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 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
specimens_results_magic.py
DESCRIPTION
combines pmag_specimens.txt file with age, location, acceptance criteria and
outputs pmag_results table along with other MagIC tables necessary for uploading to the database
SYNTAX
specimens_results_magic.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specimen input magic_measurements format file, default is "magic_measurements.txt"
-fsp: specimen input pmag_specimens format file, default is "pmag_specimens.txt"
-fsm: sample input er_samples format file, default is "er_samples.txt"
-fsi: specimen input er_sites format file, default is "er_sites.txt"
-fla: specify a file with paleolatitudes for calculating VADMs, default is not to calculate VADMS
format is: site_name paleolatitude (space delimited file)
-fa AGES: specify er_ages format file with age information
-crd [s,g,t,b]: specify coordinate system
(s, specimen, g geographic, t, tilt corrected, b, geographic and tilt corrected)
Default is to assume geographic
NB: only the tilt corrected data will appear on the results table, if both g and t are selected.
-cor [AC:CR:NL]: colon delimited list of required data adjustments for all specimens
included in intensity calculations (anisotropy, cooling rate, non-linear TRM)
unless specified, corrections will not be applied
-pri [TRM:ARM] colon delimited list of priorities for anisotropy correction (-cor must also be set to include AC). default is TRM, then ARM
-age MIN MAX UNITS: specify age boundaries and units
-exc: use exiting selection criteria (in pmag_criteria.txt file), default is default criteria
-C: no acceptance criteria
-aD: average directions per sample, default is NOT
-aI: average multiple specimen intensities per sample, default is by site
-aC: average all components together, default is NOT
-pol: calculate polarity averages
-sam: save sample level vgps and v[a]dms, default is by site
-xSi: skip the site level intensity calculation
-p: plot directions and look at intensities by site, default is NOT
-fmt: specify output for saved images, default is svg (only if -p set)
-lat: use present latitude for calculating VADMs, default is not to calculate VADMs
-xD: skip directions
-xI: skip intensities
OUPUT
writes pmag_samples, pmag_sites, pmag_results tables
"""
# set defaults
Comps=[] # list of components
version_num=pmag.get_version()
args=sys.argv
DefaultAge=["none"]
skipdirs,coord,excrit,custom,vgps,average,Iaverage,plotsites,opt=1,0,0,0,0,0,0,0,0
get_model_lat=0 # this skips VADM calculation altogether, when get_model_lat=1, uses present day
fmt='svg'
dir_path="."
model_lat_file=""
Caverage=0
infile='pmag_specimens.txt'
measfile="magic_measurements.txt"
sampfile="er_samples.txt"
sitefile="er_sites.txt"
agefile="er_ages.txt"
specout="er_specimens.txt"
sampout="pmag_samples.txt"
siteout="pmag_sites.txt"
resout="pmag_results.txt"
critout="pmag_criteria.txt"
instout="magic_instruments.txt"
sigcutoff,OBJ="",""
noDir,noInt=0,0
polarity=0
coords=['0']
Dcrit,Icrit,nocrit=0,0,0
corrections=[]
nocorrection=['DA-NL','DA-AC','DA-CR']
priorities=['DA-AC-ARM','DA-AC-TRM'] # priorities for anisotropy correction
# get command line stuff
if "-h" in args:
print(main.__doc__)
sys.exit()
if '-WD' in args:
ind=args.index("-WD")
dir_path=args[ind+1]
if '-cor' in args:
ind=args.index('-cor')
cors=args[ind+1].split(':') # list of required data adjustments
for cor in cors:
nocorrection.remove('DA-'+cor)
corrections.append('DA-'+cor)
if '-pri' in args:
ind=args.index('-pri')
priorities=args[ind+1].split(':') # list of required data adjustments
for p in priorities:
p='DA-AC-'+p
if '-f' in args:
ind=args.index("-f")
measfile=args[ind+1]
if '-fsp' in args:
ind=args.index("-fsp")
infile=args[ind+1]
if '-fsi' in args:
ind=args.index("-fsi")
sitefile=args[ind+1]
if "-crd" in args:
ind=args.index("-crd")
coord=args[ind+1]
if coord=='s':coords=['-1']
if coord=='g':coords=['0']
if coord=='t':coords=['100']
if coord=='b':coords=['0','100']
if "-usr" in args:
ind=args.index("-usr")
user=sys.argv[ind+1]
else: user=""
if "-C" in args: Dcrit,Icrit,nocrit=1,1,1 # no selection criteria
if "-sam" in args: vgps=1 # save sample level VGPS/VADMs
if "-xSi" in args:
nositeints=1 # skip site level intensity
else:
nositeints=0
if "-age" in args:
ind=args.index("-age")
DefaultAge[0]=args[ind+1]
DefaultAge.append(args[ind+2])
DefaultAge.append(args[ind+3])
Daverage,Iaverage,Caverage=0,0,0
if "-aD" in args: Daverage=1 # average by sample directions
if "-aI" in args: Iaverage=1 # average by sample intensities
if "-aC" in args: Caverage=1 # average all components together ??? why???
if "-pol" in args: polarity=1 # calculate averages by polarity
if '-xD' in args:noDir=1
if '-xI' in args:
noInt=1
elif "-fla" in args:
if '-lat' in args:
print("you should set a paleolatitude file OR use present day lat - not both")
sys.exit()
ind=args.index("-fla")
model_lat_file=dir_path+'/'+args[ind+1]
get_model_lat=2
mlat=open(model_lat_file,'r')
ModelLats=[]
for line in mlat.readlines():
ModelLat={}
tmp=line.split()
ModelLat["er_site_name"]=tmp[0]
ModelLat["site_model_lat"]=tmp[1]
ModelLat["er_sample_name"]=tmp[0]
ModelLat["sample_lat"]=tmp[1]
ModelLats.append(ModelLat)
get_model_lat=2
elif '-lat' in args:
get_model_lat=1
if "-p" in args:
plotsites=1
if "-fmt" in args:
ind=args.index("-fmt")
fmt=args[ind+1]
if noDir==0: # plot by site - set up plot window
import pmagplotlib
EQ={}
EQ['eqarea']=1
pmagplotlib.plot_init(EQ['eqarea'],5,5) # define figure 1 as equal area projection
pmagplotlib.plotNET(EQ['eqarea']) # I don't know why this has to be here, but otherwise the first plot never plots...
pmagplotlib.drawFIGS(EQ)
if '-WD' in args:
infile=dir_path+'/'+infile
measfile=dir_path+'/'+measfile
instout=dir_path+'/'+instout
sampfile=dir_path+'/'+sampfile
sitefile=dir_path+'/'+sitefile
agefile=dir_path+'/'+agefile
specout=dir_path+'/'+specout
sampout=dir_path+'/'+sampout
siteout=dir_path+'/'+siteout
resout=dir_path+'/'+resout
critout=dir_path+'/'+critout
if "-exc" in args: # use existing pmag_criteria file
if "-C" in args:
print('you can not use both existing and no criteria - choose either -exc OR -C OR neither (for default)')
sys.exit()
crit_data,file_type=pmag.magic_read(critout)
print("Acceptance criteria read in from ", critout)
else : # use default criteria (if nocrit set, then get really loose criteria as default)
crit_data=pmag.default_criteria(nocrit)
if nocrit==0:
print("Acceptance criteria are defaults")
else:
print("No acceptance criteria used ")
accept={}
for critrec in crit_data:
for key in list(critrec.keys()):
# need to migrate specimen_dang to specimen_int_dang for intensity data using old format
if 'IE-SPEC' in list(critrec.keys()) and 'specimen_dang' in list(critrec.keys()) and 'specimen_int_dang' not in list(critrec.keys()):
critrec['specimen_int_dang']=critrec['specimen_dang']
del critrec['specimen_dang']
# need to get rid of ron shaars sample_int_sigma_uT
if 'sample_int_sigma_uT' in list(critrec.keys()):
critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
if key not in list(accept.keys()) and critrec[key]!='':
accept[key]=critrec[key]
#
#
if "-exc" not in args and "-C" not in args:
print("args",args)
pmag.magic_write(critout,[accept],'pmag_criteria')
print("\n Pmag Criteria stored in ",critout,'\n')
#
# now we're done slow dancing
#
SiteNFO,file_type=pmag.magic_read(sitefile) # read in site data - has the lats and lons
SampNFO,file_type=pmag.magic_read(sampfile) # read in site data - has the lats and lons
height_nfo=pmag.get_dictitem(SiteNFO,'site_height','','F') # find all the sites with height info.
if agefile !="":AgeNFO,file_type=pmag.magic_read(agefile) # read in the age information
Data,file_type=pmag.magic_read(infile) # read in specimen interpretations
IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
comment,orient="",[]
samples,sites=[],[]
for rec in Data: # run through the data filling in missing keys and finding all components, coordinates available
# fill in missing fields, collect unique sample and site names
if 'er_sample_name' not in list(rec.keys()):
rec['er_sample_name']=""
elif rec['er_sample_name'] not in samples:
samples.append(rec['er_sample_name'])
if 'er_site_name' not in list(rec.keys()):
rec['er_site_name']=""
elif rec['er_site_name'] not in sites:
sites.append(rec['er_site_name'])
if 'specimen_int' not in list(rec.keys()):rec['specimen_int']=''
if 'specimen_comp_name' not in list(rec.keys()) or rec['specimen_comp_name']=="":rec['specimen_comp_name']='A'
if rec['specimen_comp_name'] not in Comps:Comps.append(rec['specimen_comp_name'])
rec['specimen_tilt_correction']=rec['specimen_tilt_correction'].strip('\n')
if "specimen_tilt_correction" not in list(rec.keys()): rec["specimen_tilt_correction"]="-1" # assume sample coordinates
if rec["specimen_tilt_correction"] not in orient: orient.append(rec["specimen_tilt_correction"]) # collect available coordinate systems
if "specimen_direction_type" not in list(rec.keys()): rec["specimen_direction_type"]='l' # assume direction is line - not plane
if "specimen_dec" not in list(rec.keys()): rec["specimen_direction_type"]='' # if no declination, set direction type to blank
if "specimen_n" not in list(rec.keys()): rec["specimen_n"]='' # put in n
if "specimen_alpha95" not in list(rec.keys()): rec["specimen_alpha95"]='' # put in alpha95
if "magic_method_codes" not in list(rec.keys()): rec["magic_method_codes"]=''
#
# start parsing data into SpecDirs, SpecPlanes, SpecInts
SpecInts,SpecDirs,SpecPlanes=[],[],[]
samples.sort() # get sorted list of samples and sites
sites.sort()
if noInt==0: # don't skip intensities
IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
if nocrit==0: # use selection criteria
for rec in IntData: # do selection criteria
kill=pmag.grade(rec,accept,'specimen_int')
if len(kill)==0: SpecInts.append(rec) # intensity record to be included in sample, site calculations
else:
SpecInts=IntData[:] # take everything - no selection criteria
# check for required data adjustments
if len(corrections)>0 and len(SpecInts)>0:
for cor in corrections:
SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'has') # only take specimens with the required corrections
if len(nocorrection)>0 and len(SpecInts)>0:
for cor in nocorrection:
SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'not') # exclude the corrections not specified for inclusion
# take top priority specimen of its name in remaining specimens (only one per customer)
PrioritySpecInts=[]
specimens=pmag.get_specs(SpecInts) # get list of uniq specimen names
for spec in specimens:
ThisSpecRecs=pmag.get_dictitem(SpecInts,'er_specimen_name',spec,'T') # all the records for this specimen
if len(ThisSpecRecs)==1:
PrioritySpecInts.append(ThisSpecRecs[0])
elif len(ThisSpecRecs)>1: # more than one
prec=[]
for p in priorities:
ThisSpecRecs=pmag.get_dictitem(SpecInts,'magic_method_codes',p,'has') # all the records for this specimen
if len(ThisSpecRecs)>0:prec.append(ThisSpecRecs[0])
PrioritySpecInts.append(prec[0]) # take the best one
SpecInts=PrioritySpecInts # this has the first specimen record
if noDir==0: # don't skip directions
AllDirs=pmag.get_dictitem(Data,'specimen_direction_type','','F') # retrieve specimens with directed lines and planes
Ns=pmag.get_dictitem(AllDirs,'specimen_n','','F') # get all specimens with specimen_n information
if nocrit!=1: # use selection criteria
for rec in Ns: # look through everything with specimen_n for "good" data
kill=pmag.grade(rec,accept,'specimen_dir')
if len(kill)==0: # nothing killed it
SpecDirs.append(rec)
else: # no criteria
SpecDirs=AllDirs[:] # take them all
# SpecDirs is now the list of all specimen directions (lines and planes) that pass muster
#
PmagSamps,SampDirs=[],[] # list of all sample data and list of those that pass the DE-SAMP criteria
PmagSites,PmagResults=[],[] # list of all site data and selected results
SampInts=[]
for samp in samples: # run through the sample names
if Daverage==1: # average by sample if desired
SampDir=pmag.get_dictitem(SpecDirs,'er_sample_name',samp,'T') # get all the directional data for this sample
if len(SampDir)>0: # there are some directions
for coord in coords: # step through desired coordinate systems
CoordDir=pmag.get_dictitem(SampDir,'specimen_tilt_correction',coord,'T') # get all the directions for this sample
if len(CoordDir)>0: # there are some with this coordinate system
if Caverage==0: # look component by component
for comp in Comps:
CompDir=pmag.get_dictitem(CoordDir,'specimen_comp_name',comp,'T') # get all directions from this component
if len(CompDir)>0: # there are some
PmagSampRec=pmag.lnpbykey(CompDir,'sample','specimen') # get a sample average from all specimens
PmagSampRec["er_location_name"]=CompDir[0]['er_location_name'] # decorate the sample record
PmagSampRec["er_site_name"]=CompDir[0]['er_site_name']
PmagSampRec["er_sample_name"]=samp
PmagSampRec["er_citation_names"]="This study"
PmagSampRec["er_analyst_mail_names"]=user
PmagSampRec['magic_software_packages']=version_num
if nocrit!=1:PmagSampRec['pmag_criteria_codes']="ACCEPT"
if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
PmagSampRec['sample_comp_name']=comp
PmagSampRec['sample_tilt_correction']=coord
PmagSampRec['er_specimen_names']= pmag.get_list(CompDir,'er_specimen_name') # get a list of the specimen names used
PmagSampRec['magic_method_codes']= pmag.get_list(CompDir,'magic_method_codes') # get a list of the methods used
if nocrit!=1: # apply selection criteria
kill=pmag.grade(PmagSampRec,accept,'sample_dir')
else:
kill=[]
if len(kill)==0:
SampDirs.append(PmagSampRec)
if vgps==1: # if sample level VGP info desired, do that now
PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
if PmagResRec!="":PmagResults.append(PmagResRec)
PmagSamps.append(PmagSampRec)
if Caverage==1: # average all components together basically same as above
PmagSampRec=pmag.lnpbykey(CoordDir,'sample','specimen')
PmagSampRec["er_location_name"]=CoordDir[0]['er_location_name']
PmagSampRec["er_site_name"]=CoordDir[0]['er_site_name']
PmagSampRec["er_sample_name"]=samp
PmagSampRec["er_citation_names"]="This study"
PmagSampRec["er_analyst_mail_names"]=user
PmagSampRec['magic_software_packages']=version_num
if nocrit!=1:PmagSampRec['pmag_criteria_codes']=""
if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
PmagSampRec['sample_tilt_correction']=coord
PmagSampRec['sample_comp_name']= pmag.get_list(CoordDir,'specimen_comp_name') # get components used
PmagSampRec['er_specimen_names']= pmag.get_list(CoordDir,'er_specimen_name') # get specimne names averaged
PmagSampRec['magic_method_codes']= pmag.get_list(CoordDir,'magic_method_codes') # assemble method codes
if nocrit!=1: # apply selection criteria
kill=pmag.grade(PmagSampRec,accept,'sample_dir')
if len(kill)==0: # passes the mustard
SampDirs.append(PmagSampRec)
if vgps==1:
PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
if PmagResRec!="":PmagResults.append(PmagResRec)
else: # take everything
SampDirs.append(PmagSampRec)
if vgps==1:
PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
if PmagResRec!="":PmagResults.append(PmagResRec)
PmagSamps.append(PmagSampRec)
if Iaverage==1: # average by sample if desired
SampI=pmag.get_dictitem(SpecInts,'er_sample_name',samp,'T') # get all the intensity data for this sample
if len(SampI)>0: # there are some
PmagSampRec=pmag.average_int(SampI,'specimen','sample') # get average intensity stuff
PmagSampRec["sample_description"]="sample intensity" # decorate sample record
PmagSampRec["sample_direction_type"]=""
PmagSampRec['er_site_name']=SampI[0]["er_site_name"]
PmagSampRec['er_sample_name']=samp
PmagSampRec['er_location_name']=SampI[0]["er_location_name"]
PmagSampRec["er_citation_names"]="This study"
PmagSampRec["er_analyst_mail_names"]=user
if agefile != "": PmagSampRec=pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_", AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
PmagSampRec['er_specimen_names']= pmag.get_list(SampI,'er_specimen_name')
PmagSampRec['magic_method_codes']= pmag.get_list(SampI,'magic_method_codes')
if nocrit!=1: # apply criteria!
kill=pmag.grade(PmagSampRec,accept,'sample_int')
if len(kill)==0:
PmagSampRec['pmag_criteria_codes']="ACCEPT"
SampInts.append(PmagSampRec)
PmagSamps.append(PmagSampRec)
else:PmagSampRec={} # sample rejected
else: # no criteria
SampInts.append(PmagSampRec)
PmagSamps.append(PmagSampRec)
PmagSampRec['pmag_criteria_codes']=""
if vgps==1 and get_model_lat!=0 and PmagSampRec!={}: #
if get_model_lat==1: # use sample latitude
PmagResRec=pmag.getsampVDM(PmagSampRec,SampNFO)
del(PmagResRec['model_lat']) # get rid of the model lat key
elif get_model_lat==2: # use model latitude
PmagResRec=pmag.getsampVDM(PmagSampRec,ModelLats)
if PmagResRec!={}:PmagResRec['magic_method_codes']=PmagResRec['magic_method_codes']+":IE-MLAT"
if PmagResRec!={}:
PmagResRec['er_specimen_names']=PmagSampRec['er_specimen_names']
PmagResRec['er_sample_names']=PmagSampRec['er_sample_name']
PmagResRec['pmag_criteria_codes']='ACCEPT'
PmagResRec['average_int_sigma_perc']=PmagSampRec['sample_int_sigma_perc']
PmagResRec['average_int_sigma']=PmagSampRec['sample_int_sigma']
PmagResRec['average_int_n']=PmagSampRec['sample_int_n']
PmagResRec['vadm_n']=PmagSampRec['sample_int_n']
PmagResRec['data_type']='i'
PmagResults.append(PmagResRec)
if len(PmagSamps)>0:
TmpSamps,keylist=pmag.fillkeys(PmagSamps) # fill in missing keys from different types of records
pmag.magic_write(sampout,TmpSamps,'pmag_samples') # save in sample output file
print(' sample averages written to ',sampout)
#
#create site averages from specimens or samples as specified
#
for site in sites:
if Daverage==0: key,dirlist='specimen',SpecDirs # if specimen averages at site level desired
if Daverage==1: key,dirlist='sample',SampDirs # if sample averages at site level desired
tmp=pmag.get_dictitem(dirlist,'er_site_name',site,'T') # get all the sites with directions
tmp1=pmag.get_dictitem(tmp,key+'_tilt_correction',coords[-1],'T') # use only the last coordinate if Caverage==0
sd=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T') # fish out site information (lat/lon, etc.)
if len(sd)>0:
sitedat=sd[0]
if Caverage==0: # do component wise averaging
for comp in Comps:
siteD=pmag.get_dictitem(tmp1,key+'_comp_name',comp,'T') # get all components comp
if len(siteD)>0: # there are some for this site and component name
PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get an average for this site
PmagSiteRec['site_comp_name']=comp # decorate the site record
PmagSiteRec["er_location_name"]=siteD[0]['er_location_name']
PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
PmagSiteRec['site_tilt_correction']=coords[-1]
PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
if Daverage==1:
PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
else:
PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
# determine the demagnetization code (DC3,4 or 5) for this site
AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
DC=3
if AFnum>0:DC+=1
if Tnum>0:DC+=1
PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
PmagSiteRec['magic_method_codes'].strip(":")
if plotsites==1:
print(PmagSiteRec['er_site_name'])
pmagplotlib.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key) # plot and list the data
pmagplotlib.drawFIGS(EQ)
PmagSites.append(PmagSiteRec)
else: # last component only
siteD=tmp1[:] # get the last orientation system specified
if len(siteD)>0: # there are some
PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get the average for this site
PmagSiteRec["er_location_name"]=siteD[0]['er_location_name'] # decorate the record
PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
PmagSiteRec['site_comp_name']=comp
PmagSiteRec['site_tilt_correction']=coords[-1]
PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
DC=3
if AFnum>0:DC+=1
if Tnum>0:DC+=1
PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
PmagSiteRec['magic_method_codes'].strip(":")
if Daverage==0:PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
if plotsites==1:
pmagplotlib.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key)
pmagplotlib.drawFIGS(EQ)
PmagSites.append(PmagSiteRec)
else:
print('site information not found in er_sites for site, ',site,' site will be skipped')
for PmagSiteRec in PmagSites: # now decorate each dictionary some more, and calculate VGPs etc. for results table
PmagSiteRec["er_citation_names"]="This study"
PmagSiteRec["er_analyst_mail_names"]=user
PmagSiteRec['magic_software_packages']=version_num
if agefile != "": PmagSiteRec= pmag.get_age(PmagSiteRec,"er_site_name","site_inferred_",AgeNFO,DefaultAge)
PmagSiteRec['pmag_criteria_codes']='ACCEPT'
if 'site_n_lines' in list(PmagSiteRec.keys()) and 'site_n_planes' in list(PmagSiteRec.keys()) and PmagSiteRec['site_n_lines']!="" and PmagSiteRec['site_n_planes']!="":
if int(PmagSiteRec["site_n_planes"])>0:
PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM-LP"
elif int(PmagSiteRec["site_n_lines"])>2:
PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM"
kill=pmag.grade(PmagSiteRec,accept,'site_dir')
if len(kill)==0:
PmagResRec={} # set up dictionary for the pmag_results table entry
PmagResRec['data_type']='i' # decorate it a bit
PmagResRec['magic_software_packages']=version_num
PmagSiteRec['site_description']='Site direction included in results table'
PmagResRec['pmag_criteria_codes']='ACCEPT'
dec=float(PmagSiteRec["site_dec"])
inc=float(PmagSiteRec["site_inc"])
if 'site_alpha95' in list(PmagSiteRec.keys()) and PmagSiteRec['site_alpha95']!="":
a95=float(PmagSiteRec["site_alpha95"])
else:a95=180.
sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T')[0] # fish out site information (lat/lon, etc.)
