def spitout(data):
pole_lat, pole_lon = pmag.bc02(data)
dec, inc = pmag.vgp_di(pole_lat, pole_lon, data[1], data[2])
paleo_lat = pmag.magnetic_lat(inc)
return ' %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f\n' % (data[3], paleo_lat, dec,
inc, pole_lat, pole_lon)
def spitout(data):
pole_lat,pole_lon=pmag.bc02(data)
dec,inc=pmag.vgp_di(pole_lat,pole_lon,data[1],data[2])
paleo_lat=pmag.magnetic_lat(inc)
return ' %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f\n' %(data[3],paleo_lat,dec,inc,pole_lat,pole_lon)
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
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")
