def spitout(line):
if '\t' in line:
dat=line.split('\t') # split the data on a space into columns
else:
dat=line.split() # split the data on a space into columns
b,lat=float(dat[0])*1e-6,float(dat[1])
vdm= pmag.b_vdm(b,lat) #
return vdm
def main():
"""
NAME
b_vdm.py
DESCRIPTION
converts B (in microT) and (magnetic) latitude to V(A)DM
INPUT (COMMAND LINE ENTRY)
B (microtesla), latitude (positive north)
OUTPUT
V[A]DM
SYNTAX
b_vdm.py [command line options] [< filename]
OPTIONS
-h prints help and quits
-i for interactive data entry
-f FILE input file
-F FILE output
"""
input,out="",""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'rU')
input=f.readlines()
if '-F' in sys.argv:
ind=sys.argv.index('-F')
o=sys.argv[ind+1]
out=open(o,'w')
if '-i' in sys.argv:
cont=1
while cont==1:
try:
b=1e-6*float(raw_input('B (in microtesla): <cntl-D to quit '))
lat=float(raw_input('Latitude: '))
except:
print "\nGood bye\n"
sys.exit()
vdm= pmag.b_vdm(b,lat)
print '%10.3e '%(vdm)
if input=="":
input = sys.stdin.readlines() # read from standard input
for line in input:
vdm=spitout(line)
if out=="":
print '%10.3e'%(vdm)
else:
out.write('%10.3e \n'%(vdm))
def main():
"""
NAME
igrf.py
DESCRIPTION
This program calculates igrf field values
using the routine of Malin and Barraclough (1981)
based on d/igrfs from 1900 to 2010.
between 1900 and 1000BCE, it uses CALS3K.4 or ARCH3K.1
Prior to 1000BCE, it uses CALS10k-4b
Calculates reference field vector at specified location and time.
SYNTAX
igrf.py [-h] [-i] -f FILE [< filename]
OPTIONS:
-h prints help message and quits
-i for interactive data entry
-f FILE specify file name with input data
-F FILE specify output file name
-ages MIN MAX INCR: specify age minimum in years (+/- AD), maximum and increment, default is line by line
-loc LAT LON; specify location, default is line by line
-alt ALT; specify altitude in km, default is sealevel (0)
-plt; make a plot of the time series
-fmt [pdf,jpg,eps,svg] specify format for output figure (default is svg)
-mod [arch3k,cals3k] specify model for 3ka to 1900 AD, default is cals3k.4b
INPUT FORMAT
interactive entry:
date: decimal year
alt: altitude in km
lat: positive north
lon: positive east
for file entry:
space delimited string: date alt lat long
OUTPUT FORMAT
Declination Inclination Intensity (nT) date alt lat long
"""
plt,fmt=0,'svg'
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if len(sys.argv)!=0 and '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-mod' in sys.argv:
ind=sys.argv.index('-mod')
mod3k=sys.argv[ind+1]
else: mod3k=''
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
input=numpy.loadtxt(file)
elif '-i' in sys.argv:
while 1:
try:
line=[]
line.append(float(raw_input("Decimal year: <cntrl-D to quit> ")))
alt=raw_input("Elevation in km [0] ")
if alt=="":alt="0"
line.append(float(alt))
line.append(float(raw_input("Latitude (positive north) ")))
line.append(float(raw_input("Longitude (positive east) ")))
if mod3k=='':
x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0])
else:
x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod3k=mod3k)
Dir=pmag.cart2dir((x,y,z))
print '%7.1f %7.1f %8.0f'%(Dir[0],Dir[1],f)
except EOFError:
print "\n Good-bye\n"
sys.exit()
elif '-ages' in sys.argv:
ind=sys.argv.index('-ages')
agemin=float(sys.argv[ind+1])
agemax=float(sys.argv[ind+2])
ageincr=float(sys.argv[ind+3])
if '-loc' in sys.argv:
ind=sys.argv.index('-loc')
lat=float(sys.argv[ind+1])
lon=float(sys.argv[ind+2])
else:
print "must specify lat/lon if using age range option"
sys.exit()
if '-alt' in sys.argv:
ind=sys.argv.index('-alt')
alt=float(sys.argv[ind+1])
else: alt=0
ages=numpy.arange(agemin,agemax,ageincr)
lats=numpy.ones(len(ages))*lat
lons=numpy.ones(len(ages))*lon
alts=numpy.ones(len(ages))*alt
input=numpy.array([ages,alts,lats,lons]).transpose()
else:
input=numpy.loadtxt(sys.stdin,dtype=numpy.float)
if '-F' in sys.argv:
ind=sys.argv.index('-F')
