def main():
"""
"""
dir_path='.'
ocean=0
proj='ortho'
euler_file=''
cont='ind.asc'
Poles=[]
lat_0,lon_0=0.,0.
fmt='svg'
lon_0=45.
lat_0=20.
euler_file='polerots.ind'
f=open(euler_file,'rU')
edata=f.readlines()
for line in edata:
rec=line.split()
Poles.append([float(rec[0]),float(rec[1]),float(rec[2])])
FIG={'map':1}
pmagplotlib.plot_init(FIG['map'],6,6)
# read in er_sites file
lats,lons=[],[]
data=continents.get_continent(cont)
for line in data:
lats.append(float(line[0]))
lons.append(float(line[1]))
Opts={'latmin':-90,'latmax':90,'lonmin':0.,'lonmax':360.,'lat_0':lat_0,'lon_0':lon_0,'proj':proj,'details':0,'sym':'r-','padlat':0,'padlon':0,'res':'i'}
pmagplotlib.plotMAP(FIG['map'],lats,lons,Opts)
pmagplotlib.drawFIGS(FIG)
plats=[90.]
plons=[0.]
Opts['sym']='ro'
pmagplotlib.plotMAP(FIG['map'],plats,plons,Opts)
pmagplotlib.drawFIGS(FIG)
newlats,newlons=[],[]
for lat in plats:newlats.append(lat)
for lon in plons:newlons.append(lon)
for pole in Poles:
Rlats,Rlons=pmag.PTrot(pole,newlats,newlons)
pmagplotlib.plotMAP(FIG['map'],Rlats,Rlons,Opts)
pmagplotlib.drawFIGS(FIG)
newlats,newlons=[],[]
for lat in Rlats:newlats.append(lat)
for lon in Rlons:newlons.append(lon)
files={}
for key in FIG.keys():
files[key]='pole_rot'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Site Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(FIG,files)
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,'rU')
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.plotQQunf(QQ['unf1'],Data,'QQ-Uniform') # make plot
else:
print 'you need N> 10'
sys.exit()
pmagplotlib.drawFIGS(QQ)
files={}
for key in QQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(QQ,files)
elif plot==1:
files['qq']=file+'.'+fmt
pmagplotlib.saveP(QQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(QQ,files)
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
-i for interactive filename entry
-f FILE, specify file on command line
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).
"""
if '-h' in sys.argv: # check if help is needed
print main.__doc__
sys.exit() # graceful quit
if '-i' in sys.argv: # ask for filename
file=raw_input("Enter file name with dec, inc data: ")
f=open(file,'rU')
data=f.readlines()
elif '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'rU')
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.plotQQnorm(QQ['qq'],X,'Q-Q Plot') # make plot
pmagplotlib.drawFIGS(QQ)
files,fmt={},'svg'
for key in QQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Q-Q Plot'
QQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(QQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(QQ,files)
def main():
"""
NAME
basemap_magic.py
NB: this program no longer maintained - use plot_mapPTS.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.plotMAP(FIG['map'],lats,lons,Opts)
if verbose:pmagplotlib.drawFIGS(FIG)
files={}
for key in FIG.keys():
files[key]='Site_map'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['map']='Site Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
elif verbose:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(FIG,files)
else:
pmagplotlib.saveP(FIG,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()
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.plotEQsym(FIG['eq'],DIblock,title,sym)
if plot==0:pmagplotlib.drawFIGS(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 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 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 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 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 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 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 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.plotEQsym(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors',vsym)
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plotDIsym(FIG['bdirs'],BrDIs,vsym)
else:
pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors',vsym)
if dist=='B':
if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
elif len(nDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
if len(rDIs)>3:
pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
elif len(rDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
if plot==0:pmagplotlib.drawFIGS(FIG)
if plot==0:pmagplotlib.drawFIGS(FIG)
#
files={}
for key in FIG.keys():
files[key]=title+'_'+key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
elif plot==0:
ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=="q": sys.exit()
if ans=="a":
pmagplotlib.saveP(FIG,files)
else:
pmagplotlib.saveP(FIG,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
-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 = "svg", "F", 1
plotE = 0
if "-h" in sys.argv:
print main.__doc__
sys.exit()
pmagplotlib.plot_init(FIG["eq"], 5, 5)
if "-f" in sys.argv:
ind = sys.argv.index("-f")
title = sys.argv[ind + 1]
f = open(title, "rU")
data = f.readlines()
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 = []
for line in data:
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
DIblock.append([float(rec[0]), float(rec[1])])
if len(DIblock) > 0:
pmagplotlib.plotEQ(FIG["eq"], DIblock, title)
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 > 90.0:
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 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 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 * 90.0) # Beta inc
npars.append(fpars["alpha95"]) # gamma
npars.append(fpars["dec"] + 90.0) # Beta dec
npars.append(0.0) # Beta inc
if len(rDIs) > 3:
fpars = pmag.fisher_mean(rDIs)
if pmagplotlib.verbose:
print "mode ", mode
for key in 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 * 90.0) # Beta inc
rpars.append(fpars["alpha95"]) # gamma
rpars.append(fpars["dec"] + 90.0) # Beta dec
rpars.append(0.0) # 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 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 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":
if len(nDIs) >= 10:
BnDIs = pmag.di_boot(nDIs)
Bkpars = pmag.dokent(BnDIs, 1.0)
if pmagplotlib.verbose:
print "mode ", mode
for key in 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, 1.0)
if pmagplotlib.verbose:
print "mode ", mode
for key in 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":
vsym = {"lower": ["+", "k"], "upper": ["x", "k"], "size": 5}
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
pmagplotlib.plotEQsym(FIG["bdirs"], BnDIs, "Bootstrapped Eigenvectors", vsym)
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
if len(nDIs) > 5: # plot on existing plots
pmagplotlib.plotDIsym(FIG["bdirs"], BrDIs, vsym)
else:
pmagplotlib.plotEQ(FIG["bdirs"], BrDIs, "Bootstrapped Eigenvectors", vsym)
if dist == "B":
if len(nDIs) > 3 or len(rDIs) > 3:
pmagplotlib.plotCONF(FIG["eq"], etitle, [], npars, 0)
elif len(nDIs) > 3 and dist != "BV":
pmagplotlib.plotCONF(FIG["eq"], etitle, [], npars, 0)
if len(rDIs) > 3:
pmagplotlib.plotCONF(FIG["eq"], etitle, [], rpars, 0)
elif len(rDIs) > 3 and dist != "BV":
pmagplotlib.plotCONF(FIG["eq"], etitle, [], rpars, 0)
pmagplotlib.drawFIGS(FIG)
#
files = {}
for key in FIG.keys():
files[key] = title + "_" + key + "." + fmt
if pmagplotlib.isServer:
black = "#000000"
purple = "#800080"
titles = {}
titles["eq"] = "Equal Area Plot"
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
else:
ans = raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q":
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG, files)
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored.
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets magic_measurements format input file, default: magic_measurements.txt
-fsp SPECFILE: sets pmag_specimens format file with prior interpreations, default: zeq_specimens.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-fsa SAMPFILE: sets er_samples format file with orientation information, default: er_samples.txt
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave,e,b=1,0,0 # average replicates, initial end and beginning step
plots,coord=0,'s'
noorient=0
version_num=pmag.get_version()
verbose=pmagplotlib.verbose
beg_pca,end_pca,direction_type="","",'l'
calculation_type,fmt="","svg"
user,spec_keys,locname="",[],''
plot_file=""
sfile=""
plot_file=""
PriorRecs=[] # empty list for prior interpretations
backup=0
specimen="" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
else:
dir_path='.'
inspec=dir_path+'/'+'zeq_specimens.txt'
meas_file,geo,tilt,ask,samp_file=dir_path+'/magic_measurements.txt',0,0,0,dir_path+'/er_samples.txt'
if '-f' in sys.argv:
ind=sys.argv.index('-f')
meas_file=dir_path+'/'+sys.argv[ind+1]
if '-fsp' in sys.argv:
ind=sys.argv.index('-fsp')
inspec=dir_path+'/'+sys.argv[ind+1]
if '-fsa' in sys.argv:
ind=sys.argv.index('-fsa')
samp_file=dir_path+'/'+sys.argv[ind+1]
sfile='ok'
if '-crd' in sys.argv:
ind=sys.argv.index('-crd')
coord=sys.argv[ind+1]
if coord=='g' or coord=='t':
samp_data,file_type=pmag.magic_read(samp_file)
if file_type=='er_samples':sfile='ok'
geo=1
if coord=='t':tilt=1
if '-spc' in sys.argv:
ind=sys.argv.index('-spc')
specimen=sys.argv[ind+1]
if '-dir' in sys.argv:
ind=sys.argv.index('-dir')
direction_type=sys.argv[ind+1]
beg_pca=int(sys.argv[ind+2])
end_pca=int(sys.argv[ind+3])
if direction_type=='L':calculation_type='DE-BFL'
if direction_type=='P':calculation_type='DE-BFP'
if direction_type=='F':calculation_type='DE-FM'
if '-Fp' in sys.argv:
ind=sys.argv.index('-Fp')
plot_file=dir_path+'/'+sys.argv[ind+1]
if '-A' in sys.argv: doave=0
if '-sav' in sys.argv:
plots=1
verbose=0
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
#
first_save=1
meas_data,file_type=pmag.magic_read(meas_file)
changeM,changeS=0,0 # check if data or interpretations have changed
if file_type != 'magic_measurements':
print file_type
print file_type,"This is not a valid magic_measurements file "
sys.exit()
for rec in meas_data:
if "magic_method_codes" not in rec.keys(): rec["magic_method_codes"]=""
methods=""
tmp=rec["magic_method_codes"].replace(" ","").split(":")
for meth in tmp:
methods=methods+meth+":"
rec["magic_method_codes"]=methods[:-1] # get rid of annoying spaces in Anthony's export files
if "magic_instrument_codes" not in rec.keys() :rec["magic_instrument_codes"]=""
PriorSpecs=[]
PriorRecs,file_type=pmag.magic_read(inspec)
if len(PriorRecs)==0:
if verbose:print "starting new file ",inspec
for Rec in PriorRecs:
if 'magic_software_packages' not in Rec.keys():Rec['magic_software_packages']=""
if Rec['er_specimen_name'] not in PriorSpecs:
if 'specimen_comp_name' not in Rec.keys():Rec['specimen_comp_name']="A"
PriorSpecs.append(Rec['er_specimen_name'])
else:
if 'specimen_comp_name' not in Rec.keys():Rec['specimen_comp_name']="A"
if "magic_method_codes" in Rec.keys():
methods=[]
tmp=Rec["magic_method_codes"].replace(" ","").split(":")
for meth in tmp:
methods.append(meth)
if 'DE-FM' in methods:
Rec['calculation_type']='DE-FM' # this won't be imported but helps
if 'DE-BFL' in methods:
Rec['calculation_type']='DE-BFL'
if 'DE-BFL-A' in methods:
Rec['calculation_type']='DE-BFL-A'
if 'DE-BFL-O' in methods:
Rec['calculation_type']='DE-BFL-O'
if 'DE-BFP' in methods:
Rec['calculation_type']='DE-BFP'
else:
Rec['calculation_type']='DE-BFL' # default is to assume a best-fit line
#
# get list of unique specimen names
#
sids=pmag.get_specs(meas_data)
#
# set up plots, angle sets X axis to horizontal, direction_type 'l' is best-fit line
# direction_type='p' is great circle
#
#
# draw plots for sample s - default is just to step through zijderveld diagrams
#
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
ZED={}
ZED['eqarea'],ZED['zijd'], ZED['demag']=1,2,3
pmagplotlib.plot_init(ZED['eqarea'],5,5)
pmagplotlib.plot_init(ZED['zijd'],6,5)
pmagplotlib.plot_init(ZED['demag'],5,5)
save_pca=0
if specimen=="":
k = 0
else:
k=sids.index(specimen)
angle,direction_type="",""
setangle=0
CurrRecs=[]
while k < len(sids):
CurrRecs=[]
if setangle==0:angle=""
method_codes,inst_code=[],""
s=sids[k]
PmagSpecRec={}
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec['magic_software_packages']=version_num
PmagSpecRec['specimen_description']=""
PmagSpecRec['magic_method_codes']=""
if verbose and s!="":print s, k , 'out of ',len(sids)
#
# collect info for the PmagSpecRec dictionary
#
s_meas=pmag.get_dictitem(meas_data,'er_specimen_name',s,'T') # fish out this specimen
s_meas=pmag.get_dictitem(s_meas,'magic_method_codes','Z','has') # fish out zero field steps
if len(s_meas)>0:
for rec in s_meas: # fix up a few things for the output record
PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"] # copy over instruments
PmagSpecRec["er_citation_names"]="This study"
PmagSpecRec["er_specimen_name"]=s
PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
PmagSpecRec["er_site_name"]=rec["er_site_name"]
PmagSpecRec["er_location_name"]=rec["er_location_name"]
locname=rec['er_location_name']
if 'er_expedition_name' in rec.keys(): PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
PmagSpecRec["magic_method_codes"]=rec["magic_method_codes"]
if "magic_experiment_name" not in rec.keys():
PmagSpecRec["magic_experiment_names"]=""
else:
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
break
#
# find the data from the meas_data file for this specimen
#
data,units=pmag.find_dmag_rec(s,meas_data)
PmagSpecRec["measurement_step_unit"]= units
u=units.split(":")
if "T" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-AF"
if "K" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-T"
if "J" in units:PmagSpecRec["magic_method_codes"]=PmagSpecRec["magic_method_codes"]+":LP-DIR-M"
#
# find prior interpretation
#
if len(CurrRecs)==0: # check if already in
beg_pca,end_pca="",""
calculation_type=""
if inspec !="":
if verbose: print " looking up previous interpretations..."
