Beispiel #1
0
def main():
    """
    NAME
        microwave_magic.py
    
    DESCRIPTION
        plots microwave paleointensity data, allowing interactive setting of bounds.
        Saves and reads interpretations
        from a pmag_specimen formatted table, default: microwave_specimens.txt

    SYNTAX 
        microwave_magic.py [command line options]

    OPTIONS
        -h prints help message and quits
        -f MEAS, set magic_measurements input file
        -fsp PRIOR, set pmag_specimen prior interpretations file
        -fcr CRIT, set criteria file for grading.  
        -fmt [svg,png,jpg], format for images - default is svg
        -sav,  saves plots with out review (default format)
        -spc SPEC, plots single specimen SPEC, saves plot with specified format
            with optional -b bounds adn quits
        -b BEG END: sets  bounds for calculation
           BEG: starting step for slope calculation
           END: ending step for slope calculation
        
    DEFAULTS
        MEAS: magic_measurements.txt
        CRIT: NONE
        PRIOR: microwave_specimens.txt
  
    OUTPUT 
        figures:
            ALL:  numbers refer to temperature steps in command line window
            1) Arai plot:  closed circles are zero-field first/infield
                           open circles are infield first/zero-field
                           triangles are pTRM checks
                           squares are pTRM tail checks
                           VDS is vector difference sum
                           diamonds are bounds for interpretation
            2) Zijderveld plot:  closed (open) symbols are X-Y (X-Z) planes
                                 X rotated to NRM direction
            3) (De/Re)Magnetization diagram:
                           circles are NRM remaining
                           squares are pTRM gained
        command line window:
            list is: temperature step numbers, power (J), Dec, Inc, Int (units of magic_measuements)
                     list of possible commands: type letter followed by return to select option
                     saving of plots creates .svg format files with specimen_name, plot type as name
    """
    #
    #   initializations
    #
    meas_file, critout, inspec = "magic_measurements.txt", "", "microwave_specimens.txt"
    inlt = 0
    version_num = pmag.get_version()
    Tinit, DCZ, field, first_save = 0, 0, -1, 1
    user, comment = "", ''
    ans, specimen, recnum, start, end = 0, 0, 0, 0, 0
    plots, pmag_out, samp_file, style = 0, "", "", "svg"
    fmt = '.' + style
    #
    # default acceptance criteria
    #
    accept_keys = [
        'specimen_int_ptrm_n', 'specimen_md', 'specimen_fvds',
        'specimen_b_beta', 'specimen_dang', 'specimen_drats', 'specimen_Z'
    ]
    accept = {}
    accept['specimen_int_ptrm_n'] = 2
    accept['specimen_md'] = 10
    accept['specimen_fvds'] = 0.35
    accept['specimen_b_beta'] = .1
    accept['specimen_int_mad'] = 7
    accept['specimen_dang'] = 10
    accept['specimen_drats'] = 10
    accept['specimen_Z'] = 10
    #
    # parse command line options
    #
    spc, BEG, END = "", "", ""
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-f' in sys.argv:
        ind = sys.argv.index('-f')
        meas_file = sys.argv[ind + 1]
    if '-fsp' in sys.argv:
        ind = sys.argv.index('-fsp')
        inspec = sys.argv[ind + 1]
    if '-fcr' in sys.argv:
        ind = sys.argv.index('-fcr')
        critout = sys.argv[ind + 1]
    if '-fmt' in sys.argv:
        ind = sys.argv.index('-fmt')
        fmt = '.' + sys.argv[ind + 1]
    if '-spc' in sys.argv:
        ind = sys.argv.index('-spc')
        spc = sys.argv[ind + 1]
        if '-b' in sys.argv:
            ind = sys.argv.index('-b')
            BEG = int(sys.argv[ind + 1])
            END = int(sys.argv[ind + 2])
    if critout != "":
        crit_data, file_type = pmag.magic_read(critout)
        if pmagplotlib.verbose:
            print "Acceptance criteria read in from ", critout
        accept = {}
        accept['specimen_int_ptrm_n'] = 2.0
        for critrec in crit_data:
            if critrec["pmag_criteria_code"] == "IE-SPEC":
                for key in accept_keys:
                    if key not in critrec.keys():
                        accept[key] = -1
                    else:
                        accept[key] = float(critrec[key])
    try:
        open(inspec, 'rU')
        PriorRecs, file_type = pmag.magic_read(inspec)
        if file_type != 'pmag_specimens':
            print file_type
            print file_type, inspec, " is not a valid pmag_specimens file "
            sys.exit()
        for rec in PriorRecs:
            if 'magic_software_packages' not in rec.keys():
                rec['magic_software_packages'] = ""
    except IOError:
        PriorRecs = []
        if pmagplotlib.verbose:
            print "starting new specimen interpretation file: ", inspec
    meas_data, file_type = pmag.magic_read(meas_file)
    if file_type != 'magic_measurements':
        print file_type
        print file_type, "This is not a valid magic_measurements file "
        sys.exit()
    backup = 0
    # define figure numbers for arai, zijderveld and
    #   de-,re-magization diagrams
    AZD = {}
    AZD['deremag'], AZD['zijd'], AZD['arai'], AZD['eqarea'] = 1, 2, 3, 4
    pmagplotlib.plot_init(AZD['arai'], 4, 4)
    pmagplotlib.plot_init(AZD['zijd'], 4, 4)
    pmagplotlib.plot_init(AZD['deremag'], 4, 4)
    pmagplotlib.plot_init(AZD['eqarea'], 4, 4)
    #
    #
    #
    # get list of unique specimen names
    #
    CurrRec = []
    sids = pmag.get_specs(meas_data)
    # get plots for specimen s - default is just to step through arai diagrams
    #
    if spc != "": specimen = sids.index(spc)
    while specimen < len(sids):
        methcodes = []
        if pmagplotlib.verbose and spc != "":
            print sids[specimen], specimen + 1, 'of ', len(sids)
        MeasRecs = []
        s = sids[specimen]
        datablock, trmblock = [], []
        PmagSpecRec = {}
        PmagSpecRec["er_analyst_mail_names"] = user
        PmagSpecRec["specimen_correction"] = 'u'
        #
        # find the data from the meas_data file for this specimen
        #
        for rec in meas_data:
            if rec["er_specimen_name"] == s:
                MeasRecs.append(rec)
                methods = rec["magic_method_codes"].split(":")
                meths = []
                for meth in methods:
                    meths.append(meth.strip())  # take off annoying spaces
                methods = ""
                for meth in meths:
                    if meth.strip() not in methcodes and "LP-" in meth:
                        methcodes.append(meth.strip())
                    methods = methods + meth + ":"
                methods = methods[:-1]
                rec["magic_method_codes"] = methods
                if "LP-PI-M" in meths: datablock.append(rec)
                if "LP-MRM" in meths: trmblock.append(rec)
        if len(trmblock) > 2 and inspec != "":
            if Tinit == 0:
                Tinit = 1
                AZD['MRM'] = 4
                pmagplotlib.plot_init(AZD['MRM'], 4, 4)
            elif Tinit == 1:
                pmagplotlib.clearFIG(AZD['MRM'])
        if len(datablock) < 4:
            if backup == 0:
                specimen += 1
                if pmagplotlib.verbose:
                    print 'skipping specimen - moving forward ', s
            else:
                specimen -= 1
                if pmagplotlib.verbose:
                    print 'skipping specimen - moving backward ', s
    #
    #  collect info for the PmagSpecRec dictionary
    #
        else:
            rec = datablock[0]
            PmagSpecRec["er_citation_names"] = "This study"
            PmagSpecRec["er_specimen_name"] = s
            PmagSpecRec["er_sample_name"] = rec["er_sample_name"]
            PmagSpecRec["er_site_name"] = rec["er_site_name"]
            PmagSpecRec["er_location_name"] = rec["er_location_name"]
            if "magic_instrument_codes" not in rec.keys():
                rec["magic_instrument_codes"] = ""
            PmagSpecRec["magic_instrument_codes"] = rec[
                "magic_instrument_codes"]
            PmagSpecRec["measurement_step_unit"] = "J"
            if "magic_experiment_name" not in rec.keys():
                rec["magic_experiment_name"] = ""
            else:
                PmagSpecRec["magic_experiment_names"] = rec[
                    "magic_experiment_name"]

