示例#1
0
def main():
    """
    NAME
        thellier_magic_redo.py

    DESCRIPTION
        Calculates paleointensity parameters for thellier-thellier type data using bounds
        stored in the "redo" file

    SYNTAX
        thellier_magic_redo [command line options]

    OPTIONS
        -h prints help message
        -usr USER:   identify user, default is ""
        -fcr CRIT, set criteria for grading
        -f IN: specify input file, default is magic_measurements.txt
        -fre REDO: specify redo file, default is "thellier_redo"
        -F OUT: specify output file, default is thellier_specimens.txt
        -leg:  attaches "Recalculated from original measurements; supercedes published results. " to comment field
        -CR PERC TYPE: apply a blanket cooling rate correction if none supplied in the er_samples.txt file 
            PERC should be a percentage of original (say reduce to 90%)
            TYPE should be one of the following:
               EG (for educated guess); PS (based on pilots); TRM (based on comparison of two TRMs) 
        -ANI:  perform anisotropy correction
        -fsa SAMPFILE: er_samples.txt file with cooling rate correction information, default is NO CORRECTION
        -Fcr  CRout: specify pmag_specimen format file for cooling rate corrected data
        -fan ANIFILE: specify rmag_anisotropy format file, default is rmag_anisotropy.txt 
        -Fac  ACout: specify pmag_specimen format file for anisotropy corrected data
                 default is AC_specimens.txt
        -fnl NLTFILE: specify magic_measurments format file, default is magic_measurements.txt
        -Fnl NLTout: specify pmag_specimen format file for non-linear trm corrected data
                 default is NLT_specimens.txt
        -z use z component differenences for pTRM calculation

    INPUT
        a thellier_redo file is Specimen_name Tmin Tmax (where Tmin and Tmax are in Centigrade)
    """
    dir_path = "."
    critout = ""
    version_num = pmag.get_version()
    field, first_save = -1, 1
    spec, recnum, start, end = 0, 0, 0, 0
    crfrac = 0
    NltRecs, PmagSpecs, AniSpecRecs, NltSpecRecs, CRSpecs = [], [], [], [], []
    meas_file, pmag_file, mk_file = "magic_measurements.txt", "thellier_specimens.txt", "thellier_redo"
    anis_file = "rmag_anisotropy.txt"
    anisout, nltout = "AC_specimens.txt", "NLT_specimens.txt"
    crout = "CR_specimens.txt"
    nlt_file = ""
    samp_file = ""
    comment, user = "", "unknown"
    anis, nltrm = 0, 0
    jackknife = 0  # maybe in future can do jackknife
    args = sys.argv
    Zdiff = 0
    if "-WD" in args:
        ind = args.index("-WD")
        dir_path = args[ind + 1]
    if "-h" in args:
        print main.__doc__
        sys.exit()
    if "-usr" in args:
        ind = args.index("-usr")
        user = sys.argv[ind + 1]
    if "-leg" in args:
        comment = "Recalculated from original measurements; supercedes published results. "
    cool = 0
    if "-CR" in args:
        cool = 1
        ind = args.index("-CR")
        crfrac = 0.01 * float(sys.argv[ind + 1])
        crtype = "DA-CR-" + sys.argv[ind + 2]
    if "-Fcr" in args:
        ind = args.index("-Fcr")
        crout = sys.argv[ind + 1]
    if "-f" in args:
        ind = args.index("-f")
        meas_file = sys.argv[ind + 1]
    if "-F" in args:
        ind = args.index("-F")
        pmag_file = sys.argv[ind + 1]
    if "-fre" in args:
        ind = args.index("-fre")
        mk_file = args[ind + 1]
    if "-fsa" in args:
        ind = args.index("-fsa")
        samp_file = dir_path + "/" + args[ind + 1]
        Samps, file_type = pmag.magic_read(samp_file)
        SampCRs = pmag.get_dictitem(Samps, "cooling_rate_corr", "", "F")  # get samples cooling rate corrections
        cool = 1
        if file_type != "er_samples":
            print "not a valid er_samples.txt file"
            sys.exit()
    #
    #
    if "-ANI" in args:
        anis = 1
        ind = args.index("-ANI")
        if "-Fac" in args:
            ind = args.index("-Fac")
            anisout = args[ind + 1]
        if "-fan" in args:
            ind = args.index("-fan")
            anis_file = args[ind + 1]
    #
    if "-NLT" in args:
        if "-Fnl" in args:
            ind = args.index("-Fnl")
            nltout = args[ind + 1]
        if "-fnl" in args:
            ind = args.index("-fnl")
            nlt_file = args[ind + 1]
    if "-z" in args:
        Zdiff = 1
    if "-fcr" in sys.argv:
        ind = args.index("-fcr")
        critout = sys.argv[ind + 1]
    #
    #  start reading in data:
    #
    meas_file = dir_path + "/" + meas_file
    mk_file = dir_path + "/" + mk_file
    accept = pmag.default_criteria(1)[0]  # set criteria to none
    if critout != "":
        critout = dir_path + "/" + critout
        crit_data, file_type = pmag.magic_read(critout)
        if file_type != "pmag_criteria":
            print "bad pmag_criteria file, using no acceptance criteria"
        print "Acceptance criteria read in from ", critout
        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]
    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()
    try:
        mk_f = open(mk_file, "rU")
    except:
        print "Bad redo file"
        sys.exit()
    mkspec = []
    speclist = []
    for line in mk_f.readlines():
        tmp = line.split()
        mkspec.append(tmp)
        speclist.append(tmp[0])
    if anis == 1:
        anis_file = dir_path + "/" + anis_file
        anis_data, file_type = pmag.magic_read(anis_file)
        if file_type != "rmag_anisotropy":
            print file_type
            print file_type, "This is not a valid rmag_anisotropy file "
            sys.exit()
    if nlt_file == "":
        nlt_data = pmag.get_dictitem(
            meas_data, "magic_method_codes", "LP-TRM", "has"
        )  # look for trm acquisition data in the meas_data file
    else:
        nlt_file = dir_path + "/" + nlt_file
        nlt_data, file_type = pmag.magic_read(nlt_file)
    if len(nlt_data) > 0:
        nltrm = 1
    #
    # sort the specimen names and step through one by one
    #
    sids = pmag.get_specs(meas_data)
    #
    print "Processing ", len(speclist), " specimens - please wait "
    while spec < len(speclist):
        s = speclist[spec]
        recnum = 0
        datablock = []
        PmagSpecRec = {}
        PmagSpecRec["er_analyst_mail_names"] = user
        PmagSpecRec["er_citation_names"] = "This study"
        PmagSpecRec["magic_software_packages"] = version_num
        methcodes, inst_code = [], ""
        #
        # find the data from the meas_data file for this specimen
        #
        datablock = pmag.get_dictitem(meas_data, "er_specimen_name", s, "T")
        datablock = pmag.get_dictitem(
            datablock, "magic_method_codes", "LP-PI-TRM", "has"
        )  # pick out the thellier experiment data
        if len(datablock) > 0:
            for rec in datablock:
                if "magic_instrument_codes" not in rec.keys():
                    rec["magic_instrument_codes"] = "unknown"
            #
            #  collect info for the PmagSpecRec dictionary
            #
            rec = datablock[0]
            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"]
            PmagSpecRec["measurement_step_unit"] = "K"
            PmagSpecRec["specimen_correction"] = "u"
            if "er_expedition_name" in rec.keys():
                PmagSpecRec["er_expedition_name"] = rec["er_expedition_name"]
            if "magic_instrument_codes" not in rec.keys():
                PmagSpecRec["magic_instrument_codes"] = "unknown"
            else:
                PmagSpecRec["magic_instrument_codes"] = rec["magic_instrument_codes"]
            if "magic_experiment_name" not in rec.keys():
                rec["magic_experiment_name"] = ""
            else:
                PmagSpecRec["magic_experiment_names"] = rec["magic_experiment_name"]
            meths = rec["magic_experiment_name"].split(":")
            for meth in meths:
                if meth.strip() not in methcodes and "LP-" in meth:
                    methcodes.append(meth.strip())
            #
            # sort out the data into first_Z, first_I, ptrm_check, ptrm_tail
            #
            araiblock, field = pmag.sortarai(datablock, s, Zdiff)
            first_Z = araiblock[0]
            first_I = araiblock[1]
            ptrm_check = araiblock[2]
            ptrm_tail = araiblock[3]
            if len(first_I) < 3 or len(first_Z) < 4:
                spec += 1
                print "skipping specimen ", s
            else:
                #
                # get start, end
                #
                for redospec in mkspec:
                    if redospec[0] == s:
                        b, e = float(redospec[1]), float(redospec[2])
                        break
                if e > float(first_Z[-1][0]):
                    e = float(first_Z[-1][0])
                for recnum in range(len(first_Z)):
                    if first_Z[recnum][0] == b:
                        start = recnum
                    if first_Z[recnum][0] == e:
                        end = recnum
                nsteps = end - start
                if nsteps > 2:
                    zijdblock, units = pmag.find_dmag_rec(s, meas_data)
                    pars, errcode = pmag.PintPars(datablock, araiblock, zijdblock, start, end, accept)
                    if "specimen_scat" in pars.keys():
                        PmagSpecRec["specimen_scat"] = pars["specimen_scat"]
                    if "specimen_frac" in pars.keys():
                        PmagSpecRec["specimen_frac"] = "%5.3f" % (pars["specimen_frac"])
                    if "specimen_gmax" in pars.keys():
                        PmagSpecRec["specimen_gmax"] = "%5.3f" % (pars["specimen_gmax"])
                    pars["measurement_step_unit"] = units
                    pars["specimen_lab_field_dc"] = field
                    pars["specimen_int"] = -1 * field * pars["specimen_b"]
                    PmagSpecRec["measurement_step_min"] = "%8.3e" % (pars["measurement_step_min"])
                    PmagSpecRec["measurement_step_max"] = "%8.3e" % (pars["measurement_step_max"])
                    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"])
                    if pars["method_codes"] != "" and pars["method_codes"] not in methcodes:
                        methcodes.append(pars["method_codes"])
                    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_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.strip(":")
                    PmagSpecRec["magic_software_packages"] = version_num
                    PmagSpecRec["specimen_description"] = comment
                    if critout != "":
                        kill = pmag.grade(PmagSpecRec, accept, "specimen_int")
                        if len(kill) > 0:
                            Grade = "F"  # fails
                        else:
                            Grade = "A"  # passes
                        PmagSpecRec["specimen_grade"] = Grade
                    else:
                        PmagSpecRec["specimen_grade"] = ""  # not graded
                    if nltrm == 0 and anis == 0 and cool != 0:  # apply cooling rate correction
                        SCR = pmag.get_dictitem(
                            SampCRs, "er_sample_name", PmagSpecRec["er_sample_name"], "T"
                        )  # get this samples, cooling rate correction
                        CrSpecRec = pmag.cooling_rate(PmagSpecRec, SCR, crfrac, crtype)
                        if CrSpecRec["er_specimen_name"] != "none":
                            CrSpecs.append(CrSpecRec)
                    PmagSpecs.append(PmagSpecRec)
                    NltSpecRec = ""
                    #
                    # check on non-linear TRM correction
                    #
                    if nltrm == 1:
                        #
                        # find the data from the nlt_data list for this specimen
                        #
                        TRMs, Bs = [], []
                        NltSpecRec = ""
                        NltRecs = pmag.get_dictitem(
                            nlt_data, "er_specimen_name", PmagSpecRec["er_specimen_name"], "has"
                        )  # fish out all the NLT data for this specimen
                        if len(NltRecs) > 2:
                            for NltRec in NltRecs:
                                Bs.append(float(NltRec["treatment_dc_field"]))
                                TRMs.append(float(NltRec["measurement_magn_moment"]))
                            NLTpars = nlt.NLtrm(
                                Bs,
                                TRMs,
                                float(PmagSpecRec["specimen_int"]),
                                float(PmagSpecRec["specimen_lab_field_dc"]),
                                0,
                            )
                            if NLTpars["banc"] > 0:
                                NltSpecRec = {}
                                for key in PmagSpecRec.keys():
                                    NltSpecRec[key] = PmagSpecRec[key]
                                NltSpecRec["specimen_int"] = "%9.4e" % (NLTpars["banc"])
                                NltSpecRec["magic_method_codes"] = PmagSpecRec["magic_method_codes"] + ":DA-NL"
                                NltSpecRec["specimen_correction"] = "c"
                                NltSpecRec["specimen_grade"] = PmagSpecRec["specimen_grade"]
                                NltSpecRec["magic_software_packages"] = version_num
                                print NltSpecRec["er_specimen_name"], " Banc= ", float(NLTpars["banc"]) * 1e6
                                if anis == 0 and cool != 0:
                                    SCR = pmag.get_dictitem(
                                        SampCRs, "er_sample_name", NltSpecRec["er_sample_name"], "T"
                                    )  # get this samples, cooling rate correction
                                    CrSpecRec = pmag.cooling_rate(NltSpecRec, SCR, crfrac, crtype)
                                    if CrSpecRec["er_specimen_name"] != "none":
                                        CrSpecs.append(CrSpecRec)
                                NltSpecRecs.append(NltSpecRec)
                        #
                        # check on anisotropy correction
                        if anis == 1:
                            if NltSpecRec != "":
                                Spc = NltSpecRec
                            else:  # find uncorrected data
                                Spc = PmagSpecRec
                            AniSpecs = pmag.get_dictitem(
                                anis_data, "er_specimen_name", PmagSpecRec["er_specimen_name"], "T"
                            )
                            if len(AniSpecs) > 0:
                                AniSpec = AniSpecs[0]
                                AniSpecRec = pmag.doaniscorr(Spc, AniSpec)
                                AniSpecRec["specimen_grade"] = PmagSpecRec["specimen_grade"]
                                AniSpecRec["magic_instrument_codes"] = PmagSpecRec["magic_instrument_codes"]
                                AniSpecRec["specimen_correction"] = "c"
                                AniSpecRec["magic_software_packages"] = version_num
                                if cool != 0:
                                    SCR = pmag.get_dictitem(
                                        SampCRs, "er_sample_name", AniSpecRec["er_sample_name"], "T"
                                    )  # get this samples, cooling rate correction
                                    CrSpecRec = pmag.cooling_rate(AniSpecRec, SCR, crfrac, crtype)
                                    if CrSpecRec["er_specimen_name"] != "none":
                                        CrSpecs.append(CrSpecRec)
                                AniSpecRecs.append(AniSpecRec)
                    elif anis == 1:
                        AniSpecs = pmag.get_dictitem(
                            anis_data, "er_specimen_name", PmagSpecRec["er_specimen_name"], "T"
                        )
                        if len(AniSpecs) > 0:
                            AniSpec = AniSpecs[0]
                            AniSpecRec = pmag.doaniscorr(PmagSpecRec, AniSpec)
                            AniSpecRec["specimen_grade"] = PmagSpecRec["specimen_grade"]
                            AniSpecRec["magic_instrument_codes"] = PmagSpecRec["magic_instrument_codes"]
                            AniSpecRec["specimen_correction"] = "c"
                            AniSpecRec["magic_software_packages"] = version_num
                            if crfrac != 0:
                                CrSpecRec = {}
                                for key in AniSpecRec.keys():
                                    CrSpecRec[key] = AniSpecRec[key]
                                inten = frac * float(CrSpecRec["specimen_int"])
                                CrSpecRec["specimen_int"] = "%9.4e " % (
                                    inten
                                )  # adjust specimen intensity by cooling rate correction
                                CrSpecRec["magic_method_codes"] = CrSpecRec["magic_method_codes"] + ":DA-CR-" + crtype
                                CRSpecs.append(CrSpecRec)
                            AniSpecRecs.append(AniSpecRec)
                spec += 1
        else:
            print "skipping ", s
            spec += 1
    pmag_file = dir_path + "/" + pmag_file
    pmag.magic_write(pmag_file, PmagSpecs, "pmag_specimens")
    print "uncorrected thellier data saved in: ", pmag_file
    if anis == 1 and len(AniSpecRecs) > 0:
        anisout = dir_path + "/" + anisout
        pmag.magic_write(anisout, AniSpecRecs, "pmag_specimens")
        print "anisotropy corrected data saved in: ", anisout
    if nltrm == 1 and len(NltSpecRecs) > 0:
        nltout = dir_path + "/" + nltout
        pmag.magic_write(nltout, NltSpecRecs, "pmag_specimens")
        print "non-linear TRM corrected data saved in: ", nltout
    if crfrac != 0:
        crout = dir_path + "/" + crout
        pmag.magic_write(crout, CRSpecs, "pmag_specimens")
        print "cooling rate corrected data saved in: ", crout
def main():
    """
    NAME
	specimens_results_magic.py

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

    SYNTAX
	specimens_results_magic.py [command line options]

    OPTIONS
	-h prints help message and quits
	-usr USER:   identify user, default is ""
	-f: specimen input magic_measurements format file, default is "magic_measurements.txt"
	-fsp: specimen input pmag_specimens format file, default is "pmag_specimens.txt"
	-fsm: sample input er_samples format file, default is "er_samples.txt"
	-fsi: specimen input er_sites format file, default is "er_sites.txt"
	-fla: specify a file with paleolatitudes for calculating VADMs, default is not to calculate VADMS
               format is:  site_name paleolatitude (space delimited file)
	-fa AGES: specify er_ages format file with age information
	-crd [s,g,t,b]:   specify coordinate system
	    (s, specimen, g geographic, t, tilt corrected, b, geographic and tilt corrected)
	    Default is to assume geographic
	    NB: only the tilt corrected data will appear on the results table, if both g and t are selected.
        -cor [AC:CR:NL]: colon delimited list of required data adjustments for all specimens 
            included in intensity calculations (anisotropy, cooling rate, non-linear TRM)
            unless specified, corrections will not be applied
        -pri [TRM:ARM] colon delimited list of priorities for anisotropy correction (-cor must also be set to include AC). default is TRM, then ARM 
	-age MIN MAX UNITS:   specify age boundaries and units
	-exc:  use exiting selection criteria (in pmag_criteria.txt file), default is default criteria
	-C: no acceptance criteria
	-aD:  average directions per sample, default is NOT
	-aI:  average multiple specimen intensities per sample, default is by site 
	-aC:  average all components together, default is NOT
	-pol:  calculate polarity averages
	-sam:  save sample level vgps and v[a]dms, default is by site
	-xSi:  skip the site level intensity calculation
	-p: plot directions and look at intensities by site, default is NOT
	    -fmt: specify output for saved images, default is svg (only if -p set)
	-lat: use present latitude for calculating VADMs, default is not to calculate VADMs
	-xD: skip directions
	-xI: skip intensities
    OUPUT
	writes pmag_samples, pmag_sites, pmag_results tables
    """
# set defaults
    Comps=[] # list of components
    version_num=pmag.get_version()
    args=sys.argv
    DefaultAge=["none"]
    skipdirs,coord,excrit,custom,vgps,average,Iaverage,plotsites,opt=1,0,0,0,0,0,0,0,0
    get_model_lat=0 # this skips VADM calculation altogether, when get_model_lat=1, uses present day
    fmt='svg'
    dir_path="."
    model_lat_file=""
    Caverage=0
    infile='pmag_specimens.txt'
    measfile="magic_measurements.txt"
    sampfile="er_samples.txt"
    sitefile="er_sites.txt"
    agefile="er_ages.txt"
    specout="er_specimens.txt"
    sampout="pmag_samples.txt"
    siteout="pmag_sites.txt"
    resout="pmag_results.txt"
    critout="pmag_criteria.txt"
    instout="magic_instruments.txt"
    sigcutoff,OBJ="",""
    noDir,noInt=0,0
    polarity=0
    coords=['0']
    Dcrit,Icrit,nocrit=0,0,0
    corrections=[]
    nocorrection=['DA-NL','DA-AC','DA-CR']
    priorities=['DA-AC-ARM','DA-AC-TRM'] # priorities for anisotropy correction
# get command line stuff
    if "-h" in args:
	print main.__doc__
	sys.exit()
    if '-WD' in args:
	ind=args.index("-WD")
	dir_path=args[ind+1]
    if '-cor' in args:
        ind=args.index('-cor')
        cors=args[ind+1].split(':') # list of required data adjustments
        for cor in cors:
            nocorrection.remove('DA-'+cor)
            corrections.append('DA-'+cor)
    if '-pri' in args:
        ind=args.index('-pri')
        priorities=args[ind+1].split(':') # list of required data adjustments
        for p in priorities:
            p='DA-AC-'+p
    if '-f' in args:
	ind=args.index("-f")
	measfile=args[ind+1]
    if '-fsp' in args:
	ind=args.index("-fsp")
	infile=args[ind+1]
    if '-fsi' in args:
	ind=args.index("-fsi")
	sitefile=args[ind+1]
    if "-crd" in args:
	ind=args.index("-crd")
	coord=args[ind+1]
	if coord=='s':coords=['-1']
	if coord=='g':coords=['0']
	if coord=='t':coords=['100']
	if coord=='b':coords=['0','100']
    if "-usr" in args:
	ind=args.index("-usr")
	user=sys.argv[ind+1]
    else: user=""
    if "-C" in args: Dcrit,Icrit,nocrit=1,1,1 # no selection criteria
    if "-sam" in args: vgps=1 # save sample level VGPS/VADMs
    if "-xSi" in args: 
        nositeints=1 # skip site level intensity
    else:
        nositeints=0
    if "-age" in args:
	ind=args.index("-age")
	DefaultAge[0]=args[ind+1]
	DefaultAge.append(args[ind+2])
	DefaultAge.append(args[ind+3])
    Daverage,Iaverage,Caverage=0,0,0
    if "-aD" in args: Daverage=1 # average by sample directions
    if "-aI" in args: Iaverage=1 # average by sample intensities
    if "-aC" in args: Caverage=1 # average all components together ???  why???
    if "-pol" in args: polarity=1 # calculate averages by polarity
    if '-xD' in args:noDir=1
    if '-xI' in args:
	noInt=1
    elif "-fla" in args: 
	if '-lat' in args:
	    print "you should set a paleolatitude file OR use present day lat - not both"
	    sys.exit()
	ind=args.index("-fla")
	model_lat_file=dir_path+'/'+args[ind+1]
	get_model_lat=2
	mlat=open(model_lat_file,'rU')
	ModelLats=[]
	for line in mlat.readlines():
	    ModelLat={}
	    tmp=line.split()
	    ModelLat["er_site_name"]=tmp[0]
	    ModelLat["site_model_lat"]=tmp[1]
	    ModelLat["er_sample_name"]=tmp[0] 
	    ModelLat["sample_lat"]=tmp[1]
	    ModelLats.append(ModelLat)
	get_model_lat=2
    elif '-lat' in args:
	get_model_lat=1
    if "-p" in args: 
	plotsites=1
	if "-fmt" in args: 
	    ind=args.index("-fmt")
	    fmt=args[ind+1]
	if noDir==0: # plot by site - set up plot window
	    import pmagplotlib
	    EQ={}
	    EQ['eqarea']=1
	    pmagplotlib.plot_init(EQ['eqarea'],5,5) # define figure 1 as equal area projection
            pmagplotlib.plotNET(EQ['eqarea']) # I don't know why this has to be here, but otherwise the first plot never plots...
            pmagplotlib.drawFIGS(EQ)
    if '-WD' in args:
	infile=dir_path+'/'+infile
	measfile=dir_path+'/'+measfile
	instout=dir_path+'/'+instout
	sampfile=dir_path+'/'+sampfile
	sitefile=dir_path+'/'+sitefile
	agefile=dir_path+'/'+agefile
	specout=dir_path+'/'+specout
	sampout=dir_path+'/'+sampout
	siteout=dir_path+'/'+siteout
	resout=dir_path+'/'+resout
	critout=dir_path+'/'+critout
    if "-exc" in args: # use existing pmag_criteria file 
	if "-C" in args:
	    print 'you can not use both existing and no criteria - choose either -exc OR -C OR neither (for default)'
	    sys.exit()
	crit_data,file_type=pmag.magic_read(critout)
	print "Acceptance criteria read in from ", critout
    else  : # use default criteria (if nocrit set, then get really loose criteria as default)
	crit_data=pmag.default_criteria(nocrit)
	if nocrit==0:
	    print "Acceptance criteria are defaults"
	else:
	    print "No acceptance criteria used "
    accept={}
    for critrec in crit_data:
        for key in critrec.keys():
            if 'sample_int_sigma_uT' in critrec.keys():
                critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
            if key not in accept.keys() and critrec[key]!='':
                accept[key]=critrec[key]
    #
    #
    if "-exc" not in args and "-C" not in args:
        print "args",args
        pmag.magic_write(critout,[accept],'pmag_criteria')
        print "\n Pmag Criteria stored in ",critout,'\n'
#
# now we're done slow dancing
#
    SiteNFO,file_type=pmag.magic_read(sitefile) # read in site data - has the lats and lons
    SampNFO,file_type=pmag.magic_read(sampfile) # read in site data - has the lats and lons
    height_nfo=pmag.get_dictitem(SiteNFO,'site_height','','F') # find all the sites with height info.  
    if agefile !="":AgeNFO,file_type=pmag.magic_read(agefile) # read in the age information
    Data,file_type=pmag.magic_read(infile) # read in specimen interpretations
    IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
    comment,orient="",[]
    samples,sites=[],[]
    for rec in Data: # run through the data filling in missing keys and finding all components, coordinates available
# fill in missing fields, collect unique sample and site names
	if 'er_sample_name' not in rec.keys():
	    rec['er_sample_name']=""
	elif rec['er_sample_name'] not in samples:
	    samples.append(rec['er_sample_name'])
	if 'er_site_name' not in rec.keys():
	    rec['er_site_name']=""
	elif rec['er_site_name'] not in sites:
	    sites.append(rec['er_site_name'])
	if 'specimen_int' not in rec.keys():rec['specimen_int']=''
	if 'specimen_comp_name' not in rec.keys() or rec['specimen_comp_name']=="":rec['specimen_comp_name']='A'
	if rec['specimen_comp_name'] not in Comps:Comps.append(rec['specimen_comp_name'])
        rec['specimen_tilt_correction']=rec['specimen_tilt_correction'].strip('\n')
	if "specimen_tilt_correction" not in rec.keys(): rec["specimen_tilt_correction"]="-1" # assume sample coordinates
	if rec["specimen_tilt_correction"] not in orient: orient.append(rec["specimen_tilt_correction"])  # collect available coordinate systems
	if "specimen_direction_type" not in rec.keys(): rec["specimen_direction_type"]='l'  # assume direction is line - not plane
	if "specimen_dec" not in rec.keys(): rec["specimen_direction_type"]=''  # if no declination, set direction type to blank
	if "specimen_n" not in rec.keys(): rec["specimen_n"]=''  # put in n
	if "specimen_alpha95" not in rec.keys(): rec["specimen_alpha95"]=''  # put in alpha95 
	if "magic_method_codes" not in rec.keys(): rec["magic_method_codes"]=''
     #
     # start parsing data into SpecDirs, SpecPlanes, SpecInts 
    SpecInts,SpecDirs,SpecPlanes=[],[],[]
    samples.sort() # get sorted list of samples and sites
    sites.sort()
    if noInt==0: # don't skip intensities
	IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
	if nocrit==0: # use selection criteria
	    for rec in IntData: # do selection criteria
		kill=pmag.grade(rec,accept,'specimen_int')
		if len(kill)==0: SpecInts.append(rec) # intensity record to be included in sample, site calculations
	else:
	    SpecInts=IntData[:] # take everything - no selection criteria
# check for required data adjustments
        if len(corrections)>0 and len(SpecInts)>0:
            for cor in corrections:
                SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'has') # only take specimens with the required corrections
        if len(nocorrection)>0 and len(SpecInts)>0:
            for cor in nocorrection:
                SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'not') # exclude the corrections not specified for inclusion
# take top priority specimen of its name in remaining specimens (only one per customer)
        PrioritySpecInts=[]
        specimens=pmag.get_specs(SpecInts) # get list of uniq specimen names
        for spec in specimens:
            ThisSpecRecs=pmag.get_dictitem(SpecInts,'er_specimen_name',spec,'T') # all the records for this specimen
            if len(ThisSpecRecs)==1:
                PrioritySpecInts.append(ThisSpecRecs[0])
            elif len(ThisSpecRecs)>1: # more than one
                prec=[]
                for p in priorities:
                    ThisSpecRecs=pmag.get_dictitem(SpecInts,'magic_method_codes',p,'has') # all the records for this specimen
                    if len(ThisSpecRecs)>0:prec.append(ThisSpecRecs[0])
                PrioritySpecInts.append(prec[0]) # take the best one
        SpecInts=PrioritySpecInts # this has the first specimen record 
    if noDir==0: # don't skip directions
	AllDirs=pmag.get_dictitem(Data,'specimen_direction_type','','F') # retrieve specimens with directed lines and planes
	Ns=pmag.get_dictitem(AllDirs,'specimen_n','','F')  # get all specimens with specimen_n information 
	if nocrit!=1: # use selection criteria
	    for rec in Ns: # look through everything with specimen_n for "good" data
                kill=pmag.grade(rec,accept,'specimen_dir')
                if len(kill)==0: # nothing killed it
			SpecDirs.append(rec)
	else: # no criteria
	    SpecDirs=AllDirs[:] # take them all
# SpecDirs is now the list of all specimen directions (lines and planes) that pass muster
#
    PmagSamps,SampDirs=[],[] # list of all sample data and list of those that pass the DE-SAMP criteria
    PmagSites,PmagResults=[],[] # list of all site data and selected results
    SampInts=[]
    for samp in samples: # run through the sample names
	if Daverage==1: #  average by sample if desired
	   SampDir=pmag.get_dictitem(SpecDirs,'er_sample_name',samp,'T') # get all the directional data for this sample
	   if len(SampDir)>0: # there are some directions
	       for coord in coords: # step through desired coordinate systems
		   CoordDir=pmag.get_dictitem(SampDir,'specimen_tilt_correction',coord,'T') # get all the directions for this sample
		   if len(CoordDir)>0: # there are some with this coordinate system
		       if Caverage==0: # look component by component
			   for comp in Comps:
			       CompDir=pmag.get_dictitem(CoordDir,'specimen_comp_name',comp,'T') # get all directions from this component
			       if len(CompDir)>0: # there are some
				   PmagSampRec=pmag.lnpbykey(CompDir,'sample','specimen') # get a sample average from all specimens
				   PmagSampRec["er_location_name"]=CompDir[0]['er_location_name'] # decorate the sample record
				   PmagSampRec["er_site_name"]=CompDir[0]['er_site_name']
				   PmagSampRec["er_sample_name"]=samp
				   PmagSampRec["er_citation_names"]="This study"
				   PmagSampRec["er_analyst_mail_names"]=user
				   PmagSampRec['magic_software_packages']=version_num
				   if nocrit!=1:PmagSampRec['pmag_criteria_codes']="ACCEPT"
				   if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
				   site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
				   if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
				   PmagSampRec['sample_comp_name']=comp
				   PmagSampRec['sample_tilt_correction']=coord
				   PmagSampRec['er_specimen_names']= pmag.get_list(CompDir,'er_specimen_name') # get a list of the specimen names used
				   PmagSampRec['magic_method_codes']= pmag.get_list(CompDir,'magic_method_codes') # get a list of the methods used
				   if nocrit!=1: # apply selection criteria
                                       kill=pmag.grade(PmagSampRec,accept,'sample_dir')
                                   else:
                                       kill=[]
				   if len(kill)==0:
					SampDirs.append(PmagSampRec)
					if vgps==1: # if sample level VGP info desired, do that now
					    PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
					    if PmagResRec!="":PmagResults.append(PmagResRec)
                                        PmagSamps.append(PmagSampRec)
		       if Caverage==1: # average all components together  basically same as above
			   PmagSampRec=pmag.lnpbykey(CoordDir,'sample','specimen')
			   PmagSampRec["er_location_name"]=CoordDir[0]['er_location_name']
			   PmagSampRec["er_site_name"]=CoordDir[0]['er_site_name']
			   PmagSampRec["er_sample_name"]=samp
			   PmagSampRec["er_citation_names"]="This study"
			   PmagSampRec["er_analyst_mail_names"]=user
			   PmagSampRec['magic_software_packages']=version_num
			   if nocrit!=1:PmagSampRec['pmag_criteria_codes']=""
			   if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
			   site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
			   if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
			   PmagSampRec['sample_tilt_correction']=coord
			   PmagSampRec['sample_comp_name']= pmag.get_list(CoordDir,'specimen_comp_name') # get components used
			   PmagSampRec['er_specimen_names']= pmag.get_list(CoordDir,'er_specimen_name') # get specimne names averaged
			   PmagSampRec['magic_method_codes']= pmag.get_list(CoordDir,'magic_method_codes') # assemble method codes
			   if nocrit!=1: # apply selection criteria
                               kill=pmag.grade(PmagSampRec,accept,'sample_dir')
			       if len(kill)==0: # passes the mustard
				   SampDirs.append(PmagSampRec)
				   if vgps==1:
				       PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
				       if PmagResRec!="":PmagResults.append(PmagResRec)
			   else: # take everything
			       SampDirs.append(PmagSampRec)
			       if vgps==1:
				   PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
				   if PmagResRec!="":PmagResults.append(PmagResRec)
			   PmagSamps.append(PmagSampRec)
	if Iaverage==1: #  average by sample if desired
	   SampI=pmag.get_dictitem(SpecInts,'er_sample_name',samp,'T') # get all the intensity data for this sample
	   if len(SampI)>0: # there are some
	       PmagSampRec=pmag.average_int(SampI,'specimen','sample') # get average intensity stuff
	       PmagSampRec["sample_description"]="sample intensity" # decorate sample record
	       PmagSampRec["sample_direction_type"]=""
	       PmagSampRec['er_site_name']=SampI[0]["er_site_name"]
	       PmagSampRec['er_sample_name']=samp
	       PmagSampRec['er_location_name']=SampI[0]["er_location_name"]
	       PmagSampRec["er_citation_names"]="This study"
	       PmagSampRec["er_analyst_mail_names"]=user
	       if agefile != "":   PmagSampRec=pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_", AgeNFO,DefaultAge)
	       site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
	       if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
	       PmagSampRec['er_specimen_names']= pmag.get_list(SampI,'er_specimen_name')
	       PmagSampRec['magic_method_codes']= pmag.get_list(SampI,'magic_method_codes')
	       if nocrit!=1:  # apply criteria!
                   kill=pmag.grade(PmagSampRec,accept,'sample_int')
                   if len(kill)==0:
                       PmagSampRec['pmag_criteria_codes']="ACCEPT"
	               SampInts.append(PmagSampRec)
	               PmagSamps.append(PmagSampRec)
                   else:PmagSampRec={} # sample rejected
               else: # no criteria
	           SampInts.append(PmagSampRec)
	           PmagSamps.append(PmagSampRec)
                   PmagSampRec['pmag_criteria_codes']=""
	       if vgps==1 and get_model_lat!=0 and PmagSampRec!={}: #
		  if get_model_lat==1: # use sample latitude
		      PmagResRec=pmag.getsampVDM(PmagSampRec,SampNFO)
                      del(PmagResRec['model_lat']) # get rid of the model lat key
		  elif get_model_lat==2: # use model latitude
		      PmagResRec=pmag.getsampVDM(PmagSampRec,ModelLats)
		      if PmagResRec!={}:PmagResRec['magic_method_codes']=PmagResRec['magic_method_codes']+":IE-MLAT"
		  if PmagResRec!={}:
                      PmagResRec['er_specimen_names']=PmagSampRec['er_specimen_names']
                      PmagResRec['er_sample_names']=PmagSampRec['er_sample_name']
                      PmagResRec['pmag_criteria_codes']='ACCEPT'
                      PmagResRec['average_int_sigma_perc']=PmagSampRec['sample_int_sigma_perc']
                      PmagResRec['average_int_sigma']=PmagSampRec['sample_int_sigma']
                      PmagResRec['average_int_n']=PmagSampRec['sample_int_n']
                      PmagResRec['vadm_n']=PmagSampRec['sample_int_n']
                      PmagResRec['data_type']='i'
                      PmagResults.append(PmagResRec)
    if len(PmagSamps)>0:
	TmpSamps,keylist=pmag.fillkeys(PmagSamps) # fill in missing keys from different types of records       
	pmag.magic_write(sampout,TmpSamps,'pmag_samples') # save in sample output file
	print ' sample averages written to ',sampout
   
#
#create site averages from specimens or samples as specified
#
    for site in sites:
	if Daverage==0: key,dirlist='specimen',SpecDirs # if specimen averages at site level desired
	if Daverage==1: key,dirlist='sample',SampDirs # if sample averages at site level desired
	tmp=pmag.get_dictitem(dirlist,'er_site_name',site,'T') # get all the sites with  directions
	tmp1=pmag.get_dictitem(tmp,key+'_tilt_correction',coords[-1],'T') # use only the last coordinate if Caverage==0
	sd=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T') # fish out site information (lat/lon, etc.)
	if len(sd)>0:
            sitedat=sd[0]
	    if Caverage==0: # do component wise averaging
		for comp in Comps:
		    siteD=pmag.get_dictitem(tmp1,key+'_comp_name',comp,'T') # get all components comp
		    if len(siteD)>0: # there are some for this site and component name
			PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get an average for this site
			PmagSiteRec['site_comp_name']=comp # decorate the site record
			PmagSiteRec["er_location_name"]=siteD[0]['er_location_name']
			PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
			PmagSiteRec['site_tilt_correction']=coords[-1]
			PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
                        if Daverage==1:
			    PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
                        else:
			    PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
# determine the demagnetization code (DC3,4 or 5) for this site
			AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
			Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
			DC=3
			if AFnum>0:DC+=1
			if Tnum>0:DC+=1
			PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
			PmagSiteRec['magic_method_codes'].strip(":")
			if plotsites==1:
                            print PmagSiteRec['er_site_name']
                            pmagplotlib.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key) # plot and list the data
                            pmagplotlib.drawFIGS(EQ)
			PmagSites.append(PmagSiteRec) 
	    else: # last component only
	        siteD=tmp1[:] # get the last orientation system specified
	        if len(siteD)>0: # there are some
	            PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get the average for this site 
	            PmagSiteRec["er_location_name"]=siteD[0]['er_location_name'] # decorate the record
    		    PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
		    PmagSiteRec['site_comp_name']=comp
		    PmagSiteRec['site_tilt_correction']=coords[-1]
		    PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
		    PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
		    PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
    		    AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
    	    	    Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
	    	    DC=3
		    if AFnum>0:DC+=1
		    if Tnum>0:DC+=1
		    PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
		    PmagSiteRec['magic_method_codes'].strip(":")
		    if Daverage==0:PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
	    	    if plotsites==1:
                        pmagplotlib.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key)
                        pmagplotlib.drawFIGS(EQ)
		    PmagSites.append(PmagSiteRec)
        else:
            print 'site information not found in er_sites for site, ',site,' site will be skipped'
    for PmagSiteRec in PmagSites: # now decorate each dictionary some more, and calculate VGPs etc. for results table
	PmagSiteRec["er_citation_names"]="This study"
	PmagSiteRec["er_analyst_mail_names"]=user
	PmagSiteRec['magic_software_packages']=version_num
	if agefile != "": PmagSiteRec= pmag.get_age(PmagSiteRec,"er_site_name","site_inferred_",AgeNFO,DefaultAge)
	PmagSiteRec['pmag_criteria_codes']='ACCEPT'
	if 'site_n_lines' in PmagSiteRec.keys() and 'site_n_planes' in PmagSiteRec.keys() and PmagSiteRec['site_n_lines']!="" and PmagSiteRec['site_n_planes']!="":
	    if int(PmagSiteRec["site_n_planes"])>0:
		PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM-LP"
	    elif int(PmagSiteRec["site_n_lines"])>2:
		PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM"
	    kill=pmag.grade(PmagSiteRec,accept,'site_dir')
            if len(kill)==0: 
		PmagResRec={} # set up dictionary for the pmag_results table entry
		PmagResRec['data_type']='i' # decorate it a bit
		PmagResRec['magic_software_packages']=version_num
		PmagSiteRec['site_description']='Site direction included in results table' 
		PmagResRec['pmag_criteria_codes']='ACCEPT'
		dec=float(PmagSiteRec["site_dec"])
		inc=float(PmagSiteRec["site_inc"])
                if 'site_alpha95' in PmagSiteRec.keys() and PmagSiteRec['site_alpha95']!="": 
		    a95=float(PmagSiteRec["site_alpha95"])
                else:a95=180.
	        sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T')[0] # fish out site information (lat/lon, etc.)
		lat=float(sitedat['site_lat'])
		lon=float(sitedat['site_lon'])
		plong,plat,dp,dm=pmag.dia_vgp(dec,inc,a95,lat,lon) # get the VGP for this site
		if PmagSiteRec['site_tilt_correction']=='-1':C=' (spec coord) '
		if PmagSiteRec['site_tilt_correction']=='0':C=' (geog. coord) '
		if PmagSiteRec['site_tilt_correction']=='100':C=' (strat. coord) '
		PmagResRec["pmag_result_name"]="VGP Site: "+PmagSiteRec["er_site_name"] # decorate some more
		PmagResRec["result_description"]="Site VGP, coord system = "+str(coord)+' component: '+comp
		PmagResRec['er_site_names']=PmagSiteRec['er_site_name']
		PmagResRec['pmag_criteria_codes']='ACCEPT'
		PmagResRec['er_citation_names']='This study'
		PmagResRec['er_analyst_mail_names']=user
		PmagResRec["er_location_names"]=PmagSiteRec["er_location_name"]
                if Daverage==1:
		    PmagResRec["er_sample_names"]=PmagSiteRec["er_sample_names"]
                else:
		    PmagResRec["er_specimen_names"]=PmagSiteRec["er_specimen_names"]
		PmagResRec["tilt_correction"]=PmagSiteRec['site_tilt_correction']
		PmagResRec["pole_comp_name"]=PmagSiteRec['site_comp_name']
		PmagResRec["average_dec"]=PmagSiteRec["site_dec"]
		PmagResRec["average_inc"]=PmagSiteRec["site_inc"]
		PmagResRec["average_alpha95"]=PmagSiteRec["site_alpha95"]
		PmagResRec["average_n"]=PmagSiteRec["site_n"]
		PmagResRec["average_n_lines"]=PmagSiteRec["site_n_lines"]
		PmagResRec["average_n_planes"]=PmagSiteRec["site_n_planes"]            
		PmagResRec["vgp_n"]=PmagSiteRec["site_n"]
		PmagResRec["average_k"]=PmagSiteRec["site_k"]
		PmagResRec["average_r"]=PmagSiteRec["site_r"]
		PmagResRec["average_lat"]='%10.4f ' %(lat)
		PmagResRec["average_lon"]='%10.4f ' %(lon)
		if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
		site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
		if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
		PmagResRec["vgp_lat"]='%7.1f ' % (plat)
		PmagResRec["vgp_lon"]='%7.1f ' % (plong)
		PmagResRec["vgp_dp"]='%7.1f ' % (dp)
		PmagResRec["vgp_dm"]='%7.1f ' % (dm)
		PmagResRec["magic_method_codes"]= PmagSiteRec["magic_method_codes"]
		if PmagSiteRec['site_tilt_correction']=='0':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-GEO"
                if PmagSiteRec['site_tilt_correction']=='100':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-TILT"
                PmagSiteRec['site_polarity']=""
                if polarity==1: # assign polarity based on angle of pole lat to spin axis - may want to re-think this sometime
                      angle=pmag.angle([0,0],[0,(90-plat)])
                      if angle <= 55.: PmagSiteRec["site_polarity"]='n'
                      if angle > 55. and angle < 125.: PmagSiteRec["site_polarity"]='t'
                      if angle >= 125.: PmagSiteRec["site_polarity"]='r'
                PmagResults.append(PmagResRec)
    if noInt!=1 and nositeints!=1:
      for site in sites: # now do intensities for each site
        if plotsites==1:print site
        if Iaverage==0: key,intlist='specimen',SpecInts # if using specimen level data
        if Iaverage==1: key,intlist='sample',PmagSamps # if using sample level data
        Ints=pmag.get_dictitem(intlist,'er_site_name',site,'T') # get all the intensities  for this site
        if len(Ints)>0: # there are some
            PmagSiteRec=pmag.average_int(Ints,key,'site') # get average intensity stuff for site table
            PmagResRec=pmag.average_int(Ints,key,'average') # get average intensity stuff for results table
            if plotsites==1: # if site by site examination requested - print this site out to the screen
                for rec in Ints:print rec['er_'+key+'_name'],' %7.1f'%(1e6*float(rec[key+'_int']))
                if len(Ints)>1:
                    print 'Average: ','%7.1f'%(1e6*float(PmagResRec['average_int'])),'N: ',len(Ints)
                    print 'Sigma: ','%7.1f'%(1e6*float(PmagResRec['average_int_sigma'])),'Sigma %: ',PmagResRec['average_int_sigma_perc']
                raw_input('Press any key to continue\n')
            er_location_name=Ints[0]["er_location_name"] 
            PmagSiteRec["er_location_name"]=er_location_name # decorate the records
            PmagSiteRec["er_citation_names"]="This study"
            PmagResRec["er_location_names"]=er_location_name
            PmagResRec["er_citation_names"]="This study"
            PmagSiteRec["er_analyst_mail_names"]=user
            PmagResRec["er_analyst_mail_names"]=user
            PmagResRec["data_type"]='i'
            if Iaverage==0:
                PmagSiteRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name') # list of all specimens used
                PmagResRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name')
            PmagSiteRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name') # list of all samples used
            PmagResRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name')
            PmagSiteRec['er_site_name']= site
            PmagResRec['er_site_names']= site
            PmagSiteRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
            PmagResRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
            kill=pmag.grade(PmagSiteRec,accept,'site_int')
            if nocrit==1 or len(kill)==0:
                b,sig=float(PmagResRec['average_int']),""
                if(PmagResRec['average_int_sigma'])!="":sig=float(PmagResRec['average_int_sigma'])
                sdir=pmag.get_dictitem(PmagResults,'er_site_names',site,'T') # fish out site direction
                if len(sdir)>0 and  sdir[-1]['average_inc']!="": # get the VDM for this record using last average inclination (hope it is the right one!)