precs=pmag.get_dictitem(PriorRecs,'er_specimen_name',s,'T') # get all the prior recs with this specimen name
precs=pmag.get_dictitem(precs,'magic_method_codes','LP-DIR','has') # get the directional data
PriorRecs=pmag.get_dictitem(PriorRecs,'er_specimen_name',s,'F') # take them all out of prior recs
# get the ones that meet the current coordinate system
for prec in precs:
if 'specimen_tilt_correction' not in prec.keys() or prec['specimen_tilt_correction']=='-1':
crd='s'
elif prec['specimen_tilt_correction']=='0':
crd='g'
elif prec['specimen_tilt_correction']=='100':
crd='t'
else:
crd='?'
CurrRec={}
for key in prec.keys():CurrRec[key]=prec[key]
CurrRecs.append(CurrRec) # put in CurrRecs
method_codes= CurrRec["magic_method_codes"].replace(" ","").split(':')
calculation_type='DE-BFL'
if 'DE-FM' in method_codes: calculation_type='DE-FM'
if 'DE-BFP' in method_codes: calculation_type='DE-BFP'
if 'DE-BFL-A' in method_codes: calculation_type='DE-BFL-A'
if 'specimen_dang' not in CurrRec.keys():
if verbose:print 'Run mk_redo.py and zeq_magic_redo.py to get the specimen_dang values'
CurrRec['specimen_dang']=-1
if calculation_type!='DE-FM' and crd==coord: # not a fisher mean
if verbose:print "Specimen N MAD DANG start end dec inc type component coordinates"
if units=='K':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["specimen_dang"]),float(CurrRec["measurement_step_min"])-273,float(CurrRec["measurement_step_max"])-273,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif units=='T':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["specimen_dang"]),float(CurrRec["measurement_step_min"])*1e3,float(CurrRec["measurement_step_max"])*1e3,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif 'T' in units and 'K' in units:
if float(CurrRec['measurement_step_min'])<1.0 :
min=float(CurrRec['measurement_step_min'])*1e3
else:
min=float(CurrRec['measurement_step_min'])-273
if float(CurrRec['measurement_step_max'])<1.0 :
max=float(CurrRec['measurement_step_max'])*1e3
else:
max=float(CurrRec['measurement_step_max'])-273
if verbose:print '%s %i %7.1f %i %i %7.1f %7.1f %7.1f, %s %s\n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec['specimen_dang']),min,max,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,crd)
elif 'J' in units:
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec['specimen_dang']),float(CurrRec["measurement_step_min"]),float(CurrRec["measurement_step_max"]),float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif calculation_type=='DE-FM' and crd==coord: # fisher mean
if verbose:print "Specimen a95 DANG start end dec inc type component coordinates"
if units=='K':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),float(CurrRec["measurement_step_min"])-273,float(CurrRec["measurement_step_max"])-273,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif units=='T':
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),float(CurrRec["measurement_step_min"])*1e3,float(CurrRec["measurement_step_max"])*1e3,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
elif 'T' in units and 'K' in units:
if float(CurrRec['measurement_step_min'])<1.0 :
min=float(CurrRec['measurement_step_min'])*1e3
else:
min=float(CurrRec['measurement_step_min'])-273
if float(CurrRec['measurement_step_max'])<1.0 :
max=float(CurrRec['measurement_step_max'])*1e3
else:
max=float(CurrRec['measurement_step_max'])-273
if verbose:print '%s %i %7.1f %i %i %7.1f %7.1f %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_alpha95"]),min,max,float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,crd)
elif 'J' in units:
if verbose:print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s %s %s \n' % (CurrRec["er_specimen_name"],int(CurrRec["specimen_n"]),float(CurrRec["specimen_mad"]),float(CurrRec["measurement_step_min"]),float(CurrRec["measurement_step_max"]),float(CurrRec["specimen_dec"]),float(CurrRec["specimen_inc"]),calculation_type,CurrRec['specimen_comp_name'],crd)
if len(CurrRecs)==0:beg_pca,end_pca="",""
datablock=data
noskip=1
if len(datablock) <3:
noskip=0
if backup==0:
k+=1
else:
k-=1
if len(CurrRecs)>0:
for rec in CurrRecs:
PriorRecs.append(rec)
CurrRecs=[]
else:
backup=0
if noskip:
#
# find replicate measurements at given treatment step and average them
#
# step_meth,avedata=pmag.vspec(data)
# if len(avedata) != len(datablock):
# if doave==1:
# method_codes.append("DE-VM")
# datablock=avedata
# #
# do geo or stratigraphic correction now
#
if geo==1:
#
# find top priority orientation method
orient,az_type=pmag.get_orient(samp_data,PmagSpecRec["er_sample_name"])
if az_type=='SO-NO':
if verbose: print "no orientation data for ",s
orient["sample_azimuth"]=0
orient["sample_dip"]=0
noorient=1
method_codes.append("SO-NO")
orient["sample_azimuth"]=0
orient["sample_dip"]=0
orient["sample_bed_dip_azimuth"]=0
orient["sample_bed_dip"]=0
noorient=1
method_codes.append("SO-NO")
else:
noorient=0
#
# if stratigraphic selected, get stratigraphic correction
#
tiltblock,geoblock=[],[]
for rec in datablock:
d_geo,i_geo=pmag.dogeo(rec[1],rec[2],float(orient["sample_azimuth"]),float(orient["sample_dip"]))
geoblock.append([rec[0],d_geo,i_geo,rec[3],rec[4],rec[5],rec[6]])
if tilt==1 and "sample_bed_dip" in orient.keys() and float(orient['sample_bed_dip'])!=0:
d_tilt,i_tilt=pmag.dotilt(d_geo,i_geo,float(orient["sample_bed_dip_direction"]),float(orient["sample_bed_dip"]))
tiltblock.append([rec[0],d_tilt,i_tilt,rec[3],rec[4],rec[5],rec[6]])
if tilt==1: plotblock=tiltblock
if geo==1 and tilt==0:plotblock=geoblock
if geo==0 and tilt==0: plotblock=datablock
#
# set the end pca point to last point if not set
if e==0 or e>len(plotblock)-1: e=len(plotblock)-1
if angle=="": angle=plotblock[0][1] # rotate to NRM declination
title=s+'_s'
if geo==1 and tilt==0 and noorient!=1:title=s+'_g'
if tilt==1 and noorient!=1:title=s+'_t'
pmagplotlib.plotZED(ZED,plotblock,angle,title,units)
if verbose:pmagplotlib.drawFIGS(ZED)
if len(CurrRecs)!=0:
for prec in CurrRecs:
if 'calculation_type' not in prec.keys():
calculation_type=''
else:
calculation_type=prec["calculation_type"]
direction_type=prec["specimen_direction_type"]
if calculation_type !="":
beg_pca,end_pca="",""
for j in range(len(datablock)):
if data[j][0]==float(prec["measurement_step_min"]):beg_pca=j
if data[j][0]==float(prec["measurement_step_max"]):end_pca=j
if beg_pca=="" or end_pca=="":
if verbose:
print "something wrong with prior interpretation "
break
if calculation_type!="":
if beg_pca=="":beg_pca=0
if end_pca=="":end_pca=len(plotblock)-1
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,geoblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,tiltblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars["specimen_direction_type"]!="Error":
pmagplotlib.plotDir(ZED,mpars,plotblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
#
# print out data for this sample to screen
#
recnum=0
for plotrec in plotblock:
if units=='T' and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if units=="K" and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if units=="J" and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0],' J',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if 'K' in units and 'T' in units:
if plotrec[0]>=1. and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2],plotrec[6])
if plotrec[0]<1. and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2],plotrec[6])
recnum += 1
if specimen!="":
if plot_file=="":
basename=locname+'_'+s
else:
basename=plot_file
files={}
for key in ZED.keys():
files[key]=basename+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
sys.exit()
else: # interactive
if plots==0:
ans='b'
k+=1
changeS=0
while ans != "":
if len(CurrRecs)==0:
print """
g/b: indicates good/bad measurement. "bad" measurements excluded from calculation
set s[a]ve plot, [b]ounds for pca and calculate, [p]revious, [s]pecimen,
change [h]orizontal projection angle, change [c]oordinate systems,
[e]dit data, [q]uit:
"""
else:
print """
g/b: indicates good/bad measurement. "bad" measurements excluded from calculation
set s[a]ve plot, [b]ounds for pca and calculate, [p]revious, [s]pecimen,
change [h]orizontal projection angle, change [c]oordinate systems,
[d]elete current interpretation(s), [e]dit data, [q]uit:
"""
ans=raw_input('<Return> for next specimen \n')
setangle=0
if ans=='d': # delete this interpretation
CurrRecs=[]
k-=1 # replot same specimen
ans=""
changeS=1
if ans=='q':
if changeM==1:
ans=raw_input('Save changes to magic_measurements.txt? y/[n] ')
if ans=='y':
pmag.magic_write(meas_file,meas_data,'magic_measurements')
print "Good bye"
sys.exit()
if ans=='a':
if plot_file=="":
basename=locname+'_'+s+'_'
else:
basename=plot_file
files={}
for key in ZED.keys():
files[key]=basename+'_'+coord+'_'+key+'.'+fmt
pmagplotlib.saveP(ZED,files)
ans=""
if ans=='p':
k-=2
ans=""
backup=1
if ans=='c':
k-=1 # replot same block
if tilt==0 and geo ==1:print "You are currently viewing geographic coordinates "
if tilt==1 and geo ==1:print "You are currently viewing stratigraphic coordinates "
if tilt==0 and geo ==0: print "You are currently viewing sample coordinates "
print "\n Which coordinate system do you wish to view? "
coord=raw_input(" <Return> specimen, [g] geographic, [t] tilt corrected ")
if coord=="g":geo,tilt=1,0
if coord=="t":
geo=1
tilt=1
if coord=="":
coord='s'
geo=0
tilt=0
if geo==1 and sfile=="":
samp_file=raw_input(" Input er_samples file for sample orientations [er_samples.txt] " )
if samp_file=="":samp_file="er_samples.txt"
samp_data,file_type=pmag.magic_read(samp_file)
if file_type != 'er_samples':
print file_type
print "This is not a valid er_samples file - coordinate system not changed"
else:
sfile="ok"
ans=""
if ans=='s':
keepon=1
sample=raw_input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
