Esempio n. 1
0
def main():
    """
    NAME
        eqarea_magic.py

    DESCRIPTION
       makes equal area projections from declination/inclination data

    SYNTAX 
        eqarea_magic.py [command line options]
    
    INPUT 
       takes magic formatted pmag_results, pmag_sites, pmag_samples or pmag_specimens
    
    OPTIONS
        -h prints help message and quits
        -f FILE: specify input magic format file from magic,default='pmag_results.txt'
         supported types=[magic_measurements,pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
        -obj OBJ: specify  level of plot  [all, sit, sam, spc], default is all
        -crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
                default is geographic, unspecified assumed geographic
        -fmt [svg,png,jpg] format for output plots
        -ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
        -c plot as colour contour 
        -sav save plot and quit quietly
    NOTE
        all: entire file; sit: site; sam: sample; spc: specimen
    """
    FIG = {} # plot dictionary
    FIG['eqarea'] = 1 # eqarea is figure 1
    in_file, plot_key, coord, crd = 'pmag_results.txt', 'all', "0", 'g'
    plotE, contour = 0, 0
    dir_path = '.'
    fmt = 'svg'
    verbose = pmagplotlib.verbose
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-WD' in sys.argv:
        ind = sys.argv.index('-WD')
        dir_path = sys.argv[ind + 1]
    pmagplotlib.plot_init(FIG['eqarea'], 5, 5)
    if '-f' in sys.argv:
        ind = sys.argv.index("-f")
        in_file = dir_path + "/" + sys.argv[ind + 1]
    if '-obj' in sys.argv:
        ind = sys.argv.index('-obj')
        plot_by = sys.argv[ind + 1]
        if plot_by == 'all': plot_key = 'all'
        if plot_by == 'sit': plot_key = 'er_site_name'
        if plot_by == 'sam': plot_key = 'er_sample_name'
        if plot_by == 'spc': plot_key = 'er_specimen_name'
    if '-c' in sys.argv: contour = 1
    plots = 0
    if '-sav' in sys.argv:
        plots = 1
        verbose = 0
    if '-ell' in sys.argv:
        plotE = 1
        ind = sys.argv.index('-ell')
        ell_type = sys.argv[ind + 1]
        if ell_type == 'F': dist = 'F'
        if ell_type == 'K': dist = 'K'
        if ell_type == 'B': dist = 'B'
        if ell_type == 'Be': dist = 'BE'
        if ell_type == 'Bv':
            dist = 'BV'
            FIG['bdirs'] = 2
            pmagplotlib.plot_init(FIG['bdirs'], 5, 5)
    if '-crd' in sys.argv:
        ind = sys.argv.index("-crd")
        crd = sys.argv[ind + 1]
        if crd == 's': coord = "-1"
        if crd == 'g': coord = "0"
        if crd == 't': coord = "100"
    if '-fmt' in sys.argv:
        ind = sys.argv.index("-fmt")
        fmt = sys.argv[ind + 1]
    Dec_keys = ['site_dec', 'sample_dec', 'specimen_dec', 'measurement_dec', 'average_dec', 'none']
    Inc_keys = ['site_inc', 'sample_inc', 'specimen_inc', 'measurement_inc', 'average_inc', 'none']
    Tilt_keys = ['tilt_correction', 'site_tilt_correction', 'sample_tilt_correction', 'specimen_tilt_correction',
                 'none']
    Dir_type_keys = ['', 'site_direction_type', 'sample_direction_type', 'specimen_direction_type']
    Name_keys = ['er_specimen_name', 'er_sample_name', 'er_site_name', 'pmag_result_name']
    data, file_type = pmag.magic_read(in_file)
    if file_type == 'pmag_results' and plot_key != "all": plot_key = plot_key + 's' # need plural for results table
    if verbose:
        print len(data), ' records read from ', in_file
        #
    #
    # find desired dec,inc data:
    #
    dir_type_key = ''
    #
    # get plotlist if not plotting all records
    #
    plotlist = []
    if plot_key != "all":
        plots = pmag.get_dictitem(data, plot_key, '', 'F')
        for rec in plots:
            if rec[plot_key] not in plotlist:
                plotlist.append(rec[plot_key])
        plotlist.sort()
    else:
        plotlist.append('All')
    for plot in plotlist:
        if verbose: print plot
        DIblock = []
        GCblock = []
        SLblock, SPblock = [], []
        title = plot
        mode = 1
        dec_key, inc_key, tilt_key, name_key, k = "", "", "", "", 0
        if plot != "All":
            odata = pmag.get_dictitem(data, plot_key, plot, 'T')
        else:
            odata = data # data for this obj
        for dec_key in Dec_keys:
            Decs = pmag.get_dictitem(odata, dec_key, '', 'F') # get all records with this dec_key not blank
            if len(Decs) > 0: break
        for inc_key in Inc_keys:
            Incs = pmag.get_dictitem(Decs, inc_key, '', 'F') # get all records with this inc_key not blank
            if len(Incs) > 0: break
        for tilt_key in Tilt_keys:
            if tilt_key in Incs[0].keys(): break # find the tilt_key for these records
        if tilt_key == 'none': # no tilt key in data, need to fix this with fake data which will be unknown tilt
            tilt_key = 'tilt_correction'
            for rec in Incs: rec[tilt_key] = ''
        cdata = pmag.get_dictitem(Incs, tilt_key, coord, 'T') # get all records matching specified coordinate system
        if coord == '0': # geographic
            udata = pmag.get_dictitem(Incs, tilt_key, '', 'T') # get all the blank records - assume geographic
            if len(cdata) == 0: crd = ''
            if len(udata) > 0:
                for d in udata: cdata.append(d)
                crd = crd + 'u'
        for name_key in Name_keys:
            Names = pmag.get_dictitem(cdata, name_key, '', 'F') # get all records with this name_key not blank
            if len(Names) > 0: break
        for dir_type_key in Dir_type_keys:
            Dirs = pmag.get_dictitem(cdata, dir_type_key, '', 'F') # get all records with this direction type
            if len(Dirs) > 0: break
        if dir_type_key == "": dir_type_key = 'direction_type'
        locations, site, sample, specimen = "", "", "", ""
        for rec in cdata: # pick out the data
            if 'er_location_name' in rec.keys() and rec['er_location_name'] != "" and rec[
                'er_location_name'] not in locations: locations = locations + rec['er_location_name'].replace("/",
                                                                                                              "") + "_"
            if 'er_location_names' in rec.keys() and rec['er_location_names'] != "":
                locs = rec['er_location_names'].split(':')
                for loc in locs:
                    if loc not in locations: locations = locations + loc.replace("/", "") + '_'
            if plot_key == 'er_site_name' or plot_key == 'er_sample_name' or plot_key == 'er_specimen_name':
                site = rec['er_site_name']
            if plot_key == 'er_sample_name' or plot_key == 'er_specimen_name':
                sample = rec['er_sample_name']
            if plot_key == 'er_specimen_name':
                specimen = rec['er_specimen_name']
            if plot_key == 'er_site_names' or plot_key == 'er_sample_names' or plot_key == 'er_specimen_names':
                site = rec['er_site_names']
            if plot_key == 'er_sample_names' or plot_key == 'er_specimen_names':
                sample = rec['er_sample_names']
            if plot_key == 'er_specimen_names':
                specimen = rec['er_specimen_names']
            if dir_type_key not in rec.keys() or rec[dir_type_key] == "": rec[dir_type_key] = 'l'
            if 'magic_method_codes' not in rec.keys(): rec['magic_method_codes'] = ""
            DIblock.append([float(rec[dec_key]), float(rec[inc_key])])
            SLblock.append([rec[name_key], rec['magic_method_codes']])
            if rec[tilt_key] == coord and rec[dir_type_key] != 'l' and rec[dec_key] != "" and rec[inc_key] != "":
                GCblock.append([float(rec[dec_key]), float(rec[inc_key])])
                SPblock.append([rec[name_key], rec['magic_method_codes']])
        if len(DIblock) == 0 and len(GCblock) == 0:
            if verbose: print "no records for plotting"
            sys.exit()
        if verbose:
            for k in range(len(SLblock)):
                print '%s %s %7.1f %7.1f' % (SLblock[k][0], SLblock[k][1], DIblock[k][0], DIblock[k][1])
            for k in range(len(SPblock)):
                print '%s %s %7.1f %7.1f' % (SPblock[k][0], SPblock[k][1], GCblock[k][0], GCblock[k][1])
        if len(DIblock) > 0:
            if contour == 0:
                pmagplotlib.plotEQ(FIG['eqarea'], DIblock, title)
            else:
                pmagplotlib.plotEQcont(FIG['eqarea'], DIblock)
        else:
            pmagplotlib.plotNET(FIG['eqarea'])
        if len(GCblock) > 0:
            for rec in GCblock: pmagplotlib.plotC(FIG['eqarea'], rec, 90., 'g')