                        inc=float(sdir[0]['average_inc']) # 
                        mlat=pmag.magnetic_lat(inc) # get magnetic latitude using dipole formula
                        PmagResRec["vdm"]='%8.3e '% (pmag.b_vdm(b,mlat)) # get VDM with magnetic latitude
                        PmagResRec["vdm_n"]=PmagResRec['average_int_n']
                        if 'average_int_sigma' in PmagResRec.keys() and PmagResRec['average_int_sigma']!="":
                            vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),mlat)
                            PmagResRec["vdm_sigma"]='%8.3e '% (vdm_sig)
                        else:
                            PmagResRec["vdm_sigma"]=""
                mlat="" # define a model latitude
                if get_model_lat==1: # use present site latitude
                    mlats=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T')
                    if len(mlats)>0: mlat=mlats[0]['site_lat']
                elif get_model_lat==2: # use a model latitude from some plate reconstruction model (or something)
                    mlats=pmag.get_dictitem(ModelLats,'er_site_name',site,'T')
                    if len(mlats)>0: PmagResRec['model_lat']=mlats[0]['site_model_lat']
                    mlat=PmagResRec['model_lat']
                if mlat!="":
                    PmagResRec["vadm"]='%8.3e '% (pmag.b_vdm(b,float(mlat))) # get the VADM using the desired latitude
                    if sig!="":
                        vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),float(mlat))
                        PmagResRec["vadm_sigma"]='%8.3e '% (vdm_sig)
                        PmagResRec["vadm_n"]=PmagResRec['average_int_n']
                    else:
                        PmagResRec["vadm_sigma"]=""
	        sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T') # fish out site information (lat/lon, etc.)
                if len(sitedat)>0:
                    sitedat=sitedat[0]
                    PmagResRec['average_lat']=sitedat['site_lat']
                    PmagResRec['average_lon']=sitedat['site_lon']
                else:
                    PmagResRec['average_lon']='UNKNOWN'
                    PmagResRec['average_lon']='UNKNOWN'
                PmagResRec['magic_software_packages']=version_num
                PmagResRec["pmag_result_name"]="V[A]DM: Site "+site
                PmagResRec["result_description"]="V[A]DM of site"
                PmagResRec["pmag_criteria_codes"]="ACCEPT"
                if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
                site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
                if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
                PmagSites.append(PmagSiteRec)
                PmagResults.append(PmagResRec)
    if len(PmagSites)>0:
        Tmp,keylist=pmag.fillkeys(PmagSites)         
        pmag.magic_write(siteout,Tmp,'pmag_sites')
        print ' sites written to ',siteout
    else: print "No Site level table"
    if len(PmagResults)>0:
        TmpRes,keylist=pmag.fillkeys(PmagResults)         
        pmag.magic_write(resout,TmpRes,'pmag_results')
        print ' results written to ',resout
    else: print "No Results level table"
示例#3
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 '-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)
                   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)
    #                   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)
        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"
示例#4
0
def main():
    """
    NAME
        customize_criteria.py

    DESCRIPTION
        Allows user to specify acceptance criteria, saves them in pmag_criteria.txt

    SYNTAX
        customize_criteria.py [-h][command line options]

    OPTIONS
        -h prints help message and quits
        -f IFILE, reads in existing criteria
        -F OFILE, writes to pmag_criteria format file

    DEFAULTS
         IFILE: pmag_criteria.txt
         OFILE: pmag_criteria.txt
  
    OUTPUT
        creates a pmag_criteria.txt formatted output file
    """
    infile,critout="","pmag_criteria.txt"
# parse command line options
    if  '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-f' in sys.argv:
        ind=sys.argv.index('-f')
        infile=sys.argv[ind+1]
        crit_data,file_type=pmag.magic_read(infile)
        if file_type!='pmag_criteria':
            print 'bad input file'
            print main.__doc__
            sys.exit()
        print "Acceptance criteria read in from ", infile
    if '-F' in sys.argv:
        ind=sys.argv.index('-F')
        critout=sys.argv[ind+1]
    Dcrit,Icrit,nocrit=0,0,0
    custom='1'
    crit=raw_input(" [0] Use no acceptance criteria?\n [1] Use default criteria\n [2] customize criteria \n ")
    if crit=='0':
        print 'Very very loose criteria saved in ',critout
        crit_data=pmag.default_criteria(1)
        pmag.magic_write(critout,crit_data,'pmag_criteria')
        sys.exit()
    crit_data=pmag.default_criteria(0)
    if crit=='1':
        print 'Default criteria saved in ',critout
        pmag.magic_write(critout,crit_data,'pmag_criteria')
        sys.exit()
    CritRec=crit_data[0]
    crit_keys=CritRec.keys()
    crit_keys.sort()
    print "Enter new threshold value.\n Return to keep default.\n Leave blank to not use as a criterion\n "
    for key in crit_keys:
        if key!='pmag_criteria_code' and key!='er_citation_names' and key!='criteria_definition' and CritRec[key]!="":
            print key, CritRec[key]
            new=raw_input('new value: ')
            if new != "": CritRec[key]=(new)
    pmag.magic_write(critout,[CritRec],'pmag_criteria')
    print "Criteria saved in pmag_criteria.txt"