def plot_AMS(sdata,pointsize=50,errors='None',bedding=[],incolor='N',):
"""
adapted from pmagplotlib.plotANIS
set errors to 'h' for hext ellipses, 'b' for bootstrap, 'p' for parametric bootstrap
bootstrap trials currently hard-coded as 1000
for bedding, give as [strike,dip] ;
"""
subplot_net() #set up stereonet
if incolor=='N': colours=['0.4','0.6','0.5'] #specify greyscale colours
else: colours=['lightcoral','lightskyblue','lightgreen']
#if bedding plot bedding plane
if bedding !=[]:
# hard-coded version of pmag.plotC
D_c,I_c=pmag.circ(bedding[0]-90.,90.-bedding[1],90.)
X_c_d,Y_c_d=[],[]
for k in range(len(D_c)):
XY=pmag.dimap(D_c[k],I_c[k])
if I_c[k]>0:
X_c_d.append(XY[0])
Y_c_d.append(XY[1])
plt.plot(X_c_d,Y_c_d,color='grey',dashes=[10,2],linewidth=3,zorder=1)
Vs=[]
#plot individual sample data
for s in sdata:
tau,V=pmag.doseigs(s)
Vs.append(V)
plotEVEC(Vs,pointsize,colours)
#plot mean eigenvectors
nf,sigma,avs=pmag.sbar(sdata)
Vs=[]
mtau,mV=pmag.doseigs(avs)
Vs.append(mV)
plotEVEC(Vs,pointsize*4,['w','w','w'], 'black',7)
#plot confidence limits
hpars=pmag.dohext(nf,sigma,avs)
if errors=='h':
ellpars=[hpars["v1_dec"],hpars["v1_inc"],hpars["e12"],hpars["v2_dec"],hpars["v2_inc"],hpars["e13"],hpars["v3_dec"],hpars["v3_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[hpars["v2_dec"],hpars["v2_inc"],hpars["e23"],hpars["v3_dec"],hpars["v3_inc"],hpars["e12"],hpars["v1_dec"],hpars["v1_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[hpars["v3_dec"],hpars["v3_inc"],hpars["e13"],hpars["v1_dec"],hpars["v1_inc"],hpars["e23"],hpars["v2_dec"],hpars["v2_inc"]]
plotELL(ellpars,'black',1,1)
elif errors=='b' or errors=='p':
if errors=='p': ipar=1
else: ipar=0
Tmean,Vmean,Taus,BVs=pmag.s_boot(sdata,ipar,1000) # get eigenvectors of mean tensor
# the problem with the bootstrap is that for fabrics where one or more eigenvectors is close to the horizontal,
# you end up with dipolar data
bpars=pmag.sbootpars(Taus,BVs,Vmean)
bpars['t1']=hpars['t1']
bpars['t2']=hpars['t2']
bpars['t3']=hpars['t3']
#have to pair zeta value with eta dec/inc, and vice-versa, to align error ellipses correctly.
ellpars=[bpars["v1_dec"],bpars["v1_inc"],bpars["v1_eta"],bpars["v1_eta_dec"],bpars["v1_eta_inc"],bpars["v1_zeta"],bpars["v1_zeta_dec"],bpars["v1_zeta_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[bpars["v2_dec"],bpars["v2_inc"],bpars["v2_eta"],bpars["v2_eta_dec"],bpars["v2_eta_inc"],bpars["v2_zeta"],bpars["v2_zeta_dec"],bpars["v2_zeta_inc"]]
plotELL(ellpars,'black',1,1)
ellpars=[bpars["v3_dec"],bpars["v3_inc"],bpars["v3_eta"],bpars["v3_eta_dec"],bpars["v3_eta_inc"],bpars["v3_zeta"],bpars["v3_zeta_dec"],bpars["v3_zeta_inc"]]
plotELL(ellpars,'black',1,1)
def main():
"""
NAME
s_eigs.py
DESCRIPTION
converts .s format data to eigenparameters.