outfile=sys.argv[ind+1]
out=open(outfile,'w')
else:outfile=""
if '-plt' in sys.argv:
plt=1
import matplotlib
matplotlib.use("TkAgg")
import pylab
pylab.ion()
Ages,Decs,Incs,Ints,VADMs=[],[],[],[],[]
for line in input:
if mod3k=='':
x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0])
else:
x,y,z,f=pmag.doigrf(line[3]%360.,line[2],line[1],line[0],mod3k=mod3k)
Dir=pmag.cart2dir((x,y,z))
if outfile!="":
out.write('%7.1f %7.1f %8.0f %7.1f %7.1f %7.1f %7.1f\n'%(Dir[0],Dir[1],f,line[0],line[1],line[2],line[3]))
elif plt:
Ages.append(line[0])
if Dir[0]>180: Dir[0]=Dir[0]-360.0
Decs.append(Dir[0])
Incs.append(Dir[1])
Ints.append(f*1e-3)
VADMs.append(pmag.b_vdm(f*1e-9,line[2])*1e-21)
else:
print '%7.1f %7.1f %8.0f %7.1f %7.1f %7.1f %7.1f'%(Dir[0],Dir[1],f,line[0],line[1],line[2],line[3])
if plt:
fig=pylab.figure(num=1,figsize=(7,9))
fig.add_subplot(411)
pylab.plot(Ages,Decs)
pylab.ylabel('Declination ($^{\circ}$)')
fig.add_subplot(412)
pylab.plot(Ages,Incs)
pylab.ylabel('Inclination ($^{\circ}$)')
fig.add_subplot(413)
pylab.plot(Ages,Ints)
pylab.ylabel('Intensity ($\mu$T)')
fig.add_subplot(414)
pylab.plot(Ages,VADMs)
pylab.ylabel('VADMs (ZAm$^2$)')
pylab.xlabel('Ages')
pylab.draw()
ans=raw_input("S[a]ve to save figure, <Return> to quit ")
if ans=='a':
pylab.savefig('igrf.'+fmt)
print 'Figure saved as: ','igrf.'+fmt
sys.exit()
def main():
"""
NAME
specimens_results_magic.py
DESCRIPTION
combines pmag_specimens.txt file with age, location, acceptance criteria and
outputs pmag_results table along with other MagIC tables necessary for uploading to the database
SYNTAX
specimens_results_magic.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specimen input magic_measurements format file, default is "magic_measurements.txt"
-fsp: specimen input pmag_specimens format file, default is "pmag_specimens.txt"
-fsm: sample input er_samples format file, default is "er_samples.txt"
-fsi: specimen input er_sites format file, default is "er_sites.txt"
-fla: specify a file with paleolatitudes for calculating VADMs, default is not to calculate VADMS
format is: site_name paleolatitude (space delimited file)
-fa AGES: specify er_ages format file with age information
-crd [s,g,t,b]: specify coordinate system
(s, specimen, g geographic, t, tilt corrected, b, geographic and tilt corrected)
Default is to assume geographic
NB: only the tilt corrected data will appear on the results table, if both g and t are selected.
-cor [AC:CR:NL]: colon delimited list of required data adjustments for all specimens
included in intensity calculations (anisotropy, cooling rate, non-linear TRM)
unless specified, corrections will not be applied
-pri [TRM:ARM] colon delimited list of priorities for anisotropy correction (-cor must also be set to include AC). default is TRM, then ARM
-age MIN MAX UNITS: specify age boundaries and units
-exc: use exiting selection criteria (in pmag_criteria.txt file), default is default criteria
-C: no acceptance criteria
-aD: average directions per sample, default is NOT
-aI: average multiple specimen intensities per sample, default is by site
-aC: average all components together, default is NOT
-pol: calculate polarity averages
-sam: save sample level vgps and v[a]dms, default is by site
-xSi: skip the site level intensity calculation
-p: plot directions and look at intensities by site, default is NOT
-fmt: specify output for saved images, default is svg (only if -p set)
-lat: use present latitude for calculating VADMs, default is not to calculate VADMs
-xD: skip directions
-xI: skip intensities
OUPUT
writes pmag_samples, pmag_sites, pmag_results tables
"""
# set defaults
Comps=[] # list of components
version_num=pmag.get_version()
args=sys.argv
DefaultAge=["none"]
skipdirs,coord,excrit,custom,vgps,average,Iaverage,plotsites,opt=1,0,0,0,0,0,0,0,0
get_model_lat=0 # this skips VADM calculation altogether, when get_model_lat=1, uses present day
fmt='svg'
dir_path="."
