def main():
"""
NAME
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify measurements format file, default "measurements.txt"
-T IND, specify temperature step to plot -- NOT IMPLEMENTED
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
"""
if "-h" in sys.argv:
print(main.__doc__)
return
infile = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
infile = pmag.resolve_file_name(infile, dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
save_plots = False
interactive = True
if "-sav" in sys.argv:
interactive = False
save_plots = True
experiments = pmag.get_named_arg("-e", "")
ipmag.chi_magic(infile, dir_path, experiments, fmt, save_plots,
interactive)
def main():
"""
NAME
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify measurements format file, default "measurements.txt"
-T IND, specify temperature step to plot -- NOT IMPLEMENTED
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
"""
if "-h" in sys.argv:
print(main.__doc__)
return
infile = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
infile = pmag.resolve_file_name(infile, dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
save_plots = False
interactive = True
if "-sav" in sys.argv:
interactive = False
save_plots = True
experiments = pmag.get_named_arg("-e", "")
ipmag.chi_magic(infile, dir_path, experiments, fmt, save_plots, interactive)
def test_aniso_depthplot_with_no_files(self):
program_ran, error_message = ipmag.ani_depthplot2()
expected_file = pmag.resolve_file_name('rmag_anisotropy.txt')
self.assertFalse(program_ran)
self.assertEqual(
error_message,
"Could not find rmag_anisotropy type file: {}.\nPlease provide a valid file path and try again"
.format(expected_file))
def main():
"""
NAME
dmag_magic.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot,
default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols,
(for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
# initialize variables from command line + defaults
dir_path = pmag.get_named_arg("-WD", default_val=".")
input_dir_path = pmag.get_named_arg('-ID', '')
if not input_dir_path:
input_dir_path = dir_path
in_file = pmag.get_named_arg("-f", default_val="measurements.txt")
in_file = pmag.resolve_file_name(in_file, input_dir_path)
if "-ID" not in sys.argv:
input_dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", default_val="loc")
LT = pmag.get_named_arg("-LT", "AF")
no_norm = pmag.get_flag_arg_from_sys("-N")
norm = False if no_norm else True
interactive = True
save_plots = pmag.get_flag_arg_from_sys("-sav")
if save_plots:
interactive = False
fmt = pmag.get_named_arg("-fmt", "svg")
XLP = pmag.get_named_arg("-XLP", "")
spec_file = pmag.get_named_arg("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg("-fsi", default_val="sites.txt")
loc_file = pmag.get_named_arg("-flo", default_val="locations.txt")
ipmag.dmag_magic(in_file, dir_path, input_dir_path, spec_file, samp_file,
site_file, loc_file, plot_by, LT, norm, XLP,
save_plots, fmt, interactive, n_plots="all")
def main():
"""
NAME
dmag_magic.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot,
default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols,
(for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
# initialize variables from command line + defaults
dir_path = pmag.get_named_arg("-WD", default_val=".")
input_dir_path = pmag.get_named_arg('-ID', '')
if not input_dir_path:
input_dir_path = dir_path
in_file = pmag.get_named_arg("-f", default_val="measurements.txt")
in_file = pmag.resolve_file_name(in_file, input_dir_path)
if "-ID" not in sys.argv:
input_dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", default_val="loc")
LT = pmag.get_named_arg("-LT", "AF")
no_norm = pmag.get_flag_arg_from_sys("-N")
norm = False if no_norm else True
interactive = True
save_plots = pmag.get_flag_arg_from_sys("-sav")
if save_plots:
interactive = False
fmt = pmag.get_named_arg("-fmt", "svg")
XLP = pmag.get_named_arg("-XLP", "")
spec_file = pmag.get_named_arg("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg("-fsi", default_val="sites.txt")
loc_file = pmag.get_named_arg("-flo", default_val="locations.txt")
ipmag.dmag_magic(in_file, dir_path, input_dir_path, spec_file, samp_file,
site_file, loc_file, plot_by, LT, norm, XLP,
save_plots, fmt, interactive)
def main():
"""
NAME
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify measurements format file, default "measurements.txt"
-T IND, specify temperature step to plot
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
"""
if "-h" in sys.argv:
print(main.__doc__)
return
infile = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
infile = pmag.resolve_file_name(infile, dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
show_plots = True
if "-sav" in sys.argv:
show_plots = False
experiments = pmag.get_named_arg("-e", "")
# read in data from data model 3 example file
chi_data_all = pd.read_csv(infile, sep='\t', header=1)
if not experiments:
try:
experiments = chi_data_all.experiment.unique()
except Exception as ex:
print(ex)
experiments = ["all"]
else:
experiments = [experiments]
plotnum = 0
figs = {}
fnames = {}
for exp in experiments:
if exp == "all":
chi_data = chi_data_all
chi_data = chi_data_all[chi_data_all.experiment == exp]
if len(chi_data) <= 1:
print('Not enough data to plot {}'.format(exp))
continue
plotnum += 1
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_temperature.{}'.format(fmt)
# get arrays of available temps, frequencies and fields
Ts = np.sort(chi_data.meas_temp.unique())
Fs = np.sort(chi_data.meas_freq.unique())
Bs = np.sort(chi_data.meas_field_ac.unique())
# plot chi versus temperature at constant field
b = Bs.max()
for num, f in enumerate(Fs):
this_f = chi_data[chi_data.meas_freq == f]
this_f = this_f[this_f.meas_field_ac == b]
plt.plot(this_f.meas_temp, 1e6*this_f.susc_chi_volume,
label='%i' % (f)+' Hz')
plt.legend()
plt.xlabel('Temperature (K)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = '+'%7.2e' % (b) + ' T')
plotnum += 1
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_frequency.{}'.format(fmt)
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
## plot chi versus frequency at constant B
b = Bs.max()
t = Ts.min()
this_t = chi_data[chi_data.meas_temp == t]
this_t = this_t[this_t.meas_field_ac == b]
plt.semilogx(this_t.meas_freq, 1e6 *
this_t.susc_chi_volume, label='%i' % (t)+' K')
plt.legend()
plt.xlabel('Frequency (Hz)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = '+'%7.2e' % (b) + ' T')
if show_plots:
pmagplotlib.draw_figs(figs)
ans = input(
"enter s[a]ve to save files, [return] to quit ")
if ans == 'a':
pmagplotlib.save_plots(figs, fnames)
sys.exit()
else:
sys.exit()
else:
pmagplotlib.save_plots(figs, fnames)
def test_aniso_depthplot_with_no_files(self):
program_ran, error_message = ipmag.aniso_depthplot()
expected_file = pmag.resolve_file_name('rmag_anisotropy.txt')
self.assertFalse(program_ran)
self.assertEqual(error_message, "Could not find rmag_anisotropy type file: {}.\nPlease provide a valid file path and try again".format(expected_file))
def main():
"""
NAME
lowrie_magic.py
DESCRIPTION
plots intensity decay curves for Lowrie experiments
SYNTAX
lowrie_magic.py -h [command line options]
INPUT
takes measurements formatted input files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is magic_measurements.txt
-N do not normalize by maximum magnetization
-fmt [svg, pdf, eps, png] specify fmt, default is svg
-sav saves plots and quits
-DM [2, 3] MagIC data model number
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if len(sys.argv) <= 1:
print(main.__doc__)
print('you must supply a file name')
sys.exit()
FIG = {} # plot dictionary
FIG['lowrie'] = 1 # demag is figure 1
pmagplotlib.plot_init(FIG['lowrie'], 6, 6)
norm = 1 # default is to normalize by maximum axis
in_file = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
in_file = pmag.resolve_file_name(in_file, dir_path)
data_model = pmag.get_named_arg("-DM", 3)
data_model = int(float(data_model))
fmt = pmag.get_named_arg("-fmt", "svg")
if '-N' in sys.argv:
norm = 0 # don't normalize
if '-sav' in sys.argv:
plot = 1 # silently save and quit
else:
plot = 0 # generate plots
print(in_file)
# read in data
PmagRecs, file_type = pmag.magic_read(in_file)
if data_model == 2 and file_type != "magic_measurements":
print('bad input file', file_type)
sys.exit()
if data_model == 3 and file_type != "measurements":
print('bad input file', file_type)
sys.exit()
if data_model == 2:
meth_code_col = 'magic_method_codes'
spec_col = 'er_specimen_name'
dec_col = "measurement_dec"
inc_col = 'measurement_inc'
moment_col = 'measurement_magn_moment'
temp_col = 'treatment_temp'
else:
meth_code_col = 'method_codes'
spec_col = 'specimen'
dec_col = 'dir_dec'
inc_col = 'dir_inc'
moment_col = 'magn_moment'
temp_col = "treat_temp"
PmagRecs = pmag.get_dictitem(PmagRecs, meth_code_col, 'LP-IRM-3D',
'has') # get all 3D IRM records
if len(PmagRecs) == 0:
print('no records found with the method code LP-IRM-3D')
sys.exit()
specs = pmag.get_dictkey(PmagRecs, spec_col, '')
sids = []
for spec in specs:
if spec not in sids:
sids.append(spec) # get list of unique specimen names
for spc in sids: # step through the specimen names
print(spc)
specdata = pmag.get_dictitem(PmagRecs, spec_col, spc,
'T') # get all this one's data
DIMs, Temps = [], []
for dat in specdata: # step through the data
DIMs.append([
float(dat[dec_col]),
float(dat[inc_col]),
float(dat[moment_col])
])
Temps.append(float(dat[temp_col]) - 273.)
carts = pmag.dir2cart(DIMs).transpose()
if norm == 1: # want to normalize
nrm = (DIMs[0][2]) # normalize by NRM
ylab = "M/M_o"
else:
nrm = 1. # don't normalize
ylab = "Magnetic moment (Am^2)"
xlab = "Temperature (C)"
pmagplotlib.plot_xy(FIG['lowrie'],
Temps,
abs(carts[0]) / nrm,
sym='r-')
pmagplotlib.plot_xy(FIG['lowrie'],
Temps,
abs(carts[0]) / nrm,
sym='ro') # X direction
pmagplotlib.plot_xy(FIG['lowrie'],
Temps,
abs(carts[1]) / nrm,
sym='c-')
pmagplotlib.plot_xy(FIG['lowrie'],
Temps,
abs(carts[1]) / nrm,
sym='cs') # Y direction
pmagplotlib.plot_xy(FIG['lowrie'],
Temps,
abs(carts[2]) / nrm,
sym='k-')
pmagplotlib.plot_xy(FIG['lowrie'],
Temps,
abs(carts[2]) / nrm,
sym='k^',
title=spc,
xlab=xlab,
ylab=ylab) # Z direction
files = {'lowrie': 'lowrie:_' + spc + '_.' + fmt}
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input('S[a]ve figure? [q]uit, <return> to continue ')
if ans == 'a':
pmagplotlib.save_plots(FIG, files)
elif ans == 'q':
sys.exit()
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['lowrie'])
def main():
"""
NAME
mk_redo.py
DESCRIPTION
Makes thellier_redo and zeq_redo files from existing pmag_specimens format file
SYNTAX
mk_redo.py [-h] [command line options]
INPUT
takes specimens.txt formatted input file
OPTIONS
-h: prints help message and quits
-f FILE: specify input file, default is 'specimens.txt'
-F REDO: specify output file suffix, default is redo so that
output filenames are 'thellier_redo' for thellier data and 'zeq_redo' for direction only data
OUTPUT
makes a thellier_redo or a zeq_redo format file
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
zfile, tfile = 'zeq_redo', 'thellier_redo'
zredo, tredo = "", ""
dir_path = pmag.get_named_arg('-WD', '.')
inspec = pmag.get_named_arg('-f', 'specimens.txt')
if '-F' in sys.argv:
ind = sys.argv.index('-F')
redo = sys.argv[ind + 1]
tfile = redo
zfile = redo
inspec = pmag.resolve_file_name(inspec, dir_path)
zfile = pmag.resolve_file_name(zfile, dir_path)
tfile = pmag.resolve_file_name(tfile, dir_path)
#
# read in data
#
specs = []
prior_spec_data, file_type = pmag.magic_read(inspec)
if file_type != 'specimens':
print(file_type, " this is not a valid pmag_specimens file")
sys.exit()
outstrings = []
for spec in prior_spec_data:
tmp = spec["method_codes"].split(":")
meths = []
for meth in tmp:
methods = meth.strip().split('-')
for m in methods:
if m not in meths:
meths.append(m)
if 'DIR' in meths: # DE-BFL, DE-BFP or DE-FM
specs.append(spec['specimen'])
if 'dir_comp' in list(spec.keys()) and spec['dir_comp'] != "" and spec['dir_comp'] != " ":
comp_name = spec['dir_comp']
else:
comp_name = string.ascii_uppercase[specs.count(
spec['specimen']) - 1]
calculation_type = "DE-BFL" # assume default calculation type is best-fit line
if "BFP" in meths:
calculation_type = 'DE-BFP'
elif "FM" in meths:
calculation_type = 'DE-FM'
if zredo == "":
zredo = open(zfile, "w")
outstring = '%s %s %s %s %s \n' % (
spec["specimen"], calculation_type, spec["meas_step_min"], spec["meas_step_max"], comp_name)
if outstring not in outstrings:
zredo.write(outstring)
outstrings.append(outstring) # only writes unique interpretions
elif "PI" in meths and "TRM" in meths: # thellier record
if tredo == "":
tredo = open(tfile, "w")
outstring = '%s %i %i \n' % (spec["specimen"], float(
spec["meas_step_min"]), float(spec["meas_step_max"]))
if outstring not in outstrings:
tredo.write(outstring)
outstrings.append(outstring) # only writes unique interpretions
print('Redo files saved to: ', zfile, tfile)
def plot(in_file="measurements.txt", dir_path=".", input_dir_path="",
spec_file="specimens.txt", samp_file="samples.txt",
site_file="sites.txt", loc_file="locations.txt",
plot_by="loc", LT="AF", norm=True, XLP="",
save_plots=True, fmt="svg"):
"""
plots intensity decay curves for demagnetization experiments
Parameters
----------
in_file : str, default "measurements.txt"
dir_path : str
output directory, default "."
input_dir_path : str
input file directory (if different from dir_path), default ""
spec_file : str
input specimen file name, default "specimens.txt"
samp_file: str
input sample file name, default "samples.txt"
site_file : str
input site file name, default "sites.txt"
loc_file : str
input location file name, default "locations.txt"
plot_by : str
[spc, sam, sit, loc] (specimen, sample, site, location), default "loc"
LT : str
lab treatment [T, AF, M], default AF
norm : bool
normalize by NRM magnetization, default True
XLP : str
exclude specific lab protocols, (for example, method codes like LP-PI)
default ""
save_plots : bool
plot and save non-interactively, default True
fmt : str
["png", "svg", "pdf", "jpg"], default "svg"
Returns
---------
type - Tuple : (True or False indicating if conversion was sucessful, file name(s) written)
"""
dir_path = os.path.realpath(dir_path)
if not input_dir_path:
input_dir_path = dir_path
input_dir_path = os.path.realpath(input_dir_path)
# format plot_key
name_dict = {'loc': 'location', 'sit': 'site',
'sam': 'sample', 'spc': 'specimen'}
if plot_by not in name_dict.values():
try:
plot_key = name_dict[plot_by]
except KeyError:
print('Unrecognized plot_by {}, falling back to plot by location'.format(plot_by))
plot_key = "loc"
else:
plot_key = plot_by
# figure out what kind of experiment
LT = "LT-" + LT + "-Z"
print('LT', LT)
if LT == "LT-T-Z":
units, dmag_key = 'K', 'treat_temp'
elif LT == "LT-AF-Z":
units, dmag_key = 'T', 'treat_ac_field'
elif LT == 'LT-M-Z':
units, dmag_key = 'J', 'treat_mw_energy'
else:
units = 'U'
# init
FIG = {} # plot dictionary
FIG['demag'] = 1 # demag is figure 1
# create contribution and add required headers
fnames = {"specimens": spec_file, "samples": samp_file,
'sites': site_file, 'locations': loc_file}
if not os.path.exists(pmag.resolve_file_name(in_file, input_dir_path)):
print('-E- Could not find {}'.format(in_file))
return False, []
contribution = cb.Contribution(input_dir_path, single_file=in_file,
custom_filenames=fnames)
file_type = list(contribution.tables.keys())[0]
print(len(contribution.tables['measurements'].df), ' records read from ', in_file)
# add plot_key into measurements table
if plot_key not in contribution.tables['measurements'].df.columns:
#contribution.propagate_name_down(plot_key, 'measurements')
contribution.propagate_location_to_measurements()
data_container = contribution.tables[file_type]
# pare down to only records with useful data
# grab records that have the requested code
data_slice = data_container.get_records_for_code(LT)
# and don't have the offending code
data = data_container.get_records_for_code(XLP, incl=False, use_slice=True,
sli=data_slice, strict_match=False)
# make sure quality is in the dataframe
if 'quality' not in data.columns:
data['quality'] = 'g'
# get intensity key and make sure intensity data is not blank
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
# get rid of any entirely blank intensity columns
for col_name in IntMeths:
if not data[col_name].any():
data.drop(col_name, axis=1, inplace=True)
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
if len(IntMeths) == 0:
print('-E- No intensity headers found')
return False, []
int_key = IntMeths[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
data = data[data[int_key].notnull()]
# make list of individual plots
# by default, will be by location_name
plotlist = data[plot_key].unique()
plotlist.sort()
pmagplotlib.plot_init(FIG['demag'], 5, 5)
last_plot = False
# iterate through and plot the data
for plt in plotlist:
if plt == plotlist[-1]:
last_plot = True
plot_data = data[data[plot_key] == plt].copy()
if not save_plots:
print(plt, 'plotting by: ', plot_key)
if len(plot_data) > 2:
title = plt
spcs = []
spcs = plot_data['specimen'].unique()
for spc in spcs:
INTblock = []
spec_data = plot_data[plot_data['specimen'] == spc]
for ind, rec in spec_data.iterrows():
INTblock.append([float(rec[dmag_key]), 0, 0, float(rec[int_key]), 1, rec['quality']])
if len(INTblock) > 2:
pmagplotlib.plot_mag(FIG['demag'], INTblock,
title, 0, units, norm)
if save_plots:
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer:
files[key] = title + '_' + LT + '.' + fmt
incl_dir = False
else: # if not server, include directory in output path
files[key] = os.path.join(dir_path, title + '_' + LT + '.' + fmt)
incl_dir = True
pmagplotlib.save_plots(FIG, files, incl_directory=incl_dir)
else:
pmagplotlib.draw_figs(FIG)
prompt = " S[a]ve to save plot, [q]uit, Return to continue: "
ans = input(prompt)
if ans == 'q':
return True, []
if ans == "a":
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer:
files[key] = title + '_' + LT + '.' + fmt
incl_dir = False
else: # if not server, include directory in output path
files[key] = os.path.join(dir_path, title + '_' + LT + '.' + fmt)
incl_dir = True
pmagplotlib.save_plots(FIG, files, incl_directory=incl_dir)
pmagplotlib.clearFIG(FIG['demag'])
if last_plot:
return True, []
def convert(**kwargs):
# initialize some stuff
methcode="LP-NO"
phi,theta,peakfield,labfield=0,0,0,0
pTRM,MD=0,0
dec=[315,225,180,135,45,90,270,270,270,90,180,180,0,0,0]
inc=[0,0,0,0,0,-45,-45,0,45,45,45,-45,-90,-45,45]
tdec=[0,90,0,180,270,0,0,90,0]
tinc=[0,0,90,0,0,-90,0,0,90]
missing=1
demag="N"
citations='This study'
fmt='old'
Samps=[]
trm=0
irm=0
#get args
user = kwargs.get('user', '')
dir_path = kwargs.get('dir_path', '.')
