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 = .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
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:
# make sure all new records have same set of keys
PmagSpecRec[key] = ""
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.plot_arai_zij(AZD, araiblock, zijdblock, s,
units[0])
if verbose:
pmagplotlib.draw_figs(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
# find which type of intensity
while mkey == "" and k < len(Mkeys) - 1:
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:
# strip off potential nasty spaces
meth.replace(" ", "")
if 'LT-T-I' in meths and Tnorm == "": # found first total TRM
# normalize by total TRM
Tnorm = float(tdrec[mkey])
# put in the zero step
tdsblock.append([273, zijdblock[0][3] / Tnorm, 1.])
# found a LP-TRM-TD demag step, now need complementary LT-T-Z from zijdblock
if 'LT-T-Z' in meths and Tnorm != "":
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.plot_tds(AZD['TDS'], tdsblock,
s + ':LP-PI-TDS:')
if verbose:
pmagplotlib(draw_figs(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'
# put in CurrRec, take out of PriorRecs
del PriorRecs[k]
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.plot_b(AZD, araiblock,
zijdblock, pars)
if verbose:
pmagplotlib.draw_figs(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'])
)
# calculate best fit parameters through TRM acquisition data, and get new banc
NLpars = nlt.NLtrm(
Bs, TRMs, best, blab, 0)
Mp, Bp = [], []
for k in range(int(max(Bs) * 1e6)):
Bp.append(float(k) * 1e-6)
# predicted NRM for this field
npred = nlt.TRM(
Bp[-1], NLpars['xopt'][0],
NLpars['xopt'][1])
Mp.append(npred)
pmagplotlib.plot_trm(
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.draw_figs(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.plot_b(AZD, araiblock, zijdblock, pars)
if verbose:
pmagplotlib.draw_figs(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']))
# calculate best fit parameters through TRM acquisition data, and get new banc
NLpars = nlt.NLtrm(Bs, TRMs, best, blab, 0)
#
Mp, Bp = [], []
for k in range(int(max(Bs) * 1e6)):
Bp.append(float(k) * 1e-6)
# predicted NRM for this field
npred = nlt.TRM(Bp[-1], NLpars['xopt'][0],
NLpars['xopt'][1])
files = {}
for key in AZD.keys():
files[key] = s + '_' + key + fmt
pmagplotlib.save_plots(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 = input('Return for next specimen \n')
if ans == "":
specimen += 1
if ans == "d":
save_redo(PriorRecs, inspec)
CurrRec = []
pmagplotlib.plot_arai_zij(AZD, araiblock,
zijdblock, s, units[0])
if verbose:
pmagplotlib.draw_figs(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.save_plots(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(zijdblock):
end = len(zijdblock) - 1
GoOn = 0
while GoOn == 0:
answer = input(
'Enter index of first point for calculation: ['
+ str(start) + '] ')
try:
start = int(answer)
answer = 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'
# this is redundant, but helpful - won't be imported
PmagSpecRec["direction_type"] = 'l'
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.plot_arai_zij(AZD, araiblock,
zijdblock, s, units[0])
pmagplotlib.plot_b(AZD, araiblock, zijdblock, pars)
if verbose:
pmagplotlib.draw_figs(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']))
# calculate best fit parameters through TRM acquisition data, and get new banc
NLpars = nlt.NLtrm(Bs, TRMs, best, blab, 0)
Mp, Bp = [], []
for k in range(int(max(Bs) * 1e6)):
Bp.append(float(k) * 1e-6)
# predicted NRM for this field
npred = nlt.TRM(Bp[-1], NLpars['xopt'][0],
NLpars['xopt'][1])
Mp.append(npred)
pmagplotlib.plot_trm(
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.draw_figs(AZD)
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars[
"specimen_b"]
pars, kill = pmag.scoreit(pars, PmagSpecRec,
accept, '', verbose)
saveit = input(
"Save this interpretation? [y]/n \n")
if saveit != 'n':
# put back an interpretation
PriorRecs.append(PmagSpecRec)
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.add_borders(
AZD, titles, black, purple)
pmagplotlib.save_plots(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 = input(" Save last plot? 1/[0] ")
if ans == "1":
if fmt != ".pmag":
files = {}
for key in AZD.keys():
files[key] = s + '_' + key + fmt
pmagplotlib.save_plots(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")
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"
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"
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=.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 list(critrec.keys()): # accommodate Shaar's new criterion
critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
for key in list(critrec.keys()):
if key not in list(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,'r')
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 list(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 list(rec.keys()):PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
if "magic_instrument_codes" not in list(rec.keys()):
PmagSpecRec["magic_instrument_codes"]="unknown"
else:
PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"]
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_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 list(pars.keys()): PmagSpecRec['specimen_scat']=pars['specimen_scat']
if 'specimen_frac' in list(pars.keys()): PmagSpecRec['specimen_frac']='%5.3f'%(pars['specimen_frac'])
if 'specimen_gmax' in list(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_gamma"]='%7.1f'%(pars["specimen_gamma"])
if pars["magic_method_codes"]!="" and pars["magic_method_codes"] not in methcodes: methcodes.append(pars["magic_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 list(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 list(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
nrm_specimens_magic.py
DESCRIPTION
converts NRM data in a magic_measurements type file to
geographic and tilt corrected data in a pmag_specimens type file
SYNTAX
nrm_specimens_magic.py [-h][command line options]
OPTIONS:
-h prints the help message and quits
-f MFILE: specify input file
-fsa SFILE: specify er_samples format file [with orientations]
-F PFILE: specify output file
-A do not average replicate measurements
-crd [g, t]: specify coordinate system ([g]eographic or [t]ilt adjusted)
NB: you must have the SFILE in this directory
DEFAULTS
MFILE: magic_measurements.txt
PFILE: nrm_specimens.txt
SFILE: er_samples.txt
coord: specimen
average replicate measurements?: YES
"""
#
# define some variables
#
beg,end,pole,geo,tilt,askave,save=0,0,[],0,0,0,0
samp_file=1
args=sys.argv
geo,tilt,orient=0,0,0
doave=1
user,comment,doave,coord="","",1,""
dir_path='.'
