Beispiel #1
0
def spitout(line):
    if '\t' in line:
        dat=line.split('\t') # split the data on a space into columns
    else:
        dat=line.split() # split the data on a space into columns
    b,lat=float(dat[0])*1e-6,float(dat[1])
    vdm= pmag.b_vdm(b,lat)  # 
    return vdm
Beispiel #2
0
def spitout(line):
    if '\t' in line:
        dat=line.split('\t') # split the data on a space into columns
    else:
        dat=line.split() # split the data on a space into columns
    b,lat=float(dat[0])*1e-6,float(dat[1])
    vdm= pmag.b_vdm(b,lat)  # 
    return vdm
Beispiel #3
0
def main():
    """
    NAME
        b_vdm.py
    
    DESCRIPTION
          converts B (in microT) and (magnetic) latitude to V(A)DM
 
    INPUT (COMMAND LINE ENTRY) 
           B (microtesla), latitude (positive north)

    OUTPUT
           V[A]DM
    
    SYNTAX
        b_vdm.py [command line options] [< filename]
    
    OPTIONS
        -h prints help and quits 
        -i for interactive data entry
        -f FILE input file
        -F FILE output 
    
    """
    input,out="",""
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-f' in sys.argv:
        ind=sys.argv.index('-f')
        file=sys.argv[ind+1]
        f=open(file,'rU')
        input=f.readlines()
    if '-F' in sys.argv:
        ind=sys.argv.index('-F')
        o=sys.argv[ind+1]
        out=open(o,'w')
    if '-i' in sys.argv:
        cont=1
        while cont==1:
            try:
                b=1e-6*float(raw_input('B (in microtesla): <cntl-D to quit '))
                lat=float(raw_input('Latitude: '))
            except:
                print "\nGood bye\n"
                sys.exit()
                 
            vdm= pmag.b_vdm(b,lat)
            print '%10.3e '%(vdm)
    if input=="":
        input = sys.stdin.readlines()  # read from standard input
    for line in input:
        vdm=spitout(line)
        if out=="":
            print '%10.3e'%(vdm)
        else:
            out.write('%10.3e \n'%(vdm))
Beispiel #4
0
def main():
    """
    NAME
        b_vdm.py
    
    DESCRIPTION
          converts B (in microT) and (magnetic) latitude to V(A)DM
 
    INPUT (COMMAND LINE ENTRY) 
           B (microtesla), latitude (positive north)

    OUTPUT
           V[A]DM
    
    SYNTAX
        b_vdm.py [command line options] [< filename]
    
    OPTIONS
        -h prints help and quits 
        -i for interactive data entry
        -f FILE input file
        -F FILE output 
    
    """
    input,out="",""
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    if '-f' in sys.argv:
        ind=sys.argv.index('-f')
        file=sys.argv[ind+1]
        f=open(file,'r')
        input=f.readlines()
    if '-F' in sys.argv:
        ind=sys.argv.index('-F')
        o=sys.argv[ind+1]
        out=open(o,'w')
    if '-i' in sys.argv:
        cont=1
        while cont==1:
            try:
                b=1e-6*float(input('B (in microtesla): <cntl-D to quit '))
                lat=float(input('Latitude: '))
            except:
                print("\nGood bye\n")
                sys.exit()
                 
            vdm= pmag.b_vdm(b,lat)
            print('%10.3e '%(vdm))
    if input=="":
        input = sys.stdin.readlines()  # read from standard input
    for line in input:
        vdm=spitout(line)
        if out=="":
            print('%10.3e'%(vdm))
        else:
            out.write('%10.3e \n'%(vdm))
Beispiel #5
0
def main():
    """
    NAME
        igrf.py
    DESCRIPTION
        This program calculates igrf field values 
    using the routine of Malin and  Barraclough (1981) 
    based on d/igrfs from 1900 to 2010.
    between 1900 and 1000BCE, it uses CALS3K.4, ARCH3K.1 , or PFM9K
    Prior to 1000BCE, it uses CALS10k-4b
    Calculates reference field vector at  specified location and time.
  