output_dir_path = dir_path
meas_file = kwargs.get('meas_file', 'measurements.txt') # measurement outfile
meas_file = pmag.resolve_file_name(meas_file, output_dir_path)
spec_file = kwargs.get('spec_file', 'specimens.txt') # specimen outfile
spec_file = pmag.resolve_file_name(spec_file, output_dir_path)
samp_file = kwargs.get('samp_file', 'samples.txt') # sample outfile
samp_file = pmag.resolve_file_name(samp_file, output_dir_path)
site_file = kwargs.get('site_file', 'sites.txt') # site outfile
site_file = pmag.resolve_file_name(site_file, output_dir_path)
loc_file = kwargs.get('loc_file', 'locations.txt') # location outfile
loc_file = pmag.resolve_file_name(loc_file, output_dir_path)
mag_file = kwargs.get('mag_file', '')
mag_file = pmag.resolve_file_name(mag_file, dir_path)
labfield = kwargs.get('labfield', '')
if labfield:
labfield = float(labfield) *1e-6
else:
labfield = 0
phi = kwargs.get('phi', 0)
if phi:
phi = float(phi)
else:
phi = 0
theta = kwargs.get('theta', 0)
if theta:
theta=float(theta)
else:
theta = 0
peakfield = kwargs.get('peakfield', 0)
if peakfield:
peakfield=float(peakfield) *1e-3
else:
peakfield = 0
specnum = kwargs.get('specnum', 0)
samp_con = kwargs.get('samp_con', '1')
location = kwargs.get('location', 'unknown')
samp_infile = kwargs.get('samp_infile', '')
syn = kwargs.get('syn', 0)
institution = kwargs.get('institution', '')
syntype = kwargs.get('syntype', '')
inst = kwargs.get('inst', '')
noave = kwargs.get('noave', 0)
codelist = kwargs.get('codelist', '')
coil = kwargs.get('coil', '')
cooling_rates = kwargs.get('cooling_rates', '')
lat = kwargs.get('lat', '')
lon = kwargs.get('lon', '')
timezone = kwargs.get('timezone', 'UTC')
# make sure all initial values are correctly set up (whether they come from the command line or a GUI)
if samp_infile:
Samps, file_type = pmag.magic_read(samp_infile)
if coil:
coil = str(coil)
methcode="LP-IRM"
irmunits = "V"
if coil not in ["1","2","3"]:
print(__doc__)
print('not a valid coil specification')
return False, '{} is not a valid coil specification'.format(coil)
if mag_file:
lines = pmag.open_file(mag_file)
if not lines:
print("you must provide a valid mag_file")
return False, "you must provide a valid mag_file"
if not mag_file:
print(__doc__)
print("mag_file field is required option")
return False, "mag_file field is required option"
if specnum!=0:
specnum=-specnum
if "4" == samp_con[0]:
if "-" not in samp_con:
print("naming convention option [4] must be in form 4-Z where Z is an integer")
print('---------------')
return False, "naming convention option [4] must be in form 4-Z where Z is an integer"
else:
Z=samp_con.split("-")[1]
samp_con="4"
if "7" == samp_con[0]:
if "-" not in samp_con:
print("option [7] must be in form 7-Z where Z is an integer")
return False, "option [7] must be in form 7-Z where Z is an integer"
else:
Z=samp_con.split("-")[1]
samp_con="7"
else: Z = 0
if codelist:
codes=codelist.split(':')
if "AF" in codes:
demag='AF'
if'-dc' not in sys.argv: methcode="LT-AF-Z"
if'-dc' in sys.argv: methcode="LT-AF-I"
if "T" in codes:
demag="T"
if '-dc' not in sys.argv: methcode="LT-T-Z"
if '-dc' in sys.argv: methcode="LT-T-I"
if "I" in codes:
methcode="LP-IRM"
irmunits="mT"
if "I3d" in codes:
methcode="LT-T-Z:LP-IRM-3D"
if "S" in codes:
demag="S"
methcode="LP-PI-TRM:LP-PI-ALT-AFARM"
trm_labfield=labfield
ans=input("DC lab field for ARM step: [50uT] ")
if ans=="":
arm_labfield=50e-6
else:
arm_labfield=float(ans)*1e-6
ans=input("temperature for total trm step: [600 C] ")
if ans=="":
trm_peakT=600+273 # convert to kelvin
else:
trm_peakT=float(ans)+273 # convert to kelvin
if "G" in codes: methcode="LT-AF-G"
if "D" in codes: methcode="LT-AF-D"
if "TRM" in codes:
demag="T"
trm=1
if "CR" in codes:
demag="T"
cooling_rate_experiment=1
cooling_rates_list=cooling_rates.split(',') # command_line does not exist in this code
#if command_line:
# ind=sys.argv.index("CR")
# cooling_rates=sys.argv[ind+1]
# cooling_rates_list=cooling_rates.split(',')
#else:
# cooling_rates_list=str(cooling_rates).split(',')
if demag=="T" and "ANI" in codes:
methcode="LP-AN-TRM"
if demag=="T" and "CR" in codes:
methcode="LP-CR-TRM"
if demag=="AF" and "ANI" in codes:
methcode="LP-AN-ARM"
if labfield==0: labfield=50e-6
if peakfield==0: peakfield=.180
MeasRecs,SpecRecs,SampRecs,SiteRecs,LocRecs=[],[],[],[],[]
version_num=pmag.get_version()
##################################
for line in lines:
instcode=""
if len(line)>2:
MeasRec,SpecRec,SampRec,SiteRec,LocRec={},{},{},{},{}
MeasRec['software_packages']=version_num
MeasRec["description"]=""
MeasRec["treat_temp"]='%8.3e' % (273) # room temp in kelvin
MeasRec["meas_temp"]='%8.3e' % (273) # room temp in kelvin
MeasRec["treat_ac_field"]='0'
MeasRec["treat_dc_field"]='0'
MeasRec["treat_dc_field_phi"]='0'
MeasRec["treat_dc_field_theta"]='0'
meas_type="LT-NO"
rec=line.split()
try: float(rec[0]); print("No specimen name for line #%d in the measurement file"%lines.index(line)); continue
except ValueError: pass
if rec[1]==".00":rec[1]="0.00"
treat=rec[1].split('.')
if methcode=="LP-IRM":
if irmunits=='mT':
labfield=float(treat[0])*1e-3
else:
labfield=pmag.getfield(irmunits,coil,treat[0])
if rec[1][0]!="-":
phi,theta=0.,90.
else:
phi,theta=0.,-90.
meas_type="LT-IRM"
MeasRec["treat_dc_field"]='%8.3e'%(labfield)
MeasRec["treat_dc_field_phi"]='%7.1f'%(phi)
MeasRec["treat_dc_field_theta"]='%7.1f'%(theta)
if len(rec)>6:
code1=rec[6].split(';') # break e.g., 10/15/02;7:45 indo date and time
if len(code1)==2: # old format with AM/PM
missing=0
code2=code1[0].split('/') # break date into mon/day/year
code3=rec[7].split(';') # break e.g., AM;C34;200 into time;instr/axes/measuring pos;number of measurements
yy=int(code2[2])
if yy <90:
yyyy=str(2000+yy)
else: yyyy=str(1900+yy)
mm=int(code2[0])
if mm<10:
mm="0"+str(mm)
else: mm=str(mm)
dd=int(code2[1])
if dd<10:
dd="0"+str(dd)
else: dd=str(dd)
time=code1[1].split(':')
hh=int(time[0])
if code3[0]=="PM":hh=hh+12
if hh<10:
hh="0"+str(hh)
else: hh=str(hh)
min=int(time[1])
if min<10:
min= "0"+str(min)
else: min=str(min)
dt=yyyy+":"+mm+":"+dd+":"+hh+":"+min+":00"
local = pytz.timezone(timezone)
naive = datetime.datetime.strptime(dt, "%Y:%m:%d:%H:%M:%S")
local_dt = local.localize(naive, is_dst=None)
utc_dt = local_dt.astimezone(pytz.utc)
MeasRec["timestamp"]=utc_dt.strftime("%Y-%m-%dT%H:%M:%S")+"Z"
if inst=="":
if code3[1][0]=='C':instcode='SIO-bubba'
if code3[1][0]=='G':instcode='SIO-flo'
else:
instcode=''
MeasRec["meas_n_orient"]=code3[1][2]
elif len(code1)>2: # newest format (cryo7 or later)
if "LP-AN-ARM" not in methcode:labfield=0
fmt='new'
date=code1[0].split('/') # break date into mon/day/year
yy=int(date[2])
if yy <90:
yyyy=str(2000+yy)
else: yyyy=str(1900+yy)
mm=int(date[0])
if mm<10:
mm="0"+str(mm)
else: mm=str(mm)
dd=int(date[1])
if dd<10:
dd="0"+str(dd)
else: dd=str(dd)
time=code1[1].split(':')
hh=int(time[0])
if hh<10:
hh="0"+str(hh)
else: hh=str(hh)
min=int(time[1])
if min<10:
min= "0"+str(min)
else:
min=str(min)
dt=yyyy+":"+mm+":"+dd+":"+hh+":"+min+":00"
local = pytz.timezone(timezone)
naive = datetime.datetime.strptime(dt, "%Y:%m:%d:%H:%M:%S")
local_dt = local.localize(naive, is_dst=None)
utc_dt = local_dt.astimezone(pytz.utc)
MeasRec["timestamp"]=utc_dt.strftime("%Y-%m-%dT%H:%M:%S")+"Z"
if inst=="":
if code1[6][0]=='C':
instcode='SIO-bubba'
if code1[6][0]=='G':
instcode='SIO-flo'
else:
instcode=''
if len(code1)>1:
MeasRec["meas_n_orient"]=code1[6][2]
else:
MeasRec["meas_n_orient"]=code1[7] # takes care of awkward format with bubba and flo being different
if user=="":user=code1[5]
if code1[2][-1]=='C':
demag="T"
if code1[4]=='microT' and float(code1[3])!=0. and "LP-AN-ARM" not in methcode: labfield=float(code1[3])*1e-6
if code1[2]=='mT' and methcode!="LP-IRM":
demag="AF"
if code1[4]=='microT' and float(code1[3])!=0.: labfield=float(code1[3])*1e-6
if code1[4]=='microT' and labfield!=0. and meas_type!="LT-IRM":
phi,theta=0.,-90.
if demag=="T": meas_type="LT-T-I"
if demag=="AF": meas_type="LT-AF-I"
MeasRec["treat_dc_field"]='%8.3e'%(labfield)
MeasRec["treat_dc_field_phi"]='%7.1f'%(phi)
MeasRec["treat_dc_field_theta"]='%7.1f'%(theta)
if code1[4]=='' or labfield==0. and meas_type!="LT-IRM":
if demag=='T':meas_type="LT-T-Z"
if demag=="AF":meas_type="LT-AF-Z"
MeasRec["treat_dc_field"]='0'
if syn==0:
specimen=rec[0]
MeasRec["specimen"]=specimen
if specnum!=0:
sample=rec[0][:specnum]
else:
sample=rec[0]
if samp_infile and Samps: # if samp_infile was provided AND yielded sample data
samp=pmag.get_dictitem(Samps,'sample',sample,'T')
if len(samp)>0:
location=samp[0]["location"]
site=samp[0]["site"]
else:
location=''
site=''
else:
site=pmag.parse_site(sample,samp_con,Z)
if location!='' and location not in [x['location'] if 'location' in list(x.keys()) else '' for x in LocRecs]:
LocRec['location'] = location
LocRec['lat_n'] = lat
LocRec['lat_s'] = lat
LocRec['lon_e'] = lon
LocRec['lon_w'] = lon
LocRecs.append(LocRec)
if site!='' and site not in [x['site'] if 'site' in list(x.keys()) else '' for x in SiteRecs]:
SiteRec['location'] = location
SiteRec['site'] = site
SiteRec['lat'] = lat
SiteRec['lon'] = lon
SiteRecs.append(SiteRec)
if sample!='' and sample not in [x['sample'] if 'sample' in list(x.keys()) else '' for x in SampRecs]:
SampRec['site'] = site
SampRec['sample'] = sample
SampRecs.append(SampRec)
if specimen!='' and specimen not in [x['specimen'] if 'specimen' in list(x.keys()) else '' for x in SpecRecs]:
SpecRec["specimen"]=specimen
SpecRec['sample'] = sample
SpecRecs.append(SpecRec)
else:
specimen=rec[0]
MeasRec["specimen"]=specimen
if specnum!=0:
sample=rec[0][:specnum]
else:
sample=rec[0]
site=pmag.parse_site(sample,samp_con,Z)
if location!='' and location not in [x['location'] if 'location' in list(x.keys()) else '' for x in LocRecs]:
LocRec['location'] = location
LocRec['lat_n'] = lat
LocRec['lat_s'] = lat
LocRec['lon_e'] = lon
LocRec['lon_w'] = lon
LocRecs.append(LocRec)
if site!='' and site not in [x['site'] if 'site' in list(x.keys()) else '' for x in SiteRecs]:
SiteRec['location'] = location
SiteRec['site'] = site
SiteRec['lat'] = lat
SiteRec['lon'] = lon
SiteRecs.append(SiteRec)
if sample!='' and sample not in [x['sample'] if 'sample' in list(x.keys()) else '' for x in SampRecs]:
SampRec['site'] = site
SampRec['sample'] = sample
SampRecs.append(SampRec)
if specimen!='' and specimen not in [x['specimen'] if 'specimen' in list(x.keys()) else '' for x in SpecRecs]:
SpecRec["specimen"]=specimen
SpecRec['sample'] = sample
SpecRecs.append(SpecRec)
SampRec["institution"]=institution
SampRec["material_type"]=syntype
#MeasRec["sample"]=sample
if float(rec[1])==0:
pass
elif demag=="AF":
if methcode != "LP-AN-ARM":
MeasRec["treat_ac_field"]='%8.3e' %(float(rec[1])*1e-3) # peak field in tesla
if meas_type=="LT-AF-Z": MeasRec["treat_dc_field"]='0'
else: # AARM experiment
if treat[1][0]=='0':
meas_type="LT-AF-Z:LP-AN-ARM:"
MeasRec["treat_ac_field"]='%8.3e' %(peakfield) # peak field in tesla
MeasRec["treat_dc_field"]='%8.3e'%(0)
if labfield!=0 and methcode!="LP-AN-ARM": print("Warning - inconsistency in mag file with lab field - overriding file with 0")
else:
meas_type="LT-AF-I:LP-AN-ARM"
ipos=int(treat[0])-1
MeasRec["treat_dc_field_phi"]='%7.1f' %(dec[ipos])
MeasRec["treat_dc_field_theta"]='%7.1f'% (inc[ipos])
MeasRec["treat_dc_field"]='%8.3e'%(labfield)
MeasRec["treat_ac_field"]='%8.3e' %(peakfield) # peak field in tesla
elif demag=="T" and methcode == "LP-AN-TRM":
MeasRec["treat_temp"]='%8.3e' % (float(treat[0])+273.) # temp in kelvin
if treat[1][0]=='0':
meas_type="LT-T-Z:LP-AN-TRM"
MeasRec["treat_dc_field"]='%8.3e'%(0)
MeasRec["treat_dc_field_phi"]='0'
MeasRec["treat_dc_field_theta"]='0'
else:
MeasRec["treat_dc_field"]='%8.3e'%(labfield)
if treat[1][0]=='7': # alteration check as final measurement
meas_type="LT-PTRM-I:LP-AN-TRM"
else:
meas_type="LT-T-I:LP-AN-TRM"
# find the direction of the lab field in two ways:
# (1) using the treatment coding (XX.1=+x, XX.2=+y, XX.3=+z, XX.4=-x, XX.5=-y, XX.6=-z)
ipos_code=int(treat[1][0])-1
# (2) using the magnetization
DEC=float(rec[4])
INC=float(rec[5])
if INC < 45 and INC > -45:
if DEC>315 or DEC<45: ipos_guess=0
if DEC>45 and DEC<135: ipos_guess=1
if DEC>135 and DEC<225: ipos_guess=3
if DEC>225 and DEC<315: ipos_guess=4
else:
if INC >45: ipos_guess=2
if INC <-45: ipos_guess=5
# prefer the guess over the code
ipos=ipos_guess
MeasRec["treat_dc_field_phi"]='%7.1f' %(tdec[ipos])
MeasRec["treat_dc_field_theta"]='%7.1f'% (tinc[ipos])
# check it
if ipos_guess!=ipos_code and treat[1][0]!='7':
print("-E- ERROR: check specimen %s step %s, ATRM measurements, coding does not match the direction of the lab field!"%(rec[0],".".join(list(treat))))
elif demag=="S": # Shaw experiment
if treat[1][1]=='0':
if int(treat[0])!=0:
MeasRec["treat_ac_field"]='%8.3e' % (float(treat[0])*1e-3) # AF field in tesla
MeasRec["treat_dc_field"]='0'
meas_type="LT-AF-Z" # first AF
else:
meas_type="LT-NO"
MeasRec["treat_ac_field"]='0'
MeasRec["treat_dc_field"]='0'
elif treat[1][1]=='1':
if int(treat[0])==0:
MeasRec["treat_ac_field"]='%8.3e' %(peakfield) # peak field in tesla
MeasRec["treat_dc_field"]='%8.3e'%(arm_labfield)
MeasRec["treat_dc_field_phi"]='%7.1f'%(phi)
MeasRec["treat_dc_field_theta"]='%7.1f'%(theta)
meas_type="LT-AF-I"
else:
MeasRec["treat_ac_field"]='%8.3e' % ( float(treat[0])*1e-3) # AF field in tesla
MeasRec["treat_dc_field"]='0'
meas_type="LT-AF-Z"
elif treat[1][1]=='2':
if int(treat[0])==0:
MeasRec["treat_ac_field"]='0'
MeasRec["treat_dc_field"]='%8.3e'%(trm_labfield)
MeasRec["treat_dc_field_phi"]='%7.1f'%(phi)
MeasRec["treat_dc_field_theta"]='%7.1f'%(theta)
MeasRec["treat_temp"]='%8.3e' % (trm_peakT)
meas_type="LT-T-I"
else:
MeasRec["treat_ac_field"]='%8.3e' % ( float(treat[0])*1e-3) # AF field in tesla
MeasRec["treat_dc_field"]='0'
meas_type="LT-AF-Z"
elif treat[1][1]=='3':
if int(treat[0])==0:
MeasRec["treat_ac_field"]='%8.3e' %(peakfield) # peak field in tesla
MeasRec["treat_dc_field"]='%8.3e'%(arm_labfield)
MeasRec["treat_dc_field_phi"]='%7.1f'%(phi)
MeasRec["treat_dc_field_theta"]='%7.1f'%(theta)
meas_type="LT-AF-I"
else:
MeasRec["treat_ac_field"]='%8.3e' % ( float(treat[0])*1e-3) # AF field in tesla
MeasRec["treat_dc_field"]='0'
meas_type="LT-AF-Z"
# Cooling rate experient # added by rshaar
elif demag=="T" and methcode == "LP-CR-TRM":
MeasRec["treat_temp"]='%8.3e' % (float(treat[0])+273.) # temp in kelvin
if treat[1][0]=='0':
meas_type="LT-T-Z:LP-CR-TRM"
MeasRec["treat_dc_field"]='%8.3e'%(0)
MeasRec["treat_dc_field_phi"]='0'
MeasRec["treat_dc_field_theta"]='0'
else:
MeasRec["treat_dc_field"]='%8.3e'%(labfield)
if treat[1][0]=='7': # alteration check as final measurement
meas_type="LT-PTRM-I:LP-CR-TRM"
else:
meas_type="LT-T-I:LP-CR-TRM"
MeasRec["treat_dc_field_phi"]='%7.1f' % (phi) # labfield phi
MeasRec["treat_dc_field_theta"]='%7.1f' % (theta) # labfield theta
indx=int(treat[1][0])-1
# alteration check matjed as 0.7 in the measurement file
if indx==6:
cooling_time= cooling_rates_list[-1]
else:
cooling_time=cooling_rates_list[indx]
MeasRec["description"]="cooling_rate"+":"+cooling_time+":"+"K/min"
noave=1
elif demag!='N':
if len(treat)==1:treat.append('0')
MeasRec["treat_temp"]='%8.3e' % (float(treat[0])+273.) # temp in kelvin
if trm==0: # demag=T and not trmaq
if treat[1][0]=='0':
meas_type="LT-T-Z"
else:
MeasRec["treat_dc_field"]='%8.3e' % (labfield) # labfield in tesla (convert from microT)
MeasRec["treat_dc_field_phi"]='%7.1f' % (phi) # labfield phi
MeasRec["treat_dc_field_theta"]='%7.1f' % (theta) # labfield theta
if treat[1][0]=='1':meas_type="LT-T-I" # in-field thermal step
if treat[1][0]=='2':
meas_type="LT-PTRM-I" # pTRM check
pTRM=1
if treat[1][0]=='3':
MeasRec["treat_dc_field"]='0' # this is a zero field step
meas_type="LT-PTRM-MD" # pTRM tail check
else:
labfield=float(treat[1])*1e-6
MeasRec["treat_dc_field"]='%8.3e' % (labfield) # labfield in tesla (convert from microT)
MeasRec["treat_dc_field_phi"]='%7.1f' % (phi) # labfield phi
MeasRec["treat_dc_field_theta"]='%7.1f' % (theta) # labfield theta
meas_type="LT-T-I:LP-TRM" # trm acquisition experiment
MeasRec["dir_csd"]=rec[2]
MeasRec["magn_moment"]='%10.3e'% (float(rec[3])*1e-3) # moment in Am^2 (from emu)
MeasRec["dir_dec"]=rec[4]
MeasRec["dir_inc"]=rec[5]
MeasRec["instrument_codes"]=instcode
MeasRec["analysts"]=user
MeasRec["citations"]=citations
if "LP-IRM-3D" in methcode : meas_type=methcode
#MeasRec["method_codes"]=methcode.strip(':')
MeasRec["method_codes"]=meas_type
MeasRec["quality"]='g'
if 'std' in rec[0]:
MeasRec["standard"]='s'
else:
MeasRec["standard"]='u'
MeasRec["treat_step_num"]='1'
#print MeasRec['treat_temp']
MeasRecs.append(MeasRec)
con = nb.Contribution(output_dir_path,read_tables=[])
# create MagIC tables
con.add_magic_table_from_data(dtype='specimens', data=SpecRecs)
con.add_magic_table_from_data(dtype='samples', data=SampRecs)
con.add_magic_table_from_data(dtype='sites', data=SiteRecs)
con.add_magic_table_from_data(dtype='locations', data=LocRecs)
MeasOuts=pmag.measurements_methods3(MeasRecs,noave)
con.add_magic_table_from_data(dtype='measurements', data=MeasOuts)
# write MagIC tables to file
con.tables['specimens'].write_magic_file(custom_name=spec_file)
con.tables['samples'].write_magic_file(custom_name=samp_file)
con.tables['sites'].write_magic_file(custom_name=site_file)
con.tables['locations'].write_magic_file(custom_name=loc_file)
meas_file = con.tables['measurements'].write_magic_file(custom_name=meas_file)
return True, meas_file
def main():
"""
NAME
revtest_magic.py
DESCRIPTION
calculates bootstrap statistics to test for antipodality
INPUT FORMAT
takes dec/inc data from sites table
SYNTAX
revtest_magic.py [command line options]
OPTION
-h prints help message and quits
-f FILE, sets pmag_sites filename on command line
-crd [s,g,t], set coordinate system, default is geographic
-exc use criteria file to set acceptance criteria (only available for data model 3)
-fmt [svg,png,jpg], sets format for image output
-sav saves plot and quits
-DM [2, 3] MagIC data model num, default is 3
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
dir_path = pmag.get_named_arg("-WD", ".")
coord = pmag.get_named_arg("-crd",
"0") # default to geographic coordinates
if coord == 's':
coord = '-1'
elif coord == 'g':
coord = '0'
elif coord == 't':
coord = '100'
fmt = pmag.get_named_arg("-fmt", "svg")
if '-sav' in sys.argv:
plot = 1
data_model = int(float(pmag.get_named_arg("-DM")))
if data_model == 2:
infile = pmag.get_named_arg("-f", "pmag_sites.txt")
critfile = "pmag_criteria.txt"
tilt_corr_col = 'site_tilt_correction'
dec_col = "site_dec"
inc_col = "site_inc"
crit_code_col = "pmag_criteria_code"
else:
infile = pmag.get_named_arg("-f", "sites.txt")
critfile = "criteria.txt"
tilt_corr_col = "dir_tilt_correction"
dec_col = "dir_dec"
inc_col = "dir_inc"
crit_code_col = "criterion"
D = []
#
infile = pmag.resolve_file_name(infile, dir_path)
dir_path = os.path.split(infile)[0]
critfile = pmag.resolve_file_name(critfile, dir_path)
#
if data_model == 2:
Accept = ['site_k', 'site_alpha95', 'site_n', 'site_n_lines']
else:
Accept = [
'dir_k', 'dir_alpha95', 'dir_n_samples', 'dir_n_specimens_line'
]
data, file_type = pmag.magic_read(infile)
if 'sites' not in file_type:
print("Error opening file", file_type)
sys.exit()
# ordata,file_type=pmag.magic_read(orfile)
SiteCrits = []
if '-exc' in sys.argv and data_model != 2:
crits, file_type = pmag.magic_read(critfile)
for crit in crits:
if crit[crit_code_col] == "DE-SITE":
SiteCrit = crit
SiteCrits.append(SiteCrit)
elif '-exc' in sys.argv and data_model == 2:
print(
'-W- You have selected the -exc option, which is not available with MagIC data model 2.'