            meths = rec["magic_method_codes"].split(':')
            # sort data into types
            if "LP-PI-M-D" in meths:  # this is a double heating experiment
                exp_type = "LP-PI-M-D"
            elif "LP-PI-M-S" in meths:
                exp_type = "LP-PI-M-S"
            else:
                print "experiment type not supported yet "
                break
            araiblock, field = pmag.sortmwarai(datablock, exp_type)
            first_Z = araiblock[0]
            first_I = araiblock[1]
            GammaChecks = araiblock[-3]
            ThetaChecks = araiblock[-2]
            DeltaChecks = araiblock[-1]
            if len(first_Z) < 3:
                if backup == 0:
                    specimen += 1
                    if pmagplotlib.verbose:
                        print 'skipping specimen - moving forward ', s
                else:
                    specimen -= 1
                    if pmagplotlib.verbose:
                        print 'skipping specimen - moving backward ', s
            else:
                backup = 0
                zijdblock, units = pmag.find_dmag_rec(s, meas_data)
                if exp_type == "LP-PI-M-D":
                    recnum = 0
                    print "ZStep Watts  Dec Inc  Int"
                    for plotrec in zijdblock:
                        if pmagplotlib.verbose:
                            print '%i  %i %7.1f %7.1f %8.3e ' % (
                                recnum, plotrec[0], plotrec[1], plotrec[2],
                                plotrec[3])
                            recnum += 1
                    recnum = 1
                    if GammaChecks != "":
                        print "IStep Watts  Gamma"
                        for gamma in GammaChecks:
                            if pmagplotlib.verbose:
                                print '%i %i %7.1f ' % (recnum, gamma[0],
                                                        gamma[1])
                            recnum += 1
                if exp_type == "LP-PI-M-S":
                    if pmagplotlib.verbose:
                        print "IStep Watts  Theta"
                        kk = 0
                        for theta in ThetaChecks:
                            kk += 1
                            print '%i  %i %7.1f ' % (kk, theta[0], theta[1])
                    if pmagplotlib.verbose:
                        print "Watts  Delta"
                        for delta in DeltaChecks:
                            print '%i %7.1f ' % (delta[0], delta[1])
                pmagplotlib.plotAZ(AZD, araiblock, zijdblock, s, units[0])
                if inspec != "":
                    if pmagplotlib.verbose:
                        print 'Looking up saved interpretation....'
                    found = 0
                    for k in range(len(PriorRecs)):
                        try:
                            if PriorRecs[k]["er_specimen_name"] == s:
                                found = 1
                                CurrRec.append(PriorRecs[k])
                                for j in range(len(araiblock[0])):
                                    if float(araiblock[0][j][0]) == float(
                                            PriorRecs[k]
                                        ["measurement_step_min"]):
                                        start = j
                                    if float(araiblock[0][j][0]) == float(
                                            PriorRecs[k]
                                        ["measurement_step_max"]):
                                        end = j
                                pars, errcode = pmag.PintPars(
                                    araiblock, zijdblock, start, end)
                                pars['measurement_step_unit'] = "J"
                                del PriorRecs[
                                    k]  # put in CurrRec, take out of PriorRecs
                                if errcode != 1:
                                    pars["specimen_lab_field_dc"] = field
                                    pars["specimen_int"] = -1 * field * pars[
                                        "specimen_b"]
                                    pars["er_specimen_name"] = s
                                    if pmagplotlib.verbose:
                                        print 'Saved interpretation: '
                                    pars = pmag.scoreit(
                                        pars, PmagSpecRec, accept, '', 0)
                                    pmagplotlib.plotB(AZD, araiblock,
                                                      zijdblock, pars)
                                    if len(trmblock) > 2:
                                        blab = field
                                        best = pars["specimen_int"]
                                        Bs, TRMs = [], []
                                        for trec in trmblock:
                                            Bs.append(
                                                float(
                                                    trec['treatment_dc_field'])
                                            )
                                            TRMs.append(
                                                float(trec[
                                                    'measurement_magn_moment'])
                                            )
                                        NLpars = nlt.NLtrm(
                                            Bs, TRMs, best, blab, 0
                                        )  # calculate best fit parameters through TRM acquisition data, and get new banc
                                        Mp, Bp = [], []
                                        for k in range(int(max(Bs) * 1e6)):
                                            Bp.append(float(k) * 1e-6)
                                            npred = nlt.TRM(
                                                Bp[-1], NLpars['xopt'][0],
                                                NLpars['xopt'][1]
                                            )  # predicted NRM for this field
                                            Mp.append(npred)
                                        pmagplotlib.plotTRM(
                                            AZD['MRM'], Bs, TRMs, Bp, Mp,
                                            NLpars,
                                            trec['magic_experiment_name'])
                                        print npred
                                        print 'Banc= ', float(
                                            NLpars['banc']) * 1e6
                                        if pmagplotlib.verbose:
                                            print 'Banc= ', float(
                                                NLpars['banc']) * 1e6
                                        pmagplotlib.drawFIGS(AZD)
                                else:
                                    print 'error on specimen ', s
                        except:
                            pass
                    if pmagplotlib.verbose and found == 0:
                        print '    None found :(  '
                if spc != "":
                    if BEG != "":
                        pars, errcode = pmag.PintPars(araiblock, zijdblock,
                                                      BEG, END)
                        pars['measurement_step_unit'] = "J"
                        pars["specimen_lab_field_dc"] = field
                        pars["specimen_int"] = -1 * field * pars["specimen_b"]
                        pars["er_specimen_name"] = s
                        pars['specimen_grade'] = ''  # ungraded
                        pmagplotlib.plotB(AZD, araiblock, zijdblock, pars)
                        if len(trmblock) > 2:
                            if inlt == 0:
                                donlt()
                                inlt = 1
                            blab = field
                            best = pars["specimen_int"]
                            Bs, TRMs = [], []
                            for trec in trmblock:
                                Bs.append(float(trec['treatment_dc_field']))
                                TRMs.append(
                                    float(trec['measurement_magn_moment']))
                            NLpars = nlt.NLtrm(
                                Bs, TRMs, best, blab, 0
                            )  # calculate best fit parameters through TRM acquisition data, and get new banc
                            #
                            Mp, Bp = [], []
                            for k in range(int(max(Bs) * 1e6)):
                                Bp.append(float(k) * 1e-6)
                                npred = nlt.TRM(
                                    Bp[-1], NLpars['xopt'][0], NLpars['xopt']
                                    [1])  # predicted NRM for this field
                    files = {}
                    for key in AZD.keys():
                        files[key] = s + '_' + key + fmt
                    pmagplotlib.saveP(AZD, files)
                    sys.exit()
                if plots == 0:
                    ans = 'b'
                    while ans != "":
                        print """
               s[a]ve plot, set [b]ounds for calculation, [d]elete current interpretation, [p]revious, [s]ample, [q]uit:
               """
                        ans = raw_input('Return for next specimen \n')
                        if ans == "":
                            specimen += 1
                        if ans == "d":
                            save_redo(PriorRecs, inspec)
                            CurrRec = []
                            pmagplotlib.plotAZ(AZD, araiblock, zijdblock, s,
                                               units[0])
                            pmagplotlib.drawFIGS(AZD)
                        if ans == 'a':
                            files = {}
                            for key in AZD.keys():
                                files[key] = s + '_' + key + fmt
                            pmagplotlib.saveP(AZD, files)
                            ans = ""
                        if ans == 'q':
                            print "Good bye"
                            sys.exit()
                        if ans == 'p':
                            specimen = specimen - 1
                            backup = 1
                            ans = ""
                        if ans == 's':
                            keepon = 1
                            spec = raw_input(
                                'Enter desired specimen name (or first part there of): '
                            )
                            while keepon == 1:
                                try:
                                    specimen = sids.index(spec)
                                    keepon = 0
                                except:
                                    tmplist = []
                                    for qq in range(len(sids)):
                                        if spec in sids[qq]:
                                            tmplist.append(sids[qq])
                                    print specimen, " not found, but this was: "
                                    print tmplist
                                    spec = raw_input(
                                        'Select one or try again\n ')
                            ans = ""
                        if ans == 'b':
                            if end == 0 or end >= len(araiblock[0]):
                                end = len(araiblock[0]) - 1
                            GoOn = 0
                            while GoOn == 0:
                                print 'Enter index of first point for calculation: ', '[', start, ']'
                                answer = raw_input('return to keep default  ')
                                if answer != "": start = int(answer)
                                print 'Enter index  of last point for calculation: ', '[', end, ']'
                                answer = raw_input('return to keep default  ')
                                if answer != "":
                                    end = int(answer)
                                if start >= 0 and start < len(araiblock[
                                        0]) - 2 and end > 0 and end < len(
                                            araiblock[0]) and start < end:
                                    GoOn = 1
                                else:
                                    print "Bad endpoints - try again! "
                                    start, end = 0, len(araiblock)
                            s = sids[specimen]
                            pars, errcode = pmag.PintPars(
                                araiblock, zijdblock, start, end)
                            pars['measurement_step_unit'] = "J"
                            pars["specimen_lab_field_dc"] = field
                            pars["specimen_int"] = -1 * field * pars[
                                "specimen_b"]
                            pars["er_specimen_name"] = s
                            pars = pmag.scoreit(pars, PmagSpecRec, accept, '',
                                                0)
                            PmagSpecRec["measurement_step_min"] = '%8.3e' % (
                                pars["measurement_step_min"])
                            PmagSpecRec["measurement_step_max"] = '%8.3e' % (
                                pars["measurement_step_max"])
                            PmagSpecRec["measurement_step_unit"] = "J"
                            PmagSpecRec["specimen_int_n"] = '%i' % (
                                pars["specimen_int_n"])
                            PmagSpecRec["specimen_lab_field_dc"] = '%8.3e' % (
                                pars["specimen_lab_field_dc"])
                            PmagSpecRec["specimen_int"] = '%8.3e ' % (
                                pars["specimen_int"])
                            PmagSpecRec["specimen_b"] = '%5.3f ' % (
                                pars["specimen_b"])
                            PmagSpecRec["specimen_q"] = '%5.1f ' % (
                                pars["specimen_q"])
                            PmagSpecRec["specimen_f"] = '%5.3f ' % (
                                pars["specimen_f"])
                            PmagSpecRec["specimen_fvds"] = '%5.3f' % (
                                pars["specimen_fvds"])
                            PmagSpecRec["specimen_b_beta"] = '%5.3f' % (
                                pars["specimen_b_beta"])
                            PmagSpecRec["specimen_int_mad"] = '%7.1f' % (
                                pars["specimen_int_mad"])
                            PmagSpecRec["specimen_Z"] = '%7.1f' % (
                                pars["specimen_Z"])
                            if pars["method_codes"] != "":
                                tmpcodes = pars["method_codes"].split(":")
                                for t in tmpcodes:
                                    if t.strip() not in methcodes:
                                        methcodes.append(t.strip())
                            PmagSpecRec["specimen_dec"] = '%7.1f' % (
                                pars["specimen_dec"])
                            PmagSpecRec["specimen_inc"] = '%7.1f' % (
                                pars["specimen_inc"])
                            PmagSpecRec["specimen_tilt_correction"] = '-1'
                            PmagSpecRec["specimen_direction_type"] = 'l'
                            PmagSpecRec[
                                "direction_type"] = 'l'  # this is redudant, but helpful - won't be imported
                            PmagSpecRec["specimen_dang"] = '%7.1f ' % (
                                pars["specimen_dang"])
                            PmagSpecRec["specimen_drats"] = '%7.1f ' % (
                                pars["specimen_drats"])
                            PmagSpecRec["specimen_int_ptrm_n"] = '%i ' % (
                                pars["specimen_int_ptrm_n"])
                            PmagSpecRec["specimen_rsc"] = '%6.4f ' % (
                                pars["specimen_rsc"])
                            PmagSpecRec["specimen_md"] = '%i ' % (int(
                                pars["specimen_md"]))
                            if PmagSpecRec["specimen_md"] == '-1':
                                PmagSpecRec["specimen_md"] = ""
                            PmagSpecRec["specimen_b_sigma"] = '%5.3f ' % (
                                pars["specimen_b_sigma"])
                            if "IE-TT" not in methcodes:
                                methcodes.append("IE-TT")
                            methods = ""
                            for meth in methcodes:
                                methods = methods + meth + ":"
                            PmagSpecRec["magic_method_codes"] = methods[:-1]
                            PmagSpecRec["specimen_description"] = comment
                            PmagSpecRec[
                                "magic_software_packages"] = version_num
                            pmagplotlib.plotAZ(AZD, araiblock, zijdblock, s,
                                               units[0])
                            pmagplotlib.plotB(AZD, araiblock, zijdblock, pars)
                            if len(trmblock) > 2:
                                blab = field
                                best = pars["specimen_int"]
                                Bs, TRMs = [], []
                                for trec in trmblock:
                                    Bs.append(float(
                                        trec['treatment_dc_field']))
                                    TRMs.append(
                                        float(trec['measurement_magn_moment']))
                                NLpars = nlt.NLtrm(
                                    Bs, TRMs, best, blab, 0
                                )  # calculate best fit parameters through TRM acquisition data, and get new banc
                                Mp, Bp = [], []
                                for k in range(int(max(Bs) * 1e6)):
                                    Bp.append(float(k) * 1e-6)
                                    npred = nlt.TRM(
                                        Bp[-1], NLpars['xopt'][0],
                                        NLpars['xopt']
                                        [1])  # predicted NRM for this field
                                    Mp.append(npred)
                                pmagplotlib.plotTRM(
                                    AZD['MRM'], Bs, TRMs, Bp, Mp, NLpars,
                                    trec['magic_experiment_name'])
                                print 'Banc= ', float(NLpars['banc']) * 1e6
                            pmagplotlib.drawFIGS(AZD)
                            pars["specimen_lab_field_dc"] = field
                            pars["specimen_int"] = -1 * field * pars[
                                "specimen_b"]
                            saveit = raw_input(
                                "Save this interpretation? [y]/n \n")
                            if saveit != 'n':
                                specimen += 1
                                PriorRecs.append(
                                    PmagSpecRec)  # put back an interpretation
                                save_redo(PriorRecs, inspec)
                            ans = ""
                else:
                    specimen += 1
                    if fmt != ".pmag":
                        basename = s + '_microwave' + fmt
                        files = {}
                        for key in AZD.keys():
                            files[key] = s + '_' + key + fmt
                        if pmagplotlib.isServer:
                            black = '#000000'
                            purple = '#800080'
                            titles = {}
                            titles['deremag'] = 'DeReMag Plot'
                            titles['zijd'] = 'Zijderveld Plot'
                            titles['arai'] = 'Arai Plot'
                            AZD = pmagplotlib.addBorders(
                                AZD, titles, black, purple)
                        pmagplotlib.saveP(AZD, files)
    #                   pmagplotlib.combineFigs(s,files,3)
        if len(CurrRec) > 0:
            for rec in CurrRec:
                PriorRecs.append(rec)
        CurrRec = []
    if plots != 1:
        ans = raw_input(" Save last plot? 1/[0] ")
        if ans == "1":
            if fmt != ".pmag":
                files = {}
                for key in AZD.keys():
                    files[key] = s + '_' + key + fmt
                pmagplotlib.saveP(AZD, files)
        if len(CurrRec) > 0:
            PriorRecs.append(CurrRec)  # put back an interpretation
        if len(PriorRecs) > 0:
            save_redo(PriorRecs, inspec)
            print 'Updated interpretations saved in ', inspec
    if pmagplotlib.verbose:
        print "Good bye"
Beispiel #2
0
def main():
    """
    NAME
        thellier_magic.py
    
    DESCRIPTION
        plots Thellier-Thellier, allowing interactive setting of bounds
        and customizing of selection criteria.  Saves and reads interpretations
        from a pmag_specimen formatted table, default: thellier_specimens.txt

    SYNTAX 
        thellier_magic.py [command line options]

