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
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
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
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
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
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
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
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
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a sites 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 sites format file, [default is sites.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: sites.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", "sites.txt")
con = cb.Contribution(dir_path, single_file=results_file)
if not list(con.tables.keys()):
print("-W - Couldn't read in data")
return
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons = [], []
Pars = []
dates, rlats, rlons = [], [], []
site_container = con.tables['sites']
site_df = site_container.df
# use records with vgp_lat and vgp_lon
if 'vgp_lat' in site_df.columns and 'vgp_lon' in site_df.columns:
cond1, cond2 = site_df['vgp_lat'].notnull(), site_df['vgp_lon'].notnull()
else:
print ('nothing to plot')
sys.exit()
Results = site_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
locs = Results['location'].unique()
if len(locs):
location = ":".join(Results['location'].unique())
else:
location = ""
if 'age' in Results.columns and ages == 1:
dates = Results['age'].unique()
# go through rows and extract data
for ind, row in Results.iterrows():
lat, lon = float(row['vgp_lat']), float(row['vgp_lon'])
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 'vgp_dm' in list(row.keys()) and row['vgp_dm']:
ell1 = float(row['vgp_dm'])
if 'vgp_dp' in list(row.keys()) and row['vgp_dp']:
ell2 = float(row['vgp_dp'])
if 'vgp_alpha95' in list(row.keys()) and (row['vgp_alpha95'] or row['vgp_alpha95'] == 0):
ell1, ell2 = float(row['vgp_alpha95']), float(row['vgp_alpha95'])
if ell1 and ell2:
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
try:
isign = abs(lats[-1]) / lats[-1]
except ZeroDivisionError:
isign = 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 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)
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_' + location + '_TY:_VGP_map.' + fmt
else: # use more readable naming convention
files[key] = '{}_VGP_map.{}'.format(location, fmt)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['map'] = 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 data in version 3.0 format
Reads saved interpretations from a specimen formatted table, default: specimens.txt
SYNTAX
thellier_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEAS, set measurements input file, default is 'measurements.txt'
-fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
-fcr CRIT, set criteria file for grading. # not yet implemented
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out review (in format specified by -fmt key or default)
-spc SPEC, plots single specimen SPEC, saves plot with specified format
with optional -b bounds and quits
-b BEG END: sets bounds for calculation
BEG: starting step number for slope calculation
END: ending step number for slope calculation
-z use only z component difference for pTRM calculation
OUTPUT
figures:
ALL: numbers refer to temperature steps in command line window
1) Arai plot: closed circles are zero-field first/infield
open circles are infield first/zero-field
triangles are pTRM checks
squares are pTRM tail checks
VDS is vector difference sum
diamonds are bounds for interpretation
2) Zijderveld plot: closed (open) symbols are X-Y (X-Z) planes
X rotated to NRM direction
3) (De/Re)Magnetization diagram:
circles are NRM remaining
squares are pTRM gained
4) equal area projections:
green triangles are pTRM gained direction
red (purple) circles are lower(upper) hemisphere of ZI step directions
blue (cyan) squares are lower(upper) hemisphere IZ step directions
5) Optional: TRM acquisition
6) Optional: TDS normalization
command line window:
list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of measuements)
list of possible commands: type letter followed by return to select option
saving of plots creates image files with specimen, plot type as name
"""
#
# initializations
#
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
#
# default acceptance criteria
#
accept = pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
plots, fmt, Zdiff = 0, 'svg', 0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-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")
crit_file = pmag.get_named_arg("-fcr", default_val="criteria.txt")
spec_file = os.path.join(dir_path, spec_file)
meas_file = os.path.join(dir_path, meas_file)
crit_file = os.path.join(dir_path, crit_file)
fmt = pmag.get_named_arg("-fmt", "svg")
if '-sav' in sys.argv:
plots, verbose = 1, 0
if '-z' in sys.argv:
Zdiff = 1
specimen = pmag.get_named_arg("-spc", default_val="")
if '-b' in sys.argv:
ind = sys.argv.index('-b')
start = int(sys.argv[ind + 1])
end = int(sys.argv[ind + 2])
else:
start, end = "", ""
fnames = {
'measurements': meas_file,
'specimens': spec_file,
'criteria': crit_file
}
contribution = cb.Contribution(
dir_path,
custom_filenames=fnames,
read_tables=['measurements', 'specimens', 'criteria'])
#
# import prior interpretations from specimen file
#
specimen_cols = [
'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s',
'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma',
'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1',
'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95',
'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements',
'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment',
'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma',
'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma',
'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q',
'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max',
'meas_step_min', 'meas_step_unit', 'method_codes', 'sample',
'software_packages', 'specimen'
]
spec_container, prior_spec_data = None, []
if 'specimens' in contribution.tables:
spec_container = contribution.tables['specimens']
if 'method_codes' in spec_container.df.columns:
# look up all prior intensity interpretations
prior_spec_data = spec_container.get_records_for_code(
'LP-PI-TRM', strict_match=False)
backup = 0
#
Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
#
# create measurement dataframe
#
if pmagplotlib.isServer:
contribution.propagate_location_to_measurements()
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data['method_codes'] = meas_data['method_codes'].str.replace(
" ", "") # get rid of nasty spaces
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LP-PI-TRM|LP-TRM|LP-TRM-TD') ==
True] # fish out zero field steps for plotting
intensity_types = [
col_name for col_name in meas_data.columns if col_name in Mkeys
]
# plot first intensity method found - normalized to initial value anyway -
# doesn't matter which used
int_key = meas_container.find_filled_col(intensity_types)
