def pca(data, selected_dots, system, approx_mode):
print(data, selected_dots, system, approx_mode)
df = data
n = len(selected_dots)
col_D = "Dg"
col_I = "Ig"
if system == "stratigraphic":
col_D = "Ds"
col_I = "Is"
first_col_name = "T"
if "M" in df.columns:
first_col_name = "M"
df["quality"] = "g"
data_to_pca = df[[first_col_name, col_D, col_I, "MAG", "quality"]].values.tolist()
answer = pmag.domean(data_to_pca, 0, n-1, approx_mode)
return answer["specimen_inc"], answer["specimen_dec"], answer["specimen_mad"]
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
thellier_magic.py
DESCRIPTION
plots Thellier-Thellier, allowing interactive setting of bounds
and customizing of selection criteria. Saves and reads interpretations
from a pmag_specimen formatted table, default: thellier_specimens.txt
SYNTAX
thellier_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEAS, set magic_measurements input file
-fsp PRIOR, set pmag_specimen prior interpretations file
-fan ANIS, set rmag_anisotropy file for doing the anisotropy corrections
-fcr CRIT, set criteria file for grading.
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out review (default format)
-spc SPEC, plots single specimen SPEC, saves plot with specified format
with optional -b bounds adn quits
-b BEG END: sets bounds for calculation
BEG: starting step for slope calculation
END: ending step for slope calculation
-z use only z component difference for pTRM calculation
DEFAULTS
MEAS: magic_measurements.txt
REDO: thellier_redo
CRIT: NONE
PRIOR: NONE
OUTPUT
figures:
ALL: numbers refer to temperature steps in command line window
1) Arai plot: closed circles are zero-field first/infield
open circles are infield first/zero-field
triangles are pTRM checks
squares are pTRM tail checks
VDS is vector difference sum
diamonds are bounds for interpretation
2) Zijderveld plot: closed (open) symbols are X-Y (X-Z) planes
X rotated to NRM direction
3) (De/Re)Magnetization diagram:
circles are NRM remaining
squares are pTRM gained
4) equal area projections:
green triangles are pTRM gained direction
red (purple) circles are lower(upper) hemisphere of ZI step directions
blue (cyan) squares are lower(upper) hemisphere IZ step directions
5) Optional: TRM acquisition
6) Optional: TDS normalization
command line window:
list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of magic_measuements)
list of possible commands: type letter followed by return to select option
saving of plots creates .svg format files with specimen_name, plot type as name
"""
#
# initializations
#
meas_file, critout, inspec = "magic_measurements.txt", "", "thellier_specimens.txt"
first = 1
inlt = 0
version_num = pmag.get_version()
TDinit, Tinit, field, first_save = 0, 0, -1, 1
user, comment, AniSpec, locname = "", '', "", ""
ans, specimen, recnum, start, end = 0, 0, 0, 0, 0
plots, pmag_out, samp_file, style = 0, "", "", "svg"
verbose = pmagplotlib.verbose
fmt = '.' + style
#
# default acceptance criteria
#
accept = pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
Zdiff, anis = 0, 0
spc, BEG, END = "", "", ""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index('-f')
meas_file = sys.argv[ind + 1]
if '-fsp' in sys.argv:
ind = sys.argv.index('-fsp')
inspec = sys.argv[ind + 1]
if '-fan' in sys.argv:
ind = sys.argv.index('-fan')
anisfile = sys.argv[ind + 1]
anis = 1
anis_data, file_type = pmag.magic_read(anisfile)
if verbose:
print("Anisotropy data read in from ", anisfile)
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = '.' + sys.argv[ind + 1]
if '-dpi' in sys.argv:
ind = sys.argv.index('-dpi')
dpi = '.' + sys.argv[ind + 1]
else:
dpi = 100
if '-sav' in sys.argv:
plots = 1
verbose = 0
if '-z' in sys.argv:
Zdiff = 1
if '-spc' in sys.argv:
ind = sys.argv.index('-spc')
spc = sys.argv[ind + 1]
if '-b' in sys.argv:
ind = sys.argv.index('-b')
BEG = int(sys.argv[ind + 1])
END = int(sys.argv[ind + 2])
if '-fcr' in sys.argv:
ind = sys.argv.index('-fcr')
critout = sys.argv[ind + 1]
crit_data, file_type = pmag.magic_read(critout)
if file_type != 'pmag_criteria':
if verbose:
print('bad pmag_criteria file, using no acceptance criteria')
accept = pmag.default_criteria(1)[0]
else:
if verbose:
print("Acceptance criteria read in from ", critout)
accept = {
'pmag_criteria_code': 'ACCEPTANCE',
'er_citation_names': 'This study'
}
for critrec in crit_data:
if 'sample_int_sigma_uT' in critrec.keys(
): # accommodate Shaar's new criterion
critrec['sample_int_sigma'] = '%10.3e' % (
eval(critrec['sample_int_sigma_uT']) * 1e-6)
for key in critrec.keys():
if key not in accept.keys() and critrec[key] != '':
accept[key] = critrec[key]
try:
open(inspec, 'rU')
PriorRecs, file_type = pmag.magic_read(inspec)
if file_type != 'pmag_specimens':
print(file_type)
print(file_type, inspec, " is not a valid pmag_specimens file ")
sys.exit()
for rec in PriorRecs:
if 'magic_software_packages' not in rec.keys():
rec['magic_software_packages'] = ""
except IOError:
PriorRecs = []
if verbose:
print("starting new specimen interpretation file: ", inspec)
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(file_type)
print(file_type, "This is not a valid magic_measurements file ")
sys.exit()
backup = 0
# define figure numbers for arai, zijderveld and
# de-,re-magization diagrams
AZD = {}
AZD['deremag'], AZD['zijd'], AZD['arai'], AZD['eqarea'] = 1, 2, 3, 4
pmagplotlib.plot_init(AZD['arai'], 5, 5)
pmagplotlib.plot_init(AZD['zijd'], 5, 5)
pmagplotlib.plot_init(AZD['deremag'], 5, 5)
pmagplotlib.plot_init(AZD['eqarea'], 5, 5)
#
#
#
# get list of unique specimen names
#
CurrRec = []
sids = pmag.get_specs(meas_data)
# get plots for specimen s - default is just to step through arai diagrams
#
if spc != "":
specimen = sids.index(spc)
while specimen < len(sids):
methcodes = []
if verbose:
print(sids[specimen], specimen + 1, 'of ', len(sids))
MeasRecs = []
s = sids[specimen]
datablock, trmblock, tdsrecs = [], [], []
PmagSpecRec = {}
if first == 0:
for key in keys:
# make sure all new records have same set of keys
PmagSpecRec[key] = ""
PmagSpecRec["er_analyst_mail_names"] = user
PmagSpecRec["specimen_correction"] = 'u'
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec["er_specimen_name"] == s:
MeasRecs.append(rec)
if "magic_method_codes" not in rec.keys():
rec["magic_method_codes"] = ""
methods = rec["magic_method_codes"].split(":")
meths = []
for meth in methods:
meths.append(meth.strip()) # take off annoying spaces
methods = ""
for meth in meths:
if meth.strip() not in methcodes and "LP-" in meth:
methcodes.append(meth.strip())
methods = methods + meth + ":"
methods = methods[:-1]
rec["magic_method_codes"] = methods
if "LP-PI-TRM" in meths:
datablock.append(rec)
if "LP-TRM" in meths:
trmblock.append(rec)
if "LP-TRM-TD" in meths:
tdsrecs.append(rec)
if len(trmblock) > 2 and inspec != "":
if Tinit == 0:
Tinit = 1
AZD['TRM'] = 5
pmagplotlib.plot_init(AZD['TRM'], 5, 5)
elif Tinit == 1: # clear the TRM figure if not needed
pmagplotlib.clearFIG(AZD['TRM'])
if len(tdsrecs) > 2:
if TDinit == 0:
TDinit = 1
AZD['TDS'] = 6
pmagplotlib.plot_init(AZD['TDS'], 5, 5)
elif TDinit == 1: # clear the TDS figure if not needed
pmagplotlib.clearFIG(AZD['TDS'])
if len(datablock) < 4:
if backup == 0:
specimen += 1
if verbose:
print('skipping specimen - moving forward ', s)
else:
specimen -= 1
if verbose:
print('skipping specimen - moving backward ', s)
#
# collect info for the PmagSpecRec dictionary
#
else:
rec = datablock[0]
PmagSpecRec["er_citation_names"] = "This study"
PmagSpecRec["er_specimen_name"] = s
PmagSpecRec["er_sample_name"] = rec["er_sample_name"]
PmagSpecRec["er_site_name"] = rec["er_site_name"]
PmagSpecRec["er_location_name"] = rec["er_location_name"]
locname = rec['er_location_name'].replace('/', '-')
if "er_expedition_name" in rec.keys():
PmagSpecRec["er_expedition_name"] = rec["er_expedition_name"]
if "magic_instrument_codes" not in rec.keys():
rec["magic_instrument_codes"] = ""
PmagSpecRec["magic_instrument_codes"] = rec[
"magic_instrument_codes"]
PmagSpecRec["measurement_step_unit"] = "K"
if "magic_experiment_name" not in rec.keys():
rec["magic_experiment_name"] = ""
else:
PmagSpecRec["magic_experiment_names"] = rec[
"magic_experiment_name"]
meths = rec["magic_method_codes"].split()
# sort data into types
araiblock, field = pmag.sortarai(datablock, s, Zdiff)
first_Z = araiblock[0]
GammaChecks = araiblock[5]
if len(first_Z) < 3:
if backup == 0:
specimen += 1
if verbose:
print('skipping specimen - moving forward ', s)
else:
specimen -= 1
if verbose:
print('skipping specimen - moving backward ', s)
else:
backup = 0
zijdblock, units = pmag.find_dmag_rec(s, meas_data)
recnum = 0
if verbose:
print("index step Dec Inc Int Gamma")
for plotrec in zijdblock:
if GammaChecks != "":
gamma = ""
for g in GammaChecks:
if g[0] == plotrec[0] - 273:
gamma = g[1]
break
if gamma != "":
print('%i %i %7.1f %7.1f %8.3e %7.1f' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3], gamma))
else:
print('%i %i %7.1f %7.1f %8.3e ' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3]))
recnum += 1
pmagplotlib.plot_arai_zij(AZD, araiblock, zijdblock, s,
units[0])
if verbose:
pmagplotlib.draw_figs(AZD)
if len(tdsrecs) > 2: # a TDS experiment
tdsblock = [] # make a list for the TDS data
Mkeys = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measuruement_magn_mass'
]
mkey, k = "", 0
# find which type of intensity
while mkey == "" and k < len(Mkeys) - 1:
key = Mkeys[k]
if key in tdsrecs[0].keys() and tdsrecs[0][key] != "":
mkey = key
k += 1
if mkey == "":
break # get outta here
Tnorm = ""
for tdrec in tdsrecs:
meths = tdrec['magic_method_codes'].split(":")
for meth in meths:
# strip off potential nasty spaces
meth.replace(" ", "")
if 'LT-T-I' in meths and Tnorm == "": # found first total TRM
# normalize by total TRM
Tnorm = float(tdrec[mkey])
# put in the zero step
tdsblock.append([273, zijdblock[0][3] / Tnorm, 1.])
# found a LP-TRM-TD demag step, now need complementary LT-T-Z from zijdblock
if 'LT-T-Z' in meths and Tnorm != "":
step = float(tdrec['treatment_temp'])
Tint = ""
if mkey != "":
Tint = float(tdrec[mkey])
if Tint != "":
for zrec in zijdblock:
if zrec[0] == step: # found matching
tdsblock.append([
step, zrec[3] / Tnorm, Tint / Tnorm
])
break
if len(tdsblock) > 2:
pmagplotlib.plot_tds(AZD['TDS'], tdsblock,
s + ':LP-PI-TDS:')
if verbose:
pmagplotlib(draw_figs(AZD))
else:
print("Something wrong here")
if anis == 1: # look up anisotropy data for this specimen
AniSpec = ""
for aspec in anis_data:
if aspec["er_specimen_name"] == PmagSpecRec[
"er_specimen_name"]:
AniSpec = aspec
if verbose:
print('Found anisotropy record...')
break
if inspec != "":
if verbose:
print('Looking up saved interpretation....')
found = 0
for k in range(len(PriorRecs)):
try:
if PriorRecs[k]["er_specimen_name"] == s:
found = 1
CurrRec.append(PriorRecs[k])
for j in range(len(zijdblock)):
if float(zijdblock[j][0]) == float(
PriorRecs[k]
["measurement_step_min"]):
start = j
if float(zijdblock[j][0]) == float(
PriorRecs[k]
["measurement_step_max"]):
end = j
pars, errcode = pmag.PintPars(
datablock, araiblock, zijdblock, start,
end, accept)
pars['measurement_step_unit'] = "K"
pars['experiment_type'] = 'LP-PI-TRM'
# put in CurrRec, take out of PriorRecs
del PriorRecs[k]
if errcode != 1:
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * \
field*pars["specimen_b"]
pars["er_specimen_name"] = s
if verbose:
print('Saved interpretation: ')
pars, kill = pmag.scoreit(
pars, PmagSpecRec, accept, '', verbose)
pmagplotlib.plot_b(AZD, araiblock,
zijdblock, pars)
if verbose:
pmagplotlib.draw_figs(AZD)
if len(trmblock) > 2:
blab = field
best = pars["specimen_int"]
Bs, TRMs = [], []
for trec in trmblock:
Bs.append(
float(
trec['treatment_dc_field'])
)
TRMs.append(
float(trec[
'measurement_magn_moment'])
)
# calculate best fit parameters through TRM acquisition data, and get new banc
NLpars = nlt.NLtrm(
Bs, TRMs, best, blab, 0)
Mp, Bp = [], []
for k in range(int(max(Bs) * 1e6)):
Bp.append(float(k) * 1e-6)
# predicted NRM for this field
npred = nlt.TRM(
Bp[-1], NLpars['xopt'][0],
NLpars['xopt'][1])
Mp.append(npred)
pmagplotlib.plot_trm(
AZD['TRM'], Bs, TRMs, Bp, Mp,
NLpars,
trec['magic_experiment_name'])
PmagSpecRec['specimen_int'] = NLpars[
'banc']
if verbose:
print('Banc= ',
float(NLpars['banc']) * 1e6)
pmagplotlib.draw_figs(AZD)
mpars = pmag.domean(
araiblock[1], start, end, 'DE-BFL')
if verbose:
print(
'pTRM direction= ',
'%7.1f' % (mpars['specimen_dec']),
' %7.1f' % (mpars['specimen_inc']),
' MAD:',
'%7.1f' % (mpars['specimen_mad']))
if AniSpec != "":
CpTRM = pmag.Dir_anis_corr([
mpars['specimen_dec'],
mpars['specimen_inc']
], AniSpec)
AniSpecRec = pmag.doaniscorr(
PmagSpecRec, AniSpec)
if verbose:
print(
'Anisotropy corrected TRM direction= ',
'%7.1f' % (CpTRM[0]),
' %7.1f' % (CpTRM[1]))
print(
'Anisotropy corrected intensity= ',
float(
AniSpecRec['specimen_int'])
* 1e6)
else:
print('error on specimen ', s)
except:
pass
if verbose and found == 0:
print(' None found :( ')
if spc != "":
if BEG != "":
pars, errcode = pmag.PintPars(datablock, araiblock,
zijdblock, BEG, END,
accept)
pars['measurement_step_unit'] = "K"
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars["specimen_b"]
pars["er_specimen_name"] = s
pars['specimen_grade'] = '' # ungraded
pmagplotlib.plot_b(AZD, araiblock, zijdblock, pars)
if verbose:
pmagplotlib.draw_figs(AZD)
if len(trmblock) > 2:
if inlt == 0:
inlt = 1
blab = field
best = pars["specimen_int"]
Bs, TRMs = [], []
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(
float(trec['measurement_magn_moment']))
# calculate best fit parameters through TRM acquisition data, and get new banc
NLpars = nlt.NLtrm(Bs, TRMs, best, blab, 0)
#
Mp, Bp = [], []
for k in range(int(max(Bs) * 1e6)):
Bp.append(float(k) * 1e-6)
# predicted NRM for this field
npred = nlt.TRM(Bp[-1], NLpars['xopt'][0],
NLpars['xopt'][1])
files = {}
for key in AZD.keys():
files[key] = s + '_' + key + fmt
pmagplotlib.save_plots(AZD, files, dpi=dpi)
sys.exit()
if verbose:
ans = 'b'
while ans != "":
print("""
s[a]ve plot, set [b]ounds for calculation, [d]elete current interpretation, [p]revious, [s]ample, [q]uit:
""")
ans = input('Return for next specimen \n')
if ans == "":
specimen += 1
if ans == "d":
save_redo(PriorRecs, inspec)
CurrRec = []
pmagplotlib.plot_arai_zij(AZD, araiblock,
zijdblock, s, units[0])
if verbose:
pmagplotlib.draw_figs(AZD)
if ans == 'a':
files = {}
for key in AZD.keys():
files[key] = "LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name'] + \
'_SA:_' + \
PmagSpecRec['er_sample_name'] + \
'_SP:_'+s+'_CO:_s_TY:_'+key+fmt
pmagplotlib.save_plots(AZD, files)
ans = ""
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 'p':
specimen = specimen - 1
backup = 1
ans = ""
if ans == 's':
keepon = 1
spec = input(
'Enter desired specimen name (or first part there of): '
)
while keepon == 1:
try:
specimen = sids.index(spec)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if spec in sids[qq]:
tmplist.append(sids[qq])
print(specimen,
" not found, but this was: ")
print(tmplist)
spec = input('Select one or try again\n ')
ans = ""
if ans == 'b':
if end == 0 or end >= len(zijdblock):
end = len(zijdblock) - 1
GoOn = 0
while GoOn == 0:
answer = input(
'Enter index of first point for calculation: ['
+ str(start) + '] ')
try:
start = int(answer)
answer = input(
'Enter index of last point for calculation: ['
+ str(end) + '] ')
end = int(answer)
if start >= 0 and start < len(
zijdblock
) - 2 and end > 0 and end < len(
zijdblock) or start >= end:
GoOn = 1
else:
print("Bad endpoints - try again! ")
start, end = 0, len(zijdblock)
except ValueError:
print("Bad endpoints - try again! ")
start, end = 0, len(zijdblock)
s = sids[specimen]
pars, errcode = pmag.PintPars(
datablock, araiblock, zijdblock, start, end,
accept)
pars['measurement_step_unit'] = "K"
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars[
"specimen_b"]
pars["er_specimen_name"] = s
pars, kill = pmag.scoreit(pars, PmagSpecRec,
accept, '', 0)
PmagSpecRec['specimen_scat'] = pars[
'specimen_scat']
PmagSpecRec['specimen_frac'] = '%5.3f' % (
pars['specimen_frac'])
PmagSpecRec['specimen_gmax'] = '%5.3f' % (
pars['specimen_gmax'])
PmagSpecRec["measurement_step_min"] = '%8.3e' % (
pars["measurement_step_min"])
PmagSpecRec["measurement_step_max"] = '%8.3e' % (
pars["measurement_step_max"])
PmagSpecRec["measurement_step_unit"] = "K"
PmagSpecRec["specimen_int_n"] = '%i' % (
pars["specimen_int_n"])
PmagSpecRec["specimen_lab_field_dc"] = '%8.3e' % (
pars["specimen_lab_field_dc"])
PmagSpecRec["specimen_int"] = '%9.4e ' % (
pars["specimen_int"])
PmagSpecRec["specimen_b"] = '%5.3f ' % (
pars["specimen_b"])
PmagSpecRec["specimen_q"] = '%5.1f ' % (
pars["specimen_q"])
PmagSpecRec["specimen_f"] = '%5.3f ' % (
pars["specimen_f"])
PmagSpecRec["specimen_fvds"] = '%5.3f' % (
pars["specimen_fvds"])
PmagSpecRec["specimen_b_beta"] = '%5.3f' % (
pars["specimen_b_beta"])
PmagSpecRec["specimen_int_mad"] = '%7.1f' % (
pars["specimen_int_mad"])
PmagSpecRec["specimen_Z"] = '%7.1f' % (
pars["specimen_Z"])
PmagSpecRec["specimen_gamma"] = '%7.1f' % (
pars["specimen_gamma"])
PmagSpecRec["specimen_grade"] = pars[
"specimen_grade"]
if pars["method_codes"] != "":
tmpcodes = pars["method_codes"].split(":")
for t in tmpcodes:
if t.strip() not in methcodes:
methcodes.append(t.strip())
PmagSpecRec["specimen_dec"] = '%7.1f' % (
pars["specimen_dec"])
PmagSpecRec["specimen_inc"] = '%7.1f' % (
pars["specimen_inc"])
PmagSpecRec["specimen_tilt_correction"] = '-1'
PmagSpecRec["specimen_direction_type"] = 'l'
# this is redundant, but helpful - won't be imported
PmagSpecRec["direction_type"] = 'l'
PmagSpecRec["specimen_int_dang"] = '%7.1f ' % (
pars["specimen_int_dang"])
PmagSpecRec["specimen_drats"] = '%7.1f ' % (
pars["specimen_drats"])
PmagSpecRec["specimen_drat"] = '%7.1f ' % (
pars["specimen_drat"])
PmagSpecRec["specimen_int_ptrm_n"] = '%i ' % (
pars["specimen_int_ptrm_n"])
PmagSpecRec["specimen_rsc"] = '%6.4f ' % (
pars["specimen_rsc"])
PmagSpecRec["specimen_md"] = '%i ' % (int(
pars["specimen_md"]))
if PmagSpecRec["specimen_md"] == '-1':
PmagSpecRec["specimen_md"] = ""
PmagSpecRec["specimen_b_sigma"] = '%5.3f ' % (
pars["specimen_b_sigma"])
if "IE-TT" not in methcodes:
methcodes.append("IE-TT")
methods = ""
for meth in methcodes:
methods = methods + meth + ":"
PmagSpecRec["magic_method_codes"] = methods[:-1]
PmagSpecRec["specimen_description"] = comment
PmagSpecRec[
"magic_software_packages"] = version_num
pmagplotlib.plot_arai_zij(AZD, araiblock,
zijdblock, s, units[0])
pmagplotlib.plot_b(AZD, araiblock, zijdblock, pars)
if verbose:
pmagplotlib.draw_figs(AZD)
if len(trmblock) > 2:
blab = field
best = pars["specimen_int"]
Bs, TRMs = [], []
for trec in trmblock:
Bs.append(float(
trec['treatment_dc_field']))
TRMs.append(
float(trec['measurement_magn_moment']))
# calculate best fit parameters through TRM acquisition data, and get new banc
NLpars = nlt.NLtrm(Bs, TRMs, best, blab, 0)
Mp, Bp = [], []
for k in range(int(max(Bs) * 1e6)):
Bp.append(float(k) * 1e-6)
# predicted NRM for this field
npred = nlt.TRM(Bp[-1], NLpars['xopt'][0],
NLpars['xopt'][1])
Mp.append(npred)
pmagplotlib.plot_trm(
AZD['TRM'], Bs, TRMs, Bp, Mp, NLpars,
trec['magic_experiment_name'])
if verbose:
print(
'Non-linear TRM corrected intensity= ',
float(NLpars['banc']) * 1e6)
if verbose:
pmagplotlib.draw_figs(AZD)
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars[
"specimen_b"]
pars, kill = pmag.scoreit(pars, PmagSpecRec,
accept, '', verbose)
saveit = input(
"Save this interpretation? [y]/n \n")
if saveit != 'n':
# put back an interpretation
PriorRecs.append(PmagSpecRec)
specimen += 1
save_redo(PriorRecs, inspec)
ans = ""
elif plots == 1:
specimen += 1
if fmt != ".pmag":
files = {}
for key in AZD.keys():
files[key] = "LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_' + \
PmagSpecRec['er_sample_name'] + \
'_SP:_'+s+'_CO:_s_TY:_'+key+'_'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['deremag'] = 'DeReMag Plot'
titles['zijd'] = 'Zijderveld Plot'
titles['arai'] = 'Arai Plot'
AZD = pmagplotlib.add_borders(
AZD, titles, black, purple)
pmagplotlib.save_plots(AZD, files, dpi=dpi)
# pmagplotlib.combineFigs(s,files,3)
else: # save in pmag format
script = "grep " + s + " output.mag | thellier -mfsi"
script = script + ' %8.4e' % (field)
min = '%i' % ((pars["measurement_step_min"] - 273))
Max = '%i' % ((pars["measurement_step_max"] - 273))
script = script + " " + min + " " + Max
script = script + " |plotxy;cat mypost >>thellier.ps\n"
pltf.write(script)
pmag.domagicmag(outf, MeasRecs)
if len(CurrRec) > 0:
for rec in CurrRec:
PriorRecs.append(rec)
CurrRec = []
if plots != 1 and verbose:
ans = input(" Save last plot? 1/[0] ")
if ans == "1":
if fmt != ".pmag":
files = {}
for key in AZD.keys():
files[key] = s + '_' + key + fmt
pmagplotlib.save_plots(AZD, files, dpi=dpi)
else:
print("\n Good bye\n")
sys.exit()
if len(CurrRec) > 0:
PriorRecs.append(CurrRec) # put back an interpretation
if len(PriorRecs) > 0:
save_redo(PriorRecs, inspec)
print('Updated interpretations saved in ', inspec)
if verbose:
print("Good bye")
def main():
"""
NAME
thellier_magic.py
DESCRIPTION
plots Thellier-Thellier, allowing interactive setting of bounds
and customizing of selection criteria. Saves and reads interpretations
from a pmag_specimen formatted table, default: thellier_specimens.txt
SYNTAX
thellier_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEAS, set magic_measurements input file
-fsp PRIOR, set pmag_specimen prior interpretations file
-fan ANIS, set rmag_anisotropy file for doing the anisotropy corrections
-fcr CRIT, set criteria file for grading.
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out review (default format)
-spc SPEC, plots single specimen SPEC, saves plot with specified format
with optional -b bounds adn quits
-b BEG END: sets bounds for calculation
BEG: starting step for slope calculation
END: ending step for slope calculation
-z use only z component difference for pTRM calculation
DEFAULTS
MEAS: magic_measurements.txt
REDO: thellier_redo
CRIT: NONE
PRIOR: NONE
OUTPUT
figures:
ALL: numbers refer to temperature steps in command line window
1) Arai plot: closed circles are zero-field first/infield
open circles are infield first/zero-field
triangles are pTRM checks
squares are pTRM tail checks
VDS is vector difference sum
diamonds are bounds for interpretation
2) Zijderveld plot: closed (open) symbols are X-Y (X-Z) planes
X rotated to NRM direction
3) (De/Re)Magnetization diagram:
circles are NRM remaining
squares are pTRM gained
4) equal area projections:
green triangles are pTRM gained direction
red (purple) circles are lower(upper) hemisphere of ZI step directions
blue (cyan) squares are lower(upper) hemisphere IZ step directions
5) Optional: TRM acquisition
6) Optional: TDS normalization
command line window:
list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of magic_measuements)
list of possible commands: type letter followed by return to select option
saving of plots creates .svg format files with specimen_name, plot type as name
"""
#
# initializations
#
meas_file,critout,inspec="magic_measurements.txt","","thellier_specimens.txt"
first=1
inlt=0
version_num=pmag.get_version()
TDinit,Tinit,field,first_save=0,0,-1,1
user,comment,AniSpec,locname="",'',"",""
ans,specimen,recnum,start,end=0,0,0,0,0
plots,pmag_out,samp_file,style=0,"","","svg"
verbose=pmagplotlib.verbose
fmt='.'+style
#
# default acceptance criteria
#
accept=pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
Zdiff,anis=0,0
spc,BEG,END="","",""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
meas_file=sys.argv[ind+1]
if '-fsp' in sys.argv:
ind=sys.argv.index('-fsp')
inspec=sys.argv[ind+1]
if '-fan' in sys.argv:
ind=sys.argv.index('-fan')
anisfile=sys.argv[ind+1]
anis=1
anis_data,file_type=pmag.magic_read(anisfile)
if verbose: print "Anisotropy data read in from ", anisfile
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt='.'+sys.argv[ind+1]
if '-dpi' in sys.argv:
ind=sys.argv.index('-dpi')
dpi='.'+sys.argv[ind+1]
else: dpi=100
if '-sav' in sys.argv:
plots=1
verbose=0
if '-z' in sys.argv: Zdiff=1
if '-spc' in sys.argv:
ind=sys.argv.index('-spc')
spc=sys.argv[ind+1]
if '-b' in sys.argv:
ind=sys.argv.index('-b')
BEG=int(sys.argv[ind+1])
END=int(sys.argv[ind+2])
if '-fcr' in sys.argv:
ind=sys.argv.index('-fcr')
critout=sys.argv[ind+1]
crit_data,file_type=pmag.magic_read(critout)
if file_type!='pmag_criteria':
if verbose: print 'bad pmag_criteria file, using no acceptance criteria'
accept=pmag.default_criteria(1)[0]
else:
if verbose: print "Acceptance criteria read in from ", critout
accept={'pmag_criteria_code':'ACCEPTANCE','er_citation_names':'This study'}
for critrec in crit_data:
if 'sample_int_sigma_uT' in critrec.keys(): # accommodate Shaar's new criterion
critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
for key in critrec.keys():
if key not in accept.keys() and critrec[key]!='':
accept[key]=critrec[key]
try:
open(inspec,'rU')
PriorRecs,file_type=pmag.magic_read(inspec)
if file_type != 'pmag_specimens':
print file_type
print file_type,inspec," is not a valid pmag_specimens file "
sys.exit()
for rec in PriorRecs:
if 'magic_software_packages' not in rec.keys():rec['magic_software_packages']=""
except IOError:
PriorRecs=[]
if verbose:print "starting new specimen interpretation file: ",inspec
meas_data,file_type=pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print file_type
print file_type,"This is not a valid magic_measurements file "
sys.exit()
backup=0
# define figure numbers for arai, zijderveld and
# de-,re-magization diagrams
AZD={}
AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
pmagplotlib.plot_init(AZD['arai'],5,5)
pmagplotlib.plot_init(AZD['zijd'],5,5)
pmagplotlib.plot_init(AZD['deremag'],5,5)
pmagplotlib.plot_init(AZD['eqarea'],5,5)
#
#
#
# get list of unique specimen names
#
CurrRec=[]
sids=pmag.get_specs(meas_data)
# get plots for specimen s - default is just to step through arai diagrams
#
if spc!="": specimen =sids.index(spc)
while specimen < len(sids):
methcodes=[]
if verbose:
print sids[specimen],specimen+1, 'of ', len(sids)
MeasRecs=[]
s=sids[specimen]
datablock,trmblock,tdsrecs=[],[],[]
PmagSpecRec={}
if first==0:
for key in keys:PmagSpecRec[key]="" # make sure all new records have same set of keys
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec["specimen_correction"]='u'
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec["er_specimen_name"]==s:
MeasRecs.append(rec)
if "magic_method_codes" not in rec.keys():
rec["magic_method_codes"]=""
methods=rec["magic_method_codes"].split(":")
meths=[]
for meth in methods:
meths.append(meth.strip()) # take off annoying spaces
methods=""
for meth in meths:
if meth.strip() not in methcodes and "LP-" in meth:methcodes.append(meth.strip())
methods=methods+meth+":"
methods=methods[:-1]
rec["magic_method_codes"]=methods
if "LP-PI-TRM" in meths: datablock.append(rec)
if "LP-TRM" in meths: trmblock.append(rec)
if "LP-TRM-TD" in meths: tdsrecs.append(rec)
if len(trmblock)>2 and inspec!="":
if Tinit==0:
Tinit=1
AZD['TRM']=5
pmagplotlib.plot_init(AZD['TRM'],5,5)
elif Tinit==1: # clear the TRM figure if not needed
pmagplotlib.clearFIG(AZD['TRM'])
if len(tdsrecs)>2:
if TDinit==0:
TDinit=1
AZD['TDS']=6
pmagplotlib.plot_init(AZD['TDS'],5,5)
elif TDinit==1: # clear the TDS figure if not needed
pmagplotlib.clearFIG(AZD['TDS'])
if len(datablock) <4:
if backup==0:
specimen+=1
if verbose:
print 'skipping specimen - moving forward ', s
else:
specimen-=1
if verbose:
print 'skipping specimen - moving backward ', s
#
# collect info for the PmagSpecRec dictionary
#
else:
rec=datablock[0]
PmagSpecRec["er_citation_names"]="This study"
PmagSpecRec["er_specimen_name"]=s
PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
PmagSpecRec["er_site_name"]=rec["er_site_name"]
PmagSpecRec["er_location_name"]=rec["er_location_name"]
locname=rec['er_location_name'].replace('/','-')
if "er_expedition_name" in rec.keys():PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
if "magic_instrument_codes" not in rec.keys():rec["magic_instrument_codes"]=""
PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"]
PmagSpecRec["measurement_step_unit"]="K"
if "magic_experiment_name" not in rec.keys():
rec["magic_experiment_name"]=""
else:
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
meths=rec["magic_method_codes"].split()
# sort data into types
araiblock,field=pmag.sortarai(datablock,s,Zdiff)
first_Z=araiblock[0]
GammaChecks=araiblock[5]
if len(first_Z)<3:
if backup==0:
specimen+=1
if verbose:
print 'skipping specimen - moving forward ', s
else:
specimen-=1
if verbose:
print 'skipping specimen - moving backward ', s
else:
backup=0
zijdblock,units=pmag.find_dmag_rec(s,meas_data)
recnum=0
if verbose:
print "index step Dec Inc Int Gamma"
for plotrec in zijdblock:
if GammaChecks!="":
gamma=""
for g in GammaChecks:
if g[0]==plotrec[0]-273:
gamma=g[1]
break
if gamma!="":
print '%i %i %7.1f %7.1f %8.3e %7.1f' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3],gamma)
else:
print '%i %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3])
recnum += 1
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
if verbose:pmagplotlib.drawFIGS(AZD)
if len(tdsrecs)>2: # a TDS experiment
tdsblock=[] # make a list for the TDS data
Mkeys=['measurement_magnitude','measurement_magn_moment','measurement_magn_volume','measuruement_magn_mass']
mkey,k="",0
while mkey=="" and k<len(Mkeys)-1: # find which type of intensity
key= Mkeys[k]
if key in tdsrecs[0].keys() and tdsrecs[0][key]!="": mkey=key
k+=1
if mkey=="":break # get outta here
Tnorm=""
for tdrec in tdsrecs:
meths=tdrec['magic_method_codes'].split(":")
for meth in meths: meth.replace(" ","") # strip off potential nasty spaces
if 'LT-T-I' in meths and Tnorm=="": # found first total TRM
Tnorm=float(tdrec[mkey]) # normalize by total TRM
tdsblock.append([273,zijdblock[0][3]/Tnorm,1.]) # put in the zero step
if 'LT-T-Z' in meths and Tnorm!="": # found a LP-TRM-TD demag step, now need complementary LT-T-Z from zijdblock
step=float(tdrec['treatment_temp'])
Tint=""
if mkey!="":
Tint=float(tdrec[mkey])
if Tint!="":
for zrec in zijdblock:
if zrec[0]==step: # found matching
tdsblock.append([step,zrec[3]/Tnorm,Tint/Tnorm])
break
if len(tdsblock)>2:
pmagplotlib.plotTDS(AZD['TDS'],tdsblock,s+':LP-PI-TDS:')
if verbose:pmagplotlib(drawFIGS(AZD))
else:
print "Something wrong here"
if anis==1: # look up anisotropy data for this specimen
AniSpec=""
for aspec in anis_data:
if aspec["er_specimen_name"]==PmagSpecRec["er_specimen_name"]:
AniSpec=aspec
if verbose: print 'Found anisotropy record...'
