def main():
"""
NAME
di_geo.py
DESCRIPTION
rotates specimen coordinate dec, inc data to geographic
coordinates using the azimuth and plunge of the X direction
INPUT FORMAT
declination inclination azimuth plunge
SYNTAX
di_geo.py [-h][-i][-f FILE] [< filename ]
OPTIONS
-h prints help message and quits
-i for interactive data entry
-f FILE command line entry of file name
-F OFILE, specify output file, default is standard output
OUTPUT:
declination inclination
"""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-F' in sys.argv:
ind = sys.argv.index('-F')
ofile = sys.argv[ind + 1]
out = open(ofile, 'w')
print ofile, ' opened for output'
else:
ofile = ""
if '-i' in sys.argv: # interactive flag
while 1:
try:
Dec = float(raw_input("Declination: <cntrl-D> to quit "))
except EOFError:
print "\n Good-bye\n"
sys.exit()
Inc = float(raw_input("Inclination: "))
Az = float(raw_input("Azimuth: "))
Pl = float(raw_input("Plunge: "))
print '%7.1f %7.1f' % (pmag.dogeo(Dec, Inc, Az, Pl))
elif '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
data = numpy.loadtxt(file)
else:
data = numpy.loadtxt(
sys.stdin, dtype=numpy.float) # read in the data from the datafile
D, I = pmag.dogeo_V(data)
for k in range(len(D)):
if ofile == "":
print '%7.1f %7.1f' % (D[k], I[k])
else:
out.write('%7.1f %7.1f\n' % (D[k], I[k]))
def main():
"""
NAME
di_geo.py
DESCRIPTION
rotates specimen coordinate dec, inc data to geographic
coordinates using the azimuth and plunge of the X direction
INPUT FORMAT
declination inclination azimuth plunge
SYNTAX
di_geo.py [-h][-i][-f FILE] [< filename ]
OPTIONS
-h prints help message and quits
-i for interactive data entry
-f FILE command line entry of file name
-F OFILE, specify output file, default is standard output
OUTPUT:
declination inclination
"""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-F' in sys.argv:
ind=sys.argv.index('-F')
ofile=sys.argv[ind+1]
out=open(ofile,'w')
print ofile, ' opened for output'
else: ofile=""
if '-i' in sys.argv: # interactive flag
while 1:
try:
Dec=float(raw_input("Declination: <cntrl-D> to quit "))
except EOFError:
print "\n Good-bye\n"
sys.exit()
Inc=float(raw_input("Inclination: "))
Az=float(raw_input("Azimuth: "))
Pl=float(raw_input("Plunge: "))
print '%7.1f %7.1f'%(pmag.dogeo(Dec,Inc,Az,Pl))
elif '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
data=numpy.loadtxt(file)
else:
data=numpy.loadtxt(sys.stdin,dtype=numpy.float) # read in the data from the datafile
D,I=pmag.dogeo_V(data)
for k in range(len(D)):
if ofile=="":
print '%7.1f %7.1f'%(D[k],I[k])
else:
out.write('%7.1f %7.1f\n'%(D[k],I[k]))
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file [and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored. ] Bracketed part not yet implemented
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets measurements format input file, default: measurements.txt
-fsp SPECFILE: sets specimens format file with prior interpreations, default: specimens.txt
-fsa SAMPFILE: sets samples format file sample=>site information, default: samples.txt
-fsi SITEFILE: sets sites format file with site=>location informationprior interpreations, default: samples.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave, e, b = 1, 0, 0 # average replicates, initial end and beginning step
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
plots, coord = 0, 's'
noorient = 0
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
calculation_type, fmt = "", "svg"
user, spec_keys, locname = "", [], ''
geo, tilt, ask = 0, 0, 0
PriorRecs = [] # empty list for prior interpretations
backup = 0
specimen = "" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg_from_sys("-f",
default_val="measurements.txt")
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")
#meas_file = os.path.join(dir_path, meas_file)
#spec_file = os.path.join(dir_path, spec_file)
#samp_file = os.path.join(dir_path, samp_file)
#site_file = os.path.join(dir_path, site_file)
plot_file = pmag.get_named_arg_from_sys("-Fp", default_val="")
crd = pmag.get_named_arg_from_sys("-crd", default_val="s")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
beg_pca, end_pca = "", ""
if '-dir' in sys.argv:
ind = sys.argv.index('-dir')
direction_type = sys.argv[ind + 1]
beg_pca = int(sys.argv[ind + 2])
end_pca = int(sys.argv[ind + 3])
if direction_type == 'L':
calculation_type = 'DE-BFL'
if direction_type == 'P':
calculation_type = 'DE-BFP'
if direction_type == 'F':
calculation_type = 'DE-FM'
if '-A' in sys.argv:
doave = 0
if '-sav' in sys.argv:
plots, verbose = 1, 0
#
first_save = 1
fnames = {
'measurements': meas_file,
'specimens': spec_file,
'samples': samp_file,
'sites': site_file
}
contribution = nb.Contribution(
dir_path,
custom_filenames=fnames,
read_tables=['measurements', 'specimens', 'samples', 'sites'])
#
# import specimens
specimen_cols = [
'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s',
'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma',
'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1',
'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95',
'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements',
'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment',
'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma',
'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma',
'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q',
'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max',
'meas_step_min', 'meas_step_unit', 'method_codes', 'sample',
'software_packages', 'specimen'
]
if 'specimens' in contribution.tables:
# contribution.propagate_name_down('sample','measurements')
spec_container = contribution.tables['specimens']
prior_spec_data = spec_container.get_records_for_code(
'LP-DIR', strict_match=False
) # look up all prior directional interpretations
#
# tie sample names to measurement data
#
else:
spec_container, prior_spec_data = None, []
#
# import samples for orientation info
#
if 'samples' in contribution.tables:
# contribution.propagate_name_down('site','measurements')
contribution.propagate_cols(
col_names=['azimuth', 'dip', 'orientation_flag'],
target_df_name='measurements',
source_df_name='samples')
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
#
ZED = {}
ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3
pmagplotlib.plot_init(ZED['eqarea'], 6, 6)
pmagplotlib.plot_init(ZED['zijd'], 6, 6)
pmagplotlib.plot_init(ZED['demag'], 6, 6)
# save_pca=0
angle, direction_type, setangle = "", "", 0
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LT-NO|LT-AF-Z|LT-T-Z|LT-M-Z') == True] # fish out steps for plotting
meas_data = meas_data[meas_data['method_codes'].str.contains(
'AN|ARM|LP-TRM|LP-PI-ARM') == False] # strip out unwanted experiments
intensity_types = [
col_name for col_name in meas_data.columns if col_name in intlist
]
# plot first intensity method found - normalized to initial value anyway -
# doesn't matter which used
int_key = intensity_types[0]
# get all the non-null intensity records of the same type
meas_data = meas_data[meas_data[int_key].notnull()]