if not int_key:
print("-W- No intensity data found, thellier_magic cannot run")
return
# get all the non-null intensity records of the same type
meas_data = meas_data[meas_data[int_key].notnull()]
if not len(meas_data):
print("-W- No intensity data found, thellier_magic cannot run")
return
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
meas_data = meas_data[meas_data['flag'].str.contains('g') ==
True] # only the 'good' measurements
thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')
== True] # get all the Thellier data
trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM') ==
True] # get all the TRM acquisition data
td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD') ==
True] # get all the TD data
anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN') ==
True] # get all the anisotropy data
#
# get list of unique specimen names from measurement data
#
# this is a Series of all the specimen names
specimen_names = meas_data.specimen.unique()
specimen_names = specimen_names.tolist() # turns it into a list
specimen_names.sort() # sorts by specimen name
#
# set up new DataFrame for this sessions specimen interpretations
#
spec_container = cb.MagicDataFrame(dtype='specimens',
columns=specimen_cols)
# this is for interpretations from this session
current_spec_data = spec_container.df
if specimen == "": # do all specimens
k = 0
else:
k = specimen_names.index(specimen) # just do this one
# define figure numbers for arai, zijderveld and
# de-,re-magnetization diagrams
AZD = {}
AZD['deremag'], AZD['zijd'], AZD['arai'], AZD['eqarea'] = 1, 2, 3, 4
pmagplotlib.plot_init(AZD['arai'], 5, 5)
pmagplotlib.plot_init(AZD['zijd'], 5, 5)
pmagplotlib.plot_init(AZD['deremag'], 5, 5)
pmagplotlib.plot_init(AZD['eqarea'], 5, 5)
if len(trm_data) > 0:
AZD['TRM'] = 5
pmagplotlib.plot_init(AZD['TRM'], 5, 5)
if len(td_data) > 0:
AZD['TDS'] = 6
pmagplotlib.plot_init(AZD['TDS'], 5, 5)
#
while k < len(specimen_names):
# set the current specimen for plotting
this_specimen = specimen_names[k]
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
if pmagplotlib.isServer:
this_specimen_measurements = meas_data[meas_data['specimen'] ==
this_specimen]
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 = ""
#
# set up datablocks
#
thelblock = thel_data[thel_data['specimen'].str.contains(this_specimen)
== True] # fish out this specimen
trmblock = trm_data[trm_data['specimen'].str.contains(this_specimen) ==
True] # fish out this specimen
tdsrecs = td_data[td_data['specimen'].str.contains(this_specimen) ==
True] # fish out this specimen
anisblock = anis_data[anis_data['specimen'].str.contains(this_specimen)
== True] # fish out the anisotropy data
if len(prior_spec_data):
prior_specimen_interpretations = prior_spec_data[
prior_spec_data['specimen'].str.contains(
this_specimen) == True] # fish out prior interpretation
else:
prior_specimen_interpretations = []
#
# sort data into types
#
araiblock, field = pmag.sortarai(thelblock,
this_specimen,
Zdiff,
version=3)
first_Z = araiblock[0]
GammaChecks = araiblock[5]
if len(first_Z) < 3:
if backup == 0:
k += 1
if verbose:
print('skipping specimen - moving forward ', this_specimen)
else:
k -= 1
if verbose:
print('skipping specimen - moving backward ',
this_specimen)
else:
backup = 0
zijdblock, units = pmag.find_dmag_rec(this_specimen,
thelblock,
version=3)
if start == "" and len(prior_specimen_interpretations) > 0:
if verbose:
print('Looking up saved interpretation....')
#
# get prior interpretation steps
#
beg_int = pd.to_numeric(prior_specimen_interpretations.
meas_step_min.values).tolist()[0]
end_int = pd.to_numeric(prior_specimen_interpretations.
meas_step_max.values).tolist()[0]
else:
beg_int, end_int = "", ""
recnum = 0
if verbose:
print("index step Dec Inc Int Gamma")
for plotrec in zijdblock:
if plotrec[0] == beg_int:
start = recnum # while we are at it, collect these bounds
if plotrec[0] == end_int:
end = recnum
if verbose:
if GammaChecks != "":
gamma = ""
for g in GammaChecks:
if g[0] == plotrec[0] - 273:
gamma = g[1]
break
if gamma is not "":
print('%i %i %7.1f %7.1f %8.3e %7.1f' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3], gamma))
else:
print('%i %i %7.1f %7.1f %8.3e ' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3]))
recnum += 1
for fig in list(AZD.keys()):
pmagplotlib.clearFIG(AZD[fig]) # clear all figures
if 'K' in units:
u = 'K'
elif 'J' in units:
u = 'J'
pmagplotlib.plot_arai_zij(AZD, araiblock, zijdblock, this_specimen,
u)
if verbose:
pmagplotlib.draw_figs(AZD)
if cb.is_null(start, False) or cb.is_null(end, False):
if verbose:
ans = input('Return for next specimen, q to quit: ')
if ans == 'q':
sys.exit()
k += 1 # moving on
start, end = "", ""
continue
pars, errcode = pmag.PintPars(thelblock,
araiblock,
zijdblock,
start,
end,
accept,
version=3)
pars['measurement_step_unit'] = "K"
pars['experiment_type'] = 'LP-PI-TRM'
#
# work on saving interpretations stuff later
#
if errcode != 1: # no problem in PintPars
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars["specimen_b"]
pars["er_specimen_name"] = this_specimen
# pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose)
# # deal with this later
pars["specimen_grade"] = 'None'
pars['measurement_step_min'] = pars['meas_step_min']
pars['measurement_step_max'] = pars['meas_step_max']
if pars['measurement_step_unit'] == 'K':
outstr = "specimen Tmin Tmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma Gamma_max \n"
pars_out = (this_specimen, (pars["meas_step_min"] - 273),
(pars["meas_step_max"] -
273), (pars["specimen_int_n"]),
1e6 * (pars["specimen_lab_field_dc"]),
1e6 * (pars["specimen_int"]),
pars["specimen_b"], pars["specimen_q"],
pars["specimen_f"], pars["specimen_fvds"],
pars["specimen_b_beta"], pars["int_mad_free"],
pars["int_dang"], pars["int_drats"],
pars["int_n_ptrm"], pars["specimen_grade"],
np.sqrt(pars["specimen_rsc"]),
int(pars["int_md"]), pars["specimen_b_sigma"],
pars['specimen_gamma'])
outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out + '\n'
elif pars['measurement_step_unit'] == 'J':
outstr = "specimen Wmin Wmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma ThetaMax DeltaMax GammaMax\n"
pars_out = (
this_specimen, (pars["meas_step_min"]),
(pars["meas_step_max"]), (pars["specimen_int_n"]),
1e6 * (pars["specimen_lab_field_dc"]),
1e6 * (pars["specimen_int"]), pars["specimen_b"],
pars["specimen_q"], pars["specimen_f"],
pars["specimen_fvds"], pars["specimen_b_beta"],
pars["specimen_int_mad"], pars["specimen_int_dang"],
pars["specimen_drats"], pars["specimen_int_ptrm_n"],
pars["specimen_grade"], np.sqrt(pars["specimen_rsc"]),
int(pars["specimen_md"]), pars["specimen_b_sigma"],
pars["specimen_theta"], pars["specimen_delta"],
pars["specimen_gamma"])
outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out + '\n'
print(outstr)
print(outstring)
pmagplotlib.plot_b(AZD, araiblock, zijdblock, pars)
mpars = pmag.domean(araiblock[1], start, end, 'DE-BFL')
if verbose:
pmagplotlib.draw_figs(AZD)
print('pTRM direction= ',
'%7.1f' % (mpars['specimen_dec']),
' %7.1f' % (mpars['specimen_inc']), ' MAD:',
'%7.1f' % (mpars['specimen_mad']))