    SYNTAX
       igrf.py [-h] [-i] -f FILE  [< filename]
    OPTIONS:
       -h prints help message and quits
       -i for interactive data entry
       -f FILE  specify file name with input data 
       -F FILE  specify output file name
       -ages MIN MAX INCR: specify age minimum in years (+/- AD), maximum and increment, default is line by line
       -loc LAT LON;  specify location, default is line by line
       -alt ALT;  specify altitude in km, default is sealevel (0)
       -plt; make a plot of the time series
       -sav, saves plot and quits
       -fmt [pdf,jpg,eps,svg]  specify format for output figure  (default is svg)
       -mod [arch3k,cals3k,pfm9k] specify model for 3ka to 1900 AD, default is cals3k.4b
             NB:  program uses IGRF12 for dates 1900 to 2015.
    
    INPUT FORMAT 
      interactive entry:
           date: decimal year
           alt:  altitude in km
           lat: positive north
           lon: positive east
       for file entry:
           space delimited string: date  alt   lat long
    OUTPUT  FORMAT
        Declination Inclination Intensity (nT) date alt lat long
    """
    plot,fmt=0,'svg'
    plt=0
    if '-fmt' in sys.argv:
        ind=sys.argv.index('-fmt')
        fmt=sys.argv[ind+1]
    if len(sys.argv)!=0 and '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-mod' in sys.argv:
        ind=sys.argv.index('-mod')
        mod=sys.argv[ind+1]
    else: mod='cals3k'
    if '-f' in sys.argv:
        ind=sys.argv.index('-f')
        file=sys.argv[ind+1]
        input=numpy.loadtxt(file)
    elif '-i' in sys.argv:
        while 1:
          try:
            line=[]
            line.append(float(raw_input("Decimal year: <cntrl-D to quit> ")))
            alt=raw_input("Elevation in km [0] ")
            if alt=="":alt="0"
            line.append(float(alt))
            line.append(float(raw_input("Latitude (positive north) ")))
            line.append(float(raw_input("Longitude (positive east) ")))
            if mod=='':
                x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0])
            else:
                x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod=mod)
            Dir=pmag.cart2dir((x,y,z))
            print '%8.2f %8.2f %8.0f'%(Dir[0],Dir[1],f)           
          except EOFError:
            print "\n Good-bye\n"
            sys.exit()
    elif '-ages' in sys.argv:
        ind=sys.argv.index('-ages')
        agemin=float(sys.argv[ind+1])
        agemax=float(sys.argv[ind+2])
        ageincr=float(sys.argv[ind+3])
        if '-loc' in sys.argv:
            ind=sys.argv.index('-loc')
            lat=float(sys.argv[ind+1])
            lon=float(sys.argv[ind+2])
        else: 
            print "must specify lat/lon if using age range option"
            sys.exit()
        if '-alt' in sys.argv:
            ind=sys.argv.index('-alt')
            alt=float(sys.argv[ind+1])
        else: alt=0
        ages=numpy.arange(agemin,agemax,ageincr)
        lats=numpy.ones(len(ages))*lat
        lons=numpy.ones(len(ages))*lon
        alts=numpy.ones(len(ages))*alt
        input=numpy.array([ages,alts,lats,lons]).transpose()
    else:
        input=numpy.loadtxt(sys.stdin,dtype=numpy.float)
    if '-F' in sys.argv:
        ind=sys.argv.index('-F')
        outfile=sys.argv[ind+1]
        out=open(outfile,'w')
    else:outfile=""
    if '-sav' in sys.argv:plot=1
    if '-plt' in sys.argv:
        plt=1
        import matplotlib
        matplotlib.use("TkAgg")
        import pylab
        pylab.ion()
        Ages,Decs,Incs,Ints,VADMs=[],[],[],[],[]
    for line in input:
        if mod=='':
            x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0])
        else:
            x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod=mod)
        Dir=pmag.cart2dir((x,y,z))
        if outfile!="":
            out.write('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f\n'%(Dir[0],Dir[1],f,line[0],line[1],line[2],line[3]))           
        elif plt:
            Ages.append(line[0])
            if Dir[0]>180: Dir[0]=Dir[0]-360.0
            Decs.append(Dir[0])
            Incs.append(Dir[1])
            Ints.append(f*1e-3)
            VADMs.append(pmag.b_vdm(f*1e-9,line[2])*1e-21)
        else:
            print '%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f'%(Dir[0],Dir[1],f,line[0],line[1],line[2],line[3])           
    if plt:
        fig=pylab.figure(num=1,figsize=(7,9))
        fig.add_subplot(411)
        pylab.plot(Ages,Decs)
        pylab.ylabel('Declination ($^{\circ}$)')
        fig.add_subplot(412)
        pylab.plot(Ages,Incs)
        pylab.ylabel('Inclination ($^{\circ}$)')
        fig.add_subplot(413)
        pylab.plot(Ages,Ints)
        pylab.ylabel('Intensity ($\mu$T)')
        fig.add_subplot(414)
        pylab.plot(Ages,VADMs)
        pylab.ylabel('VADMs (ZAm$^2$)')
        pylab.xlabel('Ages')
        if plot==0:
            pylab.draw()
            ans=raw_input("S[a]ve to save figure, <Return>  to quit  ")
            if ans=='a':
                pylab.savefig('igrf.'+fmt)
                print 'Figure saved as: ','igrf.'+fmt
        else: 
            pylab.savefig('igrf.'+fmt)
            print 'Figure saved as: ','igrf.'+fmt
        sys.exit()
Beispiel #6
0
def main():
    """
    NAME
        igrf.py
    DESCRIPTION
        This program calculates igrf field values 
    using the routine of Malin and  Barraclough (1981) 
    based on d/igrfs from 1900 to 2010.
    between 1900 and 1000BCE, it uses CALS3K.4, ARCH3K.1 
    Prior to 1000BCE, it uses PFM9k or CALS10k-4b
    Calculates reference field vector at  specified location and time.
  
