xI: skip intensities
    OUPUT
    writes pmag_samples, pmag_sites, pmag_results tables
    """
# set defaults
    Comps=[] # list of components
    version_num=pmag.get_version()
    args=sys.argv
    DefaultAge=["none"]
    skipdirs,coord,excrit,custom,vgps,average,Iaverage,plotsites,opt=1,0,0,0,0,0,0,0,0
    get_model_lat=0 # this skips VADM calculation altogether, when get_model_lat=1, uses present day
    fmt='svg'
    dir_path="."
    model_lat_file=""
    Caverage=0
    infile='pmag_specimens.txt'
    measfile="magic_measurements.txt"
    sampfile="er_samples.txt"
    sitefile="er_sites.txt"
    agefile="er_ages.txt"
    specout="er_specimens.txt"
    sampout="pmag_samples.txt"
    siteout="pmag_sites.txt"
    resout="pmag_results.txt"
    critout="pmag_criteria.txt"
    instout="magic_instruments.txt"
    sigcutoff,OBJ="",""
    noDir,noInt=0,0
    polarity=0
    coords=['0']
    Dcrit,Icrit,nocrit=0,0,0
    corrections=[]
    nocorrection=['DA-NL','DA-AC','DA-CR']
    priorities=['DA-AC-ARM','DA-AC-TRM'] # priorities for anisotropy correction
# get command line stuff
    if "-h" in args:
        print(main.__doc__)
        sys.exit()
    if '-WD' in args:
        ind=args.index("-WD")
        dir_path=args[ind+1]
    if '-cor' in args:
        ind=args.index('-cor')
        cors=args[ind+1].split(':') # list of required data adjustments
        for cor in cors:
            nocorrection.remove('DA-'+cor)
            corrections.append('DA-'+cor)
    if '-pri' in args:
        ind=args.index('-pri')
        priorities=args[ind+1].split(':') # list of required data adjustments
        for p in priorities:
            p='DA-AC-'+p
    if '-f' in args:
        ind=args.index("-f")
        measfile=args[ind+1]
    if '-fsp' in args:
        ind=args.index("-fsp")
        infile=args[ind+1]
    if '-fsi' in args:
        ind=args.index("-fsi")
        sitefile=args[ind+1]
    if "-crd" in args:
        ind=args.index("-crd")
        coord=args[ind+1]
        if coord=='s':coords=['-1']
        if coord=='g':coords=['0']
        if coord=='t':coords=['100']
        if coord=='b':coords=['0','100']
    if "-usr" in args:
        ind=args.index("-usr")
        user=sys.argv[ind+1]
    else: user=""
    if "-C" in args: Dcrit,Icrit,nocrit=1,1,1 # no selection criteria
    if "-sam" in args: vgps=1 # save sample level VGPS/VADMs
    if "-xSi" in args:
        nositeints=1 # skip site level intensity
    else:
        nositeints=0
    if "-age" in args:
        ind=args.index("-age")
        DefaultAge[0]=args[ind+1]
        DefaultAge.append(args[ind+2])
        DefaultAge.append(args[ind+3])
    Daverage,Iaverage,Caverage=0,0,0
    if "-aD" in args: Daverage=1 # average by sample directions
    if "-aI" in args: Iaverage=1 # average by sample intensities
    if "-aC" in args: Caverage=1 # average all components together ???  why???
    if "-pol" in args: polarity=1 # calculate averages by polarity
    if '-xD' in args:noDir=1
    if '-xI' in args:
        noInt=1
    elif "-fla" in args:
        if '-lat' in args:
            print("you should set a paleolatitude file OR use present day lat - not both")
            sys.exit()
        ind=args.index("-fla")
        model_lat_file=dir_path+'/'+args[ind+1]
        get_model_lat=2
        mlat=open(model_lat_file,'r')
        ModelLats=[]
        for line in mlat.readlines():
            ModelLat={}
            tmp=line.split()
            ModelLat["er_site_name"]=tmp[0]
            ModelLat["site_model_lat"]=tmp[1]
            ModelLat["er_sample_name"]=tmp[0]
            ModelLat["sample_lat"]=tmp[1]
            ModelLats.append(ModelLat)
        get_model_lat=2
    elif '-lat' in args:
        get_model_lat=1
    if "-p" in args:
        plotsites=1
        if "-fmt" in args:
            ind=args.index("-fmt")
            fmt=args[ind+1]
        if noDir==0: # plot by site - set up plot window
            import pmagplotlib
            EQ={}
            EQ['eqarea']=1
            pmagplotlib.plot_init(EQ['eqarea'],5,5) # define figure 1 as equal area projection
            pmagplotlib.plot_net(EQ['eqarea']) # I don't know why this has to be here, but otherwise the first plot never plots...
            pmagplotlib.draw_figs(EQ)
    if '-WD' in args:
        infile=dir_path+'/'+infile
        measfile=dir_path+'/'+measfile
        instout=dir_path+'/'+instout
        sampfile=dir_path+'/'+sampfile
        sitefile=dir_path+'/'+sitefile
        agefile=dir_path+'/'+agefile
        specout=dir_path+'/'+specout
        sampout=dir_path+'/'+sampout
        siteout=dir_path+'/'+siteout
        resout=dir_path+'/'+resout
        critout=dir_path+'/'+critout
    if "-exc" in args: # use existing pmag_criteria file
        if "-C" in args:
            print('you can not use both existing and no criteria - choose either -exc OR -C OR neither (for default)')
            sys.exit()
        crit_data,file_type=pmag.magic_read(critout)
        print("Acceptance criteria read in from ", critout)
    else  : # use default criteria (if nocrit set, then get really loose criteria as default)
        crit_data=pmag.default_criteria(nocrit)
        if nocrit==0:
            print("Acceptance criteria are defaults")
        else:
            print("No acceptance criteria used ")
    accept={}
    for critrec in crit_data:
        for key in list(critrec.keys()):
# need to migrate specimen_dang to specimen_int_dang for intensity data using old format
            if 'IE-SPEC' in list(critrec.keys()) and 'specimen_dang' in list(critrec.keys()) and 'specimen_int_dang' not in list(critrec.keys()):
                critrec['specimen_int_dang']=critrec['specimen_dang']
                del critrec['specimen_dang']
# need to get rid of ron shaars sample_int_sigma_uT
            if 'sample_int_sigma_uT' in list(critrec.keys()):
                critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
            if key not in list(accept.keys()) and critrec[key]!='':
                accept[key]=critrec[key]
    #
    #
    if "-exc" not in args and "-C" not in args:
        print("args",args)
        pmag.magic_write(critout,[accept],'pmag_criteria')
        print("\n Pmag Criteria stored in ",critout,'\n')
#
# now we're done slow dancing
#
    SiteNFO,file_type=pmag.magic_read(sitefile) # read in site data - has the lats and lons
    SampNFO,file_type=pmag.magic_read(sampfile) # read in site data - has the lats and lons
    height_nfo=pmag.get_dictitem(SiteNFO,'site_height','','F') # find all the sites with height info.
    if agefile !="":AgeNFO,file_type=pmag.magic_read(agefile) # read in the age information
    Data,file_type=pmag.magic_read(infile) # read in specimen interpretations
    IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
    comment,orient="",[]
    samples,sites=[],[]
    for rec in Data: # run through the data filling in missing keys and finding all components, coordinates available
# fill in missing fields, collect unique sample and site names
        if 'er_sample_name' not in list(rec.keys()):
            rec['er_sample_name']=""
        elif rec['er_sample_name'] not in samples:
            samples.append(rec['er_sample_name'])
        if 'er_site_name' not in list(rec.keys()):
            rec['er_site_name']=""
        elif rec['er_site_name'] not in sites:
            sites.append(rec['er_site_name'])
        if 'specimen_int' not in list(rec.keys()):rec['specimen_int']=''
        if 'specimen_comp_name' not in list(rec.keys()) or rec['specimen_comp_name']=="":rec['specimen_comp_name']='A'
        if rec['specimen_comp_name'] not in Comps:Comps.append(rec['specimen_comp_name'])
        rec['specimen_tilt_correction']=rec['specimen_tilt_correction'].strip('\n')
        if "specimen_tilt_correction" not in list(rec.keys()): rec["specimen_tilt_correction"]="-1" # assume sample coordinates
        if rec["specimen_tilt_correction"] not in orient: orient.append(rec["specimen_tilt_correction"])  # collect available coordinate systems
        if "specimen_direction_type" not in list(rec.keys()): rec["specimen_direction_type"]='l'  # assume direction is line - not plane
        if "specimen_dec" not in list(rec.keys()): rec["specimen_direction_type"]=''  # if no declination, set direction type to blank
        if "specimen_n" not in list(rec.keys()): rec["specimen_n"]=''  # put in n
        if "specimen_alpha95" not in list(rec.keys()): rec["specimen_alpha95"]=''  # put in alpha95
        if "magic_method_codes" not in list(rec.keys()): rec["magic_method_codes"]=''
     #
     # start parsing data into SpecDirs, SpecPlanes, SpecInts
    SpecInts,SpecDirs,SpecPlanes=[],[],[]
    samples.sort() # get sorted list of samples and sites
    sites.sort()
    if noInt==0: # don't skip intensities
        IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
        if nocrit==0: # use selection criteria
            for rec in IntData: # do selection criteria
                kill=pmag.grade(rec,accept,'specimen_int')
                if len(kill)==0: SpecInts.append(rec) # intensity record to be included in sample, site calculations
        else:
            SpecInts=IntData[:] # take everything - no selection criteria
    # check for required data adjustments
        if len(corrections)>0 and len(SpecInts)>0:
            for cor in corrections:
                SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'has') # only take specimens with the required corrections
        if len(nocorrection)>0 and len(SpecInts)>0:
            for cor in nocorrection:
                SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'not') # exclude the corrections not specified for inclusion
# take top priority specimen of its name in remaining specimens (only one per customer)
        PrioritySpecInts=[]
        specimens=pmag.get_specs(SpecInts) # get list of uniq specimen names
        for spec in specimens:
            ThisSpecRecs=pmag.get_dictitem(SpecInts,'er_specimen_name',spec,'T') # all the records for this specimen
            if len(ThisSpecRecs)==1:
                PrioritySpecInts.append(ThisSpecRecs[0])
            elif len(ThisSpecRecs)>1: # more than one
                prec=[]
                for p in priorities:
                    ThisSpecRecs=pmag.get_dictitem(SpecInts,'magic_method_codes',p,'has') # all the records for this specimen
                    if len(ThisSpecRecs)>0:prec.append(ThisSpecRecs[0])
                PrioritySpecInts.append(prec[0]) # take the best one
        SpecInts=PrioritySpecInts # this has the first specimen record
    if noDir==0: # don't skip directions
        AllDirs=pmag.get_dictitem(Data,'specimen_direction_type','','F') # retrieve specimens with directed lines and planes
        Ns=pmag.get_dictitem(AllDirs,'specimen_n','','F')  # get all specimens with specimen_n information
        if nocrit!=1: # use selection criteria
            for rec in Ns: # look through everything with specimen_n for "good" data
                kill=pmag.grade(rec,accept,'specimen_dir')
                if len(kill)==0: # nothing killed it
                    SpecDirs.append(rec)
        else: # no criteria
            SpecDirs=AllDirs[:] # take them all
# SpecDirs is now the list of all specimen directions (lines and planes) that pass muster
#
    PmagSamps,SampDirs=[],[] # list of all sample data and list of those that pass the DE-SAMP criteria
    PmagSites,PmagResults=[],[] # list of all site data and selected results
    SampInts=[]
    for samp in samples: # run through the sample names
        if Daverage==1: #  average by sample if desired
           SampDir=pmag.get_dictitem(SpecDirs,'er_sample_name',samp,'T') # get all the directional data for this sample
           if len(SampDir)>0: # there are some directions
               for coord in coords: # step through desired coordinate systems
                   CoordDir=pmag.get_dictitem(SampDir,'specimen_tilt_correction',coord,'T') # get all the directions for this sample
                   if len(CoordDir)>0: # there are some with this coordinate system
                       if Caverage==0: # look component by component
                           for comp in Comps:
                               CompDir=pmag.get_dictitem(CoordDir,'specimen_comp_name',comp,'T') # get all directions from this component
                               if len(CompDir)>0: # there are some
                                   PmagSampRec=pmag.lnpbykey(CompDir,'sample','specimen') # get a sample average from all specimens
                                   PmagSampRec["er_location_name"]=CompDir[0]['er_location_name'] # decorate the sample record
                                   PmagSampRec["er_site_name"]=CompDir[0]['er_site_name']
                                   PmagSampRec["er_sample_name"]=samp
                                   PmagSampRec["er_citation_names"]="This study"
                                   PmagSampRec["er_analyst_mail_names"]=user
                                   PmagSampRec['magic_software_packages']=version_num
                                   if nocrit!=1:PmagSampRec['pmag_criteria_codes']="ACCEPT"
                                   if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
                                   site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
                                   if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
                                   PmagSampRec['sample_comp_name']=comp