k =sids.index(sample)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if sample in sids[qq]:tmplist.append(sids[qq])
print sample," not found, but this was: "
print tmplist
sample=raw_input('Select one or try again\n ')
angle,direction_type="",""
setangle=0
ans=""
if ans=='h':
k-=1
angle=raw_input("Enter desired declination for X axis 0-360 ")
angle=float(angle)
if angle==0:angle=0.001
s=sids[k]
setangle=1
ans=""
if ans=='e':
k-=1
ans=""
recnum=0
for plotrec in plotblock:
if plotrec[0]<=200 and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f ' % (plotrec[5], recnum,plotrec[0]*1e3," mT",plotrec[3],plotrec[1],plotrec[2])
if plotrec[0]>200 and verbose: print '%s: %i %7.1f %s %8.3e %7.1f %7.1f ' % (plotrec[5], recnum,plotrec[0]-273,' C',plotrec[3],plotrec[1],plotrec[2])
recnum += 1
answer=raw_input('Enter index of point to change from bad to good or vice versa: ')
try:
ind=int(answer)
meas_data=pmag.mark_dmag_rec(s,ind,meas_data)
changeM=1
except:
'bad entry, try again'
if ans=='b':
if end_pca=="":end_pca=len(plotblock)-1
if beg_pca=="":beg_pca=0
k-=1 # stay on same sample until through
GoOn=0
while GoOn==0:
print 'Enter index of first point for pca: ','[',beg_pca,']'
answer=raw_input('return to keep default ')
if answer != "":
beg_pca=int(answer)
print 'Enter index of last point for pca: ','[',end_pca,']'
answer=raw_input('return to keep default ')
try:
end_pca=int(answer)
if plotblock[beg_pca][5]=='b' or plotblock[end_pca][5]=='b':
print "Can't select 'bad' measurement for PCA bounds -try again"
end_pca=len(plotblock)-1
beg_pca=0
elif beg_pca >=0 and beg_pca<=len(plotblock)-2 and end_pca>0 and end_pca<len(plotblock):
GoOn=1
else:
print beg_pca,end_pca, " are bad entry of indices - try again"
end_pca=len(plotblock)-1
beg_pca=0
except:
print beg_pca,end_pca, " are bad entry of indices - try again"
end_pca=len(plotblock)-1
beg_pca=0
GoOn=0
while GoOn==0:
if calculation_type!="":
print "Prior calculation type = ",calculation_type
ct=raw_input('Enter new Calculation Type: best-fit line, plane or fisher mean [l]/p/f : ' )
if ct=="" or ct=="l":
direction_type="l"
calculation_type="DE-BFL"
GoOn=1
elif ct=='p':
direction_type="p"
calculation_type="DE-BFP"
GoOn=1
elif ct=='f':
direction_type="l"
calculation_type="DE-FM"
GoOn=1
else:
print "bad entry of calculation type: try again. "
pmagplotlib.plotZED(ZED,plotblock,angle,s,units)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==0:
mpars=pmag.domean(geoblock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
if "SO-NO" not in method_codes:
PmagSpecRec["specimen_tilt_correction"]='0'
method_codes.append("DA-DIR-GEO")
else:
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,geoblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==1 and tilt==1:
mpars=pmag.domean(tiltblock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
if "SO-NO" not in method_codes:
PmagSpecRec["specimen_tilt_correction"]='100'
method_codes.append("DA-DIR-TILT")
else:
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,tiltblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
if geo==0 and tilt==0:
mpars=pmag.domean(datablock,beg_pca,end_pca,calculation_type)
if mpars['specimen_direction_type']=='Error':break
PmagSpecRec["specimen_dec"]='%7.1f ' %(mpars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f ' %(mpars["specimen_inc"])
PmagSpecRec["specimen_tilt_correction"]='-1'
pmagplotlib.plotDir(ZED,mpars,plotblock,angle)
if verbose:pmagplotlib.drawFIGS(ZED)
PmagSpecRec["measurement_step_min"]='%8.3e ' %(mpars["measurement_step_min"])
PmagSpecRec["measurement_step_max"]='%8.3e ' %(mpars["measurement_step_max"])
PmagSpecRec["specimen_correction"]='u'
PmagSpecRec["specimen_dang"]='%7.1f ' %(mpars['specimen_dang'])
print 'DANG: ',PmagSpecRec["specimen_dang"]
if calculation_type!='DE-FM':
PmagSpecRec["specimen_mad"]='%7.1f ' %(mpars["specimen_mad"])
PmagSpecRec["specimen_alpha95"]=""
else:
PmagSpecRec["specimen_alpha95"]='%7.1f ' %(mpars["specimen_alpha95"])
PmagSpecRec["specimen_mad"]=""
PmagSpecRec["specimen_n"]='%i ' %(mpars["specimen_n"])
PmagSpecRec["specimen_direction_type"]=direction_type
PmagSpecRec["calculation_type"]=calculation_type # redundant and won't be imported - just for convenience
method_codes=PmagSpecRec["magic_method_codes"].split(':')
if len(method_codes) != 0:
methstring=""
for meth in method_codes:
ctype=meth.split('-')
if 'DE' not in ctype:methstring=methstring+ ":" +meth # don't include old direction estimation methods
methstring=methstring+':'+calculation_type
PmagSpecRec["magic_method_codes"]= methstring.strip(':')
print 'Method codes: ',PmagSpecRec['magic_method_codes']
if calculation_type!='DE-FM':
if units=='K':
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])-273,float(PmagSpecRec["measurement_step_max"])-273,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif units== 'T':
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])*1e3,float(PmagSpecRec["measurement_step_max"])*1e3,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units and 'K' in units:
if float(PmagSpecRec['measurement_step_min'])<1.0 :
min=float(PmagSpecRec['measurement_step_min'])*1e3
else:
min=float(PmagSpecRec['measurement_step_min'])-273
if float(PmagSpecRec['measurement_step_max'])<1.0 :
max=float(PmagSpecRec['measurement_step_max'])*1e3
else:
max=float(PmagSpecRec['measurement_step_max'])-273
print '%s %i %7.1f %i %i %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),min,max,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_mad"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"]),float(PmagSpecRec["measurement_step_max"]),float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
if 'K' in units:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])-273,float(PmagSpecRec["measurement_step_max"])-273,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["specimen_dang"]),float(PmagSpecRec["measurement_step_min"])*1e3,float(PmagSpecRec["measurement_step_max"])*1e3,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
elif 'T' in units and 'K' in units:
if float(PmagSpecRec['measurement_step_min'])<1.0 :
min=float(PmagSpecRec['measurement_step_min'])*1e3
else:
min=float(PmagSpecRec['measurement_step_min'])-273
if float(PmagSpecRec['measurement_step_max'])<1.0 :
max=float(PmagSpecRec['measurement_step_max'])*1e3
else:
max=float(PmagSpecRec['measurement_step_max'])-273
print '%s %i %7.1f %i %i %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),min,max,float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
else:
print '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f, %s \n' % (PmagSpecRec["er_specimen_name"],int(PmagSpecRec["specimen_n"]),float(PmagSpecRec["specimen_alpha95"]),float(PmagSpecRec["measurement_step_min"]),float(PmagSpecRec["measurement_step_max"]),float(PmagSpecRec["specimen_dec"]),float(PmagSpecRec["specimen_inc"]),calculation_type)
saveit=raw_input("Save this interpretation? [y]/n \n")
if saveit!="n":
changeS=1
#
# put in details
#
angle,direction_type,setangle="","",0
if len(CurrRecs)>0:
replace=raw_input(" [0] add new component, or [1] replace existing interpretation(s) [default is replace] ")
if replace=="1" or replace=="":
CurrRecs=[]
PmagSpecRec['specimen_comp_name']='A'
CurrRecs.append(PmagSpecRec)
else:
print 'These are the current component names for this specimen: '
for trec in CurrRecs:print trec['specimen_comp_name']
compnum=raw_input("Enter new component name: ")
PmagSpecRec['specimen_comp_name']=compnum
print "Adding new component: ",PmagSpecRec['specimen_comp_name']
CurrRecs.append(PmagSpecRec)
else:
PmagSpecRec['specimen_comp_name']='A'
CurrRecs.append(PmagSpecRec)
k+=1
ans=""
else:
ans=""
else: # plots=1
k+=1
files={}
locname.replace('/','-')
print PmagSpecRec
for key in ZED.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_'+coord+'_TY:_'+key+'_.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['demag']='DeMag Plot'
titles['zijd']='Zijderveld Plot'
titles['eqarea']='Equal Area Plot'
ZED = pmagplotlib.addBorders(ZED,titles,black,purple)
pmagplotlib.saveP(ZED,files)
if len(CurrRecs)>0:
for rec in CurrRecs: PriorRecs.append(rec)
if changeS==1:
if len(PriorRecs)>0:
save_redo(PriorRecs,inspec)
else:
os.system('rm '+inspec)
CurrRecs,beg_pca,end_pca=[],"","" # next up
changeS=0
else: k+=1 # skip record - not enough data
if changeM==1:
pmag.magic_write(meas_file,meas_data,'magic_measurements')
def main():
"""
NAME
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, aus, eur, ind, sam, ant, grn, lau, nam]
-eye ELAT ELON [specify eyeball location]
-eul PLAT PLON OMEGA [specify euler rotation vector]
-feu EFILE, specifies series of euler rotations
vector in tab delimited file
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-prj PROJ, specify one of the following:
stere = Stereographic
geos = geostationary
lcc = lambert conformal
robin = Robinson
moll = molweide
merc = mercator
laea = Lambert azimuthal equal area
DEFAULTS
con: nam
res: i
prj: mercator
ELAT,ELON = 0,0
NB: MUST have either -eul or -feu set
"""
dir_path='.'
ocean=0
proj='ortho'
euler_file=''
cont='waf.asc'
Poles=[]
lat_0,lon_0=0.,0.
fmt='svg'
lon_0=45.
lat_0=20.
euler_file='polerots'
f=open(euler_file,'rU')
edata=f.readlines()
for line in edata:
rec=line.split()
Poles.append([float(rec[0]),float(rec[1]),float(rec[2])])
FIG={'map':1}
pmagplotlib.plot_init(FIG['map'],6,6)
# read in er_sites file
lats,lons=[],[]
data=continents.get_continent(cont)
for line in data:
lats.append(float(line[0]))
lons.append(float(line[1]))
Opts={'latmin':-90,'latmax':90,'lonmin':0.,'lonmax':360.,'lat_0':lat_0,'lon_0':lon_0,'proj':proj,'details':0,'sym':'r-','padlat':0,'padlon':0,'res':'i'}
pmagplotlib.plotMAP(FIG['map'],lats,lons,Opts)
pmagplotlib.drawFIGS(FIG)
gclats=range(20,91)
gclons=[]
for lat in gclats:gclons.append(355.)