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
# need to treat LP-NO specially for af data, treatment should be zero,
# otherwise 273.
meas_data['treatment'] = meas_data['treat_ac_field'].where(
cond=meas_data['treat_ac_field'] != '0', other=meas_data['treat_temp'])
meas_data['ZI'] = 1 # initialize these to one
meas_data['instrument_codes'] = "" # initialize these to blank
# for unusual case of microwave power....
if 'treat_mw_power' in meas_data.columns:
meas_data.loc[
meas_data.treat_mw_power != 0,
'treatment'] = meas_data.treat_mw_power * meas_data.treat_mw_time
#
# get list of unique specimen names from measurement data
#
# this is a list of all the specimen names
specimen_names = meas_data.specimen.unique()
specimen_names = specimen_names.tolist()
specimen_names.sort()
#
# set up new DataFrame for this sessions specimen interpretations
#
data_container = nb.MagicDataFrame(dtype='specimens',
columns=specimen_cols)
# this is for interpretations from this session
current_spec_data = data_container.df
locname = 'LookItUp'
if specimen == "":
k = 0
else:
k = specimen_names.index(specimen)
# let's look at the data now
while k < len(specimen_names):
# set the current specimen for plotting
this_specimen = specimen_names[k]
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
if setangle == 0:
angle = ""
this_specimen_measurements = meas_data[
meas_data['specimen'].str.contains(
this_specimen) == True] # fish out this specimen
this_specimen_measurements = this_specimen_measurements[
this_specimen_measurements['flag'].str.contains(
'g') == True] # fish out this specimen
if len(this_specimen_measurements) != 0: # if there are measurements
#
# set up datablock [[treatment,dec, inc, int, direction_type],[....]]
#
#
# figure out the method codes
#
units, methods, title = "", "", this_specimen
# this is a list of all the specimen method codes`
meas_meths = this_specimen_measurements.method_codes.unique()
tr = pd.to_numeric(this_specimen_measurements.treatment).tolist()
if set(tr) == set([0]):
k += 1
continue
for m in meas_meths:
if 'LT-AF-Z' in m:
units = 'T' # units include tesla
tr[0] = 0
if 'LT-T-Z' in m:
units = units + ":K" # units include kelvin
if 'LT-M-Z' in m:
units = units + ':J' # units include joules
tr[0] = 0
units = units.strip(':') # strip off extra colons
if 'LP-' in m:
methods = methods + ":" + m
decs = pd.to_numeric(this_specimen_measurements.dir_dec).tolist()
incs = pd.to_numeric(this_specimen_measurements.dir_inc).tolist()
#
# fix the coordinate system
#
if coord != '-1': # need to transform coordinates to geographic
azimuths = pd.to_numeric(this_specimen_measurements.azimuth
).tolist() # get the azimuths
# get the azimuths
dips = pd.to_numeric(this_specimen_measurements.dip).tolist()
dirs = [decs, incs, azimuths, dips]
# this transposes the columns and rows of the list of lists
dirs_geo = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dogeo_V(dirs_geo)
if coord == '100': # need to do tilt correction too
bed_dip_dirs = pd.to_numeric(
this_specimen_measurements.bed_dip_dir).tolist(
) # get the azimuths
bed_dips = pd.to_numeric(this_specimen_measurements.bed_dip
).tolist() # get the azimuths
dirs = [decs, incs, bed_dip_dirs, bed_dips]
# this transposes the columns and rows of the list of lists
dirs_tilt = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dotilt_V(dirs_tilt)
title = title + '_t'
else:
title = title + '_g'
if angle == "":
angle = decs[0]
ints = pd.to_numeric(this_specimen_measurements[int_key]).tolist()
ZI = this_specimen_measurements.ZI.tolist()
flags = this_specimen_measurements.flag.tolist()
codes = this_specimen_measurements.instrument_codes.tolist()
datalist = [tr, decs, incs, ints, ZI, flags, codes]
# this transposes the columns and rows of the list of lists
datablock = list(map(list, list(zip(*datalist))))
pmagplotlib.plotZED(ZED, datablock, angle, title, units)
if verbose:
pmagplotlib.drawFIGS(ZED)
#
# collect info for current_specimen_interpretation dictionary
#
if beg_pca == "" and len(prior_spec_data) != 0:
#
# find prior interpretation
#
prior_specimen_interpretations = prior_spec_data[
prior_spec_data['specimen'].str.contains(
this_specimen) == True]
beg_pcas = pd.to_numeric(prior_specimen_interpretations.
meas_step_min.values).tolist()
end_pcas = pd.to_numeric(prior_specimen_interpretations.