        if plotE == 1:
            ppars = pmag.doprinc(DIblock) # get principal directions
            nDIs, rDIs, npars, rpars = [], [], [], []
            for rec in DIblock:
                angle = pmag.angle([rec[0], rec[1]], [ppars['dec'], ppars['inc']])
                if angle > 90.:
                    rDIs.append(rec)
                else:
                    nDIs.append(rec)
            if dist == 'B': # do on whole dataset
                etitle = "Bingham confidence ellipse"
                bpars = pmag.dobingham(DIblock)
                for key in bpars.keys():
                    if key != 'n' and verbose: print "    ", key, '%7.1f' % (bpars[key])
                    if key == 'n' and verbose: print "    ", key, '       %i' % (bpars[key])
                npars.append(bpars['dec'])
                npars.append(bpars['inc'])
                npars.append(bpars['Zeta'])
                npars.append(bpars['Zdec'])
                npars.append(bpars['Zinc'])
                npars.append(bpars['Eta'])
                npars.append(bpars['Edec'])
                npars.append(bpars['Einc'])
            if dist == 'F':
                etitle = "Fisher confidence cone"
                if len(nDIs) > 2:
                    fpars = pmag.fisher_mean(nDIs)
                    for key in fpars.keys():
                        if key != 'n' and verbose: print "    ", key, '%7.1f' % (fpars[key])
                        if key == 'n' and verbose: print "    ", key, '       %i' % (fpars[key])
                    mode += 1
                    npars.append(fpars['dec'])
                    npars.append(fpars['inc'])
                    npars.append(fpars['alpha95']) # Beta
                    npars.append(fpars['dec'])
                    isign = abs(fpars['inc']) / fpars['inc']
                    npars.append(fpars['inc'] - isign * 90.) #Beta inc
                    npars.append(fpars['alpha95']) # gamma 
                    npars.append(fpars['dec'] + 90.) # Beta dec
                    npars.append(0.) #Beta inc
                if len(rDIs) > 2:
                    fpars = pmag.fisher_mean(rDIs)
                    if verbose: print "mode ", mode
                    for key in fpars.keys():
                        if key != 'n' and verbose: print "    ", key, '%7.1f' % (fpars[key])
                        if key == 'n' and verbose: print "    ", key, '       %i' % (fpars[key])
                    mode += 1
                    rpars.append(fpars['dec'])
                    rpars.append(fpars['inc'])
                    rpars.append(fpars['alpha95']) # Beta
                    rpars.append(fpars['dec'])
                    isign = abs(fpars['inc']) / fpars['inc']
                    rpars.append(fpars['inc'] - isign * 90.) #Beta inc
                    rpars.append(fpars['alpha95']) # gamma 
                    rpars.append(fpars['dec'] + 90.) # Beta dec
                    rpars.append(0.) #Beta inc
            if dist == 'K':
                etitle = "Kent confidence ellipse"
                if len(nDIs) > 3:
                    kpars = pmag.dokent(nDIs, len(nDIs))
                    if verbose: print "mode ", mode
                    for key in kpars.keys():
                        if key != 'n' and verbose: print "    ", key, '%7.1f' % (kpars[key])
                        if key == 'n' and verbose: print "    ", key, '       %i' % (kpars[key])
                    mode += 1
                    npars.append(kpars['dec'])
                    npars.append(kpars['inc'])
                    npars.append(kpars['Zeta'])
                    npars.append(kpars['Zdec'])
                    npars.append(kpars['Zinc'])
                    npars.append(kpars['Eta'])
                    npars.append(kpars['Edec'])
                    npars.append(kpars['Einc'])
                if len(rDIs) > 3:
                    kpars = pmag.dokent(rDIs, len(rDIs))
                    if verbose: print "mode ", mode
                    for key in kpars.keys():
                        if key != 'n' and verbose: print "    ", key, '%7.1f' % (kpars[key])
                        if key == 'n' and verbose: print "    ", key, '       %i' % (kpars[key])
                    mode += 1
                    rpars.append(kpars['dec'])
                    rpars.append(kpars['inc'])
                    rpars.append(kpars['Zeta'])
                    rpars.append(kpars['Zdec'])
                    rpars.append(kpars['Zinc'])
                    rpars.append(kpars['Eta'])
                    rpars.append(kpars['Edec'])
                    rpars.append(kpars['Einc'])
            else: # assume bootstrap
                if dist == 'BE':
                    if len(nDIs) > 5:
                        BnDIs = pmag.di_boot(nDIs)
                        Bkpars = pmag.dokent(BnDIs, 1.)
                        if verbose: print "mode ", mode
                        for key in Bkpars.keys():
                            if key != 'n' and verbose: print "    ", key, '%7.1f' % (Bkpars[key])
                            if key == 'n' and verbose: print "    ", key, '       %i' % (Bkpars[key])
                        mode += 1
                        npars.append(Bkpars['dec'])
                        npars.append(Bkpars['inc'])
                        npars.append(Bkpars['Zeta'])
                        npars.append(Bkpars['Zdec'])
                        npars.append(Bkpars['Zinc'])
                        npars.append(Bkpars['Eta'])
                        npars.append(Bkpars['Edec'])
                        npars.append(Bkpars['Einc'])
                    if len(rDIs) > 5:
                        BrDIs = pmag.di_boot(rDIs)
                        Bkpars = pmag.dokent(BrDIs, 1.)
                        if verbose: print "mode ", mode
                        for key in Bkpars.keys():
                            if key != 'n' and verbose: print "    ", key, '%7.1f' % (Bkpars[key])
                            if key == 'n' and verbose: print "    ", key, '       %i' % (Bkpars[key])
                        mode += 1
                        rpars.append(Bkpars['dec'])
                        rpars.append(Bkpars['inc'])
                        rpars.append(Bkpars['Zeta'])
                        rpars.append(Bkpars['Zdec'])
                        rpars.append(Bkpars['Zinc'])
                        rpars.append(Bkpars['Eta'])
                        rpars.append(Bkpars['Edec'])
                        rpars.append(Bkpars['Einc'])
                    etitle = "Bootstrapped confidence ellipse"
                elif dist == 'BV':
                    sym = {'lower': ['o', 'c'], 'upper': ['o', 'g'], 'size': 3, 'edgecolor': 'face'}
                    if len(nDIs) > 5:
                        BnDIs = pmag.di_boot(nDIs)
                        pmagplotlib.plotEQsym(FIG['bdirs'], BnDIs, 'Bootstrapped Eigenvectors', sym)
                    if len(rDIs) > 5:
                        BrDIs = pmag.di_boot(rDIs)
                        if len(nDIs) > 5:  # plot on existing plots
                            pmagplotlib.plotDIsym(FIG['bdirs'], BrDIs, sym)
                        else:
                            pmagplotlib.plotEQ(FIG['bdirs'], BrDIs, 'Bootstrapped Eigenvectors')
            if dist == 'B':
                if len(nDIs) > 3 or len(rDIs) > 3: pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], npars, 0)
            elif len(nDIs) > 3 and dist != 'BV':
                pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], npars, 0)
                if len(rDIs) > 3:
                    pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], rpars, 0)
            elif len(rDIs) > 3 and dist != 'BV':
                pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], rpars, 0)
        if verbose: pmagplotlib.drawFIGS(FIG)
        #
        files = {}
        locations = locations[:-1]
        for key in FIG.keys():
            filename = 'LO:_' + locations + '_SI:_' + site + '_SA:_' + sample + '_SP:_' + specimen + '_CO:_' + crd + '_TY:_' + key + '_.' + fmt
            files[key] = filename
        if pmagplotlib.isServer:
            black = '#000000'
            purple = '#800080'
            titles = {}
            titles['eq'] = 'Equal Area Plot'
            FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
            pmagplotlib.saveP(FIG, files)
        elif verbose:
            ans = raw_input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
            if ans == "q": sys.exit()
            if ans == "a":
                pmagplotlib.saveP(FIG, files)
        if plots:
            pmagplotlib.saveP(FIG, files)
Esempio n. 2
0
def main():
    """
    NAME
       plotdi_e.py