)
for rec in data:
if rec[tilt_corr_col] == coord:
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
if '-exc' in sys.argv and data_model != 2:
fail = False
for SiteCrit in SiteCrits:
for key in Accept:
if key not in SiteCrit['table_column']:
continue
if key not in rec:
continue
if SiteCrit['criterion_value'] != "":
op = OPS[SiteCrit['criterion_operation']]
if not op(float(rec[key]),
float(SiteCrit['criterion_value'])):
fail = True
if not fail:
D.append([Dec, Inc, 1.])
else:
D.append([Dec, Inc, 1.])
# set up plots
CDF = {'X': 1, 'Y': 2, 'Z': 3}
pmagplotlib.plot_init(CDF['X'], 5, 5)
pmagplotlib.plot_init(CDF['Y'], 5, 5)
pmagplotlib.plot_init(CDF['Z'], 5, 5)
#
# flip reverse mode
#
D1, D2 = pmag.flip(D)
counter, NumSims = 0, 500
#
# get bootstrapped means for each data set
#
if len(D1) < 5 or len(D2) < 5:
print('not enough data in two different modes for reversals test')
sys.exit()
print('doing first mode, be patient')
BDI1 = pmag.di_boot(D1)
print('doing second mode, be patient')
BDI2 = pmag.di_boot(D2)
pmagplotlib.plot_com(CDF, BDI1, BDI2, [""])
files = {}
for key in list(CDF.keys()):
files[key] = 'REV' + '_' + key + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(CDF)
ans = input("s[a]ve plots, [q]uit: ")
if ans == 'a':
pmagplotlib.save_plots(CDF, files)
else:
pmagplotlib.save_plots(CDF, files)
sys.exit()
def main():
"""
NAME
mini_magic.py
DESCRIPTION
converts the Yale minispin format to magic_measurements format files
SYNTAX
mini_magic.py [command line options]
OPTIONS
-h: prints the help message and quits.
-usr USER: identify user, default is ""
-f FILE: specify input file, required
-F FILE: specify output file, default is magic_measurements.txt
-LP [colon delimited list of protocols, include all that apply]
AF: af demag
T: thermal including thellier but not trm acquisition
-A: don't average replicate measurements
-vol: volume assumed for measurement in cm^3 (default 12 cc)
-DM NUM: MagIC data model (2 or 3, default 3)
INPUT
Must put separate experiments (all AF, thermal, etc.) in
seperate files
Format of Yale MINI files:
LL-SI-SP_STEP, Declination, Inclination, Intensity (mA/m), X,Y,Z
"""
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
# initialize some stuff
methcode = "LP-NO"
demag = "N"
#
# get command line arguments
#
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
user = pmag.get_named_arg("-usr", "")
dir_path = pmag.get_named_arg("-WD", ".")
inst = pmag.get_named_arg("-inst", "")
magfile = pmag.get_named_arg("-f", reqd=True)
magfile = pmag.resolve_file_name(magfile, dir_path)
if "-A" in args:
noave = 1
else:
noave = 0
if data_model_num == 2:
meas_file = pmag.get_named_arg("-F", "magic_measurements.txt")
else:
meas_file = pmag.get_named_arg("-F", "measurements.txt")
meas_file = pmag.resolve_file_name(meas_file, dir_path)
volume = pmag.get_named_arg("-vol", 12) # assume a volume of 12 cc if not provided
methcode = pmag.get_named_arg("-LP", "LP-NO")
#ind = args.index("-LP")
#codelist = args[ind+1]
#codes = codelist.split(':')
#if "AF" in codes:
# demag = 'AF'
# methcode = "LT-AF-Z"
#if "T" in codes:
# demag = "T"
convert.mini(magfile, dir_path, meas_file, data_model_num,
volume, noave, inst, user, methcode)
def main():
"""
NAME
lnp_magic.py
DESCRIPTION
makes equal area projections site by site
from specimen formatted file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
SYNTAX
lnp_magic [command line options]
INPUT
takes magic formatted specimens file
OUPUT
prints site_name n_lines n_planes K alpha95 dec inc R
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is 'specimens.txt', ('pmag_specimens.txt' for legacy data model 2)
-fsa FILE: specify samples file, required to plot by site for data model 3 (otherwise will plot by sample)
default is 'samples.txt'
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is specimen
-fmt [svg,png,jpg] format for plots, default is svg
-sav save plots and quit
-P: do not plot
-F FILE, specify output file of dec, inc, alpha95 data for plotting with plotdi_a and plotdi_e
-exc use criteria in criteria table # NOT IMPLEMENTED
-DM NUMBER MagIC data model (2 or 3, default 3)
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", ".")
data_model = int(float(pmag.get_named_arg("-DM", 3)))
fmt = pmag.get_named_arg("-fmt", 'svg')
if data_model == 2:
in_file = pmag.get_named_arg('-f', 'pmag_specimens.txt')
crit_file = "pmag_criteria.txt"
else:
in_file = pmag.get_named_arg('-f', 'specimens.txt')
samp_file = pmag.get_named_arg('-fsa', 'samples.txt')
crit_file = "criteria.txt"
in_file = pmag.resolve_file_name(in_file, dir_path)
dir_path = os.path.split(in_file)[0]
if data_model == 3:
samp_file = pmag.resolve_file_name(samp_file, dir_path)
if '-crd' in sys.argv:
ind = sys.argv.index("-crd")
crd = sys.argv[ind + 1]
if crd == 's':
coord = "-1"
if crd == 'g':
coord = "0"
if crd == 't':
coord = "100"
else:
coord = "-1"
out_file = pmag.get_named_arg('-F', '')
if out_file:
out = open(dir_path + '/' + out_file, 'w')
if '-P' in sys.argv:
make_plots = 0 # do not plot
else:
make_plots = 1 # do plot
if '-sav' in sys.argv:
plot = 1 # save plots and quit
else:
plot = 0 # show plots intereactively (if make_plots)
#
if data_model == 2:
Specs, file_type = pmag.magic_read(in_file)
if 'specimens' not in file_type:
print('Error opening ', in_file, file_type)
sys.exit()
else:
fnames = {'specimens': in_file, 'samples': samp_file}
con = cb.Contribution(dir_path,
read_tables=['samples', 'specimens'],
custom_filenames=fnames)
con.propagate_name_down('site', 'specimens')
if 'site' in con.tables['specimens'].df.columns:
site_col = 'site'
else:
site_col = 'sample'
tilt_corr_col = "dir_tilt_correction"
mad_col = "dir_mad_free"
alpha95_col = "dir_alpha95"
site_alpha95_col = "dir_alpha95"
dec_col = "dir_dec"
inc_col = "dir_inc"
num_meas_col = "dir_n_measurements"
k_col = "dir_k"
cols = [
site_col, tilt_corr_col, mad_col, alpha95_col, dec_col, inc_col
]
con.tables['specimens'].front_and_backfill(cols)
con.tables['specimens'].df = con.tables['specimens'].df.where(
con.tables['specimens'].df.notnull(), "")
Specs = con.tables['specimens'].convert_to_pmag_data_list()
## using criteria file was never fully implemented
#if '-exc' in sys.argv:
# Crits, file_type = pmag.magic_read(pmag.resolve_file_name(crit_file, dir_path))
# for crit in Crits:
# if mad_col in crit:
# M = float(crit['specimen_mad'])
# if num_meas_col in crit:
# N = float(crit['specimen_n'])
# if site_alpha95_col in crit and 'site' in crit:
# acutoff = float(crit['site_alpha95'])
# if k_col in crit:
# kcutoff = float(crit['site_k'])
#else:
# Crits = ""
sitelist = []
# initialize some variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
M, N, acutoff, kcutoff = 180., 1, 180., 0.
if data_model == 2:
site_col = 'er_site_name'
tilt_corr_col = "specimen_tilt_correction"
mad_col = "specimen_mad"
alpha95_col = 'specimen_alpha95'
dec_col = "specimen_dec"
inc_col = "specimen_inc"
num_meas_col = "specimen_n"
site_alpha95_col = "site_alpha95"
else: # data model 3
pass
for rec in Specs:
if rec[site_col] not in sitelist:
sitelist.append(rec[site_col])
sitelist.sort()
if make_plots == 1:
EQ = {}
EQ['eqarea'] = 1
for site in sitelist:
pmagplotlib.plot_init(EQ['eqarea'], 4, 4)
print(site)
data = []
for spec in Specs:
if tilt_corr_col not in list(spec.keys()):
spec[tilt_corr_col] = '-1' # assume unoriented
if spec[site_col] == site:
if mad_col not in list(spec.keys()) or spec[mad_col] == "":
if alpha95_col in list(
spec.keys()) and spec[alpha95_col] != "":
spec[mad_col] = spec[alpha95_col]
else:
spec[mad_col] = '180'
if not spec[num_meas_col]:
continue
if (float(spec[tilt_corr_col])
== float(coord)) and (float(spec[mad_col]) <= M) and (
float(spec[num_meas_col]) >= N):
rec = {}
for key in list(spec.keys()):
rec[key] = spec[key]
rec["dec"] = float(spec[dec_col])
rec["inc"] = float(spec[inc_col])
rec["tilt_correction"] = spec[tilt_corr_col]
data.append(rec)
if len(data) > 2:
fpars = pmag.dolnp(data, 'specimen_direction_type')
print("Site lines planes kappa a95 dec inc")
print(site, fpars["n_lines"], fpars["n_planes"], fpars["K"],
fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"])
if out_file != "":
if float(fpars["alpha95"]) <= acutoff and float(
fpars["K"]) >= kcutoff:
out.write('%s %s %s\n' %
(fpars["dec"], fpars['inc'], fpars['alpha95']))
print('% tilt correction: ', coord)
if make_plots == 1:
files = {}
files['eqarea'] = site + '_' + crd + '_' + 'eqarea' + '.' + fmt
pmagplotlib.plot_lnp(EQ['eqarea'], site, data, fpars,
'specimen_direction_type')
if plot == 0:
pmagplotlib.draw_figs(EQ)
ans = input(
"s[a]ve plot, [q]uit, <return> to continue:\n ")
if ans == "a":
pmagplotlib.save_plots(EQ, files)
if ans == "q":
sys.exit()
else:
pmagplotlib.save_plots(EQ, files)
else:
print(
'skipping site - not enough data with specified coordinate system'
)
def main():
"""
NAME
eqarea_magic.py
DESCRIPTION
makes equal area projections from declination/inclination data
SYNTAX
eqarea_magic.py [command line options]
INPUT
takes magic formatted sites, samples, specimens, or measurements
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic, default='sites.txt'
supported types=[measurements, specimens, samples, sites]
-fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
default='specimens.txt'
-fsa FILE: specify sample file name, (required if you want to plot specimens by site)
default='samples.txt'
-fsi FILE: specify site file name, default='sites.txt'
-flo FILE: specify location file name, default='locations.txt'
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-cm CM use color map CM [default is coolwarm]
-sav save plot and quit quietly
-no-tilt data are unoriented, allows plotting of measurement dec/inc
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
# extract arguments from sys.argv
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", default_val=".")
input_dir_path = pmag.get_named_arg('-ID', '')
if not input_dir_path:
input_dir_path = dir_path
in_file = pmag.get_named_arg("-f", default_val="sites.txt")
in_file = pmag.resolve_file_name(in_file, input_dir_path)
if "-ID" not in sys.argv:
input_dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", default_val="all").lower()
spec_file = pmag.get_named_arg("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg("-fsi", default_val="sites.txt")
loc_file = pmag.get_named_arg("-flo", default_val="locations.txt")
ignore_tilt = False
if '-no-tilt' in sys.argv:
ignore_tilt = True
color_map = "coolwarm"
if '-c' in sys.argv:
contour = True
if '-cm' in sys.argv:
ind = sys.argv.index('-cm')
color_map = sys.argv[ind+1]
else:
color_map = 'coolwarm'
else:
contour = False
interactive = True
save_plots = False
if '-sav' in sys.argv:
save_plots = True
interactive = False
plot_ell = False
if '-ell' in sys.argv:
plot_ell = pmag.get_named_arg("-ell", "F")
crd = pmag.get_named_arg("-crd", default_val="g")
fmt = pmag.get_named_arg("-fmt", "svg")
ipmag.eqarea_magic(in_file, dir_path, input_dir_path, spec_file, samp_file, site_file, loc_file,
plot_by, crd, ignore_tilt, save_plots, fmt, contour, color_map,
plot_ell, "all", interactive)
def main():
"""
NAME
strip_magic.py
DESCRIPTION
plots various parameters versus depth or age
SYNTAX
strip_magic.py [command line optins]
OPTIONS
-h prints help message and quits
-DM NUM: specify data model num, options 2 (legacy) or 3 (default)
-f FILE: specify input magic format file from magic,default='pmag_results.txt'
supported types=[pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
-obj [sit,sam,all]: specify object to site,sample,all for pmag_result table, default is all
-fmt [svg,png,jpg], format for images - default is svg
-x [age,pos]: specify whether age or stratigraphic position
-y [dec,inc,int,chi,lat,lon,vdm,vadm]
(lat and lon are VGP lat and lon)
-Iex: plot the expected inc at lat - only available for results with lat info in file
-ts TS amin amax: plot the GPTS for the time interval between amin and amax (numbers in Ma)
TS: [ck95, gts04]
-mcd method_code, specify method code, default is first one encountered
-sav save plot and quit
NOTES
when x and/or y are not specified, a list of possibilities will be presented to the user for choosing
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
xaxis, xplotind, yplotind = "", 0, 0 # (0 for strat pos)
yaxis, Xinc = "", ""
plot = 0
obj = 'all'
data_model_num = int(pmag.get_named_arg("-DM", 3))
# 2.5 keys
if data_model_num == 2:
supported = ['pmag_specimens', 'pmag_samples',
'pmag_sites', 'pmag_results', 'magic_web'] # available file types
Depth_keys = ['specimen_core_depth', 'specimen_height', 'specimen_elevation',
'specimen_composite_depth', 'sample_core_depth', 'sample_height',
'sample_elevation', 'sample_composite_depth', 'site_core_depth',
'site_height', 'site_elevation', 'site_composite_depth', 'average_height']
Age_keys = ['specimen_inferred_age', 'sample_inferred_age',
'site_inferred_age', 'average_age']
Unit_keys = {'specimen_inferred_age': 'specimen_inferred_age_unit',
'sample_inferred_age': 'sample_inferred_age_unit',
'site_inferred_age': 'site_inferred_age_unit', 'average_age': 'average_age_unit'}
Dec_keys = ['measurement_dec', 'specimen_dec',
'sample_dec', 'site_dec', 'average_dec']
Inc_keys = ['measurement_inc', 'specimen_inc',
'sample_inc', 'site_inc', 'average_inc']
Int_keys = ['measurement_magnitude', 'measurement_magn_moment', 'measurement_magn_volume',
'measurement_magn_mass', 'specimen_int', 'specimen_int_rel', 'sample_int',
'sample_int_rel', 'site_int', 'site_int_rel', 'average_int', 'average_int_rel']
Chi_keys = ['measurement_chi_volume', 'measurement_chi_mass']
Lat_keys = ['sample_lat', 'site_lat', 'average_lat']
VLat_keys = ['vgp_lat']
VLon_keys = ['vgp_lon']
Vdm_keys = ['vdm']
Vadm_keys = ['vadm']
method_col_name = "magic_method_codes"
else:
# 3.0 keys
supported = ["specimens", "samples", "sites", "locations"] # available file types
Depth_keys = [ "height", "core_depth", "elevation", "composite_depth" ]
Age_keys = [ "age" ]
Unit_keys = { "age": "age" }
Chi_keys = [ "susc_chi_volume", "susc_chi_mass" ]
Int_keys = [ "magn_moment", "magn_volume", "magn_mass", "int_abs", "int_rel" ]
Inc_keys = [ "dir_inc" ]
Dec_keys = [ "dir_dec" ]
Lat_Keys = [ "lat" ]
VLat_keys = [ "vgp_lat", "pole_lat" ]
VLon_keys = [ "vgp_lon", "pole_lon" ]
Vdm_keys = [ "vdm", "pdm" ]
Vadm_keys = [ "vadm", "padm" ]
method_col_name = "method_codes"
#
X_keys = [Age_keys, Depth_keys]
Y_keys = [Dec_keys, Inc_keys, Int_keys, Chi_keys,
VLat_keys, VLon_keys, Vdm_keys, Vadm_keys]
method, fmt = "", 'svg'
FIG = {'strat': 1}
plotexp, pTS = 0, 0
dir_path = pmag.get_named_arg("-WD", ".")
# default files
if data_model_num == 3:
res_file = pmag.get_named_arg("-f", "sites.txt")
else:
res_file = pmag.get_named_arg("-f", "pmag_results.txt")
res_file = pmag.resolve_file_name(res_file, dir_path)
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind+1]
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
obj = sys.argv[ind+1]
if '-x' in sys.argv:
ind = sys.argv.index('-x')
xaxis = sys.argv[ind+1]
if '-y' in sys.argv:
ind = sys.argv.index('-y')
yaxis = sys.argv[ind+1]
if yaxis == 'dec':
ykeys = Dec_keys
if yaxis == 'inc':
ykeys = Inc_keys
if yaxis == 'int':
ykeys = Int_keys
if yaxis == 'chi':
ykeys = Chi_keys
if yaxis == 'lat':
ykeys = VLat_keys
if yaxis == 'lon':
ykeys = VLon_keys
if yaxis == 'vdm':
ykeys = Vdm_keys
if yaxis == 'vadm':
ykeys = Vadm_keys
if '-mcd' in sys.argv:
ind = sys.argv.index('-mcd')
method = sys.argv[ind+1]
if '-ts' in sys.argv:
ind = sys.argv.index('-ts')
ts = sys.argv[ind+1]
amin = float(sys.argv[ind+2])
amax = float(sys.argv[ind+3])
pTS = 1
if '-Iex' in sys.argv:
plotexp = 1
if '-sav' in sys.argv:
plot = 1
#
#
# get data read in
Results, file_type = pmag.magic_read(res_file)
if file_type not in supported:
print("Unsupported file type ({}), try again".format(file_type))
sys.exit()
PltObjs = ['all']
if data_model_num == 2:
if file_type == 'pmag_results': # find out what to plot
for rec in Results:
resname = rec['pmag_result_name'].split()
if 'Sample' in resname and 'sam' not in PltObjs:
PltObjs.append('sam')
if 'Site' in resname and 'sit' not in PltObjs:
PltObjs.append('sit')
methcodes = []
# need to know all the measurement types from method_codes
if "magic_method_codes" in list(Results[0].keys()):
for rec in Results:
meths = rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in methcodes and 'LP' in meth:
# look for the lab treatments
methcodes.append(meth.strip())
#
# initialize some variables
X_unit = "" # Unit for age or depth plotting (meters if depth)
Xplots, Yplots = [], []
Xunits = []
yplotind, xplotind = 0, 0
#
# step through possible plottable keys
#
if xaxis == "" or yaxis == "":
for key in list(Results[0].keys()):
for keys in X_keys:
for xkeys in keys:
if key in xkeys:
for ResRec in Results:
if ResRec[key] != "":
# only plot something if there is something to plot!
Xplots.append(key)
break
for keys in Y_keys:
for pkeys in keys:
if key in pkeys:
for ResRec in Results:
if ResRec[key] != "":
Yplots.append(key)
break
X, Y = [], []
for plt in Xplots:
if plt in Age_keys and 'age' not in X:
X.append('age')
if plt in Depth_keys and 'pos' not in X:
X.append('pos')
for plt in Yplots:
if plt in Dec_keys and 'dec' not in Y:
Y.append('dec')
if plt in Inc_keys and 'inc' not in Y:
Y.append('inc')
if plt in Int_keys and 'int' not in Y:
Y.append('int')
if plt in Chi_keys and 'chi' not in Y:
Y.append('chi')
if plt in VLat_keys and 'lat' not in Y:
Y.append('lat')
if plt in VLon_keys and 'lon' not in Y:
Y.append('lon')
if plt in Vadm_keys and 'vadm' not in Y:
Y.append('vadm')
if plt in Vdm_keys and 'vdm' not in Y:
Y.append('vdm')
if file_type == 'pmag_results':
print('available objects for plotting: ', PltObjs)
print('available X plots: ', X)
print('available Y plots: ', Y)
print('available method codes: ', methcodes)
f = open(dir_path+'/.striprc', 'w')
for x in X:
f.write('x:'+x+'\n')
for y in Y:
f.write('y:'+y+'\n')
for m in methcodes:
f.write('m:'+m+'\n')
for obj in PltObjs:
f.write('obj:'+obj+'\n')
sys.exit()
if plotexp == 1:
for lkey in Lat_keys:
for key in list(Results[0].keys()):
if key == lkey:
lat = float(Results[0][lkey])
Xinc = [pmag.pinc(lat), -pmag.pinc(lat)]
break
if Xinc == "":
print('can not plot expected inc for site - lat unknown')
if method != "" and method not in methcodes:
print('your method not available, but these are: ')
print(methcodes)
print('use ', methcodes[0], '? ^D to quit')
if xaxis == 'age':
for akey in Age_keys:
for key in list(Results[0].keys()):
if key == akey:
Xplots.append(key)
Xunits.append(Unit_keys[key])
if xaxis == 'pos':
for dkey in Depth_keys:
for key in list(Results[0].keys()):
if key == dkey:
Xplots.append(key)
if len(Xplots) == 0:
print('desired X axis information not found')
sys.exit()
if xaxis == 'age':
age_unit = Results[0][Xunits[0]]
if len(Xplots) > 1:
print('multiple X axis keys found, using: ', Xplots[xplotind])
for ykey in ykeys:
for key in list(Results[0].keys()):
if key == ykey:
Yplots.append(key)
if len(Yplots) == 0:
print('desired Y axis information not found')
sys.exit()
if len(Yplots) > 1:
print('multiple Y axis keys found, using: ', Yplots[yplotind])
# check if age or depth info
if len(Xplots) == 0:
print("Must have either age or height info to plot ")
sys.exit()
#
# check for variable to plot
#
#
# determine X axis (age or depth)
#
if xaxis == "age":
plotind = "1"
if method == "":
try:
method = methcodes[0]
except IndexError:
method = ""
if xaxis == 'pos':
xlab = "Stratigraphic Height (meters)"
else:
xlab = "Age ("+age_unit+")"
Xkey = Xplots[xplotind]
Ykey = Yplots[yplotind]
ylab = Ykey
#
# collect the data for plotting
XY = []
isign = 1.