model_lat_file=""
Caverage=0
infile='pmag_specimens.txt'
measfile="magic_measurements.txt"
sampfile="er_samples.txt"
sitefile="er_sites.txt"
agefile="er_ages.txt"
specout="er_specimens.txt"
sampout="pmag_samples.txt"
siteout="pmag_sites.txt"
resout="pmag_results.txt"
critout="pmag_criteria.txt"
instout="magic_instruments.txt"
sigcutoff,OBJ="",""
noDir,noInt=0,0
polarity=0
coords=['0']
Dcrit,Icrit,nocrit=0,0,0
corrections=[]
nocorrection=['DA-NL','DA-AC','DA-CR']
priorities=['DA-AC-ARM','DA-AC-TRM'] # priorities for anisotropy correction
# get command line stuff
if "-h" in args:
print main.__doc__
sys.exit()
if '-WD' in args:
ind=args.index("-WD")
dir_path=args[ind+1]
if '-cor' in args:
ind=args.index('-cor')
cors=args[ind+1].split(':') # list of required data adjustments
for cor in cors:
nocorrection.remove('DA-'+cor)
corrections.append('DA-'+cor)
if '-pri' in args:
ind=args.index('-pri')
priorities=args[ind+1].split(':') # list of required data adjustments
for p in priorities:
p='DA-AC-'+p
if '-f' in args:
ind=args.index("-f")
measfile=args[ind+1]
if '-fsp' in args:
ind=args.index("-fsp")
infile=args[ind+1]
if '-fsi' in args:
ind=args.index("-fsi")
sitefile=args[ind+1]
if "-crd" in args:
ind=args.index("-crd")
coord=args[ind+1]
if coord=='s':coords=['-1']
if coord=='g':coords=['0']
if coord=='t':coords=['100']
if coord=='b':coords=['0','100']
if "-usr" in args:
ind=args.index("-usr")
user=sys.argv[ind+1]
else: user=""
if "-C" in args: Dcrit,Icrit,nocrit=1,1,1 # no selection criteria
if "-sam" in args: vgps=1 # save sample level VGPS/VADMs
if "-xSi" in args:
nositeints=1 # skip site level intensity
else:
nositeints=0
if "-age" in args:
ind=args.index("-age")
DefaultAge[0]=args[ind+1]
DefaultAge.append(args[ind+2])
DefaultAge.append(args[ind+3])
Daverage,Iaverage,Caverage=0,0,0
if "-aD" in args: Daverage=1 # average by sample directions
if "-aI" in args: Iaverage=1 # average by sample intensities
if "-aC" in args: Caverage=1 # average all components together ??? why???
if "-pol" in args: polarity=1 # calculate averages by polarity
if '-xD' in args:noDir=1
if '-xI' in args:
noInt=1
elif "-fla" in args:
if '-lat' in args:
print "you should set a paleolatitude file OR use present day lat - not both"
sys.exit()
ind=args.index("-fla")
model_lat_file=dir_path+'/'+args[ind+1]
get_model_lat=2
mlat=open(model_lat_file,'rU')
ModelLats=[]
for line in mlat.readlines():
ModelLat={}
tmp=line.split()
ModelLat["er_site_name"]=tmp[0]
ModelLat["site_model_lat"]=tmp[1]
ModelLat["er_sample_name"]=tmp[0]
ModelLat["sample_lat"]=tmp[1]
ModelLats.append(ModelLat)
get_model_lat=2
elif '-lat' in args:
get_model_lat=1
if "-p" in args:
plotsites=1
if "-fmt" in args:
ind=args.index("-fmt")
fmt=args[ind+1]
if noDir==0: # plot by site - set up plot window
import pmagplotlib
EQ={}
EQ['eqarea']=1
pmagplotlib.plot_init(EQ['eqarea'],5,5) # define figure 1 as equal area projection
pmagplotlib.plotNET(EQ['eqarea']) # I don't know why this has to be here, but otherwise the first plot never plots...
pmagplotlib.drawFIGS(EQ)
if '-WD' in args:
infile=dir_path+'/'+infile
measfile=dir_path+'/'+measfile
instout=dir_path+'/'+instout
sampfile=dir_path+'/'+sampfile
sitefile=dir_path+'/'+sitefile
agefile=dir_path+'/'+agefile
specout=dir_path+'/'+specout
sampout=dir_path+'/'+sampout
siteout=dir_path+'/'+siteout
resout=dir_path+'/'+resout
critout=dir_path+'/'+critout
if "-exc" in args: # use existing pmag_criteria file
if "-C" in args:
print 'you can not use both existing and no criteria - choose either -exc OR -C OR neither (for default)'
sys.exit()
crit_data,file_type=pmag.magic_read(critout)
print "Acceptance criteria read in from ", critout
else : # use default criteria (if nocrit set, then get really loose criteria as default)
crit_data=pmag.default_criteria(nocrit)
if nocrit==0:
print "Acceptance criteria are defaults"
else:
print "No acceptance criteria used "
accept={}
for critrec in crit_data:
for key in critrec.keys():
if 'sample_int_sigma_uT' in critrec.keys():
critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
if key not in accept.keys() and critrec[key]!='':
accept[key]=critrec[key]
#
#
if "-exc" not in args and "-C" not in args:
print "args",args
pmag.magic_write(critout,[accept],'pmag_criteria')
print "\n Pmag Criteria stored in ",critout,'\n'
#
# now we're done slow dancing
#
SiteNFO,file_type=pmag.magic_read(sitefile) # read in site data - has the lats and lons
SampNFO,file_type=pmag.magic_read(sampfile) # read in site data - has the lats and lons
height_nfo=pmag.get_dictitem(SiteNFO,'site_height','','F') # find all the sites with height info.