SYNTAX
s_eigs.py [-h][options]
OPTIONS
-h prints help message and quits
-i allows interactive entry of file name
-f FILE specifies filename on command line
-F FILE specifies output file
< filename, reads from standard input (Unix like operating systems only)
INPUT
x11,x22,x33,x12,x23,x13
OUTPUT
tau_i, dec_i inc_i of eigenvectors
"""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
elif '-i' in sys.argv:
file=raw_input("Enter filename for processing: ")
f=open(file,'rU')
data=f.readlines()
f.close()
elif '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'rU')
data=f.readlines()
f.close()
else:
data=sys.stdin.readlines()
ofile = ""
if '-F' in sys.argv:
ind=sys.argv.index('-F')
ofile=sys.argv[ind+1]
out=open(ofile, "w + a")
for line in data:
s=[]
rec=line.split()
for i in range(6):
s.append(float(rec[i]))
tau,Vdirs=pmag.doseigs(s)
outstring='%10.8f %6.2f %6.2f %10.8f %6.2f %6.2f %10.8f %6.2f %6.2f'%(tau[2],Vdirs[2][0],Vdirs[2][1],tau[1],Vdirs[1][0],Vdirs[1][1],tau[0],Vdirs[0][0],Vdirs[0][1])
if ofile == "":
print outstring
else:
out.write(outstring+'\n')
def plot_AMS(
sdata,
pointsize=50,
errors='None',
bedding=[],
incolor='N',
):
"""
adapted from pmagplotlib.plotANIS
set errors to 'h' for hext ellipses, 'b' for bootstrap, 'p' for parametric bootstrap
bootstrap trials currently hard-coded as 1000
for bedding, give as [strike,dip] ;
"""
subplot_net() #set up stereonet
if incolor == 'N':
colours = ['0.4', '0.6', '0.5'] #specify greyscale colours
else:
colours = ['lightcoral', 'lightskyblue', 'lightgreen']
#if bedding plot bedding plane
if bedding != []:
# hard-coded version of pmag.plotC
D_c, I_c = pmag.circ(bedding[0] - 90., 90. - bedding[1], 90.)
X_c_d, Y_c_d = [], []
for k in range(len(D_c)):
XY = pmag.dimap(D_c[k], I_c[k])
if I_c[k] > 0:
X_c_d.append(XY[0])
Y_c_d.append(XY[1])
plt.plot(X_c_d,
Y_c_d,
color='grey',
dashes=[10, 2],
linewidth=3,
zorder=1)
Vs = []
#plot individual sample data
for s in sdata:
tau, V = pmag.doseigs(s)
Vs.append(V)
plotEVEC(Vs, pointsize, colours)
#plot mean eigenvectors
nf, sigma, avs = pmag.sbar(sdata)
Vs = []
mtau, mV = pmag.doseigs(avs)
Vs.append(mV)
plotEVEC(Vs, pointsize * 4, ['w', 'w', 'w'], 'black', 7)
#plot confidence limits
hpars = pmag.dohext(nf, sigma, avs)
if errors == 'h':
ellpars = [
hpars["v1_dec"], hpars["v1_inc"], hpars["e12"], hpars["v2_dec"],
hpars["v2_inc"], hpars["e13"], hpars["v3_dec"], hpars["v3_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
hpars["v2_dec"], hpars["v2_inc"], hpars["e23"], hpars["v3_dec"],
hpars["v3_inc"], hpars["e12"], hpars["v1_dec"], hpars["v1_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
hpars["v3_dec"], hpars["v3_inc"], hpars["e13"], hpars["v1_dec"],
hpars["v1_inc"], hpars["e23"], hpars["v2_dec"], hpars["v2_inc"]
]
plotELL(ellpars, 'black', 1, 1)
elif errors == 'b' or errors == 'p':
if errors == 'p': ipar = 1
else: ipar = 0
Tmean, Vmean, Taus, BVs = pmag.s_boot(
sdata, ipar, 1000) # get eigenvectors of mean tensor
# the problem with the bootstrap is that for fabrics where one or more eigenvectors is close to the horizontal,
# you end up with dipolar data
bpars = pmag.sbootpars(Taus, BVs, Vmean)
bpars['t1'] = hpars['t1']
bpars['t2'] = hpars['t2']
bpars['t3'] = hpars['t3']
#have to pair zeta value with eta dec/inc, and vice-versa, to align error ellipses correctly.