if "-h" in args:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
meas_file=dir_path+"/magic_measurements.txt"
pmag_file=dir_path+"/nrm_specimens.txt"
samp_file=dir_path+"/er_samples.txt"
if "-A" in args: doave=0
if "-f" in args:
ind=args.index("-f")
meas_file=sys.argv[ind+1]
if "-F" in args:
ind=args.index("-F")
pmag_file=dir_path+'/'+sys.argv[ind+1]
speclist=[]
if "-fsa" in args:
ind=args.index("-fsa")
samp_file=dir_path+'/'+sys.argv[ind+1]
if "-crd" in args:
ind=args.index("-crd")
coord=sys.argv[ind+1]
if coord=="g":
geo,orient=1,1
if coord=="t":
tilt,orient,geo=1,1,1
#
# read in data
if samp_file!="":
samp_data,file_type=pmag.magic_read(samp_file)
if file_type != 'er_samples':
print file_type
print "This is not a valid er_samples file "
sys.exit()
else: print samp_file,' read in with ',len(samp_data),' records'
else:
print 'no orientations - will create file in specimen coordinates'
geo,tilt,orient=0,0,0
#
#
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()
#
if orient==1:
# set orientation priorities
SO_methods=[]
orientation_priorities={'0':'SO-SUN','1':'SO-GPS-DIFF','2':'SO-SIGHT-BACK','3':'SO-CMD-NORTH','4':'SO-MAG'}
for rec in samp_data:
if "magic_method_codes" in rec:
methlist=rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods: SO_methods.append(meth.strip())
#
# sort the sample names
#
sids=pmag.get_specs(meas_data)
#
#
PmagSpecRecs=[]
for s in sids:
skip=0
recnum=0
PmagSpecRec={}
PmagSpecRec["er_analyst_mail_names"]=user
method_codes,inst_code=[],""
# find the data from the meas_data file for this sample
#
# collect info for the PmagSpecRec dictionary
#
meas_meth=[]
for rec in meas_data: # copy of vital stats to PmagSpecRec from first spec record
if rec["er_specimen_name"]==s:
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["er_citation_names"]="This study"
PmagSpecRec["magic_instrument_codes"]=""
if "magic_experiment_name" not in rec.keys():
rec["magic_experiment_name"]=""
if "magic_instrument_codes" not in rec.keys():
rec["magic_instrument_codes"]=""
else:
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
if len(rec["magic_instrument_codes"]) > len(inst_code):
inst_code=rec["magic_instrument_codes"]
PmagSpecRec["magic_instrument_codes"]=inst_code # copy over instruments
break
#
# now check for correct method labels for all measurements
#
nrm_data=[]
for meas_rec in meas_data:
if meas_rec['er_specimen_name']==PmagSpecRec['er_specimen_name']:
meths=meas_rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in meas_meth:meas_meth.append(meth)
if "LT-NO" in meas_meth:nrm_data.append(meas_rec)
#
data,units=pmag.find_dmag_rec(s,nrm_data)
#
datablock=data
#
# find replicate measurements at NRM step and average them
#
Specs=[]
if doave==1:
step_meth,avedata=pmag.vspec(data)
if len(avedata) != len(datablock):
method_codes.append("DE-VM")
SpecRec=avedata[0]
print 'averaging data '
else: SpecRec=data[0]
Specs.append(SpecRec)
else:
for spec in data:Specs.append(spec)
for SpecRec in Specs:
#
# do geo or stratigraphic correction now
#
if geo==1:
#
# find top priority orientation method
redo,p=1,0
if len(SO_methods)<=1:
az_type=SO_methods[0]
orient=pmag.find_samp_rec(PmagSpecRec["er_sample_name"],samp_data,az_type)
if orient["sample_azimuth"] !="": method_codes.append(az_type)
redo=0
while redo==1:
if p>=len(orientation_priorities):
print "no orientation data for ",s
skip,redo=1,0
break
az_type=orientation_priorities[str(p)]
orient=pmag.find_samp_rec(PmagSpecRec["er_sample_name"],samp_data,az_type)
if orient["sample_azimuth"] !="":
method_codes.append(az_type.strip())
redo=0
elif orient["sample_azimuth"] =="":
p+=1
#
# if stratigraphic selected, get stratigraphic correction
#
if skip==0 and orient["sample_azimuth"]!="" and orient["sample_dip"]!="":
d_geo,i_geo=pmag.dogeo(SpecRec[1],SpecRec[2],orient["sample_azimuth"],orient["sample_dip"])
SpecRec[1]=d_geo
SpecRec[2]=i_geo
if tilt==1 and "sample_bed_dip" in orient.keys() and orient['sample_bed_dip']!="":
d_tilt,i_tilt=pmag.dotilt(d_geo,i_geo,orient["sample_bed_dip_direction"],orient["sample_bed_dip"])
SpecRec[1]=d_tilt
SpecRec[2]=i_tilt
if skip==0:
PmagSpecRec["specimen_dec"]='%7.1f ' %(SpecRec[1])
PmagSpecRec["specimen_inc"]='%7.1f ' %(SpecRec[2])
if geo==1 and tilt==0:PmagSpecRec["specimen_tilt_correction"]='0'
if geo==1 and tilt==1: PmagSpecRec["specimen_tilt_correction"]='100'
if geo==0 and tilt==0: PmagSpecRec["specimen_tilt_correction"]='-1'
PmagSpecRec["specimen_direction_type"]='l'
PmagSpecRec["magic_method_codes"]="LT-NO"
if len(method_codes) != 0:
methstring=""
for meth in method_codes:
methstring=methstring+ ":" +meth
PmagSpecRec["magic_method_codes"]=methstring[1:]
PmagSpecRec["specimen_description"]="NRM data"
PmagSpecRecs.append(PmagSpecRec)
pmag.magic_write(pmag_file,PmagSpecRecs,'pmag_specimens')
print "Data saved in ",pmag_file
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored.
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets magic_measurements format input file, default: magic_measurements.txt
-fsp SPECFILE: sets pmag_specimens format file with prior interpreations, default: zeq_specimens.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-fsa SAMPFILE: sets er_samples format file with orientation information, default: er_samples.txt
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave,e,b=1,0,0 # average replicates, initial end and beginning step
plots,coord=0,'s'
noorient=0
version_num=pmag.get_version()
verbose=pmagplotlib.verbose
beg_pca,end_pca,direction_type="","",'l'
calculation_type,fmt="","svg"
user,spec_keys,locname="",[],''
plot_file=""
sfile=""
plot_file=""
PriorRecs=[] # empty list for prior interpretations
backup=0
specimen="" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
else:
dir_path='.'
inspec=dir_path+'/'+'zeq_specimens.txt'
meas_file,geo,tilt,ask,samp_file=dir_path+'/magic_measurements.txt',0,0,0,dir_path+'/er_samples.txt'
if '-f' in sys.argv:
ind=sys.argv.index('-f')
meas_file=dir_path+'/'+sys.argv[ind+1]
if '-fsp' in sys.argv:
ind=sys.argv.index('-fsp')
inspec=dir_path+'/'+sys.argv[ind+1]
if '-fsa' in sys.argv:
ind=sys.argv.index('-fsa')
samp_file=dir_path+'/'+sys.argv[ind+1]
sfile='ok'
if '-crd' in sys.argv:
ind=sys.argv.index('-crd')
coord=sys.argv[ind+1]
if coord=='g' or coord=='t':
samp_data,file_type=pmag.magic_read(samp_file)
if file_type=='er_samples':sfile='ok'
geo=1
if coord=='t':tilt=1
if '-spc' in sys.argv:
ind=sys.argv.index('-spc')
specimen=sys.argv[ind+1]
if '-dir' in sys.argv:
ind=sys.argv.index('-dir')
direction_type=sys.argv[ind+1]
beg_pca=int(sys.argv[ind+2])
end_pca=int(sys.argv[ind+3])
if direction_type=='L':calculation_type='DE-BFL'
if direction_type=='P':calculation_type='DE-BFP'
if direction_type=='F':calculation_type='DE-FM'
if '-Fp' in sys.argv:
ind=sys.argv.index('-Fp')
plot_file=dir_path+'/'+sys.argv[ind+1]
if '-A' in sys.argv: doave=0
if '-sav' in sys.argv:
plots=1
verbose=0
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
#
first_save=1
meas_data,file_type=pmag.magic_read(meas_file)
changeM,changeS=0,0 # check if data or interpretations have changed
if file_type != 'magic_measurements':
print file_type
print file_type,"This is not a valid magic_measurements file "
sys.exit()
for rec in meas_data:
if "magic_method_codes" not in rec.keys(): rec["magic_method_codes"]=""
methods=""
tmp=rec["magic_method_codes"].replace(" ","").split(":")
for meth in tmp:
methods=methods+meth+":"
rec["magic_method_codes"]=methods[:-1] # get rid of annoying spaces in Anthony's export files