    OPTIONS
        -h prints help message and quits
        -f MEAS, set magic_measurements input file
        -fsp PRIOR, set pmag_specimen prior interpretations file
        -fan ANIS, set rmag_anisotropy file for doing the anisotropy corrections
        -fcr CRIT, set criteria file for grading.  
        -fmt [svg,png,jpg], format for images - default is svg
        -sav,  saves plots with out review (default format)
        -spc SPEC, plots single specimen SPEC, saves plot with specified format
            with optional -b bounds adn quits
        -b BEG END: sets  bounds for calculation
           BEG: starting step for slope calculation
           END: ending step for slope calculation
        -z use only z component difference for pTRM calculation
        
    DEFAULTS
        MEAS: magic_measurements.txt
        REDO: thellier_redo
        CRIT: NONE
        PRIOR: NONE
  
    OUTPUT 
        figures:
            ALL:  numbers refer to temperature steps in command line window
            1) Arai plot:  closed circles are zero-field first/infield
                           open circles are infield first/zero-field
                           triangles are pTRM checks
                           squares are pTRM tail checks
                           VDS is vector difference sum
                           diamonds are bounds for interpretation
            2) Zijderveld plot:  closed (open) symbols are X-Y (X-Z) planes
                                 X rotated to NRM direction
            3) (De/Re)Magnetization diagram:
                           circles are NRM remaining
                           squares are pTRM gained
            4) equal area projections:
 			   green triangles are pTRM gained direction
                           red (purple) circles are lower(upper) hemisphere of ZI step directions 
                           blue (cyan) squares are lower(upper) hemisphere IZ step directions 
            5) Optional:  TRM acquisition
            6) Optional: TDS normalization
        command line window:
            list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of magic_measuements)
                     list of possible commands: type letter followed by return to select option
                     saving of plots creates .svg format files with specimen_name, plot type as name
    """ 
#
#   initializations
#
    meas_file,critout,inspec="magic_measurements.txt","","thellier_specimens.txt"
    first=1
    inlt=0
    version_num=pmag.get_version()
    TDinit,Tinit,field,first_save=0,0,-1,1
    user,comment,AniSpec,locname="",'',"",""
    ans,specimen,recnum,start,end=0,0,0,0,0
    plots,pmag_out,samp_file,style=0,"","","svg"
    verbose=pmagplotlib.verbose 
    fmt='.'+style
#
# default acceptance criteria
#
    accept=pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
    Zdiff,anis=0,0
    spc,BEG,END="","",""
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-f' in sys.argv:
        ind=sys.argv.index('-f')
        meas_file=sys.argv[ind+1]
    if '-fsp' in sys.argv:
        ind=sys.argv.index('-fsp')
        inspec=sys.argv[ind+1]
    if '-fan' in sys.argv:
        ind=sys.argv.index('-fan')
        anisfile=sys.argv[ind+1]
        anis=1
        anis_data,file_type=pmag.magic_read(anisfile)
        if verbose: print "Anisotropy data read in from ", anisfile
    if '-fmt' in sys.argv:
        ind=sys.argv.index('-fmt')
        fmt='.'+sys.argv[ind+1]
    if '-dpi' in sys.argv:
        ind=sys.argv.index('-dpi')
        dpi='.'+sys.argv[ind+1]
    else: dpi=100
    if '-sav' in sys.argv: 
        plots=1
        verbose=0
    if '-z' in sys.argv: Zdiff=1
    if '-spc' in sys.argv:
        ind=sys.argv.index('-spc')
        spc=sys.argv[ind+1]
        if '-b' in sys.argv:
            ind=sys.argv.index('-b')
            BEG=int(sys.argv[ind+1])
            END=int(sys.argv[ind+2])
    if '-fcr' in sys.argv:
        ind=sys.argv.index('-fcr')
        critout=sys.argv[ind+1]
        crit_data,file_type=pmag.magic_read(critout)
        if file_type!='pmag_criteria':
            if verbose: print 'bad pmag_criteria file, using no acceptance criteria'
            accept=pmag.default_criteria(1)[0]
        else:
            if verbose: print "Acceptance criteria read in from ", critout
            accept={'pmag_criteria_code':'ACCEPTANCE','er_citation_names':'This study'}
            for critrec in crit_data:
                if 'sample_int_sigma_uT' in critrec.keys(): # accommodate Shaar's new criterion
                    critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
                for key in critrec.keys():
                    if key not in accept.keys() and critrec[key]!='':
                        accept[key]=critrec[key]
    try:
        open(inspec,'rU')
        PriorRecs,file_type=pmag.magic_read(inspec)
        if file_type != 'pmag_specimens':
            print file_type
            print file_type,inspec," is not a valid pmag_specimens file " 
            sys.exit()
        for rec in PriorRecs:
            if 'magic_software_packages' not in rec.keys():rec['magic_software_packages']=""
    except IOError:
        PriorRecs=[]
        if verbose:print "starting new specimen interpretation file: ",inspec
    meas_data,file_type=pmag.magic_read(meas_file)
    if file_type != 'magic_measurements':
        print file_type
        print file_type,"This is not a valid magic_measurements file " 
        sys.exit()
    backup=0
    # define figure numbers for arai, zijderveld and 
    #   de-,re-magization diagrams
    AZD={}
    AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
    pmagplotlib.plot_init(AZD['arai'],5,5)
    pmagplotlib.plot_init(AZD['zijd'],5,5)
    pmagplotlib.plot_init(AZD['deremag'],5,5)
    pmagplotlib.plot_init(AZD['eqarea'],5,5)
    #
    #
    #
    # get list of unique specimen names
    #
    CurrRec=[]
    sids=pmag.get_specs(meas_data)
    # get plots for specimen s - default is just to step through arai diagrams
    #
    if spc!="": specimen =sids.index(spc)
    while specimen < len(sids):
        methcodes=[]
       
        if verbose:
            print sids[specimen],specimen+1, 'of ', len(sids)
        MeasRecs=[]
        s=sids[specimen]
        datablock,trmblock,tdsrecs=[],[],[]
        PmagSpecRec={}
        if first==0:
           for key in keys:PmagSpecRec[key]="" # make sure all new records have same set of keys
        PmagSpecRec["er_analyst_mail_names"]=user
        PmagSpecRec["specimen_correction"]='u'
    #
    # find the data from the meas_data file for this specimen
    #
        for rec in meas_data:
            if rec["er_specimen_name"]==s:
                MeasRecs.append(rec)
                if "magic_method_codes" not in rec.keys():
                    rec["magic_method_codes"]=""
                methods=rec["magic_method_codes"].split(":")
                meths=[]
                for meth in methods:
                    meths.append(meth.strip()) # take off annoying spaces
                methods=""
                for meth in meths:
                    if meth.strip() not in methcodes and "LP-" in meth:methcodes.append(meth.strip())
                    methods=methods+meth+":"
                methods=methods[:-1]
                rec["magic_method_codes"]=methods 
                if "LP-PI-TRM" in meths: datablock.append(rec)
                if "LP-TRM" in meths: trmblock.append(rec)
                if "LP-TRM-TD" in meths: tdsrecs.append(rec)
        if len(trmblock)>2 and inspec!="":
            if Tinit==0:
                Tinit=1
                AZD['TRM']=5
                pmagplotlib.plot_init(AZD['TRM'],5,5)
        elif Tinit==1: # clear the TRM figure if not needed
            pmagplotlib.clearFIG(AZD['TRM'])
        if len(tdsrecs)>2:
            if TDinit==0:
                TDinit=1
                AZD['TDS']=6
                pmagplotlib.plot_init(AZD['TDS'],5,5)
        elif TDinit==1: # clear the TDS figure if not needed
            pmagplotlib.clearFIG(AZD['TDS'])
        if len(datablock) <4:
           if backup==0:
               specimen+=1
               if verbose:
                   print 'skipping specimen - moving forward ', s
           else:
               specimen-=1
               if verbose:
                   print 'skipping specimen - moving backward ', s
    #
    #  collect info for the PmagSpecRec dictionary
    #
        else:
           rec=datablock[0]
           PmagSpecRec["er_citation_names"]="This study"
           PmagSpecRec["er_specimen_name"]=s
           PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
           PmagSpecRec["er_site_name"]=rec["er_site_name"]
           PmagSpecRec["er_location_name"]=rec["er_location_name"]
           locname=rec['er_location_name'].replace('/','-')
           if "er_expedition_name" in rec.keys():PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
           if "magic_instrument_codes" not in rec.keys():rec["magic_instrument_codes"]=""
           PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"]
           PmagSpecRec["measurement_step_unit"]="K"
           if "magic_experiment_name" not in rec.keys():
               rec["magic_experiment_name"]=""
           else:
               PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
    