break
if inspec !="":
if verbose: print 'Looking up saved interpretation....'
found = 0
for k in range(len(PriorRecs)):
try:
if PriorRecs[k]["er_specimen_name"]==s:
found =1
CurrRec.append(PriorRecs[k])
for j in range(len(zijdblock)):
if float(zijdblock[j][0])==float(PriorRecs[k]["measurement_step_min"]):start=j
if float(zijdblock[j][0])==float(PriorRecs[k]["measurement_step_max"]):end=j
pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,start,end,accept)
pars['measurement_step_unit']="K"
pars['experiment_type']='LP-PI-TRM'
del PriorRecs[k] # put in CurrRec, take out of PriorRecs
if errcode!=1:
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=s
if verbose:
print 'Saved interpretation: '
pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',verbose)
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
if verbose:pmagplotlib.drawFIGS(AZD)
if len(trmblock)>2:
blab=field
best=pars["specimen_int"]
Bs,TRMs=[],[]
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(float(trec['measurement_magn_moment']))
NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
Mp,Bp=[],[]
for k in range(int(max(Bs)*1e6)):
Bp.append(float(k)*1e-6)
npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
Mp.append(npred)
pmagplotlib.plotTRM(AZD['TRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
PmagSpecRec['specimen_int']=NLpars['banc']
if verbose:
print 'Banc= ',float(NLpars['banc'])*1e6
pmagplotlib.drawFIGS(AZD)
mpars=pmag.domean(araiblock[1],start,end,'DE-BFL')
if verbose:
print 'pTRM direction= ','%7.1f'%(mpars['specimen_dec']),' %7.1f'%(mpars['specimen_inc']),' MAD:','%7.1f'%(mpars['specimen_mad'])
if AniSpec!="":
CpTRM=pmag.Dir_anis_corr([mpars['specimen_dec'],mpars['specimen_inc']],AniSpec)
AniSpecRec=pmag.doaniscorr(PmagSpecRec,AniSpec)
if verbose:
print 'Anisotropy corrected TRM direction= ','%7.1f'%(CpTRM[0]),' %7.1f'%(CpTRM[1])
print 'Anisotropy corrected intensity= ',float(AniSpecRec['specimen_int'])*1e6
else:
print 'error on specimen ',s
except:
pass
if verbose and found==0: print ' None found :( '
if spc!="":
if BEG!="":
pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,BEG,END,accept)
pars['measurement_step_unit']="K"
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=s
pars['specimen_grade']='' # ungraded
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
if verbose:pmagplotlib.drawFIGS(AZD)
if len(trmblock)>2:
if inlt==0:
inlt=1
blab=field
best=pars["specimen_int"]
Bs,TRMs=[],[]
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(float(trec['measurement_magn_moment']))
NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
#
Mp,Bp=[],[]
for k in range(int(max(Bs)*1e6)):
Bp.append(float(k)*1e-6)
npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
files={}
for key in AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(AZD,files,dpi=dpi)
sys.exit()
if verbose:
ans='b'
while ans != "":
print """
s[a]ve plot, set [b]ounds for calculation, [d]elete current interpretation, [p]revious, [s]ample, [q]uit:
"""
ans=raw_input('Return for next specimen \n')
if ans=="":
specimen +=1
if ans=="d":
save_redo(PriorRecs,inspec)
CurrRec=[]
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
if verbose:pmagplotlib.drawFIGS(AZD)
if ans=='a':
files={}
for key in AZD.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_s_TY:_'+key+fmt
pmagplotlib.saveP(AZD,files)
ans=""
if ans=='q':
print "Good bye"
sys.exit()
if ans=='p':
specimen =specimen -1
backup = 1
ans=""
if ans=='s':
keepon=1
spec=raw_input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
specimen =sids.index(spec)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if spec in sids[qq]:tmplist.append(sids[qq])
print specimen," not found, but this was: "
print tmplist
spec=raw_input('Select one or try again\n ')
ans=""
if ans=='b':
if end==0 or end >=len(zijdblock):end=len(zijdblock)-1
GoOn=0
while GoOn==0:
answer=raw_input('Enter index of first point for calculation: ['+str(start)+'] ')
try:
start=int(answer)
answer=raw_input('Enter index of last point for calculation: ['+str(end)+'] ')
end=int(answer)
if start >=0 and start <len(zijdblock)-2 and end >0 and end <len(zijdblock) or start>=end:
GoOn=1
else:
print "Bad endpoints - try again! "
start,end=0,len(zijdblock)
except ValueError:
print "Bad endpoints - try again! "
start,end=0,len(zijdblock)
s=sids[specimen]
pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,start,end,accept)
pars['measurement_step_unit']="K"
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=s
pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',0)
PmagSpecRec['specimen_scat']=pars['specimen_scat']
PmagSpecRec['specimen_frac']='%5.3f'%(pars['specimen_frac'])
PmagSpecRec['specimen_gmax']='%5.3f'%(pars['specimen_gmax'])
PmagSpecRec["measurement_step_min"]='%8.3e' % (pars["measurement_step_min"])
PmagSpecRec["measurement_step_max"]='%8.3e' % (pars["measurement_step_max"])
PmagSpecRec["measurement_step_unit"]="K"
PmagSpecRec["specimen_int_n"]='%i'%(pars["specimen_int_n"])
PmagSpecRec["specimen_lab_field_dc"]='%8.3e'%(pars["specimen_lab_field_dc"])
PmagSpecRec["specimen_int"]='%9.4e '%(pars["specimen_int"])
PmagSpecRec["specimen_b"]='%5.3f '%(pars["specimen_b"])
PmagSpecRec["specimen_q"]='%5.1f '%(pars["specimen_q"])
PmagSpecRec["specimen_f"]='%5.3f '%(pars["specimen_f"])
PmagSpecRec["specimen_fvds"]='%5.3f'%(pars["specimen_fvds"])
PmagSpecRec["specimen_b_beta"]='%5.3f'%(pars["specimen_b_beta"])
PmagSpecRec["specimen_int_mad"]='%7.1f'%(pars["specimen_int_mad"])
PmagSpecRec["specimen_Z"]='%7.1f'%(pars["specimen_Z"])
PmagSpecRec["specimen_gamma"]='%7.1f'%(pars["specimen_gamma"])
PmagSpecRec["specimen_grade"]=pars["specimen_grade"]
if pars["method_codes"]!="":
tmpcodes=pars["method_codes"].split(":")
for t in tmpcodes:
if t.strip() not in methcodes:methcodes.append(t.strip())
PmagSpecRec["specimen_dec"]='%7.1f'%(pars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f'%(pars["specimen_inc"])
PmagSpecRec["specimen_tilt_correction"]='-1'
PmagSpecRec["specimen_direction_type"]='l'
PmagSpecRec["direction_type"]='l' # this is redundant, but helpful - won't be imported
PmagSpecRec["specimen_int_dang"]='%7.1f '%(pars["specimen_int_dang"])
PmagSpecRec["specimen_drats"]='%7.1f '%(pars["specimen_drats"])
PmagSpecRec["specimen_drat"]='%7.1f '%(pars["specimen_drat"])
PmagSpecRec["specimen_int_ptrm_n"]='%i '%(pars["specimen_int_ptrm_n"])
PmagSpecRec["specimen_rsc"]='%6.4f '%(pars["specimen_rsc"])
PmagSpecRec["specimen_md"]='%i '%(int(pars["specimen_md"]))
if PmagSpecRec["specimen_md"]=='-1':PmagSpecRec["specimen_md"]=""
PmagSpecRec["specimen_b_sigma"]='%5.3f '%(pars["specimen_b_sigma"])
if "IE-TT" not in methcodes:methcodes.append("IE-TT")
methods=""
for meth in methcodes:
methods=methods+meth+":"
PmagSpecRec["magic_method_codes"]=methods[:-1]
PmagSpecRec["specimen_description"]=comment
PmagSpecRec["magic_software_packages"]=version_num
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
if verbose:pmagplotlib.drawFIGS(AZD)
if len(trmblock)>2:
blab=field
best=pars["specimen_int"]
Bs,TRMs=[],[]
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(float(trec['measurement_magn_moment']))
NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
Mp,Bp=[],[]
for k in range(int(max(Bs)*1e6)):
Bp.append(float(k)*1e-6)
npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
Mp.append(npred)
pmagplotlib.plotTRM(AZD['TRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
if verbose:
print 'Non-linear TRM corrected intensity= ',float(NLpars['banc'])*1e6
if verbose:pmagplotlib.drawFIGS(AZD)
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',verbose)
saveit=raw_input("Save this interpretation? [y]/n \n")
if saveit!='n':
PriorRecs.append(PmagSpecRec) # put back an interpretation
specimen+=1
save_redo(PriorRecs,inspec)
ans=""
elif plots==1:
specimen+=1
if fmt != ".pmag":
files={}
for key in AZD.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_s_TY:_'+key+'_'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['deremag']='DeReMag Plot'
titles['zijd']='Zijderveld Plot'
titles['arai']='Arai Plot'
AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
pmagplotlib.saveP(AZD,files,dpi=dpi)
# pmagplotlib.combineFigs(s,files,3)
else: # save in pmag format
script="grep "+s+" output.mag | thellier -mfsi"
script=script+' %8.4e'%(field)
min='%i'%((pars["measurement_step_min"]-273))
Max='%i'%((pars["measurement_step_max"]-273))
script=script+" "+min+" "+Max
script=script+" |plotxy;cat mypost >>thellier.ps\n"
pltf.write(script)
pmag.domagicmag(outf,MeasRecs)
if len(CurrRec)>0:
for rec in CurrRec:
PriorRecs.append(rec)
CurrRec=[]
if plots!=1 and verbose:
ans=raw_input(" Save last plot? 1/[0] ")
if ans=="1":
if fmt != ".pmag":
files={}
for key in AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(AZD,files,dpi=dpi)
else:
print "\n Good bye\n"
sys.exit()
if len(CurrRec)>0:PriorRecs.append(CurrRec) # put back an interpretation
if len(PriorRecs)>0:
save_redo(PriorRecs,inspec)
print 'Updated interpretations saved in ',inspec
if verbose:
print "Good bye"
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored.