Opts['sym']='b-'
pmagplotlib.plotMAP(FIG['map'],gclats,gclons,Opts)
pmagplotlib.drawFIGS(FIG)
newlats,newlons=[],[]
for lat in gclats:newlats.append(lat)
for lon in gclons:newlons.append(lon)
for pole in Poles:
Opts['sym']='b-'
Rlats,Rlons=pmag.PTrot(pole,newlats,newlons)
pmagplotlib.plotMAP(FIG['map'],Rlats,Rlons,Opts)
Opts['sym']='bo'
pmagplotlib.plotMAP(FIG['map'],[Rlats[-1]],[Rlons[-1]],Opts)
pmagplotlib.drawFIGS(FIG)
Opts['sym']='b-'
newlats,newlons=[],[]
for lat in Rlats:newlats.append(lat)
for lon in Rlons:newlons.append(lon)
files={}
for key in FIG.keys():
files[key]='pole_rot'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Site Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(FIG,files)
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,'rU').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.plotMAP(FIGS['map'],slats,slons,Opts)
pmagplotlib.plotXY(FIGS['vadms'],Age,Vadm,sym='bo',xlab='Age (Years CE)',ylab=r'VADM (ZAm$^2$)')
if verbose:pmagplotlib.drawFIGS(FIGS)
files={}
for key in FIGS.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['map']='Map'
titles['vadms']='VADMs'
FIG = pmagplotlib.addBorders(FIGS,titles,black,purple)
pmagplotlib.saveP(FIGS,files)
elif verbose:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(FIGS,files)
else:
pmagplotlib.saveP(FIGS,files)
def main():
"""
NAME
ODP_incplot.py
DESCRIPTION
plots various measurements versus core_depth
SYNTAX
ODP_incplot.py [command line optins]
OPTIONS
-h prints help message and quits
-f FILE: specify input magic_measurments format file from magic
-fsa FILE: specify input er_samples format file from magic
-AF step [in mT] to plot
-T step [in C] to plot
-d min max [in m] depth range to plot
-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]
DEFAULTS:
Measurements file: magic_measurements.txt
Samples file: er_samples.txt
NRM step
"""
method,fmt="LT-NO",'.svg'
step=0
pcol=3
plotexp,pTS=0,0
dir_path="./"
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
meas_file=dir_path+'/magic_measurements.txt'
samp_file=dir_path+'/er_samples.txt'
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
meas_file=dir_path+'/'+sys.argv[ind+1]
if '-fsa' in sys.argv:
ind=sys.argv.index('-fsa')
samp_file=dir_path+'/'+sys.argv[ind+1]
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt='.'+sys.argv[ind+1]
if '-AF' in sys.argv:
ind=sys.argv.index('-AF')
step=float(sys.argv[ind+1])*1e-3
method='LT-AF-Z'
if '-T' in sys.argv:
ind=sys.argv.index('-T')
step=float(sys.argv[ind+1])+273
method='LT-T-Z'
dmin,dmax=-1,1e6
if '-d' in sys.argv:
ind=sys.argv.index('-d')
dmin=float(sys.argv[ind+1])
dmax=float(sys.argv[ind+2])
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,pcol=1,4
if '-Iex' in sys.argv: plotexp=1
#
#
# get data read in
Meas,file_type=pmag.magic_read(meas_file)
Samps,file_type=pmag.magic_read(samp_file)
Data=[]
for rec in Meas:
for samp in Samps:
if samp['er_sample_name']== rec['er_sample_name'] and 'core_depth' in samp.keys() and samp['core_depth']!="":
rec['core_depth'] = samp['core_depth']
Data.append(rec) # fish out data with core_depth
if plotexp==1:
for lkey in Lat_keys:
for key in 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'
xlab="Core Depth (m)"
# collect the data for plotting declination
XY=[]
maxInt=-1000
samples=[]
for rec in Data:
if "magic_method_codes" in rec.keys():
meths=rec["magic_method_codes"].split(":")
if method in meths: # make sure it is desired lab treatment step
if float(rec['core_depth'])<dmax and float(rec['core_depth'])>dmin and ('LT-AF-Z' in method and float(rec['treatment_ac_field'])==step) or ('LT-NO' in method and step == 0) or ('LT-T-Z' in method and float(rec['treatment_temp'])==step):
XY.append([float(rec['core_depth']),float(rec['measurement_inc'])])
if len(XY)>0 :
FIG={'strat':1,'ts':2}
pmagplotlib.plot_init(FIG['strat'],10,5)
labels=['Depth below sea floor (m)','Inclination','']
pmagplotlib.plotSTRAT(FIG['strat'],XY,labels)
if pTS==1:
pmagplotlib.plot_init(FIG['ts'],10,5)
pmagplotlib.plotTS(FIG['ts'],[amin,amax],ts)
else:
print "No data points met your criteria - try again"
sys.exit()
files,fmt={},'svg'
for key in 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.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(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
-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
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
FIG={} # plot dictionary
FIG['eq']=1 # eqarea is figure 1
in_file,plot_key,coord,crd='pmag_results.txt','all',"-1",'g'
fmt,dist,mode='svg','F',1
plotE,contour=0,0
dir_path='.'
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['eq'],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
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")
coord=sys.argv[ind+1]
if coord=='g':coord="0"
if coord=='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']
Inc_keys=['site_inc','sample_inc','specimen_inc','measurement_inc','average_inc']
Tilt_keys=['tilt_correction','site_tilt_correction','sample_tilt_correction','specimen_tilt_correction']
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 pmagplotlib.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":
for rec in data:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
else:
plotlist.append('Whole file')
for plot in plotlist:
DIblock=[]
GCblock=[]
SLblock,SPblock=[],[]
tilt_key=""
mode=1
for rec in data: # find what data are available
if plot_key=='all' or rec[plot_key]==plot:
if plot_key!="all":
title=rec[plot_key]
else:
title=plot
if coord=='-1':title=title+' Specimen Coordinates'
if coord=='0':title=title+' Geographic Coordinates'
if coord=='100':title=title+' Tilt corrected Coordinates'
dec_key,inc_key,tilt_key,name_key,k="","","","",0
while dec_key=="" and k<len(Dec_keys):
if Dec_keys[k] in rec.keys() and rec[Dec_keys[k]]!="" and Inc_keys[k] in rec.keys() and rec[Inc_keys[k]]!="":
dec_key,inc_key =Dec_keys[k],Inc_keys[k]
k+=1
k=0
while tilt_key=="" and k<len(Tilt_keys):
if Tilt_keys[k] in rec.keys():tilt_key=Tilt_keys[k]
k+=1
k=0
while name_key=="" and k<len(Name_keys):
if Name_keys[k] in rec.keys():name_key=Name_keys[k]
k+=1
k=1
while dir_type_key=="" and k<len(Dir_type_keys):
if Dir_type_keys[k] in rec.keys():dir_type_key=Dir_type_keys[k]
k+=1
if dec_key!="":break
if tilt_key=="":tilt_key='-1'
if dir_type_key=="":dir_type_key='direction_type'
for rec in data: # pick out the data
if (plot_key=='all' or rec[plot_key]==plot) and rec[dec_key].strip()!="" and rec[inc_key].strip()!="":
if dir_type_key not in rec.keys() or rec[dir_type_key]=="":rec[dir_type_key]='l'
if tilt_key not in rec.keys():rec[tilt_key]='-1' # assume specimen coordinates unless otherwise specified
if coord=='-1':
DIblock.append([float(rec[dec_key]),float(rec[inc_key])])
SLblock.append([rec[name_key],rec['magic_method_codes']])
elif rec[tilt_key]==coord and rec[dir_type_key]=='l' and rec[dec_key]!="" and rec[inc_key]!="":
if rec[tilt_key]==coord and rec[dir_type_key]=='l' and rec[dec_key]!="" and rec[inc_key]!="":
DIblock.append([float(rec[dec_key]),float(rec[inc_key])])
SLblock.append([rec[name_key],rec['magic_method_codes']])
elif 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 pmagplotlib.verbose: print "no records for plotting"
sys.exit()
if pmagplotlib.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.plotEQ(FIG['eq'],DIblock,title)
else:
pmagplotlib.plotEQcont(FIG['eq'],DIblock)
else: pmagplotlib.plotNET(FIG['eq'])
if len(GCblock)>0:
for rec in GCblock: pmagplotlib.plotC(FIG['eq'],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 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)>2:
fpars=pmag.fisher_mean(nDIs)
for key in 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)>2:
fpars=pmag.fisher_mean(rDIs)
if pmagplotlib.verbose:print "mode ",mode
for key in 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 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 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 dist=='BE':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
if pmagplotlib.verbose:print "mode ",mode
for key in 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)>5:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
if pmagplotlib.verbose:print "mode ",mode
for key in 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':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plotEQ(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors')
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plotDI(FIG['bdirs'],BrDIs)
else:
pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
if dist=='B':
if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
elif len(nDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eq'],etitle,[],npars,0)
if len(rDIs)>3:
pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
elif len(rDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eq'],etitle,[],rpars,0)
pmagplotlib.drawFIGS(FIG)
#
files={}
for key in FIG.keys():
files[key]=title.replace(" ","_")+'_'+'eqarea'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=="q": sys.exit()
if ans=="a":
pmagplotlib.saveP(FIG,files)
def main():
"""
NAME
plot_mapPTS.py
DESCRIPTION
plots points on map
SYNTAX
plot_mapPTS.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
-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: (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
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="",""
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
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 '-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,'rU').readlines()[0].split('\t')
if 'tab' in header[0]:
if '-n' in sys.argv:prn_name=1
if '-l' in sys.argv:prn_loc=1
proj='lcc'
if 'results' in header[1]:
latkey='average_lat'
lonkey='average_lon'
namekey='pmag_result_name'
lockey='er_location_names'
elif 'sites' in header[1]:
latkey='site_lat'
lonkey='site_lon'
namekey='er_site_name'
lockey='er_location_name'
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:
f=open(file,'rU')
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)
if res=='c':skip=8
if res=='l':skip=5
if res=='i':skip=2
if res=='h':skip=1
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}
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
pmagplotlib.plotMAP(FIG['map'],Lats,Lons,Opts)
files={}
for key in FIG.keys():
files[key]='Map_PTS'+'.'+fmt
if pmagplotlib.isServer or plot:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='PT Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
pmagplotlib.drawFIGS(FIG)
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a": pmagplotlib.saveP(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
"""
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,'rU')
data=f.readlines()
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
Dbar,Ibar=ppars['dec']-180.,-ppars['inc']
for di in rDIs:
d,irot=pmag.dotilt(di[0],di[1],Dbar-180.,90.-Ibar) # rotate to mean
drot=d-180.
if drot<0:drot=drot+360.
D1.append(drot)
I1.append(irot)
Dtit='Reverse Declinations'
Itit='Reverse Inclinations'
else:
ppars=pmag.doprinc(nDIs) # get principal directions
Dbar,Ibar=ppars['dec'],ppars['inc']
for di in nDIs:
d,irot=pmag.dotilt(di[0],di[1],Dbar-180.,90.-Ibar) # rotate to mean
drot=d-180.
if drot<0:drot=drot+360.