# if float(Results[0][Xkey])/float(Results[-1][Xkey])>0 and float(Results[0][Xkey])<0:
# isign=-1. # x axis all same sign and negative, take positive (e.g.,for depth in core)
# xlab="Stratigraphic Position (meters)"
# else:
# isign=1.
for rec in Results:
if "magic_method_codes" in list(rec.keys()):
meths = rec["magic_method_codes"].split(":")
if method in meths: # make sure it is desired lab treatment step
if obj == 'all' and rec[Xkey].strip() != "":
XY.append([isign*float(rec[Xkey]), float(rec[Ykey])])
elif rec[Xkey].strip() != "":
name = rec['pmag_result_name'].split()
if obj == 'sit' and "Site" in name:
XY.append([isign*float(rec[Xkey]), float(rec[Ykey])])
if obj == 'sam' and "Sample" in name:
XY.append([isign*float(rec[Xkey]), float(rec[Ykey])])
elif method == "":
if obj == 'all' and rec[Xkey].strip() != "":
XY.append([isign*float(rec[Xkey]), float(rec[Ykey])])
elif rec[Xkey].strip() != "":
name = rec['pmag_result_name'].split()
if obj == 'sit' and "Site" in name:
XY.append([isign*float(rec[Xkey]), float(rec[Ykey])])
if obj == 'sam' and "Sample" in name:
XY.append([isign*float(rec[Xkey]), float(rec[Ykey])])
else:
print("Something wrong with your plotting choices")
break
XY.sort()
title = ""
if "er_locations_names" in list(Results[0].keys()):
title = Results[0]["er_location_names"]
if "er_locations_name" in list(Results[0].keys()):
title = Results[0]["er_location_name"]
labels = [xlab, ylab, title]
pmagplotlib.plot_init(FIG['strat'], 10, 5)
pmagplotlib.plot_strat(FIG['strat'], XY, labels) # plot them
if plotexp == 1:
pmagplotlib.plot_hs(FIG['strat'], Xinc, 'b', '--')
if yaxis == 'inc' or yaxis == 'lat':
pmagplotlib.plot_hs(FIG['strat'], [0], 'b', '-')
pmagplotlib.plot_hs(FIG['strat'], [-90, 90], 'g', '-')
if pTS == 1:
FIG['ts'] = 2
pmagplotlib.plot_init(FIG['ts'], 10, 5)
pmagplotlib.plot_ts(FIG['ts'], [amin, amax], ts)
files = {}
for key in list(FIG.keys()):
files[key] = key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
files = {}
files['strat'] = xaxis+'_'+yaxis+'_.'+fmt
files['ts'] = 'ts.'+fmt
titles = {}
titles['strat'] = 'Depth/Time Series Plot'
titles['ts'] = 'Time Series Plot'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plot == 1:
pmagplotlib.save_plots(FIG, files)
else:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
lowrie_magic.py
DESCRIPTION
plots intensity decay curves for Lowrie experiments
SYNTAX
lowrie_magic.py -h [command line options]
INPUT
takes measurements formatted input files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is magic_measurements.txt
-N do not normalize by maximum magnetization
-fmt [svg, pdf, eps, png] specify fmt, default is svg
-sav saves plots and quits
-DM [2, 3] MagIC data model number
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if len(sys.argv) <= 1:
print(main.__doc__)
print('you must supply a file name')
sys.exit()
FIG = {} # plot dictionary
FIG['lowrie'] = 1 # demag is figure 1
pmagplotlib.plot_init(FIG['lowrie'], 6, 6)
norm = 1 # default is to normalize by maximum axis
in_file = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
in_file = pmag.resolve_file_name(in_file, dir_path)
data_model = pmag.get_named_arg("-DM", 3)
data_model = int(float(data_model))
fmt = pmag.get_named_arg("-fmt", "svg")
if '-N' in sys.argv:
norm = 0 # don't normalize
if '-sav' in sys.argv:
plot = 1 # silently save and quit
else:
plot = 0 # generate plots
print(in_file)
# read in data
PmagRecs, file_type = pmag.magic_read(in_file)
if data_model == 2 and file_type != "magic_measurements":
print('bad input file', file_type)
sys.exit()
if data_model == 3 and file_type != "measurements":
print('bad input file', file_type)
sys.exit()
if data_model == 2:
meth_code_col = 'magic_method_codes'
spec_col = 'er_specimen_name'
dec_col = "measurement_dec"
inc_col = 'measurement_inc'
moment_col = 'measurement_magn_moment'
temp_col = 'treatment_temp'
else:
meth_code_col = 'method_codes'
spec_col = 'specimen'
dec_col = 'dir_dec'
inc_col = 'dir_inc'
moment_col = 'magn_moment'
temp_col = "treat_temp"
PmagRecs = pmag.get_dictitem(
PmagRecs, meth_code_col, 'LP-IRM-3D', 'has') # get all 3D IRM records
if len(PmagRecs) == 0:
print('no records found with the method code LP-IRM-3D')
sys.exit()
specs = pmag.get_dictkey(PmagRecs, spec_col, '')
sids = []
for spec in specs:
if spec not in sids:
sids.append(spec) # get list of unique specimen names
for spc in sids: # step through the specimen names
print(spc)
specdata = pmag.get_dictitem(
PmagRecs, spec_col, spc, 'T') # get all this one's data
DIMs, Temps = [], []
for dat in specdata: # step through the data
DIMs.append([float(dat[dec_col]), float(
dat[inc_col]), float(dat[moment_col])])
Temps.append(float(dat[temp_col])-273.)
carts = pmag.dir2cart(DIMs).transpose()
if norm == 1: # want to normalize
nrm = (DIMs[0][2]) # normalize by NRM
ylab = "M/M_o"
else:
nrm = 1. # don't normalize
ylab = "Magnetic moment (Am^2)"
xlab = "Temperature (C)"
pmagplotlib.plot_xy(FIG['lowrie'], Temps, abs(carts[0]) / nrm, sym='r-')
pmagplotlib.plot_xy(FIG['lowrie'], Temps, abs(carts[0]) / nrm, sym='ro') # X direction
pmagplotlib.plot_xy(FIG['lowrie'], Temps, abs(carts[1]) / nrm, sym='c-')
pmagplotlib.plot_xy(FIG['lowrie'], Temps, abs(carts[1]) / nrm, sym='cs') # Y direction
pmagplotlib.plot_xy(FIG['lowrie'], Temps, abs(carts[2]) / nrm, sym='k-')
pmagplotlib.plot_xy(FIG['lowrie'], Temps, abs(carts[2]) / nrm, sym='k^', title=spc, xlab=xlab, ylab=ylab) # Z direction
files = {'lowrie': 'lowrie:_'+spc+'_.'+fmt}
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input('S[a]ve figure? [q]uit, <return> to continue ')
if ans == 'a':
pmagplotlib.save_plots(FIG, files)
elif ans == 'q':
sys.exit()
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['lowrie'])
def convert(**kwargs):
version_num = pmag.get_version()
dir_path = kwargs.get('dir_path', '.')
mag_file = kwargs.get('mag_file')
input_dir_path = kwargs.get('input_dir_path', dir_path)
if input_dir_path == dir_path:
mag_file = pmag.resolve_file_name(mag_file, dir_path)
input_dir_path = os.path.split(mag_file)[0]
output_dir_path = dir_path
user = kwargs.get('user', '')
meas_file = kwargs.get('meas_file', 'measurements.txt') # outfile
spec_file = kwargs.get('spec_file', 'specimens.txt') # specimen outfile
samp_file = kwargs.get('samp_file', 'samples.txt') # sample outfile
site_file = kwargs.get('site_file', 'sites.txt') # site outfile
loc_file = kwargs.get('loc_file', 'locations.txt') # location outfile
specnum = kwargs.get('specnum', 1)
samp_con = kwargs.get('samp_con', '1')
location = kwargs.get('location', 'unknown')
lat = kwargs.get('lat', '')
lon = kwargs.get('lon', '')
noave = kwargs.get('noave', 0) # default (0) means DO average
meth_code = kwargs.get('meth_code', "LP-NO")
volume = float(kwargs.get('volume', 2.5)) * 1e-6
timezone = kwargs.get('timestamp', 'UTC')
# format variables
mag_file = os.path.join(input_dir_path, mag_file)
if specnum != 0: specnum = -int(specnum)
if samp_con.startswith("4"):
if "-" not in samp_con:
print("option [4] must be in form 4-Z where Z is an integer")
return False, "naming convention option [4] must be in form 4-Z where Z is an integer"
else:
Z = samp_con.split("-")[1]
samp_con = "4"
elif samp_con.startswith("7"):
if "-" not in samp_con:
print("option [7] must be in form 7-Z where Z is an integer")
return False, "naming convention option [7] must be in form 7-Z where Z is an integer"
else:
Z = samp_con.split("-")[1]
samp_con = "7"
else:
Z = 1
#create data holders
MeasRecs, SpecRecs, SampRecs, SiteRecs, LocRecs = [], [], [], [], []
data = pmag.open_file(mag_file)
# remove garbage/blank lines
data = [i for i in data if len(i) >= 5]
if not len(data):
print('No data')
return
n = 0
end = False
# loop through records
while not end:
first_line = data[n].split()
sampleName = first_line[0]
demagLevel = first_line[2]
date = first_line[3] + ":0:0:0"
n += 2
third_line = data[n].split()
if not third_line[0].startswith('SPEC.ANGLES'):
print('third line of a block should start with SPEC.ANGLES')
print(third_line)
return
specimenAngleDec = third_line[1]
specimenAngleInc = third_line[2]
n += 4
while not data[n].startswith('MEAN'):
n += 1
mean_line = data[n]
Mx = mean_line[1]
My = mean_line[2]
Mz = mean_line[3]
n += 1
precision_line = data[n].split()
if not precision_line[0].startswith('Modulus'):
print('precision line should start with "Modulus"')
return
splitExp = precision_line[2].split('A')
intensityVolStr = precision_line[1] + splitExp[0]
intensityVol = float(intensityVolStr)
# check and see if Prec is too big and messes with the parcing.
precisionStr = ''
if len(precision_line) == 6: #normal line
precisionStr = precision_line[5][0:-1]
else:
precisionStr = precision_line[4][0:-1]
precisionPer = float(precisionStr)
precision = intensityVol * precisionPer / 100
while not data[n].startswith('SPEC.'):
n += 1
specimen_line = data[n].split()
specimenDec = specimen_line[2]
specimenInc = specimen_line[3]
n += 1
geographic_line = data[n]
if not geographic_line.startswith('GEOGR'):
geographic_dec = ''
geographic_inc = ''
else:
geographic_line = geographic_line.split()
geographicDec = geographic_line[1]
geographicInc = geographic_line[2]
# Add data to various MagIC data tables.
specimen = sampleName
if specnum != 0: sample = specimen[:specnum]
else: sample = specimen
site = pmag.parse_site(sample, samp_con, Z)
MeasRec, SpecRec, SampRec, SiteRec, LocRec = {}, {}, {}, {}, {}
if specimen != "" and specimen not in [
x['specimen'] if 'specimen' in list(x.keys()) else ""
for x in SpecRecs
]:
SpecRec['specimen'] = specimen
SpecRec['sample'] = sample
SpecRec["citations"] = "This study"
SpecRec["analysts"] = user
SpecRec['volume'] = volume
SpecRecs.append(SpecRec)
if sample != "" and sample not in [
x['sample'] if 'sample' in list(x.keys()) else ""
for x in SampRecs
]:
SampRec['sample'] = sample
SampRec['site'] = site
SampRec["citations"] = "This study"
SampRec["analysts"] = user
SampRec['azimuth'] = specimenAngleDec
sample_dip = str(float(specimenAngleInc) -
90.0) #convert to magic orientation
SampRec['dip'] = sample_dip
SampRec['method_codes'] = meth_code
SampRecs.append(SampRec)
if site != "" and site not in [
x['site'] if 'site' in list(x.keys()) else "" for x in SiteRecs
]:
SiteRec['site'] = site
SiteRec['location'] = location
SiteRec["citations"] = "This study"
SiteRec["analysts"] = user
SiteRec['lat'] = lat
SiteRec['lon'] = lon
SiteRecs.append(SiteRec)
if location != "" and location not in [
x['location'] if 'location' in list(x.keys()) else ""
for x in LocRecs
]:
LocRec['location'] = location
LocRec["citations"] = "This study"
LocRec["analysts"] = user
LocRec['lat_n'] = lat
LocRec['lon_e'] = lon
LocRec['lat_s'] = lat
LocRec['lon_w'] = lon
LocRecs.append(LocRec)
local = pytz.timezone(timezone)
naive = datetime.datetime.strptime(date, "%m-%d-%Y:%H:%M:%S")
local_dt = local.localize(naive, is_dst=None)
utc_dt = local_dt.astimezone(pytz.utc)
timestamp = utc_dt.strftime("%Y-%m-%dT%H:%M:%S") + "Z"
MeasRec["specimen"] = specimen
MeasRec["timestamp"] = timestamp
MeasRec['description'] = ''
MeasRec["citations"] = "This study"
MeasRec['software_packages'] = version_num
MeasRec["treat_temp"] = '%8.3e' % (273) # room temp in kelvin
MeasRec["meas_temp"] = '%8.3e' % (273) # room temp in kelvin
MeasRec["quality"] = 'g'
MeasRec["standard"] = 'u'
MeasRec["treat_step_num"] = '1'
MeasRec["treat_ac_field"] = '0'
if demagLevel == 'NRM':
meas_type = "LT-NO"
elif demagLevel[0] == 'A':
if demagLevel[:2] == 'AD':
treat = float(demagLevel[2:])
else:
treat = float(demagLevel[1:])
meas_type = "LT-AF-Z"
MeasRec["treat_ac_field"] = '%8.3e' % (
treat * 1e-3) # convert from mT to tesla
elif demagLevel[0] == 'T':
meas_type = "LT-T-Z"
treat = float(demagLevel[1:])
MeasRec["treat_temp"] = '%8.3e' % (treat + 273.) # temp in kelvin
else:
print("measurement type unknown", demagLevel)
return False, "measurement type unknown"
MeasRec["magn_moment"] = str(intensityVol * volume) # Am^2
MeasRec["magn_volume"] = intensityVolStr # A/m
MeasRec["dir_dec"] = specimenDec
MeasRec["dir_inc"] = specimenInc
MeasRec['method_codes'] = meas_type
MeasRecs.append(MeasRec)
# ignore all the rest of the special characters. Some data files not consistantly formatted.
n += 1
while ((len(data[n]) <= 5 and data[n] != '')
or data[n].startswith('----')):
n += 1
if n >= len(data):
break
if n >= len(data):
# we're done!
end = True
#end of data while loop
con = nb.Contribution(output_dir_path, read_tables=[])
con.add_magic_table_from_data(dtype='specimens', data=SpecRecs)
con.add_magic_table_from_data(dtype='samples', data=SampRecs)
con.add_magic_table_from_data(dtype='sites', data=SiteRecs)
con.add_magic_table_from_data(dtype='locations', data=LocRecs)
MeasOuts = pmag.measurements_methods3(MeasRecs, noave)
con.add_magic_table_from_data(dtype='measurements', data=MeasOuts)
con.tables['specimens'].write_magic_file(custom_name=spec_file)
con.tables['samples'].write_magic_file(custom_name=samp_file)
con.tables['sites'].write_magic_file(custom_name=site_file)
con.tables['locations'].write_magic_file(custom_name=loc_file)
con.tables['measurements'].write_magic_file(custom_name=meas_file)
return True, meas_file
def main():
"""
NAME
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify measurements format file, default "measurements.txt"
-T IND, specify temperature step to plot
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
"""
if "-h" in sys.argv:
print(main.__doc__)
return
infile = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
infile = pmag.resolve_file_name(infile, dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
show_plots = True
if "-sav" in sys.argv:
show_plots = False
experiments = pmag.get_named_arg("-e", "")
# read in data from data model 3 example file
chi_data_all = pd.read_csv(infile, sep='\t', header=1)
if not experiments:
try:
experiments = chi_data_all.experiment.unique()
except Exception as ex:
print(ex)
experiments = ["all"]
else:
experiments = [experiments]
plotnum = 0
figs = {}
fnames = {}
for exp in experiments:
if exp == "all":
chi_data = chi_data_all
chi_data = chi_data_all[chi_data_all.experiment == exp]
if len(chi_data) <= 1:
print('Not enough data to plot {}'.format(exp))
continue
plotnum += 1
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_temperature.{}'.format(fmt)
# get arrays of available temps, frequencies and fields
Ts = np.sort(chi_data.meas_temp.unique())
Fs = np.sort(chi_data.meas_freq.unique())
Bs = np.sort(chi_data.meas_field_ac.unique())
# plot chi versus temperature at constant field
b = Bs.max()
for num, f in enumerate(Fs):
this_f = chi_data[chi_data.meas_freq == f]
this_f = this_f[this_f.meas_field_ac == b]
plt.plot(this_f.meas_temp,
1e6 * this_f.susc_chi_volume,
label='%i' % (f) + ' Hz')
plt.legend()
plt.xlabel('Temperature (K)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = ' + '%7.2e' % (b) + ' T')
plotnum += 1
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_frequency.{}'.format(fmt)
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
## plot chi versus frequency at constant B
b = Bs.max()
t = Ts.min()
this_t = chi_data[chi_data.meas_temp == t]
this_t = this_t[this_t.meas_field_ac == b]
plt.semilogx(this_t.meas_freq,
1e6 * this_t.susc_chi_volume,
label='%i' % (t) + ' K')
plt.legend()
plt.xlabel('Frequency (Hz)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = ' + '%7.2e' % (b) + ' T')
if show_plots:
pmagplotlib.draw_figs(figs)
ans = input("enter s[a]ve to save files, [return] to quit ")
if ans == 'a':
pmagplotlib.save_plots(figs, fnames)
sys.exit()
else:
sys.exit()
else:
pmagplotlib.save_plots(figs, fnames)
def main():
"""
NAME
mk_redo.py
DESCRIPTION
Makes thellier_redo and zeq_redo files from existing pmag_specimens format file
SYNTAX
mk_redo.py [-h] [command line options]
INPUT
takes specimens.txt formatted input file
OPTIONS
-h: prints help message and quits
-f FILE: specify input file, default is 'specimens.txt'
-F REDO: specify output file suffix, default is redo so that
output filenames are 'thellier_redo' for thellier data and 'zeq_redo' for direction only data
OUTPUT
makes a thellier_redo or a zeq_redo format file
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
zfile, tfile = 'zeq_redo', 'thellier_redo'
zredo, tredo = "", ""
dir_path = pmag.get_named_arg('-WD', '.')
inspec = pmag.get_named_arg('-f', 'specimens.txt')
if '-F' in sys.argv:
ind = sys.argv.index('-F')
redo = sys.argv[ind + 1]
tfile = redo
zfile = redo
inspec = pmag.resolve_file_name(inspec, dir_path)
zfile = pmag.resolve_file_name(zfile, dir_path)
tfile = pmag.resolve_file_name(tfile, dir_path)
#
# read in data
#
specs = []
prior_spec_data, file_type = pmag.magic_read(inspec)
if file_type != 'specimens':
print(file_type, " this is not a valid pmag_specimens file")
sys.exit()
outstrings = []
for spec in prior_spec_data:
tmp = spec["method_codes"].split(":")
meths = []
for meth in tmp:
methods = meth.strip().split('-')
for m in methods:
if m not in meths:
meths.append(m)
if 'DIR' in meths: # DE-BFL, DE-BFP or DE-FM
specs.append(spec['specimen'])
if 'dir_comp' in list(spec.keys(
)) and spec['dir_comp'] != "" and spec['dir_comp'] != " ":
comp_name = spec['dir_comp']
else:
comp_name = string.ascii_uppercase[
specs.count(spec['specimen']) - 1]
calculation_type = "DE-BFL" # assume default calculation type is best-fit line
if "BFP" in meths:
calculation_type = 'DE-BFP'
elif "FM" in meths:
calculation_type = 'DE-FM'
if zredo == "":
zredo = open(zfile, "w")
outstring = '%s %s %s %s %s \n' % (
spec["specimen"], calculation_type, spec["meas_step_min"],
spec["meas_step_max"], comp_name)
if outstring not in outstrings:
zredo.write(outstring)
outstrings.append(outstring) # only writes unique interpretions
elif "PI" in meths and "TRM" in meths: # thellier record
if tredo == "":
tredo = open(tfile, "w")
outstring = '%s %i %i \n' % (spec["specimen"],
float(spec["meas_step_min"]),
float(spec["meas_step_max"]))
if outstring not in outstrings:
tredo.write(outstring)
outstrings.append(outstring) # only writes unique interpretions
print('Redo files saved to: ', zfile, tfile)
def convert(**kwargs):
# initialize defaults
version_num=pmag.get_version()
citations="This study"
dir_path,demag='.','NRM'
depth_method='a'
dir_path = kwargs.get('dir_path', '.')
input_dir_path = kwargs.get('input_dir_path', dir_path)
output_dir_path = dir_path # rename dir_path after input_dir_path is set
noave = kwargs.get('noave', 0) # default (0) is DO average
csv_file = kwargs.get('csv_file', '')
meas_file = kwargs.get('meas_file', 'measurements.txt')
spec_file = kwargs.get('spec_file', 'specimens.txt')
samp_file = kwargs.get('samp_file', 'samples.txt')
site_file = kwargs.get('site_file', 'sites.txt')
loc_file = kwargs.get('loc_file', 'locations.txt')
lat = kwargs.get('lat', '')
lon = kwargs.get('lon', '')
# format variables
if csv_file=="":
filelist=os.listdir(input_dir_path) # read in list of files to import
else:
filelist=[csv_file]
# parsing the data
MeasRecs,SpecRecs,SampRecs,SiteRecs,LocRecs=[],[],[],[],[]
file_found = False
for f in filelist: # parse each file
year_warning = True
if f[-3:].lower()=='csv':
print('processing:', f)
file_found = True
# get correct full filename and read data
fname = pmag.resolve_file_name(f, input_dir_path)
full_file = open(fname)
file_input=full_file.readlines()
full_file.close()
keys=file_input[0].replace('\n','').split(',') # splits on underscores
keys=[k.strip('"') for k in keys]
if "Interval Top (cm) on SHLF" in keys:interval_key="Interval Top (cm) on SHLF"
elif " Interval Bot (cm) on SECT" in keys:interval_key=" Interval Bot (cm) on SECT"
elif "Offset (cm)" in keys: interval_key="Offset (cm)"
else: print("couldn't find interval or offset amount")
if "Top Depth (m)" in keys:depth_key="Top Depth (m)"
elif "CSF-A Top (m)" in keys:depth_key="CSF-A Top (m)"
elif "Depth CSF-A (m)" in keys:depth_key="Depth CSF-A (m)"
else: print("couldn't find depth")
if "CSF-B Top (m)" in keys: comp_depth_key="CSF-B Top (m)" # use this model if available
elif "Depth CSF-B (m)" in keys: comp_depth_key="Depth CSF-B (m)"
else: comp_depth_key=""; print("couldn't find composite depth")
if "Demag level (mT)" in keys:demag_key="Demag level (mT)"
elif "Demag Level (mT)" in keys: demag_key="Demag Level (mT)"
elif "Treatment Value" in keys: demag_key="Treatment Value"
else: print("couldn't find demag type")
if "Inclination (Tray- and Bkgrd-Corrected) (deg)" in keys:inc_key="Inclination (Tray- and Bkgrd-Corrected) (deg)"
elif "Inclination background + tray corrected (deg)" in keys:inc_key="Inclination background + tray corrected (deg)"
elif "Inclination background + tray corrected (\xc2\xb0)" in keys:inc_key="Inclination background + tray corrected (\xc2\xb0)"
elif "Inclination background & tray corrected (deg)" in keys:inc_key="Inclination background & tray corrected (deg)"
elif "Inclination background & tray corrected (deg)" in keys:inc_key="Inclination background & tray corrected (deg)"
elif "Inclination background & drift corrected (deg)" in keys:inc_key="Inclination background & drift corrected (deg)"
else: print("couldn't find inclination")
if "Declination (Tray- and Bkgrd-Corrected) (deg)" in keys:dec_key="Declination (Tray- and Bkgrd-Corrected) (deg)"
elif "Declination background + tray corrected (deg)" in keys:dec_key="Declination background + tray corrected (deg)"
elif "Declination background + tray corrected (\xc2\xb0)" in keys:dec_key="Declination background + tray corrected (\xc2\xb0)"
elif "Declination background & tray corrected (deg)" in keys:dec_key="Declination background & tray corrected (deg)"
elif "Declination background & tray corrected (deg)" in keys:dec_key="Declination background & tray corrected (deg)"
elif "Declination background & drift corrected (deg)" in keys:dec_key="Declination background & drift corrected (deg)"
else: print("couldn't find declination")
if "Intensity (Tray- and Bkgrd-Corrected) (A/m)" in keys:int_key="Intensity (Tray- and Bkgrd-Corrected) (A/m)"
elif "Intensity background + tray corrected (A/m)" in keys:int_key="Intensity background + tray corrected (A/m)"
elif "Intensity background & tray corrected (A/m)" in keys:int_key="Intensity background & tray corrected (A/m)"
elif "Intensity background & tray corrected (A/m)" in keys:int_key="Intensity background & tray corrected (A/m)"
elif "Intensity background & drift corrected (A/m)" in keys:int_key="Intensity background & drift corrected (A/m)"
else: print("couldn't find magnetic moment")
if "Core Type" in keys:
core_type="Core Type"
elif "Type" in keys: core_type="Type"
else: print("couldn't find core type")
if 'Run Number' in keys: run_number_key='Run Number'
elif 'Test No.' in keys: run_number_key='Test No.'
else: print("couldn't find run number")
if 'Test Changed On' in keys: date_key='Test Changed On'
elif "Timestamp (UTC)" in keys: date_key="Timestamp (UTC)"
else: print("couldn't find timestamp")
if "Section" in keys: sect_key="Section"
elif "Sect" in keys: sect_key="Sect"
else: print("couldn't find section number")
if 'Section Half' in keys: half_key='Section Half'
elif "A/W" in keys: half_key="A/W"
else: print("couldn't find half number")
if "Text ID" in keys: text_id="Text ID"
elif "Text Id" in keys: text_id="Text Id"
else: print("couldn't find ID number")
for line in file_input[1:]:
InRec={}
test=0
recs=line.split(',')
for k in range(len(keys)):
if len(recs)==len(keys):
InRec[keys[k]]=line.split(',')[k].strip(""" " ' """)
if 'Exp' in list(InRec.keys()) and InRec['Exp']!="": test=1 # get rid of pesky blank lines (why is this a thing?)
if not test: continue
run_number=""
inst="IODP-SRM"
volume='15.59' # set default volume to this
if 'Sample Area (cm?)' in list(InRec.keys()) and InRec['Sample Area (cm?)']!= "": volume=InRec['Sample Area (cm?)']
MeasRec,SpecRec,SampRec,SiteRec,LocRec={},{},{},{},{}
expedition=InRec['Exp']
location=InRec['Site']+InRec['Hole']
# Maintain backward compatibility for the ever-changing LIMS format (Argh!)
while len(InRec['Core'])<3:
InRec['Core']='0'+InRec['Core']
if "Last Tray Measurment" in list(InRec.keys()) and "SHLF" not in InRec[text_id] or 'dscr' in csv_file : # assume discrete sample
specimen=expedition+'-'+location+'-'+InRec['Core']+InRec[core_type]+"-"+InRec[sect_key]+'-'+InRec[half_key]+'-'+str(InRec[interval_key])
else: # mark as continuous measurements
specimen=expedition+'-'+location+'-'+InRec['Core']+InRec[core_type]+"_"+InRec[sect_key]+InRec[half_key]+'-'+str(InRec[interval_key])
sample = expedition+'-'+location+'-'+InRec['Core']+InRec[core_type]
site = expedition+'-'+location
if not InRec[dec_key] or not InRec[inc_key]:
print("No dec or inc found for specimen %s, skipping"%specimen); continue
if specimen!="" and specimen not in [x['specimen'] if 'specimen' in list(x.keys()) else "" for x in SpecRecs]:
SpecRec['specimen'] = specimen
SpecRec['sample'] = sample
SpecRec['citations']=citations
SpecRec['volume'] = volume
SpecRec['specimen_alternatives']=InRec[text_id]
SpecRecs.append(SpecRec)
if sample!="" and sample not in [x['sample'] if 'sample' in list(x.keys()) else "" for x in SampRecs]:
SampRec['sample'] = sample
SampRec['site'] = site
SampRec['citations']=citations
SampRec['azimuth']='0'
SampRec['dip']='0'
SampRec['core_depth']=InRec[depth_key]
if comp_depth_key!='':
SampRec['composite_depth']=InRec[comp_depth_key]
if "SHLF" not in InRec[text_id]:
SampRec['method_codes']='FS-C-DRILL-IODP:SP-SS-C:SO-V'
else:
SampRec['method_codes']='FS-C-DRILL-IODP:SO-V'
SampRecs.append(SampRec)
if site!="" and site not in [x['site'] if 'site' in list(x.keys()) else "" for x in SiteRecs]:
SiteRec['site'] = site
SiteRec['location'] = location
SiteRec['citations']=citations
SiteRec['lat'] = lat
SiteRec['lon'] = lon
SiteRecs.append(SiteRec)
if location!="" and location not in [x['location'] if 'location' in list(x.keys()) else "" for x in LocRecs]:
LocRec['location']=location
LocRec['citations']=citations
LocRec['expedition_name']=expedition
LocRec['lat_n'] = lat
LocRec['lon_e'] = lon
LocRec['lat_s'] = lat
LocRec['lon_w'] = lon
LocRecs.append(LocRec)
MeasRec['specimen'] = specimen
MeasRec['magic_software_packages']=version_num
MeasRec["treat_temp"]='%8.3e' % (273) # room temp in kelvin
MeasRec["meas_temp"]='%8.3e' % (273) # room temp in kelvin
MeasRec["treat_ac_field"]=0
MeasRec["treat_dc_field"]='0'
MeasRec["treat_dc_field_phi"]='0'
MeasRec["treat_dc_field_theta"]='0'
MeasRec["quality"]='g' # assume all data are "good"
MeasRec["standard"]='u' # assume all data are "good"
if run_number_key in list(InRec.keys()) and InRec[run_number_key]!= "": run_number=InRec[run_number_key]
datestamp=InRec[date_key].split() # date time is second line of file
if '/' in datestamp[0]:
mmddyy=datestamp[0].split('/') # break into month day year
if len(mmddyy[0])==1: mmddyy[0]='0'+mmddyy[0] # make 2 characters
if len(mmddyy[1])==1: mmddyy[1]='0'+mmddyy[1] # make 2 characters
if len(mmddyy[2])==1: mmddyy[2] = '0'+mmddyy[2] # make 2 characters
if len(datestamp[1])==1: datestamp[1]='0'+datestamp[1] # make 2 characters
hour, minute = datestamp[1].split(':')
if len(hour) == 1:
hour = '0' + hour
date=mmddyy[0]+':'+mmddyy[1]+":"+mmddyy[2] +':' + hour + ":" + minute + ":00"
#date=mmddyy[2] + ':'+mmddyy[0]+":"+mmddyy[1] +':' + hour + ":" + minute + ":00"
if '-' in datestamp[0]:
mmddyy=datestamp[0].split('-') # break into month day year
date=mmddyy[0]+':'+mmddyy[1]+":"+mmddyy[2] +':' +datestamp[1]+":0"
if len(date.split(":")) > 6: date=date[:-2]
# try with month:day:year
try:
utc_dt = datetime.datetime.strptime(date, "%m:%d:%Y:%H:%M:%S")
except ValueError:
# try with year:month:day
try:
utc_dt = datetime.datetime.strptime(date, "%Y:%m:%d:%H:%M:%S")
except ValueError:
# if all else fails, assume the year is in the third position
# and try padding with '20'
new_date = pad_year(date, ind=2, warn=year_warning, fname=os.path.split(f)[1])
utc_dt = datetime.datetime.strptime(new_date, "%m:%d:%Y:%H:%M:%S")
# only give warning once per csv file
year_warning = False
MeasRec['timestamp']=utc_dt.strftime("%Y-%m-%dT%H:%M:%S")+"Z"
MeasRec["method_codes"]='LT-NO'
if 'Treatment Type' in list(InRec.keys()) and InRec['Treatment Type']!="":
if "AF" in InRec['Treatment Type'].upper():
MeasRec['method_codes'] = 'LT-AF-Z'
inst=inst+':IODP-SRM-AF' # measured on shipboard in-line 2G AF
treatment_value=float(InRec[demag_key].strip('"'))*1e-3 # convert mT => T
MeasRec["treat_ac_field"]=treatment_value # AF demag in treat mT => T
elif "T" in InRec['Treatment Type'].upper():
MeasRec['method_codes'] = 'LT-T-Z'
inst=inst+':IODP-TDS' # measured on shipboard Schonstedt thermal demagnetizer
treatment_value=float(InRec['Treatment Value'])+273 # convert C => K
MeasRec["treat_temp"]=treatment_value
elif 'Alternating Frequency' in InRec['Treatment Type']:
MeasRec['method_codes'] = 'LT-AF-Z'
inst=inst+':IODP-DTECH' # measured on shipboard Dtech D2000
treatment_value=float(InRec[demag_key])*1e-3 # convert mT => T
MeasRec["treat_ac_field"]=treatment_value # AF demag in treat mT => T
elif 'Thermal' in InRec['Treatment Type']:
MeasRec['method_codes'] = 'LT-T-Z'
inst=inst+':IODP-TDS' # measured on shipboard Schonstedt thermal demagnetizer
treatment_value=float(InRec[demag_key])+273 # convert C => K
MeasRec["treat_temp"]='%8.3e'%(treatment_value) #
elif InRec[demag_key]!="0":
MeasRec['method_codes'] = 'LT-AF-Z'
inst=inst+':IODP-SRM-AF' # measured on shipboard in-line 2G AF
try: treatment_value=float(InRec[demag_key])*1e-3 # convert mT => T
except ValueError: print("Couldn't determine treatment value was given treatment value of %s and demag key %s; setting to blank you will have to manually correct this (or fix it)"%(InRec[demag_key], demag_key)); treatment_value=''
MeasRec["treat_ac_field"]=treatment_value # AF demag in treat mT => T
MeasRec["standard"]='u' # assume all data are "good"
vol=float(volume)*1e-6 # convert from cc to m^3
if run_number!="":
MeasRec['external_database_ids']={'LIMS':run_number}
else:
MeasRec['external_database_ids']=""
MeasRec['dir_inc']=InRec[inc_key]
MeasRec['dir_dec']=InRec[dec_key]
intens = InRec[int_key]
try: MeasRec['magn_moment']='%8.3e'%(float(intens)*vol) # convert intensity from A/m to Am^2 using vol
except ValueError: print("couldn't find magnetic moment for specimen %s and int_key %s; leaving this field blank you'll have to fix this manually"%(specimen, int_key)); MeasRec['magn_moment']=''
MeasRec['instrument_codes']=inst
MeasRec['treat_step_num']='1'
MeasRec['dir_csd']='0'
MeasRec['meas_n_orient']=''
MeasRecs.append(MeasRec)
if not file_found:
print("No .csv files were found")
return (False, "No .csv files were found")
con = nb.Contribution(output_dir_path,read_tables=[])
con.add_magic_table_from_data(dtype='specimens', data=SpecRecs)
con.add_magic_table_from_data(dtype='samples', data=SampRecs)
con.add_magic_table_from_data(dtype='sites', data=SiteRecs)
con.add_magic_table_from_data(dtype='locations', data=LocRecs)
#MeasSort=sorted(MeasRecs,key=lambda x: (x['specimen'], float(x['treat_ac_field'])))
#MeasSort=sorted(MeasRecs,key=lambda x: float(x['treat_ac_field']))
#MeasOuts=pmag.measurements_methods3(MeasSort,noave)
MeasOuts=pmag.measurements_methods3(MeasRecs,noave)
con.add_magic_table_from_data(dtype='measurements', data=MeasOuts)
con.write_table_to_file('specimens', custom_name=spec_file)
con.write_table_to_file('samples', custom_name=samp_file)
con.write_table_to_file('sites', custom_name=site_file)
con.write_table_to_file('locations', custom_name=loc_file)
con.write_table_to_file('measurements', custom_name=meas_file)
return (True, meas_file)
def main():
"""
NAME
foldtest_magic.py
DESCRIPTION
does a fold test (Tauxe, 2010) on data
INPUT FORMAT
pmag_specimens format file, er_samples.txt format file (for bedding)
SYNTAX
foldtest_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f sites formatted file [default for 3.0 is sites.txt, for 2.5, pmag_sites.txt]
-fsa samples formatted file
-fsi sites formatted file
-exc use criteria to set acceptance criteria (supported only for data model 3)
-n NB, set number of bootstraps, default is 1000
-b MIN, MAX, set bounds for untilting, default is -10, 150
-fmt FMT, specify format - default is svg
-sav saves plots and quits
-DM NUM MagIC data model number (2 or 3, default 3)
OUTPUT
Geographic: is an equal area projection of the input data in
original coordinates
Stratigraphic: is an equal area projection of the input data in
tilt adjusted coordinates
% Untilting: The dashed (red) curves are representative plots of
maximum eigenvalue (tau_1) as a function of untilting
The solid line is the cumulative distribution of the
% Untilting required to maximize tau for all the
bootstrapped data sets. The dashed vertical lines
are 95% confidence bounds on the % untilting that yields
the most clustered result (maximum tau_1).
Command line: prints out the bootstrapped iterations and
finally the confidence bounds on optimum untilting.
If the 95% conf bounds include 0, then a pre-tilt magnetization is indicated
If the 95% conf bounds include 100, then a post-tilt magnetization is indicated
If the 95% conf bounds exclude both 0 and 100, syn-tilt magnetization is
possible as is vertical axis rotation or other pathologies
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
kappa = 0
dir_path = pmag.get_named_arg("-WD", ".")
nboot = int(float(pmag.get_named_arg("-n", 1000))) # number of bootstraps
fmt = pmag.get_named_arg("-fmt", "svg")
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
if data_model_num == 3:
infile = pmag.get_named_arg("-f", 'sites.txt')
orfile = 'samples.txt'
site_col = 'site'
dec_col = 'dir_dec'
inc_col = 'dir_inc'
tilt_col = 'dir_tilt_correction'
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
crit_col = 'criterion'
critfile = 'criteria.txt'
else:
infile = pmag.get_named_arg("-f", 'pmag_sites.txt')
orfile = 'er_samples.txt'
site_col = 'er_site_name'
dec_col = 'site_dec'
inc_col = 'site_inc'
tilt_col = 'site_tilt_correction'
dipkey, azkey = 'sample_bed_dip', 'sample_bed_dip_direction'
crit_col = 'pmag_criteria_code'
critfile = 'pmag_criteria.txt'
if '-sav' in sys.argv:
plot = 1
else:
plot = 0
if '-b' in sys.argv:
ind = sys.argv.index('-b')
untilt_min = int(sys.argv[ind + 1])
untilt_max = int(sys.argv[ind + 2])
else:
untilt_min, untilt_max = -10, 150
if '-fsa' in sys.argv:
orfile = pmag.get_named_arg("-fsa", "")
elif '-fsi' in sys.argv:
orfile = pmag.get_named_arg("-fsi", "")
if data_model_num == 3:
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
else:
dipkey, azkey = 'site_bed_dip', 'site_bed_dip_direction'
else:
if data_model_num == 3:
orfile = 'sites.txt'
else:
orfile = 'pmag_sites.txt'
orfile = pmag.resolve_file_name(orfile, dir_path)
infile = pmag.resolve_file_name(infile, dir_path)
critfile = pmag.resolve_file_name(critfile, dir_path)
df = pd.read_csv(infile, sep='\t', header=1)
# keep only records with tilt_col
data = df.copy()
data = data[data[tilt_col].notnull()]
data = data.where(data.notnull(), "")
# turn into pmag data list
data = list(data.T.apply(dict))
# get orientation data
if data_model_num == 3:
# often orientation will be in infile (sites table)
if os.path.split(orfile)[1] == os.path.split(infile)[1]:
ordata = df[df[azkey].notnull()]
ordata = ordata[ordata[dipkey].notnull()]
ordata = list(ordata.T.apply(dict))
# sometimes orientation might be in a sample file instead
else:
ordata = pd.read_csv(orfile, sep='\t', header=1)
ordata = list(ordata.T.apply(dict))
else:
ordata, file_type = pmag.magic_read(orfile)
if '-exc' in sys.argv:
crits, file_type = pmag.magic_read(critfile)
SiteCrits = []
for crit in crits:
if crit[crit_col] == "DE-SITE":
SiteCrits.append(crit)
#break
# get to work
#
PLTS = {'geo': 1, 'strat': 2, 'taus': 3} # make plot dictionary
if not set_env.IS_WIN:
pmagplotlib.plot_init(PLTS['geo'], 5, 5)
pmagplotlib.plot_init(PLTS['strat'], 5, 5)
pmagplotlib.plot_init(PLTS['taus'], 5, 5)
if data_model_num == 2:
GEOrecs = pmag.get_dictitem(data, tilt_col, '0', 'T')
else:
GEOrecs = data
if len(GEOrecs) > 0: # have some geographic data
num_dropped = 0
DIDDs = [] # set up list for dec inc dip_direction, dip
for rec in GEOrecs: # parse data
dip, dip_dir = 0, -1
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
orecs = pmag.get_dictitem(ordata, site_col, rec[site_col], 'T')
if len(orecs) > 0:
if orecs[0][azkey] != "":
dip_dir = float(orecs[0][azkey])
if orecs[0][dipkey] != "":
dip = float(orecs[0][dipkey])
if dip != 0 and dip_dir != -1:
if '-exc' in sys.argv:
keep = 1
for site_crit in SiteCrits:
crit_name = site_crit['table_column'].split('.')[1]
if crit_name and crit_name in rec.keys(
) and rec[crit_name]:
# get the correct operation (<, >=, =, etc.)
op = OPS[site_crit['criterion_operation']]
# then make sure the site record passes
if op(float(rec[crit_name]),
float(site_crit['criterion_value'])):
keep = 0
if keep == 1:
DIDDs.append([Dec, Inc, dip_dir, dip])
else:
num_dropped += 1
else:
DIDDs.append([Dec, Inc, dip_dir, dip])
if num_dropped:
print(
"-W- Dropped {} records because each failed one or more criteria"
.format(num_dropped))
else:
print('no geographic directional data found')
sys.exit()
pmagplotlib.plot_eq(PLTS['geo'], DIDDs, 'Geographic')
data = np.array(DIDDs)
D, I = pmag.dotilt_V(data)
TCs = np.array([D, I]).transpose()
pmagplotlib.plot_eq(PLTS['strat'], TCs, 'Stratigraphic')
if plot == 0:
pmagplotlib.draw_figs(PLTS)
Percs = list(range(untilt_min, untilt_max))
Cdf, Untilt = [], []
plt.figure(num=PLTS['taus'])
print('doing ', nboot, ' iterations...please be patient.....')
for n in range(
nboot
): # do bootstrap data sets - plot first 25 as dashed red line
if n % 50 == 0:
print(n)
Taus = [] # set up lists for taus
PDs = pmag.pseudo(DIDDs)
if kappa != 0:
for k in range(len(PDs)):
d, i = pmag.fshdev(kappa)
dipdir, dip = pmag.dodirot(d, i, PDs[k][2], PDs[k][3])
PDs[k][2] = dipdir
PDs[k][3] = dip
for perc in Percs:
tilt = np.array([1., 1., 1., 0.01 * perc])
D, I = pmag.dotilt_V(PDs * tilt)
TCs = np.array([D, I]).transpose()
ppars = pmag.doprinc(TCs) # get principal directions
Taus.append(ppars['tau1'])
if n < 25:
plt.plot(Percs, Taus, 'r--')
# tilt that gives maximum tau
Untilt.append(Percs[Taus.index(np.max(Taus))])
Cdf.append(float(n) / float(nboot))
plt.plot(Percs, Taus, 'k')
plt.xlabel('% Untilting')
plt.ylabel('tau_1 (red), CDF (green)')
Untilt.sort() # now for CDF of tilt of maximum tau
plt.plot(Untilt, Cdf, 'g')
lower = int(.025 * nboot)
upper = int(.975 * nboot)
plt.axvline(x=Untilt[lower], ymin=0, ymax=1, linewidth=1, linestyle='--')
plt.axvline(x=Untilt[upper], ymin=0, ymax=1, linewidth=1, linestyle='--')
tit = '%i - %i %s' % (Untilt[lower], Untilt[upper], 'Percent Unfolding')
print(tit)
plt.title(tit)
if plot == 0:
pmagplotlib.draw_figs(PLTS)
ans = input('S[a]ve all figures, <Return> to quit \n ')
if ans != 'a':
print("Good bye")
sys.exit()
files = {}
for key in list(PLTS.keys()):
files[key] = ('foldtest_' + '%s' % (key.strip()[:2]) + '.' + fmt)
pmagplotlib.save_plots(PLTS, files)
def main():
"""
NAME
thellier_magic.py
DESCRIPTION
plots Thellier-Thellier data in version 3.0 format
Reads saved interpretations from a specimen formatted table, default: specimens.txt
SYNTAX
thellier_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEAS, set measurements input file, default is 'measurements.txt'
-WD: directory to output files to (default : current directory)
Note: if using Windows, all figures will output to current directory
-ID: directory to read files from (default : same as -WD)
-fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots without review (in format specified by -fmt key or default)
-spc SPEC, plots single specimen SPEC, saves plot with specified format
with optional -b bounds and quits
-n SPECIMENS, number of specimens to plot
OUTPUT
figures:
ALL: numbers refer to temperature steps in command line window
1) Arai plot: closed circles are zero-field first/infield
open circles are infield first/zero-field
triangles are pTRM checks
squares are pTRM tail checks
VDS is vector difference sum
diamonds are bounds for interpretation
2) Zijderveld plot: closed (open) symbols are X-Y (X-Z) planes
X rotated to NRM direction
3) (De/Re)Magnetization diagram:
circles are NRM remaining
squares are pTRM gained
4) equal area projections:
green triangles are pTRM gained direction
red (purple) circles are lower(upper) hemisphere of ZI step directions
blue (cyan) squares are lower(upper) hemisphere IZ step directions
5) Optional: TRM acquisition
6) Optional: TDS normalization
command line window:
list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of measuements)
list of possible commands: type letter followed by return to select option
saving of plots creates image files with specimen, plot type as name
"""
#
# parse command line options
#
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", default_val=".")