meas_step_max.values).tolist()
spec_methods = prior_specimen_interpretations.method_codes.tolist(
)
# step through all prior interpretations and plot them
for ind in range(len(beg_pcas)):
spec_meths = spec_methods[ind].split(':')
for m in spec_meths:
if 'DE-BFL' in m:
calculation_type = 'DE-BFL' # best fit line
if 'DE-BFP' in m:
calculation_type = 'DE-BFP' # best fit plane
if 'DE-FM' in m:
calculation_type = 'DE-FM' # fisher mean
if 'DE-BFL-A' in m:
calculation_type = 'DE-BFL-A' # anchored best fit line
start, end = tr.index(beg_pcas[ind]), tr.index(
end_pcas[ind]
) # getting the starting and ending points
# calculate direction/plane
mpars = pmag.domean(datablock, start, end,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
else:
start, end = int(beg_pca), int(end_pca)
# calculate direction/plane
mpars = pmag.domean(datablock, start, end, calculation_type)
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
if plots == 1 or specimen != "":
if plot_file == "":
basename = title
else:
basename = plot_file
files = {}
for key in list(ZED.keys()):
files[key] = basename + '_' + key + '.' + fmt
pmagplotlib.saveP(ZED, files)
if specimen != "":
sys.exit()
if verbose:
recnum = 0
for plotrec in datablock:
if units == 'T':
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] * 1e3, " mT",
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "K":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] - 273, ' C',
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "J":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0], ' J',
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if 'K' in units and 'T' in units:
if plotrec[0] >= 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] - 273, ' C',
plotrec[3], plotrec[1], plotrec[2],
plotrec[6]))
if plotrec[0] < 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] * 1e3, " mT",
plotrec[3], plotrec[1], plotrec[2],
plotrec[6]))
recnum += 1
# we have a current interpretation
elif mpars["specimen_direction_type"] != "Error":
#
# create a new specimen record for the interpreation for this
# specimen
this_specimen_interpretation = {
col: ""
for col in specimen_cols
}
# this_specimen_interpretation["analysts"]=user
this_specimen_interpretation['software_packages'] = version_num
this_specimen_interpretation['specimen'] = this_specimen
this_specimen_interpretation["method_codes"] = calculation_type
this_specimen_interpretation["meas_step_unit"] = units
this_specimen_interpretation["meas_step_min"] = tr[start]
this_specimen_interpretation["meas_step_max"] = tr[end]
this_specimen_interpretation["dir_dec"] = '%7.1f' % (
mpars['specimen_dec'])
this_specimen_interpretation["dir_inc"] = '%7.1f' % (
mpars['specimen_inc'])
this_specimen_interpretation["dir_dang"] = '%7.1f' % (
mpars['specimen_dang'])
this_specimen_interpretation["dir_n_measurements"] = '%i' % (
mpars['specimen_n'])
this_specimen_interpretation["dir_tilt_correction"] = coord
methods = methods.replace(" ", "")
if "T" in units:
methods = methods + ":LP-DIR-AF"
if "K" in units:
methods = methods + ":LP-DIR-T"
if "J" in units:
methods = methods + ":LP-DIR-M"
this_specimen_interpretation["method_codes"] = methods.strip(
':')
this_specimen_interpretation[
"experiments"] = this_specimen_measurements.experiment.unique(
)[0]
#
# print some stuff
#
if calculation_type != 'DE-FM':
this_specimen_interpretation["dir_mad_free"] = '%7.1f' % (
mpars['specimen_mad'])
this_specimen_interpretation["dir_alpha95"] = ''
if verbose:
if units == 'K':
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) - 273,
float(this_specimen_interpretation[
"meas_step_max"]) - 273,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif units == 'T':
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) * 1e3,
float(this_specimen_interpretation[
"meas_step_max"]) * 1e3,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation[
'meas_step_min']) < 1.0:
min = float(this_specimen_interpretation[
'meas_step_min']) * 1e3
else:
min = float(this_specimen_interpretation[
'meas_step_min']) - 273
if float(this_specimen_interpretation[
'meas_step_max']) < 1.0:
max = float(this_specimen_interpretation[
'meas_step_max']) * 1e3
else:
max = float(this_specimen_interpretation[
'meas_step_max']) - 273
print(
'%s %i %7.1f %i %i %7.1f %7.1f %7.1f %s \n' %
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
min, max,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]),
float(this_specimen_interpretation[
"meas_step_max"]),
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
this_specimen_interpretation["dir_alpha95"] = '%7.1f' % (
mpars['specimen_alpha95'])
this_specimen_interpretation["dir_mad_free"] = ''
if verbose:
if 'K' in units:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurments"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) - 273,
float(this_specimen_interpretation[
"meas_step_max"]) - 273,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_alpha95"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) * 1e3,
float(this_specimen_interpretation[
"meas_step_max"]) * 1e3,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation[
'meas_step_min']) < 1.0:
min = float(this_specimen_interpretation[
'meas_step_min']) * 1e3
else:
min = float(this_specimen_interpretation[
'meas_step_min']) - 273
if float(this_specimen_interpretation[
'meas_step_max']) < 1.0:
max = float(this_specimen_interpretation[
'meas_step_max']) * 1e3
else:
max = float(this_specimen_interpretation[
'meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %s \n' % (
this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(
this_specimen_interpretation["dir_alpha95"]
), min, max,
float(this_specimen_interpretation["dir_dec"]),
float(this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' %
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_alpha95"]),
float(this_specimen_interpretation[
"meas_step_min"]),
float(this_specimen_interpretation[
"meas_step_max"]),
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
if verbose:
saveit = input("Save this interpretation? [y]/n \n")
# START HERE
#
# if len(current_spec_data)==0: # no interpretations yet for this session
# print "no current interpretation"
# beg_pca,end_pca="",""
# calculation_type=""
# get the ones that meet the current coordinate system
else:
print("no data")
if verbose:
input('Ready for next specimen ')
k += 1
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file [and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored. ] Bracketed part not yet implemented
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets measurements format input file, default: measurements.txt
-fsp SPECFILE: sets specimens format file with prior interpreations, default: specimens.txt
-fsa SAMPFILE: sets samples format file sample=>site information, default: samples.txt
-fsi SITEFILE: sets sites format file with site=>location informationprior interpreations, default: samples.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave, e, b = 1, 0, 0 # average replicates, initial end and beginning step
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
plots, coord = 0, 's'
noorient = 0
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
calculation_type, fmt = "", "svg"
user, spec_keys, locname = "", [], ''
geo, tilt, ask = 0, 0, 0
PriorRecs = [] # empty list for prior interpretations
backup = 0
specimen = "" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg_from_sys(
"-f", default_val="measurements.txt")
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")
#meas_file = os.path.join(dir_path, meas_file)