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets magic_measurements format input file, default: magic_measurements.txt
-fsp SPECFILE: sets pmag_specimens format file with prior interpreations, default: zeq_specimens.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-fsa SAMPFILE: sets er_samples format file with orientation information, default: er_samples.txt
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave,e,b=1,0,0 # average replicates, initial end and beginning step
plots,coord=0,'s'
noorient=0
version_num=pmag.get_version()
verbose=pmagplotlib.verbose
beg_pca,end_pca,direction_type="","",'l'
calculation_type,fmt="","svg"
user,spec_keys,locname="",[],''
plot_file=""
sfile=""
plot_file=""
PriorRecs=[] # empty list for prior interpretations
backup=0
specimen="" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
else:
dir_path='.'
inspec=dir_path+'/'+'zeq_specimens.txt'
meas_file,geo,tilt,ask,samp_file=dir_path+'/magic_measurements.txt',0,0,0,dir_path+'/er_samples.txt'
if '-f' in sys.argv:
ind=sys.argv.index('-f')
meas_file=dir_path+'/'+sys.argv[ind+1]
if '-fsp' in sys.argv:
ind=sys.argv.index('-fsp')
inspec=dir_path+'/'+sys.argv[ind+1]
if '-fsa' in sys.argv:
ind=sys.argv.index('-fsa')
samp_file=dir_path+'/'+sys.argv[ind+1]
sfile='ok'
if '-crd' in sys.argv:
ind=sys.argv.index('-crd')
coord=sys.argv[ind+1]
if coord=='g' or coord=='t':
samp_data,file_type=pmag.magic_read(samp_file)
if file_type=='er_samples':sfile='ok'
geo=1
if coord=='t':tilt=1
if '-spc' in sys.argv:
ind=sys.argv.index('-spc')
specimen=sys.argv[ind+1]
if '-dir' in sys.argv:
ind=sys.argv.index('-dir')
direction_type=sys.argv[ind+1]
beg_pca=int(sys.argv[ind+2])
end_pca=int(sys.argv[ind+3])
if direction_type=='L':calculation_type='DE-BFL'
if direction_type=='P':calculation_type='DE-BFP'
if direction_type=='F':calculation_type='DE-FM'
if '-Fp' in sys.argv:
ind=sys.argv.index('-Fp')
plot_file=dir_path+'/'+sys.argv[ind+1]
if '-A' in sys.argv: doave=0
if '-sav' in sys.argv:
plots=1
verbose=0
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
#
first_save=1
meas_data,file_type=pmag.magic_read(meas_file)
changeM,changeS=0,0 # check if data or interpretations have changed
if file_type != 'magic_measurements':
print file_type
print file_type,"This is not a valid magic_measurements file "
sys.exit()
for rec in meas_data:
if "magic_method_codes" not in rec.keys(): rec["magic_method_codes"]=""
methods=""
tmp=rec["magic_method_codes"].replace(" ","").split(":")
for meth in tmp:
methods=methods+meth+":"
rec["magic_method_codes"]=methods[:-1] # get rid of annoying spaces in Anthony's export files
if "magic_instrument_codes" not in rec.keys() :rec["magic_instrument_codes"]=""
PriorSpecs=[]
PriorRecs,file_type=pmag.magic_read(inspec)
if len(PriorRecs)==0:
if verbose:print "starting new file ",inspec
for Rec in PriorRecs:
if 'magic_software_packages' not in Rec.keys():Rec['magic_software_packages']=""
if Rec['er_specimen_name'] not in PriorSpecs:
if 'specimen_comp_name' not in Rec.keys():Rec['specimen_comp_name']="A"
PriorSpecs.append(Rec['er_specimen_name'])
else:
if 'specimen_comp_name' not in Rec.keys():Rec['specimen_comp_name']="A"
if "magic_method_codes" in Rec.keys():
methods=[]
tmp=Rec["magic_method_codes"].replace(" ","").split(":")
for meth in tmp:
methods.append(meth)
if 'DE-FM' in methods:
Rec['calculation_type']='DE-FM' # this won't be imported but helps
if 'DE-BFL' in methods:
Rec['calculation_type']='DE-BFL'
if 'DE-BFL-A' in methods:
Rec['calculation_type']='DE-BFL-A'
if 'DE-BFL-O' in methods:
Rec['calculation_type']='DE-BFL-O'
if 'DE-BFP' in methods:
Rec['calculation_type']='DE-BFP'
else:
Rec['calculation_type']='DE-BFL' # default is to assume a best-fit line
#
# get list of unique specimen names
#
sids=pmag.get_specs(meas_data)
#
# set up plots, angle sets X axis to horizontal, direction_type 'l' is best-fit line
# direction_type='p' is great circle
#
#
# draw plots for sample s - default is just to step through zijderveld diagrams
#
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
ZED={}
ZED['eqarea'],ZED['zijd'], ZED['demag']=1,2,3
pmagplotlib.plot_init(ZED['eqarea'],5,5)
pmagplotlib.plot_init(ZED['zijd'],6,5)
pmagplotlib.plot_init(ZED['demag'],5,5)
save_pca=0
if specimen=="":
k = 0
else:
k=sids.index(specimen)
angle,direction_type="",""
setangle=0
CurrRecs=[]
while k < len(sids):
CurrRecs=[]
if setangle==0:angle=""
method_codes,inst_code=[],""
s=sids[k]
PmagSpecRec={}
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec['magic_software_packages']=version_num
PmagSpecRec['specimen_description']=""
PmagSpecRec['magic_method_codes']=""
if verbose and s!="":print s, k , 'out of ',len(sids)
#
# collect info for the PmagSpecRec dictionary
#
s_meas=pmag.get_dictitem(meas_data,'er_specimen_name',s,'T') # fish out this specimen
s_meas=pmag.get_dictitem(s_meas,'magic_method_codes','Z','has') # fish out zero field steps
if len(s_meas)>0:
for rec in s_meas: # fix up a few things for the output record
PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"] # copy over instruments
PmagSpecRec["er_citation_names"]="This study"
PmagSpecRec["er_specimen_name"]=s
PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
PmagSpecRec["er_site_name"]=rec["er_site_name"]
PmagSpecRec["er_location_name"]=rec["er_location_name"]
locname=rec['er_location_name']
if 'er_expedition_name' in rec.keys(): PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
PmagSpecRec["magic_method_codes"]=rec["magic_method_codes"]
if "magic_experiment_name" not in rec.keys():
PmagSpecRec["magic_experiment_names"]=""
else:
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
break
#
# find the data from the meas_data file for this specimen
#
data,units=pmag.find_dmag_rec(s,meas_data)
PmagSpecRec["measurement_step_unit"]= units
u=units.split(":")
if "T" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-AF"
if "K" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-T"
if "J" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-M"
#
# find prior interpretation
#
if len(CurrRecs)==0: # check if already in
beg_pca,end_pca="",""
calculation_type=""
if inspec !="":
if verbose: print " looking up previous interpretations..."
precs=pmag.get_dictitem(PriorRecs,'er_specimen_name',s,'T') # get all the prior recs with this specimen name
precs=pmag.get_dictitem(precs,'magic_method_codes','LP-DIR','has') # get the directional data
PriorRecs=pmag.get_dictitem(PriorRecs,'er_specimen_name',s,'F') # take them all out of prior recs
# get the ones that meet the current coordinate system
for prec in precs:
if 'specimen_tilt_correction' not in prec.keys() or prec['specimen_tilt_correction']=='-1':
crd='s'
elif prec['specimen_tilt_correction']=='0':
crd='g'
elif prec['specimen_tilt_correction']=='100':
crd='t'
else:
crd='?'
CurrRec={}
for key in prec.keys():CurrRec[key]=prec[key]
CurrRecs.append(CurrRec) # put in CurrRecs
method_codes= CurrRec["magic_method_codes"].replace(" ","").split(':')
calculation_type='DE-BFL'
if 'DE-FM' in method_codes: calculation_type='DE-FM'
if 'DE-BFP' in method_codes: calculation_type='DE-BFP'
if 'DE-BFL-A' in method_codes: calculation_type='DE-BFL-A'
if 'specimen_dang' not in CurrRec.keys():
if verbose:print 'Run mk_redo.py and zeq_magic_redo.py to get the specimen_dang values'
CurrRec['specimen_dang']=-1
if calculation_type!='DE-FM' and crd==coord: # not a fisher mean
if verbose:print "Specimen N MAD DANG start end dec inc type component coordinates"
if units=='K':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["specimen_dang"]),float(CurrRec["measurement_step_min"])-273,float(CurrRec["measurement_step_max"])-273,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif units=='T':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["specimen_dang"]),float(CurrRec["measurement_step_min"])*1e3,float(CurrRec["measurement_step_max"])*1e3,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif 'T' in units and 'K' in units:
if float(CurrRec['measurement_step_min'])<1.0 :
min=float(CurrRec['measurement_step_min'])*1e3
else:
min=float(CurrRec['measurement_step_min'])-273
if float(CurrRec['measurement_step_max'])<1.0 :
max=float(CurrRec['measurement_step_max'])*1e3
else:
max=float(CurrRec['measurement_step_max'])-273
if verbose:print '%s %i %7.1f %i %i %7.1f %7.1f %7.1f, %s %s\n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec['specimen_dang']),min,max,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,crd)
elif 'J' in units:
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec['specimen_dang']),float(CurrRec["measurement_step_min"]),float(CurrRec["measurement_step_max"]),float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif calculation_type=='DE-FM' and crd==coord: # fisher mean
if verbose:print "Specimen a95 DANG start end dec inc type component coordinates"
if units=='K':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),float(CurrRec["measurement_step_min"])-273,float(CurrRec["measurement_step_max"])-273,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif units=='T':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),float(CurrRec["measurement_step_min"])*1e3,float(CurrRec["measurement_step_max"])*1e3,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif 'T' in units and 'K' in units:
if float(CurrRec['measurement_step_min'])<1.0 :
min=float(CurrRec['measurement_step_min'])*1e3
else:
min=float(CurrRec['measurement_step_min'])-273
if float(CurrRec['measurement_step_max'])<1.0 :
max=float(CurrRec['measurement_step_max'])*1e3
else:
max=float(CurrRec['measurement_step_max'])-273
if verbose:print '%s %i %7.1f %i %i %7.1f %7.1f %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),min,max,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,crd)
elif 'J' in units:
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["measurement_step_min"]),float(CurrRec["measurement_step_max"]),float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
if len(CurrRecs)==0:beg_pca,end_pca="",""
datablock=data
noskip=1
if len(datablock) <3:
noskip=0
if backup==0:
k+=1
else:
k-=1
if len(CurrRecs)>0:
for rec in CurrRecs:
PriorRecs.append(rec)
CurrRecs=[]
else:
backup=0
if noskip:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
# #
# do geo or stratigraphic correction now
#
if geo==1:
#
# find top priority orientation method
orient,az_type=pmag.get_orient(samp_data,PmagSpecRec["er_sample_name"])
if az_type=='SO-NO':
if verbose: print "no orientation data for ",s
orient["sample_azimuth"]=0
orient["sample_dip"]=0
noorient=1
method_codes.append("SO-NO")
orient["sample_azimuth"]=0
orient["sample_dip"]=0
orient["sample_bed_dip_azimuth"]=0
orient["sample_bed_dip"]=0
noorient=1
method_codes.append("SO-NO")
else:
noorient=0
#
# if stratigraphic selected, get stratigraphic correction
#
tiltblock,geoblock=[],[]
for rec in datablock:
d_geo,i_geo=pmag.dogeo(rec[1],rec[2],float(orient["sample_azimuth"]),float(orient["sample_dip"]))
geoblock.append([rec[0],d_geo,i_geo,rec[3],rec[4],rec[5],rec[6]])
if tilt==1 and "sample_bed_dip" in orient.keys() and float(orient['sample_bed_dip'])!=0:
d_tilt,i_tilt=pmag.dotilt(d_geo,i_geo,float(orient["sample_bed_dip_direction"]),float(orient["sample_bed_dip"]))
tiltblock.append([rec[0],d_tilt,i_tilt,rec[3],rec[4],rec[5],rec[6]])
if tilt==1: plotblock=tiltblock
if geo==1 and tilt==0:plotblock=geoblock
if geo==0 and tilt==0: plotblock=datablock
#
# set the end pca point to last point if not set
if e==0 or e>len(plotblock)-1: e=len(plotblock)-1
if angle=="": angle=plotblock[0][1] # rotate to NRM declination
title=s+'_s'
if geo==1 and tilt==0 and noorient!=1:title=s+'_g'
if tilt==1 and noorient!=1:title=s+'_t'
pmagplotlib.plotZED(ZED,plotblock,angle,title,units)
if verbose:pmagplotlib.drawFIGS(ZED)
if len(CurrRecs)!=0:
for prec in CurrRecs:
if 'calculation_type' not in prec.keys():
calculation_type=''
else:
calculation_type=prec["calculation_type"]
direction_type=prec["specimen_direction_type"]
if calculation_type !="":
beg_pca,end_pca="",""
for j in range(len(datablock)):
if data[j][0]==float(prec["measurement_step_min"]):beg_pca=j
if data[j][0]==float(prec["measurement_step_max"]):end_pca=j
if beg_pca=="" or end_pca=="":
if verbose:
print "something wrong with prior interpretation "
break
if calculation_type!="":
if beg_pca=="":beg_pca=0
if end_pca=="":end_pca=len(plotblock)-1
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,geoblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,tiltblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,plotblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
#
# print out data for this sample to screen
#
recnum=0
for plotrec in plotblock:
if units=='T' and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if units=="K" and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if units=="J" and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0],' J',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if 'K' in units and 'T' in units:
if plotrec[0]>=1. and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if plotrec[0]<1. and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2],plotrec[6])
recnum += 1
if specimen!="":
if plot_file=="":
basename=locname+'_'+s
else:
basename=plot_file
files={}
for key in ZED.keys():
files[key]=basename+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
sys.exit()
else: # interactive
if plots==0:
ans='b'
k+=1
changeS=0
while ans != "":
if len(CurrRecs)==0:
print """
g/b: indicates good/bad measurement. "bad" measurements excluded from calculation
set s[a]ve plot, [b]ounds for pca and calculate, [p]revious, [s]pecimen,
change [h]orizontal projection angle, change [c]oordinate systems,
[e]dit data, [q]uit:
"""
else:
print """
g/b: indicates good/bad measurement. "bad" measurements excluded from calculation
set s[a]ve plot, [b]ounds for pca and calculate, [p]revious, [s]pecimen,
change [h]orizontal projection angle, change [c]oordinate systems,
[d]elete current interpretation(s), [e]dit data, [q]uit:
"""
ans=raw_input('<Return> for next specimen \n')
setangle=0
if ans=='d': # delete this interpretation
CurrRecs=[]
k-=1 # replot same specimen
ans=""
changeS=1
if ans=='q':
if changeM==1:
ans=raw_input('Save changes to magic_measurements.txt? y/[n] ')
if ans=='y':
pmag.magic_write(meas_file,meas_data,'magic_measurements')
print "Good bye"
sys.exit()
if ans=='a':
if plot_file=="":
basename=locname+'_'+s+'_'
else:
basename=plot_file
files={}
for key in ZED.keys():
files[key]=basename+'_'+coord+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
ans=""
if ans=='p':
k-=2
ans=""
backup=1
if ans=='c':
k-=1 # replot same block
if tilt==0 and geo ==1:print "You are currently viewing geographic coordinates "
if tilt==1 and geo ==1:print "You are currently viewing stratigraphic coordinates "
if tilt==0 and geo ==0: print "You are currently viewing sample coordinates "
print "\n Which coordinate system do you wish to view? "
coord=raw_input(" <Return> specimen, [g] geographic, [t] tilt corrected ")
if coord=="g":geo,tilt=1,0
if coord=="t":
geo=1
tilt=1
if coord=="":
coord='s'
geo=0
tilt=0
if geo==1 and sfile=="":
samp_file=raw_input(" Input er_samples file for sample orientations [er_samples.txt] " )
if samp_file=="":samp_file="er_samples.txt"
samp_data,file_type=pmag.magic_read(samp_file)
if file_type != 'er_samples':
print file_type
print "This is not a valid er_samples file - coordinate system not changed"
else:
sfile="ok"
ans=""
if ans=='s':
keepon=1
sample=raw_input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
k =sids.index(sample)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if sample in sids[qq]:tmplist.append(sids[qq])
print sample," not found, but this was: "
print tmplist
sample=raw_input('Select one or try again\n ')
angle,direction_type="",""
setangle=0
ans=""
if ans=='h':
k-=1
angle=raw_input("Enter desired declination for X axis 0-360 ")
angle=float(angle)
if angle==0:angle=0.001
s=sids[k]
setangle=1
ans=""
if ans=='e':
k-=1
ans=""
recnum=0
for plotrec in plotblock:
if plotrec[0]<=200 and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f ' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2])
if plotrec[0]>200 and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f ' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2])
recnum += 1
answer=raw_input('Enter index of point to change from bad to good or vice versa: ')
try:
ind=int(answer)
meas_data=pmag.mark_dmag_rec(s,ind,meas_data)
changeM=1
except:
'bad entry, try again'
if ans=='b':
if end_pca=="":end_pca=len(plotblock)-1
if beg_pca=="":beg_pca=0
k-=1 # stay on same sample until through
GoOn=0
while GoOn==0:
print 'Enter index of first point for pca: ','[',beg_pca,']'
answer=raw_input('return to keep default ')
if answer != "":
beg_pca=int(answer)
print 'Enter index of last point for pca: ','[',end_pca,']'
answer=raw_input('return to keep default ')
try:
end_pca=int(answer)
if plotblock[beg_pca][5]=='b' or plotblock[end_pca][5]=='b':
print "Can't select 'bad' measurement for PCA bounds -try again"
end_pca=len(plotblock)-1
beg_pca=0
elif beg_pca >=0 and beg_pca<=len(plotblock)-2 and end_pca>0 and end_pca<len(plotblock):
GoOn=1
else:
print beg_pca,end_pca, " are bad entry of indices - try again"
end_pca=len(plotblock)-1
beg_pca=0
except:
print beg_pca,end_pca, " are bad entry of indices - try again"
end_pca=len(plotblock)-1
beg_pca=0
GoOn=0
while GoOn==0:
if calculation_type!="":
print "Prior calculation type = ",calculation_type
ct=raw_input('Enter new Calculation Type: best-fit line, plane or fisher mean [l]/p/f : ' )
if ct=="" or ct=="l":
direction_type="l"
calculation_type="DE-BFL"
GoOn=1
elif ct=='p':
direction_type="p"
calculation_type="DE-BFP"
GoOn=1
elif ct=='f':
direction_type="l"
calculation_type="DE-FM"
GoOn=1
else:
print "bad entry of calculation type: try again. "
pmagplotlib.plotZED(ZED,plotblock,angle,s,units)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
if "SO-NO" not in method_codes:
PmagSpecRec["specimen_tilt_correction"]='0'
method_codes.append("DA-DIR-GEO")
else:
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,geoblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
if "SO-NO" not in method_codes:
PmagSpecRec["specimen_tilt_correction"]='100'
method_codes.append("DA-DIR-TILT")
else:
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,tiltblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,plotblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
PmagSpecRec["measurement_step_min"]='%8.3e ' %(mpars["measurement_step_min"])
PmagSpecRec["measurement_step_max"]='%8.3e ' %(mpars["measurement_step_max"])
PmagSpecRec["specimen_correction"]='u'
PmagSpecRec["specimen_dang"]='%7.1f ' %(mpars['specimen_dang'])
print 'DANG: ',PmagSpecRec["specimen_dang"]