if "magic_instrument_codes" not in rec.keys() :rec["magic_instrument_codes"]=""
PriorSpecs=[]
PriorRecs,file_type=pmag.magic_read(inspec)
if len(PriorRecs)==0:
if verbose:print "starting new file ",inspec
for Rec in PriorRecs:
if 'magic_software_packages' not in Rec.keys():Rec['magic_software_packages']=""
if Rec['er_specimen_name'] not in PriorSpecs:
if 'specimen_comp_name' not in Rec.keys():Rec['specimen_comp_name']="A"
PriorSpecs.append(Rec['er_specimen_name'])
else:
if 'specimen_comp_name' not in Rec.keys():Rec['specimen_comp_name']="A"
if "magic_method_codes" in Rec.keys():
methods=[]
tmp=Rec["magic_method_codes"].replace(" ","").split(":")
for meth in tmp:
methods.append(meth)
if 'DE-FM' in methods:
Rec['calculation_type']='DE-FM' # this won't be imported but helps
if 'DE-BFL' in methods:
Rec['calculation_type']='DE-BFL'
if 'DE-BFL-A' in methods:
Rec['calculation_type']='DE-BFL-A'
if 'DE-BFL-O' in methods:
Rec['calculation_type']='DE-BFL-O'
if 'DE-BFP' in methods:
Rec['calculation_type']='DE-BFP'
else:
Rec['calculation_type']='DE-BFL' # default is to assume a best-fit line
#
# get list of unique specimen names
#
sids=pmag.get_specs(meas_data)
#
# set up plots, angle sets X axis to horizontal, direction_type 'l' is best-fit line
# direction_type='p' is great circle
#
#
# draw plots for sample s - default is just to step through zijderveld diagrams
#
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
ZED={}
ZED['eqarea'],ZED['zijd'], ZED['demag']=1,2,3
pmagplotlib.plot_init(ZED['eqarea'],5,5)
pmagplotlib.plot_init(ZED['zijd'],6,5)
pmagplotlib.plot_init(ZED['demag'],5,5)
save_pca=0
if specimen=="":
k = 0
else:
k=sids.index(specimen)
angle,direction_type="",""
setangle=0
CurrRecs=[]
while k < len(sids):
CurrRecs=[]
if setangle==0:angle=""
method_codes,inst_code=[],""
s=sids[k]
PmagSpecRec={}
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec['magic_software_packages']=version_num
PmagSpecRec['specimen_description']=""
PmagSpecRec['magic_method_codes']=""
if verbose and s!="":print s, k , 'out of ',len(sids)
#
# collect info for the PmagSpecRec dictionary
#
s_meas=pmag.get_dictitem(meas_data,'er_specimen_name',s,'T') # fish out this specimen
s_meas=pmag.get_dictitem(s_meas,'magic_method_codes','Z','has') # fish out zero field steps
if len(s_meas)>0:
for rec in s_meas: # fix up a few things for the output record
PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"] # copy over instruments
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']
if 'er_expedition_name' in rec.keys(): PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
PmagSpecRec["magic_method_codes"]=rec["magic_method_codes"]
if "magic_experiment_name" not in rec.keys():
PmagSpecRec["magic_experiment_names"]=""
else:
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
break
#
# find the data from the meas_data file for this specimen
#
data,units=pmag.find_dmag_rec(s,meas_data)
PmagSpecRec["measurement_step_unit"]= units
u=units.split(":")
if "T" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-AF"
if "K" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-T"
if "J" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-M"
#
# find prior interpretation
#
if len(CurrRecs)==0: # check if already in
beg_pca,end_pca="",""
calculation_type=""
if inspec !="":
if verbose: print " looking up previous interpretations..."
precs=pmag.get_dictitem(PriorRecs,'er_specimen_name',s,'T') # get all the prior recs with this specimen name
precs=pmag.get_dictitem(precs,'magic_method_codes','LP-DIR','has') # get the directional data
PriorRecs=pmag.get_dictitem(PriorRecs,'er_specimen_name',s,'F') # take them all out of prior recs
# get the ones that meet the current coordinate system
for prec in precs:
if 'specimen_tilt_correction' not in prec.keys() or prec['specimen_tilt_correction']=='-1':
crd='s'
elif prec['specimen_tilt_correction']=='0':
crd='g'
elif prec['specimen_tilt_correction']=='100':
crd='t'
else:
crd='?'
CurrRec={}
for key in prec.keys():CurrRec[key]=prec[key]
CurrRecs.append(CurrRec) # put in CurrRecs
method_codes= CurrRec["magic_method_codes"].replace(" ","").split(':')
calculation_type='DE-BFL'
if 'DE-FM' in method_codes: calculation_type='DE-FM'
if 'DE-BFP' in method_codes: calculation_type='DE-BFP'
if 'DE-BFL-A' in method_codes: calculation_type='DE-BFL-A'
if 'specimen_dang' not in CurrRec.keys():
if verbose:print 'Run mk_redo.py and zeq_magic_redo.py to get the specimen_dang values'
CurrRec['specimen_dang']=-1
if calculation_type!='DE-FM' and crd==coord: # not a fisher mean
if verbose:print "Specimen N MAD DANG start end dec inc type component coordinates"
if units=='K':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["specimen_dang"]),float(CurrRec["measurement_step_min"])-273,float(CurrRec["measurement_step_max"])-273,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif units=='T':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["specimen_dang"]),float(CurrRec["measurement_step_min"])*1e3,float(CurrRec["measurement_step_max"])*1e3,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif 'T' in units and 'K' in units:
if float(CurrRec['measurement_step_min'])<1.0 :
min=float(CurrRec['measurement_step_min'])*1e3
else:
min=float(CurrRec['measurement_step_min'])-273
if float(CurrRec['measurement_step_max'])<1.0 :
max=float(CurrRec['measurement_step_max'])*1e3
else:
max=float(CurrRec['measurement_step_max'])-273
if verbose:print '%s %i %7.1f %i %i %7.1f %7.1f %7.1f, %s %s\n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec['specimen_dang']),min,max,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,crd)
elif 'J' in units:
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec['specimen_dang']),float(CurrRec["measurement_step_min"]),float(CurrRec["measurement_step_max"]),float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif calculation_type=='DE-FM' and crd==coord: # fisher mean
if verbose:print "Specimen a95 DANG start end dec inc type component coordinates"
if units=='K':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),float(CurrRec["measurement_step_min"])-273,float(CurrRec["measurement_step_max"])-273,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif units=='T':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),float(CurrRec["measurement_step_min"])*1e3,float(CurrRec["measurement_step_max"])*1e3,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif 'T' in units and 'K' in units:
if float(CurrRec['measurement_step_min'])<1.0 :
min=float(CurrRec['measurement_step_min'])*1e3
else:
min=float(CurrRec['measurement_step_min'])-273
if float(CurrRec['measurement_step_max'])<1.0 :
max=float(CurrRec['measurement_step_max'])*1e3
else:
max=float(CurrRec['measurement_step_max'])-273
if verbose:print '%s %i %7.1f %i %i %7.1f %7.1f %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),min,max,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,crd)
elif 'J' in units:
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["measurement_step_min"]),float(CurrRec["measurement_step_max"]),float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
if len(CurrRecs)==0:beg_pca,end_pca="",""
datablock=data
noskip=1
if len(datablock) <3:
noskip=0
if backup==0:
k+=1
else:
k-=1
if len(CurrRecs)>0:
for rec in CurrRecs:
PriorRecs.append(rec)
CurrRecs=[]
else:
backup=0
if noskip:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
# #
# do geo or stratigraphic correction now
#
if geo==1:
#
# find top priority orientation method
orient,az_type=pmag.get_orient(samp_data,PmagSpecRec["er_sample_name"])
if az_type=='SO-NO':
if verbose: print "no orientation data for ",s
orient["sample_azimuth"]=0
orient["sample_dip"]=0
noorient=1
method_codes.append("SO-NO")
orient["sample_azimuth"]=0
orient["sample_dip"]=0
orient["sample_bed_dip_azimuth"]=0
orient["sample_bed_dip"]=0
noorient=1
method_codes.append("SO-NO")
else:
noorient=0
#
# if stratigraphic selected, get stratigraphic correction
#
tiltblock,geoblock=[],[]
for rec in datablock:
d_geo,i_geo=pmag.dogeo(rec[1],rec[2],float(orient["sample_azimuth"]),float(orient["sample_dip"]))
geoblock.append([rec[0],d_geo,i_geo,rec[3],rec[4],rec[5],rec[6]])
if tilt==1 and "sample_bed_dip" in orient.keys() and float(orient['sample_bed_dip'])!=0:
d_tilt,i_tilt=pmag.dotilt(d_geo,i_geo,float(orient["sample_bed_dip_direction"]),float(orient["sample_bed_dip"]))
tiltblock.append([rec[0],d_tilt,i_tilt,rec[3],rec[4],rec[5],rec[6]])
if tilt==1: plotblock=tiltblock
if geo==1 and tilt==0:plotblock=geoblock
if geo==0 and tilt==0: plotblock=datablock
#
# set the end pca point to last point if not set
if e==0 or e>len(plotblock)-1: e=len(plotblock)-1
if angle=="": angle=plotblock[0][1] # rotate to NRM declination
title=s+'_s'
if geo==1 and tilt==0 and noorient!=1:title=s+'_g'
if tilt==1 and noorient!=1:title=s+'_t'
pmagplotlib.plotZED(ZED,plotblock,angle,title,units)
if verbose:pmagplotlib.drawFIGS(ZED)
if len(CurrRecs)!=0:
for prec in CurrRecs:
if 'calculation_type' not in prec.keys():
calculation_type=''
else:
calculation_type=prec["calculation_type"]
direction_type=prec["specimen_direction_type"]
if calculation_type !="":
beg_pca,end_pca="",""
for j in range(len(datablock)):
if data[j][0]==float(prec["measurement_step_min"]):beg_pca=j
if data[j][0]==float(prec["measurement_step_max"]):end_pca=j
if beg_pca=="" or end_pca=="":
if verbose:
print "something wrong with prior interpretation "
break
if calculation_type!="":
if beg_pca=="":beg_pca=0
if end_pca=="":end_pca=len(plotblock)-1
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,geoblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,tiltblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,plotblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
#
# print out data for this sample to screen
#
recnum=0
for plotrec in plotblock:
if units=='T' and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if units=="K" and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if units=="J" and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0],' J',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if 'K' in units and 'T' in units:
if plotrec[0]>=1. and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if plotrec[0]<1. and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2],plotrec[6])
recnum += 1
if specimen!="":
if plot_file=="":
basename=locname+'_'+s
else:
basename=plot_file
files={}
for key in ZED.keys():
files[key]=basename+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
sys.exit()
else: # interactive
if plots==0:
ans='b'
k+=1
changeS=0
while ans != "":
if len(CurrRecs)==0:
print """
g/b: indicates good/bad measurement. "bad" measurements excluded from calculation
set s[a]ve plot, [b]ounds for pca and calculate, [p]revious, [s]pecimen,
change [h]orizontal projection angle, change [c]oordinate systems,
[e]dit data, [q]uit:
"""
else:
print """
g/b: indicates good/bad measurement. "bad" measurements excluded from calculation
set s[a]ve plot, [b]ounds for pca and calculate, [p]revious, [s]pecimen,
change [h]orizontal projection angle, change [c]oordinate systems,
[d]elete current interpretation(s), [e]dit data, [q]uit:
"""
ans=raw_input('<Return> for next specimen \n')
setangle=0
if ans=='d': # delete this interpretation
CurrRecs=[]
k-=1 # replot same specimen
ans=""
changeS=1
if ans=='q':
if changeM==1:
ans=raw_input('Save changes to magic_measurements.txt? y/[n] ')
if ans=='y':
pmag.magic_write(meas_file,meas_data,'magic_measurements')
print "Good bye"
sys.exit()
if ans=='a':
if plot_file=="":
basename=locname+'_'+s+'_'
else:
basename=plot_file
files={}
for key in ZED.keys():
files[key]=basename+'_'+coord+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
ans=""
if ans=='p':
k-=2
ans=""
backup=1
if ans=='c':
k-=1 # replot same block
if tilt==0 and geo ==1:print "You are currently viewing geographic coordinates "
if tilt==1 and geo ==1:print "You are currently viewing stratigraphic coordinates "
if tilt==0 and geo ==0: print "You are currently viewing sample coordinates "
print "\n Which coordinate system do you wish to view? "
coord=raw_input(" <Return> specimen, [g] geographic, [t] tilt corrected ")
if coord=="g":geo,tilt=1,0
if coord=="t":
geo=1
tilt=1
if coord=="":
coord='s'
geo=0
tilt=0
if geo==1 and sfile=="":
samp_file=raw_input(" Input er_samples file for sample orientations [er_samples.txt] " )
if samp_file=="":samp_file="er_samples.txt"
samp_data,file_type=pmag.magic_read(samp_file)
if file_type != 'er_samples':
print file_type
print "This is not a valid er_samples file - coordinate system not changed"
else:
sfile="ok"
ans=""
if ans=='s':
keepon=1
sample=raw_input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
k =sids.index(sample)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if sample in sids[qq]:tmplist.append(sids[qq])
print sample," not found, but this was: "
print tmplist
sample=raw_input('Select one or try again\n ')
angle,direction_type="",""
setangle=0
ans=""
if ans=='h':
k-=1
angle=raw_input("Enter desired declination for X axis 0-360 ")
angle=float(angle)
if angle==0:angle=0.001
s=sids[k]
setangle=1
ans=""
if ans=='e':
k-=1
ans=""
recnum=0
for plotrec in plotblock:
if plotrec[0]<=200 and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f ' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2])
if plotrec[0]>200 and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f ' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2])
recnum += 1
answer=raw_input('Enter index of point to change from bad to good or vice versa: ')
try:
ind=int(answer)
meas_data=pmag.mark_dmag_rec(s,ind,meas_data)
changeM=1
except:
'bad entry, try again'
if ans=='b':
if end_pca=="":end_pca=len(plotblock)-1
if beg_pca=="":beg_pca=0
k-=1 # stay on same sample until through
GoOn=0
while GoOn==0:
print 'Enter index of first point for pca: ','[',beg_pca,']'
answer=raw_input('return to keep default ')
if answer != "":
beg_pca=int(answer)
print 'Enter index of last point for pca: ','[',end_pca,']'
answer=raw_input('return to keep default ')
try:
end_pca=int(answer)
if plotblock[beg_pca][5]=='b' or plotblock[end_pca][5]=='b':
print "Can't select 'bad' measurement for PCA bounds -try again"
end_pca=len(plotblock)-1
beg_pca=0
elif beg_pca >=0 and beg_pca<=len(plotblock)-2 and end_pca>0 and end_pca<len(plotblock):
GoOn=1
else:
print beg_pca,end_pca, " are bad entry of indices - try again"
end_pca=len(plotblock)-1
beg_pca=0
except:
print beg_pca,end_pca, " are bad entry of indices - try again"
end_pca=len(plotblock)-1
beg_pca=0
GoOn=0
while GoOn==0:
if calculation_type!="":
print "Prior calculation type = ",calculation_type
ct=raw_input('Enter new Calculation Type: best-fit line, plane or fisher mean [l]/p/f : ' )
if ct=="" or ct=="l":
direction_type="l"
calculation_type="DE-BFL"
GoOn=1
elif ct=='p':
direction_type="p"
calculation_type="DE-BFP"
GoOn=1
elif ct=='f':
direction_type="l"
calculation_type="DE-FM"
GoOn=1
else:
print "bad entry of calculation type: try again. "