ellpars = [
bpars["v1_dec"], bpars["v1_inc"], bpars["v1_eta"],
bpars["v1_eta_dec"], bpars["v1_eta_inc"], bpars["v1_zeta"],
bpars["v1_zeta_dec"], bpars["v1_zeta_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
bpars["v2_dec"], bpars["v2_inc"], bpars["v2_eta"],
bpars["v2_eta_dec"], bpars["v2_eta_inc"], bpars["v2_zeta"],
bpars["v2_zeta_dec"], bpars["v2_zeta_inc"]
]
plotELL(ellpars, 'black', 1, 1)
ellpars = [
bpars["v3_dec"], bpars["v3_inc"], bpars["v3_eta"],
bpars["v3_eta_dec"], bpars["v3_eta_inc"], bpars["v3_zeta"],
bpars["v3_zeta_dec"], bpars["v3_zeta_inc"]
]
plotELL(ellpars, 'black', 1, 1)
def main():
"""
NAME
aniso_magic.py
DESCRIPTION
plots anisotropy data with either bootstrap or hext ellipses
SYNTAX
aniso_magic.py [-h] [command line options]
OPTIONS
-h plots help message and quits
-usr USER: set the user name
-f AFILE, specify rmag_anisotropy formatted file for input
-F RFILE, specify rmag_results formatted file for output
-x Hext [1963] and bootstrap
-B DON'T do bootstrap, do Hext
-par Tauxe [1998] parametric bootstrap
-v plot bootstrap eigenvectors instead of ellipses
-sit plot by site instead of entire file
-crd [s,g,t] coordinate system, default is specimen (g=geographic, t=tilt corrected)
-P don't make any plots - just make rmag_results table
-sav don't make the rmag_results table - just save all the plots
-fmt [svg, png, jpg] format for output images, pdf default
-gtc DEC INC dec,inc of pole to great circle
-d Vi DEC INC; Vi (1,2,3) to compare to direction DEC INC
-nb N; specifies the number of bootstraps - default is 1000
DEFAULTS
AFILE: rmag_anisotropy.txt
RFILE: rmag_results.txt
plot bootstrap ellipses of Constable & Tauxe [1987]
NOTES
minor axis: circles
major axis: triangles
principal axis: squares
directions are plotted on the lower hemisphere
for bootstrapped eigenvector components: Xs: blue, Ys: red, Zs: black
"""
#
dir_path="."
version_num=pmag.get_version()
verbose=pmagplotlib.verbose
args=sys.argv
ipar,ihext,ivec,iboot,imeas,isite,iplot,vec=0,0,0,1,1,0,1,0
hpars,bpars,PDir=[],[],[]
CS,crd='-1','s'
nb=1000
fmt='eps'
ResRecs=[]
orlist=[]
outfile,comp,Dir,gtcirc,PDir='rmag_results.txt',0,[],0,[]
infile='rmag_anisotropy.txt'
if "-h" in args:
print main.__doc__
sys.exit()
if '-WD' in args:
ind=args.index('-WD')
dir_path=args[ind+1]
if '-nb' in args:
ind=args.index('-nb')
nb=int(args[ind+1])
if '-usr' in args:
ind=args.index('-usr')
user=args[ind+1]
else:
user=""
if '-B' in args:iboot,ihext=0,1
if '-par' in args:ipar=1
if '-x' in args:ihext=1
if '-v' in args:ivec=1
if '-sit' in args:isite=1
if '-P' in args:iplot=0
if '-f' in args:
ind=args.index('-f')
infile=args[ind+1]
if '-F' in args:
ind=args.index('-F')
outfile=args[ind+1]
if '-crd' in sys.argv:
ind=sys.argv.index('-crd')
crd=sys.argv[ind+1]
if crd=='g':CS='0'
if crd=='t': CS='100'
if '-fmt' in args:
ind=args.index('-fmt')