lat=float(sitedat['site_lat'])
lon=float(sitedat['site_lon'])
plong,plat,dp,dm=pmag.dia_vgp(dec,inc,a95,lat,lon) # get the VGP for this site
if PmagSiteRec['site_tilt_correction']=='-1':C=' (spec coord) '
if PmagSiteRec['site_tilt_correction']=='0':C=' (geog. coord) '
if PmagSiteRec['site_tilt_correction']=='100':C=' (strat. coord) '
PmagResRec["pmag_result_name"]="VGP Site: "+PmagSiteRec["er_site_name"] # decorate some more
PmagResRec["result_description"]="Site VGP, coord system = "+str(coord)+' component: '+comp
PmagResRec['er_site_names']=PmagSiteRec['er_site_name']
PmagResRec['pmag_criteria_codes']='ACCEPT'
PmagResRec['er_citation_names']='This study'
PmagResRec['er_analyst_mail_names']=user
PmagResRec["er_location_names"]=PmagSiteRec["er_location_name"]
if Daverage==1:
PmagResRec["er_sample_names"]=PmagSiteRec["er_sample_names"]
else:
PmagResRec["er_specimen_names"]=PmagSiteRec["er_specimen_names"]
PmagResRec["tilt_correction"]=PmagSiteRec['site_tilt_correction']
PmagResRec["pole_comp_name"]=PmagSiteRec['site_comp_name']
PmagResRec["average_dec"]=PmagSiteRec["site_dec"]
PmagResRec["average_inc"]=PmagSiteRec["site_inc"]
PmagResRec["average_alpha95"]=PmagSiteRec["site_alpha95"]
PmagResRec["average_n"]=PmagSiteRec["site_n"]
PmagResRec["average_n_lines"]=PmagSiteRec["site_n_lines"]
PmagResRec["average_n_planes"]=PmagSiteRec["site_n_planes"]
PmagResRec["vgp_n"]=PmagSiteRec["site_n"]
PmagResRec["average_k"]=PmagSiteRec["site_k"]
PmagResRec["average_r"]=PmagSiteRec["site_r"]
PmagResRec["average_lat"]='%10.4f ' %(lat)
PmagResRec["average_lon"]='%10.4f ' %(lon)
if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
PmagResRec["vgp_lat"]='%7.1f ' % (plat)
PmagResRec["vgp_lon"]='%7.1f ' % (plong)
PmagResRec["vgp_dp"]='%7.1f ' % (dp)
PmagResRec["vgp_dm"]='%7.1f ' % (dm)
PmagResRec["magic_method_codes"]= PmagSiteRec["magic_method_codes"]
if PmagSiteRec['site_tilt_correction']=='0':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-GEO"
if PmagSiteRec['site_tilt_correction']=='100':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-TILT"
PmagSiteRec['site_polarity']=""
if polarity==1: # assign polarity based on angle of pole lat to spin axis - may want to re-think this sometime
angle=pmag.angle([0,0],[0,(90-plat)])
if angle <= 55.: PmagSiteRec["site_polarity"]='n'
if angle > 55. and angle < 125.: PmagSiteRec["site_polarity"]='t'
if angle >= 125.: PmagSiteRec["site_polarity"]='r'
PmagResults.append(PmagResRec)
if polarity==1:
crecs=pmag.get_dictitem(PmagSites,'site_tilt_correction','100','T') # find the tilt corrected data
if len(crecs)<2:crecs=pmag.get_dictitem(PmagSites,'site_tilt_correction','0','T') # if there aren't any, find the geographic corrected data
if len(crecs)>2: # if there are some,
comp=pmag.get_list(crecs,'site_comp_name').split(':')[0] # find the first component
crecs=pmag.get_dictitem(crecs,'site_comp_name',comp,'T') # fish out all of the first component
precs=[]
for rec in crecs:
precs.append({'dec':rec['site_dec'],'inc':rec['site_inc'],'name':rec['er_site_name'],'loc':rec['er_location_name']})
polpars=pmag.fisher_by_pol(precs) # calculate average by polarity
for mode in list(polpars.keys()): # hunt through all the modes (normal=A, reverse=B, all=ALL)
PolRes={}
PolRes['er_citation_names']='This study'
PolRes["pmag_result_name"]="Polarity Average: Polarity "+mode #
PolRes["data_type"]="a"
PolRes["average_dec"]='%7.1f'%(polpars[mode]['dec'])
PolRes["average_inc"]='%7.1f'%(polpars[mode]['inc'])
PolRes["average_n"]='%i'%(polpars[mode]['n'])
PolRes["average_r"]='%5.4f'%(polpars[mode]['r'])
PolRes["average_k"]='%6.0f'%(polpars[mode]['k'])
PolRes["average_alpha95"]='%7.1f'%(polpars[mode]['alpha95'])
PolRes['er_site_names']= polpars[mode]['sites']
PolRes['er_location_names']= polpars[mode]['locs']
PolRes['magic_software_packages']=version_num
PmagResults.append(PolRes)
if noInt!=1 and nositeints!=1:
for site in sites: # now do intensities for each site
if plotsites==1:print(site)
if Iaverage==0: key,intlist='specimen',SpecInts # if using specimen level data
if Iaverage==1: key,intlist='sample',PmagSamps # if using sample level data
Ints=pmag.get_dictitem(intlist,'er_site_name',site,'T') # get all the intensities for this site
if len(Ints)>0: # there are some
PmagSiteRec=pmag.average_int(Ints,key,'site') # get average intensity stuff for site table
PmagResRec=pmag.average_int(Ints,key,'average') # get average intensity stuff for results table
if plotsites==1: # if site by site examination requested - print this site out to the screen
for rec in Ints:print(rec['er_'+key+'_name'],' %7.1f'%(1e6*float(rec[key+'_int'])))
if len(Ints)>1:
print('Average: ','%7.1f'%(1e6*float(PmagResRec['average_int'])),'N: ',len(Ints))
print('Sigma: ','%7.1f'%(1e6*float(PmagResRec['average_int_sigma'])),'Sigma %: ',PmagResRec['average_int_sigma_perc'])
input('Press any key to continue\n')
er_location_name=Ints[0]["er_location_name"]
PmagSiteRec["er_location_name"]=er_location_name # decorate the records
PmagSiteRec["er_citation_names"]="This study"
PmagResRec["er_location_names"]=er_location_name
PmagResRec["er_citation_names"]="This study"
PmagSiteRec["er_analyst_mail_names"]=user
PmagResRec["er_analyst_mail_names"]=user
PmagResRec["data_type"]='i'
if Iaverage==0:
PmagSiteRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name') # list of all specimens used
PmagResRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name')
PmagSiteRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name') # list of all samples used
PmagResRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name')
PmagSiteRec['er_site_name']= site
PmagResRec['er_site_names']= site
PmagSiteRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
PmagResRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
kill=pmag.grade(PmagSiteRec,accept,'site_int')
if nocrit==1 or len(kill)==0:
b,sig=float(PmagResRec['average_int']),""
if(PmagResRec['average_int_sigma'])!="":sig=float(PmagResRec['average_int_sigma'])
sdir=pmag.get_dictitem(PmagResults,'er_site_names',site,'T') # fish out site direction
if len(sdir)>0 and sdir[-1]['average_inc']!="": # get the VDM for this record using last average inclination (hope it is the right one!)
inc=float(sdir[0]['average_inc']) #
mlat=pmag.magnetic_lat(inc) # get magnetic latitude using dipole formula
PmagResRec["vdm"]='%8.3e '% (pmag.b_vdm(b,mlat)) # get VDM with magnetic latitude
PmagResRec["vdm_n"]=PmagResRec['average_int_n']
if 'average_int_sigma' in list(PmagResRec.keys()) and PmagResRec['average_int_sigma']!="":
vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),mlat)
PmagResRec["vdm_sigma"]='%8.3e '% (vdm_sig)
else:
PmagResRec["vdm_sigma"]=""
mlat="" # define a model latitude
if get_model_lat==1: # use present site latitude
mlats=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T')
if len(mlats)>0: mlat=mlats[0]['site_lat']
elif get_model_lat==2: # use a model latitude from some plate reconstruction model (or something)
mlats=pmag.get_dictitem(ModelLats,'er_site_name',site,'T')
if len(mlats)>0: PmagResRec['model_lat']=mlats[0]['site_model_lat']
mlat=PmagResRec['model_lat']
if mlat!="":
PmagResRec["vadm"]='%8.3e '% (pmag.b_vdm(b,float(mlat))) # get the VADM using the desired latitude
if sig!="":
vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),float(mlat))
PmagResRec["vadm_sigma"]='%8.3e '% (vdm_sig)
PmagResRec["vadm_n"]=PmagResRec['average_int_n']
else:
PmagResRec["vadm_sigma"]=""
sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T') # fish out site information (lat/lon, etc.)
if len(sitedat)>0:
sitedat=sitedat[0]
PmagResRec['average_lat']=sitedat['site_lat']
PmagResRec['average_lon']=sitedat['site_lon']
else:
PmagResRec['average_lon']='UNKNOWN'
PmagResRec['average_lon']='UNKNOWN'
PmagResRec['magic_software_packages']=version_num
PmagResRec["pmag_result_name"]="V[A]DM: Site "+site
PmagResRec["result_description"]="V[A]DM of site"
PmagResRec["pmag_criteria_codes"]="ACCEPT"
if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
PmagSites.append(PmagSiteRec)
PmagResults.append(PmagResRec)
if len(PmagSites)>0:
Tmp,keylist=pmag.fillkeys(PmagSites)
pmag.magic_write(siteout,Tmp,'pmag_sites')
print(' sites written to ',siteout)
else: print("No Site level table")
if len(PmagResults)>0:
TmpRes,keylist=pmag.fillkeys(PmagResults)
pmag.magic_write(resout,TmpRes,'pmag_results')
print(' results written to ',resout)
else: print("No Results level table")
def main():
"""
NAME
dmag_magic.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols (for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['demag'] = 1 # demag is figure 1
in_file, plot_key, LT = 'magic_measurements.txt', 'er_location_name', "LT-AF-Z"
XLP = ""
norm = 1
LT = 'LT-AF-Z'
units, dmag_key = 'T', 'treatment_ac_field'
plot = 0
fmt = 'svg'
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-N' in sys.argv: norm = 0
if '-sav' in sys.argv:
plot = 1
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
plot_by = sys.argv[ind + 1]
if plot_by == 'sit': plot_key = 'er_site_name'
if plot_by == 'sam': plot_key = 'er_sample_name'
if plot_by == 'spc': plot_key = 'er_specimen_name'
if '-XLP' in sys.argv:
ind = sys.argv.index("-XLP")
XLP = sys.argv[ind + 1] # get lab protocol for excluding
if '-LT' in sys.argv:
ind = sys.argv.index("-LT")
LT = 'LT-' + sys.argv[ind +
1] + '-Z' # get lab treatment for plotting
if LT == 'LT-T-Z':
units, dmag_key = 'K', 'treatment_temp'
elif LT == 'LT-AF-Z':
units, dmag_key = 'T', 'treatment_ac_field'
elif LT == 'LT-M-Z':
units, dmag_key = 'J', 'treatment_mw_energy'
else:
units = 'U'
data, file_type = pmag.magic_read(in_file)
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['demag'], 5, 5)
print(len(data), ' records read from ', in_file)
#
#
# find desired intensity data
#
#
plotlist, intlist = [], [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass'
]
IntMeths = []
FixData = []
for rec in data:
meths = []
methcodes = rec['magic_method_codes'].split(':')
for meth in methcodes:
meths.append(meth.strip())
for key in rec.keys():
if key in intlist and rec[key] != "":
if key not in IntMeths: IntMeths.append(key)
if rec[plot_key] not in plotlist and LT in meths:
plotlist.append(rec[plot_key])
if 'measurement_flag' not in rec.keys():
rec['measurement_flag'] = 'g'
FixData.append(rec)
plotlist.sort()
if len(IntMeths) == 0:
print('No intensity information found')
sys.exit()
data = FixData
int_key = IntMeths[
0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
for plt in plotlist:
if plot == 0: print(plt, 'plotting by: ', plot_key)
PLTblock = pmag.get_dictitem(
data, plot_key, plt,
'T') # fish out all the data for this type of plot
PLTblock = pmag.get_dictitem(
PLTblock, 'magic_method_codes', LT,
'has') # fish out all the dmag for this experiment type
PLTblock = pmag.get_dictitem(
PLTblock, int_key, '',
'F') # get all with this intensity key non-blank
if XLP != "":
PLTblock = pmag.get_dictitem(
PLTblock, 'magic_method_codes', XLP,
'not') # reject data with XLP in method_code
if len(PLTblock) > 2:
title = PLTblock[0][plot_key]
spcs = []
for rec in PLTblock:
if rec['er_specimen_name'] not in spcs:
spcs.append(rec['er_specimen_name'])
for spc in spcs:
SPCblock = pmag.get_dictitem(PLTblock, 'er_specimen_name', spc,
'T') # plot specimen by specimen
INTblock = []
for rec in SPCblock:
INTblock.append([
float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, rec['measurement_flag']
])
if len(INTblock) > 2:
pmagplotlib.plotMT(FIG['demag'], INTblock, title, 0, units,
norm)
if plot == 1:
files = {}
for key in FIG.keys():
files[key] = title + '_' + LT + '.' + fmt
pmagplotlib.saveP(FIG, files)
sys.exit()
else:
pmagplotlib.drawFIGS(FIG)
ans = raw_input(
" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q': sys.exit()
if ans == "a":
files = {}
for key in FIG.keys():
files[key] = title + '_' + LT + '.' + fmt
pmagplotlib.saveP(FIG, files)
pmagplotlib.clearFIG(FIG['demag'])
def main():
"""
NAME
trmaq_magic.py
DESCTIPTION
does non-linear trm acquisisiton correction
SYNTAX
trmaq_magic.py [-h][-i][command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of file names
-f MFILE, sets magic_measurements input file
-ft TSPEC, sets thellier_specimens input file
-F OUT, sets output for non-linear TRM acquisition corrected data
DEFAULTS
MFILE: trmaq_measurements.txt
TSPEC: thellier_specimens.txt
OUT: NLT_specimens.txt
"""
meas_file='trmaq_measurements.txt'
tspec="thellier_specimens.txt"
output='NLT_specimens.txt'
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-i' in sys.argv:
meas_file=raw_input("Input magic_measurements file name? [trmaq_measurements.txt] ")
if meas_file=="":meas_file="trmaq_measurements.txt"
tspec=raw_input(" thellier_specimens file name? [thellier_specimens.txt] ")
if tspec=="":tspec="thellier_specimens.txt"
output=raw_input("File for non-linear TRM adjusted specimen data: [NLTspecimens.txt] ")
if output=="":output="NLT_specimens.txt"
if '-f' in sys.argv:
ind=sys.argv.index('-f')
meas_file=sys.argv[ind+1]
if '-ft' in sys.argv:
ind=sys.argv.index('-ft')
tspec=sys.argv[ind+1]
if '-F' in sys.argv:
ind=sys.argv.index('-F')
output=sys.argv[ind+1]