pmagplotlib.plotZED(ZED,plotblock,angle,s,units)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
if "SO-NO" not in method_codes:
PmagSpecRec["specimen_tilt_correction"]='0'
method_codes.append("DA-DIR-GEO")
else:
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,geoblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
if "SO-NO" not in method_codes:
PmagSpecRec["specimen_tilt_correction"]='100'
method_codes.append("DA-DIR-TILT")
else:
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,tiltblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,plotblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
PmagSpecRec["measurement_step_min"]='%8.3e ' %(mpars["measurement_step_min"])
PmagSpecRec["measurement_step_max"]='%8.3e ' %(mpars["measurement_step_max"])
PmagSpecRec["specimen_correction"]='u'
PmagSpecRec["specimen_dang"]='%7.1f ' %(mpars['specimen_dang'])
print 'DANG: ',PmagSpecRec["specimen_dang"]
if calculation_type!='DE-FM':
PmagSpecRec["specimen_mad"]='%7.1f ' %(mpars["specimen_mad"])
PmagSpecRec["specimen_alpha95"]=""
else:
PmagSpecRec["specimen_alpha95"]='%7.1f ' %(mpars["specimen_alpha95"])
PmagSpecRec["specimen_mad"]=""
PmagSpecRec["specimen_n"]='%i ' %(mpars["specimen_n"])
PmagSpecRec["specimen_direction_type"]=direction_type
PmagSpecRec["calculation_type"]=calculation_type # redundant and won't be imported - just for convenience
method_codes=PmagSpecRec["magic_method_codes"].split(':')
if len(method_codes) != 0:
methstring=""
for meth in method_codes:
ctype=meth.split('-')
if 'DE' not in ctype:methstring=methstring+ ":" +meth # don't include old direction estimation methods
methstring=methstring+':'+calculation_type
PmagSpecRec["magic_method_codes"]= methstring.strip(':')
print 'Method codes: ',PmagSpecRec['magic_method_codes']
if calculation_type!='DE-FM':
if units=='K':
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])-273,float(PmagSpecRec["measurement_step_max"])-273,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif units== 'T':
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])*1e3,float(PmagSpecRec["measurement_step_max"])*1e3,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units and 'K' in units:
if float(PmagSpecRec['measurement_step_min'])<1.0 :
min=float(PmagSpecRec['measurement_step_min'])*1e3
else:
min=float(PmagSpecRec['measurement_step_min'])-273
if float(PmagSpecRec['measurement_step_max'])<1.0 :
max=float(PmagSpecRec['measurement_step_max'])*1e3
else:
max=float(PmagSpecRec['measurement_step_max'])-273
print '%s %i %7.1f %i %i %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),min,max,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"]),float(PmagSpecRec["measurement_step_max"]),float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
if 'K' in units:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])-273,float(PmagSpecRec["measurement_step_max"])-273,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])*1e3,float(PmagSpecRec["measurement_step_max"])*1e3,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units and 'K' in units:
if float(PmagSpecRec['measurement_step_min'])<1.0 :
min=float(PmagSpecRec['measurement_step_min'])*1e3
else:
min=float(PmagSpecRec['measurement_step_min'])-273
if float(PmagSpecRec['measurement_step_max'])<1.0 :
max=float(PmagSpecRec['measurement_step_max'])*1e3
else:
max=float(PmagSpecRec['measurement_step_max'])-273
print '%s %i %7.1f %i %i %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),min,max,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["measurement_step_min"]),float(PmagSpecRec["measurement_step_max"]),float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
saveit=raw_input("Save this interpretation? [y]/n \n")
if saveit!="n":
changeS=1
#
# put in details
#
angle,direction_type,setangle="","",0
if len(CurrRecs)>0:
replace=raw_input(" [0] add new component, or [1] replace existing interpretation(s) [default is replace] ")
if replace=="1" or replace=="":
CurrRecs=[]
PmagSpecRec['specimen_comp_name']='A'
CurrRecs.append(PmagSpecRec)
else:
print 'These are the current component names for this specimen: '
for trec in CurrRecs:print trec['specimen_comp_name']
compnum=raw_input("Enter new component name: ")
PmagSpecRec['specimen_comp_name']=compnum
print "Adding new component: ",PmagSpecRec['specimen_comp_name']
CurrRecs.append(PmagSpecRec)
else:
PmagSpecRec['specimen_comp_name']='A'
CurrRecs.append(PmagSpecRec)
k+=1
ans=""
else:
ans=""
else: # plots=1
k+=1
files={}
locname.replace('/','-')
print PmagSpecRec
for key in ZED.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_'+coord+'_TY:_'+key+'_.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['demag']='DeMag Plot'
titles['zijd']='Zijderveld Plot'
titles['eqarea']='Equal Area Plot'
ZED = pmagplotlib.addBorders(ZED,titles,black,purple)
pmagplotlib.saveP(ZED,files)
if len(CurrRecs)>0:
for rec in CurrRecs: PriorRecs.append(rec)
if changeS==1:
if len(PriorRecs)>0:
save_redo(PriorRecs,inspec)
else:
os.system('rm '+inspec)
CurrRecs,beg_pca,end_pca=[],"","" # next up
changeS=0
else: k+=1 # skip record - not enough data
if changeM==1:
pmag.magic_write(meas_file,meas_data,'magic_measurements')
def main():
"""
NAME
zeq_magic_redo.py
DESCRIPTION
Calculate principal components through demagnetization data using bounds and calculation type stored in "redo" file
SYNTAX
zeq_magic_redo.py [command line options]
OPTIONS
-h prints help message
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-F: specify output file, default is zeq_specimens.txt
-fre REDO: specify redo file, default is "zeq_redo"
-fsa SAMPFILE: specify er_samples format file, default is "er_samples.txt"
-A : don't average replicate measurements, default is yes
-crd [s,g,t] :
specify coordinate system [s,g,t] [default is specimen coordinates]
are specimen, geographic, and tilt corrected respectively
NB: you must have a SAMPFILE in this directory to rotate from specimen coordinates
-leg: attaches "Recalculated from original measurements; supercedes published results. " to comment field
INPUTS
zeq_redo format file is:
specimen_name calculation_type[DE-BFL,DE-BFL-A,DE-BFL-O,DE-BFP,DE-FM] step_min step_max component_name[A,B,C]
"""
dir_path='.'
INCL=["LT-NO","LT-AF-Z","LT-T-Z","LT-M-Z"] # looking for demag data
beg,end,pole,geo,tilt,askave,save=0,0,[],0,0,0,0
user,doave,comment= "",1,""
geo,tilt=0,0
version_num=pmag.get_version()
args=sys.argv
if '-WD' in args:
ind=args.index('-WD')
dir_path=args[ind+1]
meas_file,pmag_file,mk_file= dir_path+"/"+"magic_measurements.txt",dir_path+"/"+"zeq_specimens.txt",dir_path+"/"+"zeq_redo"
samp_file,coord=dir_path+"/"+"er_samples.txt",""
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind=args.index("-usr")
user=sys.argv[ind+1]
if "-A" in args:doave=0
if "-leg" in args: comment="Recalculated from original measurements; supercedes published results. "
if "-f" in args:
ind=args.index("-f")
meas_file=dir_path+'/'+sys.argv[ind+1]
if "-F" in args:
ind=args.index("-F")
pmag_file=dir_path+'/'+sys.argv[ind+1]
if "-fre" in args:
ind=args.index("-fre")
mk_file=dir_path+"/"+args[ind+1]
try:
mk_f=open(mk_file,'r')
except:
print("Bad redo file")
sys.exit()
mkspec,skipped=[],[]
speclist=[]
for line in mk_f.readlines():
tmp=line.split()
mkspec.append(tmp)
speclist.append(tmp[0])
if "-fsa" in args:
ind=args.index("-fsa")
samp_file=dir_path+'/'+sys.argv[ind+1]
if "-crd" in args:
ind=args.index("-crd")
coord=sys.argv[ind+1]
if coord=="g":geo,tilt=1,0