fmt=args[ind+1]
if '-sav' in args:
plots=1
verbose=0
else:
plots=0
if '-gtc' in args:
ind=args.index('-gtc')
d,i=float(args[ind+1]),float(args[ind+2])
PDir.append(d)
PDir.append(i)
if '-d' in args:
comp=1
ind=args.index('-d')
vec=int(args[ind+1])-1
Dir=[float(args[ind+2]),float(args[ind+3])]
#
# set up plots
#
infile=dir_path+'/'+infile
outfile=dir_path+'/'+outfile
ANIS={}
initcdf,inittcdf=0,0
ANIS['data'],ANIS['conf']=1,2
if iboot==1:
ANIS['tcdf']=3
if iplot==1:
inittcdf=1
pmagplotlib.plot_init(ANIS['tcdf'],5,5)
if comp==1 and iplot==1:
initcdf=1
ANIS['vxcdf'],ANIS['vycdf'],ANIS['vzcdf']=4,5,6
pmagplotlib.plot_init(ANIS['vxcdf'],5,5)
pmagplotlib.plot_init(ANIS['vycdf'],5,5)
pmagplotlib.plot_init(ANIS['vzcdf'],5,5)
if iplot==1:
pmagplotlib.plot_init(ANIS['conf'],5,5)
pmagplotlib.plot_init(ANIS['data'],5,5)
# read in the data
data,ifiletype=pmag.magic_read(infile)
for rec in data: # find all the orientation systems
if 'anisotropy_tilt_correction' not in rec.keys():rec['anisotropy_tilt_correction']='-1'
if rec['anisotropy_tilt_correction'] not in orlist:
orlist.append(rec['anisotropy_tilt_correction'])
if CS not in orlist:
if len(orlist)>0:
CS=orlist[0]
else:
CS='-1'
if CS=='-1':crd='s'
if CS=='0':crd='g'
if CS=='100':crd='t'
if verbose:print "desired coordinate system not available, using available: ",crd
if isite==1:
sitelist=[]
for rec in data:
if rec['er_site_name'] not in sitelist:sitelist.append(rec['er_site_name'])
sitelist.sort()
plt=len(sitelist)
else:plt=1
k=0
while k<plt:
site=""
sdata,Ss=[],[] # list of S format data
Locs,Sites,Samples,Specimens,Cits=[],[],[],[],[]
if isite==0:
sdata=data
else:
site=sitelist[k]
for rec in data:
if rec['er_site_name']==site:sdata.append(rec)
anitypes=[]
csrecs=pmag.get_dictitem(sdata,'anisotropy_tilt_correction',CS,'T')
for rec in csrecs:
if rec['anisotropy_type'] not in anitypes:anitypes.append(rec['anisotropy_type'])
if rec['er_location_name'] not in Locs:Locs.append(rec['er_location_name'])
if rec['er_site_name'] not in Sites:Sites.append(rec['er_site_name'])
if rec['er_sample_name'] not in Samples:Samples.append(rec['er_sample_name'])
if rec['er_specimen_name'] not in Specimens:Specimens.append(rec['er_specimen_name'])
if rec['er_citation_names'] not in Cits:Cits.append(rec['er_citation_names'])
s=[]
s.append(float(rec["anisotropy_s1"]))
s.append(float(rec["anisotropy_s2"]))
s.append(float(rec["anisotropy_s3"]))
s.append(float(rec["anisotropy_s4"]))
s.append(float(rec["anisotropy_s5"]))
s.append(float(rec["anisotropy_s6"]))
if s[0]<=1.0:Ss.append(s) # protect against crap
tau,Vdirs=pmag.doseigs(s)
ResRec={}
ResRec['er_location_names']=rec['er_location_name']
ResRec['er_citation_names']=rec['er_citation_names']
ResRec['er_site_names']=rec['er_site_name']
ResRec['er_sample_names']=rec['er_sample_name']
ResRec['er_specimen_names']=rec['er_specimen_name']
ResