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
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_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)