if calculation_type!='DE-FM':
PmagSpecRec["specimen_mad"]='%7.1f ' %(mpars["specimen_mad"])
PmagSpecRec["specimen_alpha95"]=""
else:
PmagSpecRec["specimen_alpha95"]='%7.1f ' %(mpars["specimen_alpha95"])
PmagSpecRec["specimen_mad"]=""
PmagSpecRec["specimen_n"]='%i ' %(mpars["specimen_n"])
PmagSpecRec["specimen_direction_type"]=direction_type
PmagSpecRec["calculation_type"]=calculation_type # redundant and won't be imported - just for convenience
method_codes=PmagSpecRec["magic_method_codes"].split(':')
if len(method_codes) != 0:
methstring=""
for meth in method_codes:
ctype=meth.split('-')
if 'DE' not in ctype:methstring=methstring+ ":" +meth # don't include old direction estimation methods
methstring=methstring+':'+calculation_type
PmagSpecRec["magic_method_codes"]= methstring.strip(':')
print 'Method codes: ',PmagSpecRec['magic_method_codes']
if calculation_type!='DE-FM':
if units=='K':
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])-273,float(PmagSpecRec["measurement_step_max"])-273,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif units== 'T':
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])*1e3,float(PmagSpecRec["measurement_step_max"])*1e3,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units and 'K' in units:
if float(PmagSpecRec['measurement_step_min'])<1.0 :
min=float(PmagSpecRec['measurement_step_min'])*1e3
else:
min=float(PmagSpecRec['measurement_step_min'])-273
if float(PmagSpecRec['measurement_step_max'])<1.0 :
max=float(PmagSpecRec['measurement_step_max'])*1e3
else:
max=float(PmagSpecRec['measurement_step_max'])-273
print '%s %i %7.1f %i %i %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),min,max,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"]),float(PmagSpecRec["measurement_step_max"]),float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
if 'K' in units:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])-273,float(PmagSpecRec["measurement_step_max"])-273,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])*1e3,float(PmagSpecRec["measurement_step_max"])*1e3,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units and 'K' in units:
if float(PmagSpecRec['measurement_step_min'])<1.0 :
min=float(PmagSpecRec['measurement_step_min'])*1e3
else:
min=float(PmagSpecRec['measurement_step_min'])-273
if float(PmagSpecRec['measurement_step_max'])<1.0 :
max=float(PmagSpecRec['measurement_step_max'])*1e3
else:
max=float(PmagSpecRec['measurement_step_max'])-273
print '%s %i %7.1f %i %i %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),min,max,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["measurement_step_min"]),float(PmagSpecRec["measurement_step_max"]),float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
saveit=raw_input("Save this interpretation? [y]/n \n")
if saveit!="n":
changeS=1
#
# put in details
#
angle,direction_type,setangle="","",0
if len(CurrRecs)>0:
replace=raw_input(" [0] add new component, or [1] replace existing interpretation(s) [default is replace] ")
if replace=="1" or replace=="":
CurrRecs=[]
PmagSpecRec['specimen_comp_name']='A'
CurrRecs.append(PmagSpecRec)
else:
print 'These are the current component names for this specimen: '
for trec in CurrRecs:print trec['specimen_comp_name']
compnum=raw_input("Enter new component name: ")
PmagSpecRec['specimen_comp_name']=compnum
print "Adding new component: ",PmagSpecRec['specimen_comp_name']
CurrRecs.append(PmagSpecRec)
else:
PmagSpecRec['specimen_comp_name']='A'
CurrRecs.append(PmagSpecRec)
k+=1
ans=""
else:
ans=""
else: # plots=1
k+=1
files={}
locname.replace('/','-')
print PmagSpecRec
for key in ZED.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_'+coord+'_TY:_'+key+'_.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['demag']='DeMag Plot'
titles['zijd']='Zijderveld Plot'
titles['eqarea']='Equal Area Plot'
ZED = pmagplotlib.addBorders(ZED,titles,black,purple)
pmagplotlib.saveP(ZED,files)
if len(CurrRecs)>0:
for rec in CurrRecs: PriorRecs.append(rec)
if changeS==1:
if len(PriorRecs)>0:
save_redo(PriorRecs,inspec)
else:
os.system('rm '+inspec)
CurrRecs,beg_pca,end_pca=[],"","" # next up
changeS=0
else: k+=1 # skip record - not enough data
if changeM==1:
pmag.magic_write(meas_file,meas_data,'magic_measurements')
def main():
"""
NAME
zeq_magic_redo.py
DESCRIPTION
Calculate principal components through demagnetization data using bounds and calculation type stored in "redo" file
SYNTAX
zeq_magic_redo.py [command line options]
OPTIONS
-h prints help message
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-F: specify output file, default is zeq_specimens.txt
-fre REDO: specify redo file, default is "zeq_redo"
-fsa SAMPFILE: specify er_samples format file, default is "er_samples.txt"
-A : don't average replicate measurements, default is yes
-crd [s,g,t] :
specify coordinate system [s,g,t] [default is specimen coordinates]
are specimen, geographic, and tilt corrected respectively
NB: you must have a SAMPFILE in this directory to rotate from specimen coordinates
-leg: attaches "Recalculated from original measurements; supercedes published results. " to comment field
INPUTS
zeq_redo format file is:
specimen_name calculation_type[DE-BFL,DE-BFL-A,DE-BFL-O,DE-BFP,DE-FM] step_min step_max component_name[A,B,C]
"""
dir_path='.'
INCL=["LT-NO","LT-AF-Z","LT-T-Z","LT-M-Z"] # looking for demag data
beg,end,pole,geo,tilt,askave,save=0,0,[],0,0,0,0
user,doave,comment= "",1,""
geo,tilt=0,0
version_num=pmag.get_version()
args=sys.argv
if '-WD' in args:
ind=args.index('-WD')
dir_path=args[ind+1]
meas_file,pmag_file,mk_file= dir_path+"/"+"magic_measurements.txt",dir_path+"/"+"zeq_specimens.txt",dir_path+"/"+"zeq_redo"
samp_file,coord=dir_path+"/"+"er_samples.txt",""
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind=args.index("-usr")
user=sys.argv[ind+1]
if "-A" in args:doave=0
if "-leg" in args: comment="Recalculated from original measurements; supercedes published results. "
if "-f" in args:
ind=args.index("-f")
meas_file=dir_path+'/'+sys.argv[ind+1]
if "-F" in args:
ind=args.index("-F")
pmag_file=dir_path+'/'+sys.argv[ind+1]
if "-fre" in args:
ind=args.index("-fre")
mk_file=dir_path+"/"+args[ind+1]
try:
mk_f=open(mk_file,'r')
except:
print("Bad redo file")
sys.exit()
mkspec,skipped=[],[]
speclist=[]
for line in mk_f.readlines():
tmp=line.split()
mkspec.append(tmp)
speclist.append(tmp[0])
if "-fsa" in args:
ind=args.index("-fsa")
samp_file=dir_path+'/'+sys.argv[ind+1]
if "-crd" in args:
ind=args.index("-crd")
coord=sys.argv[ind+1]
if coord=="g":geo,tilt=1,0
if coord=="t":geo,tilt=1,1
#
# now get down to bidness
if geo==1:
samp_data,file_type=pmag.magic_read(samp_file)
if file_type != 'er_samples':
print(file_type)
print("This is not a valid er_samples file ")
sys.exit()
#
#
#
meas_data,file_type=pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(file_type)
print(file_type,"This is not a valid magic_measurements file ")
sys.exit()
#
# sort the specimen names
#
k = 0
print('Processing ',len(speclist), ' specimens - please wait')
PmagSpecs=[]
while k < len(speclist):
s=speclist[k]
recnum=0
PmagSpecRec={}
method_codes,inst_codes=[],[]
# find the data from the meas_data file for this sample
#
# collect info for the PmagSpecRec dictionary
#
meas_meth=[]
spec=pmag.get_dictitem(meas_data,'er_specimen_name',s,'T')
if len(spec)==0:
print('no data found for specimen: ',s)
print('delete from zeq_redo input file...., then try again')
else:
for rec in spec: # copy of vital stats to PmagSpecRec from first spec record in demag block
skip=1
methods=rec["magic_method_codes"].split(":")
if len(set(methods) & set(INCL))>0:
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec["magic_software_packages"]=version_num
PmagSpecRec["er_specimen_name"]=s
PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
PmagSpecRec["er_site_name"]=rec["er_site_name"]
PmagSpecRec["er_location_name"]=rec["er_location_name"]
if "er_expedition_name" in list(rec.keys()):PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
PmagSpecRec["er_citation_names"]="This study"
if "magic_experiment_name" not in list(rec.keys()): rec["magic_experiment_name"]=""
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
if "magic_instrument_codes" not in list(rec.keys()): rec["magic_instrument_codes"]=""
inst=rec['magic_instrument_codes'].split(":")
for I in inst:
if I not in inst_codes: # copy over instruments
inst_codes.append(I)
meths=rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in meas_meth:meas_meth.append(meth)
if "LP-DIR-AF" in meas_meth or "LT-AF-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"]="T"
if "LP-DIR-AF" not in method_codes:method_codes.append("LP-DIR-AF")
if "LP-DIR-T" in meas_meth or "LT-T-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"]="K"
if "LP-DIR-T" not in method_codes:method_codes.append("LP-DIR-T")
if "LP-DIR-M" in meas_meth or "LT-M-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"]="J"
if "LP-DIR-M" not in method_codes:method_codes.append("LP-DIR-M")
#
#
datablock,units=pmag.find_dmag_rec(s,spec) # fish out the demag data for this specimen
#
if len(datablock) <2 or s not in speclist :
k+=1
# print 'skipping ', s,len(datablock)
else:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
#
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
#
# do geo or stratigraphic correction now
#
if geo==1 or tilt==1:
# find top priority orientation method
orient,az_type=pmag.get_orient(samp_data,PmagSpecRec["er_sample_name"])
if az_type not in method_codes:method_codes.append(az_type)
#
# if tilt selected, get stratigraphic correction
#
tiltblock,geoblock=[],[]
for rec in datablock:
if "sample_azimuth" in list(orient.keys()) and orient["sample_azimuth"]!="":
d_geo,i_geo=pmag.dogeo(rec[1],rec[2],float(orient["sample_azimuth"]),float(orient["sample_dip"]))
geoblock.append([rec[0],d_geo,i_geo,rec[3],rec[4],rec[5]])
if tilt==1 and "sample_bed_dip_direction" in list(orient.keys()):
d_tilt,i_tilt=pmag.dotilt(d_geo,i_geo,float(orient["sample_bed_dip_direction"]),float(orient["sample_bed_dip"]))
tiltblock.append([rec[0],d_tilt,i_tilt,rec[3],rec[4],rec[5]])
elif tilt==1:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no tilt correction for ', PmagSpecRec["er_sample_name"],' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
else:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no geographic correction for ', PmagSpecRec["er_sample_name"],' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
#
# get beg_pca, end_pca, pca
if PmagSpecRec['er_sample_name'] not in skipped:
compnum=-1
for spec in mkspec:
if spec[0]==s:
CompRec={}
for key in list(PmagSpecRec.keys()):CompRec[key]=PmagSpecRec[key]
compnum+=1
calculation_type=spec[1]
beg=float(spec[2])
end=float(spec[3])
if len(spec)>4:
comp_name=spec[4]
else:
comp_name=string.uppercase[compnum]
CompRec['specimen_comp_name']=comp_name
if beg < float(datablock[0][0]):beg=float(datablock[0][0])
if end > float(datablock[-1][0]):end=float(datablock[-1][0])
for l in range(len(datablock)):
if datablock[l][0]==beg:beg_pca=l
if datablock[l][0]==end:end_pca=l
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
CompRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
CompRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
CompRec["specimen_tilt_correction"]='0'
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
CompRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
CompRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
CompRec["specimen_tilt_correction"]='100'
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
CompRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
CompRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
CompRec["specimen_tilt_correction"]='-1'
if mpars["specimen_direction_type"]=="Error":
pass
else:
CompRec["measurement_step_min"]='%8.3e '%(datablock[beg_pca][0])
try:
CompRec["measurement_step_max"]='%8.3e '%(datablock[end_pca][0] )
except:
print('error in end_pca ',PmagSpecRec['er_specimen_name'])
CompRec["specimen_correction"]='u'
if calculation_type!='DE-FM':
CompRec["specimen_mad"]='%7.1f '%(mpars["specimen_mad"])
CompRec["specimen_alpha95"]=""
else:
CompRec["specimen_mad"]=""
CompRec["specimen_alpha95"]='%7.1f '%(mpars["specimen_alpha95"])
CompRec["specimen_n"]='%i '%(mpars["specimen_n"])
CompRec["specimen_dang"]='%7.1f '%(mpars["specimen_dang"])
CompMeths=[]
for meth in method_codes:
if meth not in CompMeths:CompMeths.append(meth)
if calculation_type not in CompMeths:CompMeths.append(calculation_type)
if geo==1: CompMeths.append("DA-DIR-GEO")
if tilt==1: CompMeths.append("DA-DIR-TILT")
if "DE-BFP" not in calculation_type:
CompRec["specimen_direction_type"]='l'
else:
CompRec["specimen_direction_type"]='p'
CompRec["magic_method_codes"]=""
if len(CompMeths) != 0:
methstring=""
for meth in CompMeths:
methstring=methstring+ ":" +meth
CompRec["magic_method_codes"]=methstring.strip(':')
CompRec["specimen_description"]=comment
if len(inst_codes) != 0:
inststring=""
for inst in inst_codes:
inststring=inststring+ ":" +inst
CompRec["magic_instrument_codes"]=inststring.strip(':')
PmagSpecs.append(CompRec)
k+=1
pmag.magic_write(pmag_file,PmagSpecs,'pmag_specimens')
print("Recalculated specimen data stored in ",pmag_file)
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
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
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'
-fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
-fcr CRIT, set criteria file for grading. # not yet implemented
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out 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
-b BEG END: sets bounds for calculation
BEG: starting step number for slope calculation
END: ending step number for slope calculation
-z use only z component difference for pTRM calculation
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
"""
#
# initializations
#
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
#
# default acceptance criteria
#
accept = pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
plots, fmt, Zdiff = 0, 'svg', 0
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")
crit_file = pmag.get_named_arg_from_sys("-fcr", default_val="criteria.txt")
spec_file = os.path.join(dir_path, spec_file)
meas_file = os.path.join(dir_path, meas_file)
crit_file = os.path.join(dir_path, crit_file)
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
if '-sav' in sys.argv: plots, verbose = 1, 0
if '-z' in sys.argv: Zdiff = 1
specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
if '-b' in sys.argv:
ind = sys.argv.index('-b')
start = int(sys.argv[ind + 1])
end = int(sys.argv[ind + 2])
else:
start, end = "", ""
fnames = {
'measurements': meas_file,
'specimens': spec_file,
'criteria': crit_file
}
contribution = nb.Contribution(
dir_path,
custom_filenames=fnames,
read_tables=['measurements', 'specimens', 'criteria'])
#
# import prior interpretations from specimen file
#
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:
spec_container = contribution.tables['specimens']
prior_spec_data = spec_container.get_records_for_code(
'LP-PI-TRM',
strict_match=False) # look up all prior intensity interpretations
else:
spec_container, prior_spec_data = None, []
backup = 0
#
Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
#
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data['method_codes'] = meas_data['method_codes'].str.replace(
" ", "") # get rid of nasty spaces
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LP-PI-TRM|LP-TRM|LP-TRM-TD') ==
True] # fish out zero field steps for plotting
intensity_types = [
col_name for col_name in meas_data.columns if col_name in Mkeys
]
int_key = intensity_types[
0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
meas_data = meas_data[meas_data[int_key].notnull(
)] # get all the non-null intensity records of the same type
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
meas_data = meas_data[meas_data['flag'].str.contains('g') ==
True] # only the 'good' measurements
thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')
== True] # get all the Thellier data
trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM') ==
True] # get all the TRM acquisition data
td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD') ==
True] # get all the TD data
anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN') ==
True] # get all the anisotropy data
#
# get list of unique specimen names from measurement data
#
specimen_names = meas_data.specimen.unique(
) # this is a Series of all the specimen names
specimen_names = specimen_names.tolist() # turns it into a list
specimen_names.sort() # sorts by specimen name
#
# set up new DataFrame for this sessions specimen interpretations
#
spec_container = nb.MagicDataFrame(dtype='specimens',
columns=specimen_cols)
current_spec_data = spec_container.df # this is for interpretations from this session
if specimen == "": # do all specimens
k = 0
else:
k = specimen_names.index(specimen) # just do this one
# define figure numbers for arai, zijderveld and
# de-,re-magnetization diagrams
AZD = {}
AZD['deremag'], AZD['zijd'], AZD['arai'], AZD['eqarea'] = 1, 2, 3, 4
pmagplotlib.plot_init(AZD['arai'], 5, 5)
pmagplotlib.plot_init(AZD['zijd'], 5, 5)
pmagplotlib.plot_init(AZD['deremag'], 5, 5)
pmagplotlib.plot_init(AZD['eqarea'], 5, 5)
if len(trm_data) > 0:
AZD['TRM'] = 5
pmagplotlib.plot_init(AZD['TRM'], 5, 5)
if len(td_data) > 0:
AZD['TDS'] = 6
pmagplotlib.plot_init(AZD['TDS'], 5, 5)
#
while k < len(specimen_names):
this_specimen = specimen_names[
k] # set the current specimen for plotting
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
#
# set up datablocks
#
thelblock = thel_data[thel_data['specimen'].str.contains(this_specimen)
== True] # fish out this specimen
trmblock = trm_data[trm_data['specimen'].str.contains(this_specimen) ==
True] # fish out this specimen
tdsrecs = td_data[td_data['specimen'].str.contains(this_specimen) ==
True] # fish out this specimen
anisblock = anis_data[anis_data['specimen'].str.contains(this_specimen)
== True] # fish out the anisotropy data
prior_specimen_interpretations = prior_spec_data[
prior_spec_data['specimen'].str.contains(
this_specimen) == True] # fish out prior interpretation
#
# sort data into types
#
araiblock, field = pmag.sortarai(thelblock,
this_specimen,
Zdiff,
version=3)
first_Z = araiblock[0]
GammaChecks = araiblock[5]
if len(first_Z) < 3:
if backup == 0:
k += 1
if verbose:
print('skipping specimen - moving forward ', this_specimen)
else:
k -= 1
if verbose:
print('skipping specimen - moving backward ',
this_specimen)
else:
backup = 0
zijdblock, units = pmag.find_dmag_rec(this_specimen,
thelblock,
version=3)
if start == "" and len(prior_specimen_interpretations) > 0:
if verbose: print('Looking up saved interpretation....')