if agefile !="":AgeNFO,file_type=pmag.magic_read(agefile) # read in the age information
Data,file_type=pmag.magic_read(infile) # read in specimen interpretations
IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
comment,orient="",[]
samples,sites=[],[]
for rec in Data: # run through the data filling in missing keys and finding all components, coordinates available
# fill in missing fields, collect unique sample and site names
if 'er_sample_name' not in rec.keys():
rec['er_sample_name']=""
elif rec['er_sample_name'] not in samples:
samples.append(rec['er_sample_name'])
if 'er_site_name' not in rec.keys():
rec['er_site_name']=""
elif rec['er_site_name'] not in sites:
sites.append(rec['er_site_name'])
if 'specimen_int' not in rec.keys():rec['specimen_int']=''
if 'specimen_comp_name' not in rec.keys() or rec['specimen_comp_name']=="":rec['specimen_comp_name']='A'
if rec['specimen_comp_name'] not in Comps:Comps.append(rec['specimen_comp_name'])
rec['specimen_tilt_correction']=rec['specimen_tilt_correction'].strip('\n')
if "specimen_tilt_correction" not in rec.keys(): rec["specimen_tilt_correction"]="-1" # assume sample coordinates
if rec["specimen_tilt_correction"] not in orient: orient.append(rec["specimen_tilt_correction"]) # collect available coordinate systems
if "specimen_direction_type" not in rec.keys(): rec["specimen_direction_type"]='l' # assume direction is line - not plane
if "specimen_dec" not in rec.keys(): rec["specimen_direction_type"]='' # if no declination, set direction type to blank
if "specimen_n" not in rec.keys(): rec["specimen_n"]='' # put in n
if "specimen_alpha95" not in rec.keys(): rec["specimen_alpha95"]='' # put in alpha95
if "magic_method_codes" not in rec.keys(): rec["magic_method_codes"]=''
#
# start parsing data into SpecDirs, SpecPlanes, SpecInts
SpecInts,SpecDirs,SpecPlanes=[],[],[]
samples.sort() # get sorted list of samples and sites
sites.sort()
if noInt==0: # don't skip intensities
IntData=pmag.get_dictitem(Data,'specimen_int','','F') # retrieve specimens with intensity data
if nocrit==0: # use selection criteria
for rec in IntData: # do selection criteria
kill=pmag.grade(rec,accept,'specimen_int')
if len(kill)==0: SpecInts.append(rec) # intensity record to be included in sample, site calculations
else:
SpecInts=IntData[:] # take everything - no selection criteria
# check for required data adjustments
if len(corrections)>0 and len(SpecInts)>0:
for cor in corrections:
SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'has') # only take specimens with the required corrections
if len(nocorrection)>0 and len(SpecInts)>0:
for cor in nocorrection:
SpecInts=pmag.get_dictitem(SpecInts,'magic_method_codes',cor,'not') # exclude the corrections not specified for inclusion
# take top priority specimen of its name in remaining specimens (only one per customer)
PrioritySpecInts=[]
specimens=pmag.get_specs(SpecInts) # get list of uniq specimen names
for spec in specimens:
ThisSpecRecs=pmag.get_dictitem(SpecInts,'er_specimen_name',spec,'T') # all the records for this specimen
if len(ThisSpecRecs)==1:
PrioritySpecInts.append(ThisSpecRecs[0])
elif len(ThisSpecRecs)>1: # more than one
prec=[]
for p in priorities:
ThisSpecRecs=pmag.get_dictitem(SpecInts,'magic_method_codes',p,'has') # all the records for this specimen
if len(ThisSpecRecs)>0:prec.append(ThisSpecRecs[0])
PrioritySpecInts.append(prec[0]) # take the best one
SpecInts=PrioritySpecInts # this has the first specimen record
if noDir==0: # don't skip directions
AllDirs=pmag.get_dictitem(Data,'specimen_direction_type','','F') # retrieve specimens with directed lines and planes
Ns=pmag.get_dictitem(AllDirs,'specimen_n','','F') # get all specimens with specimen_n information
if nocrit!=1: # use selection criteria
for rec in Ns: # look through everything with specimen_n for "good" data
kill=pmag.grade(rec,accept,'specimen_dir')
if len(kill)==0: # nothing killed it
SpecDirs.append(rec)
else: # no criteria
SpecDirs=AllDirs[:] # take them all
# SpecDirs is now the list of all specimen directions (lines and planes) that pass muster
#
PmagSamps,SampDirs=[],[] # list of all sample data and list of those that pass the DE-SAMP criteria
PmagSites,PmagResults=[],[] # list of all site data and selected results
SampInts=[]
for samp in samples: # run through the sample names