                                   PmagSampRec['sample_tilt_correction']=coord
                                   PmagSampRec['er_specimen_names']= pmag.get_list(CompDir,'er_specimen_name') # get a list of the specimen names used
                                   PmagSampRec['magic_method_codes']= pmag.get_list(CompDir,'magic_method_codes') # get a list of the methods used
                                   if nocrit!=1: # apply selection criteria
                                       kill=pmag.grade(PmagSampRec,accept,'sample_dir')
                                   else:
                                       kill=[]
                                   if len(kill)==0:
                                       SampDirs.append(PmagSampRec)
                                       if vgps==1: # if sample level VGP info desired, do that now
                                           PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
                                           if PmagResRec!="":PmagResults.append(PmagResRec)
                                       PmagSamps.append(PmagSampRec)
                       if Caverage==1: # average all components together  basically same as above
                           PmagSampRec=pmag.lnpbykey(CoordDir,'sample','specimen')
                           PmagSampRec["er_location_name"]=CoordDir[0]['er_location_name']
                           PmagSampRec["er_site_name"]=CoordDir[0]['er_site_name']
                           PmagSampRec["er_sample_name"]=samp
                           PmagSampRec["er_citation_names"]="This study"
                           PmagSampRec["er_analyst_mail_names"]=user
                           PmagSampRec['magic_software_packages']=version_num
                           if nocrit!=1:PmagSampRec['pmag_criteria_codes']=""
                           if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
                           site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
                           if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
                           PmagSampRec['sample_tilt_correction']=coord
                           PmagSampRec['sample_comp_name']= pmag.get_list(CoordDir,'specimen_comp_name') # get components used
                           PmagSampRec['er_specimen_names']= pmag.get_list(CoordDir,'er_specimen_name') # get specimne names averaged
                           PmagSampRec['magic_method_codes']= pmag.get_list(CoordDir,'magic_method_codes') # assemble method codes
                           if nocrit!=1: # apply selection criteria
                               kill=pmag.grade(PmagSampRec,accept,'sample_dir')
                               if len(kill)==0: # passes the mustard
                                   SampDirs.append(PmagSampRec)
                                   if vgps==1:
                                       PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
                                       if PmagResRec!="":PmagResults.append(PmagResRec)
                           else: # take everything
                               SampDirs.append(PmagSampRec)
                               if vgps==1:
                                   PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
                                   if PmagResRec!="":PmagResults.append(PmagResRec)
                           PmagSamps.append(PmagSampRec)
        if Iaverage==1: #  average by sample if desired
           SampI=pmag.get_dictitem(SpecInts,'er_sample_name',samp,'T') # get all the intensity data for this sample
           if len(SampI)>0: # there are some
               PmagSampRec=pmag.average_int(SampI,'specimen','sample') # get average intensity stuff
               PmagSampRec["sample_description"]="sample intensity" # decorate sample record
               PmagSampRec["sample_direction_type"]=""
               PmagSampRec['er_site_name']=SampI[0]["er_site_name"]
               PmagSampRec['er_sample_name']=samp
               PmagSampRec['er_location_name']=SampI[0]["er_location_name"]
               PmagSampRec["er_citation_names"]="This study"
               PmagSampRec["er_analyst_mail_names"]=user
               if agefile != "":   PmagSampRec=pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_", AgeNFO,DefaultAge)
               site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
               if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
               PmagSampRec['er_specimen_names']= pmag.get_list(SampI,'er_specimen_name')
               PmagSampRec['magic_method_codes']= pmag.get_list(SampI,'magic_method_codes')
               if nocrit!=1:  # apply criteria!