if len(anisblock) > 0: # this specimen has anisotropy data
if verbose:
print('Found anisotropy record... but ignoring for now ')
if plots == 1:
if fmt != "pmag":
files = {}
for key in list(AZD.keys()):
if pmagplotlib.isServer:
files[
key] = "LO:_{}_SI:_{}_SA:_{}_SP:_{}_TY:_{}_.{}".format(
loc, site, samp, this_specimen, key, fmt)
else:
files[key] = 'SP:_' + this_specimen + \
'_TY:_' + key + '_' + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['deremag'] = 'DeReMag Plot'
titles['zijd'] = 'Zijderveld Plot'
titles['arai'] = 'Arai Plot'
titles['TRM'] = 'TRM Acquisition data'
titles['eqarea'] = 'Equal Area Plot'
AZD = pmagplotlib.add_borders(AZD, titles, black,
purple)
pmagplotlib.save_plots(AZD, files)
else: # save in pmag format
print('pmag format no longer supported')
#script="grep "+this_specimen+" output.mag | thellier -mfsi"
#script=script+' %8.4e'%(field)
# min='%i'%((pars["measurement_step_min"]-273))
# Max='%i'%((pars["measurement_step_max"]-273))
#script=script+" "+min+" "+Max
#script=script+" |plotxy;cat mypost >>thellier.ps\n"
# pltf.write(script)
# pmag.domagicmag(outf,MeasRecs)
if specimen != "":
sys.exit() # syonara
if verbose:
ans = input('Return for next specimen, q to quit: ')
if ans == 'q':
sys.exit()
start, end = "", ""
k += 1 # moving on
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
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
eqarea.py
DESCRIPTION
makes equal area projections from declination/inclination data
INPUT FORMAT
takes dec/inc as first two columns in space delimited file
SYNTAX
eqarea.py [options]
OPTIONS
-f FILE, specify file on command line
-sav save figure and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
-s SIZE specify symbol size - default is 20
-Lsym SHAPE COLOR specify shape and color for lower hemisphere
-Usym SHAPE COLOR specify shape and color for upper hemisphere
shapes: 's': square,'o': circle,'^,>,v,<': [up,right,down,left] triangle, 'd': diamond,
'p': pentagram, 'h': hexagon, '8': octagon, '+': plus, 'x': cross
colors: [b]lue,[g]reen,[r]ed,[c]yan,[m]agenta,[y]ellow,blac[k],[w]hite
"""
title = ""
files, fmt = {}, 'svg'
sym = {'lower': ['o', 'r'], 'upper': ['o', 'w']}
plot = 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 '-s' in sys.argv:
ind = sys.argv.index('-s')
sym['size'] = int(sys.argv[ind + 1])
else:
sym['size'] = 20
if '-Lsym' in sys.argv:
ind = sys.argv.index('-Lsym')
sym['lower'][0] = sys.argv[ind + 1]
sym['lower'][1] = sys.argv[ind + 2]
if '-Usym' in sys.argv:
ind = sys.argv.index('-Usym')
sym['upper'][0] = sys.argv[ind + 1]
sym['upper'][1] = sys.argv[ind + 2]
if '-f' in sys.argv: # ask for filename
ind = sys.argv.index('-f')
fname = sys.argv[ind + 1]
else:
print(main.__doc__)
print(' \n -f option required')
sys.exit() # graceful quit
DI = numpy.loadtxt(fname)
EQ = {'eq': 1}
pmagplotlib.plot_init(EQ['eq'], 5, 5)
pmagplotlib.plot_eq_sym(EQ['eq'], DI, 'Equal Area Plot', sym) # make plot
if plot == 0:
pmagplotlib.draw_figs(EQ) # make it visible
for key in list(EQ.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(EQ, files)
elif plot == 1:
fname = os.path.split(fname)[1].split('.')[0]
files['eq'] = fname + '_eq.' + fmt
pmagplotlib.save_plots(EQ, files)
else:
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a":
pmagplotlib.save_plots(EQ, 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 sites, samples, specimens, or measurements
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic, default='sites.txt'
supported types=[measurements, specimens, samples, sites]
-fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
default='specimens.txt'
-fsa FILE: specify sample file name, (required if you want to plot specimens by site)
default='samples.txt'
-fsi FILE: specify site file name, default='sites.txt'
-flo FILE: specify location file name, default='locations.txt'
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-cm CM use color map CM [default is coolwarm]
-sav save plot and quit quietly
-no-tilt data are unoriented, allows plotting of measurement dec/inc
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
# initialize some default variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
plotE = 0
plt = 0 # default to not plotting
verbose = pmagplotlib.verbose
# extract arguments from sys.argv
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg("-WD", default_val=".")
pmagplotlib.plot_init(FIG['eqarea'], 5, 5)
in_file = pmag.get_named_arg("-f", default_val="sites.txt")
in_file = pmag.resolve_file_name(in_file, dir_path)
if "-WD" not in sys.argv:
dir_path = os.path.split(in_file)[0]
#full_in_file = os.path.join(dir_path, in_file)
plot_by = pmag.get_named_arg("-obj", default_val="all").lower()
spec_file = pmag.get_named_arg("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg("-fsi", default_val="sites.txt")
loc_file = pmag.get_named_arg("-flo", default_val="locations.txt")
ignore_tilt = False
if '-no-tilt' in sys.argv:
ignore_tilt = True
if plot_by == 'all':
plot_key = 'all'
elif plot_by == 'sit':
plot_key = 'site'
elif plot_by == 'sam':
plot_key = 'sample'
elif plot_by == 'spc':
plot_key = 'specimen'
else:
plot_by = 'all'
plot_key = 'all'
if '-c' in sys.argv:
contour = 1
if '-cm' in sys.argv:
ind = sys.argv.index('-cm')
color_map = sys.argv[ind + 1]
else:
color_map = 'coolwarm'
else:
contour = 0
if '-sav' in sys.argv:
plt = 1
verbose = 0
if '-ell' in sys.argv:
plotE = 1
ind = sys.argv.index('-ell')
ell_type = sys.argv[ind + 1]
ell_type = pmag.get_named_arg("-ell", "F")
dist = ell_type.upper()
# if dist type is unrecognized, use Fisher
if dist not in ['F', 'K', 'B', 'BE', 'BV']:
dist = 'F'
if dist == "BV":
FIG['bdirs'] = 2
pmagplotlib.plot_init(FIG['bdirs'], 5, 5)
crd = pmag.get_named_arg("-crd", default_val="g")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg("-fmt", "svg")
dec_key = 'dir_dec'
inc_key = 'dir_inc'
tilt_key = 'dir_tilt_correction'
# Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
#
fnames = {
"specimens": spec_file,
"samples": samp_file,
'sites': site_file,
'locations': loc_file
}
contribution = cb.Contribution(dir_path,
custom_filenames=fnames,
single_file=in_file)
try:
contribution.propagate_location_to_samples()
contribution.propagate_location_to_specimens()
contribution.propagate_location_to_measurements()
except KeyError as ex:
pass
# the object that contains the DataFrame + useful helper methods:
table_name = list(contribution.tables.keys())[0]
data_container = contribution.tables[table_name]
# the actual DataFrame:
data = data_container.df
if plot_key != "all" and plot_key not in data.columns:
print(
"-E- You can't plot by {} with the data provided".format(plot_key))
return
# add tilt key into DataFrame columns if it isn't there already
if tilt_key not in data.columns:
data.loc[:, tilt_key] = None
if verbose:
print(len(data), ' records read from ', in_file)
# find desired dec,inc data:
dir_type_key = ''
#
# get plotlist if not plotting all records
#
plotlist = []
if plot_key != "all":
# return all where plot_key is not blank
if plot_key not in data.columns:
print('Can\'t plot by "{}". That header is not in infile: {}'.