           meths=rec["magic_method_codes"].split()
       # sort data into types
           araiblock,field=pmag.sortarai(datablock,s,Zdiff)
           first_Z=araiblock[0]
           GammaChecks=araiblock[5]
           if len(first_Z)<3:
               if backup==0:
                   specimen+=1
                   if verbose:
                       print 'skipping specimen - moving forward ', s
               else:
                   specimen-=1
                   if verbose:
                       print 'skipping specimen - moving backward ', s
           else:
               backup=0
               zijdblock,units=pmag.find_dmag_rec(s,meas_data)
               recnum=0
               if verbose:
                   print "index step Dec   Inc  Int       Gamma"
                   for plotrec in zijdblock:
                       if GammaChecks!="":
                           gamma=""
                           for g in GammaChecks:
                               if g[0]==plotrec[0]-273:
                                   gamma=g[1]
                                   break
                       if gamma!="":
                           print '%i     %i %7.1f %7.1f %8.3e %7.1f' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3],gamma)
                       else:
                           print '%i     %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3])
                       recnum += 1
               pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
               if verbose:pmagplotlib.drawFIGS(AZD)
               if len(tdsrecs)>2: # a TDS experiment
                   tdsblock=[] # make a list for the TDS  data
                   Mkeys=['measurement_magnitude','measurement_magn_moment','measurement_magn_volume','measuruement_magn_mass']
                   mkey,k="",0
                   while mkey=="" and k<len(Mkeys)-1: # find which type of intensity
                       key= Mkeys[k]
                       if key in tdsrecs[0].keys() and tdsrecs[0][key]!="": mkey=key
                       k+=1
                   if mkey=="":break # get outta here
                   Tnorm=""
                   for tdrec in tdsrecs:
                       meths=tdrec['magic_method_codes'].split(":")
                       for meth in meths: meth.replace(" ","") # strip off potential nasty spaces
                       if  'LT-T-I' in meths and Tnorm=="": # found first total TRM 
                           Tnorm=float(tdrec[mkey]) # normalize by total TRM 
                           tdsblock.append([273,zijdblock[0][3]/Tnorm,1.]) # put in the zero step
                       if  'LT-T-Z' in meths and Tnorm!="": # found a LP-TRM-TD demag step, now need complementary LT-T-Z from zijdblock
                           step=float(tdrec['treatment_temp'])
                           Tint=""
                           if mkey!="":
                               Tint=float(tdrec[mkey])
                           if Tint!="":
                               for zrec in zijdblock:
                                   if zrec[0]==step:  # found matching
                                       tdsblock.append([step,zrec[3]/Tnorm,Tint/Tnorm])
                                       break
                   if len(tdsblock)>2: 
                       pmagplotlib.plotTDS(AZD['TDS'],tdsblock,s+':LP-PI-TDS:')
                       if verbose:pmagplotlib(drawFIGS(AZD)) 
                   else: 
                       print "Something wrong here"
               if anis==1:   # look up anisotropy data for this specimen
                   AniSpec=""
                   for aspec in anis_data:
                       if aspec["er_specimen_name"]==PmagSpecRec["er_specimen_name"]:
                           AniSpec=aspec
                           if verbose: print 'Found anisotropy record...'
                           break
               if inspec !="":
                   if verbose: print 'Looking up saved interpretation....'
                   found = 0
                   for k in range(len(PriorRecs)):
                       try:
                         if PriorRecs[k]["er_specimen_name"]==s:
                           found =1
                           CurrRec.append(PriorRecs[k])
                           for j in range(len(zijdblock)):
                               if float(zijdblock[j][0])==float(PriorRecs[k]["measurement_step_min"]):start=j
                               if float(zijdblock[j][0])==float(PriorRecs[k]["measurement_step_max"]):end=j
                           pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,start,end,accept)
                           pars['measurement_step_unit']="K"
                           pars['experiment_type']='LP-PI-TRM'
                           del PriorRecs[k]  # put in CurrRec, take out of PriorRecs
                           if errcode!=1:
                               pars["specimen_lab_field_dc"]=field
                               pars["specimen_int"]=-1*field*pars["specimen_b"]
                               pars["er_specimen_name"]=s
                               if verbose:
                                   print 'Saved interpretation: '
                               pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',verbose)
                               pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                               if verbose:pmagplotlib.drawFIGS(AZD)
                               if len(trmblock)>2:
                                   blab=field
                                   best=pars["specimen_int"]
                                   Bs,TRMs=[],[]
                                   for trec in trmblock:
                                       Bs.append(float(trec['treatment_dc_field']))
                                       TRMs.append(float(trec['measurement_magn_moment']))
                                   NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
                                   Mp,Bp=[],[]
                                   for k in  range(int(max(Bs)*1e6)):
                                       Bp.append(float(k)*1e-6)
                                       npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
                                       Mp.append(npred)
                                   pmagplotlib.plotTRM(AZD['TRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
                                   PmagSpecRec['specimen_int']=NLpars['banc'] 
                                   if verbose:
                                       print 'Banc= ',float(NLpars['banc'])*1e6
                                       pmagplotlib.drawFIGS(AZD)
                               mpars=pmag.domean(araiblock[1],start,end,'DE-BFL')
                               if verbose:
                                       print 'pTRM direction= ','%7.1f'%(mpars['specimen_dec']),' %7.1f'%(mpars['specimen_inc']),' MAD:','%7.1f'%(mpars['specimen_mad'])
                               if AniSpec!="":
                                   CpTRM=pmag.Dir_anis_corr([mpars['specimen_dec'],mpars['specimen_inc']],AniSpec)
                                   AniSpecRec=pmag.doaniscorr(PmagSpecRec,AniSpec)
                                   if verbose:
                                       print 'Anisotropy corrected TRM direction= ','%7.1f'%(CpTRM[0]),' %7.1f'%(CpTRM[1])
                                       print 'Anisotropy corrected intensity= ',float(AniSpecRec['specimen_int'])*1e6
                           else:
                               print 'error on specimen ',s
                       except:
                         pass
                   if verbose and found==0: print  '    None found :(  ' 
               if spc!="":
                   if BEG!="": 
                       pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,BEG,END,accept)
                       pars['measurement_step_unit']="K"
                       pars["specimen_lab_field_dc"]=field
                       pars["specimen_int"]=-1*field*pars["specimen_b"]
                       pars["er_specimen_name"]=s
                       pars['specimen_grade']='' # ungraded
                       pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                       if verbose:pmagplotlib.drawFIGS(AZD)
                       if len(trmblock)>2:
                           if inlt==0:
                               inlt=1
                           blab=field
                           best=pars["specimen_int"]
                           Bs,TRMs=[],[]
                           for trec in trmblock:
                               Bs.append(float(trec['treatment_dc_field']))
                               TRMs.append(float(trec['measurement_magn_moment']))
                           NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
    #
                           Mp,Bp=[],[]
                           for k in  range(int(max(Bs)*1e6)):
                               Bp.append(float(k)*1e-6)
                               npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
                   files={}
                   for key in AZD.keys():
                       files[key]=s+'_'+key+fmt 
                   pmagplotlib.saveP(AZD,files,dpi=dpi)
                   sys.exit()
               if verbose:
                   ans='b'
                   while ans != "":
                       print """
               s[a]ve plot, set [b]ounds for calculation, [d]elete current interpretation, [p]revious, [s]ample, [q]uit:
               """
                       ans=raw_input('Return for next specimen \n')
                       if ans=="": 
                           specimen +=1
                       if ans=="d": 
                           save_redo(PriorRecs,inspec)
                           CurrRec=[]
                           pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
                           if verbose:pmagplotlib.drawFIGS(AZD)
                       if ans=='a':
                           files={}
                           for key in AZD.keys():
                               files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_s_TY:_'+key+fmt
                           pmagplotlib.saveP(AZD,files)
                           ans=""
                       if ans=='q':
                           print "Good bye"
                           sys.exit()
                       if ans=='p':
                           specimen =specimen -1
                           backup = 1
                           ans=""
                       if ans=='s':
                           keepon=1
                           spec=raw_input('Enter desired specimen name (or first part there of): ')
                           while keepon==1:
                               try:
                                   specimen =sids.index(spec)
                                   keepon=0
                               except:
                                   tmplist=[]
                                   for qq in range(len(sids)):
                                       if spec in sids[qq]:tmplist.append(sids[qq])
                                   print specimen," not found, but this was: "
                                   print tmplist
                                   spec=raw_input('Select one or try again\n ')
                           ans=""
                       if  ans=='b':
                           if end==0 or end >=len(zijdblock):end=len(zijdblock)-1
                           GoOn=0
                           while GoOn==0:
                               answer=raw_input('Enter index of first point for calculation: ['+str(start)+']  ')
                               try:
                                   start=int(answer)
                                   answer=raw_input('Enter index  of last point for calculation: ['+str(end)+']  ')
                                   end=int(answer)
                                   if start >=0 and start <len(zijdblock)-2 and end >0 and end <len(zijdblock) or start>=end:
                                       GoOn=1
                                   else:
                                       print "Bad endpoints - try again! "
                                       start,end=0,len(zijdblock)
                               except ValueError:
                                   print "Bad endpoints - try again! "
                                   start,end=0,len(zijdblock)
                           s=sids[specimen] 
                           pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,start,end,accept)
                           pars['measurement_step_unit']="K"
                           pars["specimen_lab_field_dc"]=field
                           pars["specimen_int"]=-1*field*pars["specimen_b"]
                           pars["er_specimen_name"]=s
                           pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',0)
                           PmagSpecRec['specimen_scat']=pars['specimen_scat']
                           PmagSpecRec['specimen_frac']='%5.3f'%(pars['specimen_frac'])
                           PmagSpecRec['specimen_gmax']='%5.3f'%(pars['specimen_gmax'])
                           PmagSpecRec["measurement_step_min"]='%8.3e' % (pars["measurement_step_min"])
                           PmagSpecRec["measurement_step_max"]='%8.3e' % (pars["measurement_step_max"])
                           PmagSpecRec["measurement_step_unit"]="K"
                           PmagSpecRec["specimen_int_n"]='%i'%(pars["specimen_int_n"])
                           PmagSpecRec["specimen_lab_field_dc"]='%8.3e'%(pars["specimen_lab_field_dc"])
                           PmagSpecRec["specimen_int"]='%9.4e '%(pars["specimen_int"])
                           PmagSpecRec["specimen_b"]='%5.3f '%(pars["specimen_b"])
                           PmagSpecRec["specimen_q"]='%5.1f '%(pars["specimen_q"])
                           PmagSpecRec["specimen_f"]='%5.3f '%(pars["specimen_f"])
                           PmagSpecRec["specimen_fvds"]='%5.3f'%(pars["specimen_fvds"])
                           PmagSpecRec["specimen_b_beta"]='%5.3f'%(pars["specimen_b_beta"])
                           PmagSpecRec["specimen_int_mad"]='%7.1f'%(pars["specimen_int_mad"])
                           PmagSpecRec["specimen_Z"]='%7.1f'%(pars["specimen_Z"])
                           PmagSpecRec["specimen_gamma"]='%7.1f'%(pars["specimen_gamma"])
                           PmagSpecRec["specimen_grade"]=pars["specimen_grade"]
                           if pars["method_codes"]!="":
                               tmpcodes=pars["method_codes"].split(":")
                               for t in tmpcodes:
                                   if t.strip() not in methcodes:methcodes.append(t.strip())
                           PmagSpecRec["specimen_dec"]='%7.1f'%(pars["specimen_dec"])
                           PmagSpecRec["specimen_inc"]='%7.1f'%(pars["specimen_inc"])
                           PmagSpecRec["specimen_tilt_correction"]='-1'
                           PmagSpecRec["specimen_direction_type"]='l'
                           PmagSpecRec["direction_type"]='l' # this is redundant, but helpful - won't be imported
                           PmagSpecRec["specimen_int_dang"]='%7.1f '%(pars["specimen_int_dang"])
                           PmagSpecRec["specimen_drats"]='%7.1f '%(pars["specimen_drats"])
                           PmagSpecRec["specimen_drat"]='%7.1f '%(pars["specimen_drat"])
                           PmagSpecRec["specimen_int_ptrm_n"]='%i '%(pars["specimen_int_ptrm_n"])
                           PmagSpecRec["specimen_rsc"]='%6.4f '%(pars["specimen_rsc"])
                           PmagSpecRec["specimen_md"]='%i '%(int(pars["specimen_md"]))
                           if PmagSpecRec["specimen_md"]=='-1':PmagSpecRec["specimen_md"]=""
                           PmagSpecRec["specimen_b_sigma"]='%5.3f '%(pars["specimen_b_sigma"])
                           if "IE-TT" not in  methcodes:methcodes.append("IE-TT")
                           methods=""
                           for meth in methcodes:
                               methods=methods+meth+":"
                           PmagSpecRec["magic_method_codes"]=methods[:-1]
                           PmagSpecRec["specimen_description"]=comment
                           PmagSpecRec["magic_software_packages"]=version_num
                           pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
                           pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                           if verbose:pmagplotlib.drawFIGS(AZD)
                           if len(trmblock)>2:
                               blab=field
                               best=pars["specimen_int"]
                               Bs,TRMs=[],[]
                               for trec in trmblock:
                                   Bs.append(float(trec['treatment_dc_field']))
                                   TRMs.append(float(trec['measurement_magn_moment']))
                               NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
                               Mp,Bp=[],[]
                               for k in  range(int(max(Bs)*1e6)):
                                   Bp.append(float(k)*1e-6)
                                   npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
                                   Mp.append(npred)
                               pmagplotlib.plotTRM(AZD['TRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
                               if verbose:
                                   print 'Non-linear TRM corrected intensity= ',float(NLpars['banc'])*1e6
                           if verbose:pmagplotlib.drawFIGS(AZD)
                           pars["specimen_lab_field_dc"]=field
                           pars["specimen_int"]=-1*field*pars["specimen_b"]
                           pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',verbose)
                           saveit=raw_input("Save this interpretation? [y]/n \n")
                           if saveit!='n':
                               PriorRecs.append(PmagSpecRec) # put back an interpretation
                               specimen+=1
                               save_redo(PriorRecs,inspec)
                           ans=""
               elif plots==1:
                   specimen+=1
                   if fmt != ".pmag":
                       files={}
                       for key in AZD.keys():
                           files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_s_TY:_'+key+'_'+fmt
                       if pmagplotlib.isServer:
                           black     = '#000000'
                           purple    = '#800080'
                           titles={}
                           titles['deremag']='DeReMag Plot'
                           titles['zijd']='Zijderveld Plot'
                           titles['arai']='Arai Plot'
                           AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
                       pmagplotlib.saveP(AZD,files,dpi=dpi)
    #                   pmagplotlib.combineFigs(s,files,3)
                   else:  # save in pmag format 
                       script="grep "+s+" output.mag | thellier -mfsi"
                       script=script+' %8.4e'%(field)
                       min='%i'%((pars["measurement_step_min"]-273))
                       Max='%i'%((pars["measurement_step_max"]-273))
                       script=script+" "+min+" "+Max
                       script=script+" |plotxy;cat mypost >>thellier.ps\n"
                       pltf.write(script)
                       pmag.domagicmag(outf,MeasRecs)
        if len(CurrRec)>0:
            for rec in CurrRec:
                PriorRecs.append(rec)
        CurrRec=[]
    if plots!=1 and verbose:
        ans=raw_input(" Save last plot? 1/[0] ")
        if ans=="1":
            if fmt != ".pmag":
                files={}
                for key in AZD.keys():
                    files[key]=s+'_'+key+fmt
                pmagplotlib.saveP(AZD,files,dpi=dpi)
        else:
            print "\n Good bye\n"
            sys.exit()
        if len(CurrRec)>0:PriorRecs.append(CurrRec) # put back an interpretation
        if len(PriorRecs)>0:
            save_redo(PriorRecs,inspec)
            print 'Updated interpretations saved in ',inspec
    if verbose:
        print "Good bye"
Beispiel #3
0
def main():
    """
    NAME
        thellier_magic.py