if coord=="t":geo,tilt=1,1
#
# now get down to bidness
if geo==1:
samp_data,file_type=pmag.magic_read(samp_file)
if file_type != 'er_samples':
print(file_type)
print("This is not a valid er_samples file ")
sys.exit()
#
#
#
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()
#
# sort the specimen names
#
k = 0
print('Processing ',len(speclist), ' specimens - please wait')
PmagSpecs=[]
while k < len(speclist):
s=speclist[k]
recnum=0
PmagSpecRec={}
method_codes,inst_codes=[],[]
# find the data from the meas_data file for this sample
#
# collect info for the PmagSpecRec dictionary
#
meas_meth=[]
spec=pmag.get_dictitem(meas_data,'er_specimen_name',s,'T')
if len(spec)==0:
print('no data found for specimen: ',s)
print('delete from zeq_redo input file...., then try again')
else:
for rec in spec: # copy of vital stats to PmagSpecRec from first spec record in demag block
skip=1
methods=rec["magic_method_codes"].split(":")
if len(set(methods) & set(INCL))>0:
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec["magic_software_packages"]=version_num
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 "er_expedition_name" in list(rec.keys()):PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
PmagSpecRec["er_citation_names"]="This study"
if "magic_experiment_name" not in list(rec.keys()): rec["magic_experiment_name"]=""
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
if "magic_instrument_codes" not in list(rec.keys()): rec["magic_instrument_codes"]=""
inst=rec['magic_instrument_codes'].split(":")
for I in inst:
if I not in inst_codes: # copy over instruments
inst_codes.append(I)
meths=rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in meas_meth:meas_meth.append(meth)
if "LP-DIR-AF" in meas_meth or "LT-AF-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"]="T"
if "LP-DIR-AF" not in method_codes:method_codes.append("LP-DIR-AF")
if "LP-DIR-T" in meas_meth or "LT-T-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"]="K"
if "LP-DIR-T" not in method_codes:method_codes.append("LP-DIR-T")
if "LP-DIR-M" in meas_meth or "LT-M-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"]="J"
if "LP-DIR-M" not in method_codes:method_codes.append("LP-DIR-M")
#
#
datablock,units=pmag.find_dmag_rec(s,spec) # fish out the demag data for this specimen
#
if len(datablock) <2 or s not in speclist :
k+=1
# print 'skipping ', s,len(datablock)
else:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
#
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
#
# do geo or stratigraphic correction now
#
if geo==1 or tilt==1:
# find top priority orientation method
orient,az_type=pmag.get_orient(samp_data,PmagSpecRec["er_sample_name"])
if az_type not in method_codes:method_codes.append(az_type)
#
# if tilt selected, get stratigraphic correction
#
tiltblock,geoblock=[],[]
for rec in datablock:
if "sample_azimuth" in list(orient.keys()) and orient["sample_azimuth"]!="":
d_geo,i_geo=pmag.dogeo(rec[1],rec[2],float(orient["sample_azimuth"]),float(orient["sample_dip"]))
geoblock.append([rec[0],d_geo,i_geo,rec[3],rec[4],rec[5]])
if tilt==1 and "sample_bed_dip_direction" in list(orient.keys()):
d_tilt,i_tilt=pmag.dotilt(d_geo,i_geo,float(orient["sample_bed_dip_direction"]),float(orient["sample_bed_dip"]))
tiltblock.append([rec[0],d_tilt,i_tilt,rec[3],rec[4],rec[5]])
elif tilt==1:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no tilt correction for ', PmagSpecRec["er_sample_name"],' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
else:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no geographic correction for ', PmagSpecRec["er_sample_name"],' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
#
# get beg_pca, end_pca, pca
if PmagSpecRec['er_sample_name'] not in skipped:
compnum=-1
for spec in mkspec:
if spec[0]==s:
CompRec={}
for key in list(PmagSpecRec.keys()):CompRec[key]=PmagSpecRec[key]
compnum+=1
calculation_type=spec[1]
beg=float(spec[2])
end=float(spec[3])
if len(spec)>4:
comp_name=spec[4]
else:
comp_name=string.uppercase[compnum]
CompRec['specimen_comp_name']=comp_name
if beg < float(datablock[0][0]):beg=float(datablock[0][0])
if end > float(datablock[-1][0]):end=float(datablock[-1][0])
for l in range(len(datablock)):
if datablock[l][0]==beg:beg_pca=l
if datablock[l][0]==end:end_pca=l
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
CompRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
CompRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
CompRec["specimen_tilt_correction"]='0'
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
CompRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
CompRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
CompRec["specimen_tilt_correction"]='100'
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
CompRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
CompRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
CompRec["specimen_tilt_correction"]='-1'
if mpars["specimen_direction_type"]=="Error":
pass
else:
CompRec["measurement_step_min"]='%8.3e '%(datablock[beg_pca][0])
try:
CompRec["measurement_step_max"]='%8.3e '%(datablock[end_pca][0] )
except:
print('error in end_pca ',PmagSpecRec['er_specimen_name'])
CompRec["specimen_correction"]='u'
if calculation_type!='DE-FM':
CompRec["specimen_mad"]='%7.1f '%(mpars["specimen_mad"])
CompRec["specimen_alpha95"]=""
else:
CompRec["specimen_mad"]=""
CompRec["specimen_alpha95"]='%7.1f '%(mpars["specimen_alpha95"])
CompRec["specimen_n"]='%i '%(mpars["specimen_n"])
CompRec["specimen_dang"]='%7.1f '%(mpars["specimen_dang"])
CompMeths=[]
for meth in method_codes:
if meth not in CompMeths:CompMeths.append(meth)
if calculation_type not in CompMeths:CompMeths.append(calculation_type)
if geo==1: CompMeths.append("DA-DIR-GEO")
if tilt==1: CompMeths.append("DA-DIR-TILT")
if "DE-BFP" not in calculation_type:
CompRec["specimen_direction_type"]='l'
else:
CompRec["specimen_direction_type"]='p'
CompRec["magic_method_codes"]=""
if len(CompMeths) != 0:
methstring=""
for meth in CompMeths:
methstring=methstring+ ":" +meth
CompRec["magic_method_codes"]=methstring.strip(':')
CompRec["specimen_description"]=comment
if len(inst_codes) != 0:
inststring=""
for inst in inst_codes:
inststring=inststring+ ":" +inst
CompRec["magic_instrument_codes"]=inststring.strip(':')
PmagSpecs.append(CompRec)
k+=1
pmag.magic_write(pmag_file,PmagSpecs,'pmag_specimens')
print("Recalculated specimen data stored in ",pmag_file)
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
zeq_magic_redo.py
DESCRIPTION
Calculate principal components through demagnetization data using bounds and calculation type stored in "redo" file
SYNTAX
zeq_magic_redo.py [command line options]
OPTIONS
-h prints help message
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-F: specify output file, default is zeq_specimens.txt
-fre REDO: specify redo file, default is "zeq_redo"
-fsa SAMPFILE: specify er_samples format file, default is "er_samples.txt"
-A : don't average replicate measurements, default is yes
-crd [s,g,t] :
specify coordinate system [s,g,t] [default is specimen coordinates]
are specimen, geographic, and tilt corrected respectively
NB: you must have a SAMPFILE in this directory to rotate from specimen coordinates
-leg: attaches "Recalculated from original measurements; supercedes published results. " to comment field
INPUTS
zeq_redo format file is:
specimen_name calculation_type[DE-BFL,DE-BFL-A,DE-BFL-O,DE-BFP,DE-FM] step_min step_max component_name[A,B,C]
"""
dir_path = '.'