    DESCRIPTION
       plots equal area projection  from dec inc data and cones of confidence 
           (Fisher, kent or Bingham or bootstrap).

    INPUT FORMAT
       takes dec/inc as first two columns in space delimited file

    SYNTAX
       plotdi_e.py [command line options]

    OPTIONS
        -h prints help message and quits
        -i for interactive parameter entry
        -f FILE, sets input filename on command line 
        -Fish plots unit vector mean direction, alpha95
        -Bing plots Principal direction, Bingham confidence ellipse
        -Kent plots unit vector mean direction, confidence ellipse
        -Boot E plots unit vector mean direction, bootstrapped confidence ellipse
        -Boot V plots  unit vector mean direction, distribution of bootstrapped means

    """
    dist='F' # default distribution is Fisherian
    mode=1
    EQ={'eq':1}
    if len(sys.argv) > 0:
        if '-h' in sys.argv: # check if help is needed
            print main.__doc__
            sys.exit() # graceful quit
        if '-i' in sys.argv: # ask for filename
            file=raw_input("Enter file name with dec, inc data: ")
            dist=raw_input("Enter desired distrubution: [Fish]er, [Bing]ham, [Kent] [Boot] [default is Fisher]: ")
            if dist=="":dist="F"
            if dist=="Boot":
                 type=raw_input(" Ellipses or distribution of vectors? [E]/V ")
                 if type=="" or type=="E":
                     dist="BE"
                 else:
                     dist="BE"
        else:
#
            if '-f' in sys.argv:
                ind=sys.argv.index('-f')
                file=sys.argv[ind+1]
            else:
                print 'you must specify a file name'
                print main.__doc__
                sys.exit()
            if '-Bing' in sys.argv:dist='B'
            if '-Kent' in sys.argv:dist='K'
            if '-Boot' in sys.argv:
                ind=sys.argv.index('-Boot')
                type=sys.argv[ind+1]
                if type=='E': 
                    dist='BE'
                elif type=='V': 
                    dist='BV'
                    EQ['bdirs']=2
                    pmagplotlib.plot_init(EQ['bdirs'],5,5)
                else:
                    print main.__doc__
                    sys.exit()
    pmagplotlib.plot_init(EQ['eq'],5,5)
#
# get to work
    f=open(file,'r')
    data=f.readlines()
#
    DIs= [] # set up list for dec inc data
    DiRecs=[]
    pars=[]
    nDIs,rDIs,npars,rpars=[],[],[],[]
    mode =1
    for line in data:   # read in the data from standard input
        DiRec={}
        rec=line.split() # split each line on space to get records
        DIs.append((float(rec[0]),float(rec[1]),1.))
        DiRec['dec']=rec[0]
        DiRec['inc']=rec[1]
        DiRec['direction_type']='l'
        DiRecs.append(DiRec)
    # split into two modes
    ppars=pmag.doprinc(DIs) # get principal directions
    for rec in DIs:
        angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
        if angle>90.:
            rDIs.append(rec)
        else:
            nDIs.append(rec)
    if dist=='B': # do on whole dataset
        title="Bingham confidence ellipse"
        bpars=pmag.dobingham(DIs)
        for key in bpars.keys():
            if key!='n':print "    ",key, '%7.1f'%(bpars[key])
            if key=='n':print "    ",key, '       %i'%(bpars[key])
        npars.append(bpars['dec']) 
        npars.append(bpars['inc'])
        npars.append(bpars['Zeta']) 
        npars.append(bpars['Zdec']) 
        npars.append(bpars['Zinc'])
        npars.append(bpars['Eta']) 
        npars.append(bpars['Edec']) 
        npars.append(bpars['Einc'])
    if dist=='F':
        title="Fisher confidence cone"
        if len(nDIs)>3:
            fpars=pmag.fisher_mean(nDIs)
            print "mode ",mode
            for key in fpars.keys():
                if key!='n':print "    ",key, '%7.1f'%(fpars[key])
                if key=='n':print "    ",key, '       %i'%(fpars[key])
            mode+=1
            npars.append(fpars['dec']) 
            npars.append(fpars['inc'])
            npars.append(fpars['alpha95']) # Beta
            npars.append(fpars['dec']) 
            isign=abs(fpars['inc'])/fpars['inc'] 
            npars.append(fpars['inc']-isign*90.) #Beta inc
            npars.append(fpars['alpha95']) # gamma 
            npars.append(fpars['dec']+90.) # Beta dec
            npars.append(0.) #Beta inc
        if len(rDIs)>3:
            fpars=pmag.fisher_mean(rDIs)
            print "mode ",mode
            for key in fpars.keys():
                if key!='n':print "    ",key, '%7.1f'%(fpars[key])
                if key=='n':print "    ",key, '       %i'%(fpars[key])
            mode+=1
            rpars.append(fpars['dec']) 
            rpars.append(fpars['inc'])
            rpars.append(fpars['alpha95']) # Beta
            rpars.append(fpars['dec']) 
            isign=abs(fpars['inc'])/fpars['inc'] 
            rpars.append(fpars['inc']-isign*90.) #Beta inc
            rpars.append(fpars['alpha95']) # gamma 
            rpars.append(fpars['dec']+90.) # Beta dec
            rpars.append(0.) #Beta inc
    if dist=='K':
        title="Kent confidence ellipse"
        if len(nDIs)>3:
            kpars=pmag.dokent(nDIs,len(nDIs))
            print "mode ",mode
            for key in kpars.keys():
                if key!='n':print "    ",key, '%7.1f'%(kpars[key])
                if key=='n':print "    ",key, '       %i'%(kpars[key])
            mode+=1
            npars.append(kpars['dec']) 
            npars.append(kpars['inc'])
            npars.append(kpars['Zeta']) 
            npars.append(kpars['Zdec']) 
            npars.append(kpars['Zinc'])
            npars.append(kpars['Eta']) 
            npars.append(kpars['Edec']) 
            npars.append(kpars['Einc'])
        if len(rDIs)>3:
            kpars=pmag.dokent(rDIs,len(rDIs))
            print "mode ",mode
            for key in kpars.keys():
                if key!='n':print "    ",key, '%7.1f'%(kpars[key])
                if key=='n':print "    ",key, '       %i'%(kpars[key])
            mode+=1
            rpars.append(kpars['dec']) 
            rpars.append(kpars['inc'])
            rpars.append(kpars['Zeta']) 
            rpars.append(kpars['Zdec']) 
            rpars.append(kpars['Zinc'])
            rpars.append(kpars['Eta']) 
            rpars.append(kpars['Edec']) 
            rpars.append(kpars['Einc'])
    else: # assume bootstrap
        if dist=='BE':
            if len(nDIs)>5:
                BnDIs=pmag.di_boot(nDIs)
                Bkpars=pmag.dokent(BnDIs,1.)
                print "mode ",mode
                for key in Bkpars.keys():
                    if key!='n':print "    ",key, '%7.1f'%(Bkpars[key])
                    if key=='n':print "    ",key, '       %i'%(Bkpars[key])
                mode+=1
                npars.append(Bkpars['dec']) 
                npars.append(Bkpars['inc'])
                npars.append(Bkpars['Zeta']) 
                npars.append(Bkpars['Zdec']) 
                npars.append(Bkpars['Zinc'])
                npars.append(Bkpars['Eta']) 
                npars.append(Bkpars['Edec']) 
                npars.append(Bkpars['Einc'])
            if len(rDIs)>5:
                BrDIs=pmag.di_boot(rDIs)
                Bkpars=pmag.dokent(BrDIs,1.)
                print "mode ",mode
                for key in Bkpars.keys():
                    if key!='n':print "    ",key, '%7.1f'%(Bkpars[key])
                    if key=='n':print "    ",key, '       %i'%(Bkpars[key])
                mode+=1
                rpars.append(Bkpars['dec']) 
                rpars.append(Bkpars['inc'])
                rpars.append(Bkpars['Zeta']) 
                rpars.append(Bkpars['Zdec']) 
                rpars.append(Bkpars['Zinc'])
                rpars.append(Bkpars['Eta']) 
                rpars.append(Bkpars['Edec']) 
                rpars.append(Bkpars['Einc'])
            title="Bootstrapped confidence ellipse"
        elif dist=='BV':
            if len(nDIs)>5:
                pmagplotlib.plotEQ(EQ['eq'],nDIs,'Data')
                BnDIs=pmag.di_boot(nDIs)
                pmagplotlib.plotEQ(EQ['bdirs'],BnDIs,'Bootstrapped Eigenvectors')
            if len(rDIs)>5:
                BrDIs=pmag.di_boot(rDIs)
                if len(nDIs)>5:  # plot on existing plots
                    pmagplotlib.plotDI(EQ['eq'],rDIs)
                    pmagplotlib.plotDI(EQ['bdirs'],BrDIs)
                else:
                    pmagplotlib.plotEQ(EQ['eq'],rDIs,'Data')
                    pmagplotlib.plotEQ(EQ['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
            pmagplotlib.drawFIGS(EQ)
            ans=raw_input('s[a]ve, [q]uit ')
            if ans=='q':sys.exit()
            if ans=='a':
                files={}
                for key in EQ.keys():
                    files[key]='BE_'+key+'.svg'
                pmagplotlib.saveP(EQ,files)
            sys.exit() 
    if len(nDIs)>5:
        pmagplotlib.plotCONF(EQ['eq'],title,DiRecs,npars,1)
        if len(rDIs)>5 and dist!='B': 
            pmagplotlib.plotCONF(EQ['eq'],title,[],rpars,0)
    elif len(rDIs)>5 and dist!='B': 
        pmagplotlib.plotCONF(EQ['eq'],title,DiRecs,rpars,1)
    pmagplotlib.drawFIGS(EQ)
    ans=raw_input('s[a]ve, [q]uit ')
    if ans=='q':sys.exit()
    if ans=='a':
        files={}
        for key in EQ.keys():
            files[key]=key+'.svg'
        pmagplotlib.saveP(EQ,files)
Esempio n. 3
0
def main():
    """
    NAME
        eqarea_ell.py