    DESCRIPTION
        plots Thellier-Thellier data in version 3.0 format
        Reads saved interpretations from a specimen formatted table, default: specimens.txt

    SYNTAX
        thellier_magic.py [command line options]

    OPTIONS
        -h prints help message and quits
        -f MEAS, set measurements input file, default is 'measurements.txt'
        -fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
        -fcr CRIT, set criteria file for grading.  # not yet implemented
        -fmt [svg,png,jpg], format for images - default is svg
        -sav,  saves plots with out review (in format specified by -fmt key or default)
        -spc SPEC, plots single specimen SPEC, saves plot with specified format
            with optional -b bounds and quits
        -b BEG END: sets  bounds for calculation
           BEG: starting step number for slope calculation
           END: ending step number for slope calculation
        -z use only z component difference for pTRM calculation

    OUTPUT
        figures:
            ALL:  numbers refer to temperature steps in command line window
            1) Arai plot:  closed circles are zero-field first/infield
                           open circles are infield first/zero-field
                           triangles are pTRM checks
                           squares are pTRM tail checks
                           VDS is vector difference sum
                           diamonds are bounds for interpretation
            2) Zijderveld plot:  closed (open) symbols are X-Y (X-Z) planes
                                 X rotated to NRM direction
            3) (De/Re)Magnetization diagram:
                           circles are NRM remaining
                           squares are pTRM gained
            4) equal area projections:
               green triangles are pTRM gained direction
                           red (purple) circles are lower(upper) hemisphere of ZI step directions
                           blue (cyan) squares are lower(upper) hemisphere IZ step directions
            5) Optional:  TRM acquisition
            6) Optional: TDS normalization
        command line window:
            list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of measuements)
                     list of possible commands: type letter followed by return to select option
                     saving of plots creates image files with specimen, plot type as name
    """
#
#   initializations
#
    version_num=pmag.get_version()
    verbose=pmagplotlib.verbose
#
# default acceptance criteria
#
    accept=pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
    plots,fmt,Zdiff=0,'svg',0
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
    meas_file = pmag.get_named_arg_from_sys("-f", default_val="measurements.txt")
    spec_file=pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
    crit_file=pmag.get_named_arg_from_sys("-fcr", default_val="criteria.txt")
    spec_file=os.path.join(dir_path,spec_file)
    meas_file=os.path.join(dir_path,meas_file)
    crit_file=os.path.join(dir_path,crit_file)
    fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
    if '-sav' in sys.argv: plots,verbose=1,0
    if '-z' in sys.argv: Zdiff=1
    specimen=pmag.get_named_arg_from_sys("-spc",default_val="")
    if '-b' in sys.argv:
        ind=sys.argv.index('-b')
        start=int(sys.argv[ind+1])
        end=int(sys.argv[ind+2])
    else:
        start,end="",""
    fnames = {'measurements': meas_file, 'specimens': spec_file, 'criteria': crit_file}
    contribution = nb.Contribution(dir_path, custom_filenames=fnames, read_tables=['measurements', 'specimens', 'criteria'])
#
#   import  prior interpretations  from specimen file
#
    specimen_cols = ['analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s', 'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma', 'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1', 'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95', 'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements', 'dir_tilt_correction', 'experiments', 'geologic_classes', 'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment', 'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma', 'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma', 'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q', 'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max', 'meas_step_min', 'meas_step_unit', 'method_codes', 'sample', 'software_packages', 'specimen']
    if 'specimens' in contribution.tables:
        spec_container = contribution.tables['specimens']
        prior_spec_data=spec_container.get_records_for_code('LP-PI-TRM',strict_match=False) # look up all prior intensity interpretations
    else:
           spec_container, prior_spec_data = None, []
    backup=0
    #
    Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
#
#   create measurement dataframe
#
    meas_container = contribution.tables['measurements']
    meas_data = meas_container.df
#
    meas_data['method_codes']=meas_data['method_codes'].str.replace(" ","") # get rid of nasty spaces
    meas_data= meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM|LP-TRM|LP-TRM-TD')==True] # fish out zero field steps for plotting
    intensity_types = [col_name for col_name in meas_data.columns if col_name in Mkeys]
    int_key = intensity_types[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
    meas_data = meas_data[meas_data[int_key].notnull()] # get all the non-null intensity records of the same type
    if 'flag' not in meas_data.columns: meas_data['flag'] = 'g' # set the default flag to good
    meas_data = meas_data[meas_data['flag'].str.contains('g')==True] # only the 'good' measurements
    thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')==True] # get all the Thellier data
    trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM')==True] # get all the TRM acquisition data
    td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD')==True] # get all the TD data
    anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN')==True] # get all the anisotropy data
#
# get list of unique specimen names from measurement data
#
    specimen_names= meas_data.specimen.unique() # this is a Series of all the specimen names
    specimen_names= specimen_names.tolist() # turns it into a list
    specimen_names.sort() # sorts by specimen name
#
# set up new DataFrame for this sessions specimen interpretations
#
    spec_container = nb.MagicDataFrame(dtype='specimens', columns=specimen_cols)
    current_spec_data = spec_container.df # this is for interpretations from this session
    if specimen=="": # do all specimens
        k = 0
    else:
        k=specimen_names.index(specimen) # just do this one
    # define figure numbers for arai, zijderveld and
    #   de-,re-magnetization diagrams
    AZD={}
    AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
    pmagplotlib.plot_init(AZD['arai'],5,5)
    pmagplotlib.plot_init(AZD['zijd'],5,5)
    pmagplotlib.plot_init(AZD['deremag'],5,5)
    pmagplotlib.plot_init(AZD['eqarea'],5,5)
    if len(trm_data)>0:
        AZD['TRM']=5
        pmagplotlib.plot_init(AZD['TRM'],5,5)
    if len(td_data)>0:
        AZD['TDS']=6
        pmagplotlib.plot_init(AZD['TDS'],5,5)
    #
    while k < len(specimen_names):
        this_specimen=specimen_names[k] # set the current specimen for plotting
        if verbose and  this_specimen!="":print(this_specimen, k+1 , 'out of ',len(specimen_names))
#
#    set up datablocks
#
        thelblock= thel_data[thel_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
        trmblock= trm_data[trm_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
        tdsrecs= td_data[td_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
        anisblock= anis_data[anis_data['specimen'].str.contains(this_specimen)==True] # fish out the anisotropy data
        prior_specimen_interpretations= prior_spec_data[prior_spec_data['specimen'].str.contains(this_specimen)==True] # fish out prior interpretation
#
# sort data into types
#
        araiblock,field=pmag.sortarai(thelblock,this_specimen,Zdiff,version=3)
        first_Z=araiblock[0]
        GammaChecks=araiblock[5]
        if len(first_Z)<3:
           if backup==0:
                   k+=1
                   if verbose:
                       print('skipping specimen - moving forward ', this_specimen)
           else:
                   k-=1
                   if verbose:
                       print('skipping specimen - moving backward ', this_specimen)
        else:
               backup=0
               zijdblock,units=pmag.find_dmag_rec(this_specimen,thelblock,version=3)
               if start=="" and len(prior_specimen_interpretations)>0:
                   if verbose: print('Looking up saved interpretation....')
#
# get prior interpretation steps
#
                   beg_int=pd.to_numeric(prior_specimen_interpretations.meas_step_min.values).tolist()[0]
                   end_int=pd.to_numeric(prior_specimen_interpretations.meas_step_max.values).tolist()[0]
               else: beg_int,end_int="",""
               recnum=0
               if verbose: print("index step Dec   Inc  Int       Gamma")
               for plotrec in zijdblock:
                   if plotrec[0]==beg_int:start=recnum # while we are at it, collect these bounds
                   if plotrec[0]==end_int:end=recnum
                   if verbose:
                       if GammaChecks!="":
                           gamma=""
                           for g in GammaChecks:
                               if g[0]==plotrec[0]-273:
                                   gamma=g[1]
                                   break
                       if gamma!="":
                           print('%i     %i %7.1f %7.1f %8.3e %7.1f' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3],gamma))
                       else:
                           print('%i     %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3]))
                   recnum += 1
               for fig in list(AZD.keys()):pmagplotlib.clearFIG(AZD[fig]) # clear all figures
               pmagplotlib.plotAZ(AZD,araiblock,zijdblock,this_specimen,units[0])
               if verbose:pmagplotlib.drawFIGS(AZD)
               pars,errcode=pmag.PintPars(thelblock,araiblock,zijdblock,start,end,accept,version=3)
               pars['measurement_step_unit']="K"
               pars['experiment_type']='LP-PI-TRM'
#
# work on saving interpretations stuff later
#
               if errcode!=1: # no problem in PintPars
                    pars["specimen_lab_field_dc"]=field
                    pars["specimen_int"]=-1*field*pars["specimen_b"]
                    pars["er_specimen_name"]=this_specimen
                    #pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose) # deal with this later
                    pars["specimen_grade"]='None'
                    pars['measurement_step_min']=pars['meas_step_min']
                    pars['measurement_step_max']=pars['meas_step_max']
                    if pars['measurement_step_unit']=='K':
                        outstr= "specimen     Tmin  Tmax  N  lab_field  B_anc  b  q  f(coe)  Fvds  beta  MAD  Dang  Drats  Nptrm  Grade  R  MD%  sigma  Gamma_max \n"
                        pars_out= (this_specimen,(pars["meas_step_min"]-273),(pars["meas_step_max"]-273),(pars["specimen_int_n"]),1e6*(pars["specimen_lab_field_dc"]),1e6*(pars["specimen_int"]),pars["specimen_b"],pars["specimen_q"],pars["specimen_f"],pars["specimen_fvds"],pars["specimen_b_beta"],pars["int_mad_free"],pars["int_dang"],pars["int_drats"],pars["int_n_ptrm"],pars["specimen_grade"],np.sqrt(pars["specimen_rsc"]),int(pars["int_md"]), pars["specimen_b_sigma"],pars['specimen_gamma'])
                        outstring= '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f  %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out +'\n'
                    elif pars['measurement_step_unit']=='J':
                        outstr= "specimen     Wmin  Wmax  N  lab_field  B_anc  b  q  f(coe)  Fvds  beta  MAD  Dang  Drats  Nptrm  Grade  R  MD%  sigma  ThetaMax DeltaMax GammaMax\n"
                        pars_out= (this_specimen,(pars["meas_step_min"]),(pars["meas_step_max"]),(pars["specimen_int_n"]),1e6*(pars["specimen_lab_field_dc"]),1e6*(pars["specimen_int"]),pars["specimen_b"],pars["specimen_q"],pars["specimen_f"],pars["specimen_fvds"],pars["specimen_b_beta"],pars["specimen_int_mad"],pars["specimen_int_dang"],pars["specimen_drats"],pars["specimen_int_ptrm_n"],pars["specimen_grade"],np.sqrt(pars["specimen_rsc"]),int(pars["specimen_md"]), pars["specimen_b_sigma"],pars["specimen_theta"],pars["specimen_delta"],pars["specimen_gamma"])
                        outstring= '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f  %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out +'\n'
                    print(outstr)
                    print(outstring)
                    pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                    mpars=pmag.domean(araiblock[1],start,end,'DE-BFL')
                    if verbose:
                        pmagplotlib.drawFIGS(AZD)
                        print('pTRM direction= ','%7.1f'%(mpars['specimen_dec']),' %7.1f'%(mpars['specimen_inc']),' MAD:','%7.1f'%(mpars['specimen_mad']))
               if len(anisblock)>0:  # this specimen has anisotropy data
                           if verbose: print('Found anisotropy record... but ignoring for now ')
               if plots==1:
                   if fmt != "pmag":
                       files={}
                       for key in list(AZD.keys()):
                           files[key]='SP:_'+this_specimen+'_TY:_'+key+'_'+'.'+fmt
                       if pmagplotlib.isServer:
                           black     = '#000000'
                           purple    = '#800080'
                           titles={}
                           titles['deremag']='DeReMag Plot'
                           titles['zijd']='Zijderveld Plot'
                           titles['arai']='Arai Plot'
                           titles['TRM']='TRM Acquisition data'
                           AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
                       pmagplotlib.saveP(AZD,files)
                   else:  # save in pmag format
                       print('pmag format no longer supported')
                       #script="grep "+this_specimen+" output.mag | thellier -mfsi"
                       #script=script+' %8.4e'%(field)
                       #min='%i'%((pars["measurement_step_min"]-273))
                       #Max='%i'%((pars["measurement_step_max"]-273))
                       #script=script+" "+min+" "+Max
                       #script=script+" |plotxy;cat mypost >>thellier.ps\n"
                       #pltf.write(script)
                       #pmag.domagicmag(outf,MeasRecs)
               if specimen!="": sys.exit() # syonara
               if verbose:
                   ans=input('Return for next specimen, q to quit:  ')
                   if ans=='q':sys.exit()
               k+=1 # moving on
Beispiel #4
0
def main():
    """
    NAME
        thellier_magic.py