if Daverage==1: # average by sample if desired
SampDir=pmag.get_dictitem(SpecDirs,'er_sample_name',samp,'T') # get all the directional data for this sample
if len(SampDir)>0: # there are some directions
for coord in coords: # step through desired coordinate systems
CoordDir=pmag.get_dictitem(SampDir,'specimen_tilt_correction',coord,'T') # get all the directions for this sample
if len(CoordDir)>0: # there are some with this coordinate system
if Caverage==0: # look component by component
for comp in Comps:
CompDir=pmag.get_dictitem(CoordDir,'specimen_comp_name',comp,'T') # get all directions from this component
if len(CompDir)>0: # there are some
PmagSampRec=pmag.lnpbykey(CompDir,'sample','specimen') # get a sample average from all specimens
PmagSampRec["er_location_name"]=CompDir[0]['er_location_name'] # decorate the sample record
PmagSampRec["er_site_name"]=CompDir[0]['er_site_name']
PmagSampRec["er_sample_name"]=samp
PmagSampRec["er_citation_names"]="This study"
PmagSampRec["er_analyst_mail_names"]=user
PmagSampRec['magic_software_packages']=version_num
if nocrit!=1:PmagSampRec['pmag_criteria_codes']="ACCEPT"
if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
PmagSampRec['sample_comp_name']=comp
PmagSampRec['sample_tilt_correction']=coord
PmagSampRec['er_specimen_names']= pmag.get_list(CompDir,'er_specimen_name') # get a list of the specimen names used
PmagSampRec['magic_method_codes']= pmag.get_list(CompDir,'magic_method_codes') # get a list of the methods used
if nocrit!=1: # apply selection criteria
kill=pmag.grade(PmagSampRec,accept,'sample_dir')
else:
kill=[]
if len(kill)==0:
SampDirs.append(PmagSampRec)
if vgps==1: # if sample level VGP info desired, do that now
PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
if PmagResRec!="":PmagResults.append(PmagResRec)
PmagSamps.append(PmagSampRec)
if Caverage==1: # average all components together basically same as above
PmagSampRec=pmag.lnpbykey(CoordDir,'sample','specimen')
PmagSampRec["er_location_name"]=CoordDir[0]['er_location_name']
PmagSampRec["er_site_name"]=CoordDir[0]['er_site_name']
PmagSampRec["er_sample_name"]=samp
PmagSampRec["er_citation_names"]="This study"
PmagSampRec["er_analyst_mail_names"]=user
PmagSampRec['magic_software_packages']=version_num
if nocrit!=1:PmagSampRec['pmag_criteria_codes']=""
if agefile != "": PmagSampRec= pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
PmagSampRec['sample_tilt_correction']=coord
PmagSampRec['sample_comp_name']= pmag.get_list(CoordDir,'specimen_comp_name') # get components used
PmagSampRec['er_specimen_names']= pmag.get_list(CoordDir,'er_specimen_name') # get specimne names averaged
PmagSampRec['magic_method_codes']= pmag.get_list(CoordDir,'magic_method_codes') # assemble method codes
if nocrit!=1: # apply selection criteria
kill=pmag.grade(PmagSampRec,accept,'sample_dir')
if len(kill)==0: # passes the mustard
SampDirs.append(PmagSampRec)
if vgps==1:
PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
if PmagResRec!="":PmagResults.append(PmagResRec)
else: # take everything
SampDirs.append(PmagSampRec)
if vgps==1:
PmagResRec=pmag.getsampVGP(PmagSampRec,SiteNFO)
if PmagResRec!="":PmagResults.append(PmagResRec)
PmagSamps.append(PmagSampRec)
if Iaverage==1: # average by sample if desired
SampI=pmag.get_dictitem(SpecInts,'er_sample_name',samp,'T') # get all the intensity data for this sample
if len(SampI)>0: # there are some
PmagSampRec=pmag.average_int(SampI,'specimen','sample') # get average intensity stuff
PmagSampRec["sample_description"]="sample intensity" # decorate sample record
PmagSampRec["sample_direction_type"]=""
PmagSampRec['er_site_name']=SampI[0]["er_site_name"]
PmagSampRec['er_sample_name']=samp
PmagSampRec['er_location_name']=SampI[0]["er_location_name"]
PmagSampRec["er_citation_names"]="This study"
PmagSampRec["er_analyst_mail_names"]=user
if agefile != "": PmagSampRec=pmag.get_age(PmagSampRec,"er_site_name","sample_inferred_", AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',PmagSampRec['er_site_name'],'T')
if len(site_height)>0:PmagSampRec["sample_height"]=site_height[0]['site_height'] # add in height if available
PmagSampRec['er_specimen_names']= pmag.get_list(SampI,'er_specimen_name')
PmagSampRec['magic_method_codes']= pmag.get_list(SampI,'magic_method_codes')
if nocrit!=1: # apply criteria!