    DESCRIPTION
       makes equal area projections from declination/inclination data
       and plot ellipses

    SYNTAX 
        eqarea_ell.py -h [command line options]
    
    INPUT 
       takes space delimited Dec/Inc data
    
    OPTIONS
        -h prints help message and quits
        -f FILE
        -fmt [svg,png,jpg] format for output plots
        -ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
    """
    FIG = {}  # plot dictionary
    FIG["eq"] = 1  # eqarea is figure 1
    fmt, dist, mode = "svg", "F", 1
    plotE = 0
    if "-h" in sys.argv:
        print main.__doc__
        sys.exit()
    pmagplotlib.plot_init(FIG["eq"], 5, 5)
    if "-f" in sys.argv:
        ind = sys.argv.index("-f")
        title = sys.argv[ind + 1]
        f = open(title, "rU")
        data = f.readlines()
    if "-ell" in sys.argv:
        plotE = 1
        ind = sys.argv.index("-ell")
        ell_type = sys.argv[ind + 1]
        if ell_type == "F":
            dist = "F"
        if ell_type == "K":
            dist = "K"
        if ell_type == "B":
            dist = "B"
        if ell_type == "Be":
            dist = "BE"
        if ell_type == "Bv":
            dist = "BV"
            FIG["bdirs"] = 2
            pmagplotlib.plot_init(FIG["bdirs"], 5, 5)
    if "-fmt" in sys.argv:
        ind = sys.argv.index("-fmt")
        fmt = sys.argv[ind + 1]
    DIblock = []
    for line in data:
        if "\t" in line:
            rec = line.split("\t")  # split each line on space to get records
        else:
            rec = line.split()  # split each line on space to get records
        DIblock.append([float(rec[0]), float(rec[1])])
    if len(DIblock) > 0:
        pmagplotlib.plotEQ(FIG["eq"], DIblock, title)
    else:
        print "no data to plot"
        sys.exit()
    if plotE == 1:
        ppars = pmag.doprinc(DIblock)  # get principal directions
        nDIs, rDIs, npars, rpars = [], [], [], []
        for rec in DIblock:
            angle = pmag.angle([rec[0], rec[1]], [ppars["dec"], ppars["inc"]])
            if angle > 90.0:
                rDIs.append(rec)
            else:
                nDIs.append(rec)
        if dist == "B":  # do on whole dataset
            etitle = "Bingham confidence ellipse"
            bpars = pmag.dobingham(DIblock)
            for key in bpars.keys():
                if key != "n" and pmagplotlib.verbose:
                    print "    ", key, "%7.1f" % (bpars[key])
                if key == "n" and pmagplotlib.verbose:
                    print "    ", key, "       %i" % (bpars[key])
            npars.append(bpars["dec"])
            npars.append(bpars["inc"])
            npars.append(bpars["Zeta"])
            npars.append(bpars["Zdec"])
            npars.append(bpars["Zinc"])
            npars.append(bpars["Eta"])
            npars.append(bpars["Edec"])
            npars.append(bpars["Einc"])
        if dist == "F":
            etitle = "Fisher confidence cone"
            if len(nDIs) > 3:
                fpars = pmag.fisher_mean(nDIs)
                for key in fpars.keys():
                    if key != "n" and pmagplotlib.verbose:
                        print "    ", key, "%7.1f" % (fpars[key])
                    if key == "n" and pmagplotlib.verbose:
                        print "    ", key, "       %i" % (fpars[key])
                mode += 1
                npars.append(fpars["dec"])
                npars.append(fpars["inc"])
                npars.append(fpars["alpha95"])  # Beta
                npars.append(fpars["dec"])
                isign = abs(fpars["inc"]) / fpars["inc"]
                npars.append(fpars["inc"] - isign * 90.0)  # Beta inc
                npars.append(fpars["alpha95"])  # gamma
                npars.append(fpars["dec"] + 90.0)  # Beta dec
                npars.append(0.0)  # Beta inc
            if len(rDIs) > 3:
                fpars = pmag.fisher_mean(rDIs)
                if pmagplotlib.verbose:
                    print "mode ", mode
                for key in fpars.keys():
                    if key != "n" and pmagplotlib.verbose:
                        print "    ", key, "%7.1f" % (fpars[key])
                    if key == "n" and pmagplotlib.verbose:
                        print "    ", key, "       %i" % (fpars[key])
                mode += 1
                rpars.append(fpars["dec"])
                rpars.append(fpars["inc"])
                rpars.append(fpars["alpha95"])  # Beta
                rpars.append(fpars["dec"])
                isign = abs(fpars["inc"]) / fpars["inc"]
                rpars.append(fpars["inc"] - isign * 90.0)  # Beta inc
                rpars.append(fpars["alpha95"])  # gamma
                rpars.append(fpars["dec"] + 90.0)  # Beta dec
                rpars.append(0.0)  # Beta inc
        if dist == "K":
            etitle = "Kent confidence ellipse"
            if len(nDIs) > 3:
                kpars = pmag.dokent(nDIs, len(nDIs))
                if pmagplotlib.verbose:
                    print "mode ", mode
                for key in kpars.keys():
                    if key != "n" and pmagplotlib.verbose:
                        print "    ", key, "%7.1f" % (kpars[key])
                    if key == "n" and pmagplotlib.verbose:
                        print "    ", key, "       %i" % (kpars[key])
                mode += 1
                npars.append(kpars["dec"])
                npars.append(kpars["inc"])
                npars.append(kpars["Zeta"])
                npars.append(kpars["Zdec"])
                npars.append(kpars["Zinc"])
                npars.append(kpars["Eta"])
                npars.append(kpars["Edec"])
                npars.append(kpars["Einc"])
            if len(rDIs) > 3:
                kpars = pmag.dokent(rDIs, len(rDIs))
                if pmagplotlib.verbose:
                    print "mode ", mode
                for key in kpars.keys():
                    if key != "n" and pmagplotlib.verbose:
                        print "    ", key, "%7.1f" % (kpars[key])
                    if key == "n" and pmagplotlib.verbose:
                        print "    ", key, "       %i" % (kpars[key])
                mode += 1
                rpars.append(kpars["dec"])
                rpars.append(kpars["inc"])
                rpars.append(kpars["Zeta"])
                rpars.append(kpars["Zdec"])
                rpars.append(kpars["Zinc"])
                rpars.append(kpars["Eta"])
                rpars.append(kpars["Edec"])
                rpars.append(kpars["Einc"])
        else:  # assume bootstrap
            if len(nDIs) < 10 and len(rDIs) < 10:
                print "too few data points for bootstrap"
                sys.exit()
            if dist == "BE":
                if len(nDIs) >= 10:
                    BnDIs = pmag.di_boot(nDIs)
                    Bkpars = pmag.dokent(BnDIs, 1.0)
                    if pmagplotlib.verbose:
                        print "mode ", mode
                    for key in Bkpars.keys():
                        if key != "n" and pmagplotlib.verbose:
                            print "    ", key, "%7.1f" % (Bkpars[key])
                        if key == "n" and pmagplotlib.verbose:
                            print "    ", key, "       %i" % (Bkpars[key])
                    mode += 1
                    npars.append(Bkpars["dec"])
                    npars.append(Bkpars["inc"])
                    npars.append(Bkpars["Zeta"])
                    npars.append(Bkpars["Zdec"])
                    npars.append(Bkpars["Zinc"])
                    npars.append(Bkpars["Eta"])
                    npars.append(Bkpars["Edec"])
                    npars.append(Bkpars["Einc"])
                if len(rDIs) >= 10:
                    BrDIs = pmag.di_boot(rDIs)
                    Bkpars = pmag.dokent(BrDIs, 1.0)
                    if pmagplotlib.verbose:
                        print "mode ", mode
                    for key in Bkpars.keys():
                        if key != "n" and pmagplotlib.verbose:
                            print "    ", key, "%7.1f" % (Bkpars[key])
                        if key == "n" and pmagplotlib.verbose:
                            print "    ", key, "       %i" % (Bkpars[key])
                    mode += 1
                    rpars.append(Bkpars["dec"])
                    rpars.append(Bkpars["inc"])
                    rpars.append(Bkpars["Zeta"])
                    rpars.append(Bkpars["Zdec"])
                    rpars.append(Bkpars["Zinc"])
                    rpars.append(Bkpars["Eta"])
                    rpars.append(Bkpars["Edec"])
                    rpars.append(Bkpars["Einc"])
                etitle = "Bootstrapped confidence ellipse"
            elif dist == "BV":
                vsym = {"lower": ["+", "k"], "upper": ["x", "k"], "size": 5}
                if len(nDIs) > 5:
                    BnDIs = pmag.di_boot(nDIs)
                    pmagplotlib.plotEQsym(FIG["bdirs"], BnDIs, "Bootstrapped Eigenvectors", vsym)
                if len(rDIs) > 5:
                    BrDIs = pmag.di_boot(rDIs)
                    if len(nDIs) > 5:  # plot on existing plots
                        pmagplotlib.plotDIsym(FIG["bdirs"], BrDIs, vsym)
                    else:
                        pmagplotlib.plotEQ(FIG["bdirs"], BrDIs, "Bootstrapped Eigenvectors", vsym)
        if dist == "B":
            if len(nDIs) > 3 or len(rDIs) > 3:
                pmagplotlib.plotCONF(FIG["eq"], etitle, [], npars, 0)
        elif len(nDIs) > 3 and dist != "BV":
            pmagplotlib.plotCONF(FIG["eq"], etitle, [], npars, 0)
            if len(rDIs) > 3:
                pmagplotlib.plotCONF(FIG["eq"], etitle, [], rpars, 0)
        elif len(rDIs) > 3 and dist != "BV":
            pmagplotlib.plotCONF(FIG["eq"], etitle, [], rpars, 0)
    pmagplotlib.drawFIGS(FIG)
    #
    files = {}
    for key in FIG.keys():
        files[key] = title + "_" + key + "." + fmt
    if pmagplotlib.isServer:
        black = "#000000"
        purple = "#800080"
        titles = {}
        titles["eq"] = "Equal Area Plot"
        FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
        pmagplotlib.saveP(FIG, files)
    else:
        ans = raw_input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
        if ans == "q":
            sys.exit()
        if ans == "a":
            pmagplotlib.saveP(FIG, files)
def main():
    """
    NAME
        eqarea_ell.py