#
PLT={'aq':1}
pmagplotlib.plot_init(PLT['aq'],5,5)
#
# get name of file from command line
#
comment=""
#
#
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()
sids=pmag.get_specs(meas_data)
specimen=0
#
# read in thellier_specimen data
#
nrm,file_type=pmag.magic_read(tspec)
PmagSpecRecs=[]
while specimen < len(sids):
#
# find corresoponding paleointensity data for this specimen
#
s=sids[specimen]
blab,best="",""
for nrec in nrm: # pick out the Banc data for this spec
if nrec["er_specimen_name"]==s:
blab=float(nrec["specimen_lab_field_dc"])
best=float(nrec["specimen_int"])
TrmRec=nrec
break
if blab=="":
print "skipping ",s," : no best "
specimen+=1
else:
print sids[specimen],specimen+1, 'of ', len(sids),'Best = ',best*1e6
MeasRecs=[]
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec["er_specimen_name"]==s:
meths=rec["magic_method_codes"].split(":")
methcodes=[]
for meth in meths:
methcodes.append(meth.strip())
if "LP-TRM" in methcodes: MeasRecs.append(rec)
if len(MeasRecs) <2:
specimen+=1
print 'skipping specimen - no trm acquisition data ', s
#
# collect info for the PmagSpecRec dictionary
#
else:
TRMs,Bs=[],[]
for rec in MeasRecs:
Bs.append(float(rec['treatment_dc_field']))
TRMs.append(float(rec['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(PLT['aq'],Bs,TRMs,Bp,Mp,NLpars,rec['magic_experiment_name'])
pmagplotlib.drawFIGS(PLT)
print 'Banc= ',float(NLpars['banc'])*1e6
trmTC={}
for key in TrmRec.keys():
trmTC[key]=TrmRec[key] # copy of info from thellier_specimens record
trmTC['specimen_int']='%8.3e'%(NLpars['banc'])
trmTC['magic_method_codes']=TrmRec["magic_method_codes"]+":DA-NL"
PmagSpecRecs.append(trmTC)
ans=raw_input("Return for next specimen, s[a]ve plot ")
if ans=='a':
Name={'aq':rec['er_specimen_name']+'_TRM.svg'}
pmagplotlib.saveP(PLT,Name)
specimen+=1
pmag.magic_write(output,PmagSpecRecs,'pmag_specimens')
def main():
"""
NAME
trmaq_magic.py
DESCTIPTION
does non-linear trm acquisisiton correction
SYNTAX
trmaq_magic.py [-h][-i][command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of file names
-f MFILE, sets magic_measurements input file
-ft TSPEC, sets thellier_specimens input file
-F OUT, sets output for non-linear TRM acquisition corrected data
DEFAULTS
MFILE: trmaq_measurements.txt
TSPEC: thellier_specimens.txt
OUT: NLT_specimens.txt
"""
meas_file = 'trmaq_measurements.txt'
tspec = "thellier_specimens.txt"
output = 'NLT_specimens.txt'
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-i' in sys.argv:
meas_file = input(
"Input magic_measurements file name? [trmaq_measurements.txt] ")
if meas_file == "": meas_file = "trmaq_measurements.txt"
tspec = input(
" thellier_specimens file name? [thellier_specimens.txt] ")
if tspec == "": tspec = "thellier_specimens.txt"
output = input(
"File for non-linear TRM adjusted specimen data: [NLTspecimens.txt] "
)
if output == "": output = "NLT_specimens.txt"
if '-f' in sys.argv:
ind = sys.argv.index('-f')
meas_file = sys.argv[ind + 1]
if '-ft' in sys.argv:
ind = sys.argv.index('-ft')
tspec = sys.argv[ind + 1]
if '-F' in sys.argv:
ind = sys.argv.index('-F')
output = sys.argv[ind + 1]
#
PLT = {'aq': 1}
pmagplotlib.plot_init(PLT['aq'], 5, 5)
#
# get name of file from command line
#
comment = ""
#
#
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()
sids = pmag.get_specs(meas_data)
specimen = 0
#
# read in thellier_specimen data
#
nrm, file_type = pmag.magic_read(tspec)
PmagSpecRecs = []
while specimen < len(sids):
#
# find corresoponding paleointensity data for this specimen
#
s = sids[specimen]
blab, best = "", ""
for nrec in nrm: # pick out the Banc data for this spec
if nrec["er_specimen_name"] == s:
blab = float(nrec["specimen_lab_field_dc"])
best = float(nrec["specimen_int"])
TrmRec = nrec
break
if blab == "":
print("skipping ", s, " : no best ")
specimen += 1
else:
print(sids[specimen], specimen + 1, 'of ', len(sids), 'Best = ',
best * 1e6)
MeasRecs = []
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec["er_specimen_name"] == s:
meths = rec["magic_method_codes"].split(":")
methcodes = []
for meth in meths:
methcodes.append(meth.strip())
if "LP-TRM" in methcodes: MeasRecs.append(rec)
if len(MeasRecs) < 2:
specimen += 1
print('skipping specimen - no trm acquisition data ', s)
#
# collect info for the PmagSpecRec dictionary
#
else:
TRMs, Bs = [], []
for rec in MeasRecs:
Bs.append(float(rec['treatment_dc_field']))
TRMs.append(float(rec['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(PLT['aq'], Bs, TRMs, Bp, Mp, NLpars,
rec['magic_experiment_name'])
pmagplotlib.drawFIGS(PLT)
print('Banc= ', float(NLpars['banc']) * 1e6)
trmTC = {}
for key in list(TrmRec.keys()):
trmTC[key] = TrmRec[
key] # copy of info from thellier_specimens record
trmTC['specimen_int'] = '%8.3e' % (NLpars['banc'])
trmTC['magic_method_codes'] = TrmRec[
"magic_method_codes"] + ":DA-NL"
PmagSpecRecs.append(trmTC)
ans = input("Return for next specimen, s[a]ve plot ")
if ans == 'a':
Name = {'aq': rec['er_specimen_name'] + '_TRM.svg'}
pmagplotlib.saveP(PLT, Name)
specimen += 1
pmag.magic_write(output, PmagSpecRecs, 'pmag_specimens')
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from magic_measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units, dmag_key = 'T', 'treatment_dc_field'
XLP = []
norm = 1
in_file, plot_key, LP = 'magic_measurements.txt', 'er_location_name', "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-N' in sys.argv: norm = 0
if '-sav' in sys.argv: plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
in_file = dir_path + '/' + in_file
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
plot_by = sys.argv[ind + 1]
if plot_by == 'sit': plot_key = 'er_site_name'
if plot_by == 'sam': plot_key = 'er_sample_name'
if plot_by == 'spc': plot_key = 'er_specimen_name'
data, file_type = pmag.magic_read(in_file)
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist, intlist = [], [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass'
]
IntMeths = []
data = pmag.get_dictitem(
data, 'magic_method_codes', LP,
'has') # get all the records with this lab protocol
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
Ints[key] = pmag.get_dictitem(
data, key, '', 'F') # get all non-blank data for intensity type
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "": int_key = key
if NoInts == 1:
print 'No intensity information found'
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist: plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print plt
INTblock = []
data = pmag.get_dictitem(
Ints[int_key], plot_key, plt, 'T'
) # get data with right intensity info whose plot_key matches plot
sids = pmag.get_specs(
data) # get a list of specimens with appropriate data
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
sdata = pmag.get_dictitem(data, 'er_specimen_name', s,
'T') # get data for each specimen
for rec in sdata:
INTblock.append(
[float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plotMT(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in FIG.keys():
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.drawFIGS(FIG)
ans = raw_input(
" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q': sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
pmagplotlib.saveP(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
specimens_results_magic.py
DESCRIPTION
combines pmag_specimens.txt file with age, location, acceptance criteria and
outputs pmag_results table along with other MagIC tables necessary for uploading to the database
SYNTAX
specimens_results_magic.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specimen input magic_measurements format file, default is "magic_measurements.txt"
-fsp: specimen input pmag_specimens format file, default is "pmag_specimens.txt"
-fsm: sample input er_samples format file, default is "er_samples.txt"
-fsi: specimen input er_sites format file, default is "er_sites.txt"
-fla: specify a file with paleolatitudes for calculating VADMs, default is not to calculate VADMS
format is: site_name paleolatitude (space delimited file)
-fa AGES: specify er_ages format file with age information
-crd [s,g,t,b]: specify coordinate system
(s, specimen, g geographic, t, tilt corrected, b, geographic and tilt corrected)
Default is to assume geographic
NB: only the tilt corrected data will appear on the results table, if both g and t are selected.
-cor [AC:CR:NL]: colon delimited list of required data adjustments for all specimens
included in intensity calculations (anisotropy, cooling rate, non-linear TRM)
unless specified, corrections will not be applied
-pri [TRM:ARM] colon delimited list of priorities for anisotropy correction (-cor must also be set to include AC). default is TRM, then ARM
-age MIN MAX UNITS: specify age boundaries and units
-exc: use exiting selection criteria (in pmag_criteria.txt file), default is default criteria
-C: no acceptance criteria
-aD: average directions per sample, default is NOT
-aI: average multiple specimen intensities per sample, default is by site
-aC: average all components together, default is NOT
-pol: calculate polarity averages
-sam: save sample level vgps and v[a]dms, default is by site
-xSi: skip the site level intensity calculation
-p: plot directions and look at intensities by site, default is NOT
-fmt: specify output for saved images, default is svg (only if -p set)
-lat: use present latitude for calculating VADMs, default is not to calculate VADMs
-xD: skip directions
-xI: skip intensities
OUPUT
writes pmag_samples, pmag_sites, pmag_results tables
"""
# set defaults
Comps = [] # list of components
version_num = pmag.get_version()
args = sys.argv
DefaultAge = ["none"]
skipdirs, coord, excrit, custom, vgps, average, Iaverage, plotsites, opt = 1, 0, 0, 0, 0, 0, 0, 0, 0
get_model_lat = 0 # this skips VADM calculation altogether, when get_model_lat=1, uses present day
fmt = 'svg'
dir_path = "."
model_lat_file = ""
Caverage = 0
infile = 'pmag_specimens.txt'
measfile = "magic_measurements.txt"
sampfile = "er_samples.txt"
sitefile = "er_sites.txt"
agefile = "er_ages.txt"
specout = "er_specimens.txt"
sampout = "pmag_samples.txt"
siteout = "pmag_sites.txt"
resout = "pmag_results.txt"
critout = "pmag_criteria.txt"
instout = "magic_instruments.txt"
sigcutoff, OBJ = "", ""
noDir, noInt = 0, 0
polarity = 0
coords = ['0']
Dcrit, Icrit, nocrit = 0, 0, 0
corrections = []
nocorrection = ['DA-NL', 'DA-AC', 'DA-CR']
priorities = ['DA-AC-ARM',
'DA-AC-TRM'] # priorities for anisotropy correction
# get command line stuff
if "-h" in args:
print main.__doc__
sys.exit()
if '-WD' in args:
ind = args.index("-WD")
dir_path = args[ind + 1]
if '-cor' in args:
ind = args.index('-cor')
cors = args[ind + 1].split(':') # list of required data adjustments
for cor in cors:
nocorrection.remove('DA-' + cor)
corrections.append('DA-' + cor)
if '-pri' in args:
ind = args.index('-pri')
priorities = args[ind + 1].split(
':') # list of required data adjustments
for p in priorities:
p = 'DA-AC-' + p
if '-f' in args:
ind = args.index("-f")
measfile = args[ind + 1]
if '-fsp' in args:
ind = args.index("-fsp")
infile = args[ind + 1]
if '-fsi' in args:
ind = args.index("-fsi")
sitefile = args[ind + 1]
if "-crd" in args:
ind = args.index("-crd")
coord = args[ind + 1]
if coord == 's': coords = ['-1']
if coord == 'g': coords = ['0']
if coord == 't': coords = ['100']
if coord == 'b': coords = ['0', '100']
if "-usr" in args:
ind = args.index("-usr")
user = sys.argv[ind + 1]
else:
user = ""
if "-C" in args: Dcrit, Icrit, nocrit = 1, 1, 1 # no selection criteria
if "-sam" in args: vgps = 1 # save sample level VGPS/VADMs
if "-xSi" in args:
nositeints = 1 # skip site level intensity
else:
nositeints = 0
if "-age" in args:
ind = args.index("-age")
DefaultAge[0] = args[ind + 1]
DefaultAge.append(args[ind + 2])
DefaultAge.append(args[ind + 3])
Daverage, Iaverage, Caverage = 0, 0, 0
if "-aD" in args: Daverage = 1 # average by sample directions
if "-aI" in args: Iaverage = 1 # average by sample intensities
if "-aC" in args:
Caverage = 1 # average all components together ??? why???
if "-pol" in args: polarity = 1 # calculate averages by polarity
if '-xD' in args: noDir = 1
if '-xI' in args:
noInt = 1
elif "-fla" in args:
if '-lat' in args:
print "you should set a paleolatitude file OR use present day lat - not both"
sys.exit()
ind = args.index("-fla")
model_lat_file = dir_path + '/' + args[ind + 1]
get_model_lat = 2
mlat = open(model_lat_file, 'rU')
ModelLats = []
for line in mlat.readlines():
ModelLat = {}
tmp = line.split()
ModelLat["er_site_name"] = tmp[0]
ModelLat["site_model_lat"] = tmp[1]
ModelLat["er_sample_name"] = tmp[0]
ModelLat["sample_lat"] = tmp[1]
ModelLats.append(ModelLat)
get_model_lat = 2
elif '-lat' in args:
get_model_lat = 1
if "-p" in args:
plotsites = 1
if "-fmt" in args:
ind = args.index("-fmt")
fmt = args[ind + 1]
if noDir == 0: # plot by site - set up plot window
import pmagplotlib
EQ = {}
EQ['eqarea'] = 1
pmagplotlib.plot_init(
EQ['eqarea'], 5, 5) # define figure 1 as equal area projection
pmagplotlib.plotNET(
EQ['eqarea']
) # I don't know why this has to be here, but otherwise the first plot never plots...