    DESCRIPTION
        plots Thellier-Thellier data in version 3.0 format
        Reads saved interpretations from a specimen formatted table, default: specimens.txt

    SYNTAX
        thellier_magic.py [command line options]

    OPTIONS
        -h prints help message and quits
        -f MEAS, set measurements input file, default is 'measurements.txt'
        -fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
        -fcr CRIT, set criteria file for grading.  # not yet implemented
        -fmt [svg,png,jpg], format for images - default is svg
        -sav,  saves plots with out review (in format specified by -fmt key or default)
        -spc SPEC, plots single specimen SPEC, saves plot with specified format
            with optional -b bounds and quits
        -b BEG END: sets  bounds for calculation
           BEG: starting step number for slope calculation
           END: ending step number for slope calculation
        -z use only z component difference for pTRM calculation

    OUTPUT
        figures:
            ALL:  numbers refer to temperature steps in command line window
            1) Arai plot:  closed circles are zero-field first/infield
                           open circles are infield first/zero-field
                           triangles are pTRM checks
                           squares are pTRM tail checks
                           VDS is vector difference sum
                           diamonds are bounds for interpretation
            2) Zijderveld plot:  closed (open) symbols are X-Y (X-Z) planes
                                 X rotated to NRM direction
            3) (De/Re)Magnetization diagram:
                           circles are NRM remaining
                           squares are pTRM gained
            4) equal area projections:
               green triangles are pTRM gained direction
                           red (purple) circles are lower(upper) hemisphere of ZI step directions
                           blue (cyan) squares are lower(upper) hemisphere IZ step directions
            5) Optional:  TRM acquisition
            6) Optional: TDS normalization
        command line window:
            list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of measuements)
                     list of possible commands: type letter followed by return to select option
                     saving of plots creates image files with specimen, plot type as name
    """
    #
    #   initializations
    #
    version_num = pmag.get_version()
    verbose = pmagplotlib.verbose
    #
    # default acceptance criteria
    #
    accept = pmag.default_criteria(0)[0]  # set the default criteria
    #
    # parse command line options
    #
    plots, fmt, Zdiff = 0, 'svg', 0
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
    meas_file = pmag.get_named_arg_from_sys("-f",
                                            default_val="measurements.txt")
    spec_file = pmag.get_named_arg_from_sys("-fsp",
                                            default_val="specimens.txt")
    crit_file = pmag.get_named_arg_from_sys("-fcr", default_val="criteria.txt")
    spec_file = os.path.join(dir_path, spec_file)
    meas_file = os.path.join(dir_path, meas_file)
    crit_file = os.path.join(dir_path, crit_file)
    fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
    if '-sav' in sys.argv: plots, verbose = 1, 0
    if '-z' in sys.argv: Zdiff = 1
    specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
    if '-b' in sys.argv:
        ind = sys.argv.index('-b')
        start = int(sys.argv[ind + 1])
        end = int(sys.argv[ind + 2])
    else:
        start, end = "", ""
    fnames = {
        'measurements': meas_file,
        'specimens': spec_file,
        'criteria': crit_file
    }
    contribution = nb.Contribution(
        dir_path,
        custom_filenames=fnames,
        read_tables=['measurements', 'specimens', 'criteria'])
    #
    #   import  prior interpretations  from specimen file
    #
    specimen_cols = [
        'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s',
        'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma',
        'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1',
        'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95',
        'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements',
        'dir_tilt_correction', 'experiments', 'geologic_classes',
        'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment',
        'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma',
        'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma',
        'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q',
        'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max',
        'meas_step_min', 'meas_step_unit', 'method_codes', 'sample',
        'software_packages', 'specimen'
    ]
    if 'specimens' in contribution.tables:
        spec_container = contribution.tables['specimens']
        prior_spec_data = spec_container.get_records_for_code(
            'LP-PI-TRM',
            strict_match=False)  # look up all prior intensity interpretations
    else:
        spec_container, prior_spec_data = None, []
    backup = 0
    #
    Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
    #
    #   create measurement dataframe
    #
    meas_container = contribution.tables['measurements']
    meas_data = meas_container.df
    #
    meas_data['method_codes'] = meas_data['method_codes'].str.replace(
        " ", "")  # get rid of nasty spaces
    meas_data = meas_data[meas_data['method_codes'].str.contains(
        'LP-PI-TRM|LP-TRM|LP-TRM-TD') ==
                          True]  # fish out zero field steps for plotting
    intensity_types = [
        col_name for col_name in meas_data.columns if col_name in Mkeys
    ]
    int_key = intensity_types[
        0]  # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
    meas_data = meas_data[meas_data[int_key].notnull(
    )]  # get all the non-null intensity records of the same type
    if 'flag' not in meas_data.columns:
        meas_data['flag'] = 'g'  # set the default flag to good
    meas_data = meas_data[meas_data['flag'].str.contains('g') ==
                          True]  # only the 'good' measurements
    thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')
                          == True]  # get all the Thellier data
    trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM') ==
                         True]  # get all the TRM acquisition data
    td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD') ==
                        True]  # get all the TD data
    anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN') ==
                          True]  # get all the anisotropy data
    #
    # get list of unique specimen names from measurement data
    #
    specimen_names = meas_data.specimen.unique(
    )  # this is a Series of all the specimen names
    specimen_names = specimen_names.tolist()  # turns it into a list
    specimen_names.sort()  # sorts by specimen name
    #
    # set up new DataFrame for this sessions specimen interpretations
    #
    spec_container = nb.MagicDataFrame(dtype='specimens',
                                       columns=specimen_cols)
    current_spec_data = spec_container.df  # this is for interpretations from this session
    if specimen == "":  # do all specimens
        k = 0
    else:
        k = specimen_names.index(specimen)  # just do this one
    # define figure numbers for arai, zijderveld and
    #   de-,re-magnetization diagrams
    AZD = {}
    AZD['deremag'], AZD['zijd'], AZD['arai'], AZD['eqarea'] = 1, 2, 3, 4
    pmagplotlib.plot_init(AZD['arai'], 5, 5)
    pmagplotlib.plot_init(AZD['zijd'], 5, 5)
    pmagplotlib.plot_init(AZD['deremag'], 5, 5)
    pmagplotlib.plot_init(AZD['eqarea'], 5, 5)
    if len(trm_data) > 0:
        AZD['TRM'] = 5
        pmagplotlib.plot_init(AZD['TRM'], 5, 5)
    if len(td_data) > 0:
        AZD['TDS'] = 6
        pmagplotlib.plot_init(AZD['TDS'], 5, 5)
    #
    while k < len(specimen_names):
        this_specimen = specimen_names[
            k]  # set the current specimen for plotting
        if verbose and this_specimen != "":
            print(this_specimen, k + 1, 'out of ', len(specimen_names))
        #
        #    set up datablocks
        #
        thelblock = thel_data[thel_data['specimen'].str.contains(this_specimen)
                              == True]  # fish out this specimen
        trmblock = trm_data[trm_data['specimen'].str.contains(this_specimen) ==
                            True]  # fish out this specimen
        tdsrecs = td_data[td_data['specimen'].str.contains(this_specimen) ==
                          True]  # fish out this specimen
        anisblock = anis_data[anis_data['specimen'].str.contains(this_specimen)
                              == True]  # fish out the anisotropy data
        prior_specimen_interpretations = prior_spec_data[
            prior_spec_data['specimen'].str.contains(
                this_specimen) == True]  # fish out prior interpretation
        #
        # sort data into types
        #
        araiblock, field = pmag.sortarai(thelblock,
                                         this_specimen,
                                         Zdiff,
                                         version=3)
        first_Z = araiblock[0]
        GammaChecks = araiblock[5]
        if len(first_Z) < 3:
            if backup == 0:
                k += 1
                if verbose:
                    print('skipping specimen - moving forward ', this_specimen)
            else:
                k -= 1
                if verbose:
                    print('skipping specimen - moving backward ',
                          this_specimen)
        else:
            backup = 0
            zijdblock, units = pmag.find_dmag_rec(this_specimen,
                                                  thelblock,
                                                  version=3)
            if start == "" and len(prior_specimen_interpretations) > 0:
                if verbose: print('Looking up saved interpretation....')
                #
                # get prior interpretation steps
                #
                beg_int = pd.to_numeric(prior_specimen_interpretations.
                                        meas_step_min.values).tolist()[0]
                end_int = pd.to_numeric(prior_specimen_interpretations.
                                        meas_step_max.values).tolist()[0]
            else:
                beg_int, end_int = "", ""
            recnum = 0
            if verbose: print("index step Dec   Inc  Int       Gamma")
            for plotrec in zijdblock:
                if plotrec[0] == beg_int:
                    start = recnum  # while we are at it, collect these bounds
                if plotrec[0] == end_int: end = recnum
                if verbose:
                    if GammaChecks != "":
                        gamma = ""
                        for g in GammaChecks:
                            if g[0] == plotrec[0] - 273:
                                gamma = g[1]
                                break
                    if gamma != "":
                        print('%i     %i %7.1f %7.1f %8.3e %7.1f' %
                              (recnum, plotrec[0] - 273, plotrec[1],
                               plotrec[2], plotrec[3], gamma))
                    else:
                        print('%i     %i %7.1f %7.1f %8.3e ' %
                              (recnum, plotrec[0] - 273, plotrec[1],
                               plotrec[2], plotrec[3]))
                recnum += 1
            for fig in list(AZD.keys()):
                pmagplotlib.clearFIG(AZD[fig])  # clear all figures
            pmagplotlib.plotAZ(AZD, araiblock, zijdblock, this_specimen,
                               units[0])
            if verbose: pmagplotlib.drawFIGS(AZD)
            pars, errcode = pmag.PintPars(thelblock,
                                          araiblock,
                                          zijdblock,
                                          start,
                                          end,
                                          accept,
                                          version=3)
            pars['measurement_step_unit'] = "K"
            pars['experiment_type'] = 'LP-PI-TRM'
            #
            # work on saving interpretations stuff later
            #
            if errcode != 1:  # no problem in PintPars
                pars["specimen_lab_field_dc"] = field
                pars["specimen_int"] = -1 * field * pars["specimen_b"]
                pars["er_specimen_name"] = this_specimen
                #pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose) # deal with this later
                pars["specimen_grade"] = 'None'
                pars['measurement_step_min'] = pars['meas_step_min']
                pars['measurement_step_max'] = pars['meas_step_max']
                if pars['measurement_step_unit'] == 'K':
                    outstr = "specimen     Tmin  Tmax  N  lab_field  B_anc  b  q  f(coe)  Fvds  beta  MAD  Dang  Drats  Nptrm  Grade  R  MD%  sigma  Gamma_max \n"
                    pars_out = (this_specimen, (pars["meas_step_min"] - 273),
                                (pars["meas_step_max"] -
                                 273), (pars["specimen_int_n"]),
                                1e6 * (pars["specimen_lab_field_dc"]),
                                1e6 * (pars["specimen_int"]),
                                pars["specimen_b"], pars["specimen_q"],
                                pars["specimen_f"], pars["specimen_fvds"],
                                pars["specimen_b_beta"], pars["int_mad_free"],
                                pars["int_dang"], pars["int_drats"],
                                pars["int_n_ptrm"], pars["specimen_grade"],
                                np.sqrt(pars["specimen_rsc"]),
                                int(pars["int_md"]), pars["specimen_b_sigma"],
                                pars['specimen_gamma'])
                    outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f  %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out + '\n'
                elif pars['measurement_step_unit'] == 'J':
                    outstr = "specimen     Wmin  Wmax  N  lab_field  B_anc  b  q  f(coe)  Fvds  beta  MAD  Dang  Drats  Nptrm  Grade  R  MD%  sigma  ThetaMax DeltaMax GammaMax\n"
                    pars_out = (
                        this_specimen, (pars["meas_step_min"]),
                        (pars["meas_step_max"]), (pars["specimen_int_n"]),
                        1e6 * (pars["specimen_lab_field_dc"]),
                        1e6 * (pars["specimen_int"]), pars["specimen_b"],
                        pars["specimen_q"], pars["specimen_f"],
                        pars["specimen_fvds"], pars["specimen_b_beta"],
                        pars["specimen_int_mad"], pars["specimen_int_dang"],
                        pars["specimen_drats"], pars["specimen_int_ptrm_n"],
                        pars["specimen_grade"], np.sqrt(pars["specimen_rsc"]),
                        int(pars["specimen_md"]), pars["specimen_b_sigma"],
                        pars["specimen_theta"], pars["specimen_delta"],
                        pars["specimen_gamma"])
                    outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f  %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out + '\n'
                print(outstr)
                print(outstring)
                pmagplotlib.plotB(AZD, araiblock, zijdblock, pars)
                mpars = pmag.domean(araiblock[1], start, end, 'DE-BFL')
                if verbose:
                    pmagplotlib.drawFIGS(AZD)
                    print('pTRM direction= ',
                          '%7.1f' % (mpars['specimen_dec']),
                          ' %7.1f' % (mpars['specimen_inc']), ' MAD:',
                          '%7.1f' % (mpars['specimen_mad']))
            if len(anisblock) > 0:  # this specimen has anisotropy data
                if verbose:
                    print('Found anisotropy record... but ignoring for now ')
            if plots == 1:
                if fmt != "pmag":
                    files = {}
                    for key in list(AZD.keys()):
                        files[
                            key] = 'SP:_' + this_specimen + '_TY:_' + key + '_' + '.' + fmt
                    if pmagplotlib.isServer:
                        black = '#000000'
                        purple = '#800080'
                        titles = {}
                        titles['deremag'] = 'DeReMag Plot'
                        titles['zijd'] = 'Zijderveld Plot'
                        titles['arai'] = 'Arai Plot'
                        titles['TRM'] = 'TRM Acquisition data'
                        AZD = pmagplotlib.addBorders(AZD, titles, black,
                                                     purple)
                    pmagplotlib.saveP(AZD, files)
                else:  # save in pmag format
                    print('pmag format no longer supported')
                    #script="grep "+this_specimen+" output.mag | thellier -mfsi"
                    #script=script+' %8.4e'%(field)
                    #min='%i'%((pars["measurement_step_min"]-273))
                    #Max='%i'%((pars["measurement_step_max"]-273))
                    #script=script+" "+min+" "+Max
                    #script=script+" |plotxy;cat mypost >>thellier.ps\n"
                    #pltf.write(script)
                    #pmag.domagicmag(outf,MeasRecs)
            if specimen != "": sys.exit()  # syonara
            if verbose:
                ans = input('Return for next specimen, q to quit:  ')
                if ans == 'q': sys.exit()
            k += 1  # moving on
def main():
    """
    NAME
        microwave_magic.py
    