D1.append(drot)
I1.append(irot)
Dtit='Declinations'
Itit='Inclinations'
print drot,irot
pmagplotlib.plotQQunf(QQ['unf1'],D1,Dtit) # make plot
pmagplotlib.plotQQexp(QQ['exp1'],I1,Itit) # make plot
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,'exp2':4}
pmagplotlib.plot_init(QQ['unf2'],5,5)
pmagplotlib.plot_init(QQ['exp2'],5,5)
ppars=pmag.doprinc(rDIs) # get principal directions
Dbar,Ibar=ppars['dec']-180.,-ppars['inc']
for di in rDIs:
d,irot=pmag.dotilt(di[0],di[1],Dbar-180.,90.-Ibar) # rotate to mean
drot=d-180.
if drot<0:drot=drot+360.
D2.append(drot)
I2.append(irot)
Dtit='Reverse Declinations'
Itit='Reverse Inclinations'
pmagplotlib.plotQQunf(QQ['unf2'],D2,Dtit) # make plot
pmagplotlib.plotQQexp(QQ['exp2'],I2,Itit) # make plot
pmagplotlib.drawFIGS(QQ)
files={}
for key in QQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(QQ,files)
elif plot==1:
files['qq']=file+'.'+fmt
pmagplotlib.saveP(QQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(QQ,files)
def main():
"""
NAME
watsonsV.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
watsonsV.py [command line options]
OPTIONS
-h prints help message and quits
-f FILE (with optional second)
-f2 FILE (second file)
-ant, flip antipodal directions in FILE to opposite direction
-P (don't plot)
OUTPUT
Watson's V and the Monte Carlo Critical Value Vc.
in plot, V is solid and Vc is dashed.
"""
D1,D2=[],[]
Flip=0
plot=1
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 '-P' in sys.argv: plot=0
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file1=sys.argv[ind+1]
f=open(file1,'rU')
for line in f.readlines():
rec=line.split()
Dec,Inc=float(rec[0]),float(rec[1])
D1.append([Dec,Inc,1.])
f.close()
if '-f2' in sys.argv:
ind=sys.argv.index('-f2')
file2=sys.argv[ind+1]
f=open(file2,'rU')
for line in f.readlines():
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
Dec,Inc=float(rec[0]),float(rec[1])
if Flip==0:
D2.append([Dec,Inc,1.])
else:
D1.append([Dec,Inc,1.])
f.close()
if Flip==1:
D1,D2=pmag.flip(D1)
#
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 plot==1:print "Doing ",NumSims," simulations"
for k in range(NumSims):
counter+=1
if counter==50:
if plot==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)
print "Watson's V, Vcrit: "
print ' %10.1f %10.1f'%(V,Vp[k])
if plot==1:
CDF={'cdf':1}
pmagplotlib.plot_init(CDF['cdf'],5,5)
pmagplotlib.plotCDF(CDF['cdf'],Vp,"Watson's V",'r',"")
pmagplotlib.plotVs(CDF['cdf'],[V],'g','-')
pmagplotlib.plotVs(CDF['cdf'],[Vp[k]],'b','--')
pmagplotlib.drawFIGS(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.addBorders(CDF,titles,black,purple)
pmagplotlib.saveP(CDF,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(CDF,files)
def main():
"""
NAME
plot_mapPTS.py
DESCRIPTION
plots points on map
SYNTAX
plot_mapPTS.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]
-f FILE, specify input file
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-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
INPUTS
space delimited LON LAT data
DEFAULTS
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'
Lats,Lons=[],[]
lat_0,lon_0=0.,0.
fmt='pdf'
sym='ro'
symsize=5
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 '-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 '-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 '-f' in sys.argv:
ind = sys.argv.index('-f')
file=dir_path+'/'+sys.argv[ind+1]
f=open(file,'rU')
ptdata=f.readlines()
for line in ptdata:
rec=line.split()
if len(rec)>1:
Lons.append(float(rec[0]))
Lats.append(float(rec[1]))
else:
print "input file must be specified"
sys.exit()
FIG={'map':1}
pmagplotlib.plot_init(FIG['map'],6,6)
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.}
Opts['details']={}
Opts['details']['coasts']=1
Opts['details']['rivers']=0
Opts['details']['states']=0
Opts['details']['countries']=0
Opts['details']['ocean']=0
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
pmagplotlib.plotMAP(FIG['map'],Lats,Lons,Opts)
pmagplotlib.drawFIGS(FIG)
files={}
for key in FIG.keys():
files[key]='Map_PTS'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='PT Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(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 [-f FILE]
OPTIONS
-i for interactive filename entry
-f FILE, specify file on command line
-p save figure and quit
-fmt [svg,jpg] 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 '-p' 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 '-i' in sys.argv: # ask for filename
file=raw_input("Enter file name with dec, inc data: ")
f=open(file,'rU')
data=f.readlines()
elif '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'rU')
data=f.readlines()
DI= [] # set up list for dec inc 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
if len(rec)>1:
DI.append([float(rec[0]),float(rec[1])]) # append first two columns as DI pair
#
EQ={'eq':1}
pmagplotlib.plot_init(EQ['eq'],5,5)
pmagplotlib.plotEQsym(EQ['eq'],DI,'Equal Area Plot',sym) # make plot
pmagplotlib.drawFIGS(EQ) # make it visible
for key in EQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(EQ,files)
elif plot==1:
files['eq']=file+'.'+fmt
pmagplotlib.saveP(EQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(EQ,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
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,'rU')
data=f.readlines()
if '-F' in sys.argv:
ind=sys.argv.index('-F')
outfile=open(sys.argv[ind+1],'w') # open output file
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.plotQQunf(QQ['unf1'],D1,Dtit) # make plot
Me_n,Me_ncr=pmagplotlib.plotQQexp(QQ['exp1'],I1,Itit) # make plot
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.plotQQunf(QQ['unf2'],D2,Dtit) # make plot
Me_r,Me_rcr=pmagplotlib.plotQQexp(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)
pmagplotlib.drawFIGS(QQ)
files={}
for key in QQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(QQ,files)
elif plot==1:
files['qq']=file+'.'+fmt
pmagplotlib.saveP(QQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(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, "rU")
for line in f1.readlines():
rec = line.split()
Dec, Inc = float(rec[0]), float(rec[1])
D1.append([Dec, Inc, 1.0])
f1.close()
if "-f2" in sys.argv:
ind = sys.argv.index("-f2")
file2 = sys.argv[ind + 1]
f2 = open(file2, "rU")
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, 1.0])
f2.close()
# take the antipode for the directions in file 2
D2_flip = []
for rec in D2:
d, i = (rec[0] - 180.0) % 360.0, -rec[1]
D2_flip.append([d, i, 1.0])
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(0.95 * NumSims)
Vcrit = Vp[k]
#
# equation 18 of McFadden and McElhinny, 1990 calculates the critical value of R (Rwc)
#
Rwc = Sr - (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(((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.plotCDF(CDF["cdf"], Vp, "Watson's V", "r", "")
p2 = pmagplotlib.plotVs(CDF["cdf"], [V], "g", "-")
p3 = pmagplotlib.plotVs(CDF["cdf"], [Vp[k]], "b", "--")
pmagplotlib.drawFIGS(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.addBorders(CDF, titles, black, purple)
pmagplotlib.saveP(CDF, files)
else:
ans = raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans == "a":
pmagplotlib.saveP(CDF, files)
def main():
"""
"""
dir_path = '.'
ocean = 0
proj = 'ortho'
euler_file = ''
cont = 'ind.asc'
Poles = []
lat_0, lon_0 = 0., 0.
fmt = 'svg'
lon_0 = 45.
lat_0 = 20.
euler_file = 'polerots.ind'
f = open(euler_file, 'rU')
edata = f.readlines()
for line in edata:
rec = line.split()
Poles.append([float(rec[0]), float(rec[1]), float(rec[2])])
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons = [], []
data = continents.get_continent(cont)
for line in data:
lats.append(float(line[0]))
lons.append(float(line[1]))
Opts = {
'latmin': -90,
'latmax': 90,
'lonmin': 0.,
'lonmax': 360.,
'lat_0': lat_0,
'lon_0': lon_0,
'proj': proj,
'details': 0,
'sym': 'r-',
'padlat': 0,
'padlon': 0,
'res': 'i'
}
pmagplotlib.plotMAP(FIG['map'], lats, lons, Opts)
pmagplotlib.drawFIGS(FIG)
plats = [90.]
plons = [0.]
Opts['sym'] = 'ro'
pmagplotlib.plotMAP(FIG['map'], plats, plons, Opts)
pmagplotlib.drawFIGS(FIG)
newlats, newlons = [], []
for lat in plats:
newlats.append(lat)
for lon in plons:
newlons.append(lon)
for pole in Poles:
Rlats, Rlons = pmag.PTrot(pole, newlats, newlons)
pmagplotlib.plotMAP(FIG['map'], Rlats, Rlons, Opts)
pmagplotlib.drawFIGS(FIG)
newlats, newlons = [], []
for lat in Rlats:
newlats.append(lat)
for lon in Rlons:
newlons.append(lon)
files = {}
for key in FIG.keys():
files[key] = 'pole_rot' + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Site Map'
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
else:
ans = raw_input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.saveP(FIG, files)
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, aus, eur, ind, sam, ant, grn, lau, nam]
-eye ELAT ELON [specify eyeball location]
-eul PLAT PLON OMEGA [specify euler rotation vector]
-feu EFILE, specifies series of euler rotations
vector in tab delimited file
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-prj PROJ, specify one of the following:
stere = Stereographic
geos = geostationary
lcc = lambert conformal
robin = Robinson
moll = molweide
merc = mercator
laea = Lambert azimuthal equal area
DEFAULTS
con: nam
res: i
prj: mercator
ELAT,ELON = 0,0
NB: MUST have either -eul or -feu set
"""
dir_path = '.'
ocean = 0
proj = 'ortho'
euler_file = ''
cont = 'waf.asc'
Poles = []
lat_0, lon_0 = 0., 0.
fmt = 'svg'
lon_0 = 45.
lat_0 = 20.
euler_file = 'polerots'
f = open(euler_file, 'rU')
edata = f.readlines()
for line in edata:
rec = line.split()
Poles.append([float(rec[0]), float(rec[1]), float(rec[2])])
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons = [], []
data = continents.get_continent(cont)
for line in data:
lats.append(float(line[0]))
lons.append(float(line[1]))
Opts = {
'latmin': -90,
'latmax': 90,
'lonmin': 0.,
'lonmax': 360.,
'lat_0': lat_0,
'lon_0': lon_0,
'proj': proj,
'details': 0,
'sym': 'r-',
'padlat': 0,
'padlon': 0,
'res': 'i'
}
pmagplotlib.plotMAP(FIG['map'], lats, lons, Opts)
pmagplotlib.drawFIGS(FIG)
gclats = range(20, 91)
gclons = []
for lat in gclats:
gclons.append(355.)