#
# get prior interpretation steps
#
beg_int = pd.to_numeric(prior_specimen_interpretations.
meas_step_min.values).tolist()[0]
end_int = pd.to_numeric(prior_specimen_interpretations.
meas_step_max.values).tolist()[0]
else:
beg_int, end_int = "", ""
recnum = 0
if verbose: print("index step Dec Inc Int Gamma")
for plotrec in zijdblock:
if plotrec[0] == beg_int:
start = recnum # while we are at it, collect these bounds
if plotrec[0] == end_int: end = recnum
if verbose:
if GammaChecks != "":
gamma = ""
for g in GammaChecks:
if g[0] == plotrec[0] - 273:
gamma = g[1]
break
if gamma != "":
print('%i %i %7.1f %7.1f %8.3e %7.1f' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3], gamma))
else:
print('%i %i %7.1f %7.1f %8.3e ' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3]))
recnum += 1
for fig in list(AZD.keys()):
pmagplotlib.clearFIG(AZD[fig]) # clear all figures
pmagplotlib.plotAZ(AZD, araiblock, zijdblock, this_specimen,
units[0])
if verbose: pmagplotlib.drawFIGS(AZD)
pars, errcode = pmag.PintPars(thelblock,
araiblock,
zijdblock,
start,
end,
accept,
version=3)
pars['measurement_step_unit'] = "K"
pars['experiment_type'] = 'LP-PI-TRM'
#
# work on saving interpretations stuff later
#
if errcode != 1: # no problem in PintPars
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars["specimen_b"]
pars["er_specimen_name"] = this_specimen
#pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose) # deal with this later
pars["specimen_grade"] = 'None'
pars['measurement_step_min'] = pars['meas_step_min']
pars['measurement_step_max'] = pars['meas_step_max']
if pars['measurement_step_unit'] == 'K':
outstr = "specimen Tmin Tmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma Gamma_max \n"
pars_out = (this_specimen, (pars["meas_step_min"] - 273),
(pars["meas_step_max"] -
273), (pars["specimen_int_n"]),
1e6 * (pars["specimen_lab_field_dc"]),
1e6 * (pars["specimen_int"]),
pars["specimen_b"], pars["specimen_q"],
pars["specimen_f"], pars["specimen_fvds"],
pars["specimen_b_beta"], pars["int_mad_free"],
pars["int_dang"], pars["int_drats"],
pars["int_n_ptrm"], pars["specimen_grade"],
np.sqrt(pars["specimen_rsc"]),
int(pars["int_md"]), pars["specimen_b_sigma"],
pars['specimen_gamma'])
outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out + '\n'
elif pars['measurement_step_unit'] == 'J':
outstr = "specimen Wmin Wmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma ThetaMax DeltaMax GammaMax\n"
pars_out = (
this_specimen, (pars["meas_step_min"]),
(pars["meas_step_max"]), (pars["specimen_int_n"]),
1e6 * (pars["specimen_lab_field_dc"]),
1e6 * (pars["specimen_int"]), pars["specimen_b"],
pars["specimen_q"], pars["specimen_f"],
pars["specimen_fvds"], pars["specimen_b_beta"],
pars["specimen_int_mad"], pars["specimen_int_dang"],
pars["specimen_drats"], pars["specimen_int_ptrm_n"],
pars["specimen_grade"], np.sqrt(pars["specimen_rsc"]),
int(pars["specimen_md"]), pars["specimen_b_sigma"],
pars["specimen_theta"], pars["specimen_delta"],
pars["specimen_gamma"])
outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out + '\n'
print(outstr)
print(outstring)
pmagplotlib.plotB(AZD, araiblock, zijdblock, pars)
mpars = pmag.domean(araiblock[1], start, end, 'DE-BFL')
if verbose:
pmagplotlib.drawFIGS(AZD)
print('pTRM direction= ',
'%7.1f' % (mpars['specimen_dec']),
' %7.1f' % (mpars['specimen_inc']), ' MAD:',
'%7.1f' % (mpars['specimen_mad']))
if len(anisblock) > 0: # this specimen has anisotropy data
if verbose:
print('Found anisotropy record... but ignoring for now ')
if plots == 1:
if fmt != "pmag":
files = {}
for key in list(AZD.keys()):
files[
key] = 'SP:_' + this_specimen + '_TY:_' + key + '_' + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['deremag'] = 'DeReMag Plot'
titles['zijd'] = 'Zijderveld Plot'
titles['arai'] = 'Arai Plot'
titles['TRM'] = 'TRM Acquisition data'
AZD = pmagplotlib.addBorders(AZD, titles, black,
purple)
pmagplotlib.saveP(AZD, files)
else: # save in pmag format
print('pmag format no longer supported')
#script="grep "+this_specimen+" output.mag | thellier -mfsi"
#script=script+' %8.4e'%(field)
#min='%i'%((pars["measurement_step_min"]-273))
#Max='%i'%((pars["measurement_step_max"]-273))
#script=script+" "+min+" "+Max
#script=script+" |plotxy;cat mypost >>thellier.ps\n"
#pltf.write(script)
#pmag.domagicmag(outf,MeasRecs)
if specimen != "": sys.exit() # syonara
if verbose:
ans = input('Return for next specimen, q to quit: ')
if ans == 'q': sys.exit()
k += 1 # moving on
def main():
"""
NAME
zeq.py
DESCRIPTION
plots demagnetization data. The equal area projection has the X direction (usually North in geographic coordinates)
to the top. The red line is the X axis of the Zijderveld diagram. Solid symbols are lower hemisphere.
The solid (open) symbols in the Zijderveld diagram are X,Y (X,Z) pairs. The demagnetization diagram plots the
fractional remanence remaining after each step. The green line is the fraction of the total remaence removed
between each step.
INPUT FORMAT
takes specimen_name treatment intensity declination inclination in space
delimited file
SYNTAX
zeq.py [command line options
OPTIONS
-f FILE for reading from command line
-u [mT,C] specify units of mT OR C, default is unscaled
"""
if '-h' in sys.argv: # check if help is needed
print main.__doc__
sys.exit() # graceful quit
else:
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
else:
print main.__doc__
sys.exit()
if '-u' in sys.argv:
ind=sys.argv.index('-u')
units=sys.argv[ind+1]
if units=="C":SIunits="K"
if units=="mT":SIunits="T"
else:
units="U"
SIunits="U"
f=open(file,'rU')
data=f.readlines()
#
datablock= [] # set up list for data
fmt='svg' # default image format
s="" # initialize specimen name
angle=0.
for line in data: # read in the data from standard input
rec=line.split() # split each line on space to get records
if angle=="":angle=float(rec[3])
if s=="":s=rec[0]
if units=='mT':datablock.append([float(rec[1])*1e-3,float(rec[3]),float(rec[4]),1e-3*float(rec[2]),'','g']) # treatment, dec, inc, int # convert to T and Am^2 (assume emu)
if units=='C':datablock.append([float(rec[1])+273.,float(rec[3]),float(rec[4]),1e-3*float(rec[2]),'','g']) # treatment, dec, inc, int, convert to K and Am^2, assume emu
if units=='U':datablock.append([float(rec[1]),float(rec[3]),float(rec[4]),float(rec[2]),'','g']) # treatment, dec, inc, int, using unscaled units
# define figure numbers in a dictionary for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
ZED={}
ZED['eqarea'],ZED['zijd'], ZED['demag']=1,2,3
pmagplotlib.plot_init(ZED['eqarea'],5,5) # initialize plots
pmagplotlib.plot_init(ZED['zijd'],5,5)
pmagplotlib.plot_init(ZED['demag'],5,5)
#
#
pmagplotlib.plotZED(ZED,datablock,angle,s,SIunits) # plot the data
pmagplotlib.drawFIGS(ZED)
while 1:
#
# print out data for this sample to screen
#
recnum=0
for plotrec in datablock:
if units=='mT':print '%i %7.1f %8.3e %7.1f %7.1f ' % (recnum,plotrec[0]*1e3,plotrec[3],plotrec[1],plotrec[2])
if units=='C':print '%i %7.1f %8.3e %7.1f %7.1f ' % (recnum,plotrec[0]-273.,plotrec[3],plotrec[1],plotrec[2])
if units=='U':print '%i %7.1f %8.3e %7.1f %7.1f ' % (recnum,plotrec[0],plotrec[3],plotrec[1],plotrec[2])
recnum += 1
end_pca=len(datablock)-1 # initialize end_pca, beg_pca to first and last measurement
beg_pca=0
ans=raw_input(" s[a]ve plot, [b]ounds for pca and calculate, change [h]orizontal projection angle, [q]uit: ")
if ans =='q':
sys.exit()
if ans=='a':
files={}
for key in ZED.keys():
files[key]=s+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
if ans=='h':
angle=float(raw_input(" Declination to project onto horizontal axis? "))
pmagplotlib.plotZED(ZED,datablock,angle,s,SIunits) # plot the data
if ans=='b':
GoOn=0
while GoOn==0: # keep going until reasonable bounds are set
print 'Enter index of first point for pca: ','[',beg_pca,']'
answer=raw_input('return to keep default ')
if answer != "":beg_pca=int(answer)
print 'Enter index of last point for pca: ','[',end_pca,']'
answer=raw_input('return to keep default ')
if answer != "":
end_pca=int(answer)
if beg_pca >=0 and beg_pca<=len(datablock)-2 and end_pca>0 and end_pca<len(datablock):
GoOn=1
else:
print "Bad entry of indices - try again"
end_pca=len(datablock)-1
beg_pca=0
GoOn=0
while GoOn==0:
ct=raw_input('Enter Calculation Type: best-fit line, plane or fisher mean [l]/p/f : ' )
if ct=="" or ct=="l":
calculation_type="DE-BFL"
GoOn=1 # all good
elif ct=='p':
calculation_type="DE-BFP"
GoOn=1 # all good
elif ct=='f':
calculation_type="DE-FM"
GoOn=1 # all good
else:
print "bad entry of calculation type: try again. " # keep going
pmagplotlib.plotZED(ZED,datablock,angle,s,SIunits) # plot the data
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type) # get best-fit direction/great circle
pmagplotlib.plotDir(ZED,mpars,datablock,angle) # plot the best-fit direction/great circle
print 'Specimen, calc_type, N, min, max, MAD, dec, inc'
if units=='mT':print '%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (s,calculation_type,mpars["specimen_n"],mpars["measurement_step_min"]*1e3,mpars["measurement_step_max"]*1e3,mpars["specimen_mad"],mpars["specimen_dec"],mpars["specimen_inc"])
if units=='C':print '%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (s,calculation_type,mpars["specimen_n"],mpars["measurement_step_min"]-273,mpars["measurement_step_max"]-273,mpars["specimen_mad"],mpars["specimen_dec"],mpars["specimen_inc"])
if units=='U':print '%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (s,calculation_type,mpars["specimen_n"],mpars["measurement_step_min"],mpars["measurement_step_max"],mpars["specimen_mad"],mpars["specimen_dec"],mpars["specimen_inc"])
def main():
"""
NAME
zeq.py
DESCRIPTION
plots demagnetization data. The equal area projection has the X direction (usually North in geographic coordinates)
to the top. The red line is the X axis of the Zijderveld diagram. Solid symbols are lower hemisphere.
The solid (open) symbols in the Zijderveld diagram are X,Y (X,Z) pairs. The demagnetization diagram plots the
fractional remanence remaining after each step. The green line is the fraction of the total remaence removed
between each step.