    DESCRIPTION
        plots microwave paleointensity data, allowing interactive setting of bounds.
        Saves and reads interpretations
        from a pmag_specimen formatted table, default: microwave_specimens.txt

    SYNTAX 
        microwave_magic.py [command line options]

    OPTIONS
        -h prints help message and quits
        -f MEAS, set magic_measurements input file
        -fsp PRIOR, set pmag_specimen prior interpretations file
        -fcr CRIT, set criteria file for grading.  
        -fmt [svg,png,jpg], format for images - default is svg
        -sav,  saves plots with out review (default format)
        -spc SPEC, plots single specimen SPEC, saves plot with specified format
            with optional -b bounds adn quits
        -b BEG END: sets  bounds for calculation
           BEG: starting step for slope calculation
           END: ending step for slope calculation
        
    DEFAULTS
        MEAS: magic_measurements.txt
        CRIT: NONE
        PRIOR: microwave_specimens.txt
  
    OUTPUT 
        figures:
            ALL:  numbers refer to temperature steps in command line window
            1) Arai plot:  closed circles are zero-field first/infield
                           open circles are infield first/zero-field
                           triangles are pTRM checks
                           squares are pTRM tail checks
                           VDS is vector difference sum
                           diamonds are bounds for interpretation
            2) Zijderveld plot:  closed (open) symbols are X-Y (X-Z) planes
                                 X rotated to NRM direction
            3) (De/Re)Magnetization diagram:
                           circles are NRM remaining
                           squares are pTRM gained
        command line window:
            list is: temperature step numbers, power (J), Dec, Inc, Int (units of magic_measuements)
                     list of possible commands: type letter followed by return to select option
                     saving of plots creates .svg format files with specimen_name, plot type as name
    """ 
#
#   initializations
#
    meas_file,critout,inspec="magic_measurements.txt","","microwave_specimens.txt"
    inlt=0
    version_num=pmag.get_version()
    Tinit,DCZ,field,first_save=0,0,-1,1
    user,comment="",''
    ans,specimen,recnum,start,end=0,0,0,0,0
    plots,pmag_out,samp_file,style=0,"","","svg"
    fmt='.'+style
#
# default acceptance criteria
#
    accept_keys=['specimen_int_ptrm_n','specimen_md','specimen_fvds','specimen_b_beta','specimen_dang','specimen_drats','specimen_Z']
    accept={}
    accept['specimen_int_ptrm_n']=2
    accept['specimen_md']=10
    accept['specimen_fvds']=0.35
    accept['specimen_b_beta']=.1
    accept['specimen_int_mad']=7
    accept['specimen_dang']=10
    accept['specimen_drats']=10
    accept['specimen_Z']=10
#
# parse command line options
#
    spc,BEG,END="","",""
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    if '-f' in sys.argv:
        ind=sys.argv.index('-f')
        meas_file=sys.argv[ind+1]
    if '-fsp' in sys.argv:
        ind=sys.argv.index('-fsp')
        inspec=sys.argv[ind+1]
    if '-fcr' in sys.argv:
        ind=sys.argv.index('-fcr')
        critout=sys.argv[ind+1]
    if '-fmt' in sys.argv:
        ind=sys.argv.index('-fmt')
        fmt='.'+sys.argv[ind+1]
    if '-spc' in sys.argv:
        ind=sys.argv.index('-spc')
        spc=sys.argv[ind+1]
        if '-b' in sys.argv:
            ind=sys.argv.index('-b')
            BEG=int(sys.argv[ind+1])
            END=int(sys.argv[ind+2])
    if critout!="":
        crit_data,file_type=pmag.magic_read(critout)
        if pmagplotlib.verbose:
            print("Acceptance criteria read in from ", critout)
        accept={}
        accept['specimen_int_ptrm_n']=2.0
        for critrec in crit_data:
            if critrec["pmag_criteria_code"]=="IE-SPEC": 
                for key in accept_keys:
                    if key not in list(critrec.keys()):
                        accept[key]=-1
                    else:
                        accept[key]=float(critrec[key])
    try:
        open(inspec,'r')
        PriorRecs,file_type=pmag.magic_read(inspec)
        if file_type != 'pmag_specimens':
            print(file_type)
            print(file_type,inspec," is not a valid pmag_specimens file ") 
            sys.exit()
        for rec in PriorRecs:
            if 'magic_software_packages' not in list(rec.keys()):rec['magic_software_packages']=""
    except IOError:
        PriorRecs=[]
        if pmagplotlib.verbose:print("starting new specimen interpretation file: ",inspec)
    meas_data,file_type=pmag.magic_read(meas_file)
    if file_type != 'magic_measurements':
        print(file_type)
        print(file_type,"This is not a valid magic_measurements file ") 
        sys.exit()
    backup=0
    # define figure numbers for arai, zijderveld and 
    #   de-,re-magization diagrams
    AZD={}
    AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
    pmagplotlib.plot_init(AZD['arai'],4,4)
    pmagplotlib.plot_init(AZD['zijd'],4,4)
    pmagplotlib.plot_init(AZD['deremag'],4,4)
    pmagplotlib.plot_init(AZD['eqarea'],4,4)
    #
    #
    #
    # get list of unique specimen names
    #
    CurrRec=[]
    sids=pmag.get_specs(meas_data)
    # get plots for specimen s - default is just to step through arai diagrams
    #
    if spc!="": specimen =sids.index(spc)
    while specimen < len(sids):
        methcodes=[]
        if pmagplotlib.verbose and spc!="":
            print(sids[specimen],specimen+1, 'of ', len(sids))
        MeasRecs=[]
        s=sids[specimen]
        datablock,trmblock=[],[]
        PmagSpecRec={}
        PmagSpecRec["er_analyst_mail_names"]=user
        PmagSpecRec["specimen_correction"]='u'
    #
    # find the data from the meas_data file for this specimen
    #
        for rec in meas_data:
            if rec["er_specimen_name"]==s:
                MeasRecs.append(rec)
                methods=rec["magic_method_codes"].split(":")
                meths=[]
                for meth in methods:
                    meths.append(meth.strip()) # take off annoying spaces
                methods=""
                for meth in meths:
                    if meth.strip() not in methcodes and "LP-" in meth:methcodes.append(meth.strip())
                    methods=methods+meth+":"
                methods=methods[:-1]
                rec["magic_method_codes"]=methods 
                if "LP-PI-M" in meths: datablock.append(rec)
                if "LP-MRM" in meths: trmblock.append(rec)
        if len(trmblock)>2 and inspec!="":
            if Tinit==0:
                Tinit=1
                AZD['MRM']=4
                pmagplotlib.plot_init(AZD['MRM'],4,4)
            elif Tinit==1:
                pmagplotlib.clearFIG(AZD['MRM'])
        if len(datablock) <4:
           if backup==0:
               specimen+=1
               if pmagplotlib.verbose:
                   print('skipping specimen - moving forward ', s)
           else:
               specimen-=1
               if pmagplotlib.verbose:
                   print('skipping specimen - moving backward ', s)
    #
    #  collect info for the PmagSpecRec dictionary
    #
        else:
           rec=datablock[0]
           PmagSpecRec["er_citation_names"]="This study"
           PmagSpecRec["er_specimen_name"]=s
           PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
           PmagSpecRec["er_site_name"]=rec["er_site_name"]
           PmagSpecRec["er_location_name"]=rec["er_location_name"]
           if "magic_instrument_codes" not in list(rec.keys()):rec["magic_instrument_codes"]=""
           PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"]
           PmagSpecRec["measurement_step_unit"]="J"
           if "magic_experiment_name" not in list(rec.keys()):
               rec["magic_experiment_name"]=""
           else:
               PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
    