    DESCRIPTION
       makes equal area projections from declination/inclination data
       and plot ellipses

    SYNTAX 
        eqarea_ell.py -h [command line options]
    
    INPUT 
       takes space delimited Dec/Inc data
    
    OPTIONS
        -h prints help message and quits
        -f FILE
        -fmt [svg,png,jpg] format for output plots
        -sav  saves figures and quits
        -ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
    """
    FIG={} # plot dictionary
    FIG['eq']=1 # eqarea is figure 1
    fmt,dist,mode,plot='svg','F',1,0
    sym={'lower':['o','r'],'upper':['o','w'],'size':10}
    plotE=0
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    pmagplotlib.plot_init(FIG['eq'],5,5)
    if '-sav' in sys.argv:plot=1
    if '-f' in sys.argv:
        ind=sys.argv.index("-f")
        title=sys.argv[ind+1]
        data=numpy.loadtxt(title).transpose()
    if '-ell' in sys.argv:
        plotE=1
        ind=sys.argv.index('-ell')
        ell_type=sys.argv[ind+1]
        if ell_type=='F':dist='F' 
        if ell_type=='K':dist='K' 
        if ell_type=='B':dist='B' 
        if ell_type=='Be':dist='BE' 
        if ell_type=='Bv':
            dist='BV' 
            FIG['bdirs']=2
            pmagplotlib.plot_init(FIG['bdirs'],5,5)
    if '-fmt' in sys.argv:
        ind=sys.argv.index("-fmt")
        fmt=sys.argv[ind+1]
    DIblock=numpy.array([data[0],data[1]]).transpose()
    if len(DIblock)>0: 
        pmagplotlib.plotEQsym(FIG['eq'],DIblock,title,sym)
        if plot==0:pmagplotlib.drawFIGS(FIG)
    else:
        print "no data to plot"
        sys.exit()
    if plotE==1:
        ppars=pmag.doprinc(DIblock) # get principal directions
        nDIs,rDIs,npars,rpars=[],[],[],[]
        for rec in DIblock:
            angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
            if angle>90.:
                rDIs.append(rec)
            else:
                nDIs.append(rec)
        if dist=='B': # do on whole dataset
            etitle="Bingham confidence ellipse"
            bpars=pmag.dobingham(DIblock)
            for key in bpars.keys():
                if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(bpars[key])
                if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(bpars[key])
            npars.append(bpars['dec']) 
            npars.append(bpars['inc'])
            npars.append(bpars['Zeta']) 
            npars.append(bpars['Zdec']) 
            npars.append(bpars['Zinc'])
            npars.append(bpars['Eta']) 
            npars.append(bpars['Edec']) 
            npars.append(bpars['Einc'])
        if dist=='F':
            etitle="Fisher confidence cone"
            if len(nDIs)>3:
                fpars=pmag.fisher_mean(nDIs)
                for key in fpars.keys():
                    if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(fpars[key])
                    if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(fpars[key])
                mode+=1
                npars.append(fpars['dec']) 
                npars.append(fpars['inc'])
                npars.append(fpars['alpha95']) # Beta
                npars.append(fpars['dec']) 
                isign=abs(fpars['inc'])/fpars['inc'] 
                npars.append(fpars['inc']-isign*90.) #Beta inc
                npars.append(fpars['alpha95']) # gamma 
                npars.append(fpars['dec']+90.) # Beta dec
                npars.append(0.) #Beta inc
            if len(rDIs)>3:
                fpars=pmag.fisher_mean(rDIs)
                if pmagplotlib.verbose:print "mode ",mode
                for key in fpars.keys():
                    if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(fpars[key])
                    if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(fpars[key])
                mode+=1
                rpars.append(fpars['dec']) 
                rpars.append(fpars['inc'])
                rpars.append(fpars['alpha95']) # Beta
                rpars.append(fpars['dec']) 
                isign=abs(fpars['inc'])/fpars['inc'] 
                rpars.append(fpars['inc']-isign*90.) #Beta inc
                rpars.append(fpars['alpha95']) # gamma 
                rpars.append(fpars['dec']+90.) # Beta dec
                rpars.append(0.) #Beta inc
        if dist=='K':
            etitle="Kent confidence ellipse"
            if len(nDIs)>3:
                kpars=pmag.dokent(nDIs,len(nDIs))
                if pmagplotlib.verbose:print "mode ",mode
                for key in kpars.keys():
                    if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(kpars[key])
                    if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(kpars[key])
                mode+=1
                npars.append(kpars['dec']) 
                npars.append(kpars['inc'])
                npars.append(kpars['Zeta']) 
                npars.append(kpars['Zdec']) 
                npars.append(kpars['Zinc'])
                npars.append(kpars['Eta']) 
                npars.append(kpars['Edec']) 
                npars.append(kpars['Einc'])
            if len(rDIs)>3:
                kpars=pmag.dokent(rDIs,len(rDIs))
                if pmagplotlib.verbose:print "mode ",mode
                for key in kpars.keys():
                    if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(kpars[key])
                    if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(kpars[key])
                mode+=1
                rpars.append(kpars['dec']) 
                rpars.append(kpars['inc'])
                rpars.append(kpars['Zeta']) 
                rpars.append(kpars['Zdec']) 
                rpars.append(kpars['Zinc'])
                rpars.append(kpars['Eta']) 
                rpars.append(kpars['Edec']) 
                rpars.append(kpars['Einc'])
        else: # assume bootstrap
            if len(nDIs)<10 and len(rDIs)<10:
                print 'too few data points for bootstrap'
                sys.exit()
            if dist=='BE':
                print 'Be patient for bootstrap...'
                if len(nDIs)>=10:
                    BnDIs=pmag.di_boot(nDIs)
                    Bkpars=pmag.dokent(BnDIs,1.)
                    if pmagplotlib.verbose:print "mode ",mode
                    for key in Bkpars.keys():
                        if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(Bkpars[key])
                        if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(Bkpars[key])
                    mode+=1
                    npars.append(Bkpars['dec']) 
                    npars.append(Bkpars['inc'])
                    npars.append(Bkpars['Zeta']) 
                    npars.append(Bkpars['Zdec']) 
                    npars.append(Bkpars['Zinc'])
                    npars.append(Bkpars['Eta']) 
                    npars.append(Bkpars['Edec']) 
                    npars.append(Bkpars['Einc'])
                if len(rDIs)>=10:
                    BrDIs=pmag.di_boot(rDIs)
                    Bkpars=pmag.dokent(BrDIs,1.)
                    if pmagplotlib.verbose:print "mode ",mode
                    for key in Bkpars.keys():
                        if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(Bkpars[key])
                        if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(Bkpars[key])
                    mode+=1
                    rpars.append(Bkpars['dec']) 
                    rpars.append(Bkpars['inc'])
                    rpars.append(Bkpars['Zeta']) 
                    rpars.append(Bkpars['Zdec']) 
                    rpars.append(Bkpars['Zinc'])
                    rpars.append(Bkpars['Eta']) 
                    rpars.append(Bkpars['Edec']) 
                    rpars.append(Bkpars['Einc'])
                etitle="Bootstrapped confidence ellipse"
            elif dist=='BV':
                print 'Be patient for bootstrap...'
                vsym={'lower':['+','k'],'upper':['x','k'],'size':5}
                if len(nDIs)>5:
                    BnDIs=pmag.di_boot(nDIs)
                    pmagplotlib.plotEQsym(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors',vsym)
                if len(rDIs)>5:
                    BrDIs=pmag.di_boot(rDIs)
                    if len(nDIs)>5:  # plot on existing plots
                        pmagplotlib.plotDIsym(FIG['bdirs'],BrDIs,vsym)
                    else:
                        pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors',vsym)
        if dist=='B':
            if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
        elif len(nDIs)>3 and dist!='BV':
            pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
            if len(rDIs)>3:
                pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
        elif len(rDIs)>3 and dist!='BV':
            pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
        if plot==0:pmagplotlib.drawFIGS(FIG)
    if plot==0:pmagplotlib.drawFIGS(FIG)
        #
    files={}
    for key in FIG.keys():
        files[key]=title+'_'+key+'.'+fmt 
    if pmagplotlib.isServer:
        black     = '#000000'
        purple    = '#800080'
        titles={}
        titles['eq']='Equal Area Plot'
        FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
        pmagplotlib.saveP(FIG,files)
    elif plot==0:
        ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
        if ans=="q": sys.exit()
        if ans=="a": 
            pmagplotlib.saveP(FIG,files) 
    else:
        pmagplotlib.saveP(FIG,files)
Esempio n. 5
0
def main():
    """
    NAME
        eqarea_magic.py

    DESCRIPTION
       makes equal area projections from declination/inclination data

    SYNTAX 
        eqarea_magic.py [command line options]
    
    INPUT 
       takes magic formatted pmag_results, pmag_sites, pmag_samples or pmag_specimens
    
    OPTIONS
        -h prints help message and quits
        -f FILE: specify input magic format file from magic,default='pmag_results.txt'
         supported types=[magic_measurements,pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
        -obj OBJ: specify  level of plot  [all, sit, sam, spc], default is all
        -crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
                default is geographic
        -fmt [svg,png,jpg] format for output plots
        -ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
        -c plot as colour contour 
    NOTE
        all: entire file; sit: site; sam: sample; spc: specimen
    """
    FIG={} # plot dictionary
    FIG['eq']=1 # eqarea is figure 1
    in_file,plot_key,coord,crd='pmag_results.txt','all',"-1",'g'
    fmt,dist,mode='svg','F',1
    plotE,contour=0,0
    dir_path='.'
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-WD' in sys.argv:
        ind=sys.argv.index('-WD')
        dir_path=sys.argv[ind+1]
    pmagplotlib.plot_init(FIG['eq'],5,5)
    if '-f' in sys.argv:
        ind=sys.argv.index("-f")
        in_file=dir_path+"/"+sys.argv[ind+1]
    if '-obj' in sys.argv:
        ind=sys.argv.index('-obj')
        plot_by=sys.argv[ind+1]
        if plot_by=='all':plot_key='all'
        if plot_by=='sit':plot_key='er_site_name'
        if plot_by=='sam':plot_key='er_sample_name'
        if plot_by=='spc':plot_key='er_specimen_name'
    if '-c' in sys.argv: contour=1
    if '-ell' in sys.argv:
        plotE=1
        ind=sys.argv.index('-ell')
        ell_type=sys.argv[ind+1]
        if ell_type=='F':dist='F' 
        if ell_type=='K':dist='K' 
        if ell_type=='B':dist='B' 
        if ell_type=='Be':dist='BE' 
        if ell_type=='Bv':
            dist='BV' 
            FIG['bdirs']=2
            pmagplotlib.plot_init(FIG['bdirs'],5,5)
    if '-crd' in sys.argv:
        ind=sys.argv.index("-crd")
        coord=sys.argv[ind+1]
        if coord=='g':coord="0"
        if coord=='t':coord="100"
    if '-fmt' in sys.argv:
        ind=sys.argv.index("-fmt")
        fmt=sys.argv[ind+1]
    Dec_keys=['site_dec','sample_dec','specimen_dec','measurement_dec','average_dec']
    Inc_keys=['site_inc','sample_inc','specimen_inc','measurement_inc','average_inc']
    Tilt_keys=['tilt_correction','site_tilt_correction','sample_tilt_correction','specimen_tilt_correction']
    Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
    Name_keys=['er_specimen_name','er_sample_name','er_site_name','pmag_result_name']
    data,file_type=pmag.magic_read(in_file)
    if file_type=='pmag_results' and plot_key!="all":plot_key=plot_key+'s' # need plural for results table
    if pmagplotlib.verbose:    
        print len(data),' records read from ',in_file
    #
    #
    # find desired dec,inc data:
    #
    dir_type_key=''
    #
    # get plotlist if not plotting all records
    #
    plotlist=[]
    if plot_key!="all":
        for  rec in data:
            if rec[plot_key] not in plotlist:
                plotlist.append(rec[plot_key])
        plotlist.sort()
    else:
        plotlist.append('Whole file')
    for plot in plotlist:
        DIblock=[]
        GCblock=[]
        SLblock,SPblock=[],[]
        tilt_key=""
        mode=1
        for rec in data: # find what data are available
            if plot_key=='all' or rec[plot_key]==plot:
                if plot_key!="all":
                    title=rec[plot_key]
                else:
                    title=plot
                if coord=='-1':title=title+' Specimen Coordinates'
                if coord=='0':title=title+' Geographic Coordinates'
                if coord=='100':title=title+' Tilt corrected Coordinates'
                dec_key,inc_key,tilt_key,name_key,k="","","","",0
                while dec_key==""  and k<len(Dec_keys):
                    if Dec_keys[k]  in rec.keys() and rec[Dec_keys[k]]!="" and Inc_keys[k] in rec.keys() and rec[Inc_keys[k]]!="": 
                        dec_key,inc_key =Dec_keys[k],Inc_keys[k]
                    k+=1
                k=0
                while tilt_key==""  and k<len(Tilt_keys):
                    if Tilt_keys[k]  in rec.keys():tilt_key=Tilt_keys[k]
                    k+=1
                k=0
                while name_key==""  and k<len(Name_keys):
                    if Name_keys[k]  in rec.keys():name_key=Name_keys[k]
                    k+=1
                k=1
                while dir_type_key==""  and k<len(Dir_type_keys):
                    if Dir_type_keys[k]  in rec.keys():dir_type_key=Dir_type_keys[k]
                    k+=1
                if  dec_key!="":break 
        if tilt_key=="":tilt_key='-1'
        if dir_type_key=="":dir_type_key='direction_type'
        for rec in data: # pick out the data
          if (plot_key=='all' or rec[plot_key]==plot)  and rec[dec_key].strip()!="" and rec[inc_key].strip()!="":
            if dir_type_key not in rec.keys() or rec[dir_type_key]=="":rec[dir_type_key]='l'
            if tilt_key not in rec.keys():rec[tilt_key]='-1' # assume specimen coordinates unless otherwise specified
            if coord=='-1':
                    DIblock.append([float(rec[dec_key]),float(rec[inc_key])])
                    SLblock.append([rec[name_key],rec['magic_method_codes']])
            elif rec[tilt_key]==coord and rec[dir_type_key]=='l' and rec[dec_key]!="" and rec[inc_key]!="":
                if rec[tilt_key]==coord and rec[dir_type_key]=='l' and rec[dec_key]!="" and rec[inc_key]!="":
                    DIblock.append([float(rec[dec_key]),float(rec[inc_key])])
                    SLblock.append([rec[name_key],rec['magic_method_codes']])
            elif rec[tilt_key]==coord and rec[dir_type_key]!='l' and rec[dec_key]!="" and rec[inc_key]!="":
                    GCblock.append([float(rec[dec_key]),float(rec[inc_key])])
                    SPblock.append([rec[name_key],rec['magic_method_codes']])
        if len(DIblock)==0 and len(GCblock)==0:
            if pmagplotlib.verbose: print "no records for plotting"
            sys.exit()
        if pmagplotlib.verbose:
          for k in range(len(SLblock)):
            print '%s %s %7.1f %7.1f'%(SLblock[k][0],SLblock[k][1],DIblock[k][0],DIblock[k][1])
          for k in range(len(SPblock)):
            print '%s %s %7.1f %7.1f'%(SPblock[k][0],SPblock[k][1],GCblock[k][0],GCblock[k][1])
        if len(DIblock)>0: 
            if contour==0:
                pmagplotlib.plotEQ(FIG['eq'],DIblock,title)
            else:
                pmagplotlib.plotEQcont(FIG['eq'],DIblock)
        else:   pmagplotlib.plotNET(FIG['eq'])
        if len(GCblock)>0:
            for rec in GCblock: pmagplotlib.plotC(FIG['eq'],rec,90.,'g')
        if plotE==1:
            ppars=pmag.doprinc(DIblock) # get principal directions
            nDIs,rDIs,npars,rpars=[],[],[],[]
            for rec in DIblock:
                angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
                if angle>90.:
                    rDIs.append(rec)
                else:
                    nDIs.append(rec)
            if dist=='B': # do on whole dataset
                etitle="Bingham confidence ellipse"
                bpars=pmag.dobingham(DIblock)
                for key in bpars.keys():
                    if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(bpars[key])
                    if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(bpars[key])