INPUT FORMAT
takes specimen_name treatment intensity declination inclination in space
delimited file
SYNTAX
zeq.py [command line options
OPTIONS
-f FILE for reading from command line
-u [mT,C] specify units of mT OR C, default is unscaled
-sav save figure and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-beg [step number] treatment step for beginning of PCA calculation, 0 is default
-end [step number] treatment step for end of PCA calculation, last step is default
-ct [l,p,f] Calculation Type: best-fit line, plane or fisher mean; line is default
"""
files, fmt, plot = {}, 'svg', 0
end_pca, beg_pca = "", ""
calculation_type = 'DE-BFL'
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
else:
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
else:
print(main.__doc__)
sys.exit()
if '-u' in sys.argv:
ind = sys.argv.index('-u')
units = sys.argv[ind + 1]
if units == "C": SIunits = "K"
if units == "mT": SIunits = "T"
else:
units = "U"
SIunits = "U"
if '-sav' in sys.argv: plot = 1
if '-ct' in sys.argv:
ind = sys.argv.index('-ct')
ct = sys.argv[ind + 1]
if ct == 'f': calculation_type = 'DE-FM'
if ct == 'p': calculation_type = 'DE-BFP'
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-beg' in sys.argv:
ind = sys.argv.index('-beg')
beg_pca = int(sys.argv[ind + 1])
if '-end' in sys.argv:
ind = sys.argv.index('-end')
end_pca = int(sys.argv[ind + 1])
f = open(file, 'r')
data = f.readlines()
#
datablock = [] # set up list for data
s = "" # initialize specimen name
angle = 0.
for line in data: # read in the data from standard input
rec = line.split() # split each line on space to get records
if angle == "": angle = float(rec[3])
if s == "": s = rec[0]
if units == 'mT':
datablock.append([
float(rec[1]) * 1e-3,
float(rec[3]),
float(rec[4]), 1e-3 * float(rec[2]), '', 'g'
]) # treatment, dec, inc, int # convert to T and Am^2 (assume emu)
if units == 'C':
datablock.append([
float(rec[1]) + 273.,
float(rec[3]),
float(rec[4]), 1e-3 * float(rec[2]), '', 'g'
]) # treatment, dec, inc, int, convert to K and Am^2, assume emu
if units == 'U':
datablock.append([
float(rec[1]),
float(rec[3]),
float(rec[4]),
float(rec[2]), '', 'g'
]) # treatment, dec, inc, int, using unscaled units
# define figure numbers in a dictionary for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
ZED = {}
ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3
pmagplotlib.plot_init(ZED['eqarea'], 5, 5) # initialize plots
pmagplotlib.plot_init(ZED['zijd'], 5, 5)
pmagplotlib.plot_init(ZED['demag'], 5, 5)
#
#
pmagplotlib.plotZED(ZED, datablock, angle, s, SIunits) # plot the data
if plot == 0: pmagplotlib.drawFIGS(ZED)
#
# print out data for this sample to screen
#
recnum = 0
for plotrec in datablock:
if units == 'mT':
print(
'%i %7.1f %8.3e %7.1f %7.1f ' %
(recnum, plotrec[0] * 1e3, plotrec[3], plotrec[1], plotrec[2]))
if units == 'C':
print('%i %7.1f %8.3e %7.1f %7.1f ' %
(recnum, plotrec[0] - 273., plotrec[3], plotrec[1],
plotrec[2]))
if units == 'U':
print('%i %7.1f %8.3e %7.1f %7.1f ' %
(recnum, plotrec[0], plotrec[3], plotrec[1], plotrec[2]))
recnum += 1
if plot == 0:
while 1:
if beg_pca != "" and end_pca != "" and calculation_type != "":
pmagplotlib.plotZED(ZED, datablock, angle, s,
SIunits) # plot the data
mpars = pmag.domean(
datablock, beg_pca, end_pca,
calculation_type) # get best-fit direction/great circle
pmagplotlib.plotDir(
ZED, mpars, datablock,
angle) # plot the best-fit direction/great circle
print('Specimen, calc_type, N, min, max, MAD, dec, inc')
if units == 'mT':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"] * 1e3,
mpars["measurement_step_max"] * 1e3,
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
if units == 'C':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"] - 273,
mpars["measurement_step_max"] - 273,
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
if units == 'U':
print(
'%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"],
mpars["measurement_step_max"], mpars["specimen_mad"],
mpars["specimen_dec"], mpars["specimen_inc"]))
if end_pca == "":
end_pca = len(
datablock
) - 1 # initialize end_pca, beg_pca to first and last measurement
if beg_pca == "": beg_pca = 0
ans = input(
" s[a]ve plot, [b]ounds for pca and calculate, change [h]orizontal projection angle, [q]uit: "
)
if ans == 'q':
sys.exit()
if ans == 'a':
files = {}
for key in list(ZED.keys()):
files[key] = s + '_' + key + '.' + fmt
pmagplotlib.saveP(ZED, files)
if ans == 'h':
angle = float(
input(" Declination to project onto horizontal axis? "))
pmagplotlib.plotZED(ZED, datablock, angle, s,
SIunits) # plot the data
if ans == 'b':
GoOn = 0
while GoOn == 0: # keep going until reasonable bounds are set
print('Enter index of first point for pca: ', '[', beg_pca,
']')
answer = input('return to keep default ')
if answer != "": beg_pca = int(answer)
print('Enter index of last point for pca: ', '[', end_pca,
']')
answer = input('return to keep default ')
if answer != "":
end_pca = int(answer)
if beg_pca >= 0 and beg_pca <= len(
datablock) - 2 and end_pca > 0 and end_pca < len(
datablock):
GoOn = 1
else:
print("Bad entry of indices - try again")
end_pca = len(datablock) - 1
beg_pca = 0
GoOn = 0
while GoOn == 0:
ct = input(
'Enter Calculation Type: best-fit line, plane or fisher mean [l]/p/f : '
)
if ct == "" or ct == "l":
calculation_type = "DE-BFL"
GoOn = 1 # all good
elif ct == 'p':
calculation_type = "DE-BFP"
GoOn = 1 # all good
elif ct == 'f':
calculation_type = "DE-FM"
GoOn = 1 # all good
else:
print("bad entry of calculation type: try again. "
) # keep going
pmagplotlib.plotZED(ZED, datablock, angle, s,
SIunits) # plot the data
mpars = pmag.domean(
datablock, beg_pca, end_pca, calculation_type
) # get best-fit direction/great circle
pmagplotlib.plotDir(
ZED, mpars, datablock,
angle) # plot the best-fit direction/great circle
print('Specimen, calc_type, N, min, max, MAD, dec, inc')
if units == 'mT':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"] * 1e3,
mpars["measurement_step_max"] * 1e3,
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
if units == 'C':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"] - 273,
mpars["measurement_step_max"] - 273,
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
if units == 'U':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"],
mpars["measurement_step_max"],
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
pmagplotlib.drawFIGS(ZED)
else:
print(beg_pca, end_pca)
if beg_pca != "" and end_pca != "":
pmagplotlib.plotZED(ZED, datablock, angle, s,
SIunits) # plot the data
mpars = pmag.domean(
datablock, beg_pca, end_pca,
calculation_type) # get best-fit direction/great circle
pmagplotlib.plotDir(
ZED, mpars, datablock,
angle) # plot the best-fit direction/great circle
print('Specimen, calc_type, N, min, max, MAD, dec, inc')
if units == 'mT':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"] * 1e3,
mpars["measurement_step_max"] * 1e3,
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
if units == 'C':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"] - 273,
mpars["measurement_step_max"] - 273,
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"]))
if units == 'U':
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' %
(s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"],
mpars["measurement_step_max"], mpars["specimen_mad"],
mpars["specimen_dec"], mpars["specimen_inc"]))
files = {}
for key in list(ZED.keys()):
files[key] = s + '_' + key + '.' + fmt
pmagplotlib.saveP(ZED, files)
def main():
"""
NAME
zeq_magic_redo.py
DESCRIPTION
Calculate principal components through demagnetization data using bounds and calculation type stored in "redo" file
SYNTAX
zeq_magic_redo.py [command line options]
OPTIONS
-h prints help message
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-F: specify output file, default is zeq_specimens.txt
-fre REDO: specify redo file, default is "zeq_redo"
-fsa SAMPFILE: specify er_samples format file, default is "er_samples.txt"
-A : don't average replicate measurements, default is yes
-crd [s,g,t] :
specify coordinate system [s,g,t] [default is specimen coordinates]
are specimen, geographic, and tilt corrected respectively
NB: you must have a SAMPFILE in this directory to rotate from specimen coordinates
-leg: attaches "Recalculated from original measurements; supercedes published results. " to comment field
INPUTS
zeq_redo format file is:
specimen_name calculation_type[DE-BFL,DE-BFL-A,DE-BFL-O,DE-BFP,DE-FM] step_min step_max component_name[A,B,C]
"""
dir_path = '.'
INCL = ["LT-NO", "LT-AF-Z", "LT-T-Z", "LT-M-Z"] # looking for demag data
beg, end, pole, geo, tilt, askave, save = 0, 0, [], 0, 0, 0, 0
user, doave, comment = "", 1, ""
geo, tilt = 0, 0
version_num = pmag.get_version()
args = sys.argv
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind + 1]
meas_file, pmag_file, mk_file = dir_path + "/" + "magic_measurements.txt", dir_path + "/" + "zeq_specimens.txt", dir_path + "/" + "zeq_redo"
samp_file, coord = dir_path + "/" + "er_samples.txt", ""
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = sys.argv[ind + 1]
if "-A" in args: doave = 0
if "-leg" in args:
comment = "Recalculated from original measurements; supercedes published results. "
if "-f" in args:
ind = args.index("-f")
meas_file = dir_path + '/' + sys.argv[ind + 1]
if "-F" in args:
ind = args.index("-F")
pmag_file = dir_path + '/' + sys.argv[ind + 1]
if "-fre" in args:
ind = args.index("-fre")
mk_file = dir_path + "/" + args[ind + 1]
try:
mk_f = open(mk_file, 'r')
except:
print("Bad redo file")
sys.exit()
mkspec, skipped = [], []
speclist = []
for line in mk_f.readlines():
tmp = line.split()
mkspec.append(tmp)
speclist.append(tmp[0])
if "-fsa" in args:
ind = args.index("-fsa")
samp_file = dir_path + '/' + sys.argv[ind + 1]
if "-crd" in args:
ind = args.index("-crd")
coord = sys.argv[ind + 1]
if coord == "g": geo, tilt = 1, 0
if coord == "t": geo, tilt = 1, 1
#
# now get down to bidness
if geo == 1:
samp_data, file_type = pmag.magic_read(samp_file)
if file_type != 'er_samples':
print(file_type)
print("This is not a valid er_samples file ")
sys.exit()
#
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(file_type)
print(file_type, "This is not a valid magic_measurements file ")
sys.exit()
#
# sort the specimen names
#
k = 0
print('Processing ', len(speclist), ' specimens - please wait')
PmagSpecs = []
while k < len(speclist):
s = speclist[k]
recnum = 0
PmagSpecRec = {}
method_codes, inst_codes = [], []
# find the data from the meas_data file for this sample
#
# collect info for the PmagSpecRec dictionary
#
meas_meth = []
spec = pmag.get_dictitem(meas_data, 'er_specimen_name', s, 'T')
if len(spec) == 0:
print('no data found for specimen: ', s)
print('delete from zeq_redo input file...., then try again')
else:
for rec in spec: # copy of vital stats to PmagSpecRec from first spec record in demag block
skip = 1
methods = rec["magic_method_codes"].split(":")
if len(set(methods) & set(INCL)) > 0:
PmagSpecRec["er_analyst_mail_names"] = user
PmagSpecRec["magic_software_packages"] = version_num
PmagSpecRec["er_specimen_name"] = s
PmagSpecRec["er_sample_name"] = rec["er_sample_name"]
PmagSpecRec["er_site_name"] = rec["er_site_name"]
PmagSpecRec["er_location_name"] = rec["er_location_name"]
if "er_expedition_name" in list(rec.keys()):
PmagSpecRec["er_expedition_name"] = rec[
"er_expedition_name"]
PmagSpecRec["er_citation_names"] = "This study"
if "magic_experiment_name" not in list(rec.keys()):
rec["magic_experiment_name"] = ""
PmagSpecRec["magic_experiment_names"] = rec[
"magic_experiment_name"]
if "magic_instrument_codes" not in list(rec.keys()):
rec["magic_instrument_codes"] = ""
inst = rec['magic_instrument_codes'].split(":")
for I in inst:
if I not in inst_codes: # copy over instruments
inst_codes.append(I)
meths = rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in meas_meth:
meas_meth.append(meth)
if "LP-DIR-AF" in meas_meth or "LT-AF-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"] = "T"
if "LP-DIR-AF" not in method_codes:
method_codes.append("LP-DIR-AF")
if "LP-DIR-T" in meas_meth or "LT-T-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"] = "K"
if "LP-DIR-T" not in method_codes:
method_codes.append("LP-DIR-T")
if "LP-DIR-M" in meas_meth or "LT-M-Z" in meas_meth:
PmagSpecRec["measurement_step_unit"] = "J"
if "LP-DIR-M" not in method_codes:
method_codes.append("LP-DIR-M")
#
#
datablock, units = pmag.find_dmag_rec(
s, spec) # fish out the demag data for this specimen
#
if len(datablock) < 2 or s not in speclist:
k += 1
# print 'skipping ', s,len(datablock)
else:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
#
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
#
# do geo or stratigraphic correction now
#
if geo == 1 or tilt == 1:
# find top priority orientation method
orient, az_type = pmag.get_orient(
samp_data, PmagSpecRec["er_sample_name"])
if az_type not in method_codes: method_codes.append(az_type)
#
# if tilt selected, get stratigraphic correction
#
tiltblock, geoblock = [], []
for rec in datablock:
if "sample_azimuth" in list(
orient.keys()) and orient["sample_azimuth"] != "":
d_geo, i_geo = pmag.dogeo(
rec[1], rec[2], float(orient["sample_azimuth"]),
float(orient["sample_dip"]))
geoblock.append(
[rec[0], d_geo, i_geo, rec[3], rec[4], rec[5]])
if tilt == 1 and "sample_bed_dip_direction" in list(
orient.keys()):
d_tilt, i_tilt = pmag.dotilt(
d_geo, i_geo,
float(orient["sample_bed_dip_direction"]),
float(orient["sample_bed_dip"]))
tiltblock.append([
rec[0], d_tilt, i_tilt, rec[3], rec[4], rec[5]
])
elif tilt == 1:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no tilt correction for ',
PmagSpecRec["er_sample_name"],
' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
else:
if PmagSpecRec["er_sample_name"] not in skipped:
print('no geographic correction for ',
PmagSpecRec["er_sample_name"],
' skipping....')