input_dir_path = pmag.get_named_arg('-ID', "")
input_dir_path, dir_path = pmag.fix_directories(input_dir_path, dir_path)
meas_file = pmag.get_named_arg(
"-f", default_val="measurements.txt")
#spec_file = pmag.get_named_arg(
# "-fsp", default_val="specimens.txt")
#crit_file = pmag.get_named_arg("-fcr", default_val="criteria.txt")
#spec_file = os.path.join(dir_path, spec_file)
#crit_file = os.path.join(dir_path, crit_file)
meas_file = pmag.resolve_file_name(meas_file, input_dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
save_plots = False
interactive = True
if '-sav' in sys.argv:
save_plots = True
interactive=False
spec = pmag.get_named_arg("-spc", default_val="")
n_specs = pmag.get_named_arg("-n", default_val="all")
try:
n_specs = int(n_specs)
except ValueError:
pass
ipmag.thellier_magic(meas_file, dir_path, input_dir_path,
spec, n_specs, save_plots, fmt, interactive)
def main():
"""
NAME
foldtest_magic.py
DESCRIPTION
does a fold test (Tauxe, 2010) on data
INPUT FORMAT
pmag_specimens format file, er_samples.txt format file (for bedding)
SYNTAX
foldtest_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f sites formatted file [default for 3.0 is sites.txt, for 2.5, pmag_sites.txt]
-fsa samples formatted file
-fsi sites formatted file
-exc use criteria to set acceptance criteria (supported only for data model 3)
-n NB, set number of bootstraps, default is 1000
-b MIN, MAX, set bounds for untilting, default is -10, 150
-fmt FMT, specify format - default is svg
-sav saves plots and quits
-DM NUM MagIC data model number (2 or 3, default 3)
OUTPUT
Geographic: is an equal area projection of the input data in
original coordinates
Stratigraphic: is an equal area projection of the input data in
tilt adjusted coordinates
% Untilting: The dashed (red) curves are representative plots of
maximum eigenvalue (tau_1) as a function of untilting
The solid line is the cumulative distribution of the
% Untilting required to maximize tau for all the
bootstrapped data sets. The dashed vertical lines
are 95% confidence bounds on the % untilting that yields
the most clustered result (maximum tau_1).
Command line: prints out the bootstrapped iterations and
finally the confidence bounds on optimum untilting.
If the 95% conf bounds include 0, then a pre-tilt magnetization is indicated
If the 95% conf bounds include 100, then a post-tilt magnetization is indicated
If the 95% conf bounds exclude both 0 and 100, syn-tilt magnetization is
possible as is vertical axis rotation or other pathologies
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
kappa = 0
dir_path = pmag.get_named_arg("-WD", ".")
nboot = int(float(pmag.get_named_arg("-n", 1000))) # number of bootstraps
fmt = pmag.get_named_arg("-fmt", "svg")
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
if data_model_num == 3:
infile = pmag.get_named_arg("-f", 'sites.txt')
orfile = 'samples.txt'
site_col = 'site'
dec_col = 'dir_dec'
inc_col = 'dir_inc'
tilt_col = 'dir_tilt_correction'
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
crit_col = 'criterion'
critfile = 'criteria.txt'
else:
infile = pmag.get_named_arg("-f", 'pmag_sites.txt')
orfile = 'er_samples.txt'
site_col = 'er_site_name'
dec_col = 'site_dec'
inc_col = 'site_inc'
tilt_col = 'site_tilt_correction'
dipkey, azkey = 'sample_bed_dip', 'sample_bed_dip_direction'
crit_col = 'pmag_criteria_code'
critfile = 'pmag_criteria.txt'
if '-sav' in sys.argv:
plot = 1
else:
plot = 0
if '-b' in sys.argv:
ind = sys.argv.index('-b')
untilt_min = int(sys.argv[ind+1])
untilt_max = int(sys.argv[ind+2])
else:
untilt_min, untilt_max = -10, 150
if '-fsa' in sys.argv:
orfile = pmag.get_named_arg("-fsa", "")
elif '-fsi' in sys.argv:
orfile = pmag.get_named_arg("-fsi", "")
if data_model_num == 3:
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
else:
dipkey, azkey = 'site_bed_dip', 'site_bed_dip_direction'
else:
if data_model_num == 3:
orfile = 'sites.txt'
else:
orfile = 'pmag_sites.txt'
orfile = pmag.resolve_file_name(orfile, dir_path)
infile = pmag.resolve_file_name(infile, dir_path)
critfile = pmag.resolve_file_name(critfile, dir_path)
df = pd.read_csv(infile, sep='\t', header=1)
# keep only records with tilt_col
data = df.copy()
data = data[data[tilt_col].notnull()]
data = data.where(data.notnull(), "")
# turn into pmag data list
data = list(data.T.apply(dict))
# get orientation data
if data_model_num == 3:
# often orientation will be in infile (sites table)
if os.path.split(orfile)[1] == os.path.split(infile)[1]:
ordata = df[df[azkey].notnull()]
ordata = ordata[ordata[dipkey].notnull()]
ordata = list(ordata.T.apply(dict))
# sometimes orientation might be in a sample file instead
else:
ordata = pd.read_csv(orfile, sep='\t', header=1)
ordata = list(ordata.T.apply(dict))
else:
ordata, file_type = pmag.magic_read(orfile)
if '-exc' in sys.argv:
crits, file_type = pmag.magic_read(critfile)
SiteCrits = []
for crit in crits:
if crit[crit_col] == "DE-SITE":
SiteCrits.append(crit)
#break
# get to work
#
PLTS = {'geo': 1, 'strat': 2, 'taus': 3} # make plot dictionary
if not set_env.IS_WIN:
pmagplotlib.plot_init(PLTS['geo'], 5, 5)
pmagplotlib.plot_init(PLTS['strat'], 5, 5)
pmagplotlib.plot_init(PLTS['taus'], 5, 5)
if data_model_num == 2:
GEOrecs = pmag.get_dictitem(data, tilt_col, '0', 'T')
else:
GEOrecs = data
if len(GEOrecs) > 0: # have some geographic data
num_dropped = 0
DIDDs = [] # set up list for dec inc dip_direction, dip
for rec in GEOrecs: # parse data
dip, dip_dir = 0, -1
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
orecs = pmag.get_dictitem(
ordata, site_col, rec[site_col], 'T')
if len(orecs) > 0:
if orecs[0][azkey] != "":
dip_dir = float(orecs[0][azkey])
if orecs[0][dipkey] != "":
dip = float(orecs[0][dipkey])
if dip != 0 and dip_dir != -1:
if '-exc' in sys.argv:
keep = 1
for site_crit in SiteCrits:
crit_name = site_crit['table_column'].split('.')[1]
if crit_name and crit_name in rec.keys() and rec[crit_name]:
# get the correct operation (<, >=, =, etc.)
op = OPS[site_crit['criterion_operation']]
# then make sure the site record passes
if op(float(rec[crit_name]), float(site_crit['criterion_value'])):
keep = 0
if keep == 1:
DIDDs.append([Dec, Inc, dip_dir, dip])
else:
num_dropped += 1
else:
DIDDs.append([Dec, Inc, dip_dir, dip])
if num_dropped:
print("-W- Dropped {} records because each failed one or more criteria".format(num_dropped))
else:
print('no geographic directional data found')
sys.exit()
pmagplotlib.plot_eq(PLTS['geo'], DIDDs, 'Geographic')
data = np.array(DIDDs)
D, I = pmag.dotilt_V(data)
TCs = np.array([D, I]).transpose()
pmagplotlib.plot_eq(PLTS['strat'], TCs, 'Stratigraphic')
if plot == 0:
pmagplotlib.draw_figs(PLTS)
Percs = list(range(untilt_min, untilt_max))
Cdf, Untilt = [], []
plt.figure(num=PLTS['taus'])
print('doing ', nboot, ' iterations...please be patient.....')
for n in range(nboot): # do bootstrap data sets - plot first 25 as dashed red line
if n % 50 == 0:
print(n)
Taus = [] # set up lists for taus
PDs = pmag.pseudo(DIDDs)
if kappa != 0:
for k in range(len(PDs)):
d, i = pmag.fshdev(kappa)
dipdir, dip = pmag.dodirot(d, i, PDs[k][2], PDs[k][3])
PDs[k][2] = dipdir
PDs[k][3] = dip
for perc in Percs:
tilt = np.array([1., 1., 1., 0.01*perc])
D, I = pmag.dotilt_V(PDs*tilt)
TCs = np.array([D, I]).transpose()
ppars = pmag.doprinc(TCs) # get principal directions
Taus.append(ppars['tau1'])
if n < 25:
plt.plot(Percs, Taus, 'r--')
# tilt that gives maximum tau
Untilt.append(Percs[Taus.index(np.max(Taus))])
Cdf.append(float(n) / float(nboot))
plt.plot(Percs, Taus, 'k')
plt.xlabel('% Untilting')
plt.ylabel('tau_1 (red), CDF (green)')
Untilt.sort() # now for CDF of tilt of maximum tau
plt.plot(Untilt, Cdf, 'g')
lower = int(.025*nboot)
upper = int(.975*nboot)
plt.axvline(x=Untilt[lower], ymin=0, ymax=1, linewidth=1, linestyle='--')
plt.axvline(x=Untilt[upper], ymin=0, ymax=1, linewidth=1, linestyle='--')
tit = '%i - %i %s' % (Untilt[lower], Untilt[upper], 'Percent Unfolding')
print(tit)
plt.title(tit)
if plot == 0:
pmagplotlib.draw_figs(PLTS)
ans = input('S[a]ve all figures, <Return> to quit \n ')
if ans != 'a':
print("Good bye")
sys.exit()
files = {}
for key in list(PLTS.keys()):
files[key] = ('foldtest_'+'%s' % (key.strip()[:2])+'.'+fmt)
pmagplotlib.save_plots(PLTS, files)
def main():
"""
NAME
lnp_magic.py
DESCRIPTION
makes equal area projections site by site
from specimen formatted file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
SYNTAX
lnp_magic [command line options]
INPUT
takes magic formatted specimens file
OUPUT
prints site_name n_lines n_planes K alpha95 dec inc R
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is 'specimens.txt', ('pmag_specimens.txt' for legacy data model 2)
-fsa FILE: specify samples file, required to plot by site for data model 3 (otherwise will plot by sample)
default is 'samples.txt'
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is specimen
-fmt [svg,png,jpg] format for plots, default is svg
-sav save plots and quit
-P: do not plot
-F FILE, specify output file of dec, inc, alpha95 data for plotting with plotdi_a and plotdi_e
-exc use criteria in criteria table # NOT IMPLEMENTED
-DM NUMBER MagIC data model (2 or 3, default 3)
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", ".")
data_model = int(float(pmag.get_named_arg("-DM", 3)))
fmt = pmag.get_named_arg("-fmt", 'svg')
if data_model == 2:
in_file = pmag.get_named_arg('-f', 'pmag_specimens.txt')
crit_file = "pmag_criteria.txt"
else:
in_file = pmag.get_named_arg('-f', 'specimens.txt')
samp_file = pmag.get_named_arg('-fsa', 'samples.txt')
crit_file = "criteria.txt"
in_file = pmag.resolve_file_name(in_file, dir_path)
dir_path = os.path.split(in_file)[0]
if data_model == 3:
samp_file = pmag.resolve_file_name(samp_file, dir_path)
if '-crd' in sys.argv:
ind = sys.argv.index("-crd")
crd = sys.argv[ind+1]
if crd == 's':
coord = "-1"
if crd == 'g':
coord = "0"
if crd == 't':
coord = "100"
else:
coord = "-1"
out_file = pmag.get_named_arg('-F', '')
if out_file:
out = open(dir_path+'/'+out_file, 'w')
if '-P' in sys.argv:
make_plots = 0 # do not plot
else:
make_plots = 1 # do plot
if '-sav' in sys.argv:
plot = 1 # save plots and quit
else:
plot = 0 # show plots intereactively (if make_plots)
#
if data_model == 2:
Specs, file_type = pmag.magic_read(in_file)
if 'specimens' not in file_type:
print('Error opening ', in_file, file_type)
sys.exit()
else:
fnames = {'specimens': in_file, 'samples': samp_file}
con = cb.Contribution(dir_path, read_tables=['samples', 'specimens'],
custom_filenames=fnames)
con.propagate_name_down('site', 'specimens')
if 'site' in con.tables['specimens'].df.columns:
site_col = 'site'
else:
site_col = 'sample'
tilt_corr_col = "dir_tilt_correction"
mad_col = "dir_mad_free"
alpha95_col = "dir_alpha95"
site_alpha95_col = "dir_alpha95"
dec_col = "dir_dec"
inc_col = "dir_inc"
num_meas_col = "dir_n_measurements"
k_col = "dir_k"
cols = [site_col, tilt_corr_col, mad_col, alpha95_col, dec_col, inc_col]
con.tables['specimens'].front_and_backfill(cols)
con.tables['specimens'].df = con.tables['specimens'].df.where(con.tables['specimens'].df.notnull(), "")
Specs = con.tables['specimens'].convert_to_pmag_data_list()
## using criteria file was never fully implemented
#if '-exc' in sys.argv:
# Crits, file_type = pmag.magic_read(pmag.resolve_file_name(crit_file, dir_path))
# for crit in Crits:
# if mad_col in crit:
# M = float(crit['specimen_mad'])
# if num_meas_col in crit:
# N = float(crit['specimen_n'])
# if site_alpha95_col in crit and 'site' in crit:
# acutoff = float(crit['site_alpha95'])
# if k_col in crit:
# kcutoff = float(crit['site_k'])
#else:
# Crits = ""
sitelist = []
# initialize some variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
M, N, acutoff, kcutoff = 180., 1, 180., 0.
if data_model == 2:
site_col = 'er_site_name'
tilt_corr_col = "specimen_tilt_correction"
mad_col = "specimen_mad"
alpha95_col = 'specimen_alpha95'
dec_col = "specimen_dec"
inc_col = "specimen_inc"
num_meas_col = "specimen_n"
site_alpha95_col = "site_alpha95"
else: # data model 3
pass
for rec in Specs:
if rec[site_col] not in sitelist:
sitelist.append(rec[site_col])
sitelist.sort()
if make_plots == 1:
EQ = {}
EQ['eqarea'] = 1
for site in sitelist:
pmagplotlib.plot_init(EQ['eqarea'], 4, 4)
print(site)
data = []
for spec in Specs:
if tilt_corr_col not in list(spec.keys()):
spec[tilt_corr_col] = '-1' # assume unoriented
if spec[site_col] == site:
if mad_col not in list(spec.keys()) or spec[mad_col] == "":
if alpha95_col in list(spec.keys()) and spec[alpha95_col] != "":
spec[mad_col] = spec[alpha95_col]
else:
spec[mad_col] = '180'
if not spec[num_meas_col]:
continue
if (float(spec[tilt_corr_col]) == float(coord)) and (float(spec[mad_col]) <= M) and (float(spec[num_meas_col]) >= N):
rec = {}
for key in list(spec.keys()):
rec[key] = spec[key]
rec["dec"] = float(spec[dec_col])
rec["inc"] = float(spec[inc_col])
rec["tilt_correction"] = spec[tilt_corr_col]
data.append(rec)
if len(data) > 2:
fpars = pmag.dolnp(data, 'specimen_direction_type')
print("Site lines planes kappa a95 dec inc")
print(site, fpars["n_lines"], fpars["n_planes"], fpars["K"],
fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"])
if out_file != "":
if float(fpars["alpha95"]) <= acutoff and float(fpars["K"]) >= kcutoff:
out.write('%s %s %s\n' %
(fpars["dec"], fpars['inc'], fpars['alpha95']))
print('% tilt correction: ', coord)
if make_plots == 1:
files = {}
files['eqarea'] = site+'_'+crd+'_'+'eqarea'+'.'+fmt
pmagplotlib.plot_lnp(EQ['eqarea'], site,
data, fpars, 'specimen_direction_type')
if plot == 0:
pmagplotlib.draw_figs(EQ)
ans = input(
"s[a]ve plot, [q]uit, <return> to continue:\n ")
if ans == "a":
pmagplotlib.save_plots(EQ, files)
if ans == "q":
sys.exit()
else:
pmagplotlib.save_plots(EQ, files)
else:
print('skipping site - not enough data with specified coordinate system')
def main():
"""
NAME
strip_magic.py
DESCRIPTION
plots various parameters versus depth or age
SYNTAX
strip_magic.py [command line optins]
OPTIONS
-h prints help message and quits
-DM NUM: specify data model num, options 2 (legacy) or 3 (default)
-f FILE: specify input magic format file from magic,default='pmag_results.txt'
supported types=[pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
-obj [sit,sam,all]: specify object to site,sample,all for pmag_result table, default is all
-fmt [svg,png,jpg], format for images - default is svg
-x [age,pos]: specify whether age or stratigraphic position
-y [dec,inc,int,chi,lat,lon,vdm,vadm]
(lat and lon are VGP lat and lon)
-Iex: plot the expected inc at lat - only available for results with lat info in file
-ts TS amin amax: plot the GPTS for the time interval between amin and amax (numbers in Ma)
TS: [ck95, gts04]
-mcd method_code, specify method code, default is first one encountered
-sav save plot and quit
NOTES
when x and/or y are not specified, a list of possibilities will be presented to the user for choosing
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
xaxis, xplotind, yplotind = "", 0, 0 # (0 for strat pos)
yaxis, Xinc = "", ""
plot = 0
obj = 'all'
data_model_num = int(pmag.get_named_arg("-DM", 3))
# 2.5 keys
if data_model_num == 2:
supported = [
'pmag_specimens', 'pmag_samples', 'pmag_sites', 'pmag_results',
'magic_web'
] # available file types
Depth_keys = [
'specimen_core_depth', 'specimen_height', 'specimen_elevation',
'specimen_composite_depth', 'sample_core_depth', 'sample_height',
'sample_elevation', 'sample_composite_depth', 'site_core_depth',
'site_height', 'site_elevation', 'site_composite_depth',
'average_height'
]
Age_keys = [
'specimen_inferred_age', 'sample_inferred_age',
'site_inferred_age', 'average_age'
]
Unit_keys = {
'specimen_inferred_age': 'specimen_inferred_age_unit',
'sample_inferred_age': 'sample_inferred_age_unit',
'site_inferred_age': 'site_inferred_age_unit',
'average_age': 'average_age_unit'
}
Dec_keys = [
'measurement_dec', 'specimen_dec', 'sample_dec', 'site_dec',
'average_dec'
]
Inc_keys = [
'measurement_inc', 'specimen_inc', 'sample_inc', 'site_inc',
'average_inc'
]
Int_keys = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass', 'specimen_int',
'specimen_int_rel', 'sample_int', 'sample_int_rel', 'site_int',
'site_int_rel', 'average_int', 'average_int_rel'
]
Chi_keys = ['measurement_chi_volume', 'measurement_chi_mass']
Lat_keys = ['sample_lat', 'site_lat', 'average_lat']
VLat_keys = ['vgp_lat']
VLon_keys = ['vgp_lon']
Vdm_keys = ['vdm']
Vadm_keys = ['vadm']
method_col_name = "magic_method_codes"
else:
# 3.0 keys
supported = ["specimens", "samples", "sites",
"locations"] # available file types
Depth_keys = ["height", "core_depth", "elevation", "composite_depth"]
Age_keys = ["age"]
Unit_keys = {"age": "age"}
Chi_keys = ["susc_chi_volume", "susc_chi_mass"]
Int_keys = [
"magn_moment", "magn_volume", "magn_mass", "int_abs", "int_rel"
]
Inc_keys = ["dir_inc"]
Dec_keys = ["dir_dec"]
Lat_Keys = ["lat"]
VLat_keys = ["vgp_lat", "pole_lat"]
VLon_keys = ["vgp_lon", "pole_lon"]
Vdm_keys = ["vdm", "pdm"]
Vadm_keys = ["vadm", "padm"]
method_col_name = "method_codes"
#
X_keys = [Age_keys, Depth_keys]
Y_keys = [
Dec_keys, Inc_keys, Int_keys, Chi_keys, VLat_keys, VLon_keys, Vdm_keys,
Vadm_keys
]
method, fmt = "", 'svg'
FIG = {'strat': 1}
plotexp, pTS = 0, 0
dir_path = pmag.get_named_arg("-WD", ".")