pmagplotlib.drawFIGS(EQ)
if '-WD' in args:
infile = dir_path + '/' + infile
measfile = dir_path + '/' + measfile
instout = dir_path + '/' + instout
sampfile = dir_path + '/' + sampfile
sitefile = dir_path + '/' + sitefile
agefile = dir_path + '/' + agefile
specout = dir_path + '/' + specout
sampout = dir_path + '/' + sampout
siteout = dir_path + '/' + siteout
resout = dir_path + '/' + resout
critout = dir_path + '/' + critout
if "-exc" in args: # use existing pmag_criteria file
if "-C" in args:
print 'you can not use both existing and no criteria - choose either -exc OR -C OR neither (for default)'
sys.exit()
crit_data, file_type = pmag.magic_read(critout)
print "Acceptance criteria read in from ", critout
else: # use default criteria (if nocrit set, then get really loose criteria as default)
crit_data = pmag.default_criteria(nocrit)
if nocrit == 0:
print "Acceptance criteria are defaults"
else:
print "No acceptance criteria used "
accept = {}
for critrec in crit_data:
for key in critrec.keys():
# need to migrate specimen_dang to specimen_int_dang for intensity data using old format
if 'IE-SPEC' in critrec.keys() and 'specimen_dang' in critrec.keys(
) and 'specimen_int_dang' not in critrec.keys():
critrec['specimen_int_dang'] = critrec['specimen_dang']
del critrec['specimen_dang']
# need to get rid of ron shaars sample_int_sigma_uT
if 'sample_int_sigma_uT' in critrec.keys():
critrec['sample_int_sigma'] = '%10.3e' % (
eval(critrec['sample_int_sigma_uT']) * 1e-6)
if key not in accept.keys() and critrec[key] != '':
accept[key] = critrec[key]
#
#
if "-exc" not in args and "-C" not in args:
print "args", args
pmag.magic_write(critout, [accept], 'pmag_criteria')
print "\n Pmag Criteria stored in ", critout, '\n'
#
# now we're done slow dancing
#
SiteNFO, file_type = pmag.magic_read(
sitefile) # read in site data - has the lats and lons
SampNFO, file_type = pmag.magic_read(
sampfile) # read in site data - has the lats and lons
height_nfo = pmag.get_dictitem(SiteNFO, 'site_height', '',
'F') # find all the sites with height info.
if agefile != "":
AgeNFO, file_type = pmag.magic_read(
agefile) # read in the age information
Data, file_type = pmag.magic_read(
infile) # read in specimen interpretations
IntData = pmag.get_dictitem(Data, 'specimen_int', '',
'F') # retrieve specimens with intensity data
comment, orient = "", []
samples, sites = [], []
for rec in Data: # run through the data filling in missing keys and finding all components, coordinates available
# fill in missing fields, collect unique sample and site names
if 'er_sample_name' not in rec.keys():
rec['er_sample_name'] = ""
elif rec['er_sample_name'] not in samples:
samples.append(rec['er_sample_name'])
if 'er_site_name' not in rec.keys():
rec['er_site_name'] = ""
elif rec['er_site_name'] not in sites:
sites.append(rec['er_site_name'])
if 'specimen_int' not in rec.keys(): rec['specimen_int'] = ''
if 'specimen_comp_name' not in rec.keys(
) or rec['specimen_comp_name'] == "":
rec['specimen_comp_name'] = 'A'
if rec['specimen_comp_name'] not in Comps:
Comps.append(rec['specimen_comp_name'])
rec['specimen_tilt_correction'] = rec[
'specimen_tilt_correction'].strip('\n')
if "specimen_tilt_correction" not in rec.keys():
rec["specimen_tilt_correction"] = "-1" # assume sample coordinates
if rec["specimen_tilt_correction"] not in orient:
orient.append(rec["specimen_tilt_correction"]
) # collect available coordinate systems
if "specimen_direction_type" not in rec.keys():
rec["specimen_direction_type"] = 'l' # assume direction is line - not plane
if "specimen_dec" not in rec.keys():
rec["specimen_direction_type"] = '' # if no declination, set direction type to blank
if "specimen_n" not in rec.keys(): rec["specimen_n"] = '' # put in n
if "specimen_alpha95" not in rec.keys():
rec["specimen_alpha95"] = '' # put in alpha95
if "magic_method_codes" not in rec.keys():
rec["magic_method_codes"] = ''
#
# start parsing data into SpecDirs, SpecPlanes, SpecInts
SpecInts, SpecDirs, SpecPlanes = [], [], []
samples.sort() # get sorted list of samples and sites
sites.sort()
if noInt == 0: # don't skip intensities
IntData = pmag.get_dictitem(
Data, 'specimen_int', '',
'F') # retrieve specimens with intensity data
if nocrit == 0: # use selection criteria
for rec in IntData: # do selection criteria
kill = pmag.grade(rec, accept, 'specimen_int')
if len(kill) == 0:
SpecInts.append(
rec
) # intensity record to be included in sample, site calculations
else:
SpecInts = IntData[:] # take everything - no selection criteria
# check for required data adjustments
if len(corrections) > 0 and len(SpecInts) > 0:
for cor in corrections:
SpecInts = pmag.get_dictitem(
SpecInts, 'magic_method_codes', cor,
'has') # only take specimens with the required corrections
if len(nocorrection) > 0 and len(SpecInts) > 0:
for cor in nocorrection:
SpecInts = pmag.get_dictitem(
SpecInts, 'magic_method_codes', cor, 'not'
) # exclude the corrections not specified for inclusion
# take top priority specimen of its name in remaining specimens (only one per customer)
PrioritySpecInts = []
specimens = pmag.get_specs(SpecInts) # get list of uniq specimen names
for spec in specimens:
ThisSpecRecs = pmag.get_dictitem(
SpecInts, 'er_specimen_name', spec,
'T') # all the records for this specimen
if len(ThisSpecRecs) == 1:
PrioritySpecInts.append(ThisSpecRecs[0])
elif len(ThisSpecRecs) > 1: # more than one
prec = []
for p in priorities:
ThisSpecRecs = pmag.get_dictitem(
SpecInts, 'magic_method_codes', p,
'has') # all the records for this specimen
if len(ThisSpecRecs) > 0: prec.append(ThisSpecRecs[0])
PrioritySpecInts.append(prec[0]) # take the best one
SpecInts = PrioritySpecInts # this has the first specimen record
if noDir == 0: # don't skip directions
AllDirs = pmag.get_dictitem(
Data, 'specimen_direction_type', '',
'F') # retrieve specimens with directed lines and planes
Ns = pmag.get_dictitem(
AllDirs, 'specimen_n', '',
'F') # get all specimens with specimen_n information
if nocrit != 1: # use selection criteria
for rec in Ns: # look through everything with specimen_n for "good" data
kill = pmag.grade(rec, accept, 'specimen_dir')
if len(kill) == 0: # nothing killed it
SpecDirs.append(rec)
else: # no criteria
SpecDirs = AllDirs[:] # take them all
# SpecDirs is now the list of all specimen directions (lines and planes) that pass muster
#
PmagSamps, SampDirs = [], [
] # list of all sample data and list of those that pass the DE-SAMP criteria
PmagSites, PmagResults = [], [
] # list of all site data and selected results
SampInts = []
for samp in samples: # run through the sample names
if Daverage == 1: # average by sample if desired
SampDir = pmag.get_dictitem(
SpecDirs, 'er_sample_name', samp,
'T') # get all the directional data for this sample
if len(SampDir) > 0: # there are some directions
for coord in coords: # step through desired coordinate systems
CoordDir = pmag.get_dictitem(
SampDir, 'specimen_tilt_correction', coord,
'T') # get all the directions for this sample
if len(CoordDir
) > 0: # there are some with this coordinate system
if Caverage == 0: # look component by component
for comp in Comps:
CompDir = pmag.get_dictitem(
CoordDir, 'specimen_comp_name', comp, 'T'
) # get all directions from this component
if len(CompDir) > 0: # there are some
PmagSampRec = pmag.lnpbykey(
CompDir, 'sample', 'specimen'
) # get a sample average from all specimens
PmagSampRec["er_location_name"] = CompDir[0][
'er_location_name'] # decorate the sample record
PmagSampRec["er_site_name"] = CompDir[0][
'er_site_name']
PmagSampRec["er_sample_name"] = samp
PmagSampRec[
"er_citation_names"] = "This study"
PmagSampRec["er_analyst_mail_names"] = user
PmagSampRec[
'magic_software_packages'] = version_num
if nocrit != 1:
PmagSampRec[
'pmag_criteria_codes'] = "ACCEPT"
if agefile != "":
PmagSampRec = pmag.get_age(
PmagSampRec, "er_site_name",
"sample_inferred_", AgeNFO,
DefaultAge)
site_height = pmag.get_dictitem(
height_nfo, 'er_site_name',
PmagSampRec['er_site_name'], 'T')
if len(site_height) > 0:
PmagSampRec[
"sample_height"] = site_height[0][
'site_height'] # add in height if available
PmagSampRec['sample_comp_name'] = comp
PmagSampRec[
'sample_tilt_correction'] = coord
PmagSampRec[
'er_specimen_names'] = pmag.get_list(
CompDir, 'er_specimen_name'
) # get a list of the specimen names used
PmagSampRec[
'magic_method_codes'] = pmag.get_list(
CompDir, 'magic_method_codes'
) # get a list of the methods used
if nocrit != 1: # apply selection criteria
kill = pmag.grade(
PmagSampRec, accept, 'sample_dir')
else:
kill = []
if len(kill) == 0:
SampDirs.append(PmagSampRec)
if vgps == 1: # if sample level VGP info desired, do that now
PmagResRec = pmag.getsampVGP(
PmagSampRec, SiteNFO)
if PmagResRec != "":
PmagResults.append(PmagResRec)
PmagSamps.append(PmagSampRec)
if Caverage == 1: # average all components together basically same as above
PmagSampRec = pmag.lnpbykey(
CoordDir, 'sample', 'specimen')
PmagSampRec["er_location_name"] = CoordDir[0][
'er_location_name']
PmagSampRec["er_site_name"] = CoordDir[0][
'er_site_name']
PmagSampRec["er_sample_name"] = samp
PmagSampRec["er_citation_names"] = "This study"
PmagSampRec["er_analyst_mail_names"] = user
PmagSampRec[
'magic_software_packages'] = version_num
if nocrit != 1:
PmagSampRec['pmag_criteria_codes'] = ""
if agefile != "":
PmagSampRec = pmag.get_age(
PmagSampRec, "er_site_name",
"sample_inferred_", AgeNFO, DefaultAge)
site_height = pmag.get_dictitem(
height_nfo, 'er_site_name', site, 'T')
if len(site_height) > 0:
PmagSampRec["sample_height"] = site_height[0][
'site_height'] # add in height if available
PmagSampRec['sample_tilt_correction'] = coord
PmagSampRec['sample_comp_name'] = pmag.get_list(
CoordDir,
'specimen_comp_name') # get components used
PmagSampRec['er_specimen_names'] = pmag.get_list(
CoordDir, 'er_specimen_name'
) # get specimne names averaged
PmagSampRec['magic_method_codes'] = pmag.get_list(
CoordDir,
'magic_method_codes') # assemble method codes
if nocrit != 1: # apply selection criteria
kill = pmag.grade(PmagSampRec, accept,
'sample_dir')
if len(kill) == 0: # passes the mustard
SampDirs.append(PmagSampRec)
if vgps == 1:
PmagResRec = pmag.getsampVGP(
PmagSampRec, SiteNFO)
if PmagResRec != "":
PmagResults.append(PmagResRec)
else: # take everything
SampDirs.append(PmagSampRec)
if vgps == 1:
PmagResRec = pmag.getsampVGP(
PmagSampRec, SiteNFO)
if PmagResRec != "":
PmagResults.append(PmagResRec)
PmagSamps.append(PmagSampRec)
if Iaverage == 1: # average by sample if desired
SampI = pmag.get_dictitem(
SpecInts, 'er_sample_name', samp,
'T') # get all the intensity data for this sample
if len(SampI) > 0: # there are some
PmagSampRec = pmag.average_int(
SampI, 'specimen', 'sample') # get average intensity stuff
PmagSampRec[
"sample_description"] = "sample intensity" # decorate sample record
PmagSampRec["sample_direction_type"] = ""
PmagSampRec['er_site_name'] = SampI[0]["er_site_name"]
PmagSampRec['er_sample_name'] = samp
PmagSampRec['er_location_name'] = SampI[0]["er_location_name"]
PmagSampRec["er_citation_names"] = "This study"
PmagSampRec["er_analyst_mail_names"] = user
if agefile != "":
PmagSampRec = pmag.get_age(PmagSampRec, "er_site_name",
"sample_inferred_", AgeNFO,
DefaultAge)
site_height = pmag.get_dictitem(height_nfo, 'er_site_name',
PmagSampRec['er_site_name'],
'T')
if len(site_height) > 0:
PmagSampRec["sample_height"] = site_height[0][
'site_height'] # add in height if available
PmagSampRec['er_specimen_names'] = pmag.get_list(
SampI, 'er_specimen_name')
PmagSampRec['magic_method_codes'] = pmag.get_list(
SampI, 'magic_method_codes')
if nocrit != 1: # apply criteria!