    SYNTAX
       igrf.py [-h] [-i] -f FILE  [< filename]
    OPTIONS:
       -h prints help message and quits
       -i for interactive data entry
       -f FILE  specify file name with input data 
       -F FILE  specify output file name
       -ages MIN MAX INCR: specify age minimum in years (+/- AD), maximum and increment, default is line by line
       -loc LAT LON;  specify location, default is line by line
       -alt ALT;  specify altitude in km, default is sealevel (0)
       -plt; make a plot of the time series
       -sav, saves plot and quits
       -fmt [pdf,jpg,eps,svg]  specify format for output figure  (default is svg)
       -mod [arch3k,cals3k,pfm9k,hfm10k,cals10k_2,shadif14k,cals10k] specify model for 3ka to 1900 AD, default is cals10k
             NB:  program uses IGRF12 for dates 1900 to 2015.
    
    INPUT FORMAT 
      interactive entry:
           date: decimal year
           alt:  altitude in km
           lat: positive north
           lon: positive east
       for file entry:
           space delimited string: date  alt   lat long
    OUTPUT  FORMAT
        Declination Inclination Intensity (nT) date alt lat long
    MODELS:  ARCH3K: (Korte et al., 2009);CALS3K (Korte & Contable, 2011); CALS10k (is .1b of Korte et al., 2011); PFM9K (Nilsson et al., 2014); HFM10k (is HFM.OL1.A1 of Constable et al., 2016); CALS10k_2 (is cals10k.2 of Constable et al., 2016), SHADIF14k (SHA.DIF.14K of Pavon-Carrasco et al., 2014).
    """
    plot, fmt = 0, 'svg'
    plt = 0
    if '-fmt' in sys.argv:
        ind = sys.argv.index('-fmt')
        fmt = sys.argv[ind + 1]
    if len(sys.argv) != 0 and '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    if '-mod' in sys.argv:
        ind = sys.argv.index('-mod')
        mod = sys.argv[ind + 1]
    else:
        mod = 'cals10k'
    if '-f' in sys.argv:
        ind = sys.argv.index('-f')
        file = sys.argv[ind + 1]
        input = numpy.loadtxt(file)
    elif '-i' in sys.argv:
        while 1:
            try:
                line = []
                line.append(float(input("Decimal year: <cntrl-D to quit> ")))
                alt = input("Elevation in km [0] ")
                if alt == "": alt = "0"
                line.append(float(alt))
                line.append(float(input("Latitude (positive north) ")))
                line.append(float(input("Longitude (positive east) ")))
                if mod == '':
                    x, y, z, f = pmag.doigrf(line[3] % 360., line[2], line[1],
                                             line[0])
                else:
                    x, y, z, f = pmag.doigrf(line[3] % 360.,
                                             line[2],
                                             line[1],
                                             line[0],
                                             mod=mod)
                Dir = pmag.cart2dir((x, y, z))
                print('%8.2f %8.2f %8.0f' % (Dir[0], Dir[1], f))
            except EOFError:
                print("\n Good-bye\n")
                sys.exit()
    elif '-ages' in sys.argv:
        ind = sys.argv.index('-ages')
        agemin = float(sys.argv[ind + 1])
        agemax = float(sys.argv[ind + 2])
        ageincr = float(sys.argv[ind + 3])
        if '-loc' in sys.argv:
            ind = sys.argv.index('-loc')
            lat = float(sys.argv[ind + 1])
            lon = float(sys.argv[ind + 2])
        else:
            print("must specify lat/lon if using age range option")
            sys.exit()
        if '-alt' in sys.argv:
            ind = sys.argv.index('-alt')
            alt = float(sys.argv[ind + 1])
        else:
            alt = 0
        ages = numpy.arange(agemin, agemax, ageincr)
        lats = numpy.ones(len(ages)) * lat
        lons = numpy.ones(len(ages)) * lon
        alts = numpy.ones(len(ages)) * alt
        input = numpy.array([ages, alts, lats, lons]).transpose()
    else:
        input = numpy.loadtxt(sys.stdin, dtype=numpy.float)
    if '-F' in sys.argv:
        ind = sys.argv.index('-F')
        outfile = sys.argv[ind + 1]
        out = open(outfile, 'w')
    else:
        outfile = ""
    if '-sav' in sys.argv: plot = 1
    if '-plt' in sys.argv:
        plt = 1
        import matplotlib
        matplotlib.use("TkAgg")
        import pylab
        pylab.ion()
        Ages, Decs, Incs, Ints, VADMs = [], [], [], [], []
    for line in input:
        #if mod=='':
        #    x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0])
        #else:
        #    x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod=mod)
        x, y, z, f = pmag.doigrf(line[3] % 360.,