Opts['sym'] = 'b-'
pmagplotlib.plotMAP(FIG['map'], gclats, gclons, Opts)
pmagplotlib.drawFIGS(FIG)
newlats, newlons = [], []
for lat in gclats:
newlats.append(lat)
for lon in gclons:
newlons.append(lon)
for pole in Poles:
Opts['sym'] = 'b-'
Rlats, Rlons = pmag.PTrot(pole, newlats, newlons)
pmagplotlib.plotMAP(FIG['map'], Rlats, Rlons, Opts)
Opts['sym'] = 'bo'
pmagplotlib.plotMAP(FIG['map'], [Rlats[-1]], [Rlons[-1]], Opts)
pmagplotlib.drawFIGS(FIG)
Opts['sym'] = 'b-'
newlats, newlons = [], []
for lat in Rlats:
newlats.append(lat)
for lon in Rlons:
newlons.append(lon)
files = {}
for key in FIG.keys():
files[key] = 'pole_rot' + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Site Map'
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
else:
ans = raw_input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.saveP(FIG, 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
-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
NOTES
when x and/or y are not specified, a list of possibilities will be presented to the user for choosing
"""
xaxis,xplotind,yplotind="",0,0 # (0 for strat pos)
yaxis,Xinc="", ""
obj='all'
supported=['pmag_specimens', 'pmag_samples', 'pmag_sites', 'pmag_results','magic_web']
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']
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="./"
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
res_file=dir_path+'/pmag_results.txt'
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
res_file=dir_path+'/'+sys.argv[ind+1]
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-obj' in sys.argv:
ind=sys.argv.index('-obj')
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
#
#
# get data read in
Results,file_type=pmag.magic_read(res_file)
if file_type not in supported:
print "Unsupported file type, try again"
sys.exit()
PltObjs=['all']
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=[]
if "magic_method_codes" in Results[0].keys(): # need to know all the measurement types from method_codes
for rec in Results:
meths=rec["magic_method_codes"].split(":")
for meth in meths:
if meth.strip() not in methcodes and 'LP' in meth: methcodes.append(meth.strip()) # look for the lab treatments
#
# 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 Results[0].keys():
for keys in X_keys:
for xkeys in keys:
if key in xkeys:
for ResRec in Results:
if ResRec[key]!="":
Xplots.append(key) # only plot something if there is something to plot!
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 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 ',methocodes[0],'? ^D to quit'
if xaxis=='age':
for akey in Age_keys:
for key in 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 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 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=="":method=methcodes[0]
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 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 Results[0].keys(): title=Results[0]["er_location_names"]
if "er_locations_name" in Results[0].keys(): title=Results[0]["er_location_name"]
labels=[xlab,ylab,title]
pmagplotlib.plot_init(FIG['strat'],10,5)
pmagplotlib.plotSTRAT(FIG['strat'],XY,labels) # plot them
if plotexp==1: pmagplotlib.plotHs(FIG['strat'],Xinc,'b','--')
if yaxis=='inc' or yaxis=='lat':
pmagplotlib.plotHs(FIG['strat'],[0],'b','-')
pmagplotlib.plotHs(FIG['strat'],[-90,90],'g','-')
if pTS==1:
FIG['ts']=2
pmagplotlib.plot_init(FIG['ts'],10,5)
pmagplotlib.plotTS(FIG['ts'],[amin,amax],ts)
files={}
for key in 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.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(FIG,files)
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]
-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
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 '-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 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 '-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,'rU')
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,'rU')
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,'rU')
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.plotMAP(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.plotMAP(FIG['map'],[pt_lat],[pt_lon],Opts)
pmagplotlib.drawFIGS(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.plotMAP(FIG['map'],lats,lons,Opts)
pmagplotlib.drawFIGS(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.PTrot(pole,newlats,newlons)
Opts['sym']=sym
Opts['symsize']=3
if SEQ==0:
pmagplotlib.plotMAP(FIG['map'],Rlats,Rlons,Opts)
elif pole==Poles[-1]: # plot only last pole for sequential rotations
pmagplotlib.plotMAP(FIG['map'],Rlats,Rlons,Opts)
pmagplotlib.drawFIGS(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.plotMAP(FIG['map'],[pt[0]],[pt[1]],Opts)
pmagplotlib.drawFIGS(FIG)
Opts['pltgrid']=-1 # turns off replotting of meridians and parallels
for pole in Poles:
Opts['sym']=sym
Opts['symsize']=symsize
Rlats,Rlons=pmag.PTrot(pole,[pt_lat],[pt_lon])
print Rlats,Rlons
pmagplotlib.plotMAP(FIG['map'],Rlats,Rlons,Opts)
pmagplotlib.drawFIGS(FIG)
Opts['sym']='g^'
Opts['symsize']=5
pmagplotlib.plotMAP(FIG['map'],[pole[0]],[pole[1]],Opts)
pmagplotlib.drawFIGS(FIG)
files={}
for key in FIG.keys():
files[key]='Cont_rot'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Site Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(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
plots = 0
if '-sav' in sys.argv:
plots = 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:
Decs = pmag.get_dictitem(odata, dec_key, '', 'F') # get all records with this dec_key not blank
if len(Decs) > 0: break
for inc_key in Inc_keys:
Incs = pmag.get_dictitem(Decs, inc_key, '', 'F') # get all records with this inc_key not blank
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] = ''
cdata = pmag.get_dictitem(Incs, tilt_key, coord, 'T') # get all records matching specified coordinate system
if coord == '0': # geographic
udata = pmag.get_dictitem(Incs, tilt_key, '', 'T') # get all the blank records - assume geographic
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:
Names = pmag.get_dictitem(cdata, name_key, '', 'F') # get all records with this name_key not blank
if len(Names) > 0: break
for dir_type_key in Dir_type_keys:
Dirs = pmag.get_dictitem(cdata, dir_type_key, '', 'F') # get all records with this direction type
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.plotEQ(FIG['eqarea'], DIblock, title)
else:
pmagplotlib.plotEQcont(FIG['eqarea'], DIblock)
else:
pmagplotlib.plotNET(FIG['eqarea'])
if len(GCblock) > 0:
for rec in GCblock: pmagplotlib.plotC(FIG['eqarea'], rec, 90., 'g')
if 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.plotEQsym(FIG['bdirs'], BnDIs, 'Bootstrapped Eigenvectors', sym)
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
if len(nDIs) > 5: # plot on existing plots
pmagplotlib.plotDIsym(FIG['bdirs'], BrDIs, sym)
else:
pmagplotlib.plotEQ(FIG['bdirs'], BrDIs, 'Bootstrapped Eigenvectors')
if dist == 'B':
if len(nDIs) > 3 or len(rDIs) > 3: pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], npars, 0)
elif len(nDIs) > 3 and dist != 'BV':
pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], npars, 0)
if len(rDIs) > 3:
pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], rpars, 0)
elif len(rDIs) > 3 and dist != 'BV':
pmagplotlib.plotCONF(FIG['eqarea'], etitle, [], rpars, 0)
if verbose: pmagplotlib.drawFIGS(FIG)
#
files = {}
locations = locations[:-1]
for key in FIG.keys():
filename = 'LO:_' + locations + '_SI:_' + site + '_SA:_' + sample + '_SP:_' + specimen + '_CO:_' + crd + '_TY:_' + key + '_.' + fmt
files[key] = filename
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
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.saveP(FIG, files)
if plots:
pmagplotlib.saveP(FIG, files)
def main():
"""
NAME
watsonsV.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
watsonsV.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()
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()
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:
CDF={'cdf':1}
pmagplotlib.plot_init(CDF['cdf'],5,5)
pmagplotlib.plotCDF(CDF['cdf'],Vp,"Watson's V",'r',"")
pmagplotlib.plotVs(CDF['cdf'],[V],'g','-')
pmagplotlib.plotVs(CDF['cdf'],[Vp[k]],'b','--')
if plot==0:pmagplotlib.drawFIGS(CDF)
files={}
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.addBorders(CDF,titles,black,purple)
pmagplotlib.saveP(CDF,files)
elif plot==0:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(CDF,files)
if plot==1: # save and quit silently
pmagplotlib.saveP(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()
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.plotEQsym(FIG['eq'], DIblock, title, sym)
if plot == 0: pmagplotlib.drawFIGS(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 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 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 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 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 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 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 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.plotEQsym(FIG['bdirs'], BnDIs,
'Bootstrapped Eigenvectors', vsym)
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
if len(nDIs) > 5: # plot on existing plots
pmagplotlib.plotDIsym(FIG['bdirs'], BrDIs, vsym)
else:
pmagplotlib.plotEQ(FIG['bdirs'], BrDIs,
'Bootstrapped Eigenvectors', vsym)
if dist == 'B':
if len(nDIs) > 3 or len(rDIs) > 3:
pmagplotlib.plotCONF(FIG['eq'], etitle, [], npars, 0)
elif len(nDIs) > 3 and dist != 'BV':
pmagplotlib.plotCONF(FIG['eq'], etitle, [], npars, 0)
if len(rDIs) > 3:
pmagplotlib.plotCONF(FIG['eq'], etitle, [], rpars, 0)
elif len(rDIs) > 3 and dist != 'BV':
pmagplotlib.plotCONF(FIG['eq'], etitle, [], rpars, 0)
if plot == 0: pmagplotlib.drawFIGS(FIG)
if plot == 0: pmagplotlib.drawFIGS(FIG)
#
files = {}
for key in FIG.keys():
files[key] = title + '_' + key + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
elif plot == 0:
ans = raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q": sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
pmagplotlib.saveP(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 '-sav' in sys.argv:
plots=1
verbose=0
if '-z' in sys.argv: Zdiff=1
if '-spc' in sys.argv:
ind=sys.argv.index('-spc')
spc=sys.argv[ind+1]
if '-b' in sys.argv:
ind=sys.argv.index('-b')
BEG=int(sys.argv[ind+1])
END=int(sys.argv[ind+2])
if '-fcr' in sys.argv:
ind=sys.argv.index('-fcr')
critout=sys.argv[ind+1]
crit_data,file_type=pmag.magic_read(critout)
if file_type!='pmag_criteria':
if verbose: print 'bad pmag_criteria file, using no acceptance criteria'
accept=pmag.default_criteria(1)[0]
else:
if verbose: print "Acceptance criteria read in from ", critout
accept={'pmag_criteria_code':'ACCEPTANCE','er_citation_names':'This study'}
for critrec in crit_data:
if 'sample_int_sigma_uT' in critrec.keys(): # accommodate Shaar's new criterion
critrec['sample_int_sigma']='%10.3e'%(eval(critrec['sample_int_sigma_uT'])*1e-6)
for key in critrec.keys():
if key not in accept.keys() and critrec[key]!='':