kill=pmag.grade(PmagSampRec,accept,'sample_int')
if len(kill)==0:
PmagSampRec['pmag_criteria_codes']="ACCEPT"
SampInts.append(PmagSampRec)
PmagSamps.append(PmagSampRec)
else:PmagSampRec={} # sample rejected
else: # no criteria
SampInts.append(PmagSampRec)
PmagSamps.append(PmagSampRec)
PmagSampRec['pmag_criteria_codes']=""
if vgps==1 and get_model_lat!=0 and PmagSampRec!={}: #
if get_model_lat==1: # use sample latitude
PmagResRec=pmag.getsampVDM(PmagSampRec,SampNFO)
del(PmagResRec['model_lat']) # get rid of the model lat key
elif get_model_lat==2: # use model latitude
PmagResRec=pmag.getsampVDM(PmagSampRec,ModelLats)
if PmagResRec!={}:PmagResRec['magic_method_codes']=PmagResRec['magic_method_codes']+":IE-MLAT"
if PmagResRec!={}:
PmagResRec['er_specimen_names']=PmagSampRec['er_specimen_names']
PmagResRec['er_sample_names']=PmagSampRec['er_sample_name']
PmagResRec['pmag_criteria_codes']='ACCEPT'
PmagResRec['average_int_sigma_perc']=PmagSampRec['sample_int_sigma_perc']
PmagResRec['average_int_sigma']=PmagSampRec['sample_int_sigma']
PmagResRec['average_int_n']=PmagSampRec['sample_int_n']
PmagResRec['vadm_n']=PmagSampRec['sample_int_n']
PmagResRec['data_type']='i'
PmagResults.append(PmagResRec)
if len(PmagSamps)>0:
TmpSamps,keylist=pmag.fillkeys(PmagSamps) # fill in missing keys from different types of records
pmag.magic_write(sampout,TmpSamps,'pmag_samples') # save in sample output file
print ' sample averages written to ',sampout
#
#create site averages from specimens or samples as specified
#
for site in sites:
if Daverage==0: key,dirlist='specimen',SpecDirs # if specimen averages at site level desired
if Daverage==1: key,dirlist='sample',SampDirs # if sample averages at site level desired
tmp=pmag.get_dictitem(dirlist,'er_site_name',site,'T') # get all the sites with directions
tmp1=pmag.get_dictitem(tmp,key+'_tilt_correction',coords[-1],'T') # use only the last coordinate if Caverage==0
sd=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T') # fish out site information (lat/lon, etc.)
if len(sd)>0:
sitedat=sd[0]
if Caverage==0: # do component wise averaging
for comp in Comps:
siteD=pmag.get_dictitem(tmp1,key+'_comp_name',comp,'T') # get all components comp
if len(siteD)>0: # there are some for this site and component name
PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get an average for this site
PmagSiteRec['site_comp_name']=comp # decorate the site record
PmagSiteRec["er_location_name"]=siteD[0]['er_location_name']
PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
PmagSiteRec['site_tilt_correction']=coords[-1]
PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
if Daverage==1:
PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
else:
PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
# determine the demagnetization code (DC3,4 or 5) for this site
AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
DC=3
if AFnum>0:DC+=1
if Tnum>0:DC+=1
PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
PmagSiteRec['magic_method_codes'].strip(":")
if plotsites==1:
print PmagSiteRec['er_site_name']
pmagplotlib.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key) # plot and list the data
pmagplotlib.drawFIGS(EQ)
PmagSites.append(PmagSiteRec)
else: # last component only
siteD=tmp1[:] # get the last orientation system specified
if len(siteD)>0: # there are some
PmagSiteRec=pmag.lnpbykey(siteD,'site',key) # get the average for this site
PmagSiteRec["er_location_name"]=siteD[0]['er_location_name'] # decorate the record
PmagSiteRec["er_site_name"]=siteD[0]['er_site_name']
PmagSiteRec['site_comp_name']=comp
PmagSiteRec['site_tilt_correction']=coords[-1]
PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
PmagSiteRec['er_specimen_names']= pmag.get_list(siteD,'er_specimen_name')
PmagSiteRec['er_sample_names']= pmag.get_list(siteD,'er_sample_name')
AFnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-AF','has'))
Tnum=len(pmag.get_dictitem(siteD,'magic_method_codes','LP-DIR-T','has'))
DC=3
if AFnum>0:DC+=1
if Tnum>0:DC+=1
PmagSiteRec['magic_method_codes']= pmag.get_list(siteD,'magic_method_codes')+':'+ 'LP-DC'+str(DC)
PmagSiteRec['magic_method_codes'].strip(":")
if Daverage==0:PmagSiteRec['site_comp_name']= pmag.get_list(siteD,key+'_comp_name')
if plotsites==1:
pmagplotlib.plotSITE(EQ['eqarea'],PmagSiteRec,siteD,key)
pmagplotlib.drawFIGS(EQ)
PmagSites.append(PmagSiteRec)
else:
print 'site information not found in er_sites for site, ',site,' site will be skipped'
for PmagSiteRec in PmagSites: # now decorate each dictionary some more, and calculate VGPs etc. for results table
PmagSiteRec["er_citation_names"]="This study"
PmagSiteRec["er_analyst_mail_names"]=user
PmagSiteRec['magic_software_packages']=version_num
if agefile != "": PmagSiteRec= pmag.get_age(PmagSiteRec,"er_site_name","site_inferred_",AgeNFO,DefaultAge)
PmagSiteRec['pmag_criteria_codes']='ACCEPT'
if 'site_n_lines' in PmagSiteRec.keys() and 'site_n_planes' in PmagSiteRec.keys() and PmagSiteRec['site_n_lines']!="" and PmagSiteRec['site_n_planes']!="":
if int(PmagSiteRec["site_n_planes"])>0:
PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM-LP"
elif int(PmagSiteRec["site_n_lines"])>2:
PmagSiteRec["magic_method_codes"]=PmagSiteRec['magic_method_codes']+":DE-FM"
kill=pmag.grade(PmagSiteRec,accept,'site_dir')
if len(kill)==0:
PmagResRec={} # set up dictionary for the pmag_results table entry
PmagResRec['data_type']='i' # decorate it a bit
PmagResRec['magic_software_packages']=version_num
PmagSiteRec['site_description']='Site direction included in results table'
PmagResRec['pmag_criteria_codes']='ACCEPT'
dec=float(PmagSiteRec["site_dec"])
inc=float(PmagSiteRec["site_inc"])
if 'site_alpha95' in PmagSiteRec.keys() and PmagSiteRec['site_alpha95']!="":
a95=float(PmagSiteRec["site_alpha95"])
else:a95=180.
sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T')[0] # fish out site information (lat/lon, etc.)
lat=float(sitedat['site_lat'])
lon=float(sitedat['site_lon'])
plong,plat,dp,dm=pmag.dia_vgp(dec,inc,a95,lat,lon) # get the VGP for this site
if PmagSiteRec['site_tilt_correction']=='-1':C=' (spec coord) '
if PmagSiteRec['site_tilt_correction']=='0':C=' (geog. coord) '
if PmagSiteRec['site_tilt_correction']=='100':C=' (strat. coord) '
PmagResRec["pmag_result_name"]="VGP Site: "+PmagSiteRec["er_site_name"] # decorate some more
PmagResRec["result_description"]="Site VGP, coord system = "+str(coord)+' component: '+comp
PmagResRec['er_site_names']=PmagSiteRec['er_site_name']
PmagResRec['pmag_criteria_codes']='ACCEPT'
PmagResRec['er_citation_names']='This study'
PmagResRec['er_analyst_mail_names']=user
PmagResRec["er_location_names"]=PmagSiteRec["er_location_name"]
if Daverage==1:
PmagResRec["er_sample_names"]=PmagSiteRec["er_sample_names"]
else:
PmagResRec["er_specimen_names"]=PmagSiteRec["er_specimen_names"]
PmagResRec["tilt_correction"]=PmagSiteRec['site_tilt_correction']
PmagResRec["pole_comp_name"]=PmagSiteRec['site_comp_name']
PmagResRec["average_dec"]=PmagSiteRec["site_dec"]
PmagResRec["average_inc"]=PmagSiteRec["site_inc"]
PmagResRec["average_alpha95"]=PmagSiteRec["site_alpha95"]
PmagResRec["average_n"]=PmagSiteRec["site_n"]
PmagResRec["average_n_lines"]=PmagSiteRec["site_n_lines"]
PmagResRec["average_n_planes"]=PmagSiteRec["site_n_planes"]
PmagResRec["vgp_n"]=PmagSiteRec["site_n"]
PmagResRec["average_k"]=PmagSiteRec["site_k"]
PmagResRec["average_r"]=PmagSiteRec["site_r"]
PmagResRec["average_lat"]='%10.4f ' %(lat)
PmagResRec["average_lon"]='%10.4f ' %(lon)
if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
PmagResRec["vgp_lat"]='%7.1f ' % (plat)
PmagResRec["vgp_lon"]='%7.1f ' % (plong)
PmagResRec["vgp_dp"]='%7.1f ' % (dp)
PmagResRec["vgp_dm"]='%7.1f ' % (dm)
PmagResRec["magic_method_codes"]= PmagSiteRec["magic_method_codes"]
if PmagSiteRec['site_tilt_correction']=='0':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-GEO"
if PmagSiteRec['site_tilt_correction']=='100':PmagSiteRec['magic_method_codes']=PmagSiteRec['magic_method_codes']+":DA-DIR-TILT"
PmagSiteRec['site_polarity']=""
if polarity==1: # assign polarity based on angle of pole lat to spin axis - may want to re-think this sometime
angle=pmag.angle([0,0],[0,(90-plat)])
if angle <= 55.: PmagSiteRec["site_polarity"]='n'
if angle > 55. and angle < 125.: PmagSiteRec["site_polarity"]='t'
if angle >= 125.: PmagSiteRec["site_polarity"]='r'
PmagResults.append(PmagResRec)
if noInt!=1 and nositeints!=1:
for site in sites: # now do intensities for each site
if plotsites==1:print site
if Iaverage==0: key,intlist='specimen',SpecInts # if using specimen level data
if Iaverage==1: key,intlist='sample',PmagSamps # if using sample level data
Ints=pmag.get_dictitem(intlist,'er_site_name',site,'T') # get all the intensities for this site
if len(Ints)>0: # there are some
PmagSiteRec=pmag.average_int(Ints,key,'site') # get average intensity stuff for site table
PmagResRec=pmag.average_int(Ints,key,'average') # get average intensity stuff for results table
if plotsites==1: # if site by site examination requested - print this site out to the screen
for rec in Ints:print rec['er_'+key+'_name'],' %7.1f'%(1e6*float(rec[key+'_int']))
if len(Ints)>1:
print 'Average: ','%7.1f'%(1e6*float(PmagResRec['average_int'])),'N: ',len(Ints)
print 'Sigma: ','%7.1f'%(1e6*float(PmagResRec['average_int_sigma'])),'Sigma %: ',PmagResRec['average_int_sigma_perc']
raw_input('Press any key to continue\n')
er_location_name=Ints[0]["er_location_name"]
PmagSiteRec["er_location_name"]=er_location_name # decorate the records