                npars.append(bpars['dec']) 
                npars.append(bpars['inc'])
                npars.append(bpars['Zeta']) 
                npars.append(bpars['Zdec']) 
                npars.append(bpars['Zinc'])
                npars.append(bpars['Eta']) 
                npars.append(bpars['Edec']) 
                npars.append(bpars['Einc'])
            if dist=='F':
                etitle="Fisher confidence cone"
                if len(nDIs)>2:
                    fpars=pmag.fisher_mean(nDIs)
                    for key in fpars.keys():
                        if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(fpars[key])
                        if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(fpars[key])
                    mode+=1
                    npars.append(fpars['dec']) 
                    npars.append(fpars['inc'])
                    npars.append(fpars['alpha95']) # Beta
                    npars.append(fpars['dec']) 
                    isign=abs(fpars['inc'])/fpars['inc'] 
                    npars.append(fpars['inc']-isign*90.) #Beta inc
                    npars.append(fpars['alpha95']) # gamma 
                    npars.append(fpars['dec']+90.) # Beta dec
                    npars.append(0.) #Beta inc
                if len(rDIs)>2:
                    fpars=pmag.fisher_mean(rDIs)
                    if pmagplotlib.verbose:print "mode ",mode
                    for key in fpars.keys():
                        if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(fpars[key])
                        if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(fpars[key])
                    mode+=1
                    rpars.append(fpars['dec']) 
                    rpars.append(fpars['inc'])
                    rpars.append(fpars['alpha95']) # Beta
                    rpars.append(fpars['dec']) 
                    isign=abs(fpars['inc'])/fpars['inc'] 
                    rpars.append(fpars['inc']-isign*90.) #Beta inc
                    rpars.append(fpars['alpha95']) # gamma 
                    rpars.append(fpars['dec']+90.) # Beta dec
                    rpars.append(0.) #Beta inc
            if dist=='K':
                etitle="Kent confidence ellipse"
                if len(nDIs)>3:
                    kpars=pmag.dokent(nDIs,len(nDIs))
                    if pmagplotlib.verbose:print "mode ",mode
                    for key in kpars.keys():
                        if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(kpars[key])
                        if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(kpars[key])
                    mode+=1
                    npars.append(kpars['dec']) 
                    npars.append(kpars['inc'])
                    npars.append(kpars['Zeta']) 
                    npars.append(kpars['Zdec']) 
                    npars.append(kpars['Zinc'])
                    npars.append(kpars['Eta']) 
                    npars.append(kpars['Edec']) 
                    npars.append(kpars['Einc'])
                if len(rDIs)>3:
                    kpars=pmag.dokent(rDIs,len(rDIs))
                    if pmagplotlib.verbose:print "mode ",mode
                    for key in kpars.keys():
                        if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(kpars[key])
                        if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(kpars[key])
                    mode+=1
                    rpars.append(kpars['dec']) 
                    rpars.append(kpars['inc'])
                    rpars.append(kpars['Zeta']) 
                    rpars.append(kpars['Zdec']) 
                    rpars.append(kpars['Zinc'])
                    rpars.append(kpars['Eta']) 
                    rpars.append(kpars['Edec']) 
                    rpars.append(kpars['Einc'])
            else: # assume bootstrap
                if dist=='BE':
                    if len(nDIs)>5:
                        BnDIs=pmag.di_boot(nDIs)
                        Bkpars=pmag.dokent(BnDIs,1.)
                        if pmagplotlib.verbose:print "mode ",mode
                        for key in Bkpars.keys():
                            if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(Bkpars[key])
                            if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(Bkpars[key])
                        mode+=1
                        npars.append(Bkpars['dec']) 
                        npars.append(Bkpars['inc'])
                        npars.append(Bkpars['Zeta']) 
                        npars.append(Bkpars['Zdec']) 
                        npars.append(Bkpars['Zinc'])
                        npars.append(Bkpars['Eta']) 
                        npars.append(Bkpars['Edec']) 
                        npars.append(Bkpars['Einc'])
                    if len(rDIs)>5:
                        BrDIs=pmag.di_boot(rDIs)
                        Bkpars=pmag.dokent(BrDIs,1.)
                        if pmagplotlib.verbose:print "mode ",mode
                        for key in Bkpars.keys():
                            if key!='n' and pmagplotlib.verbose:print "    ",key, '%7.1f'%(Bkpars[key])
                            if key=='n' and pmagplotlib.verbose:print "    ",key, '       %i'%(Bkpars[key])
                        mode+=1
                        rpars.append(Bkpars['dec']) 
                        rpars.append(Bkpars['inc'])
                        rpars.append(Bkpars['Zeta']) 
                        rpars.append(Bkpars['Zdec']) 
                        rpars.append(Bkpars['Zinc'])
                        rpars.append(Bkpars['Eta']) 
                        rpars.append(Bkpars['Edec']) 
                        rpars.append(Bkpars['Einc'])
                    etitle="Bootstrapped confidence ellipse"
                elif dist=='BV':
                    if len(nDIs)>5:
                        BnDIs=pmag.di_boot(nDIs)
                        pmagplotlib.plotEQ(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors')
                    if len(rDIs)>5:
                        BrDIs=pmag.di_boot(rDIs)
                        if len(nDIs)>5:  # plot on existing plots
                            pmagplotlib.plotDI(FIG['bdirs'],BrDIs)
                        else:
                            pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
            if dist=='B':
                if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
            elif len(nDIs)>3 and dist!='BV':
                pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
                if len(rDIs)>3:
                    pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
            elif len(rDIs)>3 and dist!='BV':
                pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
        pmagplotlib.drawFIGS(FIG)
            #
        files={}
        for key in FIG.keys():
            files[key]=title.replace(" ","_")+'_'+'eqarea'+'.'+fmt 
        if pmagplotlib.isServer:
            black     = '#000000'
            purple    = '#800080'
            titles={}
            titles['eq']='Equal Area Plot'
            FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
            pmagplotlib.saveP(FIG,files)
        else:
            ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
            if ans=="q": sys.exit()
            if ans=="a": 
                pmagplotlib.saveP(FIG,files) 
Esempio n. 6
0
def main():
    """
    NAME
        eqarea_ell.py

    DESCRIPTION
       makes equal area projections from declination/inclination data
       and plot ellipses

    SYNTAX 
        eqarea_ell.py -h [command line options]
    