accept[key]=critrec[key]
try:
open(inspec,'rU')
PriorRecs,file_type=pmag.magic_read(inspec)
if file_type != 'pmag_specimens':
print file_type
print file_type,inspec," is not a valid pmag_specimens file "
sys.exit()
for rec in PriorRecs:
if 'magic_software_packages' not in rec.keys():rec['magic_software_packages']=""
except IOError:
PriorRecs=[]
if verbose:print "starting new specimen interpretation file: ",inspec
meas_data,file_type=pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print file_type
print file_type,"This is not a valid magic_measurements file "
sys.exit()
backup=0
# define figure numbers for arai, zijderveld and
# de-,re-magization diagrams
AZD={}
AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
pmagplotlib.plot_init(AZD['arai'],5,5)
pmagplotlib.plot_init(AZD['zijd'],5,5)
pmagplotlib.plot_init(AZD['deremag'],5,5)
pmagplotlib.plot_init(AZD['eqarea'],5,5)
#
#
#
# get list of unique specimen names
#
CurrRec=[]
sids=pmag.get_specs(meas_data)
# get plots for specimen s - default is just to step through arai diagrams
#
if spc!="": specimen =sids.index(spc)
while specimen < len(sids):
methcodes=[]
if verbose:
print sids[specimen],specimen+1, 'of ', len(sids)
MeasRecs=[]
s=sids[specimen]
datablock,trmblock,tdsrecs=[],[],[]
PmagSpecRec={}
if first==0:
for key in keys:PmagSpecRec[key]="" # make sure all new records have same set of keys
PmagSpecRec["er_analyst_mail_names"]=user
PmagSpecRec["specimen_correction"]='u'
#
# find the data from the meas_data file for this specimen
#
for rec in meas_data:
if rec["er_specimen_name"]==s:
MeasRecs.append(rec)
if "magic_method_codes" not in rec.keys():
rec["magic_method_codes"]=""
methods=rec["magic_method_codes"].split(":")
meths=[]
for meth in methods:
meths.append(meth.strip()) # take off annoying spaces
methods=""
for meth in meths:
if meth.strip() not in methcodes and "LP-" in meth:methcodes.append(meth.strip())
methods=methods+meth+":"
methods=methods[:-1]
rec["magic_method_codes"]=methods
if "LP-PI-TRM" in meths: datablock.append(rec)
if "LP-TRM" in meths: trmblock.append(rec)
if "LP-TRM-TD" in meths: tdsrecs.append(rec)
if len(trmblock)>2 and inspec!="":
if Tinit==0:
Tinit=1
AZD['TRM']=5
pmagplotlib.plot_init(AZD['TRM'],5,5)
elif Tinit==1: # clear the TRM figure if not needed
pmagplotlib.clearFIG(AZD['TRM'])
if len(tdsrecs)>2:
if TDinit==0:
TDinit=1
AZD['TDS']=6
pmagplotlib.plot_init(AZD['TDS'],5,5)
elif TDinit==1: # clear the TDS figure if not needed
pmagplotlib.clearFIG(AZD['TDS'])
if len(datablock) <4:
if backup==0:
specimen+=1
if verbose:
print 'skipping specimen - moving forward ', s
else:
specimen-=1
if verbose:
print 'skipping specimen - moving backward ', s
#
# collect info for the PmagSpecRec dictionary
#
else:
rec=datablock[0]
PmagSpecRec["er_citation_names"]="This study"
PmagSpecRec["er_specimen_name"]=s
PmagSpecRec["er_sample_name"]=rec["er_sample_name"]
PmagSpecRec["er_site_name"]=rec["er_site_name"]
PmagSpecRec["er_location_name"]=rec["er_location_name"]
locname=rec['er_location_name'].replace('/','-')
if "er_expedition_name" in rec.keys():PmagSpecRec["er_expedition_name"]=rec["er_expedition_name"]
if "magic_instrument_codes" not in rec.keys():rec["magic_instrument_codes"]=""
PmagSpecRec["magic_instrument_codes"]=rec["magic_instrument_codes"]
PmagSpecRec["measurement_step_unit"]="K"
if "magic_experiment_name" not in rec.keys():
rec["magic_experiment_name"]=""
else:
PmagSpecRec["magic_experiment_names"]=rec["magic_experiment_name"]
meths=rec["magic_method_codes"].split()
# sort data into types
araiblock,field=pmag.sortarai(datablock,s,Zdiff)
first_Z=araiblock[0]
GammaChecks=araiblock[5]
if len(first_Z)<3:
if backup==0:
specimen+=1
if verbose:
print 'skipping specimen - moving forward ', s
else:
specimen-=1
if verbose:
print 'skipping specimen - moving backward ', s
else:
backup=0
zijdblock,units=pmag.find_dmag_rec(s,meas_data)
recnum=0
if verbose:
print "index step Dec Inc Int Gamma"
for plotrec in zijdblock:
if GammaChecks!="":
gamma=""
for g in GammaChecks:
if g[0]==plotrec[0]-273:
gamma=g[1]
break
if gamma!="":
print '%i %i %7.1f %7.1f %8.3e %7.1f' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3],gamma)
else:
print '%i %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3])
recnum += 1
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
if verbose:pmagplotlib.drawFIGS(AZD)
if len(tdsrecs)>2: # a TDS experiment
tdsblock=[] # make a list for the TDS data
Mkeys=['measurement_magnitude','measurement_magn_moment','measurement_magn_volume','measuruement_magn_mass']
mkey,k="",0
while mkey=="" and k<len(Mkeys)-1: # find which type of intensity
key= Mkeys[k]
if key in tdsrecs[0].keys() and tdsrecs[0][key]!="": mkey=key
k+=1
if mkey=="":break # get outta here
Tnorm=""
for tdrec in tdsrecs:
meths=tdrec['magic_method_codes'].split(":")
for meth in meths: meth.replace(" ","") # strip off potential nasty spaces
if 'LT-T-I' in meths and Tnorm=="": # found first total TRM
Tnorm=float(tdrec[mkey]) # normalize by total TRM
tdsblock.append([273,zijdblock[0][3]/Tnorm,1.]) # put in the zero step
if 'LT-T-Z' in meths and Tnorm!="": # found a LP-TRM-TD demag step, now need complementary LT-T-Z from zijdblock
step=float(tdrec['treatment_temp'])
Tint=""
if mkey!="":
Tint=float(tdrec[mkey])
if Tint!="":
for zrec in zijdblock:
if zrec[0]==step: # found matching
tdsblock.append([step,zrec[3]/Tnorm,Tint/Tnorm])
break
if len(tdsblock)>2:
pmagplotlib.plotTDS(AZD['TDS'],tdsblock,s+':LP-PI-TDS:')
if verbose:pmagplotlib(drawFIGS(AZD))
else:
print "Something wrong here"
if anis==1: # look up anisotropy data for this specimen
AniSpec=""
for aspec in anis_data:
if aspec["er_specimen_name"]==PmagSpecRec["er_specimen_name"]:
AniSpec=aspec
if verbose: print 'Found anisotropy record...'
break
if inspec !="":
if verbose: print 'Looking up saved interpretation....'
found = 0
for k in range(len(PriorRecs)):
try:
if PriorRecs[k]["er_specimen_name"]==s:
found =1
CurrRec.append(PriorRecs[k])
for j in range(len(zijdblock)):
if float(zijdblock[j][0])==float(PriorRecs[k]["measurement_step_min"]):start=j
if float(zijdblock[j][0])==float(PriorRecs[k]["measurement_step_max"]):end=j
pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,start,end,accept)
pars['measurement_step_unit']="K"
pars['experiment_type']='LP-PI-TRM'
del PriorRecs[k] # put in CurrRec, take out of PriorRecs
if errcode!=1:
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=s
if verbose:
print 'Saved interpretation: '
pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',verbose)
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
if verbose:pmagplotlib.drawFIGS(AZD)
if len(trmblock)>2:
blab=field
best=pars["specimen_int"]
Bs,TRMs=[],[]
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(float(trec['measurement_magn_moment']))
NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
Mp,Bp=[],[]
for k in range(int(max(Bs)*1e6)):
Bp.append(float(k)*1e-6)
npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
Mp.append(npred)
pmagplotlib.plotTRM(AZD['TRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
PmagSpecRec['specimen_int']=NLpars['banc']
if verbose:
print 'Banc= ',float(NLpars['banc'])*1e6
pmagplotlib.drawFIGS(AZD)
mpars=pmag.domean(araiblock[1],start,end,'DE-BFL')
if verbose:
print 'pTRM direction= ','%7.1f'%(mpars['specimen_dec']),' %7.1f'%(mpars['specimen_inc']),' MAD:','%7.1f'%(mpars['specimen_mad'])
if AniSpec!="":
CpTRM=pmag.Dir_anis_corr([mpars['specimen_dec'],mpars['specimen_inc']],AniSpec)
AniSpecRec=pmag.doaniscorr(PmagSpecRec,AniSpec)
if verbose:
print 'Anisotropy corrected TRM direction= ','%7.1f'%(CpTRM[0]),' %7.1f'%(CpTRM[1])
print 'Anisotropy corrected intensity= ',float(AniSpecRec['specimen_int'])*1e6
else:
print 'error on specimen ',s
except:
pass
if verbose and found==0: print ' None found :( '
if spc!="":
if BEG!="":
pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,BEG,END,accept)
pars['measurement_step_unit']="K"
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=s
pars['specimen_grade']='' # ungraded
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
if verbose:pmagplotlib.drawFIGS(AZD)
if len(trmblock)>2:
if inlt==0:
inlt=1
blab=field
best=pars["specimen_int"]
Bs,TRMs=[],[]
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(float(trec['measurement_magn_moment']))
NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
#
Mp,Bp=[],[]
for k in range(int(max(Bs)*1e6)):
Bp.append(float(k)*1e-6)
npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
files={}
for key in AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(AZD,files)
sys.exit()
if verbose:
ans='b'
while ans != "":
print """
s[a]ve plot, set [b]ounds for calculation, [d]elete current interpretation, [p]revious, [s]ample, [q]uit:
"""
ans=raw_input('Return for next specimen \n')
if ans=="":
specimen +=1
if ans=="d":
save_redo(PriorRecs,inspec)
CurrRec=[]
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
if verbose:pmagplotlib.drawFIGS(AZD)
if ans=='a':
files={}
for key in AZD.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_s_TY:_'+key+fmt
pmagplotlib.saveP(AZD,files)
ans=""
if ans=='q':
print "Good bye"
sys.exit()
if ans=='p':
specimen =specimen -1
backup = 1
ans=""
if ans=='s':
keepon=1
spec=raw_input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
specimen =sids.index(spec)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if spec in sids[qq]:tmplist.append(sids[qq])
print specimen," not found, but this was: "
print tmplist
spec=raw_input('Select one or try again\n ')
ans=""
if ans=='b':
if end==0 or end >=len(zijdblock):end=len(zijdblock)-1
GoOn=0
while GoOn==0:
answer=raw_input('Enter index of first point for calculation: ['+str(start)+'] ')
try:
start=int(answer)
answer=raw_input('Enter index of last point for calculation: ['+str(end)+'] ')
end=int(answer)
if start >=0 and start <len(zijdblock)-2 and end >0 and end <len(zijdblock) or start>=end:
GoOn=1
else:
print "Bad endpoints - try again! "
start,end=0,len(zijdblock)
except ValueError:
print "Bad endpoints - try again! "
start,end=0,len(zijdblock)
s=sids[specimen]
pars,errcode=pmag.PintPars(datablock,araiblock,zijdblock,start,end,accept)
pars['measurement_step_unit']="K"
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=s
pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',0)
PmagSpecRec['specimen_scat']=pars['specimen_scat']
PmagSpecRec['specimen_frac']='%5.3f'%(pars['specimen_frac'])
PmagSpecRec['specimen_gmax']='%5.3f'%(pars['specimen_gmax'])
PmagSpecRec["measurement_step_min"]='%8.3e' % (pars["measurement_step_min"])
PmagSpecRec["measurement_step_max"]='%8.3e' % (pars["measurement_step_max"])
PmagSpecRec["measurement_step_unit"]="K"
PmagSpecRec["specimen_int_n"]='%i'%(pars["specimen_int_n"])
PmagSpecRec["specimen_lab_field_dc"]='%8.3e'%(pars["specimen_lab_field_dc"])
PmagSpecRec["specimen_int"]='%9.4e '%(pars["specimen_int"])
PmagSpecRec["specimen_b"]='%5.3f '%(pars["specimen_b"])
PmagSpecRec["specimen_q"]='%5.1f '%(pars["specimen_q"])
PmagSpecRec["specimen_f"]='%5.3f '%(pars["specimen_f"])
PmagSpecRec["specimen_fvds"]='%5.3f'%(pars["specimen_fvds"])
PmagSpecRec["specimen_b_beta"]='%5.3f'%(pars["specimen_b_beta"])