           meths=rec["magic_method_codes"].split(':')
       # sort data into types
           if "LP-PI-M-D" in meths: # this is a double heating experiment
               exp_type="LP-PI-M-D"
           elif "LP-PI-M-S" in meths:
               exp_type="LP-PI-M-S"
           else:
               print("experiment type not supported yet ")
               break
           araiblock,field=pmag.sortmwarai(datablock,exp_type)
           first_Z=araiblock[0]
           first_I=araiblock[1]
           GammaChecks=araiblock[-3]
           ThetaChecks=araiblock[-2]
           DeltaChecks=araiblock[-1]
           if len(first_Z)<3:
               if backup==0:
                   specimen+=1
                   if pmagplotlib.verbose:
                       print('skipping specimen - moving forward ', s)
               else:
                   specimen-=1
                   if pmagplotlib.verbose:
                       print('skipping specimen - moving backward ', s)
           else:
               backup=0
               zijdblock,units=pmag.find_dmag_rec(s,meas_data)
               if exp_type=="LP-PI-M-D":
                   recnum=0
                   print("ZStep Watts  Dec Inc  Int")
                   for plotrec in zijdblock:
                       if pmagplotlib.verbose:
                           print('%i  %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0],plotrec[1],plotrec[2],plotrec[3]))
                           recnum += 1
                   recnum = 1
                   if GammaChecks!="":
                       print("IStep Watts  Gamma")
                       for gamma in GammaChecks:
                           if pmagplotlib.verbose: print('%i %i %7.1f ' % (recnum, gamma[0],gamma[1]))
                           recnum += 1
               if exp_type=="LP-PI-M-S":
                   if pmagplotlib.verbose:
                       print("IStep Watts  Theta")
                       kk=0
                       for theta in ThetaChecks:
                           kk+=1
                           print('%i  %i %7.1f ' % (kk,theta[0],theta[1]))
                   if pmagplotlib.verbose:
                       print("Watts  Delta")
                       for delta in DeltaChecks:
                           print('%i %7.1f ' % (delta[0],delta[1]))
               pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
               if inspec !="":
                   if pmagplotlib.verbose: print('Looking up saved interpretation....')
                   found = 0
                   for k in range(len(PriorRecs)):
                       try:
                         if PriorRecs[k]["er_specimen_name"]==s:
                           found =1
                           CurrRec.append(PriorRecs[k])
                           for j in range(len(araiblock[0])):
                               if float(araiblock[0][j][0])==float(PriorRecs[k]["measurement_step_min"]):start=j
                               if float(araiblock[0][j][0])==float(PriorRecs[k]["measurement_step_max"]):end=j
                           pars,errcode=pmag.PintPars(araiblock,zijdblock,start,end)
                           pars['measurement_step_unit']="J"
                           del PriorRecs[k]  # put in CurrRec, take out of PriorRecs
                           if errcode!=1:
                               pars["specimen_lab_field_dc"]=field
                               pars["specimen_int"]=-1*field*pars["specimen_b"]
                               pars["er_specimen_name"]=s
                               if pmagplotlib.verbose:
                                   print('Saved interpretation: ')
                               pars=pmag.scoreit(pars,PmagSpecRec,accept,'',0)
                               pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                               if len(trmblock)>2:
                                   blab=field
                                   best=pars["specimen_int"]
                                   Bs,TRMs=[],[]
                                   for trec in trmblock:
                                       Bs.append(float(trec['treatment_dc_field']))
                                       TRMs.append(float(trec['measurement_magn_moment']))
                                   NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
                                   Mp,Bp=[],[]
                                   for k in  range(int(max(Bs)*1e6)):
                                       Bp.append(float(k)*1e-6)
                                       npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
                                       Mp.append(npred)
                                   pmagplotlib.plotTRM(AZD['MRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
                                   print(npred)
                                   print('Banc= ',float(NLpars['banc'])*1e6)
                                   if pmagplotlib.verbose:
                                       print('Banc= ',float(NLpars['banc'])*1e6)
                                   pmagplotlib.drawFIGS(AZD)
                           else:
                               print('error on specimen ',s)
                       except:
                         pass
                   if pmagplotlib.verbose and found==0: print('    None found :(  ') 
               if spc!="":
                   if BEG!="":
                       pars,errcode=pmag.PintPars(araiblock,zijdblock,BEG,END)
                       pars['measurement_step_unit']="J"
                       pars["specimen_lab_field_dc"]=field
                       pars["specimen_int"]=-1*field*pars["specimen_b"]
                       pars["er_specimen_name"]=s
                       pars['specimen_grade']='' # ungraded
                       pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                       if len(trmblock)>2:
                           if inlt==0:
                               donlt()
                               inlt=1
                           blab=field
                           best=pars["specimen_int"]
                           Bs,TRMs=[],[]
                           for trec in trmblock:
                               Bs.append(float(trec['treatment_dc_field']))
                               TRMs.append(float(trec['measurement_magn_moment']))
                           NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
    #
                           Mp,Bp=[],[]
                           for k in  range(int(max(Bs)*1e6)):
                               Bp.append(float(k)*1e-6)
                               npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
                   files={}
                   for key in list(AZD.keys()):
                       files[key]=s+'_'+key+fmt 
                   pmagplotlib.saveP(AZD,files)
                   sys.exit()
               if plots==0:
                   ans='b'
                   while ans != "":
                       print("""
               s[a]ve plot, set [b]ounds for calculation, [d]elete current interpretation, [p]revious, [s]ample, [q]uit:
               """)
                       ans=input('Return for next specimen \n')
                       if ans=="": 
                           specimen +=1
                       if ans=="d": 
                           save_redo(PriorRecs,inspec)
                           CurrRec=[]
                           pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
                           pmagplotlib.drawFIGS(AZD)
                       if ans=='a':
                           files={}
                           for key in list(AZD.keys()):
                               files[key]=s+'_'+key+fmt 
                           pmagplotlib.saveP(AZD,files)
                           ans=""
                       if ans=='q':
                           print("Good bye")
                           sys.exit()
                       if ans=='p':
                           specimen =specimen -1
                           backup = 1
                           ans=""
                       if ans=='s':
                           keepon=1
                           spec=input('Enter desired specimen name (or first part there of): ')
                           while keepon==1:
                               try:
                                   specimen =sids.index(spec)
                                   keepon=0
                               except:
                                   tmplist=[]
                                   for qq in range(len(sids)):
                                       if spec in sids[qq]:tmplist.append(sids[qq])
                                   print(specimen," not found, but this was: ")
                                   print(tmplist)
                                   spec=input('Select one or try again\n ')
                           ans=""
                       if  ans=='b':
                           if end==0 or end >=len(araiblock[0]):end=len(araiblock[0])-1
                           GoOn=0
                           while GoOn==0:
                               print('Enter index of first point for calculation: ','[',start,']')
                               answer=input('return to keep default  ')
                               if answer != "":start=int(answer)
                               print('Enter index  of last point for calculation: ','[',end,']')
                               answer=input('return to keep default  ')
                               if answer != "":
                                   end=int(answer)
                               if start >=0 and start <len(araiblock[0])-2 and end >0 and end <len(araiblock[0]) and start<end:
                                   GoOn=1
                               else:
                                   print("Bad endpoints - try again! ")
                                   start,end=0,len(araiblock)
                           s=sids[specimen]
                           pars,errcode=pmag.PintPars(araiblock,zijdblock,start,end)
                           pars['measurement_step_unit']="J"
                           pars["specimen_lab_field_dc"]=field
                           pars["specimen_int"]=-1*field*pars["specimen_b"]
                           pars["er_specimen_name"]=s
                           pars=pmag.scoreit(pars,PmagSpecRec,accept,'',0)
                           PmagSpecRec["measurement_step_min"]='%8.3e' % (pars["measurement_step_min"])
                           PmagSpecRec["measurement_step_max"]='%8.3e' % (pars["measurement_step_max"])
                           PmagSpecRec["measurement_step_unit"]="J"
                           PmagSpecRec["specimen_int_n"]='%i'%(pars["specimen_int_n"])
                           PmagSpecRec["specimen_lab_field_dc"]='%8.3e'%(pars["specimen_lab_field_dc"])
                           PmagSpecRec["specimen_int"]='%8.3e '%(pars["specimen_int"])
                           PmagSpecRec["specimen_b"]='%5.3f '%(pars["specimen_b"])
                           PmagSpecRec["specimen_q"]='%5.1f '%(pars["specimen_q"])
                           PmagSpecRec["specimen_f"]='%5.3f '%(pars["specimen_f"])
                           PmagSpecRec["specimen_fvds"]='%5.3f'%(pars["specimen_fvds"])
                           PmagSpecRec["specimen_b_beta"]='%5.3f'%(pars["specimen_b_beta"])
                           PmagSpecRec["specimen_int_mad"]='%7.1f'%(pars["specimen_int_mad"])
                           PmagSpecRec["specimen_Z"]='%7.1f'%(pars["specimen_Z"])
                           if pars["method_codes"]!="":
                               tmpcodes=pars["method_codes"].split(":")
                               for t in tmpcodes:
                                   if t.strip() not in methcodes:methcodes.append(t.strip())
                           PmagSpecRec["specimen_dec"]='%7.1f'%(pars["specimen_dec"])
                           PmagSpecRec["specimen_inc"]='%7.1f'%(pars["specimen_inc"])
                           PmagSpecRec["specimen_tilt_correction"]='-1'
                           PmagSpecRec["specimen_direction_type"]='l'
                           PmagSpecRec["direction_type"]='l' # this is redudant, but helpful - won't be imported
                           PmagSpecRec["specimen_dang"]='%7.1f '%(pars["specimen_dang"])
                           PmagSpecRec["specimen_drats"]='%7.1f '%(pars["specimen_drats"])
                           PmagSpecRec["specimen_int_ptrm_n"]='%i '%(pars["specimen_int_ptrm_n"])
                           PmagSpecRec["specimen_rsc"]='%6.4f '%(pars["specimen_rsc"])
                           PmagSpecRec["specimen_md"]='%i '%(int(pars["specimen_md"]))
                           if PmagSpecRec["specimen_md"]=='-1':PmagSpecRec["specimen_md"]=""
                           PmagSpecRec["specimen_b_sigma"]='%5.3f '%(pars["specimen_b_sigma"])
                           if "IE-TT" not in  methcodes:methcodes.append("IE-TT")
                           methods=""
                           for meth in methcodes:
                               methods=methods+meth+":"
                           PmagSpecRec["magic_method_codes"]=methods[:-1]
                           PmagSpecRec["specimen_description"]=comment
                           PmagSpecRec["magic_software_packages"]=version_num
                           pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
                           pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
                           if len(trmblock)>2:
                               blab=field
                               best=pars["specimen_int"]
                               Bs,TRMs=[],[]
                               for trec in trmblock:
                                   Bs.append(float(trec['treatment_dc_field']))
                                   TRMs.append(float(trec['measurement_magn_moment']))
                               NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
                               Mp,Bp=[],[]
                               for k in  range(int(max(Bs)*1e6)):
                                   Bp.append(float(k)*1e-6)
                                   npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
                                   Mp.append(npred)
                               pmagplotlib.plotTRM(AZD['MRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
                               print('Banc= ',float(NLpars['banc'])*1e6)
                           pmagplotlib.drawFIGS(AZD)
                           pars["specimen_lab_field_dc"]=field
                           pars["specimen_int"]=-1*field*pars["specimen_b"]
                           saveit=input("Save this interpretation? [y]/n \n")
                           if saveit!='n':
                               specimen+=1
                               PriorRecs.append(PmagSpecRec) # put back an interpretation
                               save_redo(PriorRecs,inspec)
                           ans=""
               else:
                   specimen+=1
                   if fmt != ".pmag":
                       basename=s+'_microwave'+fmt
                       files={}
                       for key in list(AZD.keys()):
                           files[key]=s+'_'+key+fmt 
                       if pmagplotlib.isServer:
                           black     = '#000000'
                           purple    = '#800080'
                           titles={}
                           titles['deremag']='DeReMag Plot'
                           titles['zijd']='Zijderveld Plot'
                           titles['arai']='Arai Plot'
                           AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
                       pmagplotlib.saveP(AZD,files)
    #                   pmagplotlib.combineFigs(s,files,3)
        if len(CurrRec)>0:
            for rec in CurrRec:
                PriorRecs.append(rec)
        CurrRec=[]
    if plots!=1:
        ans=input(" Save last plot? 1/[0] ")
        if ans=="1":
            if fmt != ".pmag":
                files={}
                for key in list(AZD.keys()):
                    files[key]=s+'_'+key+fmt
                pmagplotlib.saveP(AZD,files)
        if len(CurrRec)>0:PriorRecs.append(CurrRec) # put back an interpretation
        if len(PriorRecs)>0:
            save_redo(PriorRecs,inspec)
            print('Updated interpretations saved in ',inspec)
    if pmagplotlib.verbose:
        print("Good bye")