    INPUT 
       takes space delimited Dec/Inc data
    
    OPTIONS
        -h prints help message and quits
        -f FILE
        -fmt [svg,png,jpg] format for output plots
        -sav  saves figures and quits
        -ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
    """
    FIG = {}  # plot dictionary
    FIG['eq'] = 1  # eqarea is figure 1
    fmt, dist, mode, plot = 'svg', 'F', 1, 0
    sym = {'lower': ['o', 'r'], 'upper': ['o', 'w'], 'size': 10}
    plotE = 0
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    pmagplotlib.plot_init(FIG['eq'], 5, 5)
    if '-sav' in sys.argv: plot = 1
    if '-f' in sys.argv:
        ind = sys.argv.index("-f")
        title = sys.argv[ind + 1]
        data = numpy.loadtxt(title).transpose()
    if '-ell' in sys.argv:
        plotE = 1
        ind = sys.argv.index('-ell')
        ell_type = sys.argv[ind + 1]
        if ell_type == 'F': dist = 'F'
        if ell_type == 'K': dist = 'K'
        if ell_type == 'B': dist = 'B'
        if ell_type == 'Be': dist = 'BE'
        if ell_type == 'Bv':
            dist = 'BV'
            FIG['bdirs'] = 2
            pmagplotlib.plot_init(FIG['bdirs'], 5, 5)
    if '-fmt' in sys.argv:
        ind = sys.argv.index("-fmt")
        fmt = sys.argv[ind + 1]
    DIblock = numpy.array([data[0], data[1]]).transpose()
    if len(DIblock) > 0:
        pmagplotlib.plotEQsym(FIG['eq'], DIblock, title, sym)
        if plot == 0: pmagplotlib.drawFIGS(FIG)
    else:
        print "no data to plot"
        sys.exit()
    if plotE == 1:
        ppars = pmag.doprinc(DIblock)  # get principal directions
        nDIs, rDIs, npars, rpars = [], [], [], []
        for rec in DIblock:
            angle = pmag.angle([rec[0], rec[1]], [ppars['dec'], ppars['inc']])
            if angle > 90.:
                rDIs.append(rec)
            else:
                nDIs.append(rec)
        if dist == 'B':  # do on whole dataset
            etitle = "Bingham confidence ellipse"
            bpars = pmag.dobingham(DIblock)
            for key in bpars.keys():
                if key != 'n' and pmagplotlib.verbose:
                    print "    ", key, '%7.1f' % (bpars[key])
                if key == 'n' and pmagplotlib.verbose:
                    print "    ", key, '       %i' % (bpars[key])
            npars.append(bpars['dec'])
            npars.append(bpars['inc'])
            npars.append(bpars['Zeta'])
            npars.append(bpars['Zdec'])
            npars.append(bpars['Zinc'])
            npars.append(bpars['Eta'])
            npars.append(bpars['Edec'])
            npars.append(bpars['Einc'])
        if dist == 'F':
            etitle = "Fisher confidence cone"
            if len(nDIs) > 3:
                fpars = pmag.fisher_mean(nDIs)
                for key in fpars.keys():
                    if key != 'n' and pmagplotlib.verbose:
                        print "    ", key, '%7.1f' % (fpars[key])
                    if key == 'n' and pmagplotlib.verbose:
                        print "    ", key, '       %i' % (fpars[key])
                mode += 1
                npars.append(fpars['dec'])
                npars.append(fpars['inc'])
                npars.append(fpars['alpha95'])  # Beta
                npars.append(fpars['dec'])
                isign = abs(fpars['inc']) / fpars['inc']
                npars.append(fpars['inc'] - isign * 90.)  #Beta inc
                npars.append(fpars['alpha95'])  # gamma
                npars.append(fpars['dec'] + 90.)  # Beta dec
                npars.append(0.)  #Beta inc
            if len(rDIs) > 3:
                fpars = pmag.fisher_mean(rDIs)
                if pmagplotlib.verbose: print "mode ", mode
                for key in fpars.keys():
                    if key != 'n' and pmagplotlib.verbose:
                        print "    ", key, '%7.1f' % (fpars[key])
                    if key == 'n' and pmagplotlib.verbose:
                        print "    ", key, '       %i' % (fpars[key])
                mode += 1
                rpars.append(fpars['dec'])
                rpars.append(fpars['inc'])
                rpars.append(fpars['alpha95'])  # Beta
                rpars.append(fpars['dec'])
                isign = abs(fpars['inc']) / fpars['inc']
                rpars.append(fpars['inc'] - isign * 90.)  #Beta inc
                rpars.append(fpars['alpha95'])  # gamma
                rpars.append(fpars['dec'] + 90.)  # Beta dec
                rpars.append(0.)  #Beta inc
        if dist == 'K':
            etitle = "Kent confidence ellipse"
            if len(nDIs) > 3:
                kpars = pmag.dokent(nDIs, len(nDIs))
                if pmagplotlib.verbose: print "mode ", mode
                for key in kpars.keys():
                    if key != 'n' and pmagplotlib.verbose:
                        print "    ", key, '%7.1f' % (kpars[key])
                    if key == 'n' and pmagplotlib.verbose:
                        print "    ", key, '       %i' % (kpars[key])
                mode += 1
                npars.append(kpars['dec'])
                npars.append(kpars['inc'])
                npars.append(kpars['Zeta'])
                npars.append(kpars['Zdec'])
                npars.append(kpars['Zinc'])
                npars.append(kpars['Eta'])
                npars.append(kpars['Edec'])
                npars.append(kpars['Einc'])
            if len(rDIs) > 3:
                kpars = pmag.dokent(rDIs, len(rDIs))
                if pmagplotlib.verbose: print "mode ", mode
                for key in kpars.keys():
                    if key != 'n' and pmagplotlib.verbose:
                        print "    ", key, '%7.1f' % (kpars[key])
                    if key == 'n' and pmagplotlib.verbose:
                        print "    ", key, '       %i' % (kpars[key])
                mode += 1
                rpars.append(kpars['dec'])
                rpars.append(kpars['inc'])
                rpars.append(kpars['Zeta'])
                rpars.append(kpars['Zdec'])
                rpars.append(kpars['Zinc'])
                rpars.append(kpars['Eta'])
                rpars.append(kpars['Edec'])
                rpars.append(kpars['Einc'])
        else:  # assume bootstrap
            if len(nDIs) < 10 and len(rDIs) < 10:
                print 'too few data points for bootstrap'
                sys.exit()
            if dist == 'BE':
                print 'Be patient for bootstrap...'
                if len(nDIs) >= 10:
                    BnDIs = pmag.di_boot(nDIs)
                    Bkpars = pmag.dokent(BnDIs, 1.)
                    if pmagplotlib.verbose: print "mode ", mode
                    for key in Bkpars.keys():
                        if key != 'n' and pmagplotlib.verbose:
                            print "    ", key, '%7.1f' % (Bkpars[key])
                        if key == 'n' and pmagplotlib.verbose:
                            print "    ", key, '       %i' % (Bkpars[key])
                    mode += 1
                    npars.append(Bkpars['dec'])
                    npars.append(Bkpars['inc'])
                    npars.append(Bkpars['Zeta'])
                    npars.append(Bkpars['Zdec'])
                    npars.append(Bkpars['Zinc'])
                    npars.append(Bkpars['Eta'])
                    npars.append(Bkpars['Edec'])
                    npars.append(Bkpars['Einc'])
                if len(rDIs) >= 10:
                    BrDIs = pmag.di_boot(rDIs)
                    Bkpars = pmag.dokent(BrDIs, 1.)
                    if pmagplotlib.verbose: print "mode ", mode
                    for key in Bkpars.keys():
                        if key != 'n' and pmagplotlib.verbose:
                            print "    ", key, '%7.1f' % (Bkpars[key])
                        if key == 'n' and pmagplotlib.verbose:
                            print "    ", key, '       %i' % (Bkpars[key])
                    mode += 1
                    rpars.append(Bkpars['dec'])
                    rpars.append(Bkpars['inc'])
                    rpars.append(Bkpars['Zeta'])
                    rpars.append(Bkpars['Zdec'])
                    rpars.append(Bkpars['Zinc'])
                    rpars.append(Bkpars['Eta'])
                    rpars.append(Bkpars['Edec'])
                    rpars.append(Bkpars['Einc'])
                etitle = "Bootstrapped confidence ellipse"
            elif dist == 'BV':
                print 'Be patient for bootstrap...'
                vsym = {'lower': ['+', 'k'], 'upper': ['x', 'k'], 'size': 5}
                if len(nDIs) > 5:
                    BnDIs = pmag.di_boot(nDIs)
                    pmagplotlib.plotEQsym(FIG['bdirs'], BnDIs,
                                          'Bootstrapped Eigenvectors', vsym)
                if len(rDIs) > 5:
                    BrDIs = pmag.di_boot(rDIs)
                    if len(nDIs) > 5:  # plot on existing plots
                        pmagplotlib.plotDIsym(FIG['bdirs'], BrDIs, vsym)
                    else:
                        pmagplotlib.plotEQ(FIG['bdirs'], BrDIs,
                                           'Bootstrapped Eigenvectors', vsym)
        if dist == 'B':
            if len(nDIs) > 3 or len(rDIs) > 3:
                pmagplotlib.plotCONF(FIG['eq'], etitle, [], npars, 0)
        elif len(nDIs) > 3 and dist != 'BV':
            pmagplotlib.plotCONF(FIG['eq'], etitle, [], npars, 0)
            if len(rDIs) > 3:
                pmagplotlib.plotCONF(FIG['eq'], etitle, [], rpars, 0)
        elif len(rDIs) > 3 and dist != 'BV':
            pmagplotlib.plotCONF(FIG['eq'], etitle, [], rpars, 0)
        if plot == 0: pmagplotlib.drawFIGS(FIG)
    if plot == 0: pmagplotlib.drawFIGS(FIG)
    #
    files = {}
    for key in FIG.keys():
        files[key] = title + '_' + key + '.' + fmt
    if pmagplotlib.isServer:
        black = '#000000'
        purple = '#800080'
        titles = {}
        titles['eq'] = 'Equal Area Plot'
        FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
        pmagplotlib.saveP(FIG, files)
    elif plot == 0:
        ans = raw_input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
        if ans == "q": sys.exit()
        if ans == "a":
            pmagplotlib.saveP(FIG, files)
    else:
        pmagplotlib.saveP(FIG, files)