                                 line[2],
                                 line[1],
                                 line[0],
                                 mod=mod)
        Dir = pmag.cart2dir((x, y, z))
        if outfile != "":
            out.write('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f\n' %
                      (Dir[0], Dir[1], f, line[0], line[1], line[2], line[3]))
        elif plt:
            Ages.append(line[0])
            if Dir[0] > 180: Dir[0] = Dir[0] - 360.0
            Decs.append(Dir[0])
            Incs.append(Dir[1])
            Ints.append(f * 1e-3)
            VADMs.append(pmag.b_vdm(f * 1e-9, line[2]) * 1e-21)
        else:
            print('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f' %
                  (Dir[0], Dir[1], f, line[0], line[1], line[2], line[3]))
    if plt:
        fig = pylab.figure(num=1, figsize=(7, 9))
        fig.add_subplot(411)
        pylab.plot(Ages, Decs)
        pylab.ylabel('Declination ($^{\circ}$)')
        fig.add_subplot(412)
        pylab.plot(Ages, Incs)
        pylab.ylabel('Inclination ($^{\circ}$)')
        fig.add_subplot(413)
        pylab.plot(Ages, Ints)
        pylab.ylabel('Intensity ($\mu$T)')
        fig.add_subplot(414)
        pylab.plot(Ages, VADMs)
        pylab.ylabel('VADMs (ZAm$^2$)')
        pylab.xlabel('Ages')
        if plot == 0:
            pylab.draw()
            ans = input("S[a]ve to save figure, <Return>  to quit  ")
            if ans == 'a':
                pylab.savefig('igrf.' + fmt)
                print('Figure saved as: ', 'igrf.' + fmt)
        else:
            pylab.savefig('igrf.' + fmt)
            print('Figure saved as: ', 'igrf.' + fmt)
        sys.exit()
Beispiel #7
0
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, 'rU')
        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.plotNET(
                EQ['eqarea']
            )  # I don't know why this has to be here, but otherwise the first plot never plots...
            pmagplotlib.drawFIGS(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 critrec.keys():
            # need to migrate specimen_dang to specimen_int_dang for intensity data using old format
            if 'IE-SPEC' in critrec.keys() and 'specimen_dang' in critrec.keys(
            ) and 'specimen_int_dang' not in 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 critrec.keys():
                critrec['sample_int_sigma'] = '%10.3e' % (
                    eval(critrec['sample_int_sigma_uT']) * 1e-6)
            if key not in 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 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 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 rec.keys(): rec['specimen_int'] = ''
        if 'specimen_comp_name' not in 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 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 rec.keys():
            rec["specimen_direction_type"] = 'l'  # assume direction is line - not plane
        if "specimen_dec" not in rec.keys():
            rec["specimen_direction_type"] = ''  # if no declination, set direction type to blank
        if "specimen_n" not in rec.keys(): rec["specimen_n"] = ''  # put in n
        if "specimen_alpha95" not in rec.keys():
            rec["specimen_alpha95"] = ''  # put in alpha95
        if "magic_method_codes" not in 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.plotSITE(EQ['eqarea'], PmagSiteRec,
                                                 siteD,
                                                 key)  # plot and list the data
                            pmagplotlib.drawFIGS(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.plotSITE(EQ['eqarea'], PmagSiteRec, siteD,
                                             key)
                        pmagplotlib.drawFIGS(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 PmagSiteRec.keys(
        ) and 'site_n_planes' in 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 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 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']
                    raw_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 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"
Beispiel #8
0
def main():
    """
    NAME
        igrf.py
    DESCRIPTION
        This program calculates igrf field values 
    using the routine of Malin and  Barraclough (1981) 
    based on d/igrfs from 1900 to 2010.
    between 1900 and 1000BCE, it uses CALS3K.4, ARCH3K.1 
    Prior to 1000BCE, it uses PFM9k or CALS10k-4b
    Calculates reference field vector at  specified location and time.
  