                   kill=pmag.grade(PmagSampRec,accept,'sample_int')
                   if len(kill)==0:
                       PmagSampRec['pmag_criteria_codes']="ACCEPT"
                       SampInts.append(PmagSampRec)
                       PmagSamps.append(PmagSampRec)
                   else:PmagSampRec={} # sample rejected
               else: # no criteria
                   SampInts.append(PmagSampRec)
                   PmagSamps.append(PmagSampRec)
                   PmagSampRec['pmag_criteria_codes']=""
               if vgps==1 and get_model_lat!=0 and PmagSampRec!={}: #
                   if get_model_lat==1: # use sample latitude
                       PmagResRec=pmag.getsampVDM(PmagSampRec,SampNFO)
                       del(PmagResRec['model_lat']) # get rid of the model lat key
                   elif get_model_lat==2: # use model latitude
                       PmagResRec=pmag.getsampVDM(PmagSampRec,ModelLats)
                       if PmagResRec!={}:PmagResRec['magic_method_codes']=PmagResRec['magic_method_codes']+":IE-MLAT"
                   if PmagResRec!={}:
                          PmagResRec['er_specimen_names']=PmagSampRec['er_specimen_names']
                          PmagResRec['er_sample_names']=PmagSampRec['er_sample_name']
                          PmagResRec['pmag_criteria_codes']='ACCEPT'
                          PmagResRec['average_int_sigma_perc']=PmagSampRec['sample_int_sigma_perc']
                          PmagResRec['average_int_sigma']=PmagSampRec['sample_int_sigma']
                          PmagResRec['average_int_n']=PmagSampRec['sample_int_n']
                          PmagResRec['vadm_n']=PmagSampRec['sample_int_n']
                          PmagResRec['data_type']='i'
                          PmagResults.append(PmagResRec)
    if len(PmagSamps)>0:
        TmpSamps,keylist=pmag.fillkeys(PmagSamps) # fill in missing keys from different types of records
        pmag.magic_write(sampout,TmpSamps,'pmag_samples') # save in sample output file
        print(' sample averages written to ',sampout)

#
#create site averages from specimens or samples as specified
#
    for site in sites:
        if Daverage==0: key,dirlist='specimen',SpecDirs # if specimen averages at site level desired
        if Daverage==1: key,dirlist='sample',SampDirs # if sample averages at site level desired
        tmp=pmag.get_dictitem(dirlist,'er_site_name',site,'T') # get all the sites with  directions
        tmp1=pmag.get_dictitem(tmp,key+'_tilt_correction',coords[-1],'T') # use only the last coordinate if Caverage==0
        sd=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T') # fish out site information (lat/lon, etc.)
        if len(sd)>0:
            sitedat=sd[0]
            if Caverage==0: # do component wise averaging
                for comp in Comps:
                    siteD=pmag.get_dictitem(tmp1,key+'_comp_name',comp,'T') # get all components comp
                    if len(siteD)>0: # there are some for this site and component name
                        PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get an average for this site
                        PmagSiteRec['site_comp_name']=comp # decorate the site record
                        PmagSiteRec["er_location_name"]=siteD[0]['er_location_name']
                        PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
                        PmagSiteRec['site_tilt_correction']=coords[-1]
                        PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
                        if Daverage==1:
                            PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
                        else:
                            PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
        # determine the demagnetization code (DC3,4 or 5) for this site
                        AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
                        Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
                        DC=3
                        if AFnum>0:DC+=1
                        if Tnum>0:DC+=1
                        PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
                        PmagSiteRec['magic_method_codes'].strip(":")
                        if plotsites==1:
                            print(PmagSiteRec['er_site_name'])
                            pmagplotlib.plot_site(EQ['eqarea'],PmagSiteRec,siteD,key) # plot and list the data
                            pmagplotlib.draw_figs(EQ)
                        PmagSites.append(PmagSiteRec)
            else: # last component only
                siteD=tmp1[:] # get the last orientation system specified
                if len(siteD)>0: # there are some