kill = pmag.grade(PmagSampRec, accept, 'sample_int')
if len(kill) == 0:
PmagSampRec['pmag_criteria_codes'] = "ACCEPT"
SampInts.append(PmagSampRec)
PmagSamps.append(PmagSampRec)
else:
PmagSampRec = {} # sample rejected
else: # no criteria
SampInts.append(PmagSampRec)
PmagSamps.append(PmagSampRec)
PmagSampRec['pmag_criteria_codes'] = ""
if vgps == 1 and get_model_lat != 0 and PmagSampRec != {}: #
if get_model_lat == 1: # use sample latitude
PmagResRec = pmag.getsampVDM(PmagSampRec, SampNFO)
del (PmagResRec['model_lat']
) # get rid of the model lat key
elif get_model_lat == 2: # use model latitude
PmagResRec = pmag.getsampVDM(PmagSampRec, ModelLats)
if PmagResRec != {}:
PmagResRec['magic_method_codes'] = PmagResRec[
'magic_method_codes'] + ":IE-MLAT"
if PmagResRec != {}:
PmagResRec['er_specimen_names'] = PmagSampRec[
'er_specimen_names']
PmagResRec['er_sample_names'] = PmagSampRec[
'er_sample_name']
PmagResRec['pmag_criteria_codes'] = 'ACCEPT'
PmagResRec['average_int_sigma_perc'] = PmagSampRec[
'sample_int_sigma_perc']
PmagResRec['average_int_sigma'] = PmagSampRec[
'sample_int_sigma']
PmagResRec['average_int_n'] = PmagSampRec[
'sample_int_n']
PmagResRec['vadm_n'] = PmagSampRec['sample_int_n']
PmagResRec['data_type'] = 'i'
PmagResults.append(PmagResRec)
if len(PmagSamps) > 0:
TmpSamps, keylist = pmag.fillkeys(
PmagSamps) # fill in missing keys from different types of records
pmag.magic_write(sampout, TmpSamps,
'pmag_samples') # save in sample output file
print ' sample averages written to ', sampout
#
#create site averages from specimens or samples as specified
#
for site in sites:
if Daverage == 0:
key, dirlist = 'specimen', SpecDirs # if specimen averages at site level desired
if Daverage == 1:
key, dirlist = 'sample', SampDirs # if sample averages at site level desired
tmp = pmag.get_dictitem(dirlist, 'er_site_name', site,
'T') # get all the sites with directions
tmp1 = pmag.get_dictitem(
tmp, key + '_tilt_correction', coords[-1],
'T') # use only the last coordinate if Caverage==0
sd = pmag.get_dictitem(
SiteNFO, 'er_site_name', site,
'T') # fish out site information (lat/lon, etc.)
if len(sd) > 0:
sitedat = sd[0]
if Caverage == 0: # do component wise averaging
for comp in Comps:
siteD = pmag.get_dictitem(tmp1, key + '_comp_name', comp,
'T') # get all components comp
if len(
siteD
) > 0: # there are some for this site and component name
PmagSiteRec = pmag.lnpbykey(
siteD, 'site', key) # get an average for this site
PmagSiteRec[
'site_comp_name'] = comp # decorate the site record
PmagSiteRec["er_location_name"] = siteD[0][
'er_location_name']
PmagSiteRec["er_site_name"] = siteD[0]['er_site_name']
PmagSiteRec['site_tilt_correction'] = coords[-1]
PmagSiteRec['site_comp_name'] = pmag.get_list(
siteD, key + '_comp_name')
if Daverage == 1:
PmagSiteRec['er_sample_names'] = pmag.get_list(
siteD, 'er_sample_name')
else:
PmagSiteRec['er_specimen_names'] = pmag.get_list(
siteD, 'er_specimen_name')
# determine the demagnetization code (DC3,4 or 5) for this site
AFnum = len(
pmag.get_dictitem(siteD, 'magic_method_codes',
'LP-DIR-AF', 'has'))
Tnum = len(
pmag.get_dictitem(siteD, 'magic_method_codes',
'LP-DIR-T', 'has'))
DC = 3
if AFnum > 0: DC += 1
if Tnum > 0: DC += 1
PmagSiteRec['magic_method_codes'] = pmag.get_list(
siteD,
'magic_method_codes') + ':' + 'LP-DC' + str(DC)
PmagSiteRec['magic_method_codes'].strip(":")
if plotsites == 1:
print PmagSiteRec['er_site_name']
pmagplotlib.plotSITE(EQ['eqarea'], PmagSiteRec,
siteD,
key) # plot and list the data
pmagplotlib.drawFIGS(EQ)
PmagSites.append(PmagSiteRec)
else: # last component only
siteD = tmp1[:] # get the last orientation system specified
if len(siteD) > 0: # there are some
PmagSiteRec = pmag.lnpbykey(
siteD, 'site', key) # get the average for this site
PmagSiteRec["er_location_name"] = siteD[0][
'er_location_name'] # decorate the record
PmagSiteRec["er_site_name"] = siteD[0]['er_site_name']
PmagSiteRec['site_comp_name'] = comp
PmagSiteRec['site_tilt_correction'] = coords[-1]
PmagSiteRec['site_comp_name'] = pmag.get_list(
siteD, key + '_comp_name')
PmagSiteRec['er_specimen_names'] = pmag.get_list(
siteD, 'er_specimen_name')
PmagSiteRec['er_sample_names'] = pmag.get_list(
siteD, 'er_sample_name')
AFnum = len(
pmag.get_dictitem(siteD, 'magic_method_codes',
'LP-DIR-AF', 'has'))
Tnum = len(
pmag.get_dictitem(siteD, 'magic_method_codes',
'LP-DIR-T', 'has'))
DC = 3
if AFnum > 0: DC += 1
if Tnum > 0: DC += 1
PmagSiteRec['magic_method_codes'] = pmag.get_list(
siteD, 'magic_method_codes') + ':' + 'LP-DC' + str(DC)
PmagSiteRec['magic_method_codes'].strip(":")
if Daverage == 0:
PmagSiteRec['site_comp_name'] = pmag.get_list(
siteD, key + '_comp_name')
if plotsites == 1:
pmagplotlib.plotSITE(EQ['eqarea'], PmagSiteRec, siteD,
key)
pmagplotlib.drawFIGS(EQ)
PmagSites.append(PmagSiteRec)
else:
print 'site information not found in er_sites for site, ', site, ' site will be skipped'
for PmagSiteRec in PmagSites: # now decorate each dictionary some more, and calculate VGPs etc. for results table
PmagSiteRec["er_citation_names"] = "This study"
PmagSiteRec["er_analyst_mail_names"] = user
PmagSiteRec['magic_software_packages'] = version_num
if agefile != "":
PmagSiteRec = pmag.get_age(PmagSiteRec, "er_site_name",
"site_inferred_", AgeNFO, DefaultAge)
PmagSiteRec['pmag_criteria_codes'] = 'ACCEPT'
if 'site_n_lines' in PmagSiteRec.keys(
) and 'site_n_planes' in PmagSiteRec.keys() and PmagSiteRec[
'site_n_lines'] != "" and PmagSiteRec['site_n_planes'] != "":
if int(PmagSiteRec["site_n_planes"]) > 0:
PmagSiteRec["magic_method_codes"] = PmagSiteRec[
'magic_method_codes'] + ":DE-FM-LP"
elif int(PmagSiteRec["site_n_lines"]) > 2:
PmagSiteRec["magic_method_codes"] = PmagSiteRec[
'magic_method_codes'] + ":DE-FM"
kill = pmag.grade(PmagSiteRec, accept, 'site_dir')
if len(kill) == 0:
PmagResRec = {
} # set up dictionary for the pmag_results table entry
PmagResRec['data_type'] = 'i' # decorate it a bit
PmagResRec['magic_software_packages'] = version_num
PmagSiteRec[
'site_description'] = 'Site direction included in results table'
PmagResRec['pmag_criteria_codes'] = 'ACCEPT'
dec = float(PmagSiteRec["site_dec"])
inc = float(PmagSiteRec["site_inc"])
if 'site_alpha95' in PmagSiteRec.keys(
) and PmagSiteRec['site_alpha95'] != "":
a95 = float(PmagSiteRec["site_alpha95"])
else:
a95 = 180.
sitedat = pmag.get_dictitem(
SiteNFO, 'er_site_name', PmagSiteRec['er_site_name'],
'T')[0] # fish out site information (lat/lon, etc.)
lat = float(sitedat['site_lat'])
lon = float(sitedat['site_lon'])
plong, plat, dp, dm = pmag.dia_vgp(
dec, inc, a95, lat, lon) # get the VGP for this site
if PmagSiteRec['site_tilt_correction'] == '-1':
C = ' (spec coord) '
if PmagSiteRec['site_tilt_correction'] == '0':
C = ' (geog. coord) '
if PmagSiteRec['site_tilt_correction'] == '100':
C = ' (strat. coord) '
PmagResRec["pmag_result_name"] = "VGP Site: " + PmagSiteRec[
"er_site_name"] # decorate some more
PmagResRec[
"result_description"] = "Site VGP, coord system = " + str(
coord) + ' component: ' + comp
PmagResRec['er_site_names'] = PmagSiteRec['er_site_name']
PmagResRec['pmag_criteria_codes'] = 'ACCEPT'
PmagResRec['er_citation_names'] = 'This study'
PmagResRec['er_analyst_mail_names'] = user
PmagResRec["er_location_names"] = PmagSiteRec[
"er_location_name"]
if Daverage == 1:
PmagResRec["er_sample_names"] = PmagSiteRec[
"er_sample_names"]
else:
PmagResRec["er_specimen_names"] = PmagSiteRec[
"er_specimen_names"]
PmagResRec["tilt_correction"] = PmagSiteRec[
'site_tilt_correction']
PmagResRec["pole_comp_name"] = PmagSiteRec['site_comp_name']
PmagResRec["average_dec"] = PmagSiteRec["site_dec"]
PmagResRec["average_inc"] = PmagSiteRec["site_inc"]
PmagResRec["average_alpha95"] = PmagSiteRec["site_alpha95"]
PmagResRec["average_n"] = PmagSiteRec["site_n"]
PmagResRec["average_n_lines"] = PmagSiteRec["site_n_lines"]
PmagResRec["average_n_planes"] = PmagSiteRec["site_n_planes"]
PmagResRec["vgp_n"] = PmagSiteRec["site_n"]
PmagResRec["average_k"] = PmagSiteRec["site_k"]
PmagResRec["average_r"] = PmagSiteRec["site_r"]
PmagResRec["average_lat"] = '%10.4f ' % (lat)
PmagResRec["average_lon"] = '%10.4f ' % (lon)
if agefile != "":
PmagResRec = pmag.get_age(PmagResRec, "er_site_names",
"average_", AgeNFO, DefaultAge)
site_height = pmag.get_dictitem(height_nfo, 'er_site_name',
site, 'T')
if len(site_height) > 0:
PmagResRec["average_height"] = site_height[0][
'site_height']
PmagResRec["vgp_lat"] = '%7.1f ' % (plat)
PmagResRec["vgp_lon"] = '%7.1f ' % (plong)
PmagResRec["vgp_dp"] = '%7.1f ' % (dp)
PmagResRec["vgp_dm"] = '%7.1f ' % (dm)
PmagResRec["magic_method_codes"] = PmagSiteRec[
"magic_method_codes"]
if PmagSiteRec['site_tilt_correction'] == '0':
PmagSiteRec['magic_method_codes'] = PmagSiteRec[
'magic_method_codes'] + ":DA-DIR-GEO"
if PmagSiteRec['site_tilt_correction'] == '100':
PmagSiteRec['magic_method_codes'] = PmagSiteRec[
'magic_method_codes'] + ":DA-DIR-TILT"
PmagSiteRec['site_polarity'] = ""
if polarity == 1: # assign polarity based on angle of pole lat to spin axis - may want to re-think this sometime
angle = pmag.angle([0, 0], [0, (90 - plat)])
if angle <= 55.: PmagSiteRec["site_polarity"] = 'n'
if angle > 55. and angle < 125.:
PmagSiteRec["site_polarity"] = 't'
if angle >= 125.: PmagSiteRec["site_polarity"] = 'r'
PmagResults.append(PmagResRec)
if polarity == 1:
crecs = pmag.get_dictitem(PmagSites, 'site_tilt_correction', '100',
'T') # find the tilt corrected data
if len(crecs) < 2:
crecs = pmag.get_dictitem(
PmagSites, 'site_tilt_correction', '0',
'T') # if there aren't any, find the geographic corrected data
if len(crecs) > 2: # if there are some,
comp = pmag.get_list(
crecs,
'site_comp_name').split(':')[0] # find the first component
crecs = pmag.get_dictitem(
crecs, 'site_comp_name', comp,
'T') # fish out all of the first component
precs = []
for rec in crecs:
precs.append({
'dec': rec['site_dec'],
'inc': rec['site_inc'],
'name': rec['er_site_name'],
'loc': rec['er_location_name']
})
polpars = pmag.fisher_by_pol(
precs) # calculate average by polarity
for mode in polpars.keys(
): # hunt through all the modes (normal=A, reverse=B, all=ALL)
PolRes = {}
PolRes['er_citation_names'] = 'This study'
PolRes[
"pmag_result_name"] = "Polarity Average: Polarity " + mode #
PolRes["data_type"] = "a"
PolRes["average_dec"] = '%7.1f' % (polpars[mode]['dec'])
PolRes["average_inc"] = '%7.1f' % (polpars[mode]['inc'])
PolRes["average_n"] = '%i' % (polpars[mode]['n'])
PolRes["average_r"] = '%5.4f' % (polpars[mode]['r'])
PolRes["average_k"] = '%6.0f' % (polpars[mode]['k'])
PolRes["average_alpha95"] = '%7.1f' % (
polpars[mode]['alpha95'])
PolRes['er_site_names'] = polpars[mode]['sites']
PolRes['er_location_names'] = polpars[mode]['locs']
PolRes['magic_software_packages'] = version_num
PmagResults.append(PolRes)
if noInt != 1 and nositeints != 1:
for site in sites: # now do intensities for each site
if plotsites == 1: print site
if Iaverage == 0:
key, intlist = 'specimen', SpecInts # if using specimen level data
if Iaverage == 1:
key, intlist = 'sample', PmagSamps # if using sample level data
Ints = pmag.get_dictitem(
intlist, 'er_site_name', site,
'T') # get all the intensities for this site
if len(Ints) > 0: # there are some
PmagSiteRec = pmag.average_int(
Ints, key,
'site') # get average intensity stuff for site table
PmagResRec = pmag.average_int(
Ints, key,
'average') # get average intensity stuff for results table
if plotsites == 1: # if site by site examination requested - print this site out to the screen
for rec in Ints:
print rec['er_' + key + '_name'], ' %7.1f' % (
1e6 * float(rec[key + '_int']))
if len(Ints) > 1:
print 'Average: ', '%7.1f' % (1e6 * float(
PmagResRec['average_int'])), 'N: ', len(Ints)
print 'Sigma: ', '%7.1f' % (
1e6 * float(PmagResRec['average_int_sigma'])
), 'Sigma %: ', PmagResRec['average_int_sigma_perc']
raw_input('Press any key to continue\n')
er_location_name = Ints[0]["er_location_name"]
PmagSiteRec[
"er_location_name"] = er_location_name # decorate the records
PmagSiteRec["er_citation_names"] = "This study"
PmagResRec["er_location_names"] = er_location_name
PmagResRec["er_citation_names"] = "This study"
PmagSiteRec["er_analyst_mail_names"] = user
PmagResRec["er_analyst_mail_names"] = user
PmagResRec["data_type"] = 'i'
if Iaverage == 0:
PmagSiteRec['er_specimen_names'] = pmag.get_list(
Ints, 'er_specimen_name') # list of all specimens used
PmagResRec['er_specimen_names'] = pmag.get_list(
Ints, 'er_specimen_name')
PmagSiteRec['er_sample_names'] = pmag.get_list(
Ints, 'er_sample_name') # list of all samples used
PmagResRec['er_sample_names'] = pmag.get_list(
Ints, 'er_sample_name')
PmagSiteRec['er_site_name'] = site
PmagResRec['er_site_names'] = site
PmagSiteRec['magic_method_codes'] = pmag.get_list(
Ints, 'magic_method_codes')
PmagResRec['magic_method_codes'] = pmag.get_list(
Ints, 'magic_method_codes')
kill = pmag.grade(PmagSiteRec, accept, 'site_int')
if nocrit == 1 or len(kill) == 0:
b, sig = float(PmagResRec['average_int']), ""
if (PmagResRec['average_int_sigma']) != "":
sig = float(PmagResRec['average_int_sigma'])
sdir = pmag.get_dictitem(PmagResults, 'er_site_names',
site,
'T') # fish out site direction
if len(sdir) > 0 and sdir[-1][
'average_inc'] != "": # get the VDM for this record using last average inclination (hope it is the right one!)