#spec_file = os.path.join(dir_path, spec_file)
#samp_file = os.path.join(dir_path, samp_file)
#site_file = os.path.join(dir_path, site_file)
plot_file = pmag.get_named_arg_from_sys("-Fp", default_val="")
crd = pmag.get_named_arg_from_sys("-crd", default_val="s")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
beg_pca, end_pca = "", ""
if '-dir' in sys.argv:
ind = sys.argv.index('-dir')
direction_type = sys.argv[ind + 1]
beg_pca = int(sys.argv[ind + 2])
end_pca = int(sys.argv[ind + 3])
if direction_type == 'L':
calculation_type = 'DE-BFL'
if direction_type == 'P':
calculation_type = 'DE-BFP'
if direction_type == 'F':
calculation_type = 'DE-FM'
if '-A' in sys.argv:
doave = 0
if '-sav' in sys.argv:
plots, verbose = 1, 0
#
first_save = 1
fnames = {'measurements': meas_file, 'specimens': spec_file,
'samples': samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames, read_tables=[
'measurements', 'specimens', 'samples', 'sites'])
#
# import specimens
specimen_cols = ['analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s', 'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma', 'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1', 'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95', 'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements', 'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment', 'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma', 'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma', 'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q', 'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max', 'meas_step_min', 'meas_step_unit', 'method_codes', 'sample', 'software_packages', 'specimen']
if 'specimens' in contribution.tables:
# contribution.propagate_name_down('sample','measurements')
spec_container = contribution.tables['specimens']
if 'method_codes' not in spec_container.df.columns:
spec_container.df['method_codes'] = None
prior_spec_data = spec_container.get_records_for_code(
'LP-DIR', strict_match=False) # look up all prior directional interpretations
#
# tie sample names to measurement data
#
else:
spec_container, prior_spec_data = None, []
#
# import samples for orientation info
#
if ('samples' in contribution.tables) and ('specimens' in contribution.tables):
# contribution.propagate_name_down('site','measurements')
contribution.propagate_cols(col_names=[
'azimuth', 'dip', 'orientation_quality'], target_df_name='measurements', source_df_name='samples')
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
#
ZED = {}
ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3
pmagplotlib.plot_init(ZED['eqarea'], 6, 6)
pmagplotlib.plot_init(ZED['zijd'], 6, 6)
pmagplotlib.plot_init(ZED['demag'], 6, 6)
# save_pca=0
angle, direction_type, setangle = "", "", 0
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LT-NO|LT-AF-Z|LT-T-Z|LT-M-Z') == True] # fish out steps for plotting
meas_data = meas_data[meas_data['method_codes'].str.contains(
'AN|ARM|LP-TRM|LP-PI-ARM') == False] # strip out unwanted experiments
intensity_types = [
col_name for col_name in meas_data.columns if col_name in intlist]
intensity_types = [
col_name for col_name in intensity_types if any(meas_data[col_name])]
if not len(intensity_types):
print('-W- No intensity columns found')
return
# plot first non-empty intensity method found - normalized to initial value anyway -
# doesn't matter which used
int_key = intensity_types[0]
# get all the non-null intensity records of the same type
meas_data = meas_data[meas_data[int_key].notnull()]
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
# need to treat LP-NO specially for af data, treatment should be zero,
# otherwise 273.
meas_data['treatment'] = meas_data['treat_ac_field'].where(
cond=meas_data['treat_ac_field'] != 0, other=meas_data['treat_temp'])
meas_data['ZI'] = 1 # initialize these to one
meas_data['instrument_codes'] = "" # initialize these to blank
# for unusual case of microwave power....
if 'treat_mw_power' in meas_data.columns:
meas_data.loc[
(meas_data.treat_mw_power != 0) &
(meas_data.treat_mw_power) &
(meas_data.treat_mw_time),
'treatment'] = meas_data.treat_mw_power * meas_data.treat_mw_time
#
# get list of unique specimen names from measurement data
#
# this is a list of all the specimen names
specimen_names = meas_data.specimen.unique()
specimen_names = specimen_names.tolist()
specimen_names.sort()
#
# set up new DataFrame for this sessions specimen interpretations
#
data_container = nb.MagicDataFrame(
dtype='specimens', columns=specimen_cols)
# this is for interpretations from this session
current_spec_data = data_container.df
locname = 'LookItUp'
if specimen == "":
k = 0
else:
k = specimen_names.index(specimen)
# let's look at the data now
while k < len(specimen_names):
mpars = None
# set the current specimen for plotting
this_specimen = specimen_names[k]
# reset beginning/end pca if plotting more than one specimen
if not specimen:
beg_pca, end_pca = "", ""
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
if setangle == 0:
angle = ""
this_specimen_measurements = meas_data[meas_data['specimen'].str.contains(
this_specimen) == True] # fish out this specimen
this_specimen_measurements = this_specimen_measurements[this_specimen_measurements['flag'].str.contains(
'g') == True] # fish out this specimen
if len(this_specimen_measurements) != 0: # if there are measurements
#
# set up datablock [[treatment,dec, inc, int, direction_type],[....]]
#
#
# figure out the method codes
#
units, methods, title = "", "", this_specimen
# this is a list of all the specimen method codes`
meas_meths = this_specimen_measurements.method_codes.unique()
tr = pd.to_numeric(this_specimen_measurements.treatment).tolist()
if set(tr) == set([0]):
k += 1
continue
for m in meas_meths:
if 'LT-AF-Z' in m:
units = 'T' # units include tesla
tr[0] = 0
if 'LT-T-Z' in m:
units = units + ":K" # units include kelvin
if 'LT-M-Z' in m:
units = units + ':J' # units include joules
tr[0] = 0
units = units.strip(':') # strip off extra colons
if 'LP-' in m:
methods = methods + ":" + m
decs = pd.to_numeric(this_specimen_measurements.dir_dec).tolist()
incs = pd.to_numeric(this_specimen_measurements.dir_inc).tolist()
#
# fix the coordinate system
#
if coord != '-1': # need to transform coordinates to geographic
azimuths = pd.to_numeric(
this_specimen_measurements.azimuth).tolist() # get the azimuths
# get the azimuths
dips = pd.to_numeric(this_specimen_measurements.dip).tolist()
dirs = [decs, incs, azimuths, dips]
# this transposes the columns and rows of the list of lists
dirs_geo = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dogeo_V(dirs_geo)
if coord == '100': # need to do tilt correction too
bed_dip_dirs = pd.to_numeric(
this_specimen_measurements.bed_dip_dir).tolist() # get the azimuths
bed_dips = pd.to_numeric(
this_specimen_measurements.bed_dip).tolist() # get the azimuths
dirs = [decs, incs, bed_dip_dirs, bed_dips]
# this transposes the columns and rows of the list of lists
dirs_tilt = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dotilt_V(dirs_tilt)
title = title + '_t'
else:
title = title + '_g'
if angle == "":
angle = decs[0]
ints = pd.to_numeric(this_specimen_measurements[int_key]).tolist()
ZI = this_specimen_measurements.ZI.tolist()
flags = this_specimen_measurements.flag.tolist()
codes = this_specimen_measurements.instrument_codes.tolist()
datalist = [tr, decs, incs, ints, ZI, flags, codes]
# this transposes the columns and rows of the list of lists
datablock = list(map(list, list(zip(*datalist))))