                    PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get the average for this site
                    PmagSiteRec["er_location_name"]=siteD[0]['er_location_name'] # decorate the record
                    PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
                    PmagSiteRec['site_comp_name']=comp
                    PmagSiteRec['site_tilt_correction']=coords[-1]
                    PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
                    PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
                    PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
                    AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
                    Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
                    DC=3
                    if AFnum>0:DC+=1
                    if Tnum>0:DC+=1
                    PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
                    PmagSiteRec['magic_method_codes'].strip(":")
                    if Daverage==0:PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
                    if plotsites==1:
                        pmagplotlib.plot_site(EQ['eqarea'],PmagSiteRec,siteD,key)
                        pmagplotlib.draw_figs(EQ)
                    PmagSites.append(PmagSiteRec)
        else:
            print('site information not found in er_sites for site, ',site,' site will be skipped')
    for PmagSiteRec in PmagSites: # now decorate each dictionary some more, and calculate VGPs etc. for results table
        PmagSiteRec["er_citation_names"]="This study"
        PmagSiteRec["er_analyst_mail_names"]=user
        PmagSiteRec['magic_software_packages']=version_num
        if agefile != "": PmagSiteRec= pmag.get_age(PmagSiteRec,"er_site_name","site_inferred_",AgeNFO,DefaultAge)
        PmagSiteRec['pmag_criteria_codes']='ACCEPT'
        if 'site_n_lines' in list(PmagSiteRec.keys()) and 'site_n_planes' in list(PmagSiteRec.keys()) and PmagSiteRec['site_n_lines']!="" and PmagSiteRec['site_n_planes']!="":
            if int(PmagSiteRec["site_n_planes"])>0:
                PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM-LP"
            elif int(PmagSiteRec["site_n_lines"])>2:
                PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM"
            kill=pmag.grade(PmagSiteRec,accept,'site_dir')
            if len(kill)==0:
                PmagResRec={} # set up dictionary for the pmag_results table entry
                PmagResRec['data_type']='i' # decorate it a bit
                PmagResRec['magic_software_packages']=version_num
                PmagSiteRec['site_description']='Site direction included in results table'
                PmagResRec['pmag_criteria_codes']='ACCEPT'
                dec=float(PmagSiteRec["site_dec"])
                inc=float(PmagSiteRec["site_inc"])
                if 'site_alpha95' in list(PmagSiteRec.keys()) and PmagSiteRec['site_alpha95']!="":
                    a95=float(PmagSiteRec["site_alpha95"])
                else:a95=180.
                sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T')[0] # fish out site information (lat/lon, etc.)
                lat=float(sitedat['site_lat'])
                lon=float(sitedat['site_lon'])
                plong,plat,dp,dm=pmag.dia_vgp(dec,inc,a95,lat,lon) # get the VGP for this site
                if PmagSiteRec['site_tilt_correction']=='-1':C=' (spec coord) '
                if PmagSiteRec['site_tilt_correction']=='0':C=' (geog. coord) '
                if PmagSiteRec['site_tilt_correction']=='100':C=' (strat. coord) '
                PmagResRec["pmag_result_name"]="VGP Site: "+PmagSiteRec["er_site_name"] # decorate some more
                PmagResRec["result_description"]="Site VGP, coord system = "+str(coord)+' component: '+comp
                PmagResRec['er_site_names']=PmagSiteRec['er_site_name']
                PmagResRec['pmag_criteria_codes']='ACCEPT'
                PmagResRec['er_citation_names']='This study'
                PmagResRec['er_analyst_mail_names']=user
                PmagResRec["er_location_names"]=PmagSiteRec["er_location_name"]
                if Daverage==1:
                    PmagResRec["er_sample_names"]=PmagSiteRec["er_sample_names"]
                else:
                    PmagResRec["er_specimen_names"]=PmagSiteRec["er_specimen_names"]
                PmagResRec["tilt_correction"]=PmagSiteRec['site_tilt_correction']
                PmagResRec["pole_comp_name"]=PmagSiteRec['site_comp_name']
                PmagResRec["average_dec"]=PmagSiteRec["site_dec"]
                PmagResRec["average_inc"]=PmagSiteRec["site_inc"]
                PmagResRec["average_alpha95"]=PmagSiteRec["site_alpha95"]
                PmagResRec["average_n"]=PmagSiteRec["site_n"]