inc = float(sdir[0]['average_inc']) #
mlat = pmag.magnetic_lat(
inc) # get magnetic latitude using dipole formula
PmagResRec["vdm"] = '%8.3e ' % (pmag.b_vdm(
b, mlat)) # get VDM with magnetic latitude
PmagResRec["vdm_n"] = PmagResRec['average_int_n']
if 'average_int_sigma' in PmagResRec.keys(
) and PmagResRec['average_int_sigma'] != "":
vdm_sig = pmag.b_vdm(
float(PmagResRec['average_int_sigma']), mlat)
PmagResRec["vdm_sigma"] = '%8.3e ' % (vdm_sig)
else:
PmagResRec["vdm_sigma"] = ""
mlat = "" # define a model latitude
if get_model_lat == 1: # use present site latitude
mlats = pmag.get_dictitem(SiteNFO, 'er_site_name',
site, 'T')
if len(mlats) > 0: mlat = mlats[0]['site_lat']
elif get_model_lat == 2: # use a model latitude from some plate reconstruction model (or something)
mlats = pmag.get_dictitem(ModelLats, 'er_site_name',
site, 'T')
if len(mlats) > 0:
PmagResRec['model_lat'] = mlats[0][
'site_model_lat']
mlat = PmagResRec['model_lat']
if mlat != "":
PmagResRec["vadm"] = '%8.3e ' % (
pmag.b_vdm(b, float(mlat))
) # get the VADM using the desired latitude
if sig != "":
vdm_sig = pmag.b_vdm(
float(PmagResRec['average_int_sigma']),
float(mlat))
PmagResRec["vadm_sigma"] = '%8.3e ' % (vdm_sig)
PmagResRec["vadm_n"] = PmagResRec['average_int_n']
else:
PmagResRec["vadm_sigma"] = ""
sitedat = pmag.get_dictitem(
SiteNFO, 'er_site_name', PmagSiteRec['er_site_name'],
'T') # fish out site information (lat/lon, etc.)
if len(sitedat) > 0:
sitedat = sitedat[0]
PmagResRec['average_lat'] = sitedat['site_lat']
PmagResRec['average_lon'] = sitedat['site_lon']
else:
PmagResRec['average_lon'] = 'UNKNOWN'
PmagResRec['average_lon'] = 'UNKNOWN'
PmagResRec['magic_software_packages'] = version_num
PmagResRec["pmag_result_name"] = "V[A]DM: Site " + site
PmagResRec["result_description"] = "V[A]DM of site"
PmagResRec["pmag_criteria_codes"] = "ACCEPT"
if agefile != "":
PmagResRec = pmag.get_age(PmagResRec, "er_site_names",
"average_", AgeNFO,
DefaultAge)
site_height = pmag.get_dictitem(height_nfo, 'er_site_name',
site, 'T')
if len(site_height) > 0:
PmagResRec["average_height"] = site_height[0][
'site_height']
PmagSites.append(PmagSiteRec)
PmagResults.append(PmagResRec)
if len(PmagSites) > 0:
Tmp, keylist = pmag.fillkeys(PmagSites)
pmag.magic_write(siteout, Tmp, 'pmag_sites')
print ' sites written to ', siteout
else:
print "No Site level table"
if len(PmagResults) > 0:
TmpRes, keylist = pmag.fillkeys(PmagResults)
pmag.magic_write(resout, TmpRes, 'pmag_results')
print ' results written to ', resout
else:
print "No Results level table"
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(' By default, this information is not available in your measurement file.')
print(' Trying to acquire this information from {}'.format(dir_path))
con = cb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if meas_df is None:
print('-W- No data found in {}'.format(dir_path))
return
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(plot_key))
# need to take the data directly from the contribution here, to keep
# location/site/sample columns in the measurements table
data = con.tables['measurements'].convert_to_pmag_data_list()
file_type = "measurements"
else:
data, file_type = pmag.magic_read(in_file)
# read in data
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append([float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plot_mag(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt != plotlist[-1]: # if it isn't the last plot, init the next one
pmagplotlib.plot_init(FIG['exp'], 6, 6)
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
replace_AC_specimens.py
DESCRIPTION
finds anisotropy corrected data and
replaces that specimen with it.
puts in pmag_specimen format file
SYNTAX
replace_AC_specimens.py [command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of file names
-fu TFILE uncorrected pmag_specimen format file with thellier interpretations
created by thellier_magic_redo.py
-fc AFILE anisotropy corrected pmag_specimen format file
created by thellier_magic_redo.py
-F FILE pmag_specimens format output file
DEFAULTS
TFILE: thellier_specimens.txt
AFILE: AC_specimens.txt
FILE: TorAC_specimens.txt
"""
dir_path='.'
tspec="thellier_specimens.txt"
aspec="AC_specimens.txt"
ofile="TorAC_specimens.txt"
critfile="pmag_criteria.txt"
ACSamplist,Samplist,sigmin=[],[],10000
GoodSamps,SpecOuts=[],[]
# get arguments from command line
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-fu' in sys.argv:
ind=sys.argv.index('-fu')
tspec=sys.argv[ind+1]
if '-fc' in sys.argv:
ind=sys.argv.index('-fc')
aspec=sys.argv[ind+1]
if '-F' in sys.argv:
ind=sys.argv.index('-F')
ofile=sys.argv[ind+1]
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
# read in pmag_specimens file
tspec=dir_path+'/'+tspec
aspec=dir_path+'/'+aspec
ofile=dir_path+'/'+ofile
Specs,file_type=pmag.magic_read(tspec)
Specs,file_type=pmag.magic_read(tspec)
Speclist=pmag.get_specs(Specs)
ACSpecs,file_type=pmag.magic_read(aspec)
ACspeclist=pmag.get_specs(ACSpecs)
for spec in Specs:
if spec["er_sample_name"] not in Samplist:Samplist.append(spec["er_sample_name"])
for spec in ACSpecs:
if spec["er_sample_name"] not in ACSamplist:ACSamplist.append(spec["er_sample_name"])
#
for samp in Samplist:
useAC,Ints,ACInts,GoodSpecs,AC,UC=0,[],[],[],[],[]
for spec in Specs:
if spec["er_sample_name"].lower()==samp.lower():
UC.append(spec)
if samp in ACSamplist:
for spec in ACSpecs:
if spec["er_sample_name"].lower()==samp.lower():
AC.append(spec)
if len(AC)>0:
AClist=[]
for spec in AC:
SpecOuts.append(spec)
AClist.append(spec['er_specimen_name'])
print('using AC: ',spec['er_specimen_name'],'%7.1f'%(1e6*float(spec['specimen_int'])))
for spec in UC:
if spec['er_specimen_name'] not in AClist:
SpecOuts.append(spec)
# print 'using UC: ',spec['er_specimen_name'],'%7.1f'%(1e6*float(spec['specimen_int']))
else:
for spec in UC:
SpecOuts.append(spec)
# print 'using UC: ',spec['er_specimen_name'],'%7.1f'%(1e6*float(spec['specimen_int']))
SpecOuts,keys=pmag.fillkeys(SpecOuts)
pmag.magic_write(ofile,SpecOuts,'pmag_specimens')
print('thellier data assessed for AC correction put in ', ofile)
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(
' By default, this information is not available in your measurement file.'
)
print(
' Trying to acquire this information from {}'.format(dir_path))
con = cb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if meas_df is None:
print('-W- No data found in {}'.format(dir_path))
return
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(
plot_key))
# need to take the data directly from the contribution here, to keep
# location/site/sample columns in the measurements table
data = con.tables['measurements'].convert_to_pmag_data_list()
file_type = "measurements"
else:
data, file_type = pmag.magic_read(in_file)
# read in data
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass'
]
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append(
[float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plot_mag(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt != plotlist[
-1]: # if it isn't the last plot, init the next one
pmagplotlib.plot_init(FIG['exp'], 6, 6)
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from magic_measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG={} # plot dictionary
FIG['exp']=1 # exp is figure 1
dir_path='./'
plot,fmt=0,'svg'
units,dmag_key='T','treatment_dc_field'
XLP=[]
norm=1
in_file,plot_key,LP='magic_measurements.txt','er_location_name',"LP-IRM"
if len(sys.argv)>1:
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-N' in sys.argv:norm=0
if '-sav' in sys.argv:plot=1
if '-fmt' in sys.argv:
ind=sys.argv.index("-fmt")
fmt=sys.argv[ind+1]
if '-f' in sys.argv:
ind=sys.argv.index("-f")
in_file=sys.argv[ind+1]
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
in_file=dir_path+'/'+in_file
if '-obj' in sys.argv:
ind=sys.argv.index('-obj')
plot_by=sys.argv[ind+1]
if plot_by=='sit':plot_key='er_site_name'
if plot_by=='sam':plot_key='er_sample_name'
if plot_by=='spc':plot_key='er_specimen_name'
data,file_type=pmag.magic_read(in_file)
sids=pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'],6,6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist,intlist=[],['measurement_magnitude','measurement_magn_moment','measurement_magn_volume','measurement_magn_mass']
IntMeths=[]
data=pmag.get_dictitem(data,'magic_method_codes',LP,'has') # get all the records with this lab protocol
Ints={}
NoInts,int_key=1,""
for key in intlist:
Ints[key]=pmag.get_dictitem(data,key,'','F') # get all non-blank data for intensity type
if len(Ints[key])>0:
NoInts=0
if int_key=="":int_key=key
if NoInts==1:
print 'No intensity information found'
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist: plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print plt
INTblock=[]
data=pmag.get_dictitem(Ints[int_key],plot_key,plt,'T') # get data with right intensity info whose plot_key matches plot
sids=pmag.get_specs(data) # get a list of specimens with appropriate data
if len(sids)>0:
title=data[0][plot_key]
for s in sids:
INTblock=[]
sdata=pmag.get_dictitem(data,'er_specimen_name',s,'T') # get data for each specimen
for rec in sdata:
INTblock.append([float(rec[dmag_key]),0,0,float(rec[int_key]),1,'g'])
pmagplotlib.plotMT(FIG['exp'],INTblock,title,0,units,norm)
files={}
for key in FIG.keys():
files[key]=title+'_'+LP+'.'+fmt
if plot==0:
pmagplotlib.drawFIGS(FIG)
ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=='q':sys.exit()
if ans=="a":
pmagplotlib.saveP(FIG,files)
else:
pmagplotlib.saveP(FIG,files)
pmagplotlib.clearFIG(FIG['exp'])
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
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
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
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
replace_AC_specimens.py
DESCRIPTION
finds anisotropy corrected data and
replaces that specimen with it.