pmagplotlib.plotZED(ZED, datablock, angle, title, units)
if verbose:
pmagplotlib.drawFIGS(ZED)
#
# collect info for current_specimen_interpretation dictionary
#
#
# find prior interpretation
#
prior_specimen_interpretations = prior_spec_data[prior_spec_data['specimen'].str.contains(this_specimen) == True]
if (beg_pca == "") and (len(prior_specimen_interpretations) != 0):
if len(prior_specimen_interpretations)>0:
beg_pcas = pd.to_numeric(
prior_specimen_interpretations.meas_step_min.values).tolist()
end_pcas = pd.to_numeric(
prior_specimen_interpretations.meas_step_max.values).tolist()
spec_methods = prior_specimen_interpretations.method_codes.tolist()
# step through all prior interpretations and plot them
for ind in range(len(beg_pcas)):
spec_meths = spec_methods[ind].split(':')
for m in spec_meths:
if 'DE-BFL' in m:
calculation_type = 'DE-BFL' # best fit line
if 'DE-BFP' in m:
calculation_type = 'DE-BFP' # best fit plane
if 'DE-FM' in m:
calculation_type = 'DE-FM' # fisher mean
if 'DE-BFL-A' in m:
calculation_type = 'DE-BFL-A' # anchored best fit line
start, end = tr.index(beg_pcas[ind]), tr.index(
end_pcas[ind]) # getting the starting and ending points
# calculate direction/plane
mpars = pmag.domean(
datablock, start, end, calculation_type)
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
else:
try:
start, end = int(beg_pca), int(end_pca)
except ValueError:
beg_pca = 0
end_pca = len(datablock) - 1
start, end = int(beg_pca), int(end_pca)
# calculate direction/plane
try:
mpars = pmag.domean(datablock, start, end, calculation_type)
except Exception as ex:
print('-I- Problem with {}'.format(this_specimen))
print(' ', ex)
print(' Skipping')
k += 1
continue
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
if plots == 1 or specimen != "":
if plot_file == "":
basename = title
else:
basename = plot_file
files = {}
for key in list(ZED.keys()):
files[key] = basename + '_' + key + '.' + fmt
pmagplotlib.saveP(ZED, files)
if specimen != "":
sys.exit()
if verbose:
recnum = 0
for plotrec in datablock:
if units == 'T':
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] * 1e3, " mT", plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "K":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] - 273, ' C', plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "J":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0], ' J', plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if 'K' in units and 'T' in units:
if plotrec[0] >= 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] - 273, ' C', plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if plotrec[0] < 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] * 1e3, " mT", plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
recnum += 1
# we have a current interpretation
elif mpars["specimen_direction_type"] != "Error":
#
# create a new specimen record for the interpreation for this
# specimen
this_specimen_interpretation = {
col: "" for col in specimen_cols}
# this_specimen_interpretation["analysts"]=user
this_specimen_interpretation['software_packages'] = version_num
this_specimen_interpretation['specimen'] = this_specimen
this_specimen_interpretation["method_codes"] = calculation_type
this_specimen_interpretation["meas_step_unit"] = units
this_specimen_interpretation["meas_step_min"] = tr[start]
this_specimen_interpretation["meas_step_max"] = tr[end]
this_specimen_interpretation["dir_dec"] = '%7.1f' % (
mpars['specimen_dec'])
this_specimen_interpretation["dir_inc"] = '%7.1f' % (
mpars['specimen_inc'])
this_specimen_interpretation["dir_dang"] = '%7.1f' % (
mpars['specimen_dang'])
this_specimen_interpretation["dir_n_measurements"] = '%i' % (
mpars['specimen_n'])
this_specimen_interpretation["dir_tilt_correction"] = coord
methods = methods.replace(" ", "")
if "T" in units:
methods = methods + ":LP-DIR-AF"
if "K" in units:
methods = methods + ":LP-DIR-T"
if "J" in units:
methods = methods + ":LP-DIR-M"
this_specimen_interpretation["method_codes"] = methods.strip(
':')
this_specimen_interpretation["experiments"] = this_specimen_measurements.experiment.unique()[
0]
#
# print some stuff
#
if calculation_type != 'DE-FM':
this_specimen_interpretation["dir_mad_free"] = '%7.1f' % (
mpars['specimen_mad'])
this_specimen_interpretation["dir_alpha95"] = ''
if verbose:
if units == 'K':
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) - 273, float(this_specimen_interpretation["meas_step_max"]) - 273, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif units == 'T':
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) * 1e3, float(this_specimen_interpretation["meas_step_max"]) * 1e3, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation['meas_step_min']) < 1.0:
min = float(
this_specimen_interpretation['meas_step_min']) * 1e3
else:
min = float(
this_specimen_interpretation['meas_step_min']) - 273
if float(this_specimen_interpretation['meas_step_max']) < 1.0:
max = float(
this_specimen_interpretation['meas_step_max']) * 1e3
else:
max = float(
this_specimen_interpretation['meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(
this_specimen_interpretation["dir_dang"]), min, max, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
else:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]), float(this_specimen_interpretation["meas_step_max"]), float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
else:
this_specimen_interpretation["dir_alpha95"] = '%7.1f' % (
mpars['specimen_alpha95'])
this_specimen_interpretation["dir_mad_free"] = ''
if verbose:
if 'K' in units:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurments"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) - 273, float(this_specimen_interpretation["meas_step_max"]) - 273, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif 'T' in units:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_alpha95"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) * 1e3, float(this_specimen_interpretation["meas_step_max"]) * 1e3, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation['meas_step_min']) < 1.0:
min = float(
this_specimen_interpretation['meas_step_min']) * 1e3
else:
min = float(
this_specimen_interpretation['meas_step_min']) - 273
if float(this_specimen_interpretation['meas_step_max']) < 1.0:
max = float(
this_specimen_interpretation['meas_step_max']) * 1e3
else:
max = float(
this_specimen_interpretation['meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(
this_specimen_interpretation["dir_alpha95"]), min, max, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
else:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_alpha95"]), float(
this_specimen_interpretation["meas_step_min"]), float(this_specimen_interpretation["meas_step_max"]), float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
if verbose:
saveit = input("Save this interpretation? [y]/n \n")
# START HERE
#
# if len(current_spec_data)==0: # no interpretations yet for this session
# print "no current interpretation"
# beg_pca,end_pca="",""
# calculation_type=""
# get the ones that meet the current coordinate system
else:
print("no data")
if verbose:
res = input(' <return> for next specimen, [q]uit ')
if res == 'q':
return
k += 1
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file [and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored. ] Bracketed part not yet implemented
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets measurements format input file, default: measurements.txt
-fsp SPECFILE: sets specimens format file with prior interpreations, default: specimens.txt