                PmagResRec["average_n_lines"]=PmagSiteRec["site_n_lines"]
                PmagResRec["average_n_planes"]=PmagSiteRec["site_n_planes"]
                PmagResRec["vgp_n"]=PmagSiteRec["site_n"]
                PmagResRec["average_k"]=PmagSiteRec["site_k"]
                PmagResRec["average_r"]=PmagSiteRec["site_r"]
                PmagResRec["average_lat"]='%10.4f ' %(lat)
                PmagResRec["average_lon"]='%10.4f ' %(lon)
                if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
                site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
                if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
                PmagResRec["vgp_lat"]='%7.1f ' % (plat)
                PmagResRec["vgp_lon"]='%7.1f ' % (plong)
                PmagResRec["vgp_dp"]='%7.1f ' % (dp)
                PmagResRec["vgp_dm"]='%7.1f ' % (dm)
                PmagResRec["magic_method_codes"]= PmagSiteRec["magic_method_codes"]
                if PmagSiteRec['site_tilt_correction']=='0':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-GEO"
                if PmagSiteRec['site_tilt_correction']=='100':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-TILT"
                PmagSiteRec['site_polarity']=""
                if polarity==1: # assign polarity based on angle of pole lat to spin axis - may want to re-think this sometime
                    angle=pmag.angle([0,0],[0,(90-plat)])
                    if angle <= 55.: PmagSiteRec["site_polarity"]='n'
                    if angle > 55. and angle < 125.: PmagSiteRec["site_polarity"]='t'
                    if angle >= 125.: PmagSiteRec["site_polarity"]='r'
                PmagResults.append(PmagResRec)
    if polarity==1:
        crecs=pmag.get_dictitem(PmagSites,'site_tilt_correction','100','T') # find the tilt corrected data
        if len(crecs)<2:crecs=pmag.get_dictitem(PmagSites,'site_tilt_correction','0','T') # if there aren't any, find the geographic corrected data
        if len(crecs)>2: # if there are some,
            comp=pmag.get_list(crecs,'site_comp_name').split(':')[0] # find the first component
            crecs=pmag.get_dictitem(crecs,'site_comp_name',comp,'T') # fish out all of the first component
            precs=[]
            for rec in crecs:
                precs.append({'dec':rec['site_dec'],'inc':rec['site_inc'],'name':rec['er_site_name'],'loc':rec['er_location_name']})
            polpars=pmag.fisher_by_pol(precs) # calculate average by polarity
            for mode in list(polpars.keys()): # hunt through all the modes (normal=A, reverse=B, all=ALL)
                PolRes={}
                PolRes['er_citation_names']='This study'
                PolRes["pmag_result_name"]="Polarity Average: Polarity "+mode #
                PolRes["data_type"]="a"
                PolRes["average_dec"]='%7.1f'%(polpars[mode]['dec'])
                PolRes["average_inc"]='%7.1f'%(polpars[mode]['inc'])
                PolRes["average_n"]='%i'%(polpars[mode]['n'])
                PolRes["average_r"]='%5.4f'%(polpars[mode]['r'])
                PolRes["average_k"]='%6.0f'%(polpars[mode]['k'])
                PolRes["average_alpha95"]='%7.1f'%(polpars[mode]['alpha95'])
                PolRes['er_site_names']= polpars[mode]['sites']
                PolRes['er_location_names']= polpars[mode]['locs']
                PolRes['magic_software_packages']=version_num
                PmagResults.append(PolRes)

    if noInt!=1 and nositeints!=1:
      for site in sites: # now do intensities for each site
        if plotsites==1:print(site)
        if Iaverage==0: key,intlist='specimen',SpecInts # if using specimen level data
        if Iaverage==1: key,intlist='sample',PmagSamps # if using sample level data
        Ints=pmag.get_dictitem(intlist,'er_site_name',site,'T') # get all the intensities  for this site
        if len(Ints)>0: # there are some
            PmagSiteRec=pmag.average_int(Ints,key,'site') # get average intensity stuff for site table
            PmagResRec=pmag.average_int(Ints,key,'average') # get average intensity stuff for results table
            if plotsites==1: # if site by site examination requested - print this site out to the screen
                for rec in Ints:print(rec['er_'+key+'_name'],' %7.1f'%(1e6*float(rec[key+'_int'])))
                if len(Ints)>1:
                    print('Average: ','%7.1f'%(1e6*float(PmagResRec['average_int'])),'N: ',len(Ints))
                    print('Sigma: ','%7.1f'%(1e6*float(PmagResRec['average_int_sigma'])),'Sigma %: ',PmagResRec['average_int_sigma_perc'])
                input('Press any key to continue\n')
            er_location_name=Ints[0]["er_location_name"]
            PmagSiteRec["er_location_name"]=er_location_name # decorate the records