# default files
if data_model_num == 3:
res_file = pmag.get_named_arg("-f", "sites.txt")
else:
res_file = pmag.get_named_arg("-f", "pmag_results.txt")
res_file = pmag.resolve_file_name(res_file, dir_path)
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
obj = sys.argv[ind + 1]
if '-x' in sys.argv:
ind = sys.argv.index('-x')
xaxis = sys.argv[ind + 1]
if '-y' in sys.argv:
ind = sys.argv.index('-y')
yaxis = sys.argv[ind + 1]
if yaxis == 'dec':
ykeys = Dec_keys
if yaxis == 'inc':
ykeys = Inc_keys
if yaxis == 'int':
ykeys = Int_keys
if yaxis == 'chi':
ykeys = Chi_keys
if yaxis == 'lat':
ykeys = VLat_keys
if yaxis == 'lon':
ykeys = VLon_keys
if yaxis == 'vdm':
ykeys = Vdm_keys
if yaxis == 'vadm':
ykeys = Vadm_keys
if '-mcd' in sys.argv:
ind = sys.argv.index('-mcd')
method = sys.argv[ind + 1]
if '-ts' in sys.argv:
ind = sys.argv.index('-ts')
ts = sys.argv[ind + 1]
amin = float(sys.argv[ind + 2])
amax = float(sys.argv[ind + 3])
pTS = 1
if '-Iex' in sys.argv:
plotexp = 1
if '-sav' in sys.argv:
plot = 1
#
#
# get data read in
Results, file_type = pmag.magic_read(res_file)
if file_type not in supported:
print("Unsupported file type ({}), try again".format(file_type))
sys.exit()
PltObjs = ['all']
if data_model_num == 2:
if file_type == 'pmag_results': # find out what to plot
for rec in Results:
resname = rec['pmag_result_name'].split()
if 'Sample' in resname and 'sam' not in PltObjs:
PltObjs.append('sam')
if 'Site' in resname and 'sit' not in PltObjs:
PltObjs.append('sit')
methcodes = []
# need to know all the measurement types from method_codes
if "magic_method_codes" in list(Results[0].keys()):
for rec in Results:
meths = rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in methcodes and 'LP' in meth:
# look for the lab treatments
methcodes.append(meth.strip())
#
# initialize some variables
X_unit = "" # Unit for age or depth plotting (meters if depth)
Xplots, Yplots = [], []
Xunits = []
yplotind, xplotind = 0, 0
#
# step through possible plottable keys
#
if xaxis == "" or yaxis == "":
for key in list(Results[0].keys()):
for keys in X_keys:
for xkeys in keys:
if key in xkeys:
for ResRec in Results:
if ResRec[key] != "":
# only plot something if there is something to plot!
Xplots.append(key)
break
for keys in Y_keys:
for pkeys in keys:
if key in pkeys:
for ResRec in Results:
if ResRec[key] != "":
Yplots.append(key)
break
X, Y = [], []
for plt in Xplots:
if plt in Age_keys and 'age' not in X:
X.append('age')
if plt in Depth_keys and 'pos' not in X:
X.append('pos')
for plt in Yplots:
if plt in Dec_keys and 'dec' not in Y:
Y.append('dec')
if plt in Inc_keys and 'inc' not in Y:
Y.append('inc')
if plt in Int_keys and 'int' not in Y:
Y.append('int')
if plt in Chi_keys and 'chi' not in Y:
Y.append('chi')
if plt in VLat_keys and 'lat' not in Y:
Y.append('lat')
if plt in VLon_keys and 'lon' not in Y:
Y.append('lon')
if plt in Vadm_keys and 'vadm' not in Y:
Y.append('vadm')
if plt in Vdm_keys and 'vdm' not in Y:
Y.append('vdm')
if file_type == 'pmag_results':
print('available objects for plotting: ', PltObjs)
print('available X plots: ', X)
print('available Y plots: ', Y)
print('available method codes: ', methcodes)
f = open(dir_path + '/.striprc', 'w')
for x in X:
f.write('x:' + x + '\n')
for y in Y:
f.write('y:' + y + '\n')
for m in methcodes:
f.write('m:' + m + '\n')
for obj in PltObjs:
f.write('obj:' + obj + '\n')
sys.exit()
if plotexp == 1:
for lkey in Lat_keys:
for key in list(Results[0].keys()):
if key == lkey:
lat = float(Results[0][lkey])
Xinc = [pmag.pinc(lat), -pmag.pinc(lat)]
break
if Xinc == "":
print('can not plot expected inc for site - lat unknown')
if method != "" and method not in methcodes:
print('your method not available, but these are: ')
print(methcodes)
print('use ', methcodes[0], '? ^D to quit')
if xaxis == 'age':
for akey in Age_keys:
for key in list(Results[0].keys()):
if key == akey:
Xplots.append(key)
Xunits.append(Unit_keys[key])
if xaxis == 'pos':
for dkey in Depth_keys:
for key in list(Results[0].keys()):
if key == dkey:
Xplots.append(key)
if len(Xplots) == 0:
print('desired X axis information not found')
sys.exit()
if xaxis == 'age':
age_unit = Results[0][Xunits[0]]
if len(Xplots) > 1:
print('multiple X axis keys found, using: ', Xplots[xplotind])
for ykey in ykeys:
for key in list(Results[0].keys()):
if key == ykey:
Yplots.append(key)
if len(Yplots) == 0:
print('desired Y axis information not found')
sys.exit()
if len(Yplots) > 1:
print('multiple Y axis keys found, using: ', Yplots[yplotind])
# check if age or depth info
if len(Xplots) == 0:
print("Must have either age or height info to plot ")
sys.exit()
#
# check for variable to plot
#
#
# determine X axis (age or depth)
#
if xaxis == "age":
plotind = "1"
if method == "":
try:
method = methcodes[0]
except IndexError:
method = ""
if xaxis == 'pos':
xlab = "Stratigraphic Height (meters)"
else:
xlab = "Age (" + age_unit + ")"
Xkey = Xplots[xplotind]
Ykey = Yplots[yplotind]
ylab = Ykey
#
# collect the data for plotting
XY = []
isign = 1.
# if float(Results[0][Xkey])/float(Results[-1][Xkey])>0 and float(Results[0][Xkey])<0:
# isign=-1. # x axis all same sign and negative, take positive (e.g.,for depth in core)
# xlab="Stratigraphic Position (meters)"
# else:
# isign=1.
for rec in Results:
if "magic_method_codes" in list(rec.keys()):
meths = rec["magic_method_codes"].split(":")
if method in meths: # make sure it is desired lab treatment step
if obj == 'all' and rec[Xkey].strip() != "":
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
elif rec[Xkey].strip() != "":
name = rec['pmag_result_name'].split()
if obj == 'sit' and "Site" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
if obj == 'sam' and "Sample" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
elif method == "":
if obj == 'all' and rec[Xkey].strip() != "":
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
elif rec[Xkey].strip() != "":
name = rec['pmag_result_name'].split()
if obj == 'sit' and "Site" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
if obj == 'sam' and "Sample" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
else:
print("Something wrong with your plotting choices")
break
XY.sort()
title = ""
if "er_locations_names" in list(Results[0].keys()):
title = Results[0]["er_location_names"]
if "er_locations_name" in list(Results[0].keys()):
title = Results[0]["er_location_name"]
labels = [xlab, ylab, title]
pmagplotlib.plot_init(FIG['strat'], 10, 5)
pmagplotlib.plot_strat(FIG['strat'], XY, labels) # plot them
if plotexp == 1:
pmagplotlib.plot_hs(FIG['strat'], Xinc, 'b', '--')
if yaxis == 'inc' or yaxis == 'lat':
pmagplotlib.plot_hs(FIG['strat'], [0], 'b', '-')
pmagplotlib.plot_hs(FIG['strat'], [-90, 90], 'g', '-')
if pTS == 1:
FIG['ts'] = 2
pmagplotlib.plot_init(FIG['ts'], 10, 5)
pmagplotlib.plot_ts(FIG['ts'], [amin, amax], ts)
files = {}
for key in list(FIG.keys()):
files[key] = key + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
files = {}
files['strat'] = xaxis + '_' + yaxis + '_.' + fmt
files['ts'] = 'ts.' + fmt
titles = {}
titles['strat'] = 'Depth/Time Series Plot'
titles['ts'] = 'Time Series Plot'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plot == 1:
pmagplotlib.save_plots(FIG, files)
else:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(' By default, this information is not available in your measurement file.')
print(' Trying to acquire this information from {}'.format(dir_path))
con = cb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if meas_df is None:
print('-W- No data found in {}'.format(dir_path))
return
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(plot_key))
# need to take the data directly from the contribution here, to keep
# location/site/sample columns in the measurements table
data = con.tables['measurements'].convert_to_pmag_data_list()
file_type = "measurements"
else:
data, file_type = pmag.magic_read(in_file)
# read in data
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append([float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plot_mag(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt != plotlist[-1]: # if it isn't the last plot, init the next one
pmagplotlib.plot_init(FIG['exp'], 6, 6)
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(
' By default, this information is not available in your measurement file.'
)
print(
' Trying to acquire this information from {}'.format(dir_path))
con = cb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if meas_df is None:
print('-W- No data found in {}'.format(dir_path))
return
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(
plot_key))
# need to take the data directly from the contribution here, to keep
# location/site/sample columns in the measurements table
data = con.tables['measurements'].convert_to_pmag_data_list()
file_type = "measurements"
else:
data, file_type = pmag.magic_read(in_file)
# read in data
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass'
]
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append(
[float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plot_mag(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt != plotlist[
-1]: # if it isn't the last plot, init the next one
pmagplotlib.plot_init(FIG['exp'], 6, 6)
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
revtest_magic.py
DESCRIPTION
calculates bootstrap statistics to test for antipodality
INPUT FORMAT
takes dec/inc data from sites table
SYNTAX
revtest_magic.py [command line options]
OPTION
-h prints help message and quits
-f FILE, sets pmag_sites filename on command line
-crd [s,g,t], set coordinate system, default is geographic
-exc use criteria file to set acceptance criteria (only available for data model 3)
-fmt [svg,png,jpg], sets format for image output
-sav saves plot and quits
-DM [2, 3] MagIC data model num, default is 3
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
dir_path = pmag.get_named_arg("-WD", ".")
coord = pmag.get_named_arg("-crd", "0") # default to geographic coordinates
if coord == 's':
coord = '-1'
elif coord == 'g':
coord = '0'
elif coord == 't':
coord = '100'
fmt = pmag.get_named_arg("-fmt", "svg")
if '-sav' in sys.argv:
plot = 1
data_model = int(float(pmag.get_named_arg("-DM")))
if data_model == 2:
infile = pmag.get_named_arg("-f", "pmag_sites.txt")
critfile = "pmag_criteria.txt"
tilt_corr_col = 'site_tilt_correction'
dec_col = "site_dec"
inc_col = "site_inc"
crit_code_col = "pmag_criteria_code"
else:
infile = pmag.get_named_arg("-f", "sites.txt")
critfile = "criteria.txt"
tilt_corr_col = "dir_tilt_correction"
dec_col = "dir_dec"
inc_col = "dir_inc"
crit_code_col = "criterion"
D = []
#
infile = pmag.resolve_file_name(infile, dir_path)
dir_path = os.path.split(infile)[0]
critfile = pmag.resolve_file_name(critfile, dir_path)
#
if data_model == 2:
Accept = ['site_k', 'site_alpha95', 'site_n', 'site_n_lines']
else:
Accept = ['dir_k', 'dir_alpha95', 'dir_n_samples', 'dir_n_specimens_line']
data, file_type = pmag.magic_read(infile)
if 'sites' not in file_type:
print("Error opening file", file_type)
sys.exit()
# ordata,file_type=pmag.magic_read(orfile)
SiteCrits = []
if '-exc' in sys.argv and data_model != 2:
crits, file_type = pmag.magic_read(critfile)
for crit in crits:
if crit[crit_code_col] == "DE-SITE":
SiteCrit = crit
SiteCrits.append(SiteCrit)
elif '-exc' in sys.argv and data_model == 2:
print('-W- You have selected the -exc option, which is not available with MagIC data model 2.')
for rec in data:
if rec[tilt_corr_col] == coord:
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
if '-exc' in sys.argv and data_model != 2:
fail = False
for SiteCrit in SiteCrits:
for key in Accept:
if key not in SiteCrit['table_column']:
continue
if key not in rec:
continue
if SiteCrit['criterion_value'] != "":
op = OPS[SiteCrit['criterion_operation']]
if not op(float(rec[key]), float(SiteCrit['criterion_value'])):
fail = True
if not fail:
D.append([Dec, Inc, 1.])
else:
D.append([Dec, Inc, 1.])
# set up plots
CDF = {'X': 1, 'Y': 2, 'Z': 3}
pmagplotlib.plot_init(CDF['X'], 5, 5)
pmagplotlib.plot_init(CDF['Y'], 5, 5)
pmagplotlib.plot_init(CDF['Z'], 5, 5)
#
# flip reverse mode
#
D1, D2 = pmag.flip(D)
counter, NumSims = 0, 500
#
# get bootstrapped means for each data set
#
if len(D1) < 5 or len(D2) < 5:
print('not enough data in two different modes for reversals test')
sys.exit()
print('doing first mode, be patient')
BDI1 = pmag.di_boot(D1)
print('doing second mode, be patient')
BDI2 = pmag.di_boot(D2)
pmagplotlib.plot_com(CDF, BDI1, BDI2, [""])
files = {}
for key in list(CDF.keys()):
files[key] = 'REV'+'_'+key+'.'+fmt
if plot == 0:
pmagplotlib.draw_figs(CDF)
ans = input("s[a]ve plots, [q]uit: ")
if ans == 'a':
pmagplotlib.save_plots(CDF, files)
else:
pmagplotlib.save_plots(CDF, files)
sys.exit()
def main():
"""
NAME
eqarea_magic.py
DESCRIPTION
makes equal area projections from declination/inclination data
SYNTAX
eqarea_magic.py [command line options]
INPUT
takes magic formatted sites, samples, specimens, or measurements
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic, default='sites.txt'
supported types=[measurements, specimens, samples, sites]
-fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
default='specimens.txt'
-fsa FILE: specify sample file name, (required if you want to plot specimens by site)
default='samples.txt'
-fsi FILE: specify site file name, default='sites.txt'
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-sav save plot and quit quietly
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
# initialize some default variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
plotE = 0
plt = 0 # default to not plotting
verbose = pmagplotlib.verbose
# extract arguments from sys.argv
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=".")
pmagplotlib.plot_init(FIG['eqarea'],5,5)
in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
in_file = pmag.resolve_file_name(in_file, dir_path)
if "-WD" not in sys.argv:
dir_path = os.path.split(in_file)[0]
#full_in_file = os.path.join(dir_path, in_file)
plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
if plot_by == 'all':
plot_key = 'all'
elif plot_by == 'sit':
plot_key = 'site'
elif plot_by == 'sam':
plot_key = 'sample'
elif plot_by == 'spc':
plot_key = 'specimen'
else:
plot_by = 'all'
plot_key = 'all'
if '-c' in sys.argv:
contour = 1
else:
contour = 0
if '-sav' in sys.argv:
plt = 1
verbose = 0
if '-ell' in sys.argv:
plotE = 1
ind = sys.argv.index('-ell')
ell_type = sys.argv[ind+1]
ell_type = pmag.get_named_arg_from_sys("-ell", "F")
dist = ell_type.upper()
# if dist type is unrecognized, use Fisher
if dist not in ['F', 'K', 'B', 'BE', 'BV']:
dist = 'F'
if dist == "BV":
FIG['bdirs'] = 2
pmagplotlib.plot_init(FIG['bdirs'],5,5)
crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
dec_key = 'dir_dec'
inc_key = 'dir_inc'
tilt_key = 'dir_tilt_correction'
#Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
#
fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames,
single_file=in_file)
try:
contribution.propagate_location_to_samples()
contribution.propagate_location_to_specimens()
contribution.propagate_location_to_measurements()
except KeyError as ex:
pass
# the object that contains the DataFrame + useful helper methods:
table_name = list(contribution.tables.keys())[0]
data_container = contribution.tables[table_name]
# the actual DataFrame:
data = data_container.df
if plot_key != "all" and plot_key not in data.columns:
print("-E- You can't plot by {} with the data provided".format(plot_key))
return
# add tilt key into DataFrame columns if it isn't there already
if tilt_key not in data.columns:
data.loc[:, tilt_key] = None
if verbose:
print(len(data), ' records read from ', in_file)
# find desired dec,inc data:
dir_type_key = ''
#
# get plotlist if not plotting all records
#
plotlist=[]
if plot_key != "all":
# return all where plot_key is not blank
if plot_key not in data.columns:
print('Can\'t plot by "{}". That header is not in infile: {}'.format(plot_key, in_file))
return
plots = data[data[plot_key].notnull()]
plotlist = plots[plot_key].unique() # grab unique values
else:
plotlist.append('All')
for plot in plotlist:
if verbose:
print(plot)
if plot == 'All':
# plot everything at once
plot_data = data
else:
# pull out only partial data
plot_data = data[data[plot_key] == plot]
DIblock = []
GCblock = []
# SLblock, SPblock = [], []
title = plot
mode = 1
k = 0
if dec_key not in plot_data.columns:
print("-W- No dec/inc data")
continue
# get all records where dec & inc values exist
plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
if plot_data.empty:
continue
# this sorting out is done in get_di_bock
#if coord == '0': # geographic, use records with no tilt key (or tilt_key 0)
# cond1 = plot_data[tilt_key].fillna('') == coord
# cond2 = plot_data[tilt_key].isnull()
# plot_data = plot_data[cond1 | cond2]
#else: # not geographic coordinates, use only records with correct tilt_key
# plot_data = plot_data[plot_data[tilt_key] == coord]
# get metadata for naming the plot file
locations = data_container.get_name('location', df_slice=plot_data)
site = data_container.get_name('site', df_slice=plot_data)
sample = data_container.get_name('sample', df_slice=plot_data)
specimen = data_container.get_name('specimen', df_slice=plot_data)
# make sure method_codes is in plot_data
if 'method_codes' not in plot_data.columns:
plot_data['method_codes'] = ''
# get data blocks
DIblock = data_container.get_di_block(df_slice=plot_data,
tilt_corr=coord, excl=['DE-BFP'])
#SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
# get great circles
great_circle_data = data_container.get_records_for_code('DE-BFP', incl=True,
use_slice=True, sli=plot_data)
if len(great_circle_data) > 0:
gc_cond = great_circle_data[tilt_key] == coord
GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
#SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]
if len(DIblock) > 0:
if contour == 0:
pmagplotlib.plotEQ(FIG['eqarea'], DIblock, title)
else:
pmagplotlib.plotEQcont(FIG['eqarea'], DIblock)
else:
pmagplotlib.plotNET(FIG['eqarea'])
if len(GCblock)>0:
for rec in GCblock:
pmagplotlib.plotC(FIG['eqarea'], rec, 90., 'g')
if len(DIblock) == 0 and len(GCblock) == 0:
if verbose:
print("no records for plotting")
continue
#sys.exit()
if plotE == 1:
ppars = pmag.doprinc(DIblock) # get principal directions
nDIs, rDIs, npars, rpars = [], [], [], []
for rec in DIblock:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist=='B': # do on whole dataset
etitle="Bingham confidence ellipse"
bpars=pmag.dobingham(DIblock)
for key in list(bpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(bpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist=='F':
etitle="Fisher confidence cone"
if len(nDIs)>2:
fpars=pmag.fisher_mean(nDIs)
for key in list(fpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(fpars[key]))
mode+=1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign=old_div(abs(fpars['inc']),fpars['inc'])
npars.append(fpars['inc']-isign*90.) #Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) #Beta inc
if len(rDIs)>2:
fpars=pmag.fisher_mean(rDIs)
if verbose: print("mode ",mode)
for key in list(fpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(fpars[key]))
mode+=1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign=old_div(abs(fpars['inc']),fpars['inc'])
rpars.append(fpars['inc']-isign*90.) #Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) #Beta inc
if dist=='K':
etitle="Kent confidence ellipse"
if len(nDIs)>3:
kpars=pmag.dokent(nDIs,len(nDIs))
if verbose: print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(kpars[key]))
mode+=1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs)>3:
kpars=pmag.dokent(rDIs,len(rDIs))
if verbose: print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(kpars[key]))
mode+=1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist=='BE':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
if verbose: print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
if verbose: print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
etitle="Bootstrapped confidence ellipse"
elif dist=='BV':
sym={'lower':['o','c'],'upper':['o','g'],'size':3,'edgecolor':'face'}
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plotEQsym(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors', sym)
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plotDIsym(FIG['bdirs'],BrDIs,sym)
else:
pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
if dist=='B':
if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],npars,0)
elif len(nDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],npars,0)
if len(rDIs)>3:
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],rpars,0)
elif len(rDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],rpars,0)
for key in list(FIG.keys()):
files = {}
filename = pmag.get_named_arg_from_sys('-fname')
if filename: # use provided filename
filename+= '.' + fmt
elif pmagplotlib.isServer: # use server plot naming convention
filename='LO:_'+locations+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
elif plot_key == 'all':
filename = 'all'
if 'location' in plot_data.columns:
locs = plot_data['location'].unique()
loc_string = "_".join([loc.replace(' ', '_') for loc in locs])
filename += "_" + loc_string
filename += "_" + crd + "_" + key
filename += ".{}".format(fmt)
else: # use more readable naming convention
filename = ''
# fix this if plot_by is location , for example
use_names = {'location': [locations], 'site': [locations, site],
'sample': [locations, site, sample],
'specimen': [locations, site, sample, specimen]}
use = use_names[plot_key]
use.extend([crd, key])
for item in use: #[locations, site, sample, specimen, crd, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key]=filename
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
if plt:
pmagplotlib.saveP(FIG,files)
continue
if verbose:
pmagplotlib.drawFIGS(FIG)
ans=input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q":
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG,files)
continue
def convert(**kwargs):
# initialize some stuff
methcode = "LP-NO"
phi, theta, peakfield, labfield = 0, 0, 0, 0
pTRM, MD = 0, 0
dec = [315, 225, 180, 135, 45, 90, 270, 270, 270, 90, 180, 180, 0, 0, 0]
inc = [0, 0, 0, 0, 0, -45, -45, 0, 45, 45, 45, -45, -90, -45, 45]
tdec = [0, 90, 0, 180, 270, 0, 0, 90, 0]
tinc = [0, 0, 90, 0, 0, -90, 0, 0, 90]
missing = 1
demag = "N"
citations = 'This study'
fmt = 'old'
Samps = []
trm = 0
irm = 0
#get args
user = kwargs.get('user', '')
dir_path = kwargs.get('dir_path', '.')