-fsa SAMPFILE: sets samples format file sample=>site information, default: samples.txt
-fsi SITEFILE: sets sites format file with site=>location informationprior interpreations, default: samples.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave, e, b = 1, 0, 0 # average replicates, initial end and beginning step
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
plots, coord = 0, 's'
noorient = 0
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
calculation_type, fmt = "", "svg"
spec_keys = []
geo, tilt, ask = 0, 0, 0
PriorRecs = [] # empty list for prior interpretations
backup = 0
specimen = "" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg("-f", default_val="measurements.txt")
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")
#meas_file = os.path.join(dir_path, meas_file)
#spec_file = os.path.join(dir_path, spec_file)
#samp_file = os.path.join(dir_path, samp_file)
#site_file = os.path.join(dir_path, site_file)
plot_file = pmag.get_named_arg("-Fp", default_val="")
crd = pmag.get_named_arg("-crd", default_val="s")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
saved_coord = coord
fmt = pmag.get_named_arg("-fmt", "svg")
specimen = pmag.get_named_arg("-spc", default_val="")
#if specimen: # just save plot and exit
# plots, verbose = 1, 0
beg_pca, end_pca = "", ""
if '-dir' in sys.argv:
ind = sys.argv.index('-dir')
direction_type = sys.argv[ind + 1]
beg_pca = int(sys.argv[ind + 2])
end_pca = int(sys.argv[ind + 3])
if direction_type == 'L':
calculation_type = 'DE-BFL'
if direction_type == 'P':
calculation_type = 'DE-BFP'
if direction_type == 'F':
calculation_type = 'DE-FM'
if '-A' in sys.argv:
doave = 0
if '-sav' in sys.argv:
plots, verbose = 1, 0
#
first_save = 1
fnames = {
'measurements': meas_file,
'specimens': spec_file,
'samples': samp_file,
'sites': site_file
}
contribution = cb.Contribution(
dir_path,
custom_filenames=fnames,
read_tables=['measurements', 'specimens', 'samples', 'sites'])
#
# import specimens
if 'measurements' not in contribution.tables:
print('-W- No measurements table found in your working directory')
return
specimen_cols = [
'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s',
'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma',
'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1',
'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95',
'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements',
'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment',
'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma',
'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma',
'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q',
'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max',
'meas_step_min', 'meas_step_unit', 'method_codes', 'sample',
'software_packages', 'specimen'
]
if 'specimens' in contribution.tables:
contribution.propagate_name_down('sample', 'measurements')
# add location/site info to measurements table for naming plots
if pmagplotlib.isServer:
contribution.propagate_name_down('site', 'measurements')
contribution.propagate_name_down('location', 'measurements')
spec_container = contribution.tables['specimens']
if 'method_codes' not in spec_container.df.columns:
spec_container.df['method_codes'] = None
prior_spec_data = spec_container.get_records_for_code(
'LP-DIR', strict_match=False
) # look up all prior directional interpretations
#
# tie sample names to measurement data
#
else:
spec_container, prior_spec_data = None, []
#
# import samples for orientation info
#
if 'samples' in contribution.tables:
samp_container = contribution.tables['samples']
samps = samp_container.df
samp_data = samps.to_dict(
'records'
) # convert to list of dictionaries for use with get_orient
else:
samp_data = []
#if ('samples' in contribution.tables) and ('specimens' in contribution.tables):
# # contribution.propagate_name_down('site','measurements')
# contribution.propagate_cols(col_names=[
# 'azimuth', 'dip', 'orientation_quality','bed_dip','bed_dip_direction'], target_df_name='measurements', source_df_name='samples')
##
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
#
ZED = {}
ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3
pmagplotlib.plot_init(ZED['eqarea'], 6, 6)
pmagplotlib.plot_init(ZED['zijd'], 6, 6)
pmagplotlib.plot_init(ZED['demag'], 6, 6)
# save_pca=0
angle, direction_type, setangle = "", "", 0
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LT-NO|LT-AF-Z|LT-T-Z|LT-M-Z') == True] # fish out steps for plotting
meas_data = meas_data[meas_data['method_codes'].str.contains(
'AN|ARM|LP-TRM|LP-PI-ARM') == False] # strip out unwanted experiments
intensity_types = [
col_name for col_name in meas_data.columns if col_name in intlist
]
intensity_types = [
col_name for col_name in intensity_types if any(meas_data[col_name])
]
if not len(intensity_types):
print('-W- No intensity columns found')
return
# plot first non-empty intensity method found - normalized to initial value anyway -
# doesn't matter which used
int_key = intensity_types[0]
# get all the non-null intensity records of the same type
meas_data = meas_data[meas_data[int_key].notnull()]
if 'quality' not in meas_data.columns:
meas_data['quality'] = 'g' # set the default flag to good
# need to treat LP-NO specially for af data, treatment should be zero,
# otherwise 273.
#meas_data['treatment'] = meas_data['treat_ac_field'].where(
# cond=meas_data['treat_ac_field'] != 0, other=meas_data['treat_temp'])
meas_data['treatment'] = meas_data['treat_ac_field'].where(
cond=meas_data['treat_ac_field'].astype(bool),
other=meas_data['treat_temp'])
meas_data['ZI'] = 1 # initialize these to one
meas_data['instrument_codes'] = "" # initialize these to blank
# for unusual case of microwave power....
if 'treat_mw_power' in meas_data.columns:
meas_data.loc[
(meas_data.treat_mw_power != 0) & (meas_data.treat_mw_power) &
(meas_data.treat_mw_time),
'treatment'] = meas_data.treat_mw_power * meas_data.treat_mw_time
#
# get list of unique specimen names from measurement data
#
# this is a list of all the specimen names
specimen_names = meas_data.specimen.unique()
specimen_names = specimen_names.tolist()
specimen_names.sort()
#
# set up new DataFrame for this sessions specimen interpretations
#
data_container = cb.MagicDataFrame(dtype='specimens',
columns=specimen_cols)
# this is for interpretations from this session
current_spec_data = data_container.df
if specimen == "":
k = 0
else:
k = specimen_names.index(specimen)
# let's look at the data now
while k < len(specimen_names):
mpars = {"specimen_direction_type": "Error"}
# set the current specimen for plotting
this_specimen = specimen_names[k]
# reset beginning/end pca if plotting more than one specimen
if not specimen:
beg_pca, end_pca = "", ""
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
if setangle == 0:
angle = ""
this_specimen_measurements = meas_data[
meas_data['specimen'].str.contains(this_specimen).astype(
bool)] # fish out this specimen
this_specimen_measurements = this_specimen_measurements[
-this_specimen_measurements['quality'].str.contains('b').astype(
bool)] # remove bad measurements
if len(this_specimen_measurements) != 0: # if there are measurements
meas_list = this_specimen_measurements.to_dict(
'records') # get a list of dictionaries
this_sample = ""
if coord != '-1' and 'sample' in meas_list[0].keys(
): # look up sample name
this_sample = pmag.get_dictitem(meas_list, 'specimen',
this_specimen, 'T')
if len(this_sample) > 0:
this_sample = this_sample[0]['sample']