PmagSpecRec["specimen_int_mad"]='%7.1f'%(pars["specimen_int_mad"])
PmagSpecRec["specimen_Z"]='%7.1f'%(pars["specimen_Z"])
PmagSpecRec["specimen_gamma"]='%7.1f'%(pars["specimen_gamma"])
PmagSpecRec["specimen_grade"]=pars["specimen_grade"]
if pars["method_codes"]!="":
tmpcodes=pars["method_codes"].split(":")
for t in tmpcodes:
if t.strip() not in methcodes:methcodes.append(t.strip())
PmagSpecRec["specimen_dec"]='%7.1f'%(pars["specimen_dec"])
PmagSpecRec["specimen_inc"]='%7.1f'%(pars["specimen_inc"])
PmagSpecRec["specimen_tilt_correction"]='-1'
PmagSpecRec["specimen_direction_type"]='l'
PmagSpecRec["direction_type"]='l' # this is redundant, but helpful - won't be imported
PmagSpecRec["specimen_int_dang"]='%7.1f '%(pars["specimen_int_dang"])
PmagSpecRec["specimen_drats"]='%7.1f '%(pars["specimen_drats"])
PmagSpecRec["specimen_drat"]='%7.1f '%(pars["specimen_drat"])
PmagSpecRec["specimen_int_ptrm_n"]='%i '%(pars["specimen_int_ptrm_n"])
PmagSpecRec["specimen_rsc"]='%6.4f '%(pars["specimen_rsc"])
PmagSpecRec["specimen_md"]='%i '%(int(pars["specimen_md"]))
if PmagSpecRec["specimen_md"]=='-1':PmagSpecRec["specimen_md"]=""
PmagSpecRec["specimen_b_sigma"]='%5.3f '%(pars["specimen_b_sigma"])
if "IE-TT" not in methcodes:methcodes.append("IE-TT")
methods=""
for meth in methcodes:
methods=methods+meth+":"
PmagSpecRec["magic_method_codes"]=methods[:-1]
PmagSpecRec["specimen_description"]=comment
PmagSpecRec["magic_software_packages"]=version_num
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
if verbose:pmagplotlib.drawFIGS(AZD)
if len(trmblock)>2:
blab=field
best=pars["specimen_int"]
Bs,TRMs=[],[]
for trec in trmblock:
Bs.append(float(trec['treatment_dc_field']))
TRMs.append(float(trec['measurement_magn_moment']))
NLpars=nlt.NLtrm(Bs,TRMs,best,blab,0) # calculate best fit parameters through TRM acquisition data, and get new banc
Mp,Bp=[],[]
for k in range(int(max(Bs)*1e6)):
Bp.append(float(k)*1e-6)
npred=nlt.TRM(Bp[-1],NLpars['xopt'][0],NLpars['xopt'][1]) # predicted NRM for this field
Mp.append(npred)
pmagplotlib.plotTRM(AZD['TRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
if verbose:
print 'Non-linear TRM corrected intensity= ',float(NLpars['banc'])*1e6
if verbose:pmagplotlib.drawFIGS(AZD)
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars,kill=pmag.scoreit(pars,PmagSpecRec,accept,'',verbose)
saveit=raw_input("Save this interpretation? [y]/n \n")
if saveit!='n':
PriorRecs.append(PmagSpecRec) # put back an interpretation
specimen+=1
save_redo(PriorRecs,inspec)
ans=""
elif plots==1:
specimen+=1
if fmt != ".pmag":
files={}
for key in AZD.keys():
files[key]="LO:_"+locname+'_SI:_'+PmagSpecRec['er_site_name']+'_SA:_'+PmagSpecRec['er_sample_name']+'_SP:_'+s+'_CO:_s_TY:_'+key+'_'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['deremag']='DeReMag Plot'
titles['zijd']='Zijderveld Plot'
titles['arai']='Arai Plot'
AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
pmagplotlib.saveP(AZD,files)
# pmagplotlib.combineFigs(s,files,3)
else: # save in pmag format
script="grep "+s+" output.mag | thellier -mfsi"
script=script+' %8.4e'%(field)
min='%i'%((pars["measurement_step_min"]-273))
Max='%i'%((pars["measurement_step_max"]-273))
script=script+" "+min+" "+Max
script=script+" |plotxy;cat mypost >>thellier.ps\n"
pltf.write(script)
pmag.domagicmag(outf,MeasRecs)
if len(CurrRec)>0:
for rec in CurrRec:
PriorRecs.append(rec)
CurrRec=[]
if plots!=1 and verbose:
ans=raw_input(" Save last plot? 1/[0] ")
if ans=="1":
if fmt != ".pmag":
files={}
for key in AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(AZD,files)
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
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
-i for interactive filename entry
-f FILE to read file name from command line
"""
fmt='svg'
if len(sys.argv) > 0:
if '-h' in sys.argv: # check if help is needed
print main.__doc__
sys.exit() # graceful quit
if '-i' in sys.argv: # ask for filename
file=raw_input("Enter file name with dec, inc data: ")
f=open(file,'rU')
data=f.readlines()
elif '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'rU')
data=f.readlines()
else:
data=sys.stdin.readlines() # read in data from standard input
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.plotEQ(EQ['eq'],DIs,title)# plot directions
for k in range(len(Pars)):
pmagplotlib.plotELL(EQ['eq'],Pars[k],'b',0,1) # plot ellipses
pmagplotlib.drawFIGS(EQ)
files={}
for key in EQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(EQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans=="q": sys.exit()
if ans=="a":
pmagplotlib.saveP(EQ,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
-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=""
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 '-i' in sys.argv:
#
# get name of file from command line
#
file=raw_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=raw_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=raw_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 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 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 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 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.plotXY(FIG['fig'],X,Y,'ro',methx,methy,plot+':Biplot')
if not pmagplotlib.isServer:
ans=raw_input('S[a]ve plots, [q]uit, Return for next plot ' )
if ans=='a':
files={}
for key in FIG.keys(): files[key]=plot+'_'+key+fmt
pmagplotlib.saveP(FIG,files)
if ans=='q':
print "Good-bye\n"
sys.exit()
else:
files={}
for key in FIG.keys(): files[key]=plot+'_'+key+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['fig']='X Y Plot'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
print 'nothing to plot for ',plot
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')
file=sys.argv[ind+1]
else:
print main.__doc__
print ' \n -f option required'
sys.exit() # graceful quit
DI=numpy.loadtxt(file)
EQ={'eq':1}
pmagplotlib.plot_init(EQ['eq'],5,5)
pmagplotlib.plotEQsym(EQ['eq'],DI,'Equal Area Plot',sym) # make plot
if plot==0:pmagplotlib.drawFIGS(EQ) # make it visible
for key in EQ.keys():
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.addBorders(EQ,titles,black,purple)
pmagplotlib.saveP(EQ,files)
elif plot==1:
files['eq']=file+'.'+fmt
pmagplotlib.saveP(EQ,files)
else:
ans=raw_input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.saveP(EQ,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]
-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
DEFAULTS
FILE: pmag_results.txt
res: c
prj: mercator
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
dir_path='.'
res,ages='c',0
proj='npstere'
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
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 '-res' in sys.argv:
ind = sys.argv.index('-res')
res=sys.argv[ind+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=[],[],[]
Results=[]
for rec in data:
if 'pmag_result_name' in rec.keys():
name=rec['pmag_result_name'].split()
if 'Site' in name:
if coord=="" or rec['tilt_correction']==coord:Results.append(rec)
elif coord=="" or rec['tilt_correction']==coord:Results.append(rec)
for rec in Results:
if 'vgp_lat' in rec.keys() and rec['vgp_lat']!="" and 'vgp_lon' in rec.keys() and rec['vgp_lon']!="":
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)
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}
pmagplotlib.plotMAP(FIG['map'],[90.],[0.],Opts) # make the base map with a blue triangle at the pole`
Opts['details']={'coasts':0,'rivers':0, 'states':0, 'countries':0,'ocean':0}
Opts['pltgrid']=-1
Opts['sym']=sym
Opts['symsize']=size
if len(dates)>0:Opts['names']=dates
if len(lats)>0:pmagplotlib.plotMAP(FIG['map'],lats,lons,Opts) # add the lats and lons of the poles
Opts['names']=[]
if len(rlats)>0:
Opts['sym']=rsym
Opts['symsize']=rsize
pmagplotlib.plotMAP(FIG['map'],rlats,rlons,Opts) # add the lats and lons of the poles
pmagplotlib.drawFIGS(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.plotELL(FIG['map'],ppars,'g.',0,0)
elats,elons=[],[]
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
pmagplotlib.plotMAP(FIG['map'],elats,elons,Opts) # make the base map with a blue triangle at the pole`
pmagplotlib.drawFIGS(FIG)
files={}
for key in FIG.keys():
files[key]='VGP_map'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='VGP Map'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
else:
ans=raw_input(" S[a]ve to save plot, Return to quit: ")
if ans=="a":
pmagplotlib.saveP(FIG,files)
else:
print "Good bye"
sys.exit()
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 critrec.keys():
accept[key]=-1
else:
accept[key]=float(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 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 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 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.plotAZ(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.plotB(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.plotTRM(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.drawFIGS(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.plotB(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 AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(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=raw_input('Return for next specimen \n')
if ans=="":
specimen +=1
if ans=="d":
save_redo(PriorRecs,inspec)
CurrRec=[]
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,s,units[0])
pmagplotlib.drawFIGS(AZD)
if ans=='a':
files={}
for key in AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(AZD,files)
ans=""
if ans=='q':
print "Good bye"
sys.exit()
if ans=='p':
specimen =specimen -1
backup = 1
ans=""
if ans=='s':
keepon=1
spec=raw_input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
specimen =sids.index(spec)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if spec in sids[qq]:tmplist.append(sids[qq])
print specimen," not found, but this was: "
print tmplist
spec=raw_input('Select one or try again\n ')
ans=""
if ans=='b':
if end==0 or end >=len(araiblock[0]):end=len(araiblock[0])-1
GoOn=0
while GoOn==0:
print 'Enter index of first point for calculation: ','[',start,']'
answer=raw_input('return to keep default ')
if answer != "":start=int(answer)
print 'Enter index of last point for calculation: ','[',end,']'
answer=raw_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.plotAZ(AZD,araiblock,zijdblock,s,units[0])
pmagplotlib.plotB(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.plotTRM(AZD['MRM'],Bs,TRMs,Bp,Mp,NLpars,trec['magic_experiment_name'])
print 'Banc= ',float(NLpars['banc'])*1e6
pmagplotlib.drawFIGS(AZD)
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
saveit=raw_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 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.addBorders(AZD,titles,black,purple)
pmagplotlib.saveP(AZD,files)
# pmagplotlib.combineFigs(s,files,3)
if len(CurrRec)>0:
for rec in CurrRec:
PriorRecs.append(rec)
CurrRec=[]
if plots!=1:
ans=raw_input(" Save last plot? 1/[0] ")
if ans=="1":
if fmt != ".pmag":
files={}
for key in AZD.keys():
files[key]=s+'_'+key+fmt
pmagplotlib.saveP(AZD,files)
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"