PmagSiteRec["er_citation_names"]="This study"
PmagResRec["er_location_names"]=er_location_name
PmagResRec["er_citation_names"]="This study"
PmagSiteRec["er_analyst_mail_names"]=user
PmagResRec["er_analyst_mail_names"]=user
PmagResRec["data_type"]='i'
if Iaverage==0:
PmagSiteRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name') # list of all specimens used
PmagResRec['er_specimen_names']= pmag.get_list(Ints,'er_specimen_name')
PmagSiteRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name') # list of all samples used
PmagResRec['er_sample_names']= pmag.get_list(Ints,'er_sample_name')
PmagSiteRec['er_site_name']= site
PmagResRec['er_site_names']= site
PmagSiteRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
PmagResRec['magic_method_codes']= pmag.get_list(Ints,'magic_method_codes')
kill=pmag.grade(PmagSiteRec,accept,'site_int')
if nocrit==1 or len(kill)==0:
b,sig=float(PmagResRec['average_int']),""
if(PmagResRec['average_int_sigma'])!="":sig=float(PmagResRec['average_int_sigma'])
sdir=pmag.get_dictitem(PmagResults,'er_site_names',site,'T') # fish out site direction
if len(sdir)>0 and sdir[-1]['average_inc']!="": # get the VDM for this record using last average inclination (hope it is the right one!)
inc=float(sdir[0]['average_inc']) #
mlat=pmag.magnetic_lat(inc) # get magnetic latitude using dipole formula
PmagResRec["vdm"]='%8.3e '% (pmag.b_vdm(b,mlat)) # get VDM with magnetic latitude
PmagResRec["vdm_n"]=PmagResRec['average_int_n']
if 'average_int_sigma' in PmagResRec.keys() and PmagResRec['average_int_sigma']!="":
vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),mlat)
PmagResRec["vdm_sigma"]='%8.3e '% (vdm_sig)
else:
PmagResRec["vdm_sigma"]=""
mlat="" # define a model latitude
if get_model_lat==1: # use present site latitude
mlats=pmag.get_dictitem(SiteNFO,'er_site_name',site,'T')
if len(mlats)>0: mlat=mlats[0]['site_lat']
elif get_model_lat==2: # use a model latitude from some plate reconstruction model (or something)
mlats=pmag.get_dictitem(ModelLats,'er_site_name',site,'T')
if len(mlats)>0: PmagResRec['model_lat']=mlats[0]['site_model_lat']
mlat=PmagResRec['model_lat']
if mlat!="":
PmagResRec["vadm"]='%8.3e '% (pmag.b_vdm(b,float(mlat))) # get the VADM using the desired latitude
if sig!="":
vdm_sig=pmag.b_vdm(float(PmagResRec['average_int_sigma']),float(mlat))
PmagResRec["vadm_sigma"]='%8.3e '% (vdm_sig)
PmagResRec["vadm_n"]=PmagResRec['average_int_n']
else:
PmagResRec["vadm_sigma"]=""
sitedat=pmag.get_dictitem(SiteNFO,'er_site_name',PmagSiteRec['er_site_name'],'T') # fish out site information (lat/lon, etc.)
if len(sitedat)>0:
sitedat=sitedat[0]
PmagResRec['average_lat']=sitedat['site_lat']
PmagResRec['average_lon']=sitedat['site_lon']
else:
PmagResRec['average_lon']='UNKNOWN'
PmagResRec['average_lon']='UNKNOWN'
PmagResRec['magic_software_packages']=version_num
PmagResRec["pmag_result_name"]="V[A]DM: Site "+site
PmagResRec["result_description"]="V[A]DM of site"
PmagResRec["pmag_criteria_codes"]="ACCEPT"
if agefile != "": PmagResRec= pmag.get_age(PmagResRec,"er_site_names","average_",AgeNFO,DefaultAge)
site_height=pmag.get_dictitem(height_nfo,'er_site_name',site,'T')
if len(site_height)>0:PmagResRec["average_height"]=site_height[0]['site_height']
PmagSites.append(PmagSiteRec)
PmagResults.append(PmagResRec)
if len(PmagSites)>0:
Tmp,keylist=pmag.fillkeys(PmagSites)
pmag.magic_write(siteout,Tmp,'pmag_sites')
print ' sites written to ',siteout
else: print "No Site level table"
if len(PmagResults)>0:
TmpRes,keylist=pmag.fillkeys(PmagResults)
pmag.magic_write(resout,TmpRes,'pmag_results')
print ' results written to ',resout
else: print "No Results level table"
