def main():
"""
NAME
qqunf.py
DESCRIPTION
makes qq plot from input data against uniform distribution
SYNTAX
qqunf.py [command line options]
OPTIONS
-h help message
-f FILE, specify file on command line
"""
fmt, plot = 'svg', 0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
elif '-f' in sys.argv: # ask for filename
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
f = open(file, 'r')
input = f.readlines()
Data = []
for line in input:
line.replace('\n', '')
if '\t' in line: # read in the data from standard input
rec = line.split('\t') # split each line on space to get records
else:
rec = line.split() # split each line on space to get records
Data.append(float(rec[0]))
#
if len(Data) >= 10:
QQ = {'unf1': 1}
pmagplotlib.plot_init(QQ['unf1'], 5, 5)
pmagplotlib.plot_qq_unf(QQ['unf1'], Data, 'QQ-Uniform') # make plot
else:
print('you need N> 10')
sys.exit()
pmagplotlib.draw_figs(QQ)
files = {}
for key in list(QQ.keys()):
files[key] = key + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Equal Area Plot'
EQ = pmagplotlib.add_borders(EQ, titles, black, purple)
pmagplotlib.save_plots(QQ, files)
elif plot == 1:
files['qq'] = file + '.' + fmt
pmagplotlib.save_plots(QQ, files)
else:
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a": pmagplotlib.save_plots(QQ, files)
def main():
"""
NAME
plot_2cdfs.py
DESCRIPTION
makes plots of cdfs of data in input file
SYNTAX
plot_2cdfs.py [-h][command line options]
OPTIONS
-h prints help message and quits
-f FILE1 FILE2
-t TITLE
-fmt [svg,eps,png,pdf,jpg..] specify format of output figure, default is svg
"""
fmt = 'svg'
title = ""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
X = numpy.loadtxt(file)
file = sys.argv[ind + 2]
X2 = numpy.loadtxt(file)
# else:
# X=numpy.loadtxt(sys.stdin,dtype=numpy.float)
else:
print('-f option required')
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-t' in sys.argv:
ind = sys.argv.index('-t')
title = sys.argv[ind + 1]
CDF = {'X': 1}
pmagplotlib.plot_init(CDF['X'], 5, 5)
pmagplotlib.plot_cdf(CDF['X'], X, '', 'r', '')
pmagplotlib.plot_cdf(CDF['X'], X2, title, 'b', '')
D, p = scipy.stats.ks_2samp(X, X2)
if p >= .05:
print(D, p, ' not rejected at 95%')
else:
print(D, p, ' rejected at 95%')
pmagplotlib.draw_figs(CDF)
ans = input('S[a]ve plot, <Return> to quit ')
if ans == 'a':
files = {'X': 'CDF_.' + fmt}
pmagplotlib.save_plots(CDF, files)
def main():
"""
NAME
plot_2cdfs.py
DESCRIPTION
makes plots of cdfs of data in input file
SYNTAX
plot_2cdfs.py [-h][command line options]
OPTIONS
-h prints help message and quits
-f FILE1 FILE2
-t TITLE
-fmt [svg,eps,png,pdf,jpg..] specify format of output figure, default is svg
"""
fmt='svg'
title=""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
X=numpy.loadtxt(file)
file=sys.argv[ind+2]
X2=numpy.loadtxt(file)
# else:
# X=numpy.loadtxt(sys.stdin,dtype=numpy.float)
else:
print('-f option required')
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-t' in sys.argv:
ind=sys.argv.index('-t')
title=sys.argv[ind+1]
CDF={'X':1}
pmagplotlib.plot_init(CDF['X'],5,5)
pmagplotlib.plot_cdf(CDF['X'],X,'','r','')
pmagplotlib.plot_cdf(CDF['X'],X2,title,'b','')
D,p=scipy.stats.ks_2samp(X,X2)
if p>=.05:
print(D,p,' not rejected at 95%')
else:
print(D,p,' rejected at 95%')
pmagplotlib.draw_figs(CDF)
ans= input('S[a]ve plot, <Return> to quit ')
if ans=='a':
files={'X':'CDF_.'+fmt}
pmagplotlib.save_plots(CDF,files)
def main():
"""
NAME
plot_cdf.py
DESCRIPTION
makes plots of cdfs of data in input file
SYNTAX
plot_cdf.py [-h][command line options]
OPTIONS
-h prints help message and quits
-f FILE
-t TITLE
-fmt [svg,eps,png,pdf,jpg..] specify format of output figure, default is svg
-sav saves plot and quits
"""
fmt, plot = 'svg', 0
title = ""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-sav' in sys.argv: plot = 1
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
X = numpy.loadtxt(file)
# else:
# X=numpy.loadtxt(sys.stdin,dtype=numpy.float)
else:
print('-f option required')
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-t' in sys.argv:
ind = sys.argv.index('-t')
title = sys.argv[ind + 1]
CDF = {'X': 1}
pmagplotlib.plot_init(CDF['X'], 5, 5)
pmagplotlib.plot_cdf(CDF['X'], X, title, 'r', '')
files = {'X': 'CDF_.' + fmt}
if plot == 0:
pmagplotlib.draw_figs(CDF)
ans = input('S[a]ve plot, <Return> to quit ')
if ans == 'a':
pmagplotlib.save_plots(CDF, files)
else:
pmagplotlib.save_plots(CDF, files)
def main():
"""
NAME
plot_cdf.py
DESCRIPTION
makes plots of cdfs of data in input file
SYNTAX
plot_cdf.py [-h][command line options]
OPTIONS
-h prints help message and quits
-f FILE
-t TITLE
-fmt [svg,eps,png,pdf,jpg..] specify format of output figure, default is svg
-sav saves plot and quits
"""
fmt,plot='svg',0
title=""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-sav' in sys.argv:plot=1
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
X=numpy.loadtxt(file)
# else:
# X=numpy.loadtxt(sys.stdin,dtype=numpy.float)
else:
print('-f option required')
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-t' in sys.argv:
ind=sys.argv.index('-t')
title=sys.argv[ind+1]
CDF={'X':1}
pmagplotlib.plot_init(CDF['X'],5,5)
pmagplotlib.plot_cdf(CDF['X'],X,title,'r','')
files={'X':'CDF_.'+fmt}
if plot==0:
pmagplotlib.draw_figs(CDF)
ans= input('S[a]ve plot, <Return> to quit ')
if ans=='a':
pmagplotlib.save_plots(CDF,files)
else:
pmagplotlib.save_plots(CDF,files)
def plot(self, save=False, fmt="svg"):
fig = plt.figure(figsize=(6, 5), facecolor='white')
fig.subplots_adjust(left=0.18,
right=0.97,
bottom=0.18,
top=0.9,
wspace=0.5,
hspace=0.5)
#ax = fig.add_subplot(1,1,1)
plt.contour(self.xi * 1000,
self.yi * 1000,
self.zi,
9,
colors='k',
linewidths=0.5) # mt to T
# plt.pcolormesh(X,Y,Z_a,cmap=plt.get_cmap('rainbow'))#vmin=np.min(rho)-0.2)
plt.pcolormesh(self.xi * 1000,
self.yi * 1000,
self.zi,
cmap=plt.get_cmap('rainbow')) # vmin=np.min(rho)-0.2)
plt.colorbar()
# plt.xlim(0,0.15)
# plt.ylim(-0.1,0.1)
plt.xlabel('B$_{c}$ (mT)', fontsize=12)
plt.ylabel('B$_{i}$ (mT)', fontsize=12)
from pmagpy import pmagplotlib
if save:
pmagplotlib.save_plots({'forc': 1},
{'forc': 'forc.{}'.format(fmt)})
return
else:
pmagplotlib.draw_figs({'forc': 1})
res = pmagplotlib.save_or_quit()
if res == 'a':
pmagplotlib.save_plots({'forc': 1},
{'forc': 'forc.{}'.format(fmt)})
def main():
"""
NAME
foldtest_magic.py
DESCRIPTION
does a fold test (Tauxe, 2010) on data
INPUT FORMAT
pmag_specimens format file, er_samples.txt format file (for bedding)
SYNTAX
foldtest_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f sites formatted file [default for 3.0 is sites.txt, for 2.5, pmag_sites.txt]
-fsa samples formatted file
-fsi sites formatted file
-exc use criteria to set acceptance criteria (supported only for data model 3)
-n NB, set number of bootstraps, default is 1000
-b MIN, MAX, set bounds for untilting, default is -10, 150
-fmt FMT, specify format - default is svg
-sav saves plots and quits
-DM NUM MagIC data model number (2 or 3, default 3)
OUTPUT
Geographic: is an equal area projection of the input data in
original coordinates
Stratigraphic: is an equal area projection of the input data in
tilt adjusted coordinates
% Untilting: The dashed (red) curves are representative plots of
maximum eigenvalue (tau_1) as a function of untilting
The solid line is the cumulative distribution of the
% Untilting required to maximize tau for all the
bootstrapped data sets. The dashed vertical lines
are 95% confidence bounds on the % untilting that yields
the most clustered result (maximum tau_1).
Command line: prints out the bootstrapped iterations and
finally the confidence bounds on optimum untilting.
If the 95% conf bounds include 0, then a pre-tilt magnetization is indicated
If the 95% conf bounds include 100, then a post-tilt magnetization is indicated
If the 95% conf bounds exclude both 0 and 100, syn-tilt magnetization is
possible as is vertical axis rotation or other pathologies
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
kappa = 0
dir_path = pmag.get_named_arg("-WD", ".")
nboot = int(float(pmag.get_named_arg("-n", 1000))) # number of bootstraps
fmt = pmag.get_named_arg("-fmt", "svg")
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
if data_model_num == 3:
infile = pmag.get_named_arg("-f", 'sites.txt')
orfile = 'samples.txt'
site_col = 'site'
dec_col = 'dir_dec'
inc_col = 'dir_inc'
tilt_col = 'dir_tilt_correction'
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
crit_col = 'criterion'
critfile = 'criteria.txt'
else:
infile = pmag.get_named_arg("-f", 'pmag_sites.txt')
orfile = 'er_samples.txt'
site_col = 'er_site_name'
dec_col = 'site_dec'
inc_col = 'site_inc'
tilt_col = 'site_tilt_correction'
dipkey, azkey = 'sample_bed_dip', 'sample_bed_dip_direction'
crit_col = 'pmag_criteria_code'
critfile = 'pmag_criteria.txt'
if '-sav' in sys.argv:
plot = 1
else:
plot = 0
if '-b' in sys.argv:
ind = sys.argv.index('-b')
untilt_min = int(sys.argv[ind + 1])
untilt_max = int(sys.argv[ind + 2])
else:
untilt_min, untilt_max = -10, 150
if '-fsa' in sys.argv:
orfile = pmag.get_named_arg("-fsa", "")
elif '-fsi' in sys.argv:
orfile = pmag.get_named_arg("-fsi", "")
if data_model_num == 3:
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
else:
dipkey, azkey = 'site_bed_dip', 'site_bed_dip_direction'
else:
if data_model_num == 3:
orfile = 'sites.txt'
else:
orfile = 'pmag_sites.txt'
orfile = pmag.resolve_file_name(orfile, dir_path)
infile = pmag.resolve_file_name(infile, dir_path)
critfile = pmag.resolve_file_name(critfile, dir_path)
df = pd.read_csv(infile, sep='\t', header=1)
# keep only records with tilt_col
data = df.copy()
data = data[data[tilt_col].notnull()]
data = data.where(data.notnull(), "")
# turn into pmag data list
data = list(data.T.apply(dict))
# get orientation data
if data_model_num == 3:
# often orientation will be in infile (sites table)
if os.path.split(orfile)[1] == os.path.split(infile)[1]:
ordata = df[df[azkey].notnull()]
ordata = ordata[ordata[dipkey].notnull()]
ordata = list(ordata.T.apply(dict))
# sometimes orientation might be in a sample file instead
else:
ordata = pd.read_csv(orfile, sep='\t', header=1)
ordata = list(ordata.T.apply(dict))
else:
ordata, file_type = pmag.magic_read(orfile)
if '-exc' in sys.argv:
crits, file_type = pmag.magic_read(critfile)
SiteCrits = []
for crit in crits:
if crit[crit_col] == "DE-SITE":
SiteCrits.append(crit)
#break
# get to work
#
PLTS = {'geo': 1, 'strat': 2, 'taus': 3} # make plot dictionary
if not set_env.IS_WIN:
pmagplotlib.plot_init(PLTS['geo'], 5, 5)
pmagplotlib.plot_init(PLTS['strat'], 5, 5)
pmagplotlib.plot_init(PLTS['taus'], 5, 5)
if data_model_num == 2:
GEOrecs = pmag.get_dictitem(data, tilt_col, '0', 'T')
else:
GEOrecs = data
if len(GEOrecs) > 0: # have some geographic data
num_dropped = 0
DIDDs = [] # set up list for dec inc dip_direction, dip
for rec in GEOrecs: # parse data
dip, dip_dir = 0, -1
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
orecs = pmag.get_dictitem(ordata, site_col, rec[site_col], 'T')
if len(orecs) > 0:
if orecs[0][azkey] != "":
dip_dir = float(orecs[0][azkey])
if orecs[0][dipkey] != "":
dip = float(orecs[0][dipkey])
if dip != 0 and dip_dir != -1:
if '-exc' in sys.argv:
keep = 1
for site_crit in SiteCrits:
crit_name = site_crit['table_column'].split('.')[1]
if crit_name and crit_name in rec.keys(
) and rec[crit_name]:
# get the correct operation (<, >=, =, etc.)
op = OPS[site_crit['criterion_operation']]
# then make sure the site record passes
if op(float(rec[crit_name]),
float(site_crit['criterion_value'])):
keep = 0
if keep == 1:
DIDDs.append([Dec, Inc, dip_dir, dip])
else:
num_dropped += 1
else:
DIDDs.append([Dec, Inc, dip_dir, dip])
if num_dropped:
print(
"-W- Dropped {} records because each failed one or more criteria"
.format(num_dropped))
else:
print('no geographic directional data found')
sys.exit()
pmagplotlib.plot_eq(PLTS['geo'], DIDDs, 'Geographic')
data = np.array(DIDDs)
D, I = pmag.dotilt_V(data)
TCs = np.array([D, I]).transpose()
pmagplotlib.plot_eq(PLTS['strat'], TCs, 'Stratigraphic')
if plot == 0:
pmagplotlib.draw_figs(PLTS)
Percs = list(range(untilt_min, untilt_max))
Cdf, Untilt = [], []
plt.figure(num=PLTS['taus'])
print('doing ', nboot, ' iterations...please be patient.....')
for n in range(
nboot
): # do bootstrap data sets - plot first 25 as dashed red line
if n % 50 == 0:
print(n)
Taus = [] # set up lists for taus
PDs = pmag.pseudo(DIDDs)
if kappa != 0:
for k in range(len(PDs)):
d, i = pmag.fshdev(kappa)
dipdir, dip = pmag.dodirot(d, i, PDs[k][2], PDs[k][3])
PDs[k][2] = dipdir
PDs[k][3] = dip
for perc in Percs:
tilt = np.array([1., 1., 1., 0.01 * perc])
D, I = pmag.dotilt_V(PDs * tilt)
TCs = np.array([D, I]).transpose()
ppars = pmag.doprinc(TCs) # get principal directions
Taus.append(ppars['tau1'])
if n < 25:
plt.plot(Percs, Taus, 'r--')
# tilt that gives maximum tau
Untilt.append(Percs[Taus.index(np.max(Taus))])
Cdf.append(float(n) / float(nboot))
plt.plot(Percs, Taus, 'k')
plt.xlabel('% Untilting')
plt.ylabel('tau_1 (red), CDF (green)')
Untilt.sort() # now for CDF of tilt of maximum tau
plt.plot(Untilt, Cdf, 'g')
lower = int(.025 * nboot)
upper = int(.975 * nboot)
plt.axvline(x=Untilt[lower], ymin=0, ymax=1, linewidth=1, linestyle='--')
plt.axvline(x=Untilt[upper], ymin=0, ymax=1, linewidth=1, linestyle='--')
tit = '%i - %i %s' % (Untilt[lower], Untilt[upper], 'Percent Unfolding')
print(tit)
plt.title(tit)
if plot == 0:
pmagplotlib.draw_figs(PLTS)
ans = input('S[a]ve all figures, <Return> to quit \n ')
if ans != 'a':
print("Good bye")
sys.exit()
files = {}
for key in list(PLTS.keys()):
files[key] = ('foldtest_' + '%s' % (key.strip()[:2]) + '.' + fmt)
pmagplotlib.save_plots(PLTS, files)
def main():
"""
NAME
common_mean.py
DESCRIPTION
calculates bootstrap statistics to test for common mean
INPUT FORMAT
takes dec/inc as first two columns in two space delimited files
SYNTAX
common_mean.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, input file
-f2 FILE, optional second file to compare with first file
-dir D I, optional direction to compare with input file
-fmt [svg,jpg,pnd,pdf] set figure format [default is svg]
NOTES
must have either F2 OR dir but not both
"""
d, i, file2 = "", "", ""
fmt, plot = 'svg', 0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-sav' in sys.argv: plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file1 = sys.argv[ind + 1]
if '-f2' in sys.argv:
ind = sys.argv.index('-f2')
file2 = sys.argv[ind + 1]
if '-dir' in sys.argv:
ind = sys.argv.index('-dir')
d = float(sys.argv[ind + 1])
i = float(sys.argv[ind + 2])
D1 = numpy.loadtxt(file1, dtype=numpy.float)
if file2 != "": D2 = numpy.loadtxt(file2, dtype=numpy.float)
#
counter, NumSims = 0, 1000
#
# get bootstrapped means for first data set
#
print("Doing first set of directions, please be patient..")
BDI1 = pmag.di_boot(D1)
#
# convert to cartesian coordinates X1,X2, Y1,Y2 and Z1, Z2
#
if d == "": # repeat for second data set
print("Doing second set of directions, please be patient..")
BDI2 = pmag.di_boot(D2)
else:
BDI2 = []
# set up plots
CDF = {'X': 1, 'Y': 2, 'Z': 3}
pmagplotlib.plot_init(CDF['X'], 4, 4)
pmagplotlib.plot_init(CDF['Y'], 4, 4)
pmagplotlib.plot_init(CDF['Z'], 4, 4)
# draw the cdfs
pmagplotlib.plot_com(CDF, BDI1, BDI2, [d, i])
files = {}
files['X'] = 'CD_X.' + fmt
files['Y'] = 'CD_Y.' + fmt
files['Z'] = 'CD_Z.' + fmt
if plot == 0:
pmagplotlib.draw_figs(CDF)
ans = input("S[a]ve plots, <Return> to quit ")
if ans == "a":
pmagplotlib.save_plots(CDF, files)
else:
sys.exit()
else:
pmagplotlib.save_plots(CDF, files)
sys.exit()
def main():
"""
NAME
dmag_magic2.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols (for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['demag'] = 1 # demag is figure 1
in_file, plot_key, LT = 'magic_measurements.txt', 'er_location_name', "LT-AF-Z"
XLP = ""
norm = 1
LT = 'LT-AF-Z'
units, dmag_key = 'T', 'treatment_ac_field'
plot = 0
fmt = 'svg'
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind+1]
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind+1]
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
plot_by = sys.argv[ind+1]
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
if '-XLP' in sys.argv:
ind = sys.argv.index("-XLP")
XLP = sys.argv[ind+1] # get lab protocol for excluding
if '-LT' in sys.argv:
ind = sys.argv.index("-LT")
LT = 'LT-'+sys.argv[ind+1]+'-Z' # get lab treatment for plotting
if LT == 'LT-T-Z':
units, dmag_key = 'K', 'treatment_temp'
elif LT == 'LT-AF-Z':
units, dmag_key = 'T', 'treatment_ac_field'
elif LT == 'LT-M-Z':
units, dmag_key = 'J', 'treatment_mw_energy'
else:
units = 'U'
data, file_type = pmag.magic_read(in_file)
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['demag'], 5, 5)
print(len(data), ' records read from ', in_file)
#
#
# find desired intensity data
#
#
plotlist, intlist = [], ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
IntMeths = []
FixData = []
for rec in data:
meths = []
methcodes = rec['magic_method_codes'].split(':')
for meth in methcodes:
meths.append(meth.strip())
for key in rec.keys():
if key in intlist and rec[key] != "":
if key not in IntMeths:
IntMeths.append(key)
if rec[plot_key] not in plotlist and LT in meths:
plotlist.append(rec[plot_key])
if 'measurement_flag' not in rec.keys():
rec['measurement_flag'] = 'g'
FixData.append(rec)
plotlist.sort()
if len(IntMeths) == 0:
print('No intensity information found')
sys.exit()
data = FixData
# plot first intensity method found - normalized to initial value anyway - doesn't matter which used
int_key = IntMeths[0]
for plt in plotlist:
if plot == 0:
print(plt, 'plotting by: ', plot_key)
# fish out all the data for this type of plot
PLTblock = pmag.get_dictitem(data, plot_key, plt, 'T')
# fish out all the dmag for this experiment type
PLTblock = pmag.get_dictitem(PLTblock, 'magic_method_codes', LT, 'has')
# get all with this intensity key non-blank
PLTblock = pmag.get_dictitem(PLTblock, int_key, '', 'F')
if XLP != "":
# reject data with XLP in method_code
PLTblock = pmag.get_dictitem(
PLTblock, 'magic_method_codes', XLP, 'not')
if len(PLTblock) > 2:
title = PLTblock[0][plot_key]
spcs = []
for rec in PLTblock:
if rec['er_specimen_name'] not in spcs:
spcs.append(rec['er_specimen_name'])
for spc in spcs:
# plot specimen by specimen
SPCblock = pmag.get_dictitem(
PLTblock, 'er_specimen_name', spc, 'T')
INTblock = []
for rec in SPCblock:
INTblock.append([float(rec[dmag_key]), 0, 0, float(
rec[int_key]), 1, rec['measurement_flag']])
if len(INTblock) > 2:
pmagplotlib.plot_mag(
FIG['demag'], INTblock, title, 0, units, norm)
if plot == 1:
files = {}
for key in FIG.keys():
files[key] = title+'_'+LT+'.'+fmt
pmagplotlib.save_plots(FIG, files)
sys.exit()
else:
pmagplotlib.draw_figs(FIG)
ans = input(
" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
files = {}
for key in FIG.keys():
files[key] = title+'_'+LT+'.'+fmt
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['demag'])
def main():
"""
NAME
histplot.py
DESCRIPTION
makes histograms for data
OPTIONS
-h prints help message and quits
-f input file name
-b binsize
-fmt [svg,png,pdf,eps,jpg] specify format for image, default is svg
-sav save figure and quit
-F output file name, default is hist.fmt
-N don't normalize
-xlab Label of X axis
-ylab Label of Y axis
INPUT FORMAT
single variable
SYNTAX
histplot.py [command line options] [<file]
"""
fname, fmt = "", 'svg'
plot = 0
if '-sav' in sys.argv:
plot = 1
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-f' in sys.argv:
ind = sys.argv.index('-f')
fname = sys.argv[ind + 1]
if '-F' in sys.argv:
ind = sys.argv.index('-F')
outfile = sys.argv[ind + 1]
fmt = ""
else:
outfile = 'hist.' + fmt
print(outfile)
if '-N' in sys.argv:
norm = 0
ylab = 'Number'
else:
norm = 1
ylab = 'Frequency'
if '-b' in sys.argv:
ind = sys.argv.index('-b')
binsize = int(sys.argv[ind + 1])
else:
binsize = 5
if '-xlab' in sys.argv:
ind = sys.argv.index('-xlab')
xlab = sys.argv[ind + 1]
else:
xlab = 'x'
if fname != "":
D = numpy.loadtxt(fname)
else:
print('-I- Trying to read from stdin... <ctrl>-c to quit')
D = numpy.loadtxt(sys.stdin, dtype=numpy.float)
# read in data
#
try:
if not D:
print('-W- No data found')
return
except ValueError:
pass
pmagplotlib.plot_init(1, 8, 7)
Nbins = old_div(len(D), binsize)
# n,bins,patches=plt.hist(D,bins=Nbins,facecolor='white',histtype='step',color='black',normed=norm)
n, bins, patches = plt.hist(D,
bins=Nbins,
facecolor='white',
histtype='step',
color='black',
density=norm)
plt.axis([D.min(), D.max(), 0, n.max() + .1 * n.max()])
plt.xlabel(xlab)
plt.ylabel(ylab)
name = 'N = ' + str(len(D))
plt.title(name)
if plot == 0:
# plt.draw()
# plt.show()
pmagplotlib.draw_figs({1: 'hist'})
p = input('s[a]ve to save plot, [q]uit to exit without saving ')
if p != 'a':
sys.exit()
plt.savefig(outfile)
print('plot saved in ', outfile)
def main():
"""
NAME
find_EI.py
DESCRIPTION
Applies series of assumed flattening factor and "unsquishes" inclinations assuming tangent function.
Finds flattening factor that gives elongation/inclination pair consistent with TK03.
Finds bootstrap confidence bounds
SYNTAX
find_EI.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE specify input file name
-n N specify number of bootstraps - the more the better, but slower!, default is 1000
-sc uses a "site-level" correction to a Fisherian distribution instead
of a "study-level" correction to a TK03-consistent distribution.
Note that many directions (~ 100) are needed for this correction to be reliable.
-fmt [svg,png,eps,pdf..] change plot format, default is svg
-sav saves the figures and quits
INPUT
dec/inc pairs, delimited with space or tabs
OUTPUT
four plots: 1) equal area plot of original directions
2) Elongation/inclination pairs as a function of f, data plus 25 bootstrap samples
3) Cumulative distribution of bootstrapped optimal inclinations plus uncertainties.
Estimate from original data set plotted as solid line
4) Orientation of principle direction through unflattening
NOTE: If distribution does not have a solution, plot labeled: Pathological. Some bootstrap samples may have
valid solutions and those are plotted in the CDFs and E/I plot.
"""
fmt, nb = 'svg', 1000
plot = 0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit() # graceful quit
elif '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
else:
print(main.__doc__)
sys.exit()
if '-n' in sys.argv:
ind = sys.argv.index('-n')
nb = int(sys.argv[ind + 1])
if '-sc' in sys.argv:
site_correction = True
else:
site_correction = False
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-sav' in sys.argv: plot = 1
data = numpy.loadtxt(file)
upper, lower = int(round(.975 * nb)), int(round(.025 * nb))
E, I = [], []
PLTS = {'eq': 1, 'ei': 2, 'cdf': 3, 'v2': 4}
pmagplotlib.plot_init(PLTS['eq'], 6, 6)
pmagplotlib.plot_init(PLTS['ei'], 5, 5)
pmagplotlib.plot_init(PLTS['cdf'], 5, 5)
pmagplotlib.plot_init(PLTS['v2'], 5, 5)
pmagplotlib.plot_eq(PLTS['eq'], data, 'Data')
# this is a problem
#if plot==0:pmagplotlib.draw_figs(PLTS)
ppars = pmag.doprinc(data)
Io = ppars['inc']
n = ppars["N"]
Es, Is, Fs, V2s = pmag.find_f(data)
if site_correction:
Inc, Elong = Is[Es.index(min(Es))], Es[Es.index(min(Es))]
flat_f = Fs[Es.index(min(Es))]
else:
Inc, Elong = Is[-1], Es[-1]
flat_f = Fs[-1]
pmagplotlib.plot_ei(PLTS['ei'], Es, Is, flat_f)
pmagplotlib.plot_v2s(PLTS['v2'], V2s, Is, flat_f)
b = 0
print("Bootstrapping.... be patient")
while b < nb:
bdata = pmag.pseudo(data)
Esb, Isb, Fsb, V2sb = pmag.find_f(bdata)
if b < 25:
pmagplotlib.plot_ei(PLTS['ei'], Esb, Isb, Fsb[-1])
if Esb[-1] != 0:
ppars = pmag.doprinc(bdata)
if site_correction:
I.append(abs(Isb[Esb.index(min(Esb))]))
E.append(Esb[Esb.index(min(Esb))])
else:
I.append(abs(Isb[-1]))
E.append(Esb[-1])
b += 1
if b % 25 == 0: print(b, ' out of ', nb)
I.sort()
E.sort()
Eexp = []
for i in I:
Eexp.append(pmag.EI(i))
if Inc == 0:
title = 'Pathological Distribution: ' + '[%7.1f, %7.1f]' % (I[lower],
I[upper])
else:
title = '%7.1f [%7.1f, %7.1f]' % (Inc, I[lower], I[upper])
pmagplotlib.plot_ei(PLTS['ei'], Eexp, I, 1)
pmagplotlib.plot_cdf(PLTS['cdf'], I, 'Inclinations', 'r', title)
pmagplotlib.plot_vs(PLTS['cdf'], [I[lower], I[upper]], 'b', '--')
pmagplotlib.plot_vs(PLTS['cdf'], [Inc], 'g', '-')
pmagplotlib.plot_vs(PLTS['cdf'], [Io], 'k', '-')
if plot == 0:
print('%7.1f %s %7.1f _ %7.1f ^ %7.1f: %6.4f _ %6.4f ^ %6.4f' %
(Io, " => ", Inc, I[lower], I[upper], Elong, E[lower], E[upper]))
print("Io Inc I_lower, I_upper, Elon, E_lower, E_upper")
pmagplotlib.draw_figs(PLTS)
ans = ""
while ans not in ['q', 'a']:
ans = input("S[a]ve plots - <q> to quit: ")
if ans == 'q':
print("\n Good bye\n")
sys.exit()
files = {}
files['eq'] = 'findEI_eq.' + fmt
files['ei'] = 'findEI_ei.' + fmt
files['cdf'] = 'findEI_cdf.' + fmt
files['v2'] = 'findEI_v2.' + fmt
pmagplotlib.save_plots(PLTS, files)
def main():
"""
NAME
plot_magmap.py
DESCRIPTION
makes a color contour map of desired field model
SYNTAX
plot_magmap.py [command line options]
OPTIONS
-h prints help and quits
-f FILE specify field model file with format: l m g h
-fmt [pdf,eps,svg,png] specify format for output figure (default is png)
-mod [arch3k,cals3k,pfm9k,hfm10k,cals10k.2,shadif14k,cals10k.1b] specify model for 3ka to 1900 CE, default is cals10k
-alt ALT; specify altitude in km, default is sealevel (0)
-age specify date in decimal year, default is 2016
-lon0: 0 longitude for map, default is 0
-el: [D,I,B,Br] specify element for plotting
-cm: [see https://matplotlib.org/users/colormaps.html] specify color map for plotting (default is RdYlBu)
"""
cmap = 'RdYlBu'
date = 2016.
if not Basemap:
print("-W- You must intstall the Basemap module to run plot_magmap.py")
sys.exit()
dir_path = '.'