format(plot_key, in_file))
return
plots = data[data[plot_key].notnull()]
plotlist = plots[plot_key].unique() # grab unique values
else:
plotlist.append('All')
for plot in plotlist:
if verbose:
print(plot)
if plot == 'All':
# plot everything at once
plot_data = data
else:
# pull out only partial data
plot_data = data[data[plot_key] == plot]
DIblock = []
GCblock = []
# SLblock, SPblock = [], []
title = plot
mode = 1
k = 0
if dec_key not in plot_data.columns:
print("-W- No dec/inc data")
continue
# get all records where dec & inc values exist
plot_data = plot_data[plot_data[dec_key].notnull()
& plot_data[inc_key].notnull()]
if plot_data.empty:
continue
# this sorting out is done in get_di_bock
# if coord == '0': # geographic, use records with no tilt key (or tilt_key 0)
# cond1 = plot_data[tilt_key].fillna('') == coord
# cond2 = plot_data[tilt_key].isnull()
# plot_data = plot_data[cond1 | cond2]
# else: # not geographic coordinates, use only records with correct tilt_key
# plot_data = plot_data[plot_data[tilt_key] == coord]
# get metadata for naming the plot file
locations = data_container.get_name('location', df_slice=plot_data)
site = data_container.get_name('site', df_slice=plot_data)
sample = data_container.get_name('sample', df_slice=plot_data)
specimen = data_container.get_name('specimen', df_slice=plot_data)
# make sure method_codes is in plot_data
if 'method_codes' not in plot_data.columns:
plot_data['method_codes'] = ''
# get data blocks
# would have to ignore tilt to use measurement level data
DIblock = data_container.get_di_block(df_slice=plot_data,
tilt_corr=coord,
excl=['DE-BFP'],
ignore_tilt=ignore_tilt)
#SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
# get great circles
great_circle_data = data_container.get_records_for_code('DE-BFP',
incl=True,
use_slice=True,
sli=plot_data)
if len(great_circle_data) > 0:
gc_cond = great_circle_data[tilt_key] == coord
GCblock = [[float(row[dec_key]),
float(row[inc_key])]
for ind, row in great_circle_data[gc_cond].iterrows()]
#SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]
if len(DIblock) > 0:
if contour == 0:
pmagplotlib.plot_eq(FIG['eqarea'], DIblock, title)
else:
pmagplotlib.plot_eq_cont(FIG['eqarea'],
DIblock,
color_map=color_map)
else:
pmagplotlib.plot_net(FIG['eqarea'])
if len(GCblock) > 0:
for rec in GCblock:
pmagplotlib.plot_circ(FIG['eqarea'], rec, 90., 'g')
if len(DIblock) == 0 and len(GCblock) == 0:
if verbose:
print("no records for plotting")
continue
# sys.exit()
if plotE == 1:
ppars = pmag.doprinc(DIblock) # get principal directions
nDIs, rDIs, npars, rpars = [], [], [], []
for rec in DIblock:
angle = pmag.angle([rec[0], rec[1]],
[ppars['dec'], ppars['inc']])
if angle > 90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist == 'B': # do on whole dataset
etitle = "Bingham confidence ellipse"
bpars = pmag.dobingham(DIblock)
for key in list(bpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (bpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist == 'F':
etitle = "Fisher confidence cone"
if len(nDIs) > 2:
fpars = pmag.fisher_mean(nDIs)
for key in list(fpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (fpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (fpars[key]))
mode += 1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign = abs(fpars['inc']) / fpars['inc']
npars.append(fpars['inc'] - isign * 90.) # Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec'] + 90.) # Beta dec
npars.append(0.) # Beta inc
if len(rDIs) > 2:
fpars = pmag.fisher_mean(rDIs)
if verbose:
print("mode ", mode)
for key in list(fpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (fpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (fpars[key]))
mode += 1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign = abs(fpars['inc']) / fpars['inc']
rpars.append(fpars['inc'] - isign * 90.) # Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec'] + 90.) # Beta dec
rpars.append(0.) # Beta inc
if dist == 'K':
etitle = "Kent confidence ellipse"
if len(nDIs) > 3:
kpars = pmag.dokent(nDIs, len(nDIs))
if verbose:
print("mode ", mode)
for key in list(kpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (kpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (kpars[key]))
mode += 1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs) > 3:
kpars = pmag.dokent(rDIs, len(rDIs))
if verbose:
print("mode ", mode)
for key in list(kpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (kpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (kpars[key]))
mode += 1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist == 'BE':
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
Bkpars = pmag.dokent(BnDIs, 1.)
if verbose:
print("mode ", mode)
for key in list(Bkpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (Bkpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (Bkpars[key]))
mode += 1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
Bkpars = pmag.dokent(BrDIs, 1.)
if verbose:
print("mode ", mode)
for key in list(Bkpars.keys()):
if key != 'n' and verbose:
print(" ", key, '%7.1f' % (Bkpars[key]))
if key == 'n' and verbose:
print(" ", key, ' %i' % (Bkpars[key]))
mode += 1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
etitle = "Bootstrapped confidence ellipse"
elif dist == 'BV':
sym = {
'lower': ['o', 'c'],
'upper': ['o', 'g'],
'size': 3,
'edgecolor': 'face'
}
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
pmagplotlib.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)
for key in list(FIG.keys()):
files = {}
filename = pmag.get_named_arg('-fname')
if filename: # use provided filename
filename += '.' + fmt
elif pmagplotlib.isServer: # use server plot naming convention
filename = 'LO:_'+locations+'_SI:_'+site+'_SA:_'+sample + \
'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
elif plot_key == 'all':
filename = 'all'
if 'location' in plot_data.columns:
locs = plot_data['location'].unique()
loc_string = "_".join(
[str(loc).replace(' ', '_') for loc in locs])
filename += "_" + loc_string
filename += "_" + crd + "_" + key
filename += ".{}".format(fmt)
else: # use more readable naming convention
filename = ''
# fix this if plot_by is location , for example
use_names = {
'location': [locations],
'site': [locations, site],
'sample': [locations, site, sample],
'specimen': [locations, site, sample, specimen]
}
use = use_names[plot_key]
use.extend([crd, key])
# [locations, site, sample, specimen, crd, key]:
for item in use:
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['eqarea'] = 'Equal Area Plot'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
elif plt:
pmagplotlib.save_plots(FIG, files)
continue
if verbose:
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)
continue
def main():
"""
NAME
cont_rot.py
DESCRIPTION
rotates continental fragments according to specified Euler pole
SYNTAX
cont_rot.py [command line options]
OPTIONS
-h prints help and quits
-con [af, congo, kala, aus, balt, eur, ind, sam, ant, grn, lau, nam, gond] , specify colon delimited list of continents to be displayed, e.g., af, af:aus], etc
-age use finite rotations of Torsvik et al. 2008 for specific age (5 Ma increments <325Ma)
rotates to paleomagnetic reference frame
available conts: [congo kala aus eur ind sam ant grn nam]
-sac include rotation of south african craton to pmag reference
-sym [ro, bs, g^, r., b-, etc.] [1,5,10] symbol and size for continent
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]
-pfr PLAT PLON OMEGA [specify pole of finite rotation lat,lon and degrees]
-ffr FFILE, specifies series of finite rotations
vector in tab delimited file
-sr treat poles as sequential rotations
-fpp PFILE, specifies series of paleopoles from which
euler poles can be calculated: vector in tab delimited file
-pt LAT LON, specify a point to rotate along with continent
-fpt PTFILE, specifies file with a series of points to be plotted
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-fmt [png,jpg,svg,pdf] format for saved figure - pdf is default
-sav saves plots and quits
-prj PROJ, specify one of the supported projections: (see basemap.py online documentation)
aeqd = Azimuthal Equidistant
poly = Polyconic
gnom = Gnomonic
moll = Mollweide
tmerc = Transverse Mercator
nplaea = North-Polar Lambert Azimuthal
mill = Miller Cylindrical
merc = Mercator
stere = Stereographic
npstere = North-Polar Stereographic
geos = Geostationary
laea = Lambert Azimuthal Equal Area
sinu = Sinusoidal
spstere = South-Polar Stereographic
lcc = Lambert Conformal
npaeqd = North-Polar Azimuthal Equidistant
eqdc = Equidistant Conic
cyl = Cylindrical Equidistant
omerc = Oblique Mercator
aea = Albers Equal Area
spaeqd = South-Polar Azimuthal Equidistant
ortho = Orthographic
cass= Cassini-Soldner
splaea = South-Polar Lambert Azimuthal
robin = Robinson
DEFAULTS
con: nam
res: c
prj: mollweide
ELAT,ELON = 0,0
NB: high resolution or lines can be very slow
"""
dir_path = '.'
ocean = 0
res = 'c'
proj = 'moll'
euler_file = ''
Conts = []
Poles = []
PTS = []
lat_0, lon_0 = 0., 0.
fmt = 'pdf'
sym = 'r.'
symsize = 5
plot = 0
SEQ, age, SAC = 0, 0, 0
rconts = [
'af', 'congo', 'kala', 'aus', 'eur', 'ind', 'sam', 'ant', 'grn', 'nam'
]
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 '-con' in sys.argv:
ind = sys.argv.index('-con')
Conts = sys.argv[ind + 1].split(':')
if '-age' in sys.argv:
ind = sys.argv.index('-age')
age = int(sys.argv[ind + 1])
if age % 5 != 0 and age > 320:
print(main.__doc__)
print('age must be multiple of 5 less than 325')
sys.exit()
import pmagpy.frp as frp
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 '-prj' in sys.argv:
ind = sys.argv.index('-prj')
proj = sys.argv[ind + 1]
if '-sav' in sys.argv:
plot = 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 '-pt' in sys.argv:
ind = sys.argv.index('-pt')
pt_lat = float(sys.argv[ind + 1])
pt_lon = float(sys.argv[ind + 2])
PTS.append([pt_lat, pt_lon])
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = sys.argv[ind + 1]
symsize = int(sys.argv[ind + 2])
# if '-rsym' in sys.argv:
# ind = sys.argv.index('-rsym')
# rsym=sys.argv[ind+1]
# rsymsize=int(sys.argv[ind+2])
if '-sr' in sys.argv:
SEQ = 1
if '-sac' in sys.argv:
SAC = 1
if '-pfr' in sys.argv:
ind = sys.argv.index('-pfr')
Poles.append([
float(sys.argv[ind + 1]),
float(sys.argv[ind + 2]),
float(sys.argv[ind + 3])
])
elif '-ffr' in sys.argv:
ind = sys.argv.index('-ffr')
file = dir_path + '/' + sys.argv[ind + 1]
f = open(file, 'r')
edata = f.readlines()
for line in edata:
rec = line.split()
Poles.append([float(rec[0]), float(rec[1]), float(rec[2])])
elif '-fpp' in sys.argv:
ind = sys.argv.index('-fpp')
file = dir_path + '/' + sys.argv[ind + 1]
f = open(file, 'r')
pdata = f.readlines()
for line in pdata:
rec = line.split()
# transform paleopole to Euler pole taking shortest route
Poles.append([0., float(rec[1]) - 90., 90. - float(rec[0])])
if '-fpt' in sys.argv:
ind = sys.argv.index('-fpt')
file = dir_path + '/' + sys.argv[ind + 1]
f = open(file, 'r')
ptdata = f.readlines()
for line in ptdata:
rec = line.split()
PTS.append([float(rec[0]), float(rec[1])])
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
if res == 'c':
skip = 8
if res == 'l':
skip = 5
if res == 'i':
skip = 2
if res == 'h':
skip = 1
cnt = 0
Opts = {
'latmin': -90,
'latmax': 90,
'lonmin': 0.,
'lonmax': 360.,
'lat_0': lat_0,
'lon_0': lon_0,
'proj': proj,
'sym': sym,
'symsize': 3,
'pltgrid': 0,
'res': res,
'boundinglat': 0.