            PmagSiteRec["er_citation_names"]="This study"
            PmagResRec["er_location_names"]=er_location_name
            PmagResRec["er_citation_names"]="This study"
            PmagSiteRec["er_analyst_mail_names"]=user
            PmagResRec["er_analyst_mail_names"]=user
            PmagResRec["data_type"]='i'
            if Iaverage==0:
                PmagSiteRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name') # list of all specimens used
                PmagResRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name')
            PmagSiteRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name') # list of all samples used
            PmagResRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name')
            PmagSiteRec['er_site_name']= site
            PmagResRec['er_site_names']= site
            PmagSiteRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
            PmagResRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
            kill=pmag.grade(PmagSiteRec,accept,'site_int')
            if nocrit==1 or len(kill)==0:
                b,sig=float(PmagResRec['average_int']),""
                if(PmagResRec['average_int_sigma'])!="":sig=float(PmagResRec['average_int_sigma'])
                sdir=pmag.get_dictitem(PmagResults,'er_site_names',site,'T') # fish out site direction
                if len(sdir)>0 and  sdir[-1]['average_inc']!="": # get the VDM for this record using last average inclination (hope it is the right one!)
                        inc=float(sdir[0]['average_inc']) #
                        mlat=pmag.magnetic_lat(inc) # get magnetic latitude using dipole formula
                        PmagResRec["vdm"]='%8.3e '% (pmag.b_vdm(b,mlat)) # get VDM with magnetic latitude
                        PmagResRec["vdm_n"]=PmagResRec['average_int_n']
                        if 'average_int_sigma' in list(PmagResRec.keys()) and PmagResRec['average_int_sigma']!="":
                            vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),mlat)
                            PmagResRec["vdm_sigma"]='%8.3e '% (vdm_sig)
                        else:
                            PmagResRec["vdm_sigma"]=""
                mlat="" # define a model latitude
                if get_model_lat==1: # use present site latitude
                    mlats=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T')
                    if len(mlats)>0: mlat=mlats[0]['site_lat']
                elif get_model_lat==2: # use a model latitude from some plate reconstruction model (or something)
                    mlats=pmag.get_dictitem(ModelLats,'er_site_name',site,'T')
                    if len(mlats)>0: PmagResRec['model_lat']=mlats[0]['site_model_lat']
                    mlat=PmagResRec['model_lat']
                if mlat!="":
                    PmagResRec["vadm"]='%8.3e '% (pmag.b_vdm(b,float(mlat))) # get the VADM using the desired latitude
                    if sig!="":
                        vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),float(mlat))
                        PmagResRec["vadm_sigma"]='%8.3e '% (vdm_sig)
                        PmagResRec["vadm_n"]=PmagResRec['average_int_n']
                    else:
                        PmagResRec["vadm_sigma"]=""
                sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T') # fish out site information (lat/lon, etc.)
                if len(sitedat)>0:
                    sitedat=sitedat[0]
                    PmagResRec['average_lat']=sitedat['site_lat']
                    PmagResRec['average_lon']=sitedat['site_lon']
                else:
                    PmagResRec['average_lon']='UNKNOWN'
                    PmagResRec['average_lon']='UNKNOWN'
                PmagResRec['magic_software_packages']=version_num
                PmagResRec["pmag_result_name"]="V[A]DM: Site "+site
                PmagResRec["result_description"]="V[A]DM of site"
                PmagResRec["pmag_criteria_codes"]="ACCEPT"
                if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
                site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
                if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
                PmagSites.append(PmagSiteRec)
                PmagResults.append(PmagResRec)
    if len(PmagSites)>0:
        Tmp,keylist=pmag.fillkeys(PmagSites)
        pmag.magic_write(siteout,Tmp,'pmag_sites')
        print(' sites written to ',siteout)
    else: print("No Site level table")
    if len(PmagResults)>0:
        TmpRes,keylist=pmag.fillkeys(PmagResults)
        pmag.magic_write(resout,TmpRes,'pmag_results')
        print(' results written to ',resout)
    else: print("No Results level table")