lincr = 1 # level increment for contours
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if fmt == 'jpg':
print('jpg not a supported option')
print(main.__doc__)
sys.exit()
else:
fmt = 'png'
if '-cm' in sys.argv:
ind = sys.argv.index('-cm')
cmap = sys.argv[ind + 1]
if '-el' in sys.argv:
ind = sys.argv.index('-el')
el = sys.argv[ind + 1]
else:
el = 'B'
if '-alt' in sys.argv:
ind = sys.argv.index('-alt')
alt = sys.argv[ind + 1]
else:
alt = 0
if '-lon0' in sys.argv:
ind = sys.argv.index('-lon0')
lon_0 = float(sys.argv[ind + 1])
else:
lon_0 = 0
if '-mod' in sys.argv:
ind = sys.argv.index('-mod')
mod = sys.argv[ind + 1]
ghfile = ''
elif '-f' in sys.argv:
ind = sys.argv.index('-f')
ghfile = sys.argv[ind + 1]
mod = 'custom'
date = ''
else:
mod, ghfile = 'cals10k', ''
if '-age' in sys.argv:
ind = sys.argv.index('-age')
date = float(sys.argv[ind + 1])
if '-alt' in sys.argv:
ind = sys.argv.index('-alt')
alt = float(sys.argv[ind + 1])
else:
alt = 0
save = pmag.get_flag_arg_from_sys("-sav")
if mod == 'custom':
d = 'Custom'
else:
d = str(date)
Ds, Is, Bs, Brs, lons, lats = pmag.do_mag_map(date,
mod=mod,
lon_0=lon_0,
alt=alt,
file=ghfile)
if el == 'D':
element = Ds
elif el == 'I':
element = Is
elif el == 'B':
element = Bs
elif el == 'Br':
element = Brs
elif el == 'I':
element = Is
else:
print(main.__doc__)
sys.exit()
pmagplotlib.plot_mag_map(1, element, lons, lats, el, lon_0=0, date=date)
if not save:
pmagplotlib.draw_figs({'map': 1})
res = pmagplotlib.save_or_quit()
if res == 'a':
figname = 'igrf' + d + '.' + fmt
print("1 saved in ", figname)
plt.savefig('igrf' + d + '.' + fmt)
sys.exit()
plt.savefig('igrf' + d + '.' + fmt)
print('Figure saved as: ', 'igrf' + d + '.' + fmt)
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
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of FILE and temperature step
-f FILE, specify magic_measurements format file
-T IND, specify temperature step to plot
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
DEFAULTS
FILE: magic_measurements.txt
IND: first
SPEC: step through one by one
"""
cont, FTinit, BTinit, k = "", 0, 0, 0
meas_file = "magic_measurements.txt"
spec = ""
Tind, cont = 0, ""
EXP = ""
fmt = 'svg' # default image type for saving
plot = 0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-i' in sys.argv:
fname = input(
"Input magic_measurements file name? [magic_measurements.txt] ")
if fname != "":
meas_file = fname
if '-e' in sys.argv:
ind = sys.argv.index('-e')
EXP = sys.argv[ind+1]
if '-f' in sys.argv:
ind = sys.argv.index('-f')
meas_file = sys.argv[ind+1]
if '-T' in sys.argv:
ind = sys.argv.index('-T')
Tind = int(sys.argv[ind+1])
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind+1]
if '-sav' in sys.argv:
plot = 1
#
meas_data, file_type = pmag.magic_read(meas_file)
#
# get list of unique experiment names
#
# initialize some variables (a continuation flag, plot initialization flags and the experiment counter
experiment_names = []
for rec in meas_data:
if rec['magic_experiment_name'] not in experiment_names:
experiment_names.append(rec['magic_experiment_name'])
#
# hunt through by experiment name
if EXP != "":
try:
k = experiment_names.index(EXP)
except:
print("Bad experiment name")
sys.exit()
while k < len(experiment_names):
e = experiment_names[k]
if EXP == "":
print(e, k+1, 'out of ', len(experiment_names))
#
# initialize lists of data, susceptibility, temperature, frequency and field
X, T, F, B = [], [], [], []
for rec in meas_data:
methcodes = rec['magic_method_codes']
meths = methcodes.strip().split(':')
if rec['magic_experiment_name'] == e and "LP-X" in meths: # looking for chi measurement
if 'measurement_temp' not in list(rec.keys()):
rec['measurement_temp'] = '300' # set defaults
if 'measurement_freq' not in list(rec.keys()):
rec['measurement_freq'] = '0' # set defaults
if 'measurement_lab_field_ac' not in list(rec.keys()):
rec['measurement_lab_field_ac'] = '0' # set default
if 'measurement_x' in rec.keys():
# backward compatibility
X.append(float(rec['measurement_x']))
else:
# data model 2.5
X.append(float(rec['measurement_chi_volume']))
T.append(float(rec['measurement_temp']))
F.append(float(rec['measurement_freq']))
B.append(float(rec['measurement_lab_field_ac']))
#
# get unique list of Ts,Fs, and Bs
#
Ts, Fs, Bs = [], [], []
for k in range(len(X)): # hunt through all the measurements
if T[k] not in Ts:
Ts.append(T[k]) # append if not in list
if F[k] not in Fs:
Fs.append(F[k])
if B[k] not in Bs:
Bs.append(B[k])
Ts.sort() # sort list of temperatures, frequencies and fields
Fs.sort()
Bs.sort()
if '-x' in sys.argv:
k = len(experiment_names)+1 # just plot the one
else:
k += 1 # increment experiment number
#
# plot chi versus T and F holding B constant
#
plotnum = 1 # initialize plot number to 1
if len(X) > 2: # if there are any data to plot, continue
b = Bs[-1] # keeping field constant and at maximum
XTF = [] # initialize list of chi versus Temp and freq
for f in Fs: # step through frequencies sequentially
XT = [] # initialize list of chi versus temp
for kk in range(len(X)): # hunt through all the data
if F[kk] == f and B[kk] == b: # select data with given freq and field
XT.append([X[kk], T[kk]]) # append to list
XTF.append(XT) # append list to list of frequencies
if len(XT) > 1: # if there are any temperature dependent data
pmagplotlib.plot_init(plotnum, 5, 5) # initialize plot
# call the plotting function
pmagplotlib.plot_xtf(plotnum, XTF, Fs, e, b)
if plot == 0:
pmagplotlib.draw_figs({'fig': plotnum}) # make it visible
plotnum += 1 # increment plot number
f = Fs[0] # set frequency to minimum
XTB = [] # initialize list if chi versus Temp and field
for b in Bs: # step through field values
XT = [] # initial chi versus temp list for this field
for kk in range(len(X)): # hunt through all the data
if F[kk] == f and B[kk] == b: # select data with given freq and field
XT.append([X[kk], T[kk]]) # append to list
XTB.append(XT)
if len(XT) > 1: # if there are any temperature dependent data
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
# call the plotting function
pmagplotlib.plot_xtb(plotnum, XTB, Bs, e, f)
if plot == 0:
pmagplotlib.draw_figs({'fig': plotnum})
plotnum += 1 # increment plot number
if '-i' in sys.argv:
for ind in range(len(Ts)): # print list of temperatures available
print(ind, int(Ts[ind]))
cont = input(
"Enter index of desired temperature step, s[a]ve plots, [return] to quit ")
if cont == 'a':
files = {}
PLTS = {}
for p in range(1, plotnum):
key = str(p)
files[key] = e+'_'+key+'.'+fmt
PLTS[key] = key
pmagplotlib.save_plots(PLTS, files)
cont = input(
"Enter index of desired temperature step, s[a]ve plots, [return] to quit ")
if cont == "":
cont = 'q'
while cont != "q":
if '-i' in sys.argv:
Tind = int(cont) # set temperature index
b = Bs[-1] # set field to max available
XF = [] # initial chi versus frequency list
for kk in range(len(X)): # hunt through the data
if T[kk] == Ts[Tind] and B[kk] == b: # if temperature and field match,
XF.append([X[kk], F[kk]]) # append the data
if len(XF) > 1: # if there are any data to plot
if FTinit == 0: # if not already initialized, initialize plot
# print 'initializing ',plotnum
pmagplotlib.plot_init(plotnum, 5, 5)
FTinit = 1
XFplot = plotnum
plotnum += 1 # increment plotnum
pmagplotlib.plot_xft(XFplot, XF, Ts[Tind], e, b)
if plot == 0:
pmagplotlib.draw_figs({'fig': plotnum})
else:
print(
'\n *** Skipping susceptibitily-frequency plot as a function of temperature *** \n')
f = Fs[0] # set frequency to minimum available
XB = [] # initialize chi versus field list
for kk in range(len(X)): # hunt through the data
# if temperature and field match those desired
if T[kk] == Ts[Tind] and F[kk] == f:
XB.append([X[kk], B[kk]]) # append the data to list
if len(XB) > 4: # if there are any data
if BTinit == 0: # if plot not already initialized
pmagplotlib.plot_init(plotnum, 5, 5) # do it
BTinit = 1
# and call plotting function
pmagplotlib.plot_xbt(plotnum, XB, Ts[Tind], e, f)
if plot == 0:
pmagplotlib.draw_figs({'fig': plotnum})
else:
print(
'Skipping susceptibitily - AC field plot as a function of temperature')
files = {}
PLTS = {}
for p in range(1, plotnum):
key = str(p)
files[key] = e+'_'+key+'.'+fmt
PLTS[key] = p
if '-i' in sys.argv:
# just in case you forgot, print out a new list of temperatures
for ind in range(len(Ts)):
print(ind, int(Ts[ind]))
# ask for new temp
cont = input(
"Enter index of next temperature step, s[a]ve plots, [return] to quit ")
if cont == "":
sys.exit()
if cont == 'a':
pmagplotlib.save_plots(PLTS, files)
cont = input(
"Enter index of desired temperature step, s[a]ve plots, [return] to quit ")
if cont == "":
sys.exit()
elif plot == 0:
ans = input(
"enter s[a]ve to save files, [return] to quit ")
if ans == 'a':
pmagplotlib.save_plots(PLTS, files)
sys.exit()
else:
sys.exit()
else:
pmagplotlib.save_plots(PLTS, files)
sys.exit()
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(
' By default, this information is not available in your measurement file.'
)
print(
' Trying to acquire this information from {}'.format(dir_path))
con = cb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if meas_df is None:
print('-W- No data found in {}'.format(dir_path))
return
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(
plot_key))
# need to take the data directly from the contribution here, to keep
# location/site/sample columns in the measurements table
data = con.tables['measurements'].convert_to_pmag_data_list()
file_type = "measurements"
else:
data, file_type = pmag.magic_read(in_file)
# read in data
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass'
]
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append(
[float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plot_mag(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt != plotlist[
-1]: # if it isn't the last plot, init the next one
pmagplotlib.plot_init(FIG['exp'], 6, 6)
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
plot_geomagia.py
DESCRIPTION
makes a map and VADM plot of geomagia download file
SYNTAX
plot_geomagia.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify geomagia download file
-res [c,l,i,h] specify resolution (crude,low,intermediate,high)
-etp plot the etopo20 topographic mesh
-pad [LAT LON] pad bounding box by LAT/LON (default is [.5 .5] degrees)
-grd SPACE specify grid spacing
-prj [lcc] , specify projection (lcc=lambert conic conformable), default is mercator
-o color ocean blue/land green (default is not)
-d plot details of rivers, boundaries, etc.
-sav save plot and quit quietly
-fmt [png,svg,eps,jpg,pdf] specify format for output, default is pdf
DEFAULTS
resolution: intermediate
saved images are in pdf
"""
dir_path='.'
names,res,proj,locs,padlon,padlat,fancy,gridspace,details=[],'l','lcc','',0,0,0,15,1
Age_bounds=[-5000,2000]
Lat_bounds=[20,45]
Lon_bounds=[15,55]
fmt='pdf'
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index('-f')
sites_file=sys.argv[ind+1]
if '-res' in sys.argv:
ind = sys.argv.index('-res')
res=sys.argv[ind+1]
if '-etp' in sys.argv:fancy=1
if '-o' in sys.argv:ocean=1
if '-d' in sys.argv:details=1
if '-prj' in sys.argv:
ind = sys.argv.index('-prj')
proj=sys.argv[ind+1]
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
verbose=pmagplotlib.verbose
if '-sav' in sys.argv:
verbose=0
if '-pad' in sys.argv:
ind = sys.argv.index('-pad')
padlat=float(sys.argv[ind+1])
padlon=float(sys.argv[ind+2])
if '-grd' in sys.argv:
ind = sys.argv.index('-grd')
gridspace=float(sys.argv[ind+1])
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
sites_file=dir_path+'/'+sites_file
geo_in=open(sites_file,'r').readlines()
Age,AgeErr,Vadm,VadmErr,slats,slons=[],[],[],[],[],[]
for line in geo_in[2:]: # skip top two rows`
rec=line.split()
if float(rec[0])>Age_bounds[0] and float(rec[0])<Age_bounds[1] \
and float(rec[12])>Lat_bounds[0] and float(rec[12]) < Lat_bounds[1]\
and float(rec[13])>Lon_bounds[0] and float(rec[13])<Lon_bounds[1]:
Age.append(float(rec[0]))
AgeErr.append(float(rec[1]))
Vadm.append(10.*float(rec[6]))
VadmErr.append(10.*float(rec[7]))
slats.append(float(rec[12]))
slons.append(float(rec[13]))
FIGS={'map':1,'vadms':2}
pmagplotlib.plot_init(FIGS['map'],6,6)
pmagplotlib.plot_init(FIGS['vadms'],6,6)
Opts={'res':res,'proj':proj,'loc_name':locs,'padlon':padlon,'padlat':padlat,'latmin':numpy.min(slats)-padlat,'latmax':numpy.max(slats)+padlat,'lonmin':numpy.min(slons)-padlon,'lonmax':numpy.max(slons)+padlon,'sym':'ro','boundinglat':0.,'pltgrid':1}
Opts['lon_0']=int(0.5*(numpy.min(slons)+numpy.max(slons)))
Opts['lat_0']=int(0.5*(numpy.min(slats)+numpy.max(slats)))
Opts['gridspace']=gridspace
if details==1:
Opts['details']={'coasts':1,'rivers':0,'states':1,'countries':1,'ocean':1}
else:
Opts['details']={'coasts':1,'rivers':0,'states':0,'countries':0,'ocean':1}
Opts['details']['fancy']=fancy
pmagplotlib.plot_map(FIGS['map'],slats,slons,Opts)
pmagplotlib.plot_xy(FIGS['vadms'],Age,Vadm,sym='bo',xlab='Age (Years CE)',ylab=r'VADM (ZAm$^2$)')
if verbose:pmagplotlib.draw_figs(FIGS)
files={}
for key in list(FIGS.keys()):
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['map']='Map'
titles['vadms']='VADMs'
FIG = pmagplotlib.add_borders(FIGS,titles,black,purple)
pmagplotlib.save_plots(FIGS,files)
elif verbose:
ans=input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.save_plots(FIGS,files)
else:
pmagplotlib.save_plots(FIGS,files)
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.plot_zed(ZED, datablock, angle, s, SIunits) # plot the data
if plot == 0: pmagplotlib.draw_figs(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.plot_zed(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.plot_dir(
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.save_plots(ZED, files)
if ans == 'h':
angle = float(
input(" Declination to project onto horizontal axis? "))
pmagplotlib.plot_zed(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.plot_zed(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.plot_dir(
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.draw_figs(ZED)
else:
print(beg_pca, end_pca)
if beg_pca != "" and end_pca != "":
pmagplotlib.plot_zed(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.plot_dir(
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.save_plots(ZED, files)
def main():
"""
NAME
basemap_magic.py
NB: this program no longer maintained - use plot_map_pts.py for greater functionality
DESCRIPTION
makes a map of locations in er_sites.txt
SYNTAX
basemap_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f SFILE, specify er_sites.txt or pmag_results.txt format file
-res [c,l,i,h] specify resolution (crude,low,intermediate,high)
-etp plot the etopo20 topographic mesh
-pad [LAT LON] pad bounding box by LAT/LON (default is [.5 .5] degrees)
-grd SPACE specify grid spacing
-prj [lcc] , specify projection (lcc=lambert conic conformable), default is mercator
-n print site names (default is not)
-l print location names (default is not)
-o color ocean blue/land green (default is not)
-R don't plot details of rivers
-B don't plot national/state boundaries, etc.
-sav save plot and quit quietly
-fmt [png,svg,eps,jpg,pdf] specify format for output, default is pdf
DEFAULTS
SFILE: 'er_sites.txt'
resolution: intermediate
saved images are in pdf
"""
dir_path = '.'
sites_file = 'er_sites.txt'
ocean = 0
res = 'i'
proj = 'merc'
prn_name = 0
prn_loc = 0
fancy = 0
rivers, boundaries = 0, 0
padlon, padlat, gridspace, details = .5, .5, .5, 1
fmt = 'pdf'
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index('-f')
sites_file = sys.argv[ind+1]
if '-res' in sys.argv:
ind = sys.argv.index('-res')
res = sys.argv[ind+1]
if '-etp' in sys.argv:
fancy = 1
if '-n' in sys.argv:
prn_name = 1
if '-l' in sys.argv:
prn_loc = 1
if '-o' in sys.argv:
ocean = 1
if '-R' in sys.argv:
rivers = 0
if '-B' in sys.argv:
boundaries = 0
if '-prj' in sys.argv:
ind = sys.argv.index('-prj')
proj = sys.argv[ind+1]
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind+1]
verbose = pmagplotlib.verbose
if '-sav' in sys.argv:
verbose = 0
if '-pad' in sys.argv:
ind = sys.argv.index('-pad')
padlat = float(sys.argv[ind+1])
padlon = float(sys.argv[ind+2])
if '-grd' in sys.argv:
ind = sys.argv.index('-grd')
gridspace = float(sys.argv[ind+1])
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind+1]
sites_file = dir_path+'/'+sites_file
location = ""
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
Sites, file_type = pmag.magic_read(sites_file)
if 'results' in file_type:
latkey = 'average_lat'
lonkey = 'average_lon'
namekey = 'pmag_result_name'
lockey = 'er_location_names'
else:
latkey = 'site_lat'
lonkey = 'site_lon'
namekey = 'er_site_name'
lockey = 'er_location_name'
lats, lons = [], []
slats, slons = [], []
names, locs = [], []
for site in Sites:
if prn_loc == 1 and location == "":
location = site['er_location_name']
lats.append(float(site[latkey]))
l = float(site[lonkey])
if l < 0:
l = l+360. # make positive
lons.append(l)
if prn_name == 1:
names.append(site[namekey])
if prn_loc == 1:
locs.append(site[lockey])
for lat in lats:
slats.append(lat)
for lon in lons:
slons.append(lon)
Opts = {'res': res, 'proj': proj, 'loc_name': locs, 'padlon': padlon, 'padlat': padlat, 'latmin': numpy.min(slats)-padlat, 'latmax': numpy.max(
slats)+padlat, 'lonmin': numpy.min(slons)-padlon, 'lonmax': numpy.max(slons)+padlon, 'sym': 'ro', 'boundinglat': 0., 'pltgrid': 1.}
Opts['lon_0'] = 0.5*(numpy.min(slons)+numpy.max(slons))
Opts['lat_0'] = 0.5*(numpy.min(slats)+numpy.max(slats))
Opts['names'] = names
Opts['gridspace'] = gridspace
Opts['details'] = {'coasts': 1, 'rivers': 1,
'states': 1, 'countries': 1, 'ocean': 0}
if ocean == 1:
Opts['details']['ocean'] = 1
if rivers == 1:
Opts['details']['rivers'] = 0
if boundaries == 1:
Opts['details']['states'] = 0
Opts['details']['countries'] = 0
Opts['details']['fancy'] = fancy
pmagplotlib.plot_map(FIG['map'], lats, lons, Opts)
if verbose:
pmagplotlib.draw_figs(FIG)
files = {}
for key in list(FIG.keys()):
files[key] = 'Site_map'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['map'] = 'Site Map'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif verbose:
ans = input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
else:
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
lnp_magic.py
DESCRIPTION
makes equal area projections site by site
from specimen formatted file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
SYNTAX
lnp_magic [command line options]
INPUT
takes magic formatted specimens file
OUPUT
prints site_name n_lines n_planes K alpha95 dec inc R
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is 'specimens.txt', ('pmag_specimens.txt' for legacy data model 2)
-fsa FILE: specify samples file, required to plot by site for data model 3 (otherwise will plot by sample)
default is 'samples.txt'
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is specimen
-fmt [svg,png,jpg] format for plots, default is svg
-sav save plots and quit
-P: do not plot
-F FILE, specify output file of dec, inc, alpha95 data for plotting with plotdi_a and plotdi_e
-exc use criteria in criteria table # NOT IMPLEMENTED
-DM NUMBER MagIC data model (2 or 3, default 3)
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", ".")
data_model = int(float(pmag.get_named_arg("-DM", 3)))
fmt = pmag.get_named_arg("-fmt", 'svg')
if data_model == 2:
in_file = pmag.get_named_arg('-f', 'pmag_specimens.txt')
crit_file = "pmag_criteria.txt"
else:
in_file = pmag.get_named_arg('-f', 'specimens.txt')
samp_file = pmag.get_named_arg('-fsa', 'samples.txt')
crit_file = "criteria.txt"
in_file = pmag.resolve_file_name(in_file, dir_path)
dir_path = os.path.split(in_file)[0]
if data_model == 3:
samp_file = pmag.resolve_file_name(samp_file, dir_path)
if '-crd' in sys.argv:
ind = sys.argv.index("-crd")
crd = sys.argv[ind + 1]
if crd == 's':
coord = "-1"
if crd == 'g':
coord = "0"
if crd == 't':
coord = "100"
else:
coord = "-1"
out_file = pmag.get_named_arg('-F', '')
if out_file:
out = open(dir_path + '/' + out_file, 'w')
if '-P' in sys.argv:
make_plots = 0 # do not plot
else:
make_plots = 1 # do plot
if '-sav' in sys.argv:
plot = 1 # save plots and quit
else:
plot = 0 # show plots intereactively (if make_plots)
#
if data_model == 2:
Specs, file_type = pmag.magic_read(in_file)
if 'specimens' not in file_type:
print('Error opening ', in_file, file_type)
sys.exit()
else:
fnames = {'specimens': in_file, 'samples': samp_file}
con = cb.Contribution(dir_path,
read_tables=['samples', 'specimens'],
custom_filenames=fnames)
con.propagate_name_down('site', 'specimens')
if 'site' in con.tables['specimens'].df.columns:
site_col = 'site'
else:
site_col = 'sample'
tilt_corr_col = "dir_tilt_correction"
mad_col = "dir_mad_free"
alpha95_col = "dir_alpha95"
site_alpha95_col = "dir_alpha95"
dec_col = "dir_dec"
inc_col = "dir_inc"
num_meas_col = "dir_n_measurements"
k_col = "dir_k"
cols = [
site_col, tilt_corr_col, mad_col, alpha95_col, dec_col, inc_col
]
con.tables['specimens'].front_and_backfill(cols)
con.tables['specimens'].df = con.tables['specimens'].df.where(
con.tables['specimens'].df.notnull(), "")
Specs = con.tables['specimens'].convert_to_pmag_data_list()
## using criteria file was never fully implemented
#if '-exc' in sys.argv:
# Crits, file_type = pmag.magic_read(pmag.resolve_file_name(crit_file, dir_path))
# for crit in Crits:
# if mad_col in crit:
# M = float(crit['specimen_mad'])
# if num_meas_col in crit:
# N = float(crit['specimen_n'])
# if site_alpha95_col in crit and 'site' in crit:
# acutoff = float(crit['site_alpha95'])
# if k_col in crit:
# kcutoff = float(crit['site_k'])
#else:
# Crits = ""
sitelist = []
# initialize some variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
M, N, acutoff, kcutoff = 180., 1, 180., 0.
if data_model == 2:
site_col = 'er_site_name'
tilt_corr_col = "specimen_tilt_correction"
mad_col = "specimen_mad"
alpha95_col = 'specimen_alpha95'
dec_col = "specimen_dec"
inc_col = "specimen_inc"
num_meas_col = "specimen_n"
site_alpha95_col = "site_alpha95"
else: # data model 3
pass
for rec in Specs:
if rec[site_col] not in sitelist:
sitelist.append(rec[site_col])
sitelist.sort()
if make_plots == 1:
EQ = {}
EQ['eqarea'] = 1
for site in sitelist:
pmagplotlib.plot_init(EQ['eqarea'], 4, 4)
print(site)
data = []
for spec in Specs:
if tilt_corr_col not in list(spec.keys()):
spec[tilt_corr_col] = '-1' # assume unoriented
if spec[site_col] == site:
if mad_col not in list(spec.keys()) or spec[mad_col] == "":
if alpha95_col in list(
spec.keys()) and spec[alpha95_col] != "":
spec[mad_col] = spec[alpha95_col]
else:
spec[mad_col] = '180'
if not spec[num_meas_col]:
continue
if (float(spec[tilt_corr_col])
== float(coord)) and (float(spec[mad_col]) <= M) and (
float(spec[num_meas_col]) >= N):
rec = {}
for key in list(spec.keys()):
rec[key] = spec[key]
rec["dec"] = float(spec[dec_col])
rec["inc"] = float(spec[inc_col])
rec["tilt_correction"] = spec[tilt_corr_col]
data.append(rec)
if len(data) > 2:
fpars = pmag.dolnp(data, 'specimen_direction_type')
print("Site lines planes kappa a95 dec inc")
print(site, fpars["n_lines"], fpars["n_planes"], fpars["K"],
fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"])
if out_file != "":
if float(fpars["alpha95"]) <= acutoff and float(
fpars["K"]) >= kcutoff:
out.write('%s %s %s\n' %
(fpars["dec"], fpars['inc'], fpars['alpha95']))
print('% tilt correction: ', coord)
if make_plots == 1:
files = {}
files['eqarea'] = site + '_' + crd + '_' + 'eqarea' + '.' + fmt
pmagplotlib.plot_lnp(EQ['eqarea'], site, data, fpars,
'specimen_direction_type')
if plot == 0:
pmagplotlib.draw_figs(EQ)
ans = input(
"s[a]ve plot, [q]uit, <return> to continue:\n ")
if ans == "a":
pmagplotlib.save_plots(EQ, files)
if ans == "q":
sys.exit()
else:
pmagplotlib.save_plots(EQ, files)
else:
print(
'skipping site - not enough data with specified coordinate system'
)
def main():
"""
NAME
polemap_magic.py
DESCRIPTION
makes a map of paleomagnetic poles and a95/dp,dm for pole in a locations table
SYNTAX
polemap_magic.py [command line options]
OPTIONS
-h prints help and quits
-eye ELAT ELON [specify eyeball location], default is 90., 0.
-f FILE location format file, [default is locations.txt]
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-etp plot the etopo20 topographpy data (requires high resolution data set)
-prj PROJ, specify one of the following:
ortho = orthographic
lcc = lambert conformal
moll = molweide
merc = mercator
-sym SYM SIZE: choose a symbol and size, examples:
ro 5 : small red circles
bs 10 : intermediate blue squares
g^ 20 : large green triangles
-ell plot dp/dm or a95 ellipses
-rev RSYM RSIZE : flip reverse poles to normal antipode
-S: plot antipodes of all poles
-age : plot the ages next to the poles
-crd [g,t] : choose coordinate system, default is to plot all location poles
-fmt [pdf, png, eps...] specify output format, default is pdf
-sav save and quit
DEFAULTS
FILE: locations.txt
res: c
prj: ortho
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", ".")
# plot: default is 0, if -sav in sys.argv should be 1
plot = pmag.get_flag_arg_from_sys("-sav", true=1, false=0)
fmt = pmag.get_named_arg("-fmt", "pdf")
res = pmag.get_named_arg("-res", "c")
proj = pmag.get_named_arg("-prj", "ortho")
anti = pmag.get_flag_arg_from_sys("-S", true=1, false=0)
fancy = pmag.get_flag_arg_from_sys("-etp", true=1, false=0)
ell = pmag.get_flag_arg_from_sys("-ell", true=1, false=0)
ages = pmag.get_flag_arg_from_sys("-age", true=1, false=0)
if '-rev' in sys.argv:
flip = 1
ind = sys.argv.index('-rev')
rsym = (sys.argv[ind + 1])
rsize = int(sys.argv[ind + 2])
else:
flip, rsym, rsize = 0, "g^", 8
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = (sys.argv[ind + 1])
size = int(sys.argv[ind + 2])
else:
sym, size = 'ro', 8
if '-eye' in sys.argv:
ind = sys.argv.index('-eye')
lat_0 = float(sys.argv[ind + 1])
lon_0 = float(sys.argv[ind + 2])
else:
lat_0, lon_0 = 90., 0.
crd = pmag.get_named_arg("-crd", "")
coord_dict = {'g': 0, 't': 100}
coord = coord_dict[crd] if crd else ""
results_file = pmag.get_named_arg("-f", "locations.txt")
con = cb.Contribution(dir_path, single_file=results_file)
if not list(con.tables.keys()):
print("-W - Couldn't read in data")
return False, "Couldn't read in data"
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in location file
lats, lons = [], []
Pars = []
dates, rlats, rlons = [], [], []
polarities = []
pole_container = con.tables['locations']
pole_df = pole_container.df
# use individual results
if not pmagplotlib.isServer:
if 'result_type' in pole_df.columns:
pole_df = pole_df[pole_df['result_type'] == 'a']
if 'pole_lat' not in pole_df.columns or 'pole_lon' not in pole_df.columns:
print(
"-W- pole_lat and pole_lon are required columns to run polemap_magic.py"
)
return False, "pole_lat and pole_lon are required columns to run polemap_magic.py"
# use records with pole_lat and pole_lon
cond1, cond2 = pole_df['pole_lat'].notnull(), pole_df['pole_lon'].notnull()
Results = pole_df[cond1 & cond2]
# use tilt correction
if coord and 'dir_tilt_correction' in Results.columns:
Results = Results[Results['dir_tilt_correction'] == coord]
# get location name and average ages
loc_list = Results['location'].values
locations = ":".join(Results['location'].unique())
if 'age' not in Results.columns and 'age_low' in Results.columns and 'age_high' in Results.columns:
Results['age'] = Results['age_low']+0.5 * \
(Results['age_high']-Results['age_low'])
if 'age' in Results.columns and ages == 1:
dates = Results['age'].unique()
if not any(Results.index):
print("-W- No poles could be plotted")
return False, "No poles could be plotted"
# go through rows and extract data
for ind, row in Results.iterrows():
lat, lon = float(row['pole_lat']), float(row['pole_lon'])
if 'dir_polarity' in row:
polarities.append(row['dir_polarity'])
if anti == 1:
lats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360.
lons.append(lon)
elif flip == 0:
lats.append(lat)
lons.append(lon)
elif flip == 1:
if lat < 0:
rlats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360
rlons.append(lon)
else:
lats.append(lat)
lons.append(lon)
ppars = []
ppars.append(lon)
ppars.append(lat)
ell1, ell2 = "", ""
if 'pole_dm' in list(row.keys()) and row['pole_dm']:
ell1 = float(row['pole_dm'])
if 'pole_dp' in list(row.keys()) and row['pole_dp']:
ell2 = float(row['pole_dp'])
if 'pole_alpha95' in list(row.keys()) and row['pole_alpha95']:
ell1, ell2 = float(row['pole_alpha95']), float(row['pole_alpha95'])
if ell1 and ell2:
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
isign = abs(lats[-1]) / lats[-1]
ppars.append(lats[-1] - isign * 90.)
ppars.append(ell2)
ppars.append(lons[-1] + 90.)
ppars.append(0.)
Pars.append(ppars)
locations = locations.strip(':')
Opts = {
'latmin': -90,
'latmax': 90,
'lonmin': 0.,
'lonmax': 360.,
'lat_0': lat_0,
'lon_0': lon_0,
'proj': proj,
'sym': 'bs',
'symsize': 3,
'pltgrid': 0,
'res': res,
'boundinglat': 0.
}
Opts['details'] = {
'coasts': 1,
'rivers': 0,
'states': 0,
'countries': 0,
'ocean': 1,
'fancy': fancy
}
base_Opts = Opts.copy()
# make the base map with a blue triangle at the pole
pmagplotlib.plot_map(FIG['map'], [90.], [0.], Opts)
Opts['pltgrid'] = -1
Opts['sym'] = sym
Opts['symsize'] = size
if len(dates) > 0:
Opts['names'] = dates
if len(lats) > 0:
# add the lats and lons of the poles
pmagplotlib.plot_map(FIG['map'], lats, lons, Opts)
Opts['names'] = []
titles = {}
files = {}
if pmagplotlib.isServer:
# plot each indvidual pole for the server
for ind in range(len(lats)):
lat = lats[ind]
lon = lons[ind]
polarity = ""
if 'polarites' in locals():
polarity = polarities[ind]
polarity = "_" + polarity if polarity else ""
location = loc_list[ind]
FIG["map_{}".format(ind)] = ind + 2
pmagplotlib.plot_init(FIG['map'], 6, 6)
# if with baseOpts, lat/lon don't show
# if with Opts, grid lines don't show
pmagplotlib.plot_map(ind + 2, [90], [0.], base_Opts)
pmagplotlib.plot_map(ind + 2, [lat], [lon], Opts)
titles["map_{}".format(ind)] = location
files["map_{}".format(ind)] = "LO:_{}{}_TY:_POLE_map_.{}".format(
location, polarity, fmt)
# truncate location names so that ultra long filenames are not created
if len(locations) > 50:
locations = locations[:50]
if pmagplotlib.isServer:
# use server plot naming convention
if 'contribution' in con.tables:
# try to get contribution id
con_id = con.tables['contribution'].df.iloc[0].id
files['map'] = 'MC:_{}_TY:_POLE_map.{}'.format(con_id, fmt)
else:
# no contribution id available
files['map'] = 'LO:_' + locations + '_TY:_POLE_map.' + fmt
else:
# use readable naming convention for non-database use
files['map'] = '{}_POLE_map.{}'.format(locations, fmt)
#
if len(rlats) > 0:
Opts['sym'] = rsym
Opts['symsize'] = rsize
# add the lats and lons of the poles
pmagplotlib.plot_map(FIG['map'], rlats, rlons, Opts)
if plot == 0 and not set_env.IS_WIN:
pmagplotlib.draw_figs(FIG)
if ell == 1: # add ellipses if desired.
Opts['details'] = {
'coasts': 0,
'rivers': 0,
'states': 0,
'countries': 0,
'ocean': 0,
'fancy': fancy
}
Opts['pltgrid'] = -1 # turn off meridian replotting
Opts['symsize'] = 2
Opts['sym'] = 'g-'
for ppars in Pars:
if ppars[2] != 0:
PTS = pmagplotlib.plot_ell(FIG['map'], ppars, 'g.', 0, 0)
elats, elons = [], []
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
# make the base map with a blue triangle at the pole
pmagplotlib.plot_map(FIG['map'], elats, elons, Opts)
if plot == 0 and not set_env.IS_WIN:
pmagplotlib.draw_figs(FIG)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles['map'] = 'LO:_' + locations + '_POLE_map'
if 'contribution' in con.tables:
con_id = con.tables['contribution'].df.iloc[0].id
titles['map'] = "MagIC contribution {} all locations".format(
con_id)
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
else:
print("Good bye")
else:
pmagplotlib.save_plots(FIG, files)
return True, files
def main():
"""
NAME
foldtest_magic.py
DESCRIPTION
does a fold test (Tauxe, 2010) on data
INPUT FORMAT
pmag_specimens format file, er_samples.txt format file (for bedding)
SYNTAX
foldtest_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f sites formatted file [default for 3.0 is sites.txt, for 2.5, pmag_sites.txt]
-fsa samples formatted file
-fsi sites formatted file
-exc use criteria to set acceptance criteria (supported only for data model 3)
-n NB, set number of bootstraps, default is 1000
-b MIN, MAX, set bounds for untilting, default is -10, 150
-fmt FMT, specify format - default is svg
-sav saves plots and quits
-DM NUM MagIC data model number (2 or 3, default 3)
OUTPUT
Geographic: is an equal area projection of the input data in
original coordinates
Stratigraphic: is an equal area projection of the input data in
tilt adjusted coordinates
% Untilting: The dashed (red) curves are representative plots of
maximum eigenvalue (tau_1) as a function of untilting
The solid line is the cumulative distribution of the
% Untilting required to maximize tau for all the
bootstrapped data sets. The dashed vertical lines
are 95% confidence bounds on the % untilting that yields
the most clustered result (maximum tau_1).
Command line: prints out the bootstrapped iterations and
finally the confidence bounds on optimum untilting.
If the 95% conf bounds include 0, then a pre-tilt magnetization is indicated
If the 95% conf bounds include 100, then a post-tilt magnetization is indicated
If the 95% conf bounds exclude both 0 and 100, syn-tilt magnetization is
possible as is vertical axis rotation or other pathologies
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
kappa = 0
dir_path = pmag.get_named_arg("-WD", ".")
nboot = int(float(pmag.get_named_arg("-n", 1000))) # number of bootstraps
fmt = pmag.get_named_arg("-fmt", "svg")
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
if data_model_num == 3:
infile = pmag.get_named_arg("-f", 'sites.txt')
orfile = 'samples.txt'
site_col = 'site'
dec_col = 'dir_dec'
inc_col = 'dir_inc'
tilt_col = 'dir_tilt_correction'
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
crit_col = 'criterion'
critfile = 'criteria.txt'
else:
infile = pmag.get_named_arg("-f", 'pmag_sites.txt')
orfile = 'er_samples.txt'
site_col = 'er_site_name'
dec_col = 'site_dec'
inc_col = 'site_inc'
tilt_col = 'site_tilt_correction'
dipkey, azkey = 'sample_bed_dip', 'sample_bed_dip_direction'
crit_col = 'pmag_criteria_code'
critfile = 'pmag_criteria.txt'
if '-sav' in sys.argv:
plot = 1
else:
plot = 0
if '-b' in sys.argv:
ind = sys.argv.index('-b')
untilt_min = int(sys.argv[ind+1])
untilt_max = int(sys.argv[ind+2])
else:
untilt_min, untilt_max = -10, 150
if '-fsa' in sys.argv:
orfile = pmag.get_named_arg("-fsa", "")
elif '-fsi' in sys.argv:
orfile = pmag.get_named_arg("-fsi", "")
if data_model_num == 3:
dipkey, azkey = 'bed_dip', 'bed_dip_direction'
else:
dipkey, azkey = 'site_bed_dip', 'site_bed_dip_direction'
else:
if data_model_num == 3:
orfile = 'sites.txt'
else:
orfile = 'pmag_sites.txt'
orfile = pmag.resolve_file_name(orfile, dir_path)
infile = pmag.resolve_file_name(infile, dir_path)
critfile = pmag.resolve_file_name(critfile, dir_path)
df = pd.read_csv(infile, sep='\t', header=1)
# keep only records with tilt_col
data = df.copy()
data = data[data[tilt_col].notnull()]
data = data.where(data.notnull(), "")
# turn into pmag data list
data = list(data.T.apply(dict))
# get orientation data
if data_model_num == 3:
# often orientation will be in infile (sites table)
if os.path.split(orfile)[1] == os.path.split(infile)[1]:
ordata = df[df[azkey].notnull()]
ordata = ordata[ordata[dipkey].notnull()]
ordata = list(ordata.T.apply(dict))
# sometimes orientation might be in a sample file instead
else:
ordata = pd.read_csv(orfile, sep='\t', header=1)
ordata = list(ordata.T.apply(dict))
else:
ordata, file_type = pmag.magic_read(orfile)
if '-exc' in sys.argv:
crits, file_type = pmag.magic_read(critfile)
SiteCrits = []
for crit in crits:
if crit[crit_col] == "DE-SITE":
SiteCrits.append(crit)
#break
# get to work
#
PLTS = {'geo': 1, 'strat': 2, 'taus': 3} # make plot dictionary
if not set_env.IS_WIN:
pmagplotlib.plot_init(PLTS['geo'], 5, 5)
pmagplotlib.plot_init(PLTS['strat'], 5, 5)
pmagplotlib.plot_init(PLTS['taus'], 5, 5)
if data_model_num == 2:
GEOrecs = pmag.get_dictitem(data, tilt_col, '0', 'T')
else:
GEOrecs = data
if len(GEOrecs) > 0: # have some geographic data
num_dropped = 0
DIDDs = [] # set up list for dec inc dip_direction, dip
for rec in GEOrecs: # parse data
dip, dip_dir = 0, -1
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
orecs = pmag.get_dictitem(
ordata, site_col, rec[site_col], 'T')
if len(orecs) > 0:
if orecs[0][azkey] != "":
dip_dir = float(orecs[0][azkey])
if orecs[0][dipkey] != "":
dip = float(orecs[0][dipkey])
if dip != 0 and dip_dir != -1:
if '-exc' in sys.argv:
keep = 1
for site_crit in SiteCrits:
crit_name = site_crit['table_column'].split('.')[1]
if crit_name and crit_name in rec.keys() and rec[crit_name]:
# get the correct operation (<, >=, =, etc.)
op = OPS[site_crit['criterion_operation']]
# then make sure the site record passes
if op(float(rec[crit_name]), float(site_crit['criterion_value'])):
keep = 0
if keep == 1:
DIDDs.append([Dec, Inc, dip_dir, dip])
else:
num_dropped += 1
else:
DIDDs.append([Dec, Inc, dip_dir, dip])
if num_dropped:
print("-W- Dropped {} records because each failed one or more criteria".format(num_dropped))
else:
print('no geographic directional data found')
sys.exit()
pmagplotlib.plot_eq(PLTS['geo'], DIDDs, 'Geographic')
data = np.array(DIDDs)
D, I = pmag.dotilt_V(data)
TCs = np.array([D, I]).transpose()
pmagplotlib.plot_eq(PLTS['strat'], TCs, 'Stratigraphic')
if plot == 0:
pmagplotlib.draw_figs(PLTS)
Percs = list(range(untilt_min, untilt_max))
Cdf, Untilt = [], []
plt.figure(num=PLTS['taus'])
print('doing ', nboot, ' iterations...please be patient.....')
for n in range(nboot): # do bootstrap data sets - plot first 25 as dashed red line
if n % 50 == 0:
print(n)
Taus = [] # set up lists for taus
PDs = pmag.pseudo(DIDDs)
if kappa != 0:
for k in range(len(PDs)):
d, i = pmag.fshdev(kappa)
dipdir, dip = pmag.dodirot(d, i, PDs[k][2], PDs[k][3])
PDs[k][2] = dipdir
PDs[k][3] = dip
for perc in Percs:
tilt = np.array([1., 1., 1., 0.01*perc])
D, I = pmag.dotilt_V(PDs*tilt)
TCs = np.array([D, I]).transpose()
ppars = pmag.doprinc(TCs) # get principal directions
Taus.append(ppars['tau1'])
if n < 25:
plt.plot(Percs, Taus, 'r--')
# tilt that gives maximum tau
Untilt.append(Percs[Taus.index(np.max(Taus))])
Cdf.append(float(n) / float(nboot))
plt.plot(Percs, Taus, 'k')
plt.xlabel('% Untilting')
plt.ylabel('tau_1 (red), CDF (green)')
Untilt.sort() # now for CDF of tilt of maximum tau
plt.plot(Untilt, Cdf, 'g')
lower = int(.025*nboot)
upper = int(.975*nboot)
plt.axvline(x=Untilt[lower], ymin=0, ymax=1, linewidth=1, linestyle='--')
plt.axvline(x=Untilt[upper], ymin=0, ymax=1, linewidth=1, linestyle='--')
tit = '%i - %i %s' % (Untilt[lower], Untilt[upper], 'Percent Unfolding')
print(tit)
plt.title(tit)
if plot == 0:
pmagplotlib.draw_figs(PLTS)
ans = input('S[a]ve all figures, <Return> to quit \n ')
if ans != 'a':
print("Good bye")
sys.exit()
files = {}
for key in list(PLTS.keys()):
files[key] = ('foldtest_'+'%s' % (key.strip()[:2])+'.'+fmt)
pmagplotlib.save_plots(PLTS, files)
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(' By default, this information is not available in your measurement file.')
print(' Trying to acquire this information from {}'.format(dir_path))
con = cb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if meas_df is None:
print('-W- No data found in {}'.format(dir_path))
return
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(plot_key))
# need to take the data directly from the contribution here, to keep
# location/site/sample columns in the measurements table
data = con.tables['measurements'].convert_to_pmag_data_list()
file_type = "measurements"
else:
data, file_type = pmag.magic_read(in_file)
# read in data
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append([float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plot_mag(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt != plotlist[-1]: # if it isn't the last plot, init the next one
pmagplotlib.plot_init(FIG['exp'], 6, 6)
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a pmag_results table
SYNTAX
vgpmap_magic.py [command line options]
OPTIONS
-h prints help and quits
-eye ELAT ELON [specify eyeball location], default is 90., 0.
-f FILE pmag_results format file, [default is pmag_results.txt]
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-etp plot the etopo20 topographpy data (requires high resolution data set)
-prj PROJ, specify one of the following:
ortho = orthographic
lcc = lambert conformal
moll = molweide
merc = mercator
-sym SYM SIZE: choose a symbol and size, examples:
ro 5 : small red circles
bs 10 : intermediate blue squares
g^ 20 : large green triangles
-ell plot dp/dm or a95 ellipses
-rev RSYM RSIZE : flip reverse poles to normal antipode
-S: plot antipodes of all poles
-age : plot the ages next to the poles
-crd [g,t] : choose coordinate system, default is to plot all site VGPs
-fmt [pdf, png, eps...] specify output format, default is pdf
-sav save and quit
DEFAULTS
FILE: pmag_results.txt
res: c
prj: ortho
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
dir_path = '.'
res, ages = 'c', 0
plot = 0
proj = 'ortho'
results_file = 'pmag_results.txt'
ell, flip = 0, 0
lat_0, lon_0 = 90., 0.
fmt = 'pdf'
sym, size = 'ro', 8
rsym, rsize = 'g^', 8
anti = 0
fancy = 0
coord = ""
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind+1]
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-S' in sys.argv:
anti = 1
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind+1]
if '-sav' in sys.argv:
plot = 1
if '-res' in sys.argv:
ind = sys.argv.index('-res')
res = sys.argv[ind+1]
if '-etp' in sys.argv:
fancy = 1
if '-prj' in sys.argv:
ind = sys.argv.index('-prj')
proj = sys.argv[ind+1]
if '-rev' in sys.argv:
flip = 1
ind = sys.argv.index('-rev')
rsym = (sys.argv[ind+1])
rsize = int(sys.argv[ind+2])
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = (sys.argv[ind+1])
size = int(sys.argv[ind+2])
if '-eye' in sys.argv:
ind = sys.argv.index('-eye')
lat_0 = float(sys.argv[ind+1])
lon_0 = float(sys.argv[ind+2])
if '-ell' in sys.argv:
ell = 1
if '-age' in sys.argv:
ages = 1
if '-f' in sys.argv:
ind = sys.argv.index('-f')
results_file = sys.argv[ind+1]
if '-crd' in sys.argv:
ind = sys.argv.index('-crd')
crd = sys.argv[ind+1]
if crd == 'g':
coord = '0'
if crd == 't':
coord = '100'
results_file = dir_path+'/'+results_file
data, file_type = pmag.magic_read(results_file)
if file_type != 'pmag_results':
print("bad results file")
sys.exit()
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons, dp, dm, a95 = [], [], [], [], []
Pars = []
dates, rlats, rlons = [], [], []
if 'data_type' in data[0].keys():
# get all site level data
Results = pmag.get_dictitem(data, 'data_type', 'i', 'T')
else:
Results = data
# get all non-blank latitudes
Results = pmag.get_dictitem(Results, 'vgp_lat', '', 'F')
# get all non-blank longitudes
Results = pmag.get_dictitem(Results, 'vgp_lon', '', 'F')
if coord != "":
# get specified coordinate system
Results = pmag.get_dictitem(Results, 'tilt_correction', coord, 'T')
location = ""
for rec in Results:
if rec['er_location_names'] not in location:
location = location+':'+rec['er_location_names']
if 'average_age' in rec.keys() and rec['average_age'] != "" and ages == 1:
dates.append(rec['average_age'])
lat = float(rec['vgp_lat'])
lon = float(rec['vgp_lon'])
if flip == 0:
lats.append(lat)
lons.append(lon)
elif flip == 1:
if lat < 0:
rlats.append(-lat)
lon = lon+180.
if lon > 360:
lon = lon-360.
rlons.append(lon)
else:
lats.append(lat)
lons.append(lon)
elif anti == 1:
lats.append(-lat)
lon = lon+180.
if lon > 360:
lon = lon-360.
lons.append(lon)
ppars = []
ppars.append(lon)
ppars.append(lat)
ell1, ell2 = "", ""
if 'vgp_dm' in rec.keys() and rec['vgp_dm'] != "":
ell1 = float(rec['vgp_dm'])
if 'vgp_dp' in rec.keys() and rec['vgp_dp'] != "":
ell2 = float(rec['vgp_dp'])
if 'vgp_alpha95' in rec.keys() and rec['vgp_alpha95'] != "":
ell1, ell2 = float(rec['vgp_alpha95']), float(rec['vgp_alpha95'])
if ell1 != "" and ell2 != "":
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
isign = abs(lats[-1])/lats[-1]
ppars.append(lats[-1]-isign*90.)
ppars.append(ell2)
ppars.append(lons[-1]+90.)
ppars.append(0.)
Pars.append(ppars)
location = location.strip(':')
Opts = {'latmin': -90, 'latmax': 90, 'lonmin': 0., 'lonmax': 360., 'lat_0': lat_0, 'lon_0': lon_0,
'proj': proj, 'sym': 'bs', 'symsize': 3, 'pltgrid': 0, 'res': res, 'boundinglat': 0.}
Opts['details'] = {'coasts': 1, 'rivers': 0, 'states': 0,
'countries': 0, 'ocean': 1, 'fancy': fancy}
# make the base map with a blue triangle at the pole`
pmagplotlib.plot_map(FIG['map'], [90.], [0.], Opts)
Opts['pltgrid'] = -1
Opts['sym'] = sym
Opts['symsize'] = size
if len(dates) > 0:
Opts['names'] = dates
if len(lats) > 0:
# add the lats and lons of the poles
pmagplotlib.plot_map(FIG['map'], lats, lons, Opts)
Opts['names'] = []
if len(rlats) > 0:
Opts['sym'] = rsym
Opts['symsize'] = rsize
# add the lats and lons of the poles
pmagplotlib.plot_map(FIG['map'], rlats, rlons, Opts)
if plot == 0:
pmagplotlib.draw_figs(FIG)
if ell == 1: # add ellipses if desired.
Opts['details'] = {'coasts': 0, 'rivers': 0,
'states': 0, 'countries': 0, 'ocean': 0}
Opts['pltgrid'] = -1 # turn off meridian replotting
Opts['symsize'] = 2
Opts['sym'] = 'g-'
for ppars in Pars:
if ppars[2] != 0:
PTS = pmagplotlib.plot_ell(FIG['map'], ppars, 'g.', 0, 0)
elats, elons = [], []
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
# make the base map with a blue triangle at the pole`
pmagplotlib.plot_map(FIG['map'], elats, elons, Opts)
if plot == 0:
pmagplotlib.draw_figs(FIG)
files = {}
for key in FIG.keys():
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_'+location+'_VGP_map.'+fmt
else: # use more readable plot naming convention
files[key] = '{}_VGP_map.{}'.format(
location.replace(' ', '_'), fmt)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'LO:_'+location+'_VGP_map'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
else:
print("Good bye")
sys.exit()
else:
pmagplotlib.save_plots(FIG, files)
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
find_EI.py
DESCRIPTION
Applies series of assumed flattening factor and "unsquishes" inclinations assuming tangent function.
Finds flattening factor that gives elongation/inclination pair consistent with TK03.
Finds bootstrap confidence bounds
SYNTAX
find_EI.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE specify input file name
-n N specify number of bootstraps - the more the better, but slower!, default is 1000
-sc uses a "site-level" correction to a Fisherian distribution instead
of a "study-level" correction to a TK03-consistent distribution.
Note that many directions (~ 100) are needed for this correction to be reliable.
-fmt [svg,png,eps,pdf..] change plot format, default is svg
-sav saves the figures and quits
INPUT
dec/inc pairs, delimited with space or tabs
OUTPUT
four plots: 1) equal area plot of original directions
2) Elongation/inclination pairs as a function of f, data plus 25 bootstrap samples
3) Cumulative distribution of bootstrapped optimal inclinations plus uncertainties.
Estimate from original data set plotted as solid line
4) Orientation of principle direction through unflattening
NOTE: If distribution does not have a solution, plot labeled: Pathological. Some bootstrap samples may have
valid solutions and those are plotted in the CDFs and E/I plot.
"""
fmt,nb='svg',1000
plot=0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit() # graceful quit
elif '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
else:
print(main.__doc__)
sys.exit()
if '-n' in sys.argv:
ind=sys.argv.index('-n')
nb=int(sys.argv[ind+1])
if '-sc' in sys.argv:
site_correction = True
else:
site_correction = False
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-sav' in sys.argv:plot=1
data=numpy.loadtxt(file)
upper,lower=int(round(.975*nb)),int(round(.025*nb))
E,I=[],[]
PLTS={'eq':1,'ei':2,'cdf':3,'v2':4}
pmagplotlib.plot_init(PLTS['eq'],6,6)
pmagplotlib.plot_init(PLTS['ei'],5,5)
pmagplotlib.plot_init(PLTS['cdf'],5,5)
pmagplotlib.plot_init(PLTS['v2'],5,5)
pmagplotlib.plot_eq(PLTS['eq'],data,'Data')
# this is a problem
#if plot==0:pmagplotlib.draw_figs(PLTS)
ppars=pmag.doprinc(data)
Io=ppars['inc']
n=ppars["N"]
Es,Is,Fs,V2s=pmag.find_f(data)
if site_correction:
Inc,Elong=Is[Es.index(min(Es))],Es[Es.index(min(Es))]
flat_f = Fs[Es.index(min(Es))]
else:
Inc,Elong=Is[-1],Es[-1]
flat_f = Fs[-1]
pmagplotlib.plot_ei(PLTS['ei'],Es,Is,flat_f)
pmagplotlib.plot_v2s(PLTS['v2'],V2s,Is,flat_f)
b=0
print("Bootstrapping.... be patient")
while b<nb:
bdata=pmag.pseudo(data)
Esb,Isb,Fsb,V2sb=pmag.find_f(bdata)
if b<25:
pmagplotlib.plot_ei(PLTS['ei'],Esb,Isb,Fsb[-1])
if Esb[-1]!=0:
ppars=pmag.doprinc(bdata)
if site_correction:
I.append(abs(Isb[Esb.index(min(Esb))]))
E.append(Esb[Esb.index(min(Esb))])
else:
I.append(abs(Isb[-1]))
E.append(Esb[-1])
b+=1
if b%25==0:print(b,' out of ',nb)
I.sort()
E.sort()
Eexp=[]
for i in I:
Eexp.append(pmag.EI(i))
if Inc==0:
title= 'Pathological Distribution: '+'[%7.1f, %7.1f]' %(I[lower],I[upper])
else:
title= '%7.1f [%7.1f, %7.1f]' %( Inc, I[lower],I[upper])
pmagplotlib.plot_ei(PLTS['ei'],Eexp,I,1)
pmagplotlib.plot_cdf(PLTS['cdf'],I,'Inclinations','r',title)
pmagplotlib.plot_vs(PLTS['cdf'],[I[lower],I[upper]],'b','--')
pmagplotlib.plot_vs(PLTS['cdf'],[Inc],'g','-')
pmagplotlib.plot_vs(PLTS['cdf'],[Io],'k','-')
if plot==0:
print('%7.1f %s %7.1f _ %7.1f ^ %7.1f: %6.4f _ %6.4f ^ %6.4f' %(Io, " => ", Inc, I[lower],I[upper], Elong, E[lower],E[upper]))
print("Io Inc I_lower, I_upper, Elon, E_lower, E_upper")
pmagplotlib.draw_figs(PLTS)
ans = ""
while ans not in ['q', 'a']:
ans= input("S[a]ve plots - <q> to quit: ")
if ans=='q':
print("\n Good bye\n")
sys.exit()
files={}
files['eq']='findEI_eq.'+fmt
files['ei']='findEI_ei.'+fmt
files['cdf']='findEI_cdf.'+fmt
files['v2']='findEI_v2.'+fmt
pmagplotlib.save_plots(PLTS,files)
def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input file, default is measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
plots = 0
pltspec = ""
verbose = pmagplotlib.verbose
#version_num = pmag.get_version()
dir_path = pmag.get_named_arg('-WD', '.')
dir_path = os.path.realpath(dir_path)
meas_file = pmag.get_named_arg('-f', 'measurements.txt')
fmt = pmag.get_named_arg('-fmt', 'png')
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind + 1]
verbose = 0
plots = 1
#
con = cb.Contribution(dir_path,
read_tables=['measurements'],
custom_filenames={'measurements': meas_file})
# get as much name data as possible (used for naming plots)
if not 'measurements' in con.tables:
print("-W- No measurement file found")
return
con.propagate_location_to_measurements()
if 'measurements' not in con.tables:
print(main.__doc__)
print('bad file')
sys.exit()
meas_container = con.tables['measurements']
#meas_df = meas_container.df
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs = []
HDD = {}
HDD['hyst'] = 1
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
#
# get list of unique experiment names and specimen names
#
sids = []
hyst_data = meas_container.get_records_for_code('LP-HYS')
#experiment_names = hyst_data['experiment_name'].unique()
if not len(hyst_data):
print("-W- No hysteresis data found")
return
sids = hyst_data['specimen'].unique()
# if 'treat_temp' is provided, use that value, otherwise assume 300
hyst_data['treat_temp'].where(hyst_data['treat_temp'].notnull(),
'300',
inplace=True)
# start at first specimen, or at provided specimen ('-spc')
k = 0
if pltspec != "":
try:
print(sids)
k = list(sids).index(pltspec)
except ValueError:
print('-W- No specimen named: {}.'.format(pltspec))
print('-W- Please provide a valid specimen name')
return
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
while k < len(sids):
locname, site, sample, synth = '', '', '', ''
s = sids[k]
if verbose:
print(s, k + 1, 'out of ', len(sids))
# B, M for hysteresis, Bdcd,Mdcd for irm-dcd data
B, M = [], []
# get all measurements for this specimen
spec = hyst_data[hyst_data['specimen'] == s]
# get names
if 'location' in spec:
locname = spec['location'].iloc[0]
if 'site' in spec:
site = spec['sample'].iloc[0]
if 'sample' in spec:
sample = spec['sample'].iloc[0]
# get all records with non-blank values in any intlist column
# find intensity data
for int_column in intlist:
if int_column in spec.columns:
int_col = int_column
break
meas_data = spec[spec[int_column].notnull()]
if len(meas_data) == 0:
break
#
c = ['k-', 'b-', 'c-', 'g-', 'm-', 'r-', 'y-']
cnum = 0
Temps = []
xlab, ylab, title = '', '', ''
Temps = meas_data['treat_temp'].unique()
for t in Temps:
print('working on t: ', t)
t_data = meas_data[meas_data['treat_temp'] == t]
m = int_col
B = t_data['meas_field_dc'].astype(float).values
M = t_data[m].astype(float).values
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = 'Field (T)'
ylab = m
title = 'Hysteresis: ' + s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD['hyst'])
pmagplotlib.plot_xy(HDD['hyst'],
B,
M,
sym=c[cnum],
xlab=xlab,
ylab=ylab,
title=title)
pmagplotlib.plot_xy(HDD['hyst'],
[1.1 * B.min(), 1.1 * B.max()], [0, 0],
sym='k-',
xlab=xlab,
ylab=ylab,
title=title)
pmagplotlib.plot_xy(HDD['hyst'], [0, 0],
[1.1 * M.min(), 1.1 * M.max()],
sym='k-',
xlab=xlab,
ylab=ylab,
title=title)
if verbose and not set_env.IS_WIN:
pmagplotlib.draw_figs(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
for key in list(HDD.keys()):
if pmagplotlib.isServer:
if synth == '':
files[
key] = "LO:_" + locname + '_SI:_' + site + '_SA:_' + sample + '_SP:_' + s + '_TY:_' + key + '_.' + fmt
else:
files[
key] = 'SY:_' + synth + '_TY:_' + key + '_.' + fmt
else:
if synth == '':
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
else:
files[key] = "{}_{}.{}".format(synth, key, fmt)
pmagplotlib.save_plots(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.draw_figs(HDD)
ans = input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n "
)
if ans == "a":
files = {}
for key in list(HDD.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[
key] = "LO:_" + locname + '_SI:_' + site + '_SA:_' + sample + '_SP:_' + s + '_TY:_' + key + '_.' + fmt
else: # use more readable plot naming convention
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
pmagplotlib.save_plots(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1
def main():
"""
NAME
lnp_magic.py
DESCRIPTION
makes equal area projections site by site
from specimen formatted file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
SYNTAX
lnp_magic [command line options]
INPUT
takes magic formatted specimens file
OUPUT
prints site_name n_lines n_planes K alpha95 dec inc R
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is 'specimens.txt', ('pmag_specimens.txt' for legacy data model 2)
-fsa FILE: specify samples file, required to plot by site for data model 3 (otherwise will plot by sample)
default is 'samples.txt'
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is specimen
-fmt [svg,png,jpg] format for plots, default is svg
-sav save plots and quit
-P: do not plot
-F FILE, specify output file of dec, inc, alpha95 data for plotting with plotdi_a and plotdi_e
-exc use criteria in criteria table # NOT IMPLEMENTED
-DM NUMBER MagIC data model (2 or 3, default 3)
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", ".")
data_model = int(float(pmag.get_named_arg("-DM", 3)))
fmt = pmag.get_named_arg("-fmt", 'svg')
if data_model == 2:
in_file = pmag.get_named_arg('-f', 'pmag_specimens.txt')
crit_file = "pmag_criteria.txt"
else:
in_file = pmag.get_named_arg('-f', 'specimens.txt')
samp_file = pmag.get_named_arg('-fsa', 'samples.txt')
crit_file = "criteria.txt"
in_file = pmag.resolve_file_name(in_file, dir_path)
dir_path = os.path.split(in_file)[0]
if data_model == 3:
samp_file = pmag.resolve_file_name(samp_file, dir_path)
if '-crd' in sys.argv:
ind = sys.argv.index("-crd")
crd = sys.argv[ind+1]
if crd == 's':
coord = "-1"
if crd == 'g':
coord = "0"
if crd == 't':
coord = "100"
else:
coord = "-1"
out_file = pmag.get_named_arg('-F', '')
if out_file:
out = open(dir_path+'/'+out_file, 'w')
if '-P' in sys.argv:
make_plots = 0 # do not plot
else:
make_plots = 1 # do plot
if '-sav' in sys.argv:
plot = 1 # save plots and quit
else:
plot = 0 # show plots intereactively (if make_plots)
#
if data_model == 2:
Specs, file_type = pmag.magic_read(in_file)
if 'specimens' not in file_type:
print('Error opening ', in_file, file_type)
sys.exit()
else:
fnames = {'specimens': in_file, 'samples': samp_file}
con = cb.Contribution(dir_path, read_tables=['samples', 'specimens'],
custom_filenames=fnames)
con.propagate_name_down('site', 'specimens')
if 'site' in con.tables['specimens'].df.columns:
site_col = 'site'
else:
site_col = 'sample'
tilt_corr_col = "dir_tilt_correction"
mad_col = "dir_mad_free"
alpha95_col = "dir_alpha95"
site_alpha95_col = "dir_alpha95"
dec_col = "dir_dec"
inc_col = "dir_inc"
num_meas_col = "dir_n_measurements"
k_col = "dir_k"
cols = [site_col, tilt_corr_col, mad_col, alpha95_col, dec_col, inc_col]
con.tables['specimens'].front_and_backfill(cols)
con.tables['specimens'].df = con.tables['specimens'].df.where(con.tables['specimens'].df.notnull(), "")
Specs = con.tables['specimens'].convert_to_pmag_data_list()
## using criteria file was never fully implemented
#if '-exc' in sys.argv:
# Crits, file_type = pmag.magic_read(pmag.resolve_file_name(crit_file, dir_path))
# for crit in Crits:
# if mad_col in crit:
# M = float(crit['specimen_mad'])
# if num_meas_col in crit:
# N = float(crit['specimen_n'])
# if site_alpha95_col in crit and 'site' in crit:
# acutoff = float(crit['site_alpha95'])
# if k_col in crit:
# kcutoff = float(crit['site_k'])
#else:
# Crits = ""
sitelist = []
# initialize some variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
M, N, acutoff, kcutoff = 180., 1, 180., 0.
if data_model == 2:
site_col = 'er_site_name'
tilt_corr_col = "specimen_tilt_correction"
mad_col = "specimen_mad"
alpha95_col = 'specimen_alpha95'
dec_col = "specimen_dec"
inc_col = "specimen_inc"
num_meas_col = "specimen_n"
site_alpha95_col = "site_alpha95"
else: # data model 3
pass
for rec in Specs:
if rec[site_col] not in sitelist:
sitelist.append(rec[site_col])
sitelist.sort()
if make_plots == 1:
EQ = {}
EQ['eqarea'] = 1
for site in sitelist:
pmagplotlib.plot_init(EQ['eqarea'], 4, 4)
print(site)
data = []
for spec in Specs:
if tilt_corr_col not in list(spec.keys()):
spec[tilt_corr_col] = '-1' # assume unoriented
if spec[site_col] == site:
if mad_col not in list(spec.keys()) or spec[mad_col] == "":
if alpha95_col in list(spec.keys()) and spec[alpha95_col] != "":
spec[mad_col] = spec[alpha95_col]
else:
spec[mad_col] = '180'
if not spec[num_meas_col]:
continue
if (float(spec[tilt_corr_col]) == float(coord)) and (float(spec[mad_col]) <= M) and (float(spec[num_meas_col]) >= N):
rec = {}
for key in list(spec.keys()):
rec[key] = spec[key]
rec["dec"] = float(spec[dec_col])
rec["inc"] = float(spec[inc_col])
rec["tilt_correction"] = spec[tilt_corr_col]
data.append(rec)
if len(data) > 2:
fpars = pmag.dolnp(data, 'specimen_direction_type')
print("Site lines planes kappa a95 dec inc")
print(site, fpars["n_lines"], fpars["n_planes"], fpars["K"],
fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"])
if out_file != "":
if float(fpars["alpha95"]) <= acutoff and float(fpars["K"]) >= kcutoff:
out.write('%s %s %s\n' %
(fpars["dec"], fpars['inc'], fpars['alpha95']))
print('% tilt correction: ', coord)
if make_plots == 1:
files = {}
files['eqarea'] = site+'_'+crd+'_'+'eqarea'+'.'+fmt
pmagplotlib.plot_lnp(EQ['eqarea'], site,
data, fpars, 'specimen_direction_type')
if plot == 0:
pmagplotlib.draw_figs(EQ)
ans = input(
"s[a]ve plot, [q]uit, <return> to continue:\n ")
if ans == "a":
pmagplotlib.save_plots(EQ, files)
if ans == "q":
sys.exit()
else:
pmagplotlib.save_plots(EQ, files)
else:
print('skipping site - not enough data with specified coordinate system')
def main():
"""
NAME
common_mean.py
DESCRIPTION
calculates bootstrap statistics to test for common mean
INPUT FORMAT
takes dec/inc as first two columns in two space delimited files
SYNTAX
common_mean.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, input file
-f2 FILE, optional second file to compare with first file
-dir D I, optional direction to compare with input file
-fmt [svg,jpg,pnd,pdf] set figure format [default is svg]
NOTES
must have either F2 OR dir but not both
"""
d,i,file2="","",""
fmt,plot='svg',0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-sav' in sys.argv: plot=1
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file1=sys.argv[ind+1]
if '-f2' in sys.argv:
ind=sys.argv.index('-f2')
file2=sys.argv[ind+1]
if '-dir' in sys.argv:
ind=sys.argv.index('-dir')
d=float(sys.argv[ind+1])
i=float(sys.argv[ind+2])
D1=numpy.loadtxt(file1,dtype=numpy.float)
if file2!="": D2=numpy.loadtxt(file2,dtype=numpy.float)
#
counter,NumSims=0,1000
#
# get bootstrapped means for first data set
#
print("Doing first set of directions, please be patient..")
BDI1=pmag.di_boot(D1)
#
# convert to cartesian coordinates X1,X2, Y1,Y2 and Z1, Z2
#
if d=="": # repeat for second data set
print("Doing second set of directions, please be patient..")
BDI2=pmag.di_boot(D2)
else:
BDI2=[]
# set up plots
CDF={'X':1,'Y':2,'Z':3}
pmagplotlib.plot_init(CDF['X'],4,4)
pmagplotlib.plot_init(CDF['Y'],4,4)
pmagplotlib.plot_init(CDF['Z'],4,4)
# draw the cdfs
pmagplotlib.plot_com(CDF,BDI1,BDI2,[d,i])
files={}
files['X']='CD_X.'+fmt
files['Y']='CD_Y.'+fmt
files['Z']='CD_Z.'+fmt
if plot==0:
pmagplotlib.draw_figs(CDF)
ans=input("S[a]ve plots, <Return> to quit ")
if ans=="a":
pmagplotlib.save_plots(CDF,files)
else:
sys.exit()
else:
pmagplotlib.save_plots(CDF,files)
sys.exit()
def main():
"""
NAME
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a pmag_results table
SYNTAX
vgpmap_magic.py [command line options]
OPTIONS
-h prints help and quits
-eye ELAT ELON [specify eyeball location], default is 90., 0.
-f FILE pmag_results format file, [default is pmag_results.txt]
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-etp plot the etopo20 topographpy data (requires high resolution data set)
-prj PROJ, specify one of the following:
ortho = orthographic
lcc = lambert conformal
moll = molweide
merc = mercator
-sym SYM SIZE: choose a symbol and size, examples:
ro 5 : small red circles
bs 10 : intermediate blue squares
g^ 20 : large green triangles
-ell plot dp/dm or a95 ellipses
-rev RSYM RSIZE : flip reverse poles to normal antipode
-S: plot antipodes of all poles
-age : plot the ages next to the poles
-crd [g,t] : choose coordinate system, default is to plot all site VGPs
-fmt [pdf, png, eps...] specify output format, default is pdf
-sav save and quit
DEFAULTS
FILE: pmag_results.txt
res: c
prj: ortho
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
dir_path = '.'
res, ages = 'c', 0
plot = 0
proj = 'ortho'
results_file = 'pmag_results.txt'
ell, flip = 0, 0
lat_0, lon_0 = 90., 0.
fmt = 'pdf'
sym, size = 'ro', 8
rsym, rsize = 'g^', 8
anti = 0
fancy = 0
coord = ""
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-S' in sys.argv:
anti = 1
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-sav' in sys.argv:
plot = 1
if '-res' in sys.argv:
ind = sys.argv.index('-res')
res = sys.argv[ind + 1]
if '-etp' in sys.argv:
fancy = 1
if '-prj' in sys.argv:
ind = sys.argv.index('-prj')
proj = sys.argv[ind + 1]
if '-rev' in sys.argv:
flip = 1
ind = sys.argv.index('-rev')
rsym = (sys.argv[ind + 1])
rsize = int(sys.argv[ind + 2])
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = (sys.argv[ind + 1])
size = int(sys.argv[ind + 2])
if '-eye' in sys.argv:
ind = sys.argv.index('-eye')
lat_0 = float(sys.argv[ind + 1])
lon_0 = float(sys.argv[ind + 2])
if '-ell' in sys.argv:
ell = 1
if '-age' in sys.argv:
ages = 1
if '-f' in sys.argv:
ind = sys.argv.index('-f')
results_file = sys.argv[ind + 1]
if '-crd' in sys.argv:
ind = sys.argv.index('-crd')
crd = sys.argv[ind + 1]
if crd == 'g':
coord = '0'
if crd == 't':
coord = '100'
results_file = dir_path + '/' + results_file
data, file_type = pmag.magic_read(results_file)
if file_type != 'pmag_results':
print("bad results file")
sys.exit()
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons, dp, dm, a95 = [], [], [], [], []
Pars = []
dates, rlats, rlons = [], [], []
if 'data_type' in data[0].keys():
# get all site level data
Results = pmag.get_dictitem(data, 'data_type', 'i', 'T')
else:
Results = data
# get all non-blank latitudes
Results = pmag.get_dictitem(Results, 'vgp_lat', '', 'F')
# get all non-blank longitudes
Results = pmag.get_dictitem(Results, 'vgp_lon', '', 'F')
if coord != "":
# get specified coordinate system
Results = pmag.get_dictitem(Results, 'tilt_correction', coord, 'T')
location = ""
for rec in Results:
if rec['er_location_names'] not in location:
location = location + ':' + rec['er_location_names']
if 'average_age' in rec.keys(
) and rec['average_age'] != "" and ages == 1:
dates.append(rec['average_age'])
lat = float(rec['vgp_lat'])
lon = float(rec['vgp_lon'])
if flip == 0:
lats.append(lat)
lons.append(lon)
elif flip == 1:
if lat < 0:
rlats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360.
rlons.append(lon)
else:
lats.append(lat)
lons.append(lon)
elif anti == 1:
lats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360.
lons.append(lon)
ppars = []
ppars.append(lon)
ppars.append(lat)
ell1, ell2 = "", ""
if 'vgp_dm' in rec.keys() and rec['vgp_dm'] != "":
ell1 = float(rec['vgp_dm'])
if 'vgp_dp' in rec.keys() and rec['vgp_dp'] != "":
ell2 = float(rec['vgp_dp'])
if 'vgp_alpha95' in rec.keys() and rec['vgp_alpha95'] != "":
ell1, ell2 = float(rec['vgp_alpha95']), float(rec['vgp_alpha95'])
if ell1 != "" and ell2 != "":
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
isign = abs(lats[-1]) / lats[-1]
ppars.append(lats[-1] - isign * 90.)
ppars.append(ell2)
ppars.append(lons[-1] + 90.)
ppars.append(0.)
Pars.append(ppars)
location = location.strip(':')
Opts = {
'latmin': -90,
'latmax': 90,
'lonmin': 0.,
'lonmax': 360.,
'lat_0': lat_0,
'lon_0': lon_0,
'proj': proj,
'sym': 'bs',
'symsize': 3,
'pltgrid': 0,
'res': res,
'boundinglat': 0.
}
Opts['details'] = {
'coasts': 1,
'rivers': 0,
'states': 0,
'countries': 0,
'ocean': 1,
'fancy': fancy
}
# make the base map with a blue triangle at the pole`
pmagplotlib.plot_map(FIG['map'], [90.], [0.], Opts)
Opts['pltgrid'] = -1
Opts['sym'] = sym
Opts['symsize'] = size
if len(dates) > 0:
Opts['names'] = dates
if len(lats) > 0:
# add the lats and lons of the poles
pmagplotlib.plot_map(FIG['map'], lats, lons, Opts)
Opts['names'] = []
if len(rlats) > 0:
Opts['sym'] = rsym
Opts['symsize'] = rsize
# add the lats and lons of the poles
pmagplotlib.plot_map(FIG['map'], rlats, rlons, Opts)
if plot == 0:
pmagplotlib.draw_figs(FIG)
if ell == 1: # add ellipses if desired.
Opts['details'] = {
'coasts': 0,
'rivers': 0,
'states': 0,
'countries': 0,
'ocean': 0
}
Opts['pltgrid'] = -1 # turn off meridian replotting
Opts['symsize'] = 2
Opts['sym'] = 'g-'
for ppars in Pars:
if ppars[2] != 0:
PTS = pmagplotlib.plot_ell(FIG['map'], ppars, 'g.', 0, 0)
elats, elons = [], []
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
# make the base map with a blue triangle at the pole`
pmagplotlib.plot_map(FIG['map'], elats, elons, Opts)
if plot == 0:
pmagplotlib.draw_figs(FIG)
files = {}
for key in FIG.keys():
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_' + location + '_VGP_map.' + fmt
else: # use more readable plot naming convention
files[key] = '{}_VGP_map.{}'.format(location.replace(' ', '_'),
fmt)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'LO:_' + location + '_VGP_map'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
else:
print("Good bye")
sys.exit()
else:
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
revtest_magic.py
DESCRIPTION
calculates bootstrap statistics to test for antipodality
INPUT FORMAT
takes dec/inc data from sites table
SYNTAX
revtest_magic.py [command line options]
OPTION
-h prints help message and quits
-f FILE, sets pmag_sites filename on command line
-crd [s,g,t], set coordinate system, default is geographic
-exc use criteria file to set acceptance criteria (only available for data model 3)
-fmt [svg,png,jpg], sets format for image output
-sav saves plot and quits
-DM [2, 3] MagIC data model num, default is 3
"""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
dir_path = pmag.get_named_arg("-WD", ".")
coord = pmag.get_named_arg("-crd",
"0") # default to geographic coordinates
if coord == 's':
coord = '-1'
elif coord == 'g':
coord = '0'
elif coord == 't':
coord = '100'
fmt = pmag.get_named_arg("-fmt", "svg")
if '-sav' in sys.argv:
plot = 1
data_model = int(float(pmag.get_named_arg("-DM")))
if data_model == 2:
infile = pmag.get_named_arg("-f", "pmag_sites.txt")
critfile = "pmag_criteria.txt"
tilt_corr_col = 'site_tilt_correction'
dec_col = "site_dec"
inc_col = "site_inc"
crit_code_col = "pmag_criteria_code"
else:
infile = pmag.get_named_arg("-f", "sites.txt")
critfile = "criteria.txt"
tilt_corr_col = "dir_tilt_correction"
dec_col = "dir_dec"
inc_col = "dir_inc"
crit_code_col = "criterion"
D = []
#
infile = pmag.resolve_file_name(infile, dir_path)
dir_path = os.path.split(infile)[0]
critfile = pmag.resolve_file_name(critfile, dir_path)
#
if data_model == 2:
Accept = ['site_k', 'site_alpha95', 'site_n', 'site_n_lines']
else:
Accept = [
'dir_k', 'dir_alpha95', 'dir_n_samples', 'dir_n_specimens_line'
]
data, file_type = pmag.magic_read(infile)
if 'sites' not in file_type:
print("Error opening file", file_type)
sys.exit()
# ordata,file_type=pmag.magic_read(orfile)
SiteCrits = []
if '-exc' in sys.argv and data_model != 2:
crits, file_type = pmag.magic_read(critfile)
for crit in crits:
if crit[crit_code_col] == "DE-SITE":
SiteCrit = crit
SiteCrits.append(SiteCrit)
elif '-exc' in sys.argv and data_model == 2:
print(
'-W- You have selected the -exc option, which is not available with MagIC data model 2.'
)
for rec in data:
if rec[tilt_corr_col] == coord:
Dec = float(rec[dec_col])
Inc = float(rec[inc_col])
if '-exc' in sys.argv and data_model != 2:
fail = False
for SiteCrit in SiteCrits:
for key in Accept:
if key not in SiteCrit['table_column']:
continue
if key not in rec:
continue
if SiteCrit['criterion_value'] != "":
op = OPS[SiteCrit['criterion_operation']]
if not op(float(rec[key]),
float(SiteCrit['criterion_value'])):
fail = True
if not fail:
D.append([Dec, Inc, 1.])
else:
D.append([Dec, Inc, 1.])
# set up plots
CDF = {'X': 1, 'Y': 2, 'Z': 3}
pmagplotlib.plot_init(CDF['X'], 5, 5)
pmagplotlib.plot_init(CDF['Y'], 5, 5)
pmagplotlib.plot_init(CDF['Z'], 5, 5)
#
# flip reverse mode
#
D1, D2 = pmag.flip(D)
counter, NumSims = 0, 500
#
# get bootstrapped means for each data set
#
if len(D1) < 5 or len(D2) < 5:
print('not enough data in two different modes for reversals test')
sys.exit()
print('doing first mode, be patient')
BDI1 = pmag.di_boot(D1)
print('doing second mode, be patient')
BDI2 = pmag.di_boot(D2)
pmagplotlib.plot_com(CDF, BDI1, BDI2, [""])
files = {}
for key in list(CDF.keys()):
files[key] = 'REV' + '_' + key + '.' + fmt
if plot == 0:
pmagplotlib.draw_figs(CDF)
ans = input("s[a]ve plots, [q]uit: ")
if ans == 'a':
pmagplotlib.save_plots(CDF, files)
else:
pmagplotlib.save_plots(CDF, files)
sys.exit()
def main():
"""
NAME
site_edit_magic.py
DESCRIPTION
makes equal area projections site by site
from pmag_specimens.txt file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
allows testing and reject specimens for bad orientations
SYNTAX
site_edit_magic.py [command line options]
OPTIONS
-h: prints help and quits
-f: specify pmag_specimen format file, default is pmag_specimens.txt
-fsa: specify er_samples.txt file
-exc: use existing pmag_criteria.txt file
-N: reset all sample flags to good
OUPUT
edited er_samples.txt file
"""
dir_path = '.'
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
in_file = 'pmag_specimens.txt'
sampfile = 'er_samples.txt'
out_file = ""
fmt, plot = 'svg', 1
Crits = ""
M, N = 180., 1
repeat = ''
renew = 0
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]
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
if '-fsa' in sys.argv:
ind = sys.argv.index("-fsa")
sampfile = sys.argv[ind + 1]
if '-exc' in sys.argv:
Crits, file_type = pmag.magic_read(dir_path + '/pmag_criteria.txt')
for crit in Crits:
if crit['pmag_criteria_code'] == 'DE-SPEC':
M = float(crit['specimen_mad'])
N = float(crit['specimen_n'])
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if '-N' in sys.argv: renew = 1
#
if in_file[0] != "/": in_file = dir_path + '/' + in_file
if sampfile[0] != "/": sampfile = dir_path + '/' + sampfile
crd = 's'
Specs, file_type = pmag.magic_read(in_file)
if file_type != 'pmag_specimens':
print(' bad pmag_specimen input file')
sys.exit()
Samps, file_type = pmag.magic_read(sampfile)
if file_type != 'er_samples':
print(' bad er_samples input file')
sys.exit()
SO_methods = []
for rec in Samps:
if 'sample_orientation_flag' not in list(rec.keys()):
rec['sample_orientation_flag'] = 'g'
if 'sample_description' not in list(rec.keys()):
rec['sample_description'] = ''
if renew == 1:
rec['sample_orientation_flag'] = 'g'
description = rec['sample_description']
if '#' in description:
newdesc = ""
c = 0
while description[c] != '#' and c < len(
description) - 1: # look for first pound sign
newdesc = newdesc + description[c]
c += 1
while description[c] == '#':
c += 1 # skip first set of pound signs
while description[c] != '#':
c += 1 # find second set of pound signs
while description[c] == '#' and c < len(description) - 1:
c += 1 # skip second set of pound signs
while c < len(description) - 1: # look for first pound sign
newdesc = newdesc + description[c]
c += 1
rec['sample_description'] = newdesc # edit out old comment about orientations
if "magic_method_codes" in rec:
methlist = rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth.strip() and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods:
SO_methods.append(meth.strip())
pmag.magic_write(sampfile, Samps, 'er_samples')
SO_priorities = pmag.set_priorities(SO_methods, 0)
sitelist = []
for rec in Specs:
if rec['er_site_name'] not in sitelist:
sitelist.append(rec['er_site_name'])
sitelist.sort()
EQ = {}
EQ['eqarea'] = 1
pmagplotlib.plot_init(EQ['eqarea'], 5, 5)
k = 0
while k < len(sitelist):
site = sitelist[k]
print(site)
data = []
ThisSiteSpecs = pmag.get_dictitem(Specs, 'er_site_name', site, 'T')
ThisSiteSpecs = pmag.get_dictitem(ThisSiteSpecs,
'specimen_tilt_correction', '-1',
'T') # get all the unoriented data
for spec in ThisSiteSpecs:
if spec['specimen_mad'] != "" and spec[
'specimen_n'] != "" and float(
spec['specimen_mad']) <= M and float(
spec['specimen_n']) >= N:
# good spec, now get orientation....
redo, p = 1, 0
if len(SO_methods) <= 1:
az_type = SO_methods[0]
orient = pmag.find_samp_rec(spec["er_sample_name"], Samps,
az_type)
redo = 0
while redo == 1:
if p >= len(SO_priorities):
print("no orientation data for ",
spec['er_sample_name'])
orient["sample_azimuth"] = ""
orient["sample_dip"] = ""
redo = 0
else:
az_type = SO_methods[SO_methods.index(
SO_priorities[p])]
orient = pmag.find_samp_rec(spec["er_sample_name"],
Samps, az_type)
if orient["sample_azimuth"] != "":
redo = 0
p += 1
if orient['sample_azimuth'] != "":
rec = {}
for key in list(spec.keys()):
rec[key] = spec[key]
rec['dec'], rec['inc'] = pmag.dogeo(
float(spec['specimen_dec']),
float(spec['specimen_inc']),
float(orient['sample_azimuth']),
float(orient['sample_dip']))
rec["tilt_correction"] = '1'
crd = 'g'
rec['sample_azimuth'] = orient['sample_azimuth']
rec['sample_dip'] = orient['sample_dip']
data.append(rec)
if len(data) > 2:
print('specimen, dec, inc, n_meas/MAD,| method codes ')
for i in range(len(data)):
print('%s: %7.1f %7.1f %s / %s | %s' %
(data[i]['er_specimen_name'], data[i]['dec'],
data[i]['inc'], data[i]['specimen_n'],
data[i]['specimen_mad'], data[i]['magic_method_codes']))
fpars = pmag.dolnp(data, 'specimen_direction_type')
print("\n Site lines planes kappa a95 dec inc")
print(site, fpars["n_lines"], fpars["n_planes"], fpars["K"],
fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"])
if out_file != "":
if float(fpars["alpha95"]) <= acutoff and float(
fpars["K"]) >= kcutoff:
out.write('%s %s %s\n' %
(fpars["dec"], fpars['inc'], fpars['alpha95']))
pmagplotlib.plot_lnp(EQ['eqarea'], site, data, fpars,
'specimen_direction_type')
pmagplotlib.draw_figs(EQ)
if k != 0 and repeat != 'y':
ans = input(
"s[a]ve plot, [q]uit, [e]dit specimens, [p]revious site, <return> to continue:\n "
)
elif k == 0 and repeat != 'y':
ans = input(
"s[a]ve plot, [q]uit, [e]dit specimens, <return> to continue:\n "
)
if ans == "p": k -= 2
if ans == "a":
files = {}
files['eqarea'] = site + '_' + crd + '_eqarea' + '.' + fmt
pmagplotlib.save_plots(EQ, files)
if ans == "q": sys.exit()
if ans == "e" and Samps == []:
print("can't edit samples without orientation file, sorry")
elif ans == "e":
# k-=1
testspec = input("Enter name of specimen to check: ")
for spec in data:
if spec['er_specimen_name'] == testspec:
# first test wrong direction of drill arrows (flip drill direction in opposite direction and re-calculate d,i
d, i = pmag.dogeo(float(spec['specimen_dec']),
float(spec['specimen_inc']),
float(spec['sample_azimuth']) - 180.,
-float(spec['sample_dip']))
XY = pmag.dimap(d, i)
pmagplotlib.plot_xy(EQ['eqarea'], [XY[0]], [XY[1]],
sym='g^')
# first test wrong end of compass (take az-180.)
d, i = pmag.dogeo(float(spec['specimen_dec']),
float(spec['specimen_inc']),
float(spec['sample_azimuth']) - 180.,
float(spec['sample_dip']))
XY = pmag.dimap(d, i)
pmagplotlib.plot_xy(EQ['eqarea'], [XY[0]], [XY[1]],
sym='kv')
# did the sample spin in the hole?
# now spin around specimen's z
X_up, Y_up, X_d, Y_d = [], [], [], []
for incr in range(0, 360, 5):
d, i = pmag.dogeo(
float(spec['specimen_dec']) + incr,
float(spec['specimen_inc']),
float(spec['sample_azimuth']),
float(spec['sample_dip']))
XY = pmag.dimap(d, i)
if i >= 0:
X_d.append(XY[0])
Y_d.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
pmagplotlib.plot_xy(EQ['eqarea'], X_d, Y_d, sym='b.')
pmagplotlib.plot_xy(EQ['eqarea'], X_up, Y_up, sym='c.')
pmagplotlib.draw_figs(EQ)
break
print("Triangle: wrong arrow for drill direction.")
print("Delta: wrong end of compass.")
print(
"Small circle: wrong mark on sample. [cyan upper hemisphere]"
)
deleteme = input("Mark this sample as bad? y/[n] ")
if deleteme == 'y':
reason = input(
"Reason: [1] broke, [2] wrong drill direction, [3] wrong compass direction, [4] bad mark, [5] displaced block [6] other "
)
if reason == '1':
description = ' sample broke while drilling'
if reason == '2':
description = ' wrong drill direction '
if reason == '3':
description = ' wrong compass direction '
if reason == '4':
description = ' bad mark in field'
if reason == '5':
description = ' displaced block'
if reason == '6':
description = input(
'Enter brief reason for deletion: ')
for samp in Samps:
if samp['er_sample_name'] == spec['er_sample_name']:
samp['sample_orientation_flag'] = 'b'
samp['sample_description'] = samp[
'sample_description'] + ' ## direction deleted because: ' + description + '##' # mark description
pmag.magic_write(sampfile, Samps, 'er_samples')
repeat = input("Mark another sample, this site? y/[n] ")
if repeat == 'y': k -= 1
else:
print(
'skipping site - not enough data with specified coordinate system'
)
k += 1
print("sample flags stored in ", sampfile)
def main():
"""
NAME
microwave_magic.py
DESCRIPTION
plots microwave paleointensity data, allowing interactive setting of bounds.
Saves and reads interpretations
from a pmag_specimen formatted table, default: microwave_specimens.txt
SYNTAX
microwave_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
-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
DEFAULTS
MEAS: magic_measurements.txt
CRIT: NONE
PRIOR: microwave_specimens.txt
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
command line window:
list is: temperature step numbers, power (J), 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", "", "microwave_specimens.txt"
inlt = 0
version_num = pmag.get_version()
Tinit, DCZ, field, first_save = 0, 0, -1, 1
user, comment = "", ''
ans, specimen, recnum, start, end = 0, 0, 0, 0, 0
plots, pmag_out, samp_file, style = 0, "", "", "svg"
fmt = '.' + style
#
# default acceptance criteria
#
accept_keys = [
'specimen_int_ptrm_n', 'specimen_md', 'specimen_fvds',
'specimen_b_beta', 'specimen_dang', 'specimen_drats', 'specimen_Z'
]
accept = {}
accept['specimen_int_ptrm_n'] = 2
accept['specimen_md'] = 10
accept['specimen_fvds'] = 0.35
accept['specimen_b_beta'] = .1
accept['specimen_int_mad'] = 7
accept['specimen_dang'] = 10
accept['specimen_drats'] = 10
accept['specimen_Z'] = 10
#
# parse command line options
#
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 '-fcr' in sys.argv:
ind = sys.argv.index('-fcr')
critout = sys.argv[ind + 1]
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = '.' + sys.argv[ind + 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 critout != "":
crit_data, file_type = pmag.magic_read(critout)
if pmagplotlib.verbose:
print("Acceptance criteria read in from ", critout)
accept = {}
accept['specimen_int_ptrm_n'] = 2.0
for critrec in crit_data:
if critrec["pmag_criteria_code"] == "IE-SPEC":
for key in accept_keys:
if key not in list(critrec.keys()):
accept[key] = -1
else:
accept[key] = float(critrec[key])
try:
open(inspec, 'r')
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 list(rec.keys()):
rec['magic_software_packages'] = ""
except IOError:
PriorRecs = []
if pmagplotlib.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'], 4, 4)
pmagplotlib.plot_init(AZD['zijd'], 4, 4)
pmagplotlib.plot_init(AZD['deremag'], 4, 4)
pmagplotlib.plot_init(AZD['eqarea'], 4, 4)
#
#
#
# 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 pmagplotlib.verbose and spc != "":
print(sids[specimen], specimen + 1, 'of ', len(sids))
MeasRecs = []
s = sids[specimen]
datablock, trmblock = [], []
PmagSpecRec = {}
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)
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-M" in meths: datablock.append(rec)
if "LP-MRM" in meths: trmblock.append(rec)
if len(trmblock) > 2 and inspec != "":
if Tinit == 0:
Tinit = 1
AZD['MRM'] = 4
pmagplotlib.plot_init(AZD['MRM'], 4, 4)
elif Tinit == 1:
pmagplotlib.clearFIG(AZD['MRM'])
if len(datablock) < 4:
if backup == 0:
specimen += 1
if pmagplotlib.verbose:
print('skipping specimen - moving forward ', s)
else:
specimen -= 1
if pmagplotlib.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"]
if "magic_instrument_codes" not in list(rec.keys()):
rec["magic_instrument_codes"] = ""
PmagSpecRec["magic_instrument_codes"] = rec[
"magic_instrument_codes"]
PmagSpecRec["measurement_step_unit"] = "J"
if "magic_experiment_name" not in list(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
if "LP-PI-M-D" in meths: # this is a double heating experiment
exp_type = "LP-PI-M-D"
elif "LP-PI-M-S" in meths:
exp_type = "LP-PI-M-S"
else:
print("experiment type not supported yet ")
break
araiblock, field = pmag.sortmwarai(datablock, exp_type)
first_Z = araiblock[0]
first_I = araiblock[1]
GammaChecks = araiblock[-3]
ThetaChecks = araiblock[-2]
DeltaChecks = araiblock[-1]
if len(first_Z) < 3:
if backup == 0:
specimen += 1
if pmagplotlib.verbose:
print('skipping specimen - moving forward ', s)
else:
specimen -= 1
if pmagplotlib.verbose:
print('skipping specimen - moving backward ', s)
else:
backup = 0
zijdblock, units = pmag.find_dmag_rec(s, meas_data)
if exp_type == "LP-PI-M-D":
recnum = 0
print("ZStep Watts Dec Inc Int")
for plotrec in zijdblock:
if pmagplotlib.verbose:
print('%i %i %7.1f %7.1f %8.3e ' %
(recnum, plotrec[0], plotrec[1], plotrec[2],
plotrec[3]))
recnum += 1
recnum = 1
if GammaChecks != "":
print("IStep Watts Gamma")
for gamma in GammaChecks:
if pmagplotlib.verbose:
print('%i %i %7.1f ' %
(recnum, gamma[0], gamma[1]))
recnum += 1
if exp_type == "LP-PI-M-S":
if pmagplotlib.verbose:
print("IStep Watts Theta")
kk = 0
for theta in ThetaChecks:
kk += 1
print('%i %i %7.1f ' % (kk, theta[0], theta[1]))
if pmagplotlib.verbose:
print("Watts Delta")
for delta in DeltaChecks:
print('%i %7.1f ' % (delta[0], delta[1]))
pmagplotlib.plot_arai_zij(AZD, araiblock, zijdblock, s,
units[0])
if inspec != "":
if pmagplotlib.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(araiblock[0])):
if float(araiblock[0][j][0]) == float(
PriorRecs[k]
["measurement_step_min"]):
start = j
if float(araiblock[0][j][0]) == float(
PriorRecs[k]
["measurement_step_max"]):
end = j
pars, errcode = pmag.PintPars(
araiblock, zijdblock, start, end)
pars['measurement_step_unit'] = "J"
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 pmagplotlib.verbose:
print('Saved interpretation: ')
pars = pmag.scoreit(
pars, PmagSpecRec, accept, '', 0)
pmagplotlib.plot_b(AZD, araiblock,
zijdblock, pars)
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.plot_trm(
AZD['MRM'], Bs, TRMs, Bp, Mp,
NLpars,
trec['magic_experiment_name'])
print(npred)
print('Banc= ',
float(NLpars['banc']) * 1e6)
if pmagplotlib.verbose:
print('Banc= ',
float(NLpars['banc']) * 1e6)
pmagplotlib.draw_figs(AZD)
else:
print('error on specimen ', s)
except:
pass
if pmagplotlib.verbose and found == 0:
print(' None found :( ')
if spc != "":
if BEG != "":
pars, errcode = pmag.PintPars(araiblock, zijdblock,
BEG, END)
pars['measurement_step_unit'] = "J"
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 len(trmblock) > 2:
if inlt == 0:
donlt()
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 list(AZD.keys()):
files[key] = s + '_' + key + fmt
pmagplotlib.save_plots(AZD, files)
sys.exit()
if plots == 0:
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])
pmagplotlib.draw_figs(AZD)
if ans == 'a':
files = {}
for key in list(AZD.keys()):
files[key] = s + '_' + 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(araiblock[0]):
end = len(araiblock[0]) - 1
GoOn = 0
while GoOn == 0:
print(
'Enter index of first point for calculation: ',
'[', start, ']')
answer = input('return to keep default ')
if answer != "": start = int(answer)
print(
'Enter index of last point for calculation: ',
'[', end, ']')
answer = input('return to keep default ')
if answer != "":
end = int(answer)
if start >= 0 and start < len(araiblock[
0]) - 2 and end > 0 and end < len(
araiblock[0]) and start < end:
GoOn = 1
else:
print("Bad endpoints - try again! ")
start, end = 0, len(araiblock)
s = sids[specimen]
pars, errcode = pmag.PintPars(
araiblock, zijdblock, start, end)
pars['measurement_step_unit'] = "J"
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars[
"specimen_b"]
pars["er_specimen_name"] = s
pars = pmag.scoreit(pars, PmagSpecRec, accept, '',
0)
PmagSpecRec["measurement_step_min"] = '%8.3e' % (
pars["measurement_step_min"])
PmagSpecRec["measurement_step_max"] = '%8.3e' % (
pars["measurement_step_max"])
PmagSpecRec["measurement_step_unit"] = "J"
PmagSpecRec["specimen_int_n"] = '%i' % (
pars["specimen_int_n"])
PmagSpecRec["specimen_lab_field_dc"] = '%8.3e' % (
pars["specimen_lab_field_dc"])
PmagSpecRec["specimen_int"] = '%8.3e ' % (
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"])
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 redudant, but helpful - won't be imported
PmagSpecRec["specimen_dang"] = '%7.1f ' % (
pars["specimen_dang"])
PmagSpecRec["specimen_drats"] = '%7.1f ' % (
pars["specimen_drats"])
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 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.plot_trm(
AZD['MRM'], Bs, TRMs, Bp, Mp, NLpars,
trec['magic_experiment_name'])
print('Banc= ', float(NLpars['banc']) * 1e6)
pmagplotlib.draw_figs(AZD)
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars[
"specimen_b"]
saveit = input(
"Save this interpretation? [y]/n \n")
if saveit != 'n':
specimen += 1
PriorRecs.append(
PmagSpecRec) # put back an interpretation
save_redo(PriorRecs, inspec)
ans = ""
else:
specimen += 1
if fmt != ".pmag":
basename = s + '_microwave' + fmt
files = {}
for key in list(AZD.keys()):
files[key] = s + '_' + 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)
# pmagplotlib.combineFigs(s,files,3)
if len(CurrRec) > 0:
for rec in CurrRec:
PriorRecs.append(rec)
CurrRec = []
if plots != 1:
ans = input(" Save last plot? 1/[0] ")
if ans == "1":
if fmt != ".pmag":
files = {}
for key in list(AZD.keys()):
files[key] = s + '_' + key + fmt
pmagplotlib.save_plots(AZD, files)
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 pmagplotlib.verbose:
print("Good bye")
def main():
"""
NAME
trmaq_magic.py
DESCTIPTION
does non-linear trm acquisisiton correction
SYNTAX
trmaq_magic.py [-h][-i][command line options]
OPTIONS
-h prints help message and quits
-i allows interactive setting of file names
-f MFILE, sets magic_measurements input file
-ft TSPEC, sets thellier_specimens input file
-F OUT, sets output for non-linear TRM acquisition corrected data
-sav save figures and quit
-fmt [png, svg, pdf]
-DM [2, 3] MagIC data model, default 3
DEFAULTS
MFILE: trmaq_measurements.txt
TSPEC: thellier_specimens.txt
OUT: NLT_specimens.txt
"""
meas_file = 'trmaq_measurements.txt'
tspec = "thellier_specimens.txt"
output = 'NLT_specimens.txt'
data_model_num = int(float(pmag.get_named_arg("-DM", 3)))
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-i' in sys.argv:
meas_file = input(
"Input magic_measurements file name? [trmaq_measurements.txt] ")
if meas_file == "":
meas_file = "trmaq_measurements.txt"
tspec = input(
" thellier_specimens file name? [thellier_specimens.txt] ")
if tspec == "":
tspec = "thellier_specimens.txt"
output = input(
"File for non-linear TRM adjusted specimen data: [NLTspecimens.txt] ")
if output == "":
output = "NLT_specimens.txt"
if '-f' in sys.argv:
ind = sys.argv.index('-f')
meas_file = sys.argv[ind+1]
if '-ft' in sys.argv:
ind = sys.argv.index('-ft')
tspec = sys.argv[ind+1]
if '-F' in sys.argv:
ind = sys.argv.index('-F')
output = sys.argv[ind+1]
if '-sav' in sys.argv:
save_plots = True
else:
save_plots = False
fmt = pmag.get_named_arg("-fmt", "svg")
#
PLT = {'aq': 1}
if not save_plots:
pmagplotlib.plot_init(PLT['aq'], 5, 5)
#
# get name of file from command line
#
comment = ""
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if 'measurements' not in file_type:
print(file_type, "This is not a valid measurements file ")
sys.exit()
if data_model_num == 2:
spec_col = "er_specimen_name"
lab_field_dc_col = "specimen_lab_field_dc"
int_col = "specimen_int"
meth_col = "magic_method_codes"
treat_dc_col = "treatment_dc_field"
magn_moment_col = "measurement_magn_moment"
experiment_col = "magic_experiment_name"
outfile_type = "pmag_specimens"
else:
spec_col = "specimen"
lab_field_dc_col = "int_treat_dc_field"
int_col = "int_abs"
meth_col = "method_codes"
treat_dc_col = "treat_dc_field"
magn_moment_col = "magn_moment"
experiment_col = "experiment"
outfile_type = "specimens"
sids = pmag.get_specs(meas_data)
specimen = 0
#
# read in thellier_specimen data
#
nrm, file_type = pmag.magic_read(tspec)
PmagSpecRecs= []
while specimen < len(sids):
#
# find corresoponding paleointensity data for this specimen
#
s = sids[specimen]
blab, best = "", ""
for nrec in nrm: # pick out the Banc data for this spec
if nrec[spec_col] == s:
try:
blab = float(nrec[lab_field_dc_col])
except ValueError:
continue
best = float(nrec[int_col])
TrmRec = nrec
break
if blab == "":
print("skipping ", s, " : no best ")
specimen += 1
else:
print(sids[specimen], specimen+1, 'of ',
len(sids), 'Best = ', best*1e6)
MeasRecs = []
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec[spec_col] == s:
meths = rec[meth_col].split(":")
methcodes = []
for meth in meths:
methcodes.append(meth.strip())
if "LP-TRM" in methcodes:
MeasRecs.append(rec)
if len(MeasRecs) < 2:
specimen += 1
print('skipping specimen - no trm acquisition data ', s)
#
# collect info for the PmagSpecRec dictionary
#
else:
TRMs, Bs = [], []
for rec in MeasRecs:
Bs.append(float(rec[treat_dc_col]))
TRMs.append(float(rec[magn_moment_col]))
# 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(
PLT['aq'], Bs, TRMs, Bp, Mp, NLpars, rec[experiment_col])
if not save_plots:
pmagplotlib.draw_figs(PLT)
print('Banc= ', float(NLpars['banc'])*1e6)
trmTC = {}
for key in list(TrmRec.keys()):
# copy of info from thellier_specimens record
trmTC[key] = TrmRec[key]
trmTC[int_col] = '%8.3e' % (NLpars['banc'])
trmTC[meth_col] = TrmRec[meth_col]+":DA-NL"
PmagSpecRecs.append(trmTC)
if not save_plots:
ans = input("Return for next specimen, s[a]ve plot ")
if ans == 'a':
Name = {'aq': rec[spec_col]+'_TRM.{}'.format(fmt)}
pmagplotlib.save_plots(PLT, Name)
else:
Name = {'aq': rec[spec_col]+'_TRM.{}'.format(fmt)}
pmagplotlib.save_plots(PLT, Name)
specimen += 1
pmag.magic_write(output, PmagSpecRecs, outfile_type)
def main():
"""
NAME
plot_magic_keys.py
DESCRIPTION
picks out keys and makes and xy plot
SYNTAX
plot_magic_keys.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file
-xkey KEY: specify key for X
-ykey KEY: specify key for Y
-b xmin xmax ymin ymax, sets bounds
"""
dir_path="./"
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
magic_file=dir_path+'/'+sys.argv[ind+1]
else:
print(main.__doc__)
sys.exit()
if '-xkey' in sys.argv:
ind=sys.argv.index('-xkey')
xkey=sys.argv[ind+1]
if '-ykey' in sys.argv:
ind=sys.argv.index('-ykey')
ykey=sys.argv[ind+1]
else:
print(main.__doc__)
sys.exit()
if '-b' in sys.argv:
ind=sys.argv.index('-b')
xmin=float(sys.argv[ind+1])
xmax=float(sys.argv[ind+2])
ymin=float(sys.argv[ind+3])
ymax=float(sys.argv[ind+4])
#
#
# get data read in
X,Y=[],[]
Data,file_type=pmag.magic_read(magic_file)
if len(Data)>0:
for rec in Data:
if xkey in list(rec.keys()) and rec[xkey]!="" and ykey in list(rec.keys()) and rec[ykey]!="":
try:
X.append(float(rec[xkey]))
Y.append(float(rec[ykey]))
except:
pass
FIG={'fig':1}
pmagplotlib.plot_init(FIG['fig'],5,5)
if '-b' in sys.argv:
pmagplotlib.plot_xy(FIG['fig'],X,Y,sym='ro',xlab=xkey,ylab=ykey,xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax )
else:
pmagplotlib.plot_xy(FIG['fig'],X,Y,sym='ro',xlab=xkey,ylab=ykey)
pmagplotlib.draw_figs(FIG)
ans=input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=="q": sys.exit()
if ans=="a":
files = {}
for key in list(FIG.keys()):
files[key]=str(key) + ".svg"
pmagplotlib.save_plots(FIG,files)
sys.exit()
else:
print('no data to plot')
def main():
"""
NAME
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify measurements format file, default "measurements.txt"
-T IND, specify temperature step to plot
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
"""
if "-h" in sys.argv:
print(main.__doc__)
return
infile = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
infile = pmag.resolve_file_name(infile, dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
show_plots = True
if "-sav" in sys.argv:
show_plots = False
experiments = pmag.get_named_arg("-e", "")
# read in data from data model 3 example file
chi_data_all = pd.read_csv(infile, sep='\t', header=1)
if not experiments:
try:
experiments = chi_data_all.experiment.unique()
except Exception as ex:
print(ex)
experiments = ["all"]
else:
experiments = [experiments]
plotnum = 0
figs = {}
fnames = {}
for exp in experiments:
if exp == "all":
chi_data = chi_data_all
chi_data = chi_data_all[chi_data_all.experiment == exp]
if len(chi_data) <= 1:
print('Not enough data to plot {}'.format(exp))
continue
plotnum += 1
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_temperature.{}'.format(fmt)
# get arrays of available temps, frequencies and fields
Ts = np.sort(chi_data.meas_temp.unique())
Fs = np.sort(chi_data.meas_freq.unique())
Bs = np.sort(chi_data.meas_field_ac.unique())
# plot chi versus temperature at constant field
b = Bs.max()
for num, f in enumerate(Fs):
this_f = chi_data[chi_data.meas_freq == f]
this_f = this_f[this_f.meas_field_ac == b]
plt.plot(this_f.meas_temp,
1e6 * this_f.susc_chi_volume,
label='%i' % (f) + ' Hz')
plt.legend()
plt.xlabel('Temperature (K)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = ' + '%7.2e' % (b) + ' T')
plotnum += 1
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_frequency.{}'.format(fmt)
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
## plot chi versus frequency at constant B
b = Bs.max()
t = Ts.min()
this_t = chi_data[chi_data.meas_temp == t]
this_t = this_t[this_t.meas_field_ac == b]
plt.semilogx(this_t.meas_freq,
1e6 * this_t.susc_chi_volume,
label='%i' % (t) + ' K')
plt.legend()
plt.xlabel('Frequency (Hz)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = ' + '%7.2e' % (b) + ' T')
if show_plots:
pmagplotlib.draw_figs(figs)
ans = input("enter s[a]ve to save files, [return] to quit ")
if ans == 'a':
pmagplotlib.save_plots(figs, fnames)
sys.exit()
else:
sys.exit()
else:
pmagplotlib.save_plots(figs, fnames)
def main():
"""
NAME
qqplot.py
DESCRIPTION
makes qq plot of input data against a Normal distribution.
INPUT FORMAT
takes real numbers in single column
SYNTAX
qqplot.py [-h][-i][-f FILE]
OPTIONS
-f FILE, specify file on command line
-fmt [png,svg,jpg,eps] set plot output format [default is svg]
-sav saves and quits
OUTPUT
calculates the K-S D and the D expected for a normal distribution
when D<Dc, distribution is normal (at 95% level of confidence).
"""
fmt,plot='svg',0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-sav' in sys.argv: plot=1
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
data=f.readlines()
X= [] # set up list for data
for line in data: # read in the data from standard input
rec=line.split() # split each line on space to get records
X.append(float(rec[0])) # append data to X
#
QQ={'qq':1}
pmagplotlib.plot_init(QQ['qq'],5,5)
pmagplotlib.plot_qq_norm(QQ['qq'],X,'Q-Q Plot') # make plot
if plot==0:
pmagplotlib.draw_figs(QQ)
files={}
for key in list(QQ.keys()):
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Q-Q Plot'
QQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(QQ,files)
elif plot==0:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a":
pmagplotlib.save_plots(QQ,files)
else:
pmagplotlib.save_plots(QQ,files)
def main():
"""
NAME
plot_map_pts.py
DESCRIPTION
plots points on map
SYNTAX
plot_map_pts.py [command line options]
OPTIONS
-h prints help and quits
-sym [ro, bs, g^, r., b-, etc.] [1,5,10] symbol and size for points
colors are r=red,b=blue,g=green, etc.
symbols are '.' for points, ^, for triangle, s for square, etc.
-, for lines, -- for dotted lines, see matplotlib online documentation for plot()
-eye ELAT ELON [specify eyeball location]
-etp put on topography
-cmap color map [default is jet]
-f FILE, specify input file
-o color ocean blue/land green (default is not)
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-fmt [pdf,eps, png] specify output format (default is pdf)
-R don't plot details of rivers
-B don't plot national/state boundaries, etc.
-pad [LAT LON] pad bounding box by LAT/LON (default is not)
-grd SPACE specify grid spacing
-sav save plot and quit
-prj PROJ, specify one of the supported projections:
pc = Plate Carree
aea = Albers Equal Area
aeqd = Azimuthal Equidistant
lcc = Lambert Conformal
lcyl = Lambert Cylindrical
merc = Mercator
mill = Miller Cylindrical
moll = Mollweide [default]
ortho = Orthographic
robin = Robinson
sinu = Sinusoidal
stere = Stereographic
tmerc = Transverse Mercator
utm = UTM
laea = Lambert Azimuthal Equal Area
geos = Geostationary
npstere = North-Polar Stereographic
spstere = South-Polar Stereographic
Special codes for MagIC formatted input files:
-n
-l
INPUTS
space or tab delimited LON LAT data
OR:
standard MagIC formatted er_sites or pmag_results table
DEFAULTS
res: c
prj: mollweide; lcc for MagIC format files
ELAT,ELON = 0,0
pad LAT,LON=0,0
NB: high resolution or lines can be very slow
"""
dir_path='.'
plot=0
ocean=0
res='c'
proj='moll'
Lats,Lons=[],[]
fmt='pdf'
sym='ro'
symsize=5
fancy=0
rivers,boundaries,ocean=1,1,0
latmin,latmax,lonmin,lonmax,lat_0,lon_0=-90,90,0.,360.,0.,0.
padlat,padlon,gridspace=0,0,30
lat_0,lon_0="",""
basemap=1
prn_name,prn_loc,names,locs=0,0,[],[]
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-res' in sys.argv:
ind = sys.argv.index('-res')
res=sys.argv[ind+1]
if res!= 'c' and res!='l':
print('this resolution will take a while - be patient')
if '-etp' in sys.argv:
fancy=1
print ('-W- plotting will require patience!')
if '-ctp' in sys.argv: basemap=0
if '-sav' in sys.argv: plot=1
if '-R' in sys.argv:rivers=0
if '-B' in sys.argv:boundaries=0
if '-o' in sys.argv:ocean=1
if '-cmap' in sys.argv:
ind = sys.argv.index('-cmap')
cmap=float(sys.argv[ind+1])
else:
cmap='jet'
if '-grd' in sys.argv:
ind = sys.argv.index('-grd')
gridspace=float(sys.argv[ind+1])
if '-eye' in sys.argv:
ind = sys.argv.index('-eye')
lat_0=float(sys.argv[ind+1])
lon_0=float(sys.argv[ind+2])
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym=sys.argv[ind+1]
symsize=int(sys.argv[ind+2])
if '-pad' in sys.argv:
ind = sys.argv.index('-pad')
padlat=float(sys.argv[ind+1])
padlon=float(sys.argv[ind+2])
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file=dir_path+'/'+sys.argv[ind+1]
header=open(file,'r').readlines()[0].split('\t')
if 'tab' in header[0]:
proj='lcc'
if 'sites' in header[1]:
latkey='lat'
lonkey='lon'
namekey='site'
lockey=''
else:
print('file type not supported')
print(main.__doc__)
sys.exit()
Sites,file_type=pmag.magic_read(file)
Lats=pmag.get_dictkey(Sites,latkey,'f')
Lons=pmag.get_dictkey(Sites,lonkey,'f')
if prn_name==1:names=pmag.get_dictkey(Sites,namekey,'')
if prn_loc==1:names=pmag.get_dictkey(Sites,lockey,'')
else:
ptdata=numpy.loadtxt(file)
Lons=ptdata.transpose()[0]
Lats=ptdata.transpose()[1]
latmin=numpy.min(Lats)-padlat
lonmin=numpy.min(Lons)-padlon
latmax=numpy.max(Lats)+padlat
lonmax=numpy.max(Lons)+padlon
if lon_0=="":
lon_0=0.5*(lonmin+lonmax)
lat_0=0.5*(latmin+latmax)
else:
print("input file must be specified")
sys.exit()
if '-prj' in sys.argv:
ind = sys.argv.index('-prj')
proj=sys.argv[ind+1]
FIG={'map':1}
pmagplotlib.plot_init(FIG['map'],6,6)
cnt=0
Opts={'latmin':latmin,'latmax':latmax,'lonmin':lonmin,'lonmax':lonmax,'lat_0':lat_0,'lon_0':lon_0,'proj':proj,'sym':sym,'symsize':3,'pltgrid':1,'res':res,'boundinglat':0.,'padlon':padlon,'padlat':padlat,'gridspace':gridspace,'cmap':cmap}
Opts['details']={}
Opts['details']['coasts']=1
Opts['details']['rivers']=rivers
Opts['details']['states']=boundaries
Opts['details']['countries']=boundaries
Opts['details']['ocean']=ocean
Opts['details']['fancy']=fancy
if len(names)>0:Opts['names']=names
if len(locs)>0:Opts['loc_name']=locs
if proj=='merc':
Opts['latmin']=-70
Opts['latmax']=70
Opts['lonmin']=-180
Opts['lonmax']=180
print('please wait to draw points')
Opts['sym']=sym
Opts['symsize']=symsize
if basemap:
pmagplotlib.plot_map(FIG['map'],Lats,Lons,Opts)
else:
pmagplotlib.plot_map(FIG['map'],Lats,Lons,Opts)
files={}
titles={}
titles['map']='PT Map'
for key in list(FIG.keys()):
files[key]='map_pts'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
FIG = pmagplotlib.add_borders(FIG,titles,black,purple)
pmagplotlib.save_plots(FIG,files)
if plot==1:
pmagplotlib.save_plots(FIG,files)
else:
pmagplotlib.draw_figs(FIG)
ans=input(" S[a]ve to save plot, Return to quit: ")
if ans=="a": pmagplotlib.save_plots(FIG,files)
def main():
"""
NAME
eqarea_magic.py
DESCRIPTION
makes equal area projections from declination/inclination data
SYNTAX
eqarea_magic.py [command line options]
INPUT
takes magic formatted pmag_results, pmag_sites, pmag_samples or pmag_specimens
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic,default='pmag_results.txt'
supported types=[magic_measurements,pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-sav save plot and quit quietly
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
in_file, plot_key, coord, crd = 'pmag_results.txt', 'all', "0", 'g'
plotE, contour = 0, 0
dir_path = '.'
fmt = 'svg'
verbose = pmagplotlib.verbose
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]
pmagplotlib.plot_init(FIG['eqarea'], 5, 5)
if '-f' in sys.argv:
ind = sys.argv.index("-f")
in_file = dir_path+"/"+sys.argv[ind+1]
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
plot_by = sys.argv[ind+1]
if plot_by == 'all':
plot_key = 'all'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
if '-c' in sys.argv:
contour = 1
plt = 0
if '-sav' in sys.argv:
plt = 1
verbose = 0
if '-ell' in sys.argv:
plotE = 1
ind = sys.argv.index('-ell')
ell_type = sys.argv[ind+1]
if ell_type == 'F':
dist = 'F'
if ell_type == 'K':
dist = 'K'
if ell_type == 'B':
dist = 'B'
if ell_type == 'Be':
dist = 'BE'
if ell_type == 'Bv':
dist = 'BV'
FIG['bdirs'] = 2
pmagplotlib.plot_init(FIG['bdirs'], 5, 5)
if '-crd' in sys.argv:
ind = sys.argv.index("-crd")
crd = sys.argv[ind+1]
if crd == 's':
coord = "-1"
if crd == 'g':
coord = "0"
if crd == 't':
coord = "100"
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind+1]
Dec_keys = ['site_dec', 'sample_dec', 'specimen_dec',
'measurement_dec', 'average_dec', 'none']
Inc_keys = ['site_inc', 'sample_inc', 'specimen_inc',
'measurement_inc', 'average_inc', 'none']
Tilt_keys = ['tilt_correction', 'site_tilt_correction',
'sample_tilt_correction', 'specimen_tilt_correction', 'none']
Dir_type_keys = ['', 'site_direction_type',
'sample_direction_type', 'specimen_direction_type']
Name_keys = ['er_specimen_name', 'er_sample_name',
'er_site_name', 'pmag_result_name']
data, file_type = pmag.magic_read(in_file)
if file_type == 'pmag_results' and plot_key != "all":
plot_key = plot_key+'s' # need plural for results table
if verbose:
print(len(data), ' records read from ', in_file)
#
#
# find desired dec,inc data:
#
dir_type_key = ''
#
# get plotlist if not plotting all records
#
plotlist = []
if plot_key != "all":
plots = pmag.get_dictitem(data, plot_key, '', 'F')
for rec in plots:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
else:
plotlist.append('All')
for plot in plotlist:
# if verbose: print plot
DIblock = []
GCblock = []
SLblock, SPblock = [], []
title = plot
mode = 1
dec_key, inc_key, tilt_key, name_key, k = "", "", "", "", 0
if plot != "All":
odata = pmag.get_dictitem(data, plot_key, plot, 'T')
else:
odata = data # data for this obj
for dec_key in Dec_keys:
# get all records with this dec_key not blank
Decs = pmag.get_dictitem(odata, dec_key, '', 'F')
if len(Decs) > 0:
break
for inc_key in Inc_keys:
# get all records with this inc_key not blank
Incs = pmag.get_dictitem(Decs, inc_key, '', 'F')
if len(Incs) > 0:
break
for tilt_key in Tilt_keys:
if tilt_key in Incs[0].keys():
break # find the tilt_key for these records
if tilt_key == 'none': # no tilt key in data, need to fix this with fake data which will be unknown tilt
tilt_key = 'tilt_correction'
for rec in Incs:
rec[tilt_key] = ''
# get all records matching specified coordinate system
cdata = pmag.get_dictitem(Incs, tilt_key, coord, 'T')
if coord == '0': # geographic
# get all the blank records - assume geographic
udata = pmag.get_dictitem(Incs, tilt_key, '', 'T')
if len(cdata) == 0:
crd = ''
if len(udata) > 0:
for d in udata:
cdata.append(d)
crd = crd+'u'
for name_key in Name_keys:
# get all records with this name_key not blank
Names = pmag.get_dictitem(cdata, name_key, '', 'F')
if len(Names) > 0:
break
for dir_type_key in Dir_type_keys:
# get all records with this direction type
Dirs = pmag.get_dictitem(cdata, dir_type_key, '', 'F')
if len(Dirs) > 0:
break
if dir_type_key == "":
dir_type_key = 'direction_type'
locations, site, sample, specimen = "", "", "", ""
for rec in cdata: # pick out the data
if 'er_location_name' in rec.keys() and rec['er_location_name'] != "" and rec['er_location_name'] not in locations:
locations = locations + \
rec['er_location_name'].replace("/", "")+"_"
if 'er_location_names' in rec.keys() and rec['er_location_names'] != "":
locs = rec['er_location_names'].split(':')
for loc in locs:
if loc not in locations:
locations = locations+loc.replace("/", "")+'_'
if plot_key == 'er_site_name' or plot_key == 'er_sample_name' or plot_key == 'er_specimen_name':
site = rec['er_site_name']
if plot_key == 'er_sample_name' or plot_key == 'er_specimen_name':
sample = rec['er_sample_name']
if plot_key == 'er_specimen_name':
specimen = rec['er_specimen_name']
if plot_key == 'er_site_names' or plot_key == 'er_sample_names' or plot_key == 'er_specimen_names':
site = rec['er_site_names']
if plot_key == 'er_sample_names' or plot_key == 'er_specimen_names':
sample = rec['er_sample_names']
if plot_key == 'er_specimen_names':
specimen = rec['er_specimen_names']
if dir_type_key not in rec.keys() or rec[dir_type_key] == "":
rec[dir_type_key] = 'l'
if 'magic_method_codes' not in rec.keys():
rec['magic_method_codes'] = ""
DIblock.append([float(rec[dec_key]), float(rec[inc_key])])
SLblock.append([rec[name_key], rec['magic_method_codes']])
if rec[tilt_key] == coord and rec[dir_type_key] != 'l' and rec[dec_key] != "" and rec[inc_key] != "":
GCblock.append([float(rec[dec_key]), float(rec[inc_key])])
SPblock.append([rec[name_key], rec['magic_method_codes']])
if len(DIblock) == 0 and len(GCblock) == 0:
if verbose:
print("no records for plotting")
sys.exit()
if verbose:
for k in range(len(SLblock)):
print('%s %s %7.1f %7.1f' % (
SLblock[k][0], SLblock[k][1], DIblock[k][0], DIblock[k][1]))
for k in range(len(SPblock)):
print('%s %s %7.1f %7.1f' % (
SPblock[k][0], SPblock[k][1], GCblock[k][0], GCblock[k][1]))
if len(DIblock) > 0:
if contour == 0:
pmagplotlib.plot_eq(FIG['eqarea'], DIblock, title)
else:
pmagplotlib.plot_eq_cont(FIG['eqarea'], DIblock)
else:
pmagplotlib.plot_net(FIG['eqarea'])
if len(GCblock) > 0:
for rec in GCblock:
pmagplotlib.plot_circ(FIG['eqarea'], rec, 90., 'g')
if plotE == 1:
ppars = pmag.doprinc(DIblock) # get principal directions
nDIs, rDIs, npars, rpars = [], [], [], []
for rec in DIblock:
angle = pmag.angle([rec[0], rec[1]], [
ppars['dec'], ppars['inc']])
if angle > 90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist == 'B': # do on whole dataset
etitle = "Bingham confidence ellipse"
bpars = pmag.dobingham(DIblock)
for key in bpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (bpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist == 'F':
etitle = "Fisher confidence cone"
if len(nDIs) > 2:
fpars = pmag.fisher_mean(nDIs)
for key in fpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (fpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (fpars[key]))
mode += 1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign = abs(fpars['inc'])/fpars['inc']
npars.append(fpars['inc']-isign*90.) # Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) # Beta inc
if len(rDIs) > 2:
fpars = pmag.fisher_mean(rDIs)
if verbose:
print("mode ", mode)
for key in fpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (fpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (fpars[key]))
mode += 1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign = abs(fpars['inc'])/fpars['inc']
rpars.append(fpars['inc']-isign*90.) # Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) # Beta inc
if dist == 'K':
etitle = "Kent confidence ellipse"
if len(nDIs) > 3:
kpars = pmag.dokent(nDIs, len(nDIs))
if verbose:
print("mode ", mode)
for key in kpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (kpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (kpars[key]))
mode += 1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs) > 3:
kpars = pmag.dokent(rDIs, len(rDIs))
if verbose:
print("mode ", mode)
for key in kpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (kpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (kpars[key]))
mode += 1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist == 'BE':
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
Bkpars = pmag.dokent(BnDIs, 1.)
if verbose:
print("mode ", mode)
for key in Bkpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (Bkpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (Bkpars[key]))
mode += 1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
Bkpars = pmag.dokent(BrDIs, 1.)
if verbose:
print("mode ", mode)
for key in Bkpars.keys():
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (Bkpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (Bkpars[key]))
mode += 1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
etitle = "Bootstrapped confidence ellipse"
elif dist == 'BV':
sym = {'lower': ['o', 'c'], 'upper': [
'o', 'g'], 'size': 3, 'edgecolor': 'face'}
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
pmagplotlib.plot_eq_sym(
FIG['bdirs'], BnDIs, 'Bootstrapped Eigenvectors', sym)
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
if len(nDIs) > 5: # plot on existing plots
pmagplotlib.plot_di_sym(FIG['bdirs'], BrDIs, sym)
else:
pmagplotlib.plot_eq(
FIG['bdirs'], BrDIs, 'Bootstrapped Eigenvectors')
if dist == 'B':
if len(nDIs) > 3 or len(rDIs) > 3:
pmagplotlib.plot_conf(FIG['eqarea'], etitle, [], npars, 0)
elif len(nDIs) > 3 and dist != 'BV':
pmagplotlib.plot_conf(FIG['eqarea'], etitle, [], npars, 0)
if len(rDIs) > 3:
pmagplotlib.plot_conf(FIG['eqarea'], etitle, [], rpars, 0)
elif len(rDIs) > 3 and dist != 'BV':
pmagplotlib.plot_conf(FIG['eqarea'], etitle, [], rpars, 0)
if verbose:
pmagplotlib.draw_figs(FIG)
#
files = {}
locations = locations[:-1]
for key in FIG.keys():
if pmagplotlib.isServer: # use server plot naming convention
filename = 'LO:_'+locations+'_SI:_'+site+'_SA:_'+sample + \
'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
else: # use more readable plot naming convention
filename = ''
for item in [locations, site, sample, specimen, crd, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Equal Area Plot'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif verbose:
ans = raw_input(
" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q":
sys.exit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
if plt:
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
aniso_magic.py
DESCRIPTION
plots anisotropy data with either bootstrap or hext ellipses
SYNTAX
aniso_magic.py [-h] [command line options]
OPTIONS
-h plots help message and quits
-usr USER: set the user name
-f AFILE, specify rmag_anisotropy formatted file for input
-F RFILE, specify rmag_results formatted file for output
-x Hext [1963] and bootstrap
-B DON'T do bootstrap, do Hext
-par Tauxe [1998] parametric bootstrap
-v plot bootstrap eigenvectors instead of ellipses
-sit plot by site instead of entire file
-crd [s,g,t] coordinate system, default is specimen (g=geographic, t=tilt corrected)
-P don't make any plots - just make rmag_results table
-sav don't make the rmag_results table - just save all the plots
-fmt [svg, jpg, eps] format for output images, pdf default
-gtc DEC INC dec,inc of pole to great circle [down(up) in green (cyan)
-d Vi DEC INC; Vi (1,2,3) to compare to direction DEC INC
-n N; specifies the number of bootstraps - default is 1000
DEFAULTS
AFILE: rmag_anisotropy.txt
RFILE: rmag_results.txt
plot bootstrap ellipses of Constable & Tauxe [1987]
NOTES
minor axis: circles
major axis: triangles
principal axis: squares
directions are plotted on the lower hemisphere
for bootstrapped eigenvector components: Xs: blue, Ys: red, Zs: black
"""
#
dir_path = "."
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
args = sys.argv
ipar, ihext, ivec, iboot, imeas, isite, iplot, vec = 0, 0, 0, 1, 1, 0, 1, 0
hpars, bpars, PDir = [], [], []
CS, crd = '-1', 's'
nb = 1000
fmt = 'pdf'
ResRecs = []
orlist = []
outfile, comp, Dir, gtcirc, PDir = 'rmag_results.txt', 0, [], 0, []
infile = 'rmag_anisotropy.txt'
if "-h" in args:
print(main.__doc__)
sys.exit()
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind+1]
if '-n' in args:
ind = args.index('-n')
nb = int(args[ind+1])
if '-usr' in args:
ind = args.index('-usr')
user = args[ind+1]
else:
user = ""
if '-B' in args:
iboot, ihext = 0, 1
if '-par' in args:
ipar = 1
if '-x' in args:
ihext = 1
if '-v' in args:
ivec = 1
if '-sit' in args:
isite = 1
if '-P' in args:
iplot = 0
if '-f' in args:
ind = args.index('-f')
infile = args[ind+1]
if '-F' in args:
ind = args.index('-F')
outfile = args[ind+1]
if '-crd' in sys.argv:
ind = sys.argv.index('-crd')
crd = sys.argv[ind+1]
if crd == 'g':
CS = '0'
if crd == 't':
CS = '100'
if '-fmt' in args:
ind = args.index('-fmt')
fmt = args[ind+1]
if '-sav' in args:
plots = 1
verbose = 0
else:
plots = 0
if '-gtc' in args:
ind = args.index('-gtc')
d, i = float(args[ind+1]), float(args[ind+2])
PDir.append(d)
PDir.append(i)
if '-d' in args:
comp = 1
ind = args.index('-d')
vec = int(args[ind+1])-1
Dir = [float(args[ind+2]), float(args[ind+3])]
#
# set up plots
#
if infile[0] != '/':
infile = dir_path+'/'+infile
if outfile[0] != '/':
outfile = dir_path+'/'+outfile
ANIS = {}
initcdf, inittcdf = 0, 0
ANIS['data'], ANIS['conf'] = 1, 2
if iboot == 1:
ANIS['tcdf'] = 3
if iplot == 1:
inittcdf = 1
pmagplotlib.plot_init(ANIS['tcdf'], 5, 5)
if comp == 1 and iplot == 1:
initcdf = 1
ANIS['vxcdf'], ANIS['vycdf'], ANIS['vzcdf'] = 4, 5, 6
pmagplotlib.plot_init(ANIS['vxcdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vycdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vzcdf'], 5, 5)
if iplot == 1:
pmagplotlib.plot_init(ANIS['conf'], 5, 5)
pmagplotlib.plot_init(ANIS['data'], 5, 5)
# read in the data
data, ifiletype = pmag.magic_read(infile)
for rec in data: # find all the orientation systems
if 'anisotropy_tilt_correction' not in rec.keys():
rec['anisotropy_tilt_correction'] = '-1'
if rec['anisotropy_tilt_correction'] not in orlist:
orlist.append(rec['anisotropy_tilt_correction'])
if CS not in orlist:
if len(orlist) > 0:
CS = orlist[0]
else:
CS = '-1'
if CS == '-1':
crd = 's'
if CS == '0':
crd = 'g'
if CS == '100':
crd = 't'
if verbose:
print("desired coordinate system not available, using available: ", crd)
if isite == 1:
sitelist = []
for rec in data:
if rec['er_site_name'] not in sitelist:
sitelist.append(rec['er_site_name'])
sitelist.sort()
plt = len(sitelist)
else:
plt = 1
k = 0
while k < plt:
site = ""
sdata, Ss = [], [] # list of S format data
Locs, Sites, Samples, Specimens, Cits = [], [], [], [], []
if isite == 0:
sdata = data
else:
site = sitelist[k]
for rec in data:
if rec['er_site_name'] == site:
sdata.append(rec)
anitypes = []
csrecs = pmag.get_dictitem(
sdata, 'anisotropy_tilt_correction', CS, 'T')
for rec in csrecs:
if rec['anisotropy_type'] not in anitypes:
anitypes.append(rec['anisotropy_type'])
if rec['er_location_name'] not in Locs:
Locs.append(rec['er_location_name'])
if rec['er_site_name'] not in Sites:
Sites.append(rec['er_site_name'])
if rec['er_sample_name'] not in Samples:
Samples.append(rec['er_sample_name'])
if rec['er_specimen_name'] not in Specimens:
Specimens.append(rec['er_specimen_name'])
if rec['er_citation_names'] not in Cits:
Cits.append(rec['er_citation_names'])
s = []
s.append(float(rec["anisotropy_s1"]))
s.append(float(rec["anisotropy_s2"]))
s.append(float(rec["anisotropy_s3"]))
s.append(float(rec["anisotropy_s4"]))
s.append(float(rec["anisotropy_s5"]))
s.append(float(rec["anisotropy_s6"]))
if s[0] <= 1.0:
Ss.append(s) # protect against crap
# tau,Vdirs=pmag.doseigs(s)
ResRec = {}
ResRec['er_location_names'] = rec['er_location_name']
ResRec['er_citation_names'] = rec['er_citation_names']
ResRec['er_site_names'] = rec['er_site_name']
ResRec['er_sample_names'] = rec['er_sample_name']
ResRec['er_specimen_names'] = rec['er_specimen_name']
ResRec['rmag_result_name'] = rec['er_specimen_name'] + \
":"+rec['anisotropy_type']
ResRec["er_analyst_mail_names"] = user
ResRec["tilt_correction"] = CS
ResRec["anisotropy_type"] = rec['anisotropy_type']
if "anisotropy_n" not in rec.keys():
rec["anisotropy_n"] = "6"
if "anisotropy_sigma" not in rec.keys():
rec["anisotropy_sigma"] = "0"
fpars = pmag.dohext(
int(rec["anisotropy_n"])-6, float(rec["anisotropy_sigma"]), s)
ResRec["anisotropy_v1_dec"] = '%7.1f' % (fpars['v1_dec'])
ResRec["anisotropy_v2_dec"] = '%7.1f' % (fpars['v2_dec'])
ResRec["anisotropy_v3_dec"] = '%7.1f' % (fpars['v3_dec'])
ResRec["anisotropy_v1_inc"] = '%7.1f' % (fpars['v1_inc'])
ResRec["anisotropy_v2_inc"] = '%7.1f' % (fpars['v2_inc'])
ResRec["anisotropy_v3_inc"] = '%7.1f' % (fpars['v3_inc'])
ResRec["anisotropy_t1"] = '%10.8f' % (fpars['t1'])
ResRec["anisotropy_t2"] = '%10.8f' % (fpars['t2'])
ResRec["anisotropy_t3"] = '%10.8f' % (fpars['t3'])
ResRec["anisotropy_ftest"] = '%10.3f' % (fpars['F'])
ResRec["anisotropy_ftest12"] = '%10.3f' % (fpars['F12'])
ResRec["anisotropy_ftest23"] = '%10.3f' % (fpars['F23'])
ResRec["result_description"] = 'F_crit: ' + \
fpars['F_crit']+'; F12,F23_crit: '+fpars['F12_crit']
ResRec['anisotropy_type'] = pmag.makelist(anitypes)
ResRecs.append(ResRec)
if len(Ss) > 1:
if pmagplotlib.isServer:
title = "LO:_"+ResRec['er_location_names'] + \
'_SI:_'+site+'_SA:__SP:__CO:_'+crd
else:
title = ResRec['er_location_names']
if site:
title += "_{}".format(site)
title += '_{}'.format(crd)
ResRec['er_location_names'] = pmag.makelist(Locs)
bpars, hpars = pmagplotlib.plot_anis(
ANIS, Ss, iboot, ihext, ivec, ipar, title, iplot, comp, vec, Dir, nb)
if len(PDir) > 0:
pmagplotlib.plot_circ(ANIS['data'], PDir, 90., 'g')
pmagplotlib.plot_circ(ANIS['conf'], PDir, 90., 'g')
if verbose and plots == 0:
pmagplotlib.draw_figs(ANIS)
ResRec['er_location_names'] = pmag.makelist(Locs)
if plots == 1:
save(ANIS, fmt, title)
ResRec = {}
ResRec['er_citation_names'] = pmag.makelist(Cits)
ResRec['er_location_names'] = pmag.makelist(Locs)
ResRec['er_site_names'] = pmag.makelist(Sites)
ResRec['er_sample_names'] = pmag.makelist(Samples)
ResRec['er_specimen_names'] = pmag.makelist(Specimens)
ResRec['rmag_result_name'] = pmag.makelist(
Sites)+":"+pmag.makelist(anitypes)
ResRec['anisotropy_type'] = pmag.makelist(anitypes)
ResRec["er_analyst_mail_names"] = user
ResRec["tilt_correction"] = CS
if isite == "0":
ResRec['result_description'] = "Study average using coordinate system: " + CS
if isite == "1":
ResRec['result_description'] = "Site average using coordinate system: " + CS
if hpars != [] and ihext == 1:
HextRec = {}
for key in ResRec.keys():
HextRec[key] = ResRec[key] # copy over stuff
HextRec["anisotropy_v1_dec"] = '%7.1f' % (hpars["v1_dec"])
HextRec["anisotropy_v2_dec"] = '%7.1f' % (hpars["v2_dec"])
HextRec["anisotropy_v3_dec"] = '%7.1f' % (hpars["v3_dec"])
HextRec["anisotropy_v1_inc"] = '%7.1f' % (hpars["v1_inc"])
HextRec["anisotropy_v2_inc"] = '%7.1f' % (hpars["v2_inc"])
HextRec["anisotropy_v3_inc"] = '%7.1f' % (hpars["v3_inc"])
HextRec["anisotropy_t1"] = '%10.8f' % (hpars["t1"])
HextRec["anisotropy_t2"] = '%10.8f' % (hpars["t2"])
HextRec["anisotropy_t3"] = '%10.8f' % (hpars["t3"])
HextRec["anisotropy_hext_F"] = '%7.1f ' % (hpars["F"])
HextRec["anisotropy_hext_F12"] = '%7.1f ' % (hpars["F12"])
HextRec["anisotropy_hext_F23"] = '%7.1f ' % (hpars["F23"])
HextRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars["e12"])
HextRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (hpars["v2_dec"])
HextRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (hpars["v2_inc"])
HextRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars["e13"])
HextRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars["v3_dec"])
HextRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars["v3_inc"])
HextRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars["e12"])
HextRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (hpars["v1_dec"])
HextRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (hpars["v1_inc"])
HextRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars["e23"])
HextRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars["v3_dec"])
HextRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars["v3_inc"])
HextRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars["e12"])
HextRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (hpars["v1_dec"])
HextRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (hpars["v1_inc"])
HextRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars["e23"])
HextRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars["v2_dec"])
HextRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars["v2_inc"])
HextRec["magic_method_codes"] = 'LP-AN:AE-H'
if verbose:
print("Hext Statistics: ")
print(
" tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I")
print(HextRec["anisotropy_t1"], HextRec["anisotropy_v1_dec"], HextRec["anisotropy_v1_inc"], HextRec["anisotropy_v1_eta_semi_angle"], HextRec["anisotropy_v1_eta_dec"],
HextRec["anisotropy_v1_eta_inc"], HextRec["anisotropy_v1_zeta_semi_angle"], HextRec["anisotropy_v1_zeta_dec"], HextRec["anisotropy_v1_zeta_inc"])
print(HextRec["anisotropy_t2"], HextRec["anisotropy_v2_dec"], HextRec["anisotropy_v2_inc"], HextRec["anisotropy_v2_eta_semi_angle"], HextRec["anisotropy_v2_eta_dec"],
HextRec["anisotropy_v2_eta_inc"], HextRec["anisotropy_v2_zeta_semi_angle"], HextRec["anisotropy_v2_zeta_dec"], HextRec["anisotropy_v2_zeta_inc"])
print(HextRec["anisotropy_t3"], HextRec["anisotropy_v3_dec"], HextRec["anisotropy_v3_inc"], HextRec["anisotropy_v3_eta_semi_angle"], HextRec["anisotropy_v3_eta_dec"],
HextRec["anisotropy_v3_eta_inc"], HextRec["anisotropy_v3_zeta_semi_angle"], HextRec["anisotropy_v3_zeta_dec"], HextRec["anisotropy_v3_zeta_inc"])
HextRec['magic_software_packages'] = version_num
ResRecs.append(HextRec)
if bpars != []:
BootRec = {}
for key in ResRec.keys():
BootRec[key] = ResRec[key] # copy over stuff
BootRec["anisotropy_v1_dec"] = '%7.1f' % (bpars["v1_dec"])
BootRec["anisotropy_v2_dec"] = '%7.1f' % (bpars["v2_dec"])
BootRec["anisotropy_v3_dec"] = '%7.1f' % (bpars["v3_dec"])
BootRec["anisotropy_v1_inc"] = '%7.1f' % (bpars["v1_inc"])
BootRec["anisotropy_v2_inc"] = '%7.1f' % (bpars["v2_inc"])
BootRec["anisotropy_v3_inc"] = '%7.1f' % (bpars["v3_inc"])
BootRec["anisotropy_t1"] = '%10.8f' % (bpars["t1"])
BootRec["anisotropy_t2"] = '%10.8f' % (bpars["t2"])
BootRec["anisotropy_t3"] = '%10.8f' % (bpars["t3"])
BootRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
bpars["v1_eta_inc"])
BootRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
bpars["v1_eta_dec"])
BootRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
bpars["v1_eta"])
BootRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
bpars["v1_zeta_inc"])
BootRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
bpars["v1_zeta_dec"])
BootRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
bpars["v1_zeta"])
BootRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
bpars["v2_eta_inc"])
BootRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
bpars["v2_eta_dec"])
BootRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
bpars["v2_eta"])
BootRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
bpars["v2_zeta_inc"])
BootRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
bpars["v2_zeta_dec"])
BootRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
bpars["v2_zeta"])
BootRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
bpars["v3_eta_inc"])
BootRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
bpars["v3_eta_dec"])
BootRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
bpars["v3_eta"])
BootRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
bpars["v3_zeta_inc"])
BootRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
bpars["v3_zeta_dec"])
BootRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
bpars["v3_zeta"])
BootRec["anisotropy_hext_F"] = ''
BootRec["anisotropy_hext_F12"] = ''
BootRec["anisotropy_hext_F23"] = ''
# regular bootstrap
BootRec["magic_method_codes"] = 'LP-AN:AE-H:AE-BS'
if ipar == 1:
# parametric bootstrap
BootRec["magic_method_codes"] = 'LP-AN:AE-H:AE-BS-P'
if verbose:
print("Boostrap Statistics: ")
print(
" tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I")
print(BootRec["anisotropy_t1"], BootRec["anisotropy_v1_dec"], BootRec["anisotropy_v1_inc"], BootRec["anisotropy_v1_eta_semi_angle"], BootRec["anisotropy_v1_eta_dec"],
BootRec["anisotropy_v1_eta_inc"], BootRec["anisotropy_v1_zeta_semi_angle"], BootRec["anisotropy_v1_zeta_dec"], BootRec["anisotropy_v1_zeta_inc"])
print(BootRec["anisotropy_t2"], BootRec["anisotropy_v2_dec"], BootRec["anisotropy_v2_inc"], BootRec["anisotropy_v2_eta_semi_angle"], BootRec["anisotropy_v2_eta_dec"],
BootRec["anisotropy_v2_eta_inc"], BootRec["anisotropy_v2_zeta_semi_angle"], BootRec["anisotropy_v2_zeta_dec"], BootRec["anisotropy_v2_zeta_inc"])
print(BootRec["anisotropy_t3"], BootRec["anisotropy_v3_dec"], BootRec["anisotropy_v3_inc"], BootRec["anisotropy_v3_eta_semi_angle"], BootRec["anisotropy_v3_eta_dec"],
BootRec["anisotropy_v3_eta_inc"], BootRec["anisotropy_v3_zeta_semi_angle"], BootRec["anisotropy_v3_zeta_dec"], BootRec["anisotropy_v3_zeta_inc"])
BootRec['magic_software_packages'] = version_num
ResRecs.append(BootRec)
k += 1
goon = 1
while goon == 1 and iplot == 1 and verbose:
if iboot == 1:
print("compare with [d]irection ")
print(
" plot [g]reat circle, change [c]oord. system, change [e]llipse calculation, s[a]ve plots, [q]uit ")
if isite == 1:
print(" [p]revious, [s]ite, [q]uit, <return> for next ")
ans = input("")
if ans == "q":
sys.exit()
if ans == "e":
iboot, ipar, ihext, ivec = 1, 0, 0, 0
e = input("Do Hext Statistics 1/[0]: ")
if e == "1":
ihext = 1
e = input("Suppress bootstrap 1/[0]: ")
if e == "1":
iboot = 0
if iboot == 1:
e = input("Parametric bootstrap 1/[0]: ")
if e == "1":
ipar = 1
e = input("Plot bootstrap eigenvectors: 1/[0]: ")
if e == "1":
ivec = 1
if iplot == 1:
if inittcdf == 0:
ANIS['tcdf'] = 3
pmagplotlib.plot_init(ANIS['tcdf'], 5, 5)
inittcdf = 1
bpars, hpars = pmagplotlib.plot_anis(
ANIS, Ss, iboot, ihext, ivec, ipar, title, iplot, comp, vec, Dir, nb)
if verbose and plots == 0:
pmagplotlib.draw_figs(ANIS)
if ans == "c":
print("Current Coordinate system is: ")
if CS == '-1':
print(" Specimen")
if CS == '0':
print(" Geographic")
if CS == '100':
print(" Tilt corrected")
key = input(
" Enter desired coordinate system: [s]pecimen, [g]eographic, [t]ilt corrected ")
if key == 's':
CS = '-1'
if key == 'g':
CS = '0'
if key == 't':
CS = '100'
if CS not in orlist:
if len(orlist) > 0:
CS = orlist[0]
else:
CS = '-1'
if CS == '-1':
crd = 's'
if CS == '0':
crd = 'g'
if CS == '100':
crd = 't'
print(
"desired coordinate system not available, using available: ", crd)
k -= 1
goon = 0
if ans == "":
if isite == 1:
goon = 0
else:
print("Good bye ")
sys.exit()
if ans == 'd':
if initcdf == 0:
initcdf = 1
ANIS['vxcdf'], ANIS['vycdf'], ANIS['vzcdf'] = 4, 5, 6
pmagplotlib.plot_init(ANIS['vxcdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vycdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vzcdf'], 5, 5)
Dir, comp = [], 1
print("""
Input: Vi D I to compare eigenvector Vi with direction D/I
where Vi=1: principal
Vi=2: major
Vi=3: minor
D= declination of comparison direction
I= inclination of comparison direction""")
con = 1
while con == 1:
try:
vdi = input("Vi D I: ").split()
vec = int(vdi[0])-1
Dir = [float(vdi[1]), float(vdi[2])]
con = 0
except IndexError:
print(" Incorrect entry, try again ")
bpars, hpars = pmagplotlib.plot_anis(
ANIS, Ss, iboot, ihext, ivec, ipar, title, iplot, comp, vec, Dir, nb)
Dir, comp = [], 0
if ans == 'g':
con, cnt = 1, 0
while con == 1:
try:
print(
" Input: input pole to great circle ( D I) to plot a great circle: ")
di = input(" D I: ").split()
PDir.append(float(di[0]))
PDir.append(float(di[1]))
con = 0
except:
cnt += 1
if cnt < 10:
print(
" enter the dec and inc of the pole on one line ")
else:
print(
"ummm - you are doing something wrong - i give up")
sys.exit()
pmagplotlib.plot_circ(ANIS['data'], PDir, 90., 'g')
pmagplotlib.plot_circ(ANIS['conf'], PDir, 90., 'g')
if verbose and plots == 0:
pmagplotlib.draw_figs(ANIS)
if ans == "p":
k -= 2
goon = 0
if ans == "q":
k = plt
goon = 0
if ans == "s":
keepon = 1
site = input(" print site or part of site desired: ")
while keepon == 1:
try:
k = sitelist.index(site)
keepon = 0
except:
tmplist = []
for qq in range(len(sitelist)):
if site in sitelist[qq]:
tmplist.append(sitelist[qq])
print(site, " not found, but this was: ")
print(tmplist)
site = input('Select one or try again\n ')
k = sitelist.index(site)
goon, ans = 0, ""
if ans == "a":
locs = pmag.makelist(Locs)
if pmagplotlib.isServer: # use server plot naming convention
title = "LO:_"+locs+'_SI:__'+'_SA:__SP:__CO:_'+crd
else: # use more readable plot naming convention
title = "{}_{}".format(locs, crd)
save(ANIS, fmt, title)
goon = 0
else:
if verbose:
print('skipping plot - not enough data points')
k += 1
# put rmag_results stuff here
if len(ResRecs) > 0:
ResOut, keylist = pmag.fillkeys(ResRecs)
pmag.magic_write(outfile, ResOut, 'rmag_results')
if verbose:
print(" Good bye ")
def main():
"""
NAME
histplot.py
DESCRIPTION
makes histograms for data
OPTIONS
-h prints help message and quits
-f input file name
-b binsize
-fmt [svg,png,pdf,eps,jpg] specify format for image, default is svg
-sav save figure and quit
-F output file name, default is hist.fmt
-N don't normalize
-twin plot both normalized and un-normalized y axes
-xlab Label of X axis
-ylab Label of Y axis
INPUT FORMAT
single variable
SYNTAX
histplot.py [command line options] [<file]
"""
fname, fmt = "", 'svg'
plot = 0
if '-sav' in sys.argv:
plot = 1
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind+1]
if '-f' in sys.argv:
ind = sys.argv.index('-f')
fname = sys.argv[ind+1]
if '-F' in sys.argv:
ind = sys.argv.index('-F')
outfile = sys.argv[ind+1]
fmt = ""
else:
outfile = 'hist.'+fmt
if '-N' in sys.argv:
norm = 0
ylab = 'Number'
else:
norm = 1
ylab = 'Frequency'
if '-twin' in sys.argv:
norm=-1
binsize = 0
if '-b' in sys.argv:
ind = sys.argv.index('-b')
binsize = int(sys.argv[ind+1])
if '-xlab' in sys.argv:
ind = sys.argv.index('-xlab')
xlab = sys.argv[ind+1]
else:
xlab = 'x'
if fname != "":
D = np.loadtxt(fname)
else:
print('-I- Trying to read from stdin... <ctrl>-c to quit')
D = np.loadtxt(sys.stdin, dtype=np.float)
# read in data
#
try:
if not D:
print('-W- No data found')
return
except ValueError:
pass
fig = pmagplotlib.plot_init(1, 8, 7)
try:
len(D)
except TypeError:
D = np.array([D])
if len(D) < 5:
print("-W- Not enough points to plot histogram ({} point(s) provided, 5 required)".format(len(D)))
return
# if binsize not provided, calculate reasonable binsize
if not binsize:
binsize = int(np.around(1 + 3.22 * np.log(len(D))))
Nbins = int(len(D) / binsize)
ax = fig.add_subplot(111)
if norm==1:
print ('normalizing')
n, bins, patches = ax.hist(
D, bins=Nbins, facecolor='#D3D3D3', histtype='stepfilled', color='black', density=True)
ax.set_ylabel(ylab)
elif norm==0:
print ('not normalizing')
n, bins, patches = ax.hist(
D, bins=Nbins, facecolor='#D3D3D3', histtype='stepfilled', color='black', density=False)
ax.set_ylabel(ylab)
elif norm==-1:
print ('trying twin')
n, bins, patches = ax.hist(
D, bins=Nbins, facecolor='#D3D3D3', histtype='stepfilled', color='black', density=True)
ax.set_ylabel('Frequency')
ax2=ax.twinx()
n, bins, patches = ax2.hist(
D, bins=Nbins, facecolor='#D3D3D3', histtype='stepfilled', color='black', density=False)
ax2.set_ylabel('Number',rotation=-90)
plt.axis([D.min(), D.max(), 0, n.max()+.1*n.max()])
ax.set_xlabel(xlab)
name = 'N = ' + str(len(D))
plt.title(name)
if plot == 0:
pmagplotlib.draw_figs({1: 'hist'})
p = input('s[a]ve to save plot, [q]uit to exit without saving ')
if p != 'a':
sys.exit()
if pmagplotlib.isServer:
pmagplotlib.add_borders({'hist': 1}, {'hist': 'Intensity Histogram'})
plt.savefig(outfile)
print('plot saved in ', outfile)
def main():
"""
NAME
revtest_MM1990.py
DESCRIPTION
calculates Watson's V statistic from input files through Monte Carlo simulation in order to test whether normal and reversed populations could have been drawn from a common mean (equivalent to watsonV.py). Also provides the critical angle between the two sample mean directions and the corresponding McFadden and McElhinny (1990) classification.
INPUT FORMAT
takes dec/inc as first two columns in two space delimited files (one file for normal directions, one file for reversed directions).
SYNTAX
revtest_MM1990.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE
-f2 FILE
-P (don't plot the Watson V cdf)
OUTPUT
Watson's V between the two populations and the Monte Carlo Critical Value Vc.
M&M1990 angle, critical angle and classification
Plot of Watson's V CDF from Monte Carlo simulation (red line), V is solid and Vc is dashed.
"""
D1,D2=[],[]
plot=1
Flip=1
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-P' in sys.argv: plot=0
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file1=sys.argv[ind+1]
f1=open(file1,'r')
for line in f1.readlines():
rec=line.split()
Dec,Inc=float(rec[0]),float(rec[1])
D1.append([Dec,Inc,1.])
f1.close()
if '-f2' in sys.argv:
ind=sys.argv.index('-f2')
file2=sys.argv[ind+1]
f2=open(file2,'r')
print("be patient, your computer is doing 5000 simulations...")
for line in f2.readlines():
rec=line.split()
Dec,Inc=float(rec[0]),float(rec[1])
D2.append([Dec,Inc,1.])
f2.close()
#take the antipode for the directions in file 2
D2_flip=[]
for rec in D2:
d,i=(rec[0]-180.)%360.,-rec[1]
D2_flip.append([d,i,1.])
pars_1=pmag.fisher_mean(D1)
pars_2=pmag.fisher_mean(D2_flip)
cart_1=pmag.dir2cart([pars_1["dec"],pars_1["inc"],pars_1["r"]])
cart_2=pmag.dir2cart([pars_2['dec'],pars_2['inc'],pars_2["r"]])
Sw=pars_1['k']*pars_1['r']+pars_2['k']*pars_2['r'] # k1*r1+k2*r2
xhat_1=pars_1['k']*cart_1[0]+pars_2['k']*cart_2[0] # k1*x1+k2*x2
xhat_2=pars_1['k']*cart_1[1]+pars_2['k']*cart_2[1] # k1*y1+k2*y2
xhat_3=pars_1['k']*cart_1[2]+pars_2['k']*cart_2[2] # k1*z1+k2*z2
Rw=numpy.sqrt(xhat_1**2+xhat_2**2+xhat_3**2)
V=2*(Sw-Rw)
#
#keep weighted sum for later when determining the "critical angle" let's save it as Sr (notation of McFadden and McElhinny, 1990)
#
Sr=Sw
#
# do monte carlo simulation of datasets with same kappas, but common mean
#
counter,NumSims=0,5000
Vp=[] # set of Vs from simulations
for k in range(NumSims):
#
# get a set of N1 fisher distributed vectors with k1, calculate fisher stats
#
Dirp=[]
for i in range(pars_1["n"]):
Dirp.append(pmag.fshdev(pars_1["k"]))
pars_p1=pmag.fisher_mean(Dirp)
#
# get a set of N2 fisher distributed vectors with k2, calculate fisher stats
#
Dirp=[]
for i in range(pars_2["n"]):
Dirp.append(pmag.fshdev(pars_2["k"]))
pars_p2=pmag.fisher_mean(Dirp)
#
# get the V for these
#
Vk=pmag.vfunc(pars_p1,pars_p2)
Vp.append(Vk)
#
# sort the Vs, get Vcrit (95th percentile one)
#
Vp.sort()
k=int(.95*NumSims)
Vcrit=Vp[k]
#
# equation 18 of McFadden and McElhinny, 1990 calculates the critical value of R (Rwc)
#
Rwc=Sr-(old_div(Vcrit,2))
#
#following equation 19 of McFadden and McElhinny (1990) the critical angle is calculated.
#
k1=pars_1['k']
k2=pars_2['k']
R1=pars_1['r']
R2=pars_2['r']
critical_angle=numpy.degrees(numpy.arccos(old_div(((Rwc**2)-((k1*R1)**2)-((k2*R2)**2)),(2*k1*R1*k2*R2))))
D1_mean=(pars_1['dec'],pars_1['inc'])
D2_mean=(pars_2['dec'],pars_2['inc'])
angle=pmag.angle(D1_mean,D2_mean)
#
# print the results of the test
#
print("")
print("Results of Watson V test: ")
print("")
print("Watson's V: " '%.1f' %(V))
print("Critical value of V: " '%.1f' %(Vcrit))
if V<Vcrit:
print('"Pass": Since V is less than Vcrit, the null hypothesis that the two populations are drawn from distributions that share a common mean direction (antipodal to one another) cannot be rejected.')
elif V>Vcrit:
print('"Fail": Since V is greater than Vcrit, the two means can be distinguished at the 95% confidence level.')
print("")
print("M&M1990 classification:")
print("")
print("Angle between data set means: " '%.1f'%(angle))
print("Critical angle of M&M1990: " '%.1f'%(critical_angle))
if V>Vcrit:
print("")
elif V<Vcrit:
if critical_angle<5:
print("The McFadden and McElhinny (1990) classification for this test is: 'A'")
elif critical_angle<10:
print("The McFadden and McElhinny (1990) classification for this test is: 'B'")
elif critical_angle<20:
print("The McFadden and McElhinny (1990) classification for this test is: 'C'")
else:
print("The McFadden and McElhinny (1990) classification for this test is: 'INDETERMINATE;")
if plot==1:
CDF={'cdf':1}
pmagplotlib.plot_init(CDF['cdf'],5,5)
p1 = pmagplotlib.plot_cdf(CDF['cdf'],Vp,"Watson's V",'r',"")
p2 = pmagplotlib.plot_vs(CDF['cdf'],[V],'g','-')
p3 = pmagplotlib.plot_vs(CDF['cdf'],[Vp[k]],'b','--')
pmagplotlib.draw_figs(CDF)
files,fmt={},'svg'
if file2!="":
files['cdf']='WatsonsV_'+file1+'_'+file2+'.'+fmt
else:
files['cdf']='WatsonsV_'+file1+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['cdf']='Cumulative Distribution'
CDF = pmagplotlib.add_borders(CDF,titles,black,purple)
pmagplotlib.save_plots(CDF,files)
else:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.save_plots(CDF,files)
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 plot(in_file="measurements.txt", dir_path=".", input_dir_path="",
spec_file="specimens.txt", samp_file="samples.txt",
site_file="sites.txt", loc_file="locations.txt",
plot_by="loc", LT="AF", norm=True, XLP="",
save_plots=True, fmt="svg"):
"""
plots intensity decay curves for demagnetization experiments
Parameters
----------
in_file : str, default "measurements.txt"
dir_path : str
output directory, default "."
input_dir_path : str
input file directory (if different from dir_path), default ""
spec_file : str
input specimen file name, default "specimens.txt"
samp_file: str
input sample file name, default "samples.txt"
site_file : str
input site file name, default "sites.txt"
loc_file : str
input location file name, default "locations.txt"
plot_by : str
[spc, sam, sit, loc] (specimen, sample, site, location), default "loc"
LT : str
lab treatment [T, AF, M], default AF
norm : bool
normalize by NRM magnetization, default True
XLP : str
exclude specific lab protocols, (for example, method codes like LP-PI)
default ""
save_plots : bool
plot and save non-interactively, default True
fmt : str
["png", "svg", "pdf", "jpg"], default "svg"
Returns
---------
type - Tuple : (True or False indicating if conversion was sucessful, file name(s) written)
"""
dir_path = os.path.realpath(dir_path)
if not input_dir_path:
input_dir_path = dir_path
input_dir_path = os.path.realpath(input_dir_path)
# format plot_key
name_dict = {'loc': 'location', 'sit': 'site',
'sam': 'sample', 'spc': 'specimen'}
if plot_by not in name_dict.values():
try:
plot_key = name_dict[plot_by]
except KeyError:
print('Unrecognized plot_by {}, falling back to plot by location'.format(plot_by))
plot_key = "loc"
else:
plot_key = plot_by
# figure out what kind of experiment
LT = "LT-" + LT + "-Z"
print('LT', LT)
if LT == "LT-T-Z":
units, dmag_key = 'K', 'treat_temp'
elif LT == "LT-AF-Z":
units, dmag_key = 'T', 'treat_ac_field'
elif LT == 'LT-M-Z':
units, dmag_key = 'J', 'treat_mw_energy'
else:
units = 'U'
# init
FIG = {} # plot dictionary
FIG['demag'] = 1 # demag is figure 1
# create contribution and add required headers
fnames = {"specimens": spec_file, "samples": samp_file,
'sites': site_file, 'locations': loc_file}
if not os.path.exists(pmag.resolve_file_name(in_file, input_dir_path)):
print('-E- Could not find {}'.format(in_file))
return False, []
contribution = cb.Contribution(input_dir_path, single_file=in_file,
custom_filenames=fnames)
file_type = list(contribution.tables.keys())[0]
print(len(contribution.tables['measurements'].df), ' records read from ', in_file)
# add plot_key into measurements table
if plot_key not in contribution.tables['measurements'].df.columns:
#contribution.propagate_name_down(plot_key, 'measurements')
contribution.propagate_location_to_measurements()
data_container = contribution.tables[file_type]
# pare down to only records with useful data
# grab records that have the requested code
data_slice = data_container.get_records_for_code(LT)
# and don't have the offending code
data = data_container.get_records_for_code(XLP, incl=False, use_slice=True,
sli=data_slice, strict_match=False)
# make sure quality is in the dataframe
if 'quality' not in data.columns:
data['quality'] = 'g'
# get intensity key and make sure intensity data is not blank
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
# get rid of any entirely blank intensity columns
for col_name in IntMeths:
if not data[col_name].any():
data.drop(col_name, axis=1, inplace=True)
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
if len(IntMeths) == 0:
print('-E- No intensity headers found')
return False, []
int_key = IntMeths[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
data = data[data[int_key].notnull()]
# make list of individual plots
# by default, will be by location_name
plotlist = data[plot_key].unique()
plotlist.sort()
pmagplotlib.plot_init(FIG['demag'], 5, 5)
last_plot = False
# iterate through and plot the data
for plt in plotlist:
if plt == plotlist[-1]:
last_plot = True
plot_data = data[data[plot_key] == plt].copy()
if not save_plots:
print(plt, 'plotting by: ', plot_key)
if len(plot_data) > 2:
title = plt
spcs = []
spcs = plot_data['specimen'].unique()
for spc in spcs:
INTblock = []
spec_data = plot_data[plot_data['specimen'] == spc]
for ind, rec in spec_data.iterrows():
INTblock.append([float(rec[dmag_key]), 0, 0, float(rec[int_key]), 1, rec['quality']])
if len(INTblock) > 2:
pmagplotlib.plot_mag(FIG['demag'], INTblock,
title, 0, units, norm)
if save_plots:
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer:
files[key] = title + '_' + LT + '.' + fmt
incl_dir = False
else: # if not server, include directory in output path
files[key] = os.path.join(dir_path, title + '_' + LT + '.' + fmt)
incl_dir = True
pmagplotlib.save_plots(FIG, files, incl_directory=incl_dir)
else:
pmagplotlib.draw_figs(FIG)
prompt = " S[a]ve to save plot, [q]uit, Return to continue: "
ans = input(prompt)
if ans == 'q':
return True, []
if ans == "a":
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer:
files[key] = title + '_' + LT + '.' + fmt
incl_dir = False
else: # if not server, include directory in output path
files[key] = os.path.join(dir_path, title + '_' + LT + '.' + fmt)
incl_dir = True
pmagplotlib.save_plots(FIG, files, incl_directory=incl_dir)
pmagplotlib.clearFIG(FIG['demag'])
if last_plot:
return True, []
def main():
"""
NAME
chi_magic.py
DESCRIPTION
plots magnetic susceptibility as a function of frequency and temperature and AC field
SYNTAX
chi_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE, specify measurements format file, default "measurements.txt"
-T IND, specify temperature step to plot
-e EXP, specify experiment name to plot
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-sav save figure and quit
"""
if "-h" in sys.argv:
print(main.__doc__)
return
infile = pmag.get_named_arg("-f", "measurements.txt")
dir_path = pmag.get_named_arg("-WD", ".")
infile = pmag.resolve_file_name(infile, dir_path)
fmt = pmag.get_named_arg("-fmt", "svg")
show_plots = True
if "-sav" in sys.argv:
show_plots = False
experiments = pmag.get_named_arg("-e", "")
# read in data from data model 3 example file
chi_data_all = pd.read_csv(infile, sep='\t', header=1)
if not experiments:
try:
experiments = chi_data_all.experiment.unique()
except Exception as ex:
print(ex)
experiments = ["all"]
else:
experiments = [experiments]
plotnum = 0
figs = {}
fnames = {}
for exp in experiments:
if exp == "all":
chi_data = chi_data_all
chi_data = chi_data_all[chi_data_all.experiment == exp]
if len(chi_data) <= 1:
print('Not enough data to plot {}'.format(exp))
continue
plotnum += 1
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_temperature.{}'.format(fmt)
# get arrays of available temps, frequencies and fields
Ts = np.sort(chi_data.meas_temp.unique())
Fs = np.sort(chi_data.meas_freq.unique())
Bs = np.sort(chi_data.meas_field_ac.unique())
# plot chi versus temperature at constant field
b = Bs.max()
for num, f in enumerate(Fs):
this_f = chi_data[chi_data.meas_freq == f]
this_f = this_f[this_f.meas_field_ac == b]
plt.plot(this_f.meas_temp, 1e6*this_f.susc_chi_volume,
label='%i' % (f)+' Hz')
plt.legend()
plt.xlabel('Temperature (K)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = '+'%7.2e' % (b) + ' T')
plotnum += 1
figs[str(plotnum)] = plotnum
fnames[str(plotnum)] = exp + '_frequency.{}'.format(fmt)
pmagplotlib.plot_init(plotnum, 5, 5) # set up plot
## plot chi versus frequency at constant B
b = Bs.max()
t = Ts.min()
this_t = chi_data[chi_data.meas_temp == t]
this_t = this_t[this_t.meas_field_ac == b]
plt.semilogx(this_t.meas_freq, 1e6 *
this_t.susc_chi_volume, label='%i' % (t)+' K')
plt.legend()
plt.xlabel('Frequency (Hz)')
plt.ylabel('$\chi$ ($\mu$SI)')
plt.title('B = '+'%7.2e' % (b) + ' T')
if show_plots:
pmagplotlib.draw_figs(figs)
ans = input(
"enter s[a]ve to save files, [return] to quit ")
if ans == 'a':
pmagplotlib.save_plots(figs, fnames)
sys.exit()
else:
sys.exit()
else:
pmagplotlib.save_plots(figs, fnames)
def main():
"""
NAME
igrf.py
DESCRIPTION
This program calculates igrf field values
using the routine of Malin and Barraclough (1981)
based on d/igrfs from 1900 to 2010.
between 1900 and 1000BCE, it uses CALS3K.4, ARCH3K.1
Prior to 1000BCE, it uses PFM9k or CALS10k-4b
Calculates reference field vector at specified location and time.
SYNTAX
igrf.py [-h] [-i] -f FILE [< filename]
OPTIONS:
-h prints help message and quits
-i for interactive data entry
-f FILE specify file name with input data
-fgh FILE specify file with custom field coefficients in format: l m g h
-F FILE specify output file name
-ages MIN MAX INCR: specify age minimum in years (+/- AD), maximum and increment, default is line by line
-loc LAT LON; specify location, default is line by line
-alt ALT; specify altitude in km, default is sealevel (0)
-plt; make a plot of the time series
-sav, saves plot and quits
-fmt [pdf,jpg,eps,svg] specify format for output figure (default is svg)
-mod [arch3k,cals3k,pfm9k,hfm10k,cals10k.2,shadif14k,cals10k.1b] specify model for 3ka to 1900 AD, default is cals10k
NB: program uses IGRF12 for dates 1900 to 2015.
INPUT FORMAT
interactive entry:
date: decimal year
alt: altitude in km
lat: positive north
lon: positive east
for file entry:
space delimited string: date alt lat long
OUTPUT FORMAT
Declination Inclination Intensity (nT) date alt lat long
MODELS: ARCH3K: (Korte et al., 2009);CALS3K (Korte & Contable, 2011); CALS10k (is .1b of Korte et al., 2011); PFM9K (Nilsson et al., 2014); HFM10k (is HFM.OL1.A1 of Constable et al., 2016); CALS10k_2 (is cals10k.2 of Constable et al., 2016), SHADIF14k (SHA.DIF.14K of Pavon-Carrasco et al., 2014).
"""
plot, fmt = 0, 'svg'
mod, alt, make_plot, lat, lon = 'cals10k', 0, 0, 0, 0
if '-loc' in sys.argv:
ind = sys.argv.index('-loc')
lat = float(sys.argv[ind + 1])
lon = float(sys.argv[ind + 2])
if '-alt' in sys.argv:
ind = sys.argv.index('-alt')
alt = float(sys.argv[ind + 1])
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if len(sys.argv) != 0 and '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-mod' in sys.argv:
ind = sys.argv.index('-mod')
mod = sys.argv[ind + 1]
if '-fgh' in sys.argv:
ind = sys.argv.index('-fgh')
ghfile = sys.argv[ind + 1]
lmgh = numpy.loadtxt(ghfile)
gh = []
lmgh = numpy.loadtxt(ghfile).transpose()
gh.append(lmgh[2][0])
for i in range(1, lmgh.shape[1]):
gh.append(lmgh[2][i])
gh.append(lmgh[3][i])
mod = 'custom'
inp = [[0, alt, lat, lon]]
elif '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
inp = numpy.loadtxt(file)
elif '-i' in sys.argv:
while 1:
try:
line = []
if mod != 'custom':
line.append(
float(input("Decimal year: <cntrl-D to quit> ")))
else:
line.append(0)
alt = input("Elevation in km [0] ")
if alt == "":
alt = "0"
line.append(float(alt))
line.append(float(input("Latitude (positive north) ")))
line.append(float(input("Longitude (positive east) ")))
if mod == '':
x, y, z, f = pmag.doigrf(line[3] % 360., line[2], line[1],
line[0])
elif mod == 'custom':
x, y, z, f = pmag.docustom(line[3] % 360., line[2],
line[1], gh)
else:
x, y, z, f = pmag.doigrf(line[3] % 360.,
line[2],
line[1],
line[0],
mod=mod)
Dir = pmag.cart2dir((x, y, z))
print('%8.2f %8.2f %8.0f' % (Dir[0], Dir[1], f))
except EOFError:
print("\n Good-bye\n")
sys.exit()
elif '-ages' in sys.argv:
ind = sys.argv.index('-ages')
agemin = float(sys.argv[ind + 1])
agemax = float(sys.argv[ind + 2])
ageincr = float(sys.argv[ind + 3])
ages = numpy.arange(agemin, agemax, ageincr)
lats = numpy.ones(len(ages)) * lat
lons = numpy.ones(len(ages)) * lon
alts = numpy.ones(len(ages)) * alt
inp = numpy.array([ages, alts, lats, lons]).transpose()
else:
inp = numpy.loadtxt(sys.stdin, dtype=numpy.float)
if '-F' in sys.argv:
ind = sys.argv.index('-F')
outfile = sys.argv[ind + 1]
out = open(outfile, 'w')
else:
outfile = ""
if '-sav' in sys.argv:
plot = 1
if '-plt' in sys.argv:
make_plot = 1
Ages, Decs, Incs, Ints, VADMs = [], [], [], [], []
for line in inp:
if mod != 'custom':
x, y, z, f = pmag.doigrf(line[3] % 360.,
line[2],
line[1],
line[0],
mod=mod)
else:
x, y, z, f = pmag.docustom(line[3] % 360., line[2], line[1], gh)
Dir = pmag.cart2dir((x, y, z))
if outfile != "":
out.write('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f\n' %
(Dir[0], Dir[1], f, line[0], line[1], line[2], line[3]))
elif make_plot:
Ages.append(line[0])
if Dir[0] > 180:
Dir[0] = Dir[0] - 360.0
Decs.append(Dir[0])
Incs.append(Dir[1])
Ints.append(f * 1e-3)
VADMs.append(pmag.b_vdm(f * 1e-9, line[2]) * 1e-21)
else:
print('%8.2f %8.2f %8.0f %7.1f %7.1f %7.1f %7.1f' %
(Dir[0], Dir[1], f, line[0], line[1], line[2], line[3]))
if make_plot:
pmagplotlib.plot_init(1, 7, 9)
fig = plt.figure(num=1, figsize=(7, 9))
fig.add_subplot(411)
plt.plot(Ages, Decs)
plt.ylabel('Declination ($^{\circ}$)')
fig.add_subplot(412)
plt.plot(Ages, Incs)
plt.ylabel('Inclination ($^{\circ}$)')
fig.add_subplot(413)
plt.plot(Ages, Ints)
plt.ylabel('Intensity ($\mu$T)')
fig.add_subplot(414)
plt.plot(Ages, VADMs)
plt.ylabel('VADMs (ZAm$^2$)')
plt.xlabel('Ages')
# show plot
if plot == 0:
pmagplotlib.draw_figs({'time series': 1})
ans = input("S[a]ve to save figure, <Return> to quit ")
if ans == 'a':
plt.savefig('igrf.' + fmt)
print('Figure saved as: ', 'igrf.' + fmt)
# save plot without showing
else:
plt.savefig('igrf.' + fmt)
print('Figure saved as: ', 'igrf.' + fmt)
sys.exit()
def main():
"""
NAME
plotdi_a.py
DESCRIPTION
plots equal area projection from dec inc data and fisher mean, cone of confidence
INPUT FORMAT
takes dec, inc, alpha95 as first three columns in space delimited file
SYNTAX
plotdi_a.py [-i][-f FILE]
OPTIONS
-f FILE to read file name from command line
-fmt [png,jpg,eps,pdf,svg] set plot file format ['svg' is default]
-sav save plot and quit
"""
fmt,plot='svg',0
if len(sys.argv) > 0:
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-sav' in sys.argv:plot=1
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
DIs,Pars=[],[]
for line in data: # read in the data from standard input
pars=[]
rec=line.split() # split each line on space to get records
DIs.append([float(rec[0]),float(rec[1])])
pars.append(float(rec[0]))
pars.append(float(rec[1]))
pars.append(float(rec[2]))
pars.append(float(rec[0]))
isign=abs(float(rec[1])) / float(rec[1])
pars.append(float(rec[1])-isign*90.) #Beta inc
pars.append(float(rec[2])) # gamma
pars.append(float(rec[0])+90.) # Beta dec
pars.append(0.) #Beta inc
Pars.append(pars)
#
EQ={'eq':1} # make plot dictionary
pmagplotlib.plot_init(EQ['eq'],5,5)
title='Equal area projection'
pmagplotlib.plot_eq(EQ['eq'],DIs,title)# plot directions
for k in range(len(Pars)):
pmagplotlib.plot_ell(EQ['eq'],Pars[k],'b',0,1) # plot ellipses
files={}
for key in list(EQ.keys()):
files[key]=key+'.'+fmt
titles={}
titles['eq']='Equal Area Plot'
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
EQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(EQ,files)
elif plot==0:
pmagplotlib.draw_figs(EQ)
ans=input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=="q": sys.exit()
if ans=="a":
pmagplotlib.save_plots(EQ,files)
else:
pmagplotlib.save_plots(EQ,files)
def main():
"""
NAME
strip_magic.py
DESCRIPTION
plots various parameters versus depth or age
SYNTAX
strip_magic.py [command line optins]
OPTIONS
-h prints help message and quits
-DM NUM: specify data model num, options 2 (legacy) or 3 (default)
-f FILE: specify input magic format file from magic,default='pmag_results.txt'
supported types=[pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
-obj [sit,sam,all]: specify object to site,sample,all for pmag_result table, default is all
-fmt [svg,png,jpg], format for images - default is svg
-x [age,pos]: specify whether age or stratigraphic position
-y [dec,inc,int,chi,lat,lon,vdm,vadm]
(lat and lon are VGP lat and lon)
-Iex: plot the expected inc at lat - only available for results with lat info in file
-ts TS amin amax: plot the GPTS for the time interval between amin and amax (numbers in Ma)
TS: [ck95, gts04]
-mcd method_code, specify method code, default is first one encountered
-sav save plot and quit
NOTES
when x and/or y are not specified, a list of possibilities will be presented to the user for choosing
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
xaxis, xplotind, yplotind = "", 0, 0 # (0 for strat pos)
yaxis, Xinc = "", ""
plot = 0
obj = 'all'
data_model_num = int(pmag.get_named_arg("-DM", 3))
# 2.5 keys
if data_model_num == 2:
supported = [
'pmag_specimens', 'pmag_samples', 'pmag_sites', 'pmag_results',
'magic_web'
] # available file types
Depth_keys = [
'specimen_core_depth', 'specimen_height', 'specimen_elevation',
'specimen_composite_depth', 'sample_core_depth', 'sample_height',
'sample_elevation', 'sample_composite_depth', 'site_core_depth',
'site_height', 'site_elevation', 'site_composite_depth',
'average_height'
]
Age_keys = [
'specimen_inferred_age', 'sample_inferred_age',
'site_inferred_age', 'average_age'
]
Unit_keys = {
'specimen_inferred_age': 'specimen_inferred_age_unit',
'sample_inferred_age': 'sample_inferred_age_unit',
'site_inferred_age': 'site_inferred_age_unit',
'average_age': 'average_age_unit'
}
Dec_keys = [
'measurement_dec', 'specimen_dec', 'sample_dec', 'site_dec',
'average_dec'
]
Inc_keys = [
'measurement_inc', 'specimen_inc', 'sample_inc', 'site_inc',
'average_inc'
]
Int_keys = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass', 'specimen_int',
'specimen_int_rel', 'sample_int', 'sample_int_rel', 'site_int',
'site_int_rel', 'average_int', 'average_int_rel'
]
Chi_keys = ['measurement_chi_volume', 'measurement_chi_mass']
Lat_keys = ['sample_lat', 'site_lat', 'average_lat']
VLat_keys = ['vgp_lat']
VLon_keys = ['vgp_lon']
Vdm_keys = ['vdm']
Vadm_keys = ['vadm']
method_col_name = "magic_method_codes"
else:
# 3.0 keys
supported = ["specimens", "samples", "sites",
"locations"] # available file types
Depth_keys = ["height", "core_depth", "elevation", "composite_depth"]
Age_keys = ["age"]
Unit_keys = {"age": "age"}
Chi_keys = ["susc_chi_volume", "susc_chi_mass"]
Int_keys = [
"magn_moment", "magn_volume", "magn_mass", "int_abs", "int_rel"
]
Inc_keys = ["dir_inc"]
Dec_keys = ["dir_dec"]
Lat_Keys = ["lat"]
VLat_keys = ["vgp_lat", "pole_lat"]
VLon_keys = ["vgp_lon", "pole_lon"]
Vdm_keys = ["vdm", "pdm"]
Vadm_keys = ["vadm", "padm"]
method_col_name = "method_codes"
#
X_keys = [Age_keys, Depth_keys]
Y_keys = [
Dec_keys, Inc_keys, Int_keys, Chi_keys, VLat_keys, VLon_keys, Vdm_keys,
Vadm_keys
]
method, fmt = "", 'svg'
FIG = {'strat': 1}
plotexp, pTS = 0, 0
dir_path = pmag.get_named_arg("-WD", ".")
# default files
if data_model_num == 3:
res_file = pmag.get_named_arg("-f", "sites.txt")
else:
res_file = pmag.get_named_arg("-f", "pmag_results.txt")
res_file = pmag.resolve_file_name(res_file, dir_path)
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-obj' in sys.argv:
ind = sys.argv.index('-obj')
obj = sys.argv[ind + 1]
if '-x' in sys.argv:
ind = sys.argv.index('-x')
xaxis = sys.argv[ind + 1]
if '-y' in sys.argv:
ind = sys.argv.index('-y')
yaxis = sys.argv[ind + 1]
if yaxis == 'dec':
ykeys = Dec_keys
if yaxis == 'inc':
ykeys = Inc_keys
if yaxis == 'int':
ykeys = Int_keys
if yaxis == 'chi':
ykeys = Chi_keys
if yaxis == 'lat':
ykeys = VLat_keys
if yaxis == 'lon':
ykeys = VLon_keys
if yaxis == 'vdm':
ykeys = Vdm_keys
if yaxis == 'vadm':
ykeys = Vadm_keys
if '-mcd' in sys.argv:
ind = sys.argv.index('-mcd')
method = sys.argv[ind + 1]
if '-ts' in sys.argv:
ind = sys.argv.index('-ts')
ts = sys.argv[ind + 1]
amin = float(sys.argv[ind + 2])
amax = float(sys.argv[ind + 3])
pTS = 1
if '-Iex' in sys.argv:
plotexp = 1
if '-sav' in sys.argv:
plot = 1
#
#
# get data read in
Results, file_type = pmag.magic_read(res_file)
if file_type not in supported:
print("Unsupported file type ({}), try again".format(file_type))
sys.exit()
PltObjs = ['all']
if data_model_num == 2:
if file_type == 'pmag_results': # find out what to plot
for rec in Results:
resname = rec['pmag_result_name'].split()
if 'Sample' in resname and 'sam' not in PltObjs:
PltObjs.append('sam')
if 'Site' in resname and 'sit' not in PltObjs:
PltObjs.append('sit')
methcodes = []
# need to know all the measurement types from method_codes
if "magic_method_codes" in list(Results[0].keys()):
for rec in Results:
meths = rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in methcodes and 'LP' in meth:
# look for the lab treatments
methcodes.append(meth.strip())
#
# initialize some variables
X_unit = "" # Unit for age or depth plotting (meters if depth)
Xplots, Yplots = [], []
Xunits = []
yplotind, xplotind = 0, 0
#
# step through possible plottable keys
#
if xaxis == "" or yaxis == "":
for key in list(Results[0].keys()):
for keys in X_keys:
for xkeys in keys:
if key in xkeys:
for ResRec in Results:
if ResRec[key] != "":
# only plot something if there is something to plot!
Xplots.append(key)
break
for keys in Y_keys:
for pkeys in keys:
if key in pkeys:
for ResRec in Results:
if ResRec[key] != "":
Yplots.append(key)
break
X, Y = [], []
for plt in Xplots:
if plt in Age_keys and 'age' not in X:
X.append('age')
if plt in Depth_keys and 'pos' not in X:
X.append('pos')
for plt in Yplots:
if plt in Dec_keys and 'dec' not in Y:
Y.append('dec')
if plt in Inc_keys and 'inc' not in Y:
Y.append('inc')
if plt in Int_keys and 'int' not in Y:
Y.append('int')
if plt in Chi_keys and 'chi' not in Y:
Y.append('chi')
if plt in VLat_keys and 'lat' not in Y:
Y.append('lat')
if plt in VLon_keys and 'lon' not in Y:
Y.append('lon')
if plt in Vadm_keys and 'vadm' not in Y:
Y.append('vadm')
if plt in Vdm_keys and 'vdm' not in Y:
Y.append('vdm')
if file_type == 'pmag_results':
print('available objects for plotting: ', PltObjs)
print('available X plots: ', X)
print('available Y plots: ', Y)
print('available method codes: ', methcodes)
f = open(dir_path + '/.striprc', 'w')
for x in X:
f.write('x:' + x + '\n')
for y in Y:
f.write('y:' + y + '\n')
for m in methcodes:
f.write('m:' + m + '\n')
for obj in PltObjs:
f.write('obj:' + obj + '\n')
sys.exit()
if plotexp == 1:
for lkey in Lat_keys:
for key in list(Results[0].keys()):
if key == lkey:
lat = float(Results[0][lkey])
Xinc = [pmag.pinc(lat), -pmag.pinc(lat)]
break
if Xinc == "":
print('can not plot expected inc for site - lat unknown')
if method != "" and method not in methcodes:
print('your method not available, but these are: ')
print(methcodes)
print('use ', methcodes[0], '? ^D to quit')
if xaxis == 'age':
for akey in Age_keys:
for key in list(Results[0].keys()):
if key == akey:
Xplots.append(key)
Xunits.append(Unit_keys[key])
if xaxis == 'pos':
for dkey in Depth_keys:
for key in list(Results[0].keys()):
if key == dkey:
Xplots.append(key)
if len(Xplots) == 0:
print('desired X axis information not found')
sys.exit()
if xaxis == 'age':
age_unit = Results[0][Xunits[0]]
if len(Xplots) > 1:
print('multiple X axis keys found, using: ', Xplots[xplotind])
for ykey in ykeys:
for key in list(Results[0].keys()):
if key == ykey:
Yplots.append(key)
if len(Yplots) == 0:
print('desired Y axis information not found')
sys.exit()
if len(Yplots) > 1:
print('multiple Y axis keys found, using: ', Yplots[yplotind])
# check if age or depth info
if len(Xplots) == 0:
print("Must have either age or height info to plot ")
sys.exit()
#
# check for variable to plot
#
#
# determine X axis (age or depth)
#
if xaxis == "age":
plotind = "1"
if method == "":
try:
method = methcodes[0]
except IndexError:
method = ""
if xaxis == 'pos':
xlab = "Stratigraphic Height (meters)"
else:
xlab = "Age (" + age_unit + ")"
Xkey = Xplots[xplotind]
Ykey = Yplots[yplotind]
ylab = Ykey
#
# collect the data for plotting
XY = []
isign = 1.
# if float(Results[0][Xkey])/float(Results[-1][Xkey])>0 and float(Results[0][Xkey])<0:
# isign=-1. # x axis all same sign and negative, take positive (e.g.,for depth in core)
# xlab="Stratigraphic Position (meters)"
# else:
# isign=1.
for rec in Results:
if "magic_method_codes" in list(rec.keys()):
meths = rec["magic_method_codes"].split(":")
if method in meths: # make sure it is desired lab treatment step
if obj == 'all' and rec[Xkey].strip() != "":
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
elif rec[Xkey].strip() != "":
name = rec['pmag_result_name'].split()
if obj == 'sit' and "Site" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
if obj == 'sam' and "Sample" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
elif method == "":
if obj == 'all' and rec[Xkey].strip() != "":
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
elif rec[Xkey].strip() != "":
name = rec['pmag_result_name'].split()
if obj == 'sit' and "Site" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
if obj == 'sam' and "Sample" in name:
XY.append([isign * float(rec[Xkey]), float(rec[Ykey])])
else:
print("Something wrong with your plotting choices")
break
XY.sort()
title = ""
if "er_locations_names" in list(Results[0].keys()):
title = Results[0]["er_location_names"]
if "er_locations_name" in list(Results[0].keys()):
title = Results[0]["er_location_name"]
labels = [xlab, ylab, title]
pmagplotlib.plot_init(FIG['strat'], 10, 5)
pmagplotlib.plot_strat(FIG['strat'], XY, labels) # plot them
if plotexp == 1:
pmagplotlib.plot_hs(FIG['strat'], Xinc, 'b', '--')
if yaxis == 'inc' or yaxis == 'lat':
pmagplotlib.plot_hs(FIG['strat'], [0], 'b', '-')
pmagplotlib.plot_hs(FIG['strat'], [-90, 90], 'g', '-')
if pTS == 1:
FIG['ts'] = 2
pmagplotlib.plot_init(FIG['ts'], 10, 5)
pmagplotlib.plot_ts(FIG['ts'], [amin, amax], ts)
files = {}
for key in list(FIG.keys()):
files[key] = key + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
files = {}
files['strat'] = xaxis + '_' + yaxis + '_.' + fmt
files['ts'] = 'ts.' + fmt
titles = {}
titles['strat'] = 'Depth/Time Series Plot'
titles['ts'] = 'Time Series Plot'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plot == 1:
pmagplotlib.save_plots(FIG, files)
else:
pmagplotlib.draw_figs(FIG)
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a":
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
foldtest.py
DESCRIPTION
does a fold test (Tauxe, 2010) on data
INPUT FORMAT
dec inc dip_direction dip
SYNTAX
foldtest.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE file with input data
-F FILE for confidence bounds on fold test
-u ANGLE (circular standard deviation) for uncertainty on bedding poles
-b MIN MAX bounds for quick search of percent untilting [default is -10 to 150%]
-n NB number of bootstrap samples [default is 1000]
-fmt FMT, specify format - default is svg
-sav save figures and quit
INPUT FILE
Dec Inc Dip_Direction Dip in space delimited file
OUTPUT PLOTS
Geographic: is an equal area projection of the input data in
original coordinates
Stratigraphic: is an equal area projection of the input data in
tilt adjusted coordinates
% Untilting: The dashed (red) curves are representative plots of
maximum eigenvalue (tau_1) as a function of untilting
The solid line is the cumulative distribution of the
% Untilting required to maximize tau for all the
bootstrapped data sets. The dashed vertical lines
are 95% confidence bounds on the % untilting that yields
the most clustered result (maximum tau_1).
Command line: prints out the bootstrapped iterations and
finally the confidence bounds on optimum untilting.
If the 95% conf bounds include 0, then a post-tilt magnetization is indicated
If the 95% conf bounds include 100, then a pre-tilt magnetization is indicated
If the 95% conf bounds exclude both 0 and 100, syn-tilt magnetization is
possible as is vertical axis rotation or other pathologies
Geographic: is an equal area projection of the input data in
OPTIONAL OUTPUT FILE:
The output file has the % untilting within the 95% confidence bounds
nd the number of bootstrap samples
"""
kappa = 0
fmt, plot = 'svg', 0
nb = 1000 # number of bootstraps
min, max = -10, 150
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')
outfile = open(sys.argv[ind + 1], 'w')
else:
outfile = ""
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
DIDDs = numpy.loadtxt(file)
else:
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-sav' in sys.argv: plot = 1
if '-b' in sys.argv:
ind = sys.argv.index('-b')
min = int(sys.argv[ind + 1])
max = int(sys.argv[ind + 2])
if '-n' in sys.argv:
ind = sys.argv.index('-n')
nb = int(sys.argv[ind + 1])
if '-u' in sys.argv:
ind = sys.argv.index('-u')
csd = float(sys.argv[ind + 1])
kappa = (81. / csd)**2
#
# get to work
#
PLTS = {'geo': 1, 'strat': 2, 'taus': 3} # make plot dictionary
pmagplotlib.plot_init(PLTS['geo'], 5, 5)
pmagplotlib.plot_init(PLTS['strat'], 5, 5)
pmagplotlib.plot_init(PLTS['taus'], 5, 5)
pmagplotlib.plot_eq(PLTS['geo'], DIDDs, 'Geographic')
D, I = pmag.dotilt_V(DIDDs)
TCs = numpy.array([D, I]).transpose()
pmagplotlib.plot_eq(PLTS['strat'], TCs, 'Stratigraphic')
if not set_env.IS_WIN:
if plot == 0: pmagplotlib.draw_figs(PLTS)
Percs = list(range(min, max))
Cdf, Untilt = [], []
pylab.figure(num=PLTS['taus'])
print('doing ', nb, ' iterations...please be patient.....')
for n in range(
nb): # do bootstrap data sets - plot first 25 as dashed red line
if n % 50 == 0: print(n)
Taus = [] # set up lists for taus
PDs = pmag.pseudo(DIDDs)
if kappa != 0:
for k in range(len(PDs)):
d, i = pmag.fshdev(kappa)
dipdir, dip = pmag.dodirot(d, i, PDs[k][2], PDs[k][3])
PDs[k][2] = dipdir
PDs[k][3] = dip
for perc in Percs:
tilt = numpy.array([1., 1., 1., 0.01 * perc])
D, I = pmag.dotilt_V(PDs * tilt)
TCs = numpy.array([D, I]).transpose()
ppars = pmag.doprinc(TCs) # get principal directions
Taus.append(ppars['tau1'])
if n < 25: pylab.plot(Percs, Taus, 'r--')
Untilt.append(Percs[Taus.index(
numpy.max(Taus))]) # tilt that gives maximum tau
Cdf.append(float(n) / float(nb))
pylab.plot(Percs, Taus, 'k')
pylab.xlabel('% Untilting')
pylab.ylabel('tau_1 (red), CDF (green)')
Untilt.sort() # now for CDF of tilt of maximum tau
pylab.plot(Untilt, Cdf, 'g')
lower = int(.025 * nb)
upper = int(.975 * nb)
pylab.axvline(x=Untilt[lower], ymin=0, ymax=1, linewidth=1, linestyle='--')
pylab.axvline(x=Untilt[upper], ymin=0, ymax=1, linewidth=1, linestyle='--')
tit = '%i - %i %s' % (Untilt[lower], Untilt[upper], 'Percent Unfolding')
print(tit)
print('range of all bootstrap samples: ', Untilt[0], ' - ', Untilt[-1])
pylab.title(tit)
outstring = '%i - %i; %i\n' % (Untilt[lower], Untilt[upper], nb)
if outfile != "": outfile.write(outstring)
files = {}
for key in list(PLTS.keys()):
files[key] = ('foldtest_' + '%s' % (key.strip()[:2]) + '.' + fmt)
if plot == 0:
pmagplotlib.draw_figs(PLTS)
ans = input('S[a]ve all figures, <Return> to quit ')
if ans != 'a':
print("Good bye")
sys.exit()
pmagplotlib.save_plots(PLTS, files)
def main():
"""
NAME
eqarea_ell.py
DESCRIPTION
makes equal area projections from declination/inclination data
and plot ellipses
SYNTAX
eqarea_ell.py -h [command line options]
INPUT
takes space delimited Dec/Inc data
OPTIONS
-h prints help message and quits
-f FILE
-fmt [svg,png,jpg] format for output plots
-sav saves figures and quits
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
"""
FIG={} # plot dictionary
FIG['eq']=1 # eqarea is figure 1
fmt,dist,mode,plot='svg','F',1,0
sym={'lower':['o','r'],'upper':['o','w'],'size':10}
plotE=0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if not set_env.IS_WIN:
pmagplotlib.plot_init(FIG['eq'],5,5)
if '-sav' in sys.argv:plot=1
if '-f' in sys.argv:
ind=sys.argv.index("-f")
title=sys.argv[ind+1]
data=numpy.loadtxt(title).transpose()
if '-ell' in sys.argv:
plotE=1
ind=sys.argv.index('-ell')
ell_type=sys.argv[ind+1]
if ell_type=='F':dist='F'
if ell_type=='K':dist='K'
if ell_type=='B':dist='B'
if ell_type=='Be':dist='BE'
if ell_type=='Bv':
dist='BV'
FIG['bdirs']=2
pmagplotlib.plot_init(FIG['bdirs'],5,5)
if '-fmt' in sys.argv:
ind=sys.argv.index("-fmt")
fmt=sys.argv[ind+1]
DIblock=numpy.array([data[0],data[1]]).transpose()
if len(DIblock)>0:
pmagplotlib.plot_eq_sym(FIG['eq'],DIblock,title,sym)
#if plot==0:pmagplotlib.draw_figs(FIG)
else:
print("no data to plot")
sys.exit()
if plotE==1:
ppars=pmag.doprinc(DIblock) # get principal directions
nDIs,rDIs,npars,rpars=[],[],[],[]
for rec in DIblock:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist=='B': # do on whole dataset
etitle="Bingham confidence ellipse"
bpars=pmag.dobingham(DIblock)
for key in list(bpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(bpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist=='F':
etitle="Fisher confidence cone"
if len(nDIs)>3:
fpars=pmag.fisher_mean(nDIs)
for key in list(fpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(fpars[key]))
mode+=1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign=abs(fpars['inc']) / fpars['inc']
npars.append(fpars['inc']-isign*90.) #Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) #Beta inc
if len(rDIs)>3:
fpars=pmag.fisher_mean(rDIs)
if pmagplotlib.verbose:print("mode ",mode)
for key in list(fpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(fpars[key]))
mode+=1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign=abs(fpars['inc']) / fpars['inc']
rpars.append(fpars['inc']-isign*90.) #Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) #Beta inc
if dist=='K':
etitle="Kent confidence ellipse"
if len(nDIs)>3:
kpars=pmag.dokent(nDIs,len(nDIs))
if pmagplotlib.verbose:print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(kpars[key]))
mode+=1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs)>3:
kpars=pmag.dokent(rDIs,len(rDIs))
if pmagplotlib.verbose:print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(kpars[key]))
mode+=1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if len(nDIs)<10 and len(rDIs)<10:
print('too few data points for bootstrap')
sys.exit()
if dist=='BE':
print('Be patient for bootstrap...')
if len(nDIs)>=10:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
if pmagplotlib.verbose:print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs)>=10:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
if pmagplotlib.verbose:print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and pmagplotlib.verbose:print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and pmagplotlib.verbose:print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
etitle="Bootstrapped confidence ellipse"
elif dist=='BV':
print('Be patient for bootstrap...')
vsym={'lower':['+','k'],'upper':['x','k'],'size':5}
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plot_eq_sym(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors',vsym)
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plot_di_sym(FIG['bdirs'],BrDIs,vsym)
else:
pmagplotlib.plot_eq(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors',vsym)
if dist=='B':
if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plot_conf(FIG['eq'],etitle,[],npars,0)
elif len(nDIs)>3 and dist!='BV':
pmagplotlib.plot_conf(FIG['eq'],etitle,[],npars,0)
if len(rDIs)>3:
pmagplotlib.plot_conf(FIG['eq'],etitle,[],rpars,0)
elif len(rDIs)>3 and dist!='BV':
pmagplotlib.plot_conf(FIG['eq'],etitle,[],rpars,0)
#if plot==0:pmagplotlib.draw_figs(FIG)
if plot==0:pmagplotlib.draw_figs(FIG)
#
files={}
for key in list(FIG.keys()):
files[key]=title+'_'+key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
FIG = pmagplotlib.add_borders(FIG,titles,black,purple)
pmagplotlib.save_plots(FIG,files)
elif plot==0:
ans=input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=="q": sys.exit()
if ans=="a":
pmagplotlib.save_plots(FIG,files)
else:
pmagplotlib.save_plots(FIG,files)
def main():
"""
NAME
revtest_MM1990.py
DESCRIPTION
calculates Watson's V statistic from input files through Monte Carlo simulation in order to test whether normal and reversed populations could have been drawn from a common mean (equivalent to watsonV.py). Also provides the critical angle between the two sample mean directions and the corresponding McFadden and McElhinny (1990) classification.
INPUT FORMAT
takes dec/inc as first two columns in two space delimited files (one file for normal directions, one file for reversed directions).
SYNTAX
revtest_MM1990.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE
-f2 FILE
-P (don't plot the Watson V cdf)
OUTPUT
Watson's V between the two populations and the Monte Carlo Critical Value Vc.
M&M1990 angle, critical angle and classification
Plot of Watson's V CDF from Monte Carlo simulation (red line), V is solid and Vc is dashed.
"""
D1, D2 = [], []
plot = 1
Flip = 1
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-P' in sys.argv: plot = 0
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file1 = sys.argv[ind + 1]
f1 = open(file1, 'r')
for line in f1.readlines():
rec = line.split()
Dec, Inc = float(rec[0]), float(rec[1])
D1.append([Dec, Inc, 1.])
f1.close()
if '-f2' in sys.argv:
ind = sys.argv.index('-f2')
file2 = sys.argv[ind + 1]
f2 = open(file2, 'r')
print("be patient, your computer is doing 5000 simulations...")
for line in f2.readlines():
rec = line.split()
Dec, Inc = float(rec[0]), float(rec[1])
D2.append([Dec, Inc, 1.])
f2.close()
#take the antipode for the directions in file 2
D2_flip = []
for rec in D2:
d, i = (rec[0] - 180.) % 360., -rec[1]
D2_flip.append([d, i, 1.])
pars_1 = pmag.fisher_mean(D1)
pars_2 = pmag.fisher_mean(D2_flip)
cart_1 = pmag.dir2cart([pars_1["dec"], pars_1["inc"], pars_1["r"]])
cart_2 = pmag.dir2cart([pars_2['dec'], pars_2['inc'], pars_2["r"]])
Sw = pars_1['k'] * pars_1['r'] + pars_2['k'] * pars_2['r'] # k1*r1+k2*r2
xhat_1 = pars_1['k'] * cart_1[0] + pars_2['k'] * cart_2[0] # k1*x1+k2*x2
xhat_2 = pars_1['k'] * cart_1[1] + pars_2['k'] * cart_2[1] # k1*y1+k2*y2
xhat_3 = pars_1['k'] * cart_1[2] + pars_2['k'] * cart_2[2] # k1*z1+k2*z2
Rw = numpy.sqrt(xhat_1**2 + xhat_2**2 + xhat_3**2)
V = 2 * (Sw - Rw)
#
#keep weighted sum for later when determining the "critical angle" let's save it as Sr (notation of McFadden and McElhinny, 1990)
#
Sr = Sw
#
# do monte carlo simulation of datasets with same kappas, but common mean
#
counter, NumSims = 0, 5000
Vp = [] # set of Vs from simulations
for k in range(NumSims):
#
# get a set of N1 fisher distributed vectors with k1, calculate fisher stats
#
Dirp = []
for i in range(pars_1["n"]):
Dirp.append(pmag.fshdev(pars_1["k"]))
pars_p1 = pmag.fisher_mean(Dirp)
#
# get a set of N2 fisher distributed vectors with k2, calculate fisher stats
#
Dirp = []
for i in range(pars_2["n"]):
Dirp.append(pmag.fshdev(pars_2["k"]))
pars_p2 = pmag.fisher_mean(Dirp)
#
# get the V for these
#
Vk = pmag.vfunc(pars_p1, pars_p2)
Vp.append(Vk)
#
# sort the Vs, get Vcrit (95th percentile one)
#
Vp.sort()
k = int(.95 * NumSims)
Vcrit = Vp[k]
#
# equation 18 of McFadden and McElhinny, 1990 calculates the critical value of R (Rwc)
#
Rwc = Sr - (old_div(Vcrit, 2))
#
#following equation 19 of McFadden and McElhinny (1990) the critical angle is calculated.
#
k1 = pars_1['k']
k2 = pars_2['k']
R1 = pars_1['r']
R2 = pars_2['r']
critical_angle = numpy.degrees(
numpy.arccos(
old_div(((Rwc**2) - ((k1 * R1)**2) - ((k2 * R2)**2)),
(2 * k1 * R1 * k2 * R2))))
D1_mean = (pars_1['dec'], pars_1['inc'])
D2_mean = (pars_2['dec'], pars_2['inc'])
angle = pmag.angle(D1_mean, D2_mean)
#
# print the results of the test
#
print("")
print("Results of Watson V test: ")
print("")
print("Watson's V: " '%.1f' % (V))
print("Critical value of V: " '%.1f' % (Vcrit))
if V < Vcrit:
print(
'"Pass": Since V is less than Vcrit, the null hypothesis that the two populations are drawn from distributions that share a common mean direction (antipodal to one another) cannot be rejected.'
)
elif V > Vcrit:
print(
'"Fail": Since V is greater than Vcrit, the two means can be distinguished at the 95% confidence level.'
)
print("")
print("M&M1990 classification:")
print("")
print("Angle between data set means: " '%.1f' % (angle))
print("Critical angle of M&M1990: " '%.1f' % (critical_angle))
if V > Vcrit:
print("")
elif V < Vcrit:
if critical_angle < 5:
print(
"The McFadden and McElhinny (1990) classification for this test is: 'A'"
)
elif critical_angle < 10:
print(
"The McFadden and McElhinny (1990) classification for this test is: 'B'"
)
elif critical_angle < 20:
print(
"The McFadden and McElhinny (1990) classification for this test is: 'C'"
)
else:
print(
"The McFadden and McElhinny (1990) classification for this test is: 'INDETERMINATE;"
)
if plot == 1:
CDF = {'cdf': 1}
pmagplotlib.plot_init(CDF['cdf'], 5, 5)
p1 = pmagplotlib.plot_cdf(CDF['cdf'], Vp, "Watson's V", 'r', "")
p2 = pmagplotlib.plot_vs(CDF['cdf'], [V], 'g', '-')
p3 = pmagplotlib.plot_vs(CDF['cdf'], [Vp[k]], 'b', '--')
pmagplotlib.draw_figs(CDF)
files, fmt = {}, 'svg'
if file2 != "":
files['cdf'] = 'WatsonsV_' + file1 + '_' + file2 + '.' + fmt
else:
files['cdf'] = 'WatsonsV_' + file1 + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['cdf'] = 'Cumulative Distribution'
CDF = pmagplotlib.add_borders(CDF, titles, black, purple)
pmagplotlib.save_plots(CDF, files)
else:
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a": pmagplotlib.save_plots(CDF, files)
def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
PLT = 1
plots = 0
user, meas_file = "", "magic_measurements.txt"
pltspec = ""
dir_path = '.'
fmt = 'png'
verbose = pmagplotlib.verbose
version_num = pmag.get_version()
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind+1]
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = args[ind+1]
if '-f' in args:
ind = args.index("-f")
meas_file = args[ind+1]
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind+1]
verbose = 0
plots = 1
if '-fmt' in args:
ind = args.index("-fmt")
fmt = args[ind+1]
meas_file = dir_path+'/'+meas_file
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(main.__doc__)
print('bad file')
sys.exit()
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs, RemRecs = [], []
HDD = {}
HDD['hyst'] = 1
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
#
# get list of unique experiment names and specimen names
#
experiment_names, sids = [], []
hyst_data = pmag.get_dictitem(
meas_data, 'magic_method_codes', 'LP-HYS', 'has') # get all hysteresis data
for rec in hyst_data:
if 'er_synthetic_name' in rec.keys() and rec['er_synthetic_name'] != "":
rec['er_specimen_name'] = rec['er_synthetic_name']
if rec['magic_experiment_name'] not in experiment_names:
experiment_names.append(rec['magic_experiment_name'])
if rec['er_specimen_name'] not in sids:
sids.append(rec['er_specimen_name'])
if 'measurement_temp' not in rec.keys():
# assume room T measurement unless otherwise specified
rec['measurement_temp'] = '300'
#
k = 0
if pltspec != "":
k = sids.index(pltspec)
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
while k < len(sids):
locname, site, sample, synth = '', '', '', ''
s = sids[k]
hmeths = []
if verbose:
print(s, k+1, 'out of ', len(sids))
#
#
B, M = [], [] # B,M for hysteresis, Bdcd,Mdcd for irm-dcd data
# get all measurements for this specimen
spec = pmag.get_dictitem(hyst_data, 'er_specimen_name', s, 'T')
if 'er_location_name' in spec[0].keys():
locname = spec[0]['er_location_name']
if 'er_site_name' in spec[0].keys():
site = spec[0]['er_site_name']
if 'er_sample_name' in spec[0].keys():
sample = spec[0]['er_sample_name']
if 'er_synthetic_name' in spec[0].keys():
synth = spec[0]['er_synthetic_name']
for m in intlist:
# get all non-blank data for this specimen
meas_data = pmag.get_dictitem(spec, m, '', 'F')
if len(meas_data) > 0:
break
c = ['k-', 'b-', 'c-', 'g-', 'm-', 'r-', 'y-']
cnum = 0
if len(meas_data) > 0:
Temps = []
xlab, ylab, title = '', '', ''
for rec in meas_data:
if rec['measurement_temp'] not in Temps:
Temps.append(rec['measurement_temp'])
for t in Temps:
print('working on t: ', t)
t_data = pmag.get_dictitem(
meas_data, 'measurement_temp', t, 'T')
B, M = [], []
for rec in t_data:
B.append(float(rec['measurement_lab_field_dc']))
M.append(float(rec[m]))
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = 'Field (T)'
ylab = m
title = 'Hysteresis: '+s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD['hyst'])
pmagplotlib.plot_xy(
HDD['hyst'], B, M, sym=c[cnum], xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plot_xy(HDD['hyst'], [
1.1*B.min(), 1.1*B.max()], [0, 0], sym='k-', xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plot_xy(HDD['hyst'], [0, 0], [
1.1*M.min(), 1.1*M.max()], sym='k-', xlab=xlab, ylab=ylab, title=title)
if verbose:
pmagplotlib.draw_figs(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
files = {}
for key in HDD.keys():
if pmagplotlib.isServer: # use server plot naming convention
if synth == '':
filename = "LO:_"+locname+'_SI:_'+site + \
'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
filename = 'SY:_'+synth+'_TY:_'+key+'_.'+fmt
files[key] = filename
else: # use more readable plot naming convention
if synth == '':
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
else:
filename = synth+'_'+key+'.fmt'
files[key] = filename
pmagplotlib.save_plots(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.draw_figs(HDD)
ans = raw_input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans == "a":
files = {}
for key in HDD.keys():
if pmagplotlib.isServer:
print('server')
files[key] = "LO:_"+locname+'_SI:_'+site + \
'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
print('not server')
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
print('files', files)
pmagplotlib.save_plots(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = raw_input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = raw_input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1
def main():
"""
NAME
hysteresis_magic.py
DESCRIPTION
calculates hystereis parameters and saves them in rmag_hystereis format file
makes plots if option selected
SYNTAX
hysteresis_magic.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specify input file, default is agm_measurements.txt
-fh: specify rmag_hysteresis.txt input file
-F: specify output file, default is rmag_hysteresis.txt
-P: do not make the plots
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
PLT = 1
plots = 0
user, meas_file, rmag_out, rmag_file = "", "agm_measurements.txt", "rmag_hysteresis.txt", ""
pltspec = ""
dir_path = '.'
fmt = 'svg'
verbose = pmagplotlib.verbose
version_num = pmag.get_version()
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind+1]
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = args[ind+1]
if '-f' in args:
ind = args.index("-f")
meas_file = args[ind+1]
if '-F' in args:
ind = args.index("-F")
rmag_out = args[ind+1]
if '-fh' in args:
ind = args.index("-fh")
rmag_file = args[ind+1]
rmag_file = dir_path+'/'+rmag_file
if '-P' in args:
PLT = 0
irm_init, imag_init = -1, -1
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind+1]
verbose = 0
plots = 1
if '-fmt' in args:
ind = args.index("-fmt")
fmt = args[ind+1]
rmag_out = dir_path+'/'+rmag_out
meas_file = dir_path+'/'+meas_file
rmag_rem = dir_path+"/rmag_remanence.txt"
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(main.__doc__)
print('bad file')
sys.exit()
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs, RemRecs = [], []
HDD = {}
if verbose:
if verbose and PLT:
print("Plots may be on top of each other - use mouse to place ")
if PLT:
HDD['hyst'], HDD['deltaM'], HDD['DdeltaM'] = 1, 2, 3
pmagplotlib.plot_init(HDD['DdeltaM'], 5, 5)
pmagplotlib.plot_init(HDD['deltaM'], 5, 5)
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
imag_init = 0
irm_init = 0
else:
HDD['hyst'], HDD['deltaM'], HDD['DdeltaM'], HDD['irm'], HDD['imag'] = 0, 0, 0, 0, 0
#
if rmag_file != "":
hyst_data, file_type = pmag.magic_read(rmag_file)
#
# get list of unique experiment names and specimen names
#
experiment_names, sids = [], []
for rec in meas_data:
meths = rec['magic_method_codes'].split(':')
methods = []
for meth in meths:
methods.append(meth.strip())
if 'LP-HYS' in methods:
if 'er_synthetic_name' in list(rec.keys()) and rec['er_synthetic_name'] != "":
rec['er_specimen_name'] = rec['er_synthetic_name']
if rec['magic_experiment_name'] not in experiment_names:
experiment_names.append(rec['magic_experiment_name'])
if rec['er_specimen_name'] not in sids:
sids.append(rec['er_specimen_name'])
#
k = 0
locname = ''
if pltspec != "":
k = sids.index(pltspec)
print(sids[k])
while k < len(sids):
s = sids[k]
if verbose and PLT:
print(s, k+1, 'out of ', len(sids))
#
#
# B,M for hysteresis, Bdcd,Mdcd for irm-dcd data
B, M, Bdcd, Mdcd = [], [], [], []
Bimag, Mimag = [], [] # Bimag,Mimag for initial magnetization curves
first_dcd_rec, first_rec, first_imag_rec = 1, 1, 1
for rec in meas_data:
methcodes = rec['magic_method_codes'].split(':')
meths = []
for meth in methcodes:
meths.append(meth.strip())
if rec['er_specimen_name'] == s and "LP-HYS" in meths:
B.append(float(rec['measurement_lab_field_dc']))
M.append(float(rec['measurement_magn_moment']))
if first_rec == 1:
e = rec['magic_experiment_name']
HystRec = {}
first_rec = 0
if "er_location_name" in list(rec.keys()):
HystRec["er_location_name"] = rec["er_location_name"]
locname = rec['er_location_name'].replace('/', '-')
if "er_sample_name" in list(rec.keys()):
HystRec["er_sample_name"] = rec["er_sample_name"]
if "er_site_name" in list(rec.keys()):
HystRec["er_site_name"] = rec["er_site_name"]
if "er_synthetic_name" in list(rec.keys()) and rec['er_synthetic_name'] != "":
HystRec["er_synthetic_name"] = rec["er_synthetic_name"]
else:
HystRec["er_specimen_name"] = rec["er_specimen_name"]
if rec['er_specimen_name'] == s and "LP-IRM-DCD" in meths:
Bdcd.append(float(rec['treatment_dc_field']))
Mdcd.append(float(rec['measurement_magn_moment']))
if first_dcd_rec == 1:
RemRec = {}
irm_exp = rec['magic_experiment_name']
first_dcd_rec = 0
if "er_location_name" in list(rec.keys()):
RemRec["er_location_name"] = rec["er_location_name"]
if "er_sample_name" in list(rec.keys()):
RemRec["er_sample_name"] = rec["er_sample_name"]
if "er_site_name" in list(rec.keys()):
RemRec["er_site_name"] = rec["er_site_name"]
if "er_synthetic_name" in list(rec.keys()) and rec['er_synthetic_name'] != "":
RemRec["er_synthetic_name"] = rec["er_synthetic_name"]
else:
RemRec["er_specimen_name"] = rec["er_specimen_name"]
if rec['er_specimen_name'] == s and "LP-IMAG" in meths:
if first_imag_rec == 1:
imag_exp = rec['magic_experiment_name']
first_imag_rec = 0
Bimag.append(float(rec['measurement_lab_field_dc']))
Mimag.append(float(rec['measurement_magn_moment']))
#
# now plot the hysteresis curve
#
if len(B) > 0:
hmeths = []
for meth in meths:
hmeths.append(meth)
hpars = pmagplotlib.plot_hdd(HDD, B, M, e)
if verbose and PLT:
pmagplotlib.draw_figs(HDD)
#
# get prior interpretations from hyst_data
if rmag_file != "":
hpars_prior = {}
for rec in hyst_data:
if rec['magic_experiment_names'] == e:
if rec['hysteresis_bcr'] != "" and rec['hysteresis_mr_moment'] != "":
hpars_prior['hysteresis_mr_moment'] = rec['hysteresis_mr_moment']
hpars_prior['hysteresis_ms_moment'] = rec['hysteresis_ms_moment']
hpars_prior['hysteresis_bc'] = rec['hysteresis_bc']
hpars_prior['hysteresis_bcr'] = rec['hysteresis_bcr']
break
if verbose:
pmagplotlib.plot_hpars(HDD, hpars_prior, 'ro')
else:
if verbose:
pmagplotlib.plot_hpars(HDD, hpars, 'bs')
HystRec['hysteresis_mr_moment'] = hpars['hysteresis_mr_moment']
HystRec['hysteresis_ms_moment'] = hpars['hysteresis_ms_moment']
HystRec['hysteresis_bc'] = hpars['hysteresis_bc']
HystRec['hysteresis_bcr'] = hpars['hysteresis_bcr']
HystRec['hysteresis_xhf'] = hpars['hysteresis_xhf']
HystRec['magic_experiment_names'] = e
HystRec['magic_software_packages'] = version_num
if hpars["magic_method_codes"] not in hmeths:
hmeths.append(hpars["magic_method_codes"])
methods = ""
for meth in hmeths:
methods = methods+meth.strip()+":"
HystRec["magic_method_codes"] = methods[:-1]
HystRec["er_citation_names"] = "This study"
HystRecs.append(HystRec)
#
if len(Bdcd) > 0:
rmeths = []
for meth in meths:
rmeths.append(meth)
if verbose and PLT:
print('plotting IRM')
if irm_init == 0:
HDD['irm'] = 5
pmagplotlib.plot_init(HDD['irm'], 5, 5)
irm_init = 1
rpars = pmagplotlib.plot_irm(HDD['irm'], Bdcd, Mdcd, irm_exp)
RemRec['remanence_mr_moment'] = rpars['remanence_mr_moment']
RemRec['remanence_bcr'] = rpars['remanence_bcr']
RemRec['magic_experiment_names'] = irm_exp
if rpars["magic_method_codes"] not in meths:
meths.append(rpars["magic_method_codes"])
methods = ""
for meth in rmeths:
methods = methods+meth.strip()+":"
RemRec["magic_method_codes"] = methods[:-1]
RemRec["er_citation_names"] = "This study"
RemRecs.append(RemRec)
else:
if irm_init:
pmagplotlib.clearFIG(HDD['irm'])
if len(Bimag) > 0:
if verbose:
print('plotting initial magnetization curve')
# first normalize by Ms
Mnorm = []
for m in Mimag:
Mnorm.append(m / float(hpars['hysteresis_ms_moment']))
if imag_init == 0:
HDD['imag'] = 4
pmagplotlib.plot_init(HDD['imag'], 5, 5)
imag_init = 1
pmagplotlib.plot_imag(HDD['imag'], Bimag, Mnorm, imag_exp)
else:
if imag_init:
pmagplotlib.clearFIG(HDD['imag'])
#
files = {}
if plots:
if pltspec != "":
s = pltspec
files = {}
for key in list(HDD.keys()):
files[key] = locname+'_'+s+'_'+key+'.'+fmt
pmagplotlib.save_plots(HDD, files)
if pltspec != "":
sys.exit()
if verbose and PLT:
pmagplotlib.draw_figs(HDD)
ans = input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans == "a":
files = {}
for key in list(HDD.keys()):
files[key] = locname+'_'+s+'_'+key+'.'+fmt
pmagplotlib.save_plots(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0 and len(Bdcd) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1
if rmag_out == "" and ans == 's' and verbose:
really = input(
" Do you want to overwrite the existing rmag_hystersis.txt file? 1/[0] ")
if really == "":
print('i thought not - goodbye')
sys.exit()
rmag_out = "rmag_hysteresis.txt"
if len(HystRecs) > 0:
pmag.magic_write(rmag_out, HystRecs, "rmag_hysteresis")
if verbose:
print("hysteresis parameters saved in ", rmag_out)
if len(RemRecs) > 0:
pmag.magic_write(rmag_rem, RemRecs, "rmag_remanence")
if verbose:
print("remanence parameters saved in ", rmag_rem)
def main():
"""
NAME
foldtest.py
DESCRIPTION
does a fold test (Tauxe, 2010) on data
INPUT FORMAT
dec inc dip_direction dip
SYNTAX
foldtest.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE file with input data
-F FILE for confidence bounds on fold test
-u ANGLE (circular standard deviation) for uncertainty on bedding poles
-b MIN MAX bounds for quick search of percent untilting [default is -10 to 150%]
-n NB number of bootstrap samples [default is 1000]
-fmt FMT, specify format - default is svg
-sav save figures and quit
INPUT FILE
Dec Inc Dip_Direction Dip in space delimited file
OUTPUT PLOTS
Geographic: is an equal area projection of the input data in
original coordinates
Stratigraphic: is an equal area projection of the input data in
tilt adjusted coordinates
% Untilting: The dashed (red) curves are representative plots of
maximum eigenvalue (tau_1) as a function of untilting
The solid line is the cumulative distribution of the
% Untilting required to maximize tau for all the
bootstrapped data sets. The dashed vertical lines
are 95% confidence bounds on the % untilting that yields
the most clustered result (maximum tau_1).
Command line: prints out the bootstrapped iterations and
finally the confidence bounds on optimum untilting.
If the 95% conf bounds include 0, then a post-tilt magnetization is indicated
If the 95% conf bounds include 100, then a pre-tilt magnetization is indicated
If the 95% conf bounds exclude both 0 and 100, syn-tilt magnetization is
possible as is vertical axis rotation or other pathologies
Geographic: is an equal area projection of the input data in
OPTIONAL OUTPUT FILE:
The output file has the % untilting within the 95% confidence bounds
nd the number of bootstrap samples
"""
kappa=0
fmt,plot='svg',0
nb=1000 # number of bootstraps
min,max=-10,150
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')
outfile=open(sys.argv[ind+1],'w')
else:
outfile=""
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
DIDDs=numpy.loadtxt(file)
else:
print(main.__doc__)
sys.exit()
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-sav' in sys.argv:plot=1
if '-b' in sys.argv:
ind=sys.argv.index('-b')
min=int(sys.argv[ind+1])
max=int(sys.argv[ind+2])
if '-n' in sys.argv:
ind=sys.argv.index('-n')
nb=int(sys.argv[ind+1])
if '-u' in sys.argv:
ind=sys.argv.index('-u')
csd=float(sys.argv[ind+1])
kappa=(81. / csd)**2
#
# get to work
#
PLTS={'geo':1,'strat':2,'taus':3} # make plot dictionary
pmagplotlib.plot_init(PLTS['geo'],5,5)
pmagplotlib.plot_init(PLTS['strat'],5,5)
pmagplotlib.plot_init(PLTS['taus'],5,5)
pmagplotlib.plot_eq(PLTS['geo'],DIDDs,'Geographic')
D,I=pmag.dotilt_V(DIDDs)
TCs=numpy.array([D,I]).transpose()
pmagplotlib.plot_eq(PLTS['strat'],TCs,'Stratigraphic')
if not set_env.IS_WIN:
if plot==0:pmagplotlib.draw_figs(PLTS)
Percs=list(range(min,max))
Cdf,Untilt=[],[]
pylab.figure(num=PLTS['taus'])
print('doing ',nb,' iterations...please be patient.....')
for n in range(nb): # do bootstrap data sets - plot first 25 as dashed red line
if n%50==0:print(n)
Taus=[] # set up lists for taus
PDs=pmag.pseudo(DIDDs)
if kappa!=0:
for k in range(len(PDs)):
d,i=pmag.fshdev(kappa)
dipdir,dip=pmag.dodirot(d,i,PDs[k][2],PDs[k][3])
PDs[k][2]=dipdir
PDs[k][3]=dip
for perc in Percs:
tilt=numpy.array([1.,1.,1.,0.01*perc])
D,I=pmag.dotilt_V(PDs*tilt)
TCs=numpy.array([D,I]).transpose()
ppars=pmag.doprinc(TCs) # get principal directions
Taus.append(ppars['tau1'])
if n<25:pylab.plot(Percs,Taus,'r--')
Untilt.append(Percs[Taus.index(numpy.max(Taus))]) # tilt that gives maximum tau
Cdf.append(float(n) / float(nb))
pylab.plot(Percs,Taus,'k')
pylab.xlabel('% Untilting')
pylab.ylabel('tau_1 (red), CDF (green)')
Untilt.sort() # now for CDF of tilt of maximum tau
pylab.plot(Untilt,Cdf,'g')
lower=int(.025*nb)
upper=int(.975*nb)
pylab.axvline(x=Untilt[lower],ymin=0,ymax=1,linewidth=1,linestyle='--')
pylab.axvline(x=Untilt[upper],ymin=0,ymax=1,linewidth=1,linestyle='--')
tit= '%i - %i %s'%(Untilt[lower],Untilt[upper],'Percent Unfolding')
print(tit)
print('range of all bootstrap samples: ', Untilt[0], ' - ', Untilt[-1])
pylab.title(tit)
outstring= '%i - %i; %i\n'%(Untilt[lower],Untilt[upper],nb)
if outfile!="":outfile.write(outstring)
files={}
for key in list(PLTS.keys()):
files[key]=('foldtest_'+'%s'%(key.strip()[:2])+'.'+fmt)
if plot==0:
pmagplotlib.draw_figs(PLTS)
ans= input('S[a]ve all figures, <Return> to quit ')
if ans!='a':
print("Good bye")
sys.exit()
pmagplotlib.save_plots(PLTS,files)
def main():
"""
NAME
lowrie.py
DESCRIPTION
plots intensity decay curves for Lowrie experiments
SYNTAX
lowrie -h [command line options]
INPUT
takes SIO formatted input files
OPTIONS
-h prints help message and quits
-f FILE: specify input file
-N do not normalize by maximum magnetization
-fmt [svg, pdf, eps, png] specify fmt, default is svg
-sav save plots and quit
"""
fmt, plot = 'svg', 0
FIG = {} # plot dictionary
FIG['lowrie'] = 1 # demag is figure 1
pmagplotlib.plot_init(FIG['lowrie'], 6, 6)
norm = 1 # default is to normalize by maximum axis
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-N' in sys.argv:
norm = 0 # don't normalize
if '-sav' in sys.argv:
plot = 1 # don't normalize
if '-fmt' in sys.argv: # sets input filename
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if '-f' in sys.argv: # sets input filename
ind = sys.argv.index("-f")
in_file = sys.argv[ind + 1]
else:
print(main.__doc__)
print('you must supply a file name')
sys.exit()
else:
print(main.__doc__)
print('you must supply a file name')
sys.exit()
data = pmag.open_file(in_file)
PmagRecs = [] # set up a list for the results
keys = ['specimen', 'treatment', 'csd', 'M', 'dec', 'inc']
for line in data:
PmagRec = {}
rec = line.replace('\n', '').split()
for k in range(len(keys)):
PmagRec[keys[k]] = rec[k]
PmagRecs.append(PmagRec)
specs = pmag.get_dictkey(PmagRecs, 'specimen', '')
sids = []
for spec in specs:
if spec not in sids:
sids.append(spec) # get list of unique specimen names
for spc in sids: # step through the specimen names
pmagplotlib.plot_init(FIG['lowrie'], 6, 6)
print(spc)
specdata = pmag.get_dictitem(
PmagRecs, 'specimen', spc, 'T') # get all this one's data
DIMs, Temps = [], []
for dat in specdata: # step through the data
DIMs.append([float(dat['dec']), float(
dat['inc']), float(dat['M']) * 1e-3])
Temps.append(float(dat['treatment']))
carts = pmag.dir2cart(DIMs).transpose()
# if norm==1: # want to normalize
# nrm=max(max(abs(carts[0])),max(abs(carts[1])),max(abs(carts[2]))) # by maximum of x,y,z values
# ylab="M/M_max"
if norm == 1: # want to normalize
nrm = (DIMs[0][2]) # normalize by NRM
ylab = "M/M_o"
else:
nrm = 1. # don't normalize
ylab = "Magnetic moment (Am^2)"
xlab = "Temperature (C)"
pmagplotlib.plot_xy(FIG['lowrie'], Temps, old_div(
abs(carts[0]), nrm), sym='r-')
pmagplotlib.plot_xy(FIG['lowrie'], Temps, old_div(
abs(carts[0]), nrm), sym='ro') # X direction
pmagplotlib.plot_xy(FIG['lowrie'], Temps, old_div(
abs(carts[1]), nrm), sym='c-')
pmagplotlib.plot_xy(FIG['lowrie'], Temps, old_div(
abs(carts[1]), nrm), sym='cs') # Y direction
pmagplotlib.plot_xy(FIG['lowrie'], Temps, old_div(
abs(carts[2]), nrm), sym='k-')
pmagplotlib.plot_xy(FIG['lowrie'], Temps, old_div(
abs(carts[2]), nrm), sym='k^', title=spc, xlab=xlab, ylab=ylab) # Z direction
files = {'lowrie': 'lowrie:_' + spc + '_.' + fmt}
if plot == 0:
pmagplotlib.draw_figs(FIG)
ans = input('S[a]ve figure? [q]uit, <return> to continue ')
if ans == 'a':
pmagplotlib.save_plots(FIG, files)
elif ans == 'q':
sys.exit()
else:
pmagplotlib.save_plots(FIG, files)
pmagplotlib.clearFIG(FIG['lowrie'])
def main():
"""
NAME
fishqq.py
DESCRIPTION
makes qq plot from dec,inc input data
INPUT FORMAT
takes dec/inc pairs in space delimited file
SYNTAX
fishqq.py [command line options]
OPTIONS
-h help message
-f FILE, specify file on command line
-F FILE, specify output file for statistics
-sav save and quit [saves as input file name plus fmt extension]
-fmt specify format for output [png, eps, svg, pdf]
OUTPUT:
Dec Inc N Mu Mu_crit Me Me_crit Y/N
where direction is the principal component and Y/N is Fisherian or not
separate lines for each mode with N >=10 (N and R)
"""
fmt,plot='svg',0
outfile=""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
elif '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
data=f.readlines()
if '-F' in sys.argv:
ind=sys.argv.index('-F')
outfile=open(sys.argv[ind+1],'w') # open output file
if '-sav' in sys.argv: plot=1
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
DIs,nDIs,rDIs= [],[],[] # set up list for data
for line in data: # read in the data from standard input
if '\t' in line:
rec=line.split('\t') # split each line on space to get records
else:
rec=line.split() # split each line on space to get records
DIs.append([float(rec[0]),float(rec[1])]) # append data to Inc
# split into two modes
ppars=pmag.doprinc(DIs) # get principal directions
for rec in DIs:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
#
if len(rDIs) >=10 or len(nDIs) >=10:
D1,I1=[],[]
QQ={'unf1':1,'exp1':2}
pmagplotlib.plot_init(QQ['unf1'],5,5)
pmagplotlib.plot_init(QQ['exp1'],5,5)
if len(nDIs) < 10:
ppars=pmag.doprinc(rDIs) # get principal directions
Drbar,Irbar=ppars['dec']-180.,-ppars['inc']
Nr=len(rDIs)
for di in rDIs:
d,irot=pmag.dotilt(di[0],di[1],Drbar-180.,90.-Irbar) # rotate to mean
drot=d-180.
if drot<0:drot=drot+360.
D1.append(drot)
I1.append(irot)
Dtit='Mode 2 Declinations'
Itit='Mode 2 Inclinations'
else:
ppars=pmag.doprinc(nDIs) # get principal directions
Dnbar,Inbar=ppars['dec'],ppars['inc']
Nn=len(nDIs)
for di in nDIs:
d,irot=pmag.dotilt(di[0],di[1],Dnbar-180.,90.-Inbar) # rotate to mean
drot=d-180.
if drot<0:drot=drot+360.
D1.append(drot)
I1.append(irot)
Dtit='Mode 1 Declinations'
Itit='Mode 1 Inclinations'
Mu_n,Mu_ncr=pmagplotlib.plot_qq_unf(QQ['unf1'],D1,Dtit) # make plot
Me_n,Me_ncr=pmagplotlib.plot_qq_exp(QQ['exp1'],I1,Itit) # make plot
#print Mu_n,Mu_ncr,Me_n, Me_ncr
if outfile!="":
# Dec Inc N Mu Mu_crit Me Me_crit Y/N
if Mu_n<=Mu_ncr and Me_n<=Me_ncr:
F='Y'
else:
F='N'
outstring='%7.1f %7.1f %i %5.3f %5.3f %5.3f %5.3f %s \n'%(Dnbar,Inbar,Nn,Mu_n,Mu_ncr,Me_n,Me_ncr,F)
outfile.write(outstring)
else:
print('you need N> 10 for at least one mode')
sys.exit()
if len(rDIs)>10 and len(nDIs)>10:
D2,I2=[],[]
QQ['unf2']=3
QQ['exp2']=4
pmagplotlib.plot_init(QQ['unf2'],5,5)
pmagplotlib.plot_init(QQ['exp2'],5,5)
ppars=pmag.doprinc(rDIs) # get principal directions
Drbar,Irbar=ppars['dec']-180.,-ppars['inc']
Nr=len(rDIs)
for di in rDIs:
d,irot=pmag.dotilt(di[0],di[1],Drbar-180.,90.-Irbar) # rotate to mean
drot=d-180.
if drot<0:drot=drot+360.
D2.append(drot)
I2.append(irot)
Dtit='Mode 2 Declinations'
Itit='Mode 2 Inclinations'
Mu_r,Mu_rcr=pmagplotlib.plot_qq_unf(QQ['unf2'],D2,Dtit) # make plot
Me_r,Me_rcr=pmagplotlib.plot_qq_exp(QQ['exp2'],I2,Itit) # make plot
if outfile!="":
# Dec Inc N Mu Mu_crit Me Me_crit Y/N
if Mu_r<=Mu_rcr and Me_r<=Me_rcr:
F='Y'
else:
F='N'
outstring='%7.1f %7.1f %i %5.3f %5.3f %5.3f %5.3f %s \n'%(Drbar,Irbar,Nr,Mu_r,Mu_rcr,Me_r,Me_rcr,F)
outfile.write(outstring)
files={}
for key in list(QQ.keys()):
files[key]=file+'_'+key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(QQ,files)
elif plot==1:
pmagplotlib.save_plots(QQ,files)
else:
pmagplotlib.draw_figs(QQ)
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.save_plots(QQ,files)
def main():
"""
NAME
site_edit_magic.py
DESCRIPTION
makes equal area projections site by site
from pmag_specimens.txt file with
Fisher confidence ellipse using McFadden and McElhinny (1988)
technique for combining lines and planes
allows testing and reject specimens for bad orientations
SYNTAX
site_edit_magic.py [command line options]
OPTIONS
-h: prints help and quits
-f: specify pmag_specimen format file, default is pmag_specimens.txt
-fsa: specify er_samples.txt file
-exc: use existing pmag_criteria.txt file
-N: reset all sample flags to good
OUPUT
edited er_samples.txt file
"""
dir_path='.'
FIG={} # plot dictionary
FIG['eqarea']=1 # eqarea is figure 1
in_file='pmag_specimens.txt'
sampfile='er_samples.txt'
out_file=""
fmt,plot='svg',1
Crits=""
M,N=180.,1
repeat=''
renew=0
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]
if '-f' in sys.argv:
ind=sys.argv.index("-f")
in_file=sys.argv[ind+1]
if '-fsa' in sys.argv:
ind=sys.argv.index("-fsa")
sampfile=sys.argv[ind+1]
if '-exc' in sys.argv:
Crits,file_type=pmag.magic_read(dir_path+'/pmag_criteria.txt')
for crit in Crits:
if crit['pmag_criteria_code']=='DE-SPEC':
M=float(crit['specimen_mad'])
N=float(crit['specimen_n'])
if '-fmt' in sys.argv:
ind=sys.argv.index("-fmt")
fmt=sys.argv[ind+1]
if '-N' in sys.argv: renew=1
#
if in_file[0]!="/":in_file=dir_path+'/'+in_file
if sampfile[0]!="/":sampfile=dir_path+'/'+sampfile
crd='s'
Specs,file_type=pmag.magic_read(in_file)
if file_type!='pmag_specimens':
print(' bad pmag_specimen input file')
sys.exit()
Samps,file_type=pmag.magic_read(sampfile)
if file_type!='er_samples':
print(' bad er_samples input file')
sys.exit()
SO_methods=[]
for rec in Samps:
if 'sample_orientation_flag' not in list(rec.keys()): rec['sample_orientation_flag']='g'
if 'sample_description' not in list(rec.keys()): rec['sample_description']=''
if renew==1:
rec['sample_orientation_flag']='g'
description=rec['sample_description']
if '#' in description:
newdesc=""
c=0
while description[c]!='#' and c<len(description)-1: # look for first pound sign
newdesc=newdesc+description[c]
c+=1
while description[c]=='#':
c+=1# skip first set of pound signs
while description[c]!='#':c+=1 # find second set of pound signs
while description[c]=='#' and c<len(description)-1:c+=1 # skip second set of pound signs
while c<len(description)-1: # look for first pound sign
newdesc=newdesc+description[c]
c+=1
rec['sample_description']=newdesc # edit out old comment about orientations
if "magic_method_codes" in rec:
methlist=rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth.strip() and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods: SO_methods.append(meth.strip())
pmag.magic_write(sampfile,Samps,'er_samples')
SO_priorities=pmag.set_priorities(SO_methods,0)
sitelist=[]
for rec in Specs:
if rec['er_site_name'] not in sitelist: sitelist.append(rec['er_site_name'])
sitelist.sort()
EQ={}
EQ['eqarea']=1
pmagplotlib.plot_init(EQ['eqarea'],5,5)
k=0
while k<len(sitelist):
site=sitelist[k]
print(site)
data=[]
ThisSiteSpecs=pmag.get_dictitem(Specs,'er_site_name',site,'T')
ThisSiteSpecs=pmag.get_dictitem(ThisSiteSpecs,'specimen_tilt_correction','-1','T') # get all the unoriented data
for spec in ThisSiteSpecs:
if spec['specimen_mad']!="" and spec['specimen_n']!="" and float(spec['specimen_mad'])<=M and float(spec['specimen_n'])>=N:
# good spec, now get orientation....
redo,p=1,0
if len(SO_methods)<=1:
az_type=SO_methods[0]
orient=pmag.find_samp_rec(spec["er_sample_name"],Samps,az_type)
redo=0
while redo==1:
if p>=len(SO_priorities):
print("no orientation data for ",spec['er_sample_name'])
orient["sample_azimuth"]=""
orient["sample_dip"]=""
redo=0
else:
az_type=SO_methods[SO_methods.index(SO_priorities[p])]
orient=pmag.find_samp_rec(spec["er_sample_name"],Samps,az_type)
if orient["sample_azimuth"] !="":
redo=0
p+=1
if orient['sample_azimuth']!="":
rec={}
for key in list(spec.keys()):rec[key]=spec[key]
rec['dec'],rec['inc']=pmag.dogeo(float(spec['specimen_dec']),float(spec['specimen_inc']),float(orient['sample_azimuth']),float(orient['sample_dip']))
rec["tilt_correction"]='1'
crd='g'
rec['sample_azimuth']=orient['sample_azimuth']
rec['sample_dip']=orient['sample_dip']
data.append(rec)
if len(data)>2:
print('specimen, dec, inc, n_meas/MAD,| method codes ')
for i in range(len(data)):
print('%s: %7.1f %7.1f %s / %s | %s' % (data[i]['er_specimen_name'], data[i]['dec'], data[i]['inc'], data[i]['specimen_n'], data[i]['specimen_mad'], data[i]['magic_method_codes']))
fpars=pmag.dolnp(data,'specimen_direction_type')
print("\n Site lines planes kappa a95 dec inc")
print(site, fpars["n_lines"], fpars["n_planes"], fpars["K"], fpars["alpha95"], fpars["dec"], fpars["inc"], fpars["R"])
if out_file!="":
if float(fpars["alpha95"])<=acutoff and float(fpars["K"])>=kcutoff:
out.write('%s %s %s\n'%(fpars["dec"],fpars['inc'],fpars['alpha95']))
pmagplotlib.plot_lnp(EQ['eqarea'],site,data,fpars,'specimen_direction_type')
pmagplotlib.draw_figs(EQ)
if k!=0 and repeat!='y':
ans=input("s[a]ve plot, [q]uit, [e]dit specimens, [p]revious site, <return> to continue:\n ")
elif k==0 and repeat!='y':
ans=input("s[a]ve plot, [q]uit, [e]dit specimens, <return> to continue:\n ")
if ans=="p": k-=2
if ans=="a":
files={}
files['eqarea']=site+'_'+crd+'_eqarea'+'.'+fmt
pmagplotlib.save_plots(EQ,files)
if ans=="q": sys.exit()
if ans=="e" and Samps==[]:
print("can't edit samples without orientation file, sorry")
elif ans=="e":
# k-=1
testspec=input("Enter name of specimen to check: ")
for spec in data:
if spec['er_specimen_name']==testspec:
# first test wrong direction of drill arrows (flip drill direction in opposite direction and re-calculate d,i
d,i=pmag.dogeo(float(spec['specimen_dec']),float(spec['specimen_inc']),float(spec['sample_azimuth'])-180.,-float(spec['sample_dip']))
XY=pmag.dimap(d,i)
pmagplotlib.plot_xy(EQ['eqarea'],[XY[0]],[XY[1]],sym='g^')
# first test wrong end of compass (take az-180.)
d,i=pmag.dogeo(float(spec['specimen_dec']),float(spec['specimen_inc']),float(spec['sample_azimuth'])-180.,float(spec['sample_dip']))
XY=pmag.dimap(d,i)
pmagplotlib.plot_xy(EQ['eqarea'],[XY[0]],[XY[1]],sym='kv')
# did the sample spin in the hole?
# now spin around specimen's z
X_up,Y_up,X_d,Y_d=[],[],[],[]
for incr in range(0,360,5):
d,i=pmag.dogeo(float(spec['specimen_dec'])+incr,float(spec['specimen_inc']),float(spec['sample_azimuth']),float(spec['sample_dip']))
XY=pmag.dimap(d,i)
if i>=0:
X_d.append(XY[0])
Y_d.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
pmagplotlib.plot_xy(EQ['eqarea'],X_d,Y_d,sym='b.')
pmagplotlib.plot_xy(EQ['eqarea'],X_up,Y_up,sym='c.')
pmagplotlib.draw_figs(EQ)
break
print("Triangle: wrong arrow for drill direction.")
print("Delta: wrong end of compass.")
print("Small circle: wrong mark on sample. [cyan upper hemisphere]")
deleteme=input("Mark this sample as bad? y/[n] ")
if deleteme=='y':
reason=input("Reason: [1] broke, [2] wrong drill direction, [3] wrong compass direction, [4] bad mark, [5] displaced block [6] other ")
if reason=='1':
description=' sample broke while drilling'
if reason=='2':
description=' wrong drill direction '
if reason=='3':
description=' wrong compass direction '
if reason=='4':
description=' bad mark in field'
if reason=='5':
description=' displaced block'
if reason=='6':
description=input('Enter brief reason for deletion: ')
for samp in Samps:
if samp['er_sample_name']==spec['er_sample_name']:
samp['sample_orientation_flag']='b'
samp['sample_description']=samp['sample_description']+' ## direction deleted because: '+description+'##' # mark description
pmag.magic_write(sampfile,Samps,'er_samples')
repeat=input("Mark another sample, this site? y/[n] ")
if repeat=='y': k-=1
else:
print('skipping site - not enough data with specified coordinate system')
k+=1
print("sample flags stored in ",sampfile)