}
if proj == 'merc':
Opts['latmin'] = -70
Opts['latmax'] = 70
Opts['lonmin'] = -180
Opts['lonmax'] = 180
pmagplotlib.plot_map(FIG['map'], [], [], Opts) # plot the basemap
Opts['pltgrid'] = -1 # turn off replotting of gridlines
if '-pt' in sys.argv:
Opts['sym'] = sym
Opts['symsize'] = symsize
pmagplotlib.plot_map(FIG['map'], [pt_lat], [pt_lon], Opts)
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
for cont in Conts:
Opts['sym'] = sym
lats, lons = [], []
if age != 0:
Poles = []
rcont = cont
if rcont not in rconts:
print(main.__doc__)
print(rcont)
print('continents must be one of following: ')
print(rconts)
sys.exit()
if rcont == 'congo':
rcont = 'nwaf'
if rcont == 'kala':
rcont = 'neaf'
if rcont == 'sam':
rcont = 'sac'
if rcont == 'ant':
rcont = 'eant'
if rcont != 'af':
Poles.append(frp.get_pole(rcont, age))
else:
Poles.append([0, 0, 0])
if SAC == 1:
Poles.append(frp.get_pole('saf', age))
SEQ = 1
if Poles[-1] == 'NONE':
print('continent does not exist for rotation, try again ')
sys.exit()
data = continents.get_continent(cont + '.asc')
for line in data:
if float(line[0]) == 0 and float(line[1]) == 0:
line[
0] = '100.' # change stupid 0,0s to delimeters with lat=100
if float(line[0]) > 90:
lats.append(float(line[0]))
lons.append(float(line[1]))
elif cnt % skip == 0:
lats.append(float(line[0]))
lons.append(float(line[1]))
cnt += 1
if len(lats) > 0 and len(Poles) == 0:
pmagplotlib.plot_map(FIG['map'], lats, lons, Opts)
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
newlats, newlons = [], []
for lat in lats:
newlats.append(lat)
for lon in lons:
newlons.append(lon)
Opts['pltgrid'] = -1 # turns off replotting of meridians and parallels
for pole in Poles:
Rlats, Rlons = pmag.pt_rot(pole, newlats, newlons)
Opts['sym'] = sym
Opts['symsize'] = 3
if SEQ == 0:
pmagplotlib.plot_map(FIG['map'], Rlats, Rlons, Opts)
elif pole == Poles[
-1]: # plot only last pole for sequential rotations
pmagplotlib.plot_map(FIG['map'], Rlats, Rlons, Opts)
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
if SEQ == 1: # treat poles as sequential rotations
newlats, newlons = [], []
for lat in Rlats:
newlats.append(lat)
for lon in Rlons:
newlons.append(lon)
for pt in PTS:
pt_lat = pt[0]
pt_lon = pt[1]
Opts['sym'] = 'r*'
Opts['symsize'] = 5
pmagplotlib.plot_map(FIG['map'], [pt[0]], [pt[1]], Opts)
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
Opts['pltgrid'] = -1 # turns off replotting of meridians and parallels
for pole in Poles:
Opts['sym'] = sym
Opts['symsize'] = symsize
Rlats, Rlons = pmag.pt_rot(pole, [pt_lat], [pt_lon])
print(Rlats, Rlons)
pmagplotlib.plot_map(FIG['map'], Rlats, Rlons, Opts)
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
Opts['sym'] = 'g^'
Opts['symsize'] = 5
pmagplotlib.plot_map(FIG['map'], [pole[0]], [pole[1]], Opts)
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
files = {}
for key in list(FIG.keys()):
files[key] = 'Cont_rot' + '.' + fmt
if plot == 0 and not IS_WIN:
pmagplotlib.draw_figs(FIG)
if plot == 1:
pmagplotlib.save_plots(FIG, files)
sys.exit()
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Site Map'
FIG = pmagplotlib.add_borders(FIG, titles, black, purple)
pmagplotlib.save_plots(FIG, files)
else:
pmagplotlib.draw_figs(FIG)
ans = pmagplotlib.save_or_quit()
if ans == "a":
pmagplotlib.save_plots(FIG, files)
def main():
"""
NAME
biplot_magic.py
DESCRIPTION
makes a biplot of specified variables from magic_measurements.txt format file
SYNTAX
biplot_magic.py [-h] [-i] [command line options]
INPUT
takes magic formated magic_measurments file
OPTIONS
-h prints help message and quits
-i interactively set filename and axes for plotting
-f FILE: specifies file name, default: magic_measurements.txt
-fmt [svg,png,jpg], format for images - default is svg
-sav figure and quit
-x XMETH:key:step, specify method code for X axis (optional key and treatment values)
-y YMETH:key:step, specify method code for X axis
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is whole file
-n [V,M] plot volume or mass normalized data only
NOTES
if nothing is specified for x and y, the user will be presented with options
key = ['treatment_ac_field','treatment_dc_field',treatment_temp']
step in mT for fields, K for temperatures
"""
#
file='magic_measurements.txt'
methx,methy,fmt="","",'.svg'
plot_key=''
norm_by=""
#plot=0
no_plot = pmag.get_flag_arg_from_sys('-sav')
if not no_plot:
do_plot = True
else:
do_plot = False
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]
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt='.'+sys.argv[ind+1]
if '-n' in sys.argv:
ind=sys.argv.index('-n')
norm_by=sys.argv[ind+1]
xtreat_key,ytreat_key,xstep,ystep="","","",""
if '-x' in sys.argv:
ind=sys.argv.index('-x')
meths=sys.argv[ind+1].split(':')
methx=meths[0]
if len(meths)>1:
xtreat_key=meths[1]
xstep=float(meths[2])
if '-y' in sys.argv:
ind=sys.argv.index('-y')
meths=sys.argv[ind+1].split(':')
methy=meths[0]
if len(meths)>1:
ytreat_key=meths[1]
ystep=float(meths[2])
if '-obj' in sys.argv:
ind=sys.argv.index('-obj')
plot_by=sys.argv[ind+1]
if plot_by=='loc':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'
if '-h' in sys.argv:
do_plot = False
if '-i' in sys.argv:
#
# get name of file from command line
#
file=input("Input magic_measurments file name? [magic_measurements.txt] ")
if file=="":file="magic_measurements.txt"
#
#
FIG={'fig':1}
pmagplotlib.plot_init(FIG['fig'],5,5)
data,file_type=pmag.magic_read(file)
if file_type!="magic_measurements":
print(file_type,' not correct format for magic_measurments file')
sys.exit()
#
# collect method codes
methods,plotlist=[],[]
for rec in data:
if plot_key!="":
if rec[plot_key] not in plotlist:plotlist.append(rec[plot_key])
elif len(plotlist)==0:
plotlist.append('All')
meths=rec['magic_method_codes'].split(':')
for meth in meths:
if meth.strip() not in methods and meth.strip()!="LP-":
methods.append(meth.strip())
#
if '-i' in sys.argv:
print(methods)
elif methx =="" or methy=="":
print(methods)
sys.exit()
GoOn=1
while GoOn==1:
if '-i' in sys.argv:methx=input('Select method for x axis: ')
if methx not in methods:
if '-i' in sys.argv:
print('try again! method not available')
else:
print(main.__doc__)
print('\n must specify X axis method\n')
sys.exit()
else:
if pmagplotlib.verbose: print(methx, ' selected for X axis')
GoOn=0
GoOn=1
while GoOn==1:
if '-i' in sys.argv:methy=input('Select method for y axis: ')
if methy not in methods:
if '-i' in sys.argv:
print('try again! method not available')
else:
print(main.__doc__)
print('\n must specify Y axis method\n')
sys.exit()
else:
if pmagplotlib.verbose: print(methy, ' selected for Y axis')
GoOn=0
if norm_by=="":
measkeys=['measurement_magn_mass','measurement_magn_volume','measurement_magn_moment','measurement_magnitude','measurement_chi_volume','measurement_chi_mass','measurement_chi']
elif norm_by=="V":
measkeys=['measurement_magn_volume','measurement_chi_volume']
elif norm_by=="M":
measkeys=['measurement_magn_mass','measurement_chi_mass']
xmeaskey,ymeaskey="",""
plotlist.sort()
for plot in plotlist: # go through objects
if pmagplotlib.verbose:
print(plot)
X,Y=[],[]
x,y='',''
for rec in data:
if plot_key!="" and rec[plot_key]!=plot:
pass
else:
meths=rec['magic_method_codes'].split(':')
for meth in meths:
if meth.strip()==methx:
if xmeaskey=="":
for key in measkeys:
if key in list(rec.keys()) and rec[key]!="":
xmeaskey=key
if pmagplotlib.verbose:
print(xmeaskey,' being used for plotting X.')