INCL = ["LT-NO", "LT-AF-Z", "LT-T-Z", "LT-M-Z"] # looking for demag data
beg, end, pole, geo, tilt, askave, save = 0, 0, [], 0, 0, 0, 0
user, doave, comment = "", 1, ""
geo, tilt = 0, 0
version_num = pmag.get_version()
args = sys.argv
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind + 1]
meas_file, pmag_file, mk_file = dir_path + "/" + "magic_measurements.txt", dir_path + "/" + "zeq_specimens.txt", dir_path + "/" + "zeq_redo"
samp_file, coord = dir_path + "/" + "er_samples.txt", ""
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = sys.argv[ind + 1]
if "-A" in args: doave = 0
if "-leg" in args:
comment = "Recalculated from original measurements; supercedes published results. "
if "-f" in args:
ind = args.index("-f")
meas_file = dir_path + '/' + sys.argv[ind + 1]
if "-F" in args:
ind = args.index("-F")
pmag_file = dir_path + '/' + sys.argv[ind + 1]
if "-fre" in args:
ind = args.index("-fre")
mk_file = dir_path + "/" + args[ind + 1]
try:
mk_f = open(mk_file, 'r')
except:
print("Bad redo file")
sys.exit()
mkspec, skipped = [], []
speclist = []
for line in mk_f.readlines():
tmp = line.split()
mkspec.append(tmp)
speclist.append(tmp[0])
if "-fsa" in args:
ind = args.index("-fsa")
samp_file = dir_path + '/' + sys.argv[ind + 1]
if "-crd" in args:
ind = args.index("-crd")
coord = sys.argv[ind + 1]
if coord == "g": geo, tilt = 1, 0
if coord == "t": geo, tilt = 1, 1
#
# now get down to bidness
if geo == 1:
samp_data, file_type = pmag.magic_read(samp_file)
if file_type != 'er_samples':
print(file_type)
print("This is not a valid er_samples file ")
sys.exit()
#
#
#
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()
#
# sort the specimen names
#
k = 0
print('Processing ', len(speclist), ' specimens - please wait')
PmagSpecs = []
while k < len(speclist):
s = speclist[k]
recnum = 0
PmagSpecRec = {}
method_codes, inst_codes = [], []
# find the data from the meas_data file for this sample
#
# collect info for the PmagSpecRec dictionary
#
meas_meth = []
spec = pmag.get_dictitem(meas_data, 'er_specimen_name', s, 'T')
if len(spec) == 0:
print('no data found for specimen: ', s)
print('delete from zeq_redo input file...., then try again')
else:
for rec in spec: # copy of vital stats to PmagSpecRec from first spec record in demag block
skip = 1
methods = rec["magic_method_codes"].split(":")
if len(set(methods) & set(INCL)) > 0:
PmagSpecRec["er_analyst_mail_names"] = user
PmagSpecRec["magic_software_packages"] = version_num
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 "er_expedition_name" in list(rec.keys()):
PmagSpecRec["er_expedition_name"] = rec[
"er_expedition_name"]
PmagSpecRec["er_citation_names"] = "This study"
if "magic_experiment_name" not in list(rec.keys()):
rec["magic_experiment_name"] = ""
PmagSpecRec["magic_experiment_names"] = rec[
"magic_experiment_name"]
if "magic_instrument_codes" not in list(rec.keys()):
rec["magic_instrument_codes"] = ""
inst = rec['magic_instrument_codes'].split(":")
for I in inst:
if I not in inst_codes: # copy over instruments
inst_codes.append(I)
meths = rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in meas_meth:
meas_meth.append(meth)
if "LP-DIR-AF" in meas_meth or "LT-AF-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"] = "T"
if "LP-DIR-AF" not in method_codes:
method_codes.append("LP-DIR-AF")
if "LP-DIR-T" in meas_meth or "LT-T-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"] = "K"
if "LP-DIR-T" not in method_codes:
method_codes.append("LP-DIR-T")
if "LP-DIR-M" in meas_meth or "LT-M-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"] = "J"
if "LP-DIR-M" not in method_codes:
method_codes.append("LP-DIR-M")
#
#
datablock, units = pmag.find_dmag_rec(
s, spec) # fish out the demag data for this specimen
#
if len(datablock) < 2 or s not in speclist:
k += 1
# print 'skipping ', s,len(datablock)
else:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
#
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
#
# do geo or stratigraphic correction now
#
if geo == 1 or tilt == 1:
# find top priority orientation method
orient, az_type = pmag.get_orient(
samp_data, PmagSpecRec["er_sample_name"])
if az_type not in method_codes: method_codes.append(az_type)
#
# if tilt selected, get stratigraphic correction
#
tiltblock, geoblock = [], []
for rec in datablock:
if "sample_azimuth" in list(
orient.keys()) and orient["sample_azimuth"] != "":
d_geo, i_geo = pmag.dogeo(
rec[1], rec[2], float(orient["sample_azimuth"]),
float(orient["sample_dip"]))
geoblock.append(
[rec[0], d_geo, i_geo, rec[3], rec[4], rec[5]])
if tilt == 1 and "sample_bed_dip_direction" in list(
orient.keys()):
d_tilt, i_tilt = pmag.dotilt(
d_geo, i_geo,
float(orient["sample_bed_dip_direction"]),
float(orient["sample_bed_dip"]))
tiltblock.append([
rec[0], d_tilt, i_tilt, rec[3], rec[4], rec[5]
])
elif tilt == 1:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no tilt correction for ',
PmagSpecRec["er_sample_name"],
' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
else:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no geographic correction for ',
PmagSpecRec["er_sample_name"],
' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
#
# get beg_pca, end_pca, pca
if PmagSpecRec['er_sample_name'] not in skipped:
compnum = -1
for spec in mkspec:
if spec[0] == s:
CompRec = {}
for key in list(PmagSpecRec.keys()):
CompRec[key] = PmagSpecRec[key]
compnum += 1
calculation_type = spec[1]
beg = float(spec[2])
end = float(spec[3])
if len(spec) > 4:
comp_name = spec[4]
else:
comp_name = string.uppercase[compnum]
CompRec['specimen_comp_name'] = comp_name
if beg < float(datablock[0][0]):
beg = float(datablock[0][0])
if end > float(datablock[-1][0]):
end = float(datablock[-1][0])
for l in range(len(datablock)):
if datablock[l][0] == beg: beg_pca = l
if datablock[l][0] == end: end_pca = l
if geo == 1 and tilt == 0:
mpars = pmag.domean(geoblock, beg_pca, end_pca,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
CompRec["specimen_dec"] = '%7.1f ' % (
mpars["specimen_dec"])
CompRec["specimen_inc"] = '%7.1f ' % (
mpars["specimen_inc"])
CompRec["specimen_tilt_correction"] = '0'
if geo == 1 and tilt == 1:
mpars = pmag.domean(tiltblock, beg_pca, end_pca,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
CompRec["specimen_dec"] = '%7.1f ' % (
mpars["specimen_dec"])
CompRec["specimen_inc"] = '%7.1f ' % (
mpars["specimen_inc"])
CompRec["specimen_tilt_correction"] = '100'
if geo == 0 and tilt == 0:
mpars = pmag.domean(datablock, beg_pca, end_pca,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
CompRec["specimen_dec"] = '%7.1f ' % (
mpars["specimen_dec"])
CompRec["specimen_inc"] = '%7.1f ' % (
mpars["specimen_inc"])
CompRec["specimen_tilt_correction"] = '-1'
if mpars["specimen_direction_type"] == "Error":
pass
else:
CompRec["measurement_step_min"] = '%8.3e ' % (
datablock[beg_pca][0])
try:
CompRec["measurement_step_max"] = '%8.3e ' % (
datablock[end_pca][0])
except:
print('error in end_pca ',
PmagSpecRec['er_specimen_name'])
CompRec["specimen_correction"] = 'u'
if calculation_type != 'DE-FM':
CompRec["specimen_mad"] = '%7.1f ' % (
mpars["specimen_mad"])
CompRec["specimen_alpha95"] = ""
else:
CompRec["specimen_mad"] = ""
CompRec["specimen_alpha95"] = '%7.1f ' % (
mpars["specimen_alpha95"])
CompRec["specimen_n"] = '%i ' % (
mpars["specimen_n"])
CompRec["specimen_dang"] = '%7.1f ' % (
mpars["specimen_dang"])
CompMeths = []
for meth in method_codes:
if meth not in CompMeths:
CompMeths.append(meth)
if calculation_type not in CompMeths:
CompMeths.append(calculation_type)
if geo == 1: CompMeths.append("DA-DIR-GEO")
if tilt == 1: CompMeths.append("DA-DIR-TILT")
if "DE-BFP" not in calculation_type:
CompRec["specimen_direction_type"] = 'l'
else:
CompRec["specimen_direction_type"] = 'p'
CompRec["magic_method_codes"] = ""
if len(CompMeths) != 0:
methstring = ""
for meth in CompMeths:
methstring = methstring + ":" + meth
CompRec[
"magic_method_codes"] = methstring.strip(
':')
CompRec["specimen_description"] = comment
if len(inst_codes) != 0:
inststring = ""
for inst in inst_codes:
inststring = inststring + ":" + inst
CompRec[
"magic_instrument_codes"] = inststring.strip(
':')
PmagSpecs.append(CompRec)
k += 1
pmag.magic_write(pmag_file, PmagSpecs, 'pmag_specimens')
print("Recalculated specimen data stored in ", pmag_file)
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")
def main():
"""
NAME
nrm_specimens_magic.py
DESCRIPTION
converts NRM data in a magic_measurements type file to
geographic and tilt corrected data in a pmag_specimens type file
SYNTAX
nrm_specimens_magic.py [-h][command line options]
OPTIONS:
-h prints the help message and quits
-f MFILE: specify input file
-fsa SFILE: specify er_samples format file [with orientations]
-F PFILE: specify output file
-A do not average replicate measurements
-crd [g, t]: specify coordinate system ([g]eographic or [t]ilt adjusted)
NB: you must have the SFILE in this directory
DEFAULTS
MFILE: magic_measurements.txt
PFILE: nrm_specimens.txt
SFILE: er_samples.txt
coord: specimen
average replicate measurements?: YES
"""
#
# define some variables
#
beg, end, pole, geo, tilt, askave, save = 0, 0, [], 0, 0, 0, 0
samp_file = 1
args = sys.argv
geo, tilt, orient = 0, 0, 0
doave = 1
user, comment, doave, coord = "", "", 1, ""
dir_path = "."