skipped.append(PmagSpecRec["er_sample_name"])
#
# get beg_pca, end_pca, pca
if PmagSpecRec['er_sample_name'] not in skipped:
compnum = -1
for spec in mkspec:
if spec[0] == s:
CompRec = {}
for key in list(PmagSpecRec.keys()):
CompRec[key] = PmagSpecRec[key]
compnum += 1
calculation_type = spec[1]
beg = float(spec[2])
end = float(spec[3])
if len(spec) > 4:
comp_name = spec[4]
else:
comp_name = string.uppercase[compnum]
CompRec['specimen_comp_name'] = comp_name
if beg < float(datablock[0][0]):
beg = float(datablock[0][0])
if end > float(datablock[-1][0]):
end = float(datablock[-1][0])
for l in range(len(datablock)):
if datablock[l][0] == beg: beg_pca = l
if datablock[l][0] == end: end_pca = l
if geo == 1 and tilt == 0:
mpars = pmag.domean(geoblock, beg_pca, end_pca,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
CompRec["specimen_dec"] = '%7.1f ' % (
mpars["specimen_dec"])
CompRec["specimen_inc"] = '%7.1f ' % (
mpars["specimen_inc"])
CompRec["specimen_tilt_correction"] = '0'
if geo == 1 and tilt == 1:
mpars = pmag.domean(tiltblock, beg_pca, end_pca,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
CompRec["specimen_dec"] = '%7.1f ' % (
mpars["specimen_dec"])
CompRec["specimen_inc"] = '%7.1f ' % (
mpars["specimen_inc"])
CompRec["specimen_tilt_correction"] = '100'
if geo == 0 and tilt == 0:
mpars = pmag.domean(datablock, beg_pca, end_pca,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
CompRec["specimen_dec"] = '%7.1f ' % (
mpars["specimen_dec"])
CompRec["specimen_inc"] = '%7.1f ' % (
mpars["specimen_inc"])
CompRec["specimen_tilt_correction"] = '-1'
if mpars["specimen_direction_type"] == "Error":
pass
else:
CompRec["measurement_step_min"] = '%8.3e ' % (
datablock[beg_pca][0])
try:
CompRec["measurement_step_max"] = '%8.3e ' % (
datablock[end_pca][0])
except:
print('error in end_pca ',
PmagSpecRec['er_specimen_name'])
CompRec["specimen_correction"] = 'u'
if calculation_type != 'DE-FM':
CompRec["specimen_mad"] = '%7.1f ' % (
mpars["specimen_mad"])
CompRec["specimen_alpha95"] = ""
else:
CompRec["specimen_mad"] = ""
CompRec["specimen_alpha95"] = '%7.1f ' % (
mpars["specimen_alpha95"])
CompRec["specimen_n"] = '%i ' % (
mpars["specimen_n"])
CompRec["specimen_dang"] = '%7.1f ' % (
mpars["specimen_dang"])
CompMeths = []
for meth in method_codes:
if meth not in CompMeths:
CompMeths.append(meth)
if calculation_type not in CompMeths:
CompMeths.append(calculation_type)
if geo == 1: CompMeths.append("DA-DIR-GEO")
if tilt == 1: CompMeths.append("DA-DIR-TILT")
if "DE-BFP" not in calculation_type:
CompRec["specimen_direction_type"] = 'l'
else:
CompRec["specimen_direction_type"] = 'p'
CompRec["magic_method_codes"] = ""
if len(CompMeths) != 0:
methstring = ""
for meth in CompMeths:
methstring = methstring + ":" + meth
CompRec[
"magic_method_codes"] = methstring.strip(
':')
CompRec["specimen_description"] = comment
if len(inst_codes) != 0:
inststring = ""
for inst in inst_codes:
inststring = inststring + ":" + inst
CompRec[
"magic_instrument_codes"] = inststring.strip(
':')
PmagSpecs.append(CompRec)
k += 1
pmag.magic_write(pmag_file, PmagSpecs, 'pmag_specimens')
print("Recalculated specimen data stored in ", pmag_file)
def main():
"""
NAME
pca.py
DESCRIPTION
calculates best-fit line/plane through demagnetization data
INPUT FORMAT
takes specimen_name treatment intensity declination inclination in space delimited file
SYNTAX
pca.py [command line options][< filename]
OPTIONS
-h prints help and quits
-f FILE
-dir [L,P,F][BEG][END] specify direction type, beginning and end
(L:line, P:plane or F:fisher mean of unit vectors)
BEG: first step (NRM = step zero)
END: last step (NRM = step zero)
< filename for reading from standard input
OUTPUT:
specimen_name calculation_type N beg end MAD dec inc
if calculation_type is 'p', dec and inc are pole to plane, otherwise, best-fit direction
EXAMPLE:
pca.py -dir L 1 5 <ex3.3
will calculate best-fit line through demagnetization steps 1 and 5 from file ex5.1
"""
if '-h' in sys.argv: # check if help is needed
print main.__doc__
sys.exit() # graceful quit
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
f = open(file, 'rU')
data = f.readlines()
else:
data = sys.stdin.readlines() # read in data from standard input
if '-dir' in sys.argv: #
ind = sys.argv.index('-dir')
typ = sys.argv[ind + 1]
if typ == 'L': calculation_type = 'DE-BFL'
if typ == 'P': calculation_type = 'DE-BFP'
if typ == 'F': calculation_type = 'DE-FM'
beg_pca = int(sys.argv[ind + 2])
end_pca = int(sys.argv[ind + 3])
#
#
datablock = [] # set up list for data
s = ""
ind = 0
for line in data: # read in the data from standard input
rec = line.split() # split each line on space to get records
if s == "":
s = rec[0]
print s, calculation_type
print ind, rec[1], rec[3], rec[4], rec[2]
ind += 1
datablock.append(
[float(rec[1]),
float(rec[3]),
float(rec[4]),
float(rec[2]), '0']) # treatment,dec,inc,int,dummy
mpars = pmag.domean(datablock, beg_pca, end_pca, calculation_type)
if calculation_type == "DE-FM":
print '%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (
s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"], mpars["measurement_step_max"],
mpars["specimen_a95"], mpars["specimen_dec"],
mpars["specimen_inc"])
else:
print '%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (
s, calculation_type, mpars["specimen_n"],
mpars["measurement_step_min"], mpars["measurement_step_max"],
mpars["specimen_mad"], mpars["specimen_dec"],
mpars["specimen_inc"])
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'
-fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
-fcr CRIT, set criteria file for grading. # not yet implemented
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out 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
-b BEG END: sets bounds for calculation
BEG: starting step number for slope calculation
END: ending step number for slope calculation
-z use only z component difference for pTRM calculation
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
"""
#
# initializations
#
version_num=pmag.get_version()
verbose=pmagplotlib.verbose
#
# default acceptance criteria
#
accept=pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
plots,fmt,Zdiff=0,'svg',0
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")
crit_file=pmag.get_named_arg_from_sys("-fcr", default_val="criteria.txt")
spec_file=os.path.join(dir_path,spec_file)
meas_file=os.path.join(dir_path,meas_file)
crit_file=os.path.join(dir_path,crit_file)
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
if '-sav' in sys.argv: plots,verbose=1,0
if '-z' in sys.argv: Zdiff=1
specimen=pmag.get_named_arg_from_sys("-spc",default_val="")
if '-b' in sys.argv:
ind=sys.argv.index('-b')
start=int(sys.argv[ind+1])
end=int(sys.argv[ind+2])
else:
start,end="",""
fnames = {'measurements': meas_file, 'specimens': spec_file, 'criteria': crit_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames, read_tables=['measurements', 'specimens', 'criteria'])
#
# import prior interpretations from specimen file
#
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:
spec_container = contribution.tables['specimens']
prior_spec_data=spec_container.get_records_for_code('LP-PI-TRM',strict_match=False) # look up all prior intensity interpretations
else:
spec_container, prior_spec_data = None, []
backup=0
#
Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
#
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data['method_codes']=meas_data['method_codes'].str.replace(" ","") # get rid of nasty spaces
meas_data= meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM|LP-TRM|LP-TRM-TD')==True] # fish out zero field steps for plotting
intensity_types = [col_name for col_name in meas_data.columns if col_name in Mkeys]
int_key = intensity_types[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
meas_data = meas_data[meas_data[int_key].notnull()] # get all the non-null intensity records of the same type
if 'flag' not in meas_data.columns: meas_data['flag'] = 'g' # set the default flag to good
meas_data = meas_data[meas_data['flag'].str.contains('g')==True] # only the 'good' measurements
thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')==True] # get all the Thellier data
trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM')==True] # get all the TRM acquisition data
td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD')==True] # get all the TD data
anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN')==True] # get all the anisotropy data
#
# get list of unique specimen names from measurement data
#
specimen_names= meas_data.specimen.unique() # this is a Series of all the specimen names
specimen_names= specimen_names.tolist() # turns it into a list
specimen_names.sort() # sorts by specimen name
#
# set up new DataFrame for this sessions specimen interpretations
#
spec_container = nb.MagicDataFrame(dtype='specimens', columns=specimen_cols)
current_spec_data = spec_container.df # this is for interpretations from this session
if specimen=="": # do all specimens
k = 0
else:
k=specimen_names.index(specimen) # just do this one
# define figure numbers for arai, zijderveld and
# de-,re-magnetization diagrams
AZD={}
AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
pmagplotlib.plot_init(AZD['arai'],5,5)
pmagplotlib.plot_init(AZD['zijd'],5,5)
pmagplotlib.plot_init(AZD['deremag'],5,5)
pmagplotlib.plot_init(AZD['eqarea'],5,5)
if len(trm_data)>0:
AZD['TRM']=5
pmagplotlib.plot_init(AZD['TRM'],5,5)
if len(td_data)>0:
AZD['TDS']=6
pmagplotlib.plot_init(AZD['TDS'],5,5)
#
while k < len(specimen_names):
this_specimen=specimen_names[k] # set the current specimen for plotting
if verbose and this_specimen!="":print(this_specimen, k+1 , 'out of ',len(specimen_names))
#
# set up datablocks
#
thelblock= thel_data[thel_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
trmblock= trm_data[trm_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
tdsrecs= td_data[td_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
anisblock= anis_data[anis_data['specimen'].str.contains(this_specimen)==True] # fish out the anisotropy data
prior_specimen_interpretations= prior_spec_data[prior_spec_data['specimen'].str.contains(this_specimen)==True] # fish out prior interpretation
#
# sort data into types
#
araiblock,field=pmag.sortarai(thelblock,this_specimen,Zdiff,version=3)
first_Z=araiblock[0]
GammaChecks=araiblock[5]
if len(first_Z)<3:
if backup==0:
k+=1
if verbose:
print('skipping specimen - moving forward ', this_specimen)
else:
k-=1
if verbose:
print('skipping specimen - moving backward ', this_specimen)
else:
backup=0
zijdblock,units=pmag.find_dmag_rec(this_specimen,thelblock,version=3)
if start=="" and len(prior_specimen_interpretations)>0:
if verbose: print('Looking up saved interpretation....')
#
# get prior interpretation steps
#
beg_int=pd.to_numeric(prior_specimen_interpretations.meas_step_min.values).tolist()[0]
end_int=pd.to_numeric(prior_specimen_interpretations.meas_step_max.values).tolist()[0]
else: beg_int,end_int="",""
recnum=0
if verbose: print("index step Dec Inc Int Gamma")
for plotrec in zijdblock:
if plotrec[0]==beg_int:start=recnum # while we are at it, collect these bounds
if plotrec[0]==end_int:end=recnum
if verbose:
if GammaChecks!="":
gamma=""
for g in GammaChecks:
if g[0]==plotrec[0]-273:
gamma=g[1]
break
if gamma!="":
print('%i %i %7.1f %7.1f %8.3e %7.1f' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3],gamma))
else:
print('%i %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3]))
recnum += 1
for fig in list(AZD.keys()):pmagplotlib.clearFIG(AZD[fig]) # clear all figures
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,this_specimen,units[0])
if verbose:pmagplotlib.drawFIGS(AZD)
pars,errcode=pmag.PintPars(thelblock,araiblock,zijdblock,start,end,accept,version=3)
pars['measurement_step_unit']="K"
pars['experiment_type']='LP-PI-TRM'
#
# work on saving interpretations stuff later
#
if errcode!=1: # no problem in PintPars
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=this_specimen
#pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose) # deal with this later
pars["specimen_grade"]='None'
pars['measurement_step_min']=pars['meas_step_min']
pars['measurement_step_max']=pars['meas_step_max']
if pars['measurement_step_unit']=='K':
outstr= "specimen Tmin Tmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma Gamma_max \n"
pars_out= (this_specimen,(pars["meas_step_min"]-273),(pars["meas_step_max"]-273),(pars["specimen_int_n"]),1e6*(pars["specimen_lab_field_dc"]),1e6*(pars["specimen_int"]),pars["specimen_b"],pars["specimen_q"],pars["specimen_f"],pars["specimen_fvds"],pars["specimen_b_beta"],pars["int_mad_free"],pars["int_dang"],pars["int_drats"],pars["int_n_ptrm"],pars["specimen_grade"],np.sqrt(pars["specimen_rsc"]),int(pars["int_md"]), pars["specimen_b_sigma"],pars['specimen_gamma'])
outstring= '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out +'\n'
elif pars['measurement_step_unit']=='J':
outstr= "specimen Wmin Wmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma ThetaMax DeltaMax GammaMax\n"
pars_out= (this_specimen,(pars["meas_step_min"]),(pars["meas_step_max"]),(pars["specimen_int_n"]),1e6*(pars["specimen_lab_field_dc"]),1e6*(pars["specimen_int"]),pars["specimen_b"],pars["specimen_q"],pars["specimen_f"],pars["specimen_fvds"],pars["specimen_b_beta"],pars["specimen_int_mad"],pars["specimen_int_dang"],pars["specimen_drats"],pars["specimen_int_ptrm_n"],pars["specimen_grade"],np.sqrt(pars["specimen_rsc"]),int(pars["specimen_md"]), pars["specimen_b_sigma"],pars["specimen_theta"],pars["specimen_delta"],pars["specimen_gamma"])
outstring= '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out +'\n'
print(outstr)
print(outstring)
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
mpars=pmag.domean(araiblock[1],start,end,'DE-BFL')
if verbose:
pmagplotlib.drawFIGS(AZD)
print('pTRM direction= ','%7.1f'%(mpars['specimen_dec']),' %7.1f'%(mpars['specimen_inc']),' MAD:','%7.1f'%(mpars['specimen_mad']))
if len(anisblock)>0: # this specimen has anisotropy data
if verbose: print('Found anisotropy record... but ignoring for now ')
if plots==1:
if fmt != "pmag":
files={}
for key in list(AZD.keys()):
files[key]='SP:_'+this_specimen+'_TY:_'+key+'_'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['deremag']='DeReMag Plot'
titles['zijd']='Zijderveld Plot'
titles['arai']='Arai Plot'
titles['TRM']='TRM Acquisition data'
AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
pmagplotlib.saveP(AZD,files)
else: # save in pmag format
print('pmag format no longer supported')
#script="grep "+this_specimen+" output.mag | thellier -mfsi"
#script=script+' %8.4e'%(field)
#min='%i'%((pars["measurement_step_min"]-273))
#Max='%i'%((pars["measurement_step_max"]-273))
#script=script+" "+min+" "+Max
#script=script+" |plotxy;cat mypost >>thellier.ps\n"
#pltf.write(script)
#pmag.domagicmag(outf,MeasRecs)
if specimen!="": sys.exit() # syonara
if verbose:
ans=input('Return for next specimen, q to quit: ')
if ans=='q':sys.exit()
k+=1 # moving on
def main():
"""
NAME
pca.py
DESCRIPTION
calculates best-fit line/plane through demagnetization data
INPUT FORMAT
takes specimen_name treatment intensity declination inclination in space delimited file
SYNTAX
pca.py [command line options][< filename]
OPTIONS
-h prints help and quits
-f FILE
-dir [L,P,F][BEG][END] specify direction type, beginning and end
(L:line, P:plane or F:fisher mean of unit vectors)
BEG: first step (NRM = step zero)
END: last step (NRM = step zero)
< filename for reading from standard input
OUTPUT:
specimen_name calculation_type N beg end MAD dec inc
if calculation_type is 'p', dec and inc are pole to plane, otherwise, best-fit direction
EXAMPLE:
pca.py -dir L 1 5 <ex3.3
will calculate best-fit line through demagnetization steps 1 and 5 from file ex5.1
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
data=f.readlines()
else:
data=sys.stdin.readlines() # read in data from standard input
if '-dir' in sys.argv: #
ind=sys.argv.index('-dir')
typ=sys.argv[ind+1]
if typ=='L': calculation_type='DE-BFL'
if typ=='P': calculation_type='DE-BFP'
if typ=='F': calculation_type='DE-FM'
beg_pca = int(sys.argv[ind+2])
end_pca = int(sys.argv[ind+3])
#
#
datablock= [] # set up list for data
s=""
ind=0
for line in data: # read in the data from standard input
rec=line.split() # split each line on space to get records
if s=="":
s=rec[0]
print(s, calculation_type)
print(ind,rec[1],rec[3],rec[4],rec[2])
ind+=1
datablock.append([float(rec[1]),float(rec[3]),float(rec[4]),float(rec[2]),'0']) # treatment,dec,inc,int,dummy
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if calculation_type=="DE-FM":
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (s,calculation_type,mpars["specimen_n"],mpars["measurement_step_min"],mpars["measurement_step_max"],mpars["specimen_a95"],mpars["specimen_dec"],mpars["specimen_inc"]))
else:
print('%s %s %i %6.2f %6.2f %6.1f %7.1f %7.1f' % (s,calculation_type,mpars["specimen_n"],mpars["measurement_step_min"],mpars["measurement_step_max"],mpars["specimen_mad"],mpars["specimen_dec"],mpars["specimen_inc"]))