break
if meth.strip()==methy:
if ymeaskey=="":
for key in measkeys:
if key in list(rec.keys()) and rec[key]!="":
ymeaskey=key
if pmagplotlib.verbose:
print(ymeaskey,' being used for plotting Y')
break
if ymeaskey!="" and xmeaskey!="":
for rec in data:
x,y='',''
spec=rec['er_specimen_name'] # get the ydata for this specimen
if rec[ymeaskey]!="" and methy in rec['magic_method_codes'].split(':'):
if ytreat_key=="" or (ytreat_key in list(rec.keys()) and float(rec[ytreat_key])==ystep):
y=float(rec[ymeaskey])
for rec in data: # now find the xdata
if rec['er_specimen_name']==spec and rec[xmeaskey]!="" and methx in rec['magic_method_codes'].split(':'):
if xtreat_key=="" or (xtreat_key in list(rec.keys()) and float(rec[xtreat_key])==xstep):
x=float(rec[xmeaskey])
if x != '' and y!= '':
X.append(x)
Y.append(y)
if len(X)>0:
pmagplotlib.clearFIG(FIG['fig'])
pmagplotlib.plot_xy(FIG['fig'],X,Y,sym='ro',xlab=methx,ylab=methy,title=plot+':Biplot')
if not pmagplotlib.isServer and do_plot:
pmagplotlib.draw_figs(FIG)
ans=input('S[a]ve plots, [q]uit, Return for next plot ' )
if ans=='a':
files={}
for key in list(FIG.keys()): files[key]=plot+'_'+key+fmt
pmagplotlib.save_plots(FIG,files)
if ans=='q':
print("Good-bye\n")
sys.exit()
else:
files={}
for key in list(FIG.keys()): files[key]=plot+'_'+key+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['fig']='X Y Plot'
FIG = pmagplotlib.add_borders(FIG,titles,black,purple)
pmagplotlib.save_plots(FIG,files)
else:
print('nothing to plot for ',plot)
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
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a sites 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 sites format file, [default is sites.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: sites.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", "sites.txt")
con = cb.Contribution(dir_path, single_file=results_file)
if not list(con.tables.keys()):
print("-W - Couldn't read in data")
return
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons = [], []
Pars = []
dates, rlats, rlons = [], [], []
site_container = con.tables['sites']
site_df = site_container.df
# use individual results
if 'result_type' in site_df.columns:
site_df = site_df[site_df['result_type'] == 'i']
# use records with vgp_lat and vgp_lon
if 'vgp_lat' in site_df.columns and 'vgp_lon' in site_df.columns:
cond1, cond2 = site_df['vgp_lat'].notnull(
), site_df['vgp_lon'].notnull()
else:
print('nothing to plot')
sys.exit()
Results = site_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
location = ":".join(Results['location'].unique())
if 'age' in Results.columns and ages == 1:
dates = Results['age'].unique()
# go through rows and extract data
for ind, row in Results.iterrows():
lat, lon = float(row['vgp_lat']), float(row['vgp_lon'])
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 'vgp_dm' in list(row.keys()) and row['vgp_dm']:
ell1 = float(row['vgp_dm'])
if 'vgp_dp' in list(row.keys()) and row['vgp_dp']:
ell2 = float(row['vgp_dp'])
if 'vgp_alpha95' in list(row.keys()) and row['vgp_alpha95'].notnull():
ell1, ell2 = float(row['vgp_alpha95']), float(row['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 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)
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_' + location + '_VGP_map.' + fmt
else: # use more readable naming convention
files[key] = '{}_VGP_map.{}'.format(location, fmt)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['map'] = '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
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
watsons_v.py
DESCRIPTION
calculates Watson's V statistic from input files
INPUT FORMAT
takes dec/inc as first two columns in two space delimited files
SYNTAX
watsons_v.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE (with optional second)
-f2 FILE (second file)
-ant, flip antipodal directions to opposite direction
in first file if only one file or flip all in second, if two files
-P (don't save or show plot)
-sav save figure and quit silently
-fmt [png,svg,eps,pdf,jpg] format for saved figure
OUTPUT
Watson's V and the Monte Carlo Critical Value Vc.
in plot, V is solid and Vc is dashed.