output_dir_path = dir_path
meas_file = kwargs.get('meas_file',
'measurements.txt') # measurement outfile
meas_file = pmag.resolve_file_name(meas_file, output_dir_path)
spec_file = kwargs.get('spec_file', 'specimens.txt') # specimen outfile
spec_file = pmag.resolve_file_name(spec_file, output_dir_path)
samp_file = kwargs.get('samp_file', 'samples.txt') # sample outfile
samp_file = pmag.resolve_file_name(samp_file, output_dir_path)
site_file = kwargs.get('site_file', 'sites.txt') # site outfile
site_file = pmag.resolve_file_name(site_file, output_dir_path)
loc_file = kwargs.get('loc_file', 'locations.txt') # location outfile
loc_file = pmag.resolve_file_name(loc_file, output_dir_path)
mag_file = kwargs.get('mag_file', '')
mag_file = pmag.resolve_file_name(mag_file, dir_path)
labfield = kwargs.get('labfield', '')
if labfield:
labfield = float(labfield) * 1e-6
else:
labfield = 0
phi = kwargs.get('phi', 0)
if phi:
phi = float(phi)
else:
phi = 0
theta = kwargs.get('theta', 0)
if theta:
theta = float(theta)
else:
theta = 0
peakfield = kwargs.get('peakfield', 0)
if peakfield:
peakfield = float(peakfield) * 1e-3
else:
peakfield = 0
specnum = kwargs.get('specnum', 0)
samp_con = kwargs.get('samp_con', '1')
location = kwargs.get('location', 'unknown')
samp_infile = kwargs.get('samp_infile', '')
syn = kwargs.get('syn', 0)
institution = kwargs.get('institution', '')
syntype = kwargs.get('syntype', '')
inst = kwargs.get('inst', '')
noave = kwargs.get('noave', 0)
codelist = kwargs.get('codelist', '')
coil = kwargs.get('coil', '')
cooling_rates = kwargs.get('cooling_rates', '')
lat = kwargs.get('lat', '')
lon = kwargs.get('lon', '')
timezone = kwargs.get('timezone', 'UTC')
# make sure all initial values are correctly set up (whether they come from the command line or a GUI)
if samp_infile:
Samps, file_type = pmag.magic_read(samp_infile)
if coil:
coil = str(coil)
methcode = "LP-IRM"
irmunits = "V"
if coil not in ["1", "2", "3"]:
print(__doc__)
print('not a valid coil specification')
return False, '{} is not a valid coil specification'.format(coil)
if mag_file:
lines = pmag.open_file(mag_file)
if not lines:
print("you must provide a valid mag_file")
return False, "you must provide a valid mag_file"
if not mag_file:
print(__doc__)
print("mag_file field is required option")
return False, "mag_file field is required option"
if specnum != 0:
specnum = -specnum
if "4" == samp_con[0]:
if "-" not in samp_con:
print(
"naming convention option [4] must be in form 4-Z where Z is an integer"
)
print('---------------')
return False, "naming convention option [4] must be in form 4-Z where Z is an integer"
else:
Z = samp_con.split("-")[1]
samp_con = "4"
if "7" == samp_con[0]:
if "-" not in samp_con:
print("option [7] must be in form 7-Z where Z is an integer")
return False, "option [7] must be in form 7-Z where Z is an integer"
else:
Z = samp_con.split("-")[1]
samp_con = "7"
else:
Z = 0
if codelist:
codes = codelist.split(':')
if "AF" in codes:
demag = 'AF'
if '-dc' not in sys.argv: methcode = "LT-AF-Z"
if '-dc' in sys.argv: methcode = "LT-AF-I"
if "T" in codes:
demag = "T"
if '-dc' not in sys.argv: methcode = "LT-T-Z"
if '-dc' in sys.argv: methcode = "LT-T-I"
if "I" in codes:
methcode = "LP-IRM"
irmunits = "mT"
if "I3d" in codes:
methcode = "LT-T-Z:LP-IRM-3D"
if "S" in codes:
demag = "S"
methcode = "LP-PI-TRM:LP-PI-ALT-AFARM"
trm_labfield = labfield
ans = input("DC lab field for ARM step: [50uT] ")
if ans == "":
arm_labfield = 50e-6
else:
arm_labfield = float(ans) * 1e-6
ans = input("temperature for total trm step: [600 C] ")
if ans == "":
trm_peakT = 600 + 273 # convert to kelvin
else:
trm_peakT = float(ans) + 273 # convert to kelvin
if "G" in codes: methcode = "LT-AF-G"
if "D" in codes: methcode = "LT-AF-D"
if "TRM" in codes:
demag = "T"
trm = 1
if "CR" in codes:
demag = "T"
cooling_rate_experiment = 1
cooling_rates_list = cooling_rates.split(
',') # command_line does not exist in this code
#if command_line:
# ind=sys.argv.index("CR")
# cooling_rates=sys.argv[ind+1]
# cooling_rates_list=cooling_rates.split(',')
#else:
# cooling_rates_list=str(cooling_rates).split(',')
if demag == "T" and "ANI" in codes:
methcode = "LP-AN-TRM"
if demag == "T" and "CR" in codes:
methcode = "LP-CR-TRM"
if demag == "AF" and "ANI" in codes:
methcode = "LP-AN-ARM"
if labfield == 0: labfield = 50e-6
if peakfield == 0: peakfield = .180
MeasRecs, SpecRecs, SampRecs, SiteRecs, LocRecs = [], [], [], [], []
version_num = pmag.get_version()
##################################
for line in lines:
instcode = ""
if len(line) > 2:
MeasRec, SpecRec, SampRec, SiteRec, LocRec = {}, {}, {}, {}, {}
MeasRec['software_packages'] = version_num
MeasRec["description"] = ""
MeasRec["treat_temp"] = '%8.3e' % (273) # room temp in kelvin
MeasRec["meas_temp"] = '%8.3e' % (273) # room temp in kelvin
MeasRec["treat_ac_field"] = '0'
MeasRec["treat_dc_field"] = '0'
MeasRec["treat_dc_field_phi"] = '0'
MeasRec["treat_dc_field_theta"] = '0'
meas_type = "LT-NO"
rec = line.split()
try:
float(rec[0])
print("No specimen name for line #%d in the measurement file" %
lines.index(line))
continue
except ValueError:
pass
if rec[1] == ".00": rec[1] = "0.00"
treat = rec[1].split('.')
if methcode == "LP-IRM":
if irmunits == 'mT':
labfield = float(treat[0]) * 1e-3
else:
labfield = pmag.getfield(irmunits, coil, treat[0])
if rec[1][0] != "-":
phi, theta = 0., 90.
else:
phi, theta = 0., -90.
meas_type = "LT-IRM"
MeasRec["treat_dc_field"] = '%8.3e' % (labfield)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (phi)
MeasRec["treat_dc_field_theta"] = '%7.1f' % (theta)
if len(rec) > 6:
code1 = rec[6].split(
';') # break e.g., 10/15/02;7:45 indo date and time
if len(code1) == 2: # old format with AM/PM
missing = 0
code2 = code1[0].split('/') # break date into mon/day/year
code3 = rec[7].split(
';'
) # break e.g., AM;C34;200 into time;instr/axes/measuring pos;number of measurements
yy = int(code2[2])
if yy < 90:
yyyy = str(2000 + yy)
else:
yyyy = str(1900 + yy)
mm = int(code2[0])
if mm < 10:
mm = "0" + str(mm)
else:
mm = str(mm)
dd = int(code2[1])
if dd < 10:
dd = "0" + str(dd)
else:
dd = str(dd)
time = code1[1].split(':')
hh = int(time[0])
if code3[0] == "PM": hh = hh + 12
if hh < 10:
hh = "0" + str(hh)
else:
hh = str(hh)
min = int(time[1])
if min < 10:
min = "0" + str(min)
else:
min = str(min)
dt = yyyy + ":" + mm + ":" + dd + ":" + hh + ":" + min + ":00"
local = pytz.timezone(timezone)
naive = datetime.datetime.strptime(dt, "%Y:%m:%d:%H:%M:%S")
local_dt = local.localize(naive, is_dst=None)
utc_dt = local_dt.astimezone(pytz.utc)
MeasRec["timestamp"] = utc_dt.strftime(
"%Y-%m-%dT%H:%M:%S") + "Z"
if inst == "":
if code3[1][0] == 'C': instcode = 'SIO-bubba'
if code3[1][0] == 'G': instcode = 'SIO-flo'
else:
instcode = ''
MeasRec["meas_n_orient"] = code3[1][2]
elif len(code1) > 2: # newest format (cryo7 or later)
if "LP-AN-ARM" not in methcode: labfield = 0
fmt = 'new'
date = code1[0].split('/') # break date into mon/day/year
yy = int(date[2])
if yy < 90:
yyyy = str(2000 + yy)
else:
yyyy = str(1900 + yy)
mm = int(date[0])
if mm < 10:
mm = "0" + str(mm)
else:
mm = str(mm)
dd = int(date[1])
if dd < 10:
dd = "0" + str(dd)
else:
dd = str(dd)
time = code1[1].split(':')
hh = int(time[0])
if hh < 10:
hh = "0" + str(hh)
else:
hh = str(hh)
min = int(time[1])
if min < 10:
min = "0" + str(min)
else:
min = str(min)
dt = yyyy + ":" + mm + ":" + dd + ":" + hh + ":" + min + ":00"
local = pytz.timezone(timezone)
naive = datetime.datetime.strptime(dt, "%Y:%m:%d:%H:%M:%S")
local_dt = local.localize(naive, is_dst=None)
utc_dt = local_dt.astimezone(pytz.utc)
MeasRec["timestamp"] = utc_dt.strftime(
"%Y-%m-%dT%H:%M:%S") + "Z"
if inst == "":
if code1[6][0] == 'C':
instcode = 'SIO-bubba'
if code1[6][0] == 'G':
instcode = 'SIO-flo'
else:
instcode = ''
if len(code1) > 1:
MeasRec["meas_n_orient"] = code1[6][2]
else:
MeasRec["meas_n_orient"] = code1[
7] # takes care of awkward format with bubba and flo being different
if user == "": user = code1[5]
if code1[2][-1] == 'C':
demag = "T"
if code1[4] == 'microT' and float(
code1[3]
) != 0. and "LP-AN-ARM" not in methcode:
labfield = float(code1[3]) * 1e-6
if code1[2] == 'mT' and methcode != "LP-IRM":
demag = "AF"
if code1[4] == 'microT' and float(code1[3]) != 0.:
labfield = float(code1[3]) * 1e-6
if code1[
4] == 'microT' and labfield != 0. and meas_type != "LT-IRM":
phi, theta = 0., -90.
if demag == "T": meas_type = "LT-T-I"
if demag == "AF": meas_type = "LT-AF-I"
MeasRec["treat_dc_field"] = '%8.3e' % (labfield)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (phi)
MeasRec["treat_dc_field_theta"] = '%7.1f' % (theta)
if code1[
4] == '' or labfield == 0. and meas_type != "LT-IRM":
if demag == 'T': meas_type = "LT-T-Z"
if demag == "AF": meas_type = "LT-AF-Z"
MeasRec["treat_dc_field"] = '0'
if syn == 0:
specimen = rec[0]
MeasRec["specimen"] = specimen
if specnum != 0:
sample = rec[0][:specnum]
else:
sample = rec[0]
if samp_infile and Samps: # if samp_infile was provided AND yielded sample data
samp = pmag.get_dictitem(Samps, 'sample', sample, 'T')
if len(samp) > 0:
location = samp[0]["location"]
site = samp[0]["site"]
else:
location = ''
site = ''
else:
site = pmag.parse_site(sample, samp_con, Z)
if location != '' and location not in [
x['location'] if 'location' in list(x.keys()) else ''
for x in LocRecs
]:
LocRec['location'] = location
LocRec['lat_n'] = lat
LocRec['lat_s'] = lat
LocRec['lon_e'] = lon
LocRec['lon_w'] = lon
LocRecs.append(LocRec)
if site != '' and site not in [
x['site'] if 'site' in list(x.keys()) else ''
for x in SiteRecs
]:
SiteRec['location'] = location
SiteRec['site'] = site
SiteRec['lat'] = lat
SiteRec['lon'] = lon
SiteRecs.append(SiteRec)
if sample != '' and sample not in [
x['sample'] if 'sample' in list(x.keys()) else ''
for x in SampRecs
]:
SampRec['site'] = site
SampRec['sample'] = sample
SampRecs.append(SampRec)
if specimen != '' and specimen not in [
x['specimen'] if 'specimen' in list(x.keys()) else ''
for x in SpecRecs
]:
SpecRec["specimen"] = specimen
SpecRec['sample'] = sample
SpecRecs.append(SpecRec)
else:
specimen = rec[0]
MeasRec["specimen"] = specimen
if specnum != 0:
sample = rec[0][:specnum]
else:
sample = rec[0]
site = pmag.parse_site(sample, samp_con, Z)
if location != '' and location not in [
x['location'] if 'location' in list(x.keys()) else ''
for x in LocRecs
]:
LocRec['location'] = location
LocRec['lat_n'] = lat
LocRec['lat_s'] = lat
LocRec['lon_e'] = lon
LocRec['lon_w'] = lon
LocRecs.append(LocRec)
if site != '' and site not in [
x['site'] if 'site' in list(x.keys()) else ''
for x in SiteRecs
]:
SiteRec['location'] = location
SiteRec['site'] = site
SiteRec['lat'] = lat
SiteRec['lon'] = lon
SiteRecs.append(SiteRec)
if sample != '' and sample not in [
x['sample'] if 'sample' in list(x.keys()) else ''
for x in SampRecs
]:
SampRec['site'] = site
SampRec['sample'] = sample
SampRecs.append(SampRec)
if specimen != '' and specimen not in [
x['specimen'] if 'specimen' in list(x.keys()) else ''
for x in SpecRecs
]:
SpecRec["specimen"] = specimen
SpecRec['sample'] = sample
SpecRecs.append(SpecRec)
SampRec["institution"] = institution
SampRec["material_type"] = syntype
#MeasRec["sample"]=sample
if float(rec[1]) == 0:
pass
elif demag == "AF":
if methcode != "LP-AN-ARM":
MeasRec["treat_ac_field"] = '%8.3e' % (
float(rec[1]) * 1e-3) # peak field in tesla
if meas_type == "LT-AF-Z": MeasRec["treat_dc_field"] = '0'
else: # AARM experiment
if treat[1][0] == '0':
meas_type = "LT-AF-Z:LP-AN-ARM:"
MeasRec["treat_ac_field"] = '%8.3e' % (
peakfield) # peak field in tesla
MeasRec["treat_dc_field"] = '%8.3e' % (0)
if labfield != 0 and methcode != "LP-AN-ARM":
print(
"Warning - inconsistency in mag file with lab field - overriding file with 0"
)
else:
meas_type = "LT-AF-I:LP-AN-ARM"
ipos = int(treat[0]) - 1
MeasRec["treat_dc_field_phi"] = '%7.1f' % (dec[ipos])
MeasRec["treat_dc_field_theta"] = '%7.1f' % (inc[ipos])
MeasRec["treat_dc_field"] = '%8.3e' % (labfield)
MeasRec["treat_ac_field"] = '%8.3e' % (
peakfield) # peak field in tesla
elif demag == "T" and methcode == "LP-AN-TRM":
MeasRec["treat_temp"] = '%8.3e' % (float(treat[0]) + 273.
) # temp in kelvin
if treat[1][0] == '0':
meas_type = "LT-T-Z:LP-AN-TRM"
MeasRec["treat_dc_field"] = '%8.3e' % (0)
MeasRec["treat_dc_field_phi"] = '0'
MeasRec["treat_dc_field_theta"] = '0'
else:
MeasRec["treat_dc_field"] = '%8.3e' % (labfield)
if treat[1][
0] == '7': # alteration check as final measurement
meas_type = "LT-PTRM-I:LP-AN-TRM"
else:
meas_type = "LT-T-I:LP-AN-TRM"
# find the direction of the lab field in two ways:
# (1) using the treatment coding (XX.1=+x, XX.2=+y, XX.3=+z, XX.4=-x, XX.5=-y, XX.6=-z)
ipos_code = int(treat[1][0]) - 1
# (2) using the magnetization
DEC = float(rec[4])
INC = float(rec[5])
if INC < 45 and INC > -45:
if DEC > 315 or DEC < 45: ipos_guess = 0
if DEC > 45 and DEC < 135: ipos_guess = 1
if DEC > 135 and DEC < 225: ipos_guess = 3
if DEC > 225 and DEC < 315: ipos_guess = 4
else:
if INC > 45: ipos_guess = 2
if INC < -45: ipos_guess = 5
# prefer the guess over the code
ipos = ipos_guess
MeasRec["treat_dc_field_phi"] = '%7.1f' % (tdec[ipos])
MeasRec["treat_dc_field_theta"] = '%7.1f' % (tinc[ipos])
# check it
if ipos_guess != ipos_code and treat[1][0] != '7':
print(
"-E- ERROR: check specimen %s step %s, ATRM measurements, coding does not match the direction of the lab field!"
% (rec[0], ".".join(list(treat))))
elif demag == "S": # Shaw experiment
if treat[1][1] == '0':
if int(treat[0]) != 0:
MeasRec["treat_ac_field"] = '%8.3e' % (
float(treat[0]) * 1e-3) # AF field in tesla
MeasRec["treat_dc_field"] = '0'
meas_type = "LT-AF-Z" # first AF
else:
meas_type = "LT-NO"
MeasRec["treat_ac_field"] = '0'
MeasRec["treat_dc_field"] = '0'
elif treat[1][1] == '1':
if int(treat[0]) == 0:
MeasRec["treat_ac_field"] = '%8.3e' % (
peakfield) # peak field in tesla
MeasRec["treat_dc_field"] = '%8.3e' % (arm_labfield)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (phi)
MeasRec["treat_dc_field_theta"] = '%7.1f' % (theta)
meas_type = "LT-AF-I"
else:
MeasRec["treat_ac_field"] = '%8.3e' % (
float(treat[0]) * 1e-3) # AF field in tesla
MeasRec["treat_dc_field"] = '0'
meas_type = "LT-AF-Z"
elif treat[1][1] == '2':
if int(treat[0]) == 0:
MeasRec["treat_ac_field"] = '0'
MeasRec["treat_dc_field"] = '%8.3e' % (trm_labfield)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (phi)
MeasRec["treat_dc_field_theta"] = '%7.1f' % (theta)
MeasRec["treat_temp"] = '%8.3e' % (trm_peakT)
meas_type = "LT-T-I"
else:
MeasRec["treat_ac_field"] = '%8.3e' % (
float(treat[0]) * 1e-3) # AF field in tesla
MeasRec["treat_dc_field"] = '0'
meas_type = "LT-AF-Z"
elif treat[1][1] == '3':
if int(treat[0]) == 0:
MeasRec["treat_ac_field"] = '%8.3e' % (
peakfield) # peak field in tesla
MeasRec["treat_dc_field"] = '%8.3e' % (arm_labfield)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (phi)
MeasRec["treat_dc_field_theta"] = '%7.1f' % (theta)
meas_type = "LT-AF-I"
else:
MeasRec["treat_ac_field"] = '%8.3e' % (
float(treat[0]) * 1e-3) # AF field in tesla
MeasRec["treat_dc_field"] = '0'
meas_type = "LT-AF-Z"
# Cooling rate experient # added by rshaar
elif demag == "T" and methcode == "LP-CR-TRM":
MeasRec["treat_temp"] = '%8.3e' % (float(treat[0]) + 273.
) # temp in kelvin
if treat[1][0] == '0':
meas_type = "LT-T-Z:LP-CR-TRM"
MeasRec["treat_dc_field"] = '%8.3e' % (0)
MeasRec["treat_dc_field_phi"] = '0'
MeasRec["treat_dc_field_theta"] = '0'
else:
MeasRec["treat_dc_field"] = '%8.3e' % (labfield)
if treat[1][
0] == '7': # alteration check as final measurement
meas_type = "LT-PTRM-I:LP-CR-TRM"
else:
meas_type = "LT-T-I:LP-CR-TRM"
MeasRec["treat_dc_field_phi"] = '%7.1f' % (
phi) # labfield phi
MeasRec["treat_dc_field_theta"] = '%7.1f' % (
theta) # labfield theta
indx = int(treat[1][0]) - 1
# alteration check matjed as 0.7 in the measurement file
if indx == 6:
cooling_time = cooling_rates_list[-1]
else:
cooling_time = cooling_rates_list[indx]
MeasRec[
"description"] = "cooling_rate" + ":" + cooling_time + ":" + "K/min"
noave = 1
elif demag != 'N':
if len(treat) == 1: treat.append('0')
MeasRec["treat_temp"] = '%8.3e' % (float(treat[0]) + 273.
) # temp in kelvin
if trm == 0: # demag=T and not trmaq
if treat[1][0] == '0':
meas_type = "LT-T-Z"
else:
MeasRec["treat_dc_field"] = '%8.3e' % (
labfield
) # labfield in tesla (convert from microT)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (
phi) # labfield phi
MeasRec["treat_dc_field_theta"] = '%7.1f' % (
theta) # labfield theta
if treat[1][0] == '1':
meas_type = "LT-T-I" # in-field thermal step
if treat[1][0] == '2':
meas_type = "LT-PTRM-I" # pTRM check
pTRM = 1
if treat[1][0] == '3':
MeasRec[
"treat_dc_field"] = '0' # this is a zero field step
meas_type = "LT-PTRM-MD" # pTRM tail check
else:
labfield = float(treat[1]) * 1e-6
MeasRec["treat_dc_field"] = '%8.3e' % (
labfield) # labfield in tesla (convert from microT)
MeasRec["treat_dc_field_phi"] = '%7.1f' % (
phi) # labfield phi
MeasRec["treat_dc_field_theta"] = '%7.1f' % (
theta) # labfield theta
meas_type = "LT-T-I:LP-TRM" # trm acquisition experiment
MeasRec["dir_csd"] = rec[2]
MeasRec["magn_moment"] = '%10.3e' % (float(rec[3]) * 1e-3
) # moment in Am^2 (from emu)
MeasRec["dir_dec"] = rec[4]
MeasRec["dir_inc"] = rec[5]
MeasRec["instrument_codes"] = instcode
MeasRec["analysts"] = user
MeasRec["citations"] = citations
if "LP-IRM-3D" in methcode: meas_type = methcode
#MeasRec["method_codes"]=methcode.strip(':')
MeasRec["method_codes"] = meas_type
MeasRec["quality"] = 'g'
if 'std' in rec[0]:
MeasRec["standard"] = 's'
else:
MeasRec["standard"] = 'u'
MeasRec["treat_step_num"] = '1'
#print MeasRec['treat_temp']
MeasRecs.append(MeasRec)
con = nb.Contribution(output_dir_path, read_tables=[])
# create MagIC tables
con.add_magic_table_from_data(dtype='specimens', data=SpecRecs)
con.add_magic_table_from_data(dtype='samples', data=SampRecs)
con.add_magic_table_from_data(dtype='sites', data=SiteRecs)
con.add_magic_table_from_data(dtype='locations', data=LocRecs)
MeasOuts = pmag.measurements_methods3(MeasRecs, noave)
con.add_magic_table_from_data(dtype='measurements', data=MeasOuts)
# write MagIC tables to file
con.tables['specimens'].write_magic_file(custom_name=spec_file)
con.tables['samples'].write_magic_file(custom_name=samp_file)
con.tables['sites'].write_magic_file(custom_name=site_file)
con.tables['locations'].write_magic_file(custom_name=loc_file)
meas_file = con.tables['measurements'].write_magic_file(
custom_name=meas_file)
return True, meas_file