if "-h" in args:
print main.__doc__
sys.exit()
if "-WD" in sys.argv:
ind = sys.argv.index("-WD")
dir_path = sys.argv[ind + 1]
meas_file = dir_path + "/magic_measurements.txt"
pmag_file = dir_path + "/nrm_specimens.txt"
samp_file = dir_path + "/er_samples.txt"
if "-A" in args:
doave = 0
if "-f" in args:
ind = args.index("-f")
meas_file = sys.argv[ind + 1]
if "-F" in args:
ind = args.index("-F")
pmag_file = dir_path + "/" + sys.argv[ind + 1]
speclist = []
if "-fsa" in args:
ind = args.index("-fsa")
samp_file = dir_path + "/" + sys.argv[ind + 1]
if "-crd" in args:
ind = args.index("-crd")
coord = sys.argv[ind + 1]
if coord == "g":
geo, orient = 1, 1
if coord == "t":
tilt, orient, geo = 1, 1, 1
#
# read in data
if samp_file != "":
samp_data, file_type = pmag.magic_read(samp_file)
if file_type != "er_samples":
print file_type
print "This is not a valid er_samples file "
sys.exit()
else:
print samp_file, " read in with ", len(samp_data), " records"
else:
print "no orientations - will create file in specimen coordinates"
geo, tilt, orient = 0, 0, 0
#
#
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()
#
if orient == 1:
# set orientation priorities
SO_methods = []
orientation_priorities = {
"0": "SO-SUN",
"1": "SO-GPS-DIFF",
"2": "SO-SIGHT-BACK",
"3": "SO-CMD-NORTH",
"4": "SO-MAG",
}
for rec in samp_data:
if "magic_method_codes" in rec:
methlist = rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods:
SO_methods.append(meth.strip())
#
# sort the sample names
#
sids = pmag.get_specs(meas_data)
#
#
PmagSpecRecs = []
for s in sids:
skip = 0
recnum = 0
PmagSpecRec = {}
PmagSpecRec["er_analyst_mail_names"] = user
method_codes, inst_code = [], ""
# find the data from the meas_data file for this sample
#
# collect info for the PmagSpecRec dictionary
#
meas_meth = []
for rec in meas_data: # copy of vital stats to PmagSpecRec from first spec record
if rec["er_specimen_name"] == s:
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["er_citation_names"] = "This study"
PmagSpecRec["magic_instrument_codes"] = ""
if "magic_experiment_name" not in rec.keys():
rec["magic_experiment_name"] = ""
if "magic_instrument_codes" not in rec.keys():
rec["magic_instrument_codes"] = ""
else:
PmagSpecRec["magic_experiment_names"] = rec["magic_experiment_name"]
if len(rec["magic_instrument_codes"]) > len(inst_code):
inst_code = rec["magic_instrument_codes"]
PmagSpecRec["magic_instrument_codes"] = inst_code # copy over instruments
break
#
# now check for correct method labels for all measurements
#
nrm_data = []
for meas_rec in meas_data:
if meas_rec["er_specimen_name"] == PmagSpecRec["er_specimen_name"]:
meths = meas_rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in meas_meth:
meas_meth.append(meth)
if "LT-NO" in meas_meth:
nrm_data.append(meas_rec)
#
data, units = pmag.find_dmag_rec(s, nrm_data)
#
datablock = data
#
# find replicate measurements at NRM step and average them
#
Specs = []
if doave == 1:
step_meth, avedata = pmag.vspec(data)
if len(avedata) != len(datablock):
method_codes.append("DE-VM")
SpecRec = avedata[0]
print "averaging data "
else:
SpecRec = data[0]
Specs.append(SpecRec)
else:
for spec in data:
Specs.append(spec)
for SpecRec in Specs:
#
# do geo or stratigraphic correction now
#
if geo == 1:
#
# find top priority orientation method
redo, p = 1, 0
if len(SO_methods) <= 1:
az_type = SO_methods[0]
orient = pmag.find_samp_rec(PmagSpecRec["er_sample_name"], samp_data, az_type)
if orient["sample_azimuth"] != "":
method_codes.append(az_type)
redo = 0
while redo == 1:
if p >= len(orientation_priorities):
print "no orientation data for ", s
skip, redo = 1, 0
break
az_type = orientation_priorities[str(p)]
orient = pmag.find_samp_rec(PmagSpecRec["er_sample_name"], samp_data, az_type)
if orient["sample_azimuth"] != "":
method_codes.append(az_type.strip())
redo = 0
elif orient["sample_azimuth"] == "":
p += 1
#
# if stratigraphic selected, get stratigraphic correction
#
if skip == 0 and orient["sample_azimuth"] != "" and orient["sample_dip"] != "":
d_geo, i_geo = pmag.dogeo(SpecRec[1], SpecRec[2], orient["sample_azimuth"], orient["sample_dip"])
SpecRec[1] = d_geo
SpecRec[2] = i_geo
if tilt == 1 and "sample_bed_dip" in orient.keys() and orient["sample_bed_dip"] != "":
d_tilt, i_tilt = pmag.dotilt(
d_geo, i_geo, orient["sample_bed_dip_direction"], orient["sample_bed_dip"]
)
SpecRec[1] = d_tilt
SpecRec[2] = i_tilt
if skip == 0:
PmagSpecRec["specimen_dec"] = "%7.1f " % (SpecRec[1])
PmagSpecRec["specimen_inc"] = "%7.1f " % (SpecRec[2])
if geo == 1 and tilt == 0:
PmagSpecRec["specimen_tilt_correction"] = "0"
if geo == 1 and tilt == 1:
PmagSpecRec["specimen_tilt_correction"] = "100"
if geo == 0 and tilt == 0:
PmagSpecRec["specimen_tilt_correction"] = "-1"
PmagSpecRec["specimen_direction_type"] = "l"
PmagSpecRec["magic_method_codes"] = "LT-NO"
if len(method_codes) != 0:
methstring = ""
for meth in method_codes:
methstring = methstring + ":" + meth
PmagSpecRec["magic_method_codes"] = methstring[1:]
PmagSpecRec["specimen_description"] = "NRM data"
PmagSpecRecs.append(PmagSpecRec)
pmag.magic_write(pmag_file, PmagSpecRecs, "pmag_specimens")
print "Data saved in ", pmag_file