"""
Flip=0
show,plot=1,0
fmt='svg'
file2=""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-ant' in sys.argv: Flip=1
if '-sav' in sys.argv: show,plot=0,1 # don't display, but do save plot
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-P' in sys.argv: show=0 # don't display or save plot
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file1=sys.argv[ind+1]
data=numpy.loadtxt(file1).transpose()
D1=numpy.array([data[0],data[1]]).transpose()
file1_name=os.path.split(file1)[1].split('.')[0]
else:
print("-f is required")
print(main.__doc__)
sys.exit()
if '-f2' in sys.argv:
ind=sys.argv.index('-f2')
file2=sys.argv[ind+1]
data2=numpy.loadtxt(file2).transpose()
D2=numpy.array([data2[0],data2[1]]).transpose()
file2_name=os.path.split(file2)[1].split('.')[0]
if Flip==1:
D2,D=pmag.flip(D2) # D2 are now flipped
if len(D2)!=0:
if len(D)!=0:
D2=numpy.concatenate(D,D2) # put all in D2
elif len(D)!=0:
D2=D
else:
print('length of second file is zero')
sys.exit()
elif Flip==1:D2,D1=pmag.flip(D1) # peel out antipodal directions, put in D2
#
counter,NumSims=0,5000
#
# first calculate the fisher means and cartesian coordinates of each set of Directions
#
pars_1=pmag.fisher_mean(D1)
pars_2=pmag.fisher_mean(D2)
#
# get V statistic for these
#
V=pmag.vfunc(pars_1,pars_2)
#
# do monte carlo simulation of datasets with same kappas, but common mean
#
Vp=[] # set of Vs from simulations
if show==1:print("Doing ",NumSims," simulations")
for k in range(NumSims):
counter+=1
if counter==50:
if show==1:print(k+1)
counter=0
Dirp=[]
# get a set of N1 fisher distributed vectors with k1, calculate fisher stats
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 one)
#
Vp.sort()
k=int(.95*NumSims)
if show==1:
print("Watson's V, Vcrit: ")
print(' %10.1f %10.1f'%(V,Vp[k]))
if show==1 or plot==1:
print("Watson's V, Vcrit: ")
print(' %10.1f %10.1f'%(V,Vp[k]))
CDF={'cdf':1}
pmagplotlib.plot_init(CDF['cdf'],5,5)
pmagplotlib.plot_cdf(CDF['cdf'],Vp,"Watson's V",'r',"")
pmagplotlib.plot_vs(CDF['cdf'],[V],'g','-')
pmagplotlib.plot_vs(CDF['cdf'],[Vp[k]],'b','--')
if plot==0:pmagplotlib.draw_figs(CDF)
files={}
if pmagplotlib.isServer: # use server plot naming convention
if file2!="":
files['cdf']='watsons_v_'+file1+'_'+file2+'.'+fmt
else:
files['cdf']='watsons_v_'+file1+'.'+fmt
else: # use more readable plot naming convention
if file2!="":
files['cdf']='watsons_v_'+file1_name+'_'+file2_name+'.'+fmt
else:
files['cdf']='watsons_v_'+file1_name+'.'+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)
elif plot==0:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.save_plots(CDF,files)
if plot==1: # save and quit silently
pmagplotlib.save_plots(CDF,files)
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
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
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
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
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
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
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
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
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
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
watsons_v.py
DESCRIPTION
calculates Watson's V statistic from input files
INPUT FORMAT
takes dec/inc as first two columns in two space delimited files
SYNTAX
watsons_v.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE (with optional second)
-f2 FILE (second file)
-ant, flip antipodal directions to opposite direction
in first file if only one file or flip all in second, if two files
-P (don't save or show plot)
-sav save figure and quit silently
-fmt [png,svg,eps,pdf,jpg] format for saved figure
OUTPUT
Watson's V and the Monte Carlo Critical Value Vc.
in plot, V is solid and Vc is dashed.
"""
Flip = 0
show, plot = 1, 0
fmt = 'svg'
file2 = ""
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-ant' in sys.argv: Flip = 1
if '-sav' in sys.argv: show, plot = 0, 1 # don't display, but do save plot
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-P' in sys.argv: show = 0 # don't display or save plot
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file1 = sys.argv[ind + 1]
data = numpy.loadtxt(file1).transpose()
D1 = numpy.array([data[0], data[1]]).transpose()
file1_name = os.path.split(file1)[1].split('.')[0]
else:
print("-f is required")
print(main.__doc__)
sys.exit()
if '-f2' in sys.argv:
ind = sys.argv.index('-f2')
file2 = sys.argv[ind + 1]
data2 = numpy.loadtxt(file2).transpose()
D2 = numpy.array([data2[0], data2[1]]).transpose()
file2_name = os.path.split(file2)[1].split('.')[0]
if Flip == 1:
D2, D = pmag.flip(D2) # D2 are now flipped
if len(D2) != 0:
if len(D) != 0:
D2 = numpy.concatenate(D, D2) # put all in D2
elif len(D) != 0:
D2 = D
else:
print('length of second file is zero')
sys.exit()
elif Flip == 1:
D2, D1 = pmag.flip(D1) # peel out antipodal directions, put in D2
#
counter, NumSims = 0, 5000
#
# first calculate the fisher means and cartesian coordinates of each set of Directions
#
pars_1 = pmag.fisher_mean(D1)
pars_2 = pmag.fisher_mean(D2)
#
# get V statistic for these
#
V = pmag.vfunc(pars_1, pars_2)
#
# do monte carlo simulation of datasets with same kappas, but common mean
#
Vp = [] # set of Vs from simulations
if show == 1: print("Doing ", NumSims, " simulations")
for k in range(NumSims):
counter += 1
if counter == 50:
if show == 1: print(k + 1)
counter = 0
Dirp = []
# get a set of N1 fisher distributed vectors with k1, calculate fisher stats
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 one)
#
Vp.sort()
k = int(.95 * NumSims)
if show == 1:
print("Watson's V, Vcrit: ")
print(' %10.1f %10.1f' % (V, Vp[k]))
if show == 1 or plot == 1:
print("Watson's V, Vcrit: ")
print(' %10.1f %10.1f' % (V, Vp[k]))
CDF = {'cdf': 1}
pmagplotlib.plot_init(CDF['cdf'], 5, 5)
pmagplotlib.plot_cdf(CDF['cdf'], Vp, "Watson's V", 'r', "")
pmagplotlib.plot_vs(CDF['cdf'], [V], 'g', '-')
pmagplotlib.plot_vs(CDF['cdf'], [Vp[k]], 'b', '--')
if plot == 0: pmagplotlib.draw_figs(CDF)
files = {}
if pmagplotlib.isServer: # use server plot naming convention
if file2 != "":
files['cdf'] = 'watsons_v_' + file1 + '_' + file2 + '.' + fmt
else:
files['cdf'] = 'watsons_v_' + file1 + '.' + fmt
else: # use more readable plot naming convention
if file2 != "":
files[
'cdf'] = 'watsons_v_' + file1_name + '_' + file2_name + '.' + fmt
else:
files['cdf'] = 'watsons_v_' + file1_name + '.' + 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)
elif plot == 0:
ans = input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a": pmagplotlib.save_plots(CDF, files)
if plot == 1: # save and quit silently
pmagplotlib.save_plots(CDF, files)