    SYNTAX
       igrf.py [-h] [-i] -f FILE  [< filename]
    OPTIONS:
       -h prints help message and quits
       -i for interactive data entry
       -f FILE  specify file name with input data 
       -fgh FILE specify file with custom field coefficients in format:  l m g h
       -F FILE  specify output file name
       -ages MIN MAX INCR: specify age minimum in years (+/- AD), maximum and increment, default is line by line
       -loc LAT LON;  specify location, default is line by line
       -alt ALT;  specify altitude in km, default is sealevel (0)
       -plt; make a plot of the time series
       -sav, saves plot and quits
       -fmt [pdf,jpg,eps,svg]  specify format for output figure  (default is svg)
       -mod [arch3k,cals3k,pfm9k,hfm10k,cals10k_2,shadif14k,cals10k] specify model for 3ka to 1900 AD, default is cals10k
             NB:  program uses IGRF12 for dates 1900 to 2015.
    
    INPUT FORMAT 
      interactive entry:
           date: decimal year
           alt:  altitude in km
           lat: positive north
           lon: positive east
       for file entry:
           space delimited string: date  alt   lat long
    OUTPUT  FORMAT
        Declination Inclination Intensity (nT) date alt lat long
    MODELS:  ARCH3K: (Korte et al., 2009);CALS3K (Korte & Contable, 2011); CALS10k (is .1b of Korte et al., 2011); PFM9K (Nilsson et al., 2014); HFM10k (is HFM.OL1.A1 of Constable et al., 2016); CALS10k_2 (is cals10k.2 of Constable et al., 2016), SHADIF14k (SHA.DIF.14K of Pavon-Carrasco et al., 2014).
    """
    plot,fmt=0,'svg'
    mod,alt,plt,lat,lon='cals10k',0,0,0,0
    if '-loc' in sys.argv:
        ind=sys.argv.index('-loc')
        lat=float(sys.argv[ind+1])
        lon=float(sys.argv[ind+2])
    if '-alt' in sys.argv:
        ind=sys.argv.index('-alt')
        alt=float(sys.argv[ind+1])
    if '-fmt' in sys.argv:
        ind=sys.argv.index('-fmt')
        fmt=sys.argv[ind+1]
    if len(sys.argv)!=0 and '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    if '-mod' in sys.argv:
        ind=sys.argv.index('-mod')
        mod=sys.argv[ind+1]
    if '-fgh' in sys.argv:
        ind=sys.argv.index('-fgh')
        ghfile=sys.argv[ind+1]
        lmgh=numpy.loadtxt(ghfile)
        gh=[]
        lmgh=numpy.loadtxt(ghfile).transpose()
        gh.append(lmgh[2][0])
        for i in range(1,lmgh.shape[1]):
            gh.append(lmgh[2][i])
            gh.append(lmgh[3][i])
        mod='custom'
        inp=[[0,alt,lat,lon]]
    elif '-f' in sys.argv:
        ind=sys.argv.index('-f')
        file=sys.argv[ind+1]
        inp=numpy.loadtxt(file)
    elif '-i' in sys.argv:
        while 1:
          try:
            line=[]
            if mod!='custom':
                line.append(float(input("Decimal year: <cntrl-D to quit> ")))
            else:
                line.append(0)
            alt=input("Elevation in km [0] ")
            if alt=="":alt="0"
            line.append(float(alt))
            line.append(float(input("Latitude (positive north) ")))
            line.append(float(input("Longitude (positive east) ")))
            if mod=='':
                x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0])
            elif mod=='custom':
                x,y,z,f = pmag.docustom(line[3]%360.,line[2], line[1], gh)
            else:
                x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod=mod)
            Dir=pmag.cart2dir((x,y,z))
            print('%8.2f %8.2f %8.0f'%(Dir[0],Dir[1],f))           
          except EOFError:
            print("\n Good-bye\n")
            sys.exit()
    elif '-ages' in sys.argv:
        ind=sys.argv.index('-ages')
        agemin=float(sys.argv[ind+1])
        agemax=float(sys.argv[ind+2])
        ageincr=float(sys.argv[ind+3])
        ages=numpy.arange(agemin,agemax,ageincr)
        lats=numpy.ones(len(ages))*lat
        lons=numpy.ones(len(ages))*lon
        alts=numpy.ones(len(ages))*alt
        inp=numpy.array([ages,alts,lats,lons]).transpose()
    else:
        inp=numpy.loadtxt(sys.stdin,dtype=numpy.float)
    if '-F' in sys.argv:
        ind=sys.argv.index('-F')
        outfile=sys.argv[ind+1]
        out=open(outfile,'w')
    else:outfile=""
    if '-sav' in sys.argv:plot=1
    if '-plt' in sys.argv:
        plt=1
        import matplotlib
        matplotlib.use("TkAgg")
        import pylab
        pylab.ion()
        Ages,Decs,Incs,Ints,VADMs=[],[],[],[],[]
    for line in inp:
        if mod!='custom':
            x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod=mod)
        else:
            x,y,z,f = pmag.docustom(line[3]%360.,line[2], line[1], gh)
        Dir=pmag.cart2dir((x,y,z))
        if outfile!="":
            out.write('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f\n'%(Dir[0],Dir[1],f,line[0],line[1],line[2],line[3]))           
        elif plt:
            Ages.append(line[0])
            if Dir[0]>180: Dir[0]=Dir[0]-360.0
            Decs.append(Dir[0])
            Incs.append(Dir[1])
            Ints.append(f*1e-3)
            VADMs.append(pmag.b_vdm(f*1e-9,line[2])*1e-21)
        else:
            print('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f'%(Dir[0],Dir[1],f,line[0],line[1],line[2],line[3]))           
    if plt:
        fig=pylab.figure(num=1,figsize=(7,9))
        fig.add_subplot(411)
        pylab.plot(Ages,Decs)
        pylab.ylabel('Declination ($^{\circ}$)')
        fig.add_subplot(412)
        pylab.plot(Ages,Incs)
        pylab.ylabel('Inclination ($^{\circ}$)')
        fig.add_subplot(413)
        pylab.plot(Ages,Ints)
        pylab.ylabel('Intensity ($\mu$T)')
        fig.add_subplot(414)
        pylab.plot(Ages,VADMs)
        pylab.ylabel('VADMs (ZAm$^2$)')
        pylab.xlabel('Ages')
        if plot==0:
            pylab.draw()
            ans=input("S[a]ve to save figure, <Return>  to quit  ")
            if ans=='a':
                pylab.savefig('igrf.'+fmt)
                print('Figure saved as: ','igrf.'+fmt)
        else: 
            pylab.savefig('igrf.'+fmt)
            print('Figure saved as: ','igrf.'+fmt)
        sys.exit()
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.plotNET(EQ['eqarea']) # I don't know why this has to be here, but otherwise the first plot never plots...
            pmagplotlib.drawFIGS(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.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key) # plot and list the data
                            pmagplotlib.drawFIGS(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.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key)
                        pmagplotlib.drawFIGS(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")