#
# set up datablock [[treatment,dec, inc, int, direction_type],[....]]
#
#
# figure out the method codes
#
units, methods, title = "", "", this_specimen
if pmagplotlib.isServer:
try:
loc = this_specimen_measurements.loc[:,
'location'].values[0]
except:
loc = ""
try:
site = this_specimen_measurements.loc[:, 'site'].values[0]
except:
site = ""
try:
samp = this_specimen_measurements.loc[:,
'sample'].values[0]
except:
samp = ""
title = "LO:_{}_SI:_{}_SA:_{}_SP:_{}_".format(
loc, site, samp, this_specimen)
# this is a list of all the specimen method codes
meas_meths = this_specimen_measurements.method_codes.unique()
tr = pd.to_numeric(this_specimen_measurements.treatment).tolist()
if any(cb.is_null(treat, False) for treat in tr):
print(
'-W- Missing required values in measurements.treatment for {}, skipping'
.format(this_specimen))
if specimen:
return
k += 1
continue
if set(tr) == set([0]):
print(
'-W- Missing required values in measurements.treatment for {}, skipping'
.format(this_specimen))
if specimen:
return
k += 1
continue
for m in meas_meths:
if 'LT-AF-Z' in m and 'T' not in units:
units = 'T' # units include tesla
tr[0] = 0
if 'LT-T-Z' in m and 'K' not in units:
units = units + ":K" # units include kelvin
if 'LT-M-Z' in m and 'J' not in units:
units = units + ':J' # units include joules
tr[0] = 0
units = units.strip(':') # strip off extra colons
if 'LP-' in m:
methods = methods + ":" + m
decs = pd.to_numeric(this_specimen_measurements.dir_dec).tolist()
incs = pd.to_numeric(this_specimen_measurements.dir_inc).tolist()
#
# fix the coordinate system
#
# revert to original coordinate system
coord = saved_coord
if coord != '-1': # need to transform coordinates to geographic
# get the azimuth
or_info, az_type = pmag.get_orient(samp_data,
this_sample,
data_model=3)
if 'azimuth' in or_info.keys() and cb.not_null(
or_info['azimuth']):
#azimuths = pd.to_numeric(
# this_specimen_measurements.azimuth).tolist()
#dips = pd.to_numeric(this_specimen_measurements.dip).tolist()
azimuths = len(decs) * [or_info['azimuth']]
dips = len(decs) * [or_info['dip']]
# if azimuth/dip is missing, plot using specimen coordinates instead
else:
azimuths, dips = [], []
if any([cb.is_null(az) for az in azimuths if az != 0]):
coord = '-1'
print("-W- Couldn't find azimuth and dip for {}".format(
this_specimen))
print(" Plotting with specimen coordinates instead")
elif any([cb.is_null(dip) for dip in dips if dip != 0]):
coord = '-1'
print("-W- Couldn't find azimuth and dip for {}".format(
this_specimen))
print(" Plotting with specimen coordinates instead")
else:
coord = saved_coord
# if azimuth and dip were found, continue with geographic coordinates
if coord != "-1" and len(azimuths) > 0:
dirs = [decs, incs, azimuths, dips]
# this transposes the columns and rows of the list of lists
dirs_geo = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dogeo_V(dirs_geo)
if coord == '100' and 'bed_dip_direction' in or_info.keys(
) and or_info[
'bed_dip_direction'] != "": # need to do tilt correction too
bed_dip_dirs = len(decs) * [
or_info['bed_dip_direction']
]
bed_dips = len(decs) * [or_info['bed_dip']]
#bed_dip_dirs = pd.to_numeric(
# this_specimen_measurements.bed_dip_direction).tolist() # get the azimuths
#bed_dips = pd.to_numeric(
# this_specimen_measurements.bed_dip).tolist() # get the azimuths
dirs = [decs, incs, bed_dip_dirs, bed_dips]
## this transposes the columns and rows of the list of lists
dirs_tilt = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dotilt_V(dirs_tilt)
if pmagplotlib.isServer:
title = title + "CO:_t_"
else:
title = title + '_t'
else:
if pmagplotlib.isServer:
title = title + "CO:_g_"
else:
title = title + '_g'
if angle == "":
angle = decs[0]
ints = pd.to_numeric(this_specimen_measurements[int_key]).tolist()
ZI = this_specimen_measurements.ZI.tolist()
flags = this_specimen_measurements.quality.tolist()
codes = this_specimen_measurements.instrument_codes.tolist()
datalist = [tr, decs, incs, ints, ZI, flags, codes]
# this transposes the columns and rows of the list of lists
datablock = list(map(list, list(zip(*datalist))))
pmagplotlib.plot_zed(ZED, datablock, angle, title, units)
if verbose and not set_env.IS_WIN:
pmagplotlib.draw_figs(ZED)
#
# collect info for current_specimen_interpretation dictionary
#
#
# find prior interpretation
#
prior_specimen_interpretations = []
if len(prior_spec_data):
prior_specimen_interpretations = prior_spec_data[
prior_spec_data['specimen'].str.contains(
this_specimen) == True]
if (beg_pca == "") and (len(prior_specimen_interpretations) != 0):
if len(prior_specimen_interpretations) > 0:
beg_pcas = pd.to_numeric(prior_specimen_interpretations.
meas_step_min.values).tolist()
end_pcas = pd.to_numeric(prior_specimen_interpretations.