puts in pmag_specimen format file
SYNTAX
replace_AC_specimens.py [command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of file names
-fu TFILE uncorrected pmag_specimen format file with thellier interpretations
created by thellier_magic_redo.py
-fc AFILE anisotropy corrected pmag_specimen format file
created by thellier_magic_redo.py
-F FILE pmag_specimens format output file
DEFAULTS
TFILE: thellier_specimens.txt
AFILE: AC_specimens.txt
FILE: TorAC_specimens.txt
"""
dir_path = '.'
tspec = "thellier_specimens.txt"
aspec = "AC_specimens.txt"
ofile = "TorAC_specimens.txt"
critfile = "pmag_criteria.txt"
ACSamplist, Samplist, sigmin = [], [], 10000
GoodSamps, SpecOuts = [], []
# get arguments from command line
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-fu' in sys.argv:
ind = sys.argv.index('-fu')
tspec = sys.argv[ind + 1]
if '-fc' in sys.argv:
ind = sys.argv.index('-fc')
aspec = sys.argv[ind + 1]
if '-F' in sys.argv:
ind = sys.argv.index('-F')
ofile = sys.argv[ind + 1]
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
# read in pmag_specimens file
tspec = dir_path + '/' + tspec
aspec = dir_path + '/' + aspec
ofile = dir_path + '/' + ofile
Specs, file_type = pmag.magic_read(tspec)
Specs, file_type = pmag.magic_read(tspec)
Speclist = pmag.get_specs(Specs)
ACSpecs, file_type = pmag.magic_read(aspec)
ACspeclist = pmag.get_specs(ACSpecs)
for spec in Specs:
if spec["er_sample_name"] not in Samplist:
Samplist.append(spec["er_sample_name"])
for spec in ACSpecs:
if spec["er_sample_name"] not in ACSamplist:
ACSamplist.append(spec["er_sample_name"])
#
for samp in Samplist:
useAC, Ints, ACInts, GoodSpecs, AC, UC = 0, [], [], [], [], []
for spec in Specs:
if spec["er_sample_name"].lower() == samp.lower():
UC.append(spec)
if samp in ACSamplist:
for spec in ACSpecs:
if spec["er_sample_name"].lower() == samp.lower():
AC.append(spec)
if len(AC) > 0:
AClist = []
for spec in AC:
SpecOuts.append(spec)
AClist.append(spec['er_specimen_name'])
print('using AC: ', spec['er_specimen_name'],
'%7.1f' % (1e6 * float(spec['specimen_int'])))
for spec in UC:
if spec['er_specimen_name'] not in AClist:
SpecOuts.append(spec)
# print 'using UC: ',spec['er_specimen_name'],'%7.1f'%(1e6*float(spec['specimen_int']))
else:
for spec in UC:
SpecOuts.append(spec)
# print 'using UC: ',spec['er_specimen_name'],'%7.1f'%(1e6*float(spec['specimen_int']))
SpecOuts, keys = pmag.fillkeys(SpecOuts)
pmag.magic_write(ofile, SpecOuts, 'pmag_specimens')
print('thellier data assessed for AC correction put in ', ofile)
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
trmaq_magic.py
DESCTIPTION
does non-linear trm acquisisiton correction
SYNTAX
trmaq_magic.py [-h][-i][command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of file names
-f MFILE, sets magic_measurements input file
-ft TSPEC, sets thellier_specimens input file
-F OUT, sets output for non-linear TRM acquisition corrected data
-sav save figures and quit
-fmt [png, svg, pdf]
-DM [2, 3] MagIC data model, default 3
DEFAULTS
MFILE: trmaq_measurements.txt
TSPEC: thellier_specimens.txt
OUT: NLT_specimens.txt
"""
meas_file = 'trmaq_measurements.txt'
tspec = "thellier_specimens.txt"
output = 'NLT_specimens.txt'
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-i' in sys.argv:
meas_file = input(
"Input magic_measurements file name? [trmaq_measurements.txt] ")
if meas_file == "":
meas_file = "trmaq_measurements.txt"
tspec = input(
" thellier_specimens file name? [thellier_specimens.txt] ")
if tspec == "":
tspec = "thellier_specimens.txt"
output = input(
"File for non-linear TRM adjusted specimen data: [NLTspecimens.txt] ")
if output == "":
output = "NLT_specimens.txt"
if '-f' in sys.argv:
ind = sys.argv.index('-f')
meas_file = sys.argv[ind+1]
if '-ft' in sys.argv:
ind = sys.argv.index('-ft')
tspec = sys.argv[ind+1]
if '-F' in sys.argv:
ind = sys.argv.index('-F')
output = sys.argv[ind+1]
if '-sav' in sys.argv:
save_plots = True
else:
save_plots = False
fmt = pmag.get_named_arg("-fmt", "svg")
#
PLT = {'aq': 1}
if not save_plots:
pmagplotlib.plot_init(PLT['aq'], 5, 5)
#
# get name of file from command line
#
comment = ""
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if 'measurements' not in file_type:
print(file_type, "This is not a valid measurements file ")
sys.exit()
if data_model_num == 2:
spec_col = "er_specimen_name"
lab_field_dc_col = "specimen_lab_field_dc"
int_col = "specimen_int"
meth_col = "magic_method_codes"
treat_dc_col = "treatment_dc_field"
magn_moment_col = "measurement_magn_moment"
experiment_col = "magic_experiment_name"
outfile_type = "pmag_specimens"
else:
spec_col = "specimen"
lab_field_dc_col = "int_treat_dc_field"
int_col = "int_abs"
meth_col = "method_codes"
treat_dc_col = "treat_dc_field"
magn_moment_col = "magn_moment"
experiment_col = "experiment"
outfile_type = "specimens"
sids = pmag.get_specs(meas_data)
specimen = 0
#
# read in thellier_specimen data
#
nrm, file_type = pmag.magic_read(tspec)
PmagSpecRecs= []
while specimen < len(sids):
#
# find corresoponding paleointensity data for this specimen
#
s = sids[specimen]
blab, best = "", ""
for nrec in nrm: # pick out the Banc data for this spec
if nrec[spec_col] == s:
try:
blab = float(nrec[lab_field_dc_col])
except ValueError:
continue
best = float(nrec[int_col])
TrmRec = nrec
break
if blab == "":
print("skipping ", s, " : no best ")
specimen += 1
else:
print(sids[specimen], specimen+1, 'of ',
len(sids), 'Best = ', best*1e6)
MeasRecs = []
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec[spec_col] == s:
meths = rec[meth_col].split(":")
methcodes = []
for meth in meths:
methcodes.append(meth.strip())
if "LP-TRM" in methcodes:
MeasRecs.append(rec)
if len(MeasRecs) < 2:
specimen += 1
print('skipping specimen - no trm acquisition data ', s)
#
# collect info for the PmagSpecRec dictionary
#
else:
TRMs, Bs = [], []
for rec in MeasRecs:
Bs.append(float(rec[treat_dc_col]))
TRMs.append(float(rec[magn_moment_col]))
# 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(
PLT['aq'], Bs, TRMs, Bp, Mp, NLpars, rec[experiment_col])
if not save_plots:
pmagplotlib.draw_figs(PLT)
print('Banc= ', float(NLpars['banc'])*1e6)
trmTC = {}
for key in list(TrmRec.keys()):
# copy of info from thellier_specimens record
trmTC[key] = TrmRec[key]
trmTC[int_col] = '%8.3e' % (NLpars['banc'])
trmTC[meth_col] = TrmRec[meth_col]+":DA-NL"
PmagSpecRecs.append(trmTC)
if not save_plots:
ans = input("Return for next specimen, s[a]ve plot ")
if ans == 'a':
Name = {'aq': rec[spec_col]+'_TRM.{}'.format(fmt)}
pmagplotlib.save_plots(PLT, Name)
else:
Name = {'aq': rec[spec_col]+'_TRM.{}'.format(fmt)}
pmagplotlib.save_plots(PLT, Name)
specimen += 1
pmag.magic_write(output, PmagSpecRecs, outfile_type)
def main():
"""
NAME
dmag_magic.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols (for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG={} # plot dictionary
FIG['demag']=1 # demag is figure 1
in_file,plot_key,LT='magic_measurements.txt','er_location_name',"LT-AF-Z"
XLP=""
norm=1
LT='LT-AF-Z'
units,dmag_key='T','treatment_ac_field'
plot=0
fmt='svg'
if len(sys.argv)>1:
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-N' in sys.argv: norm=0
if '-sav' in sys.argv:
plot=1
if '-f' in sys.argv:
ind=sys.argv.index("-f")
in_file=sys.argv[ind+1]
if '-fmt' in sys.argv:
ind=sys.argv.index("-fmt")
fmt=sys.argv[ind+1]
if '-obj' in sys.argv:
ind=sys.argv.index('-obj')
plot_by=sys.argv[ind+1]
if plot_by=='sit':plot_key='er_site_name'
if plot_by=='sam':plot_key='er_sample_name'
if plot_by=='spc':plot_key='er_specimen_name'
if '-XLP' in sys.argv:
ind=sys.argv.index("-XLP")
XLP=sys.argv[ind+1] # get lab protocol for excluding
if '-LT' in sys.argv:
ind=sys.argv.index("-LT")
LT='LT-'+sys.argv[ind+1]+'-Z' # get lab treatment for plotting
if LT=='LT-T-Z':
units,dmag_key='K','treatment_temp'
elif LT=='LT-AF-Z':
units,dmag_key='T','treatment_ac_field'
elif LT=='LT-M-Z':
units,dmag_key='J','treatment_mw_energy'
else:
units='U'
data,file_type=pmag.magic_read(in_file)
sids=pmag.get_specs(data)
pmagplotlib.plot_init(FIG['demag'],5,5)
print len(data),' records read from ',in_file
#
#
# find desired intensity data
#
#
plotlist,intlist=[],['measurement_magnitude','measurement_magn_moment','measurement_magn_volume','measurement_magn_mass']
IntMeths=[]
FixData=[]
for rec in data:
meths=[]
methcodes=rec['magic_method_codes'].split(':')
for meth in methcodes:meths.append(meth.strip())
for key in rec.keys():
if key in intlist and rec[key]!="":
if key not in IntMeths:IntMeths.append(key)
if rec[plot_key] not in plotlist and LT in meths: plotlist.append(rec[plot_key])
if 'measurement_flag' not in rec.keys():rec['measurement_flag']='g'
FixData.append(rec)
plotlist.sort()
if len(IntMeths)==0:
print 'No intensity information found'
sys.exit()
data=FixData
int_key=IntMeths[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
for plt in plotlist:
if plot==0: print plt,'plotting by: ',plot_key
PLTblock=pmag.get_dictitem(data,plot_key,plt,'T') # fish out all the data for this type of plot
PLTblock=pmag.get_dictitem(PLTblock,'magic_method_codes',LT,'has') # fish out all the dmag for this experiment type
PLTblock=pmag.get_dictitem(PLTblock,int_key,'','F') # get all with this intensity key non-blank
if XLP!="":PLTblock=pmag.get_dictitem(PLTblock,'magic_method_codes',XLP,'not') # reject data with XLP in method_code
if len(PLTblock)>2:
title=PLTblock[0][plot_key]
spcs=[]
for rec in PLTblock:
if rec['er_specimen_name'] not in spcs:spcs.append(rec['er_specimen_name'])
for spc in spcs:
SPCblock=pmag.get_dictitem(PLTblock,'er_specimen_name',spc,'T') # plot specimen by specimen
INTblock=[]
for rec in SPCblock:
INTblock.append([float(rec[dmag_key]),0,0,float(rec[int_key]),1,rec['measurement_flag']])
if len(INTblock)>2:
pmagplotlib.plotMT(FIG['demag'],INTblock,title,0,units,norm)
if plot==1:
files={}
for key in FIG.keys():
files[key]=title+'_'+LT+'.'+fmt
pmagplotlib.saveP(FIG,files)
sys.exit()
else:
pmagplotlib.drawFIGS(FIG)
ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=='q':sys.exit()
if ans=="a":
files={}
for key in FIG.keys():
files[key]=title+'_'+LT+'.svg'
pmagplotlib.saveP(FIG,files)
pmagplotlib.clearFIG(FIG['demag'])
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