meas_step_max.values).tolist()
spec_methods = prior_specimen_interpretations.method_codes.tolist(
)
# step through all prior interpretations and plot them
for ind in range(len(beg_pcas)):
spec_meths = spec_methods[ind].split(':')
for m in spec_meths:
if 'DE-BFL' in m:
calculation_type = 'DE-BFL' # best fit line
if 'DE-BFP' in m:
calculation_type = 'DE-BFP' # best fit plane
if 'DE-FM' in m:
calculation_type = 'DE-FM' # fisher mean
if 'DE-BFL-A' in m:
calculation_type = 'DE-BFL-A' # anchored best fit line
if len(beg_pcas) != 0:
try:
# getting the starting and ending points
start, end = tr.index(beg_pcas[ind]), tr.index(
end_pcas[ind])
mpars = pmag.domean(datablock, start, end,
calculation_type)
except ValueError:
print(
'-W- Specimen record contains invalid start/stop bounds:'
)
mpars['specimen_direction_type'] = "Error"
# calculate direction/plane
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plot_dir(ZED, mpars, datablock,
angle)
if verbose and not set_env.IS_WIN:
pmagplotlib.draw_figs(ZED)
### SKIP if no prior interpretation - this section should not be used:
# else:
# try:
# start, end = int(beg_pca), int(end_pca)
# except ValueError:
# beg_pca = 0
# end_pca = len(datablock) - 1
# start, end = int(beg_pca), int(end_pca)
# # # calculate direction/plane
# try:
# mpars = pmag.domean(datablock, start, end, calculation_type)
# except Exception as ex:
# print('-I- Problem with {}'.format(this_specimen))
# print(' ', ex)
# print(' Skipping')
# continue
# k += 1
# if mpars["specimen_direction_type"] != "Error":
# # put it on the plot
# pmagplotlib.plot_dir(ZED, mpars, datablock, angle)
# if verbose:
# pmagplotlib.draw_figs(ZED)
if plots == 1 or specimen != "":
if plot_file == "":
basename = title
else:
basename = plot_file
files = {}
for key in list(ZED.keys()):
files[key] = basename + '_' + key + '.' + fmt
if pmagplotlib.isServer:
files[key] = basename + "TY:_{}_.".format(key) + fmt
pmagplotlib.save_plots(ZED, files)
if specimen != "":
sys.exit()
if verbose:
recnum = 0
for plotrec in datablock:
if units == 'T':
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] * 1e3, " mT",
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "K":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] - 273, ' C',
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "J":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0], ' J',
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if 'K' in units and 'T' in units:
if plotrec[0] >= 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] - 273, ' C',
plotrec[3], plotrec[1], plotrec[2],
plotrec[6]))
if plotrec[0] < 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] * 1e3, " mT",
plotrec[3], plotrec[1], plotrec[2],
plotrec[6]))
recnum += 1
# we have a current interpretation
elif mpars["specimen_direction_type"] != "Error":
#
# create a new specimen record for the interpreation for this
# specimen
this_specimen_interpretation = {
col: ""
for col in specimen_cols
}
# this_specimen_interpretation["analysts"]=user
this_specimen_interpretation['software_packages'] = version_num
this_specimen_interpretation['specimen'] = this_specimen
this_specimen_interpretation["method_codes"] = calculation_type
this_specimen_interpretation["meas_step_unit"] = units
this_specimen_interpretation["meas_step_min"] = tr[start]
this_specimen_interpretation["meas_step_max"] = tr[end]
this_specimen_interpretation["dir_dec"] = '%7.1f' % (
mpars['specimen_dec'])
this_specimen_interpretation["dir_inc"] = '%7.1f' % (
mpars['specimen_inc'])
this_specimen_interpretation["dir_dang"] = '%7.1f' % (
mpars['specimen_dang'])
this_specimen_interpretation["dir_n_measurements"] = '%i' % (
mpars['specimen_n'])
this_specimen_interpretation["dir_tilt_correction"] = coord
methods = methods.replace(" ", "")
if "T" in units:
methods = methods + ":LP-DIR-AF"
if "K" in units:
methods = methods + ":LP-DIR-T"
if "J" in units:
methods = methods + ":LP-DIR-M"
this_specimen_interpretation["method_codes"] = methods.strip(
':')
this_specimen_interpretation[
"experiments"] = this_specimen_measurements.experiment.unique(
)[0]
#
# print some stuff
#
if calculation_type != 'DE-FM':
this_specimen_interpretation["dir_mad_free"] = '%7.1f' % (
mpars['specimen_mad'])
this_specimen_interpretation["dir_alpha95"] = ''
if verbose:
if units == 'K':
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) - 273,
float(this_specimen_interpretation[
"meas_step_max"]) - 273,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif units == 'T':
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) * 1e3,
float(this_specimen_interpretation[
"meas_step_max"]) * 1e3,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation[
'meas_step_min']) < 1.0:
min = float(this_specimen_interpretation[
'meas_step_min']) * 1e3
else:
min = float(this_specimen_interpretation[
'meas_step_min']) - 273
if float(this_specimen_interpretation[
'meas_step_max']) < 1.0:
max = float(this_specimen_interpretation[
'meas_step_max']) * 1e3
else:
max = float(this_specimen_interpretation[
'meas_step_max']) - 273
print(
'%s %i %7.1f %i %i %7.1f %7.1f %7.1f %s \n' %
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
min, max,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]),
float(this_specimen_interpretation[
"meas_step_max"]),
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
this_specimen_interpretation["dir_alpha95"] = '%7.1f' % (
mpars['specimen_alpha95'])
this_specimen_interpretation["dir_mad_free"] = ''
if verbose:
if 'K' in units:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurments"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) - 273,
float(this_specimen_interpretation[
"meas_step_max"]) - 273,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_alpha95"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) * 1e3,
float(this_specimen_interpretation[
"meas_step_max"]) * 1e3,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation[
'meas_step_min']) < 1.0:
min = float(this_specimen_interpretation[
'meas_step_min']) * 1e3
else:
min = float(this_specimen_interpretation[
'meas_step_min']) - 273
if float(this_specimen_interpretation[
'meas_step_max']) < 1.0:
max = float(this_specimen_interpretation[
'meas_step_max']) * 1e3
else:
max = float(this_specimen_interpretation[
'meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %s \n' % (
this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(
this_specimen_interpretation["dir_alpha95"]
), min, max,
float(this_specimen_interpretation["dir_dec"]),
float(this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' %
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_alpha95"]),
float(this_specimen_interpretation[
"meas_step_min"]),
float(this_specimen_interpretation[
"meas_step_max"]),
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
if verbose:
saveit = input("Save this interpretation? [y]/n \n")
else:
print("no data", this_specimen)
if verbose:
pmagplotlib.draw_figs(ZED)
#res = input(' <return> for next specimen, [q]uit ')
res = input("S[a]ve plots, [q]uit, or <return> to continue ")
if res == 'a':
files = {
plot_type: this_specimen + "_" + plot_type + "." + fmt
for plot_type in ZED
}
pmagplotlib.save_plots(ZED, files)
print("")
if res == 'q':
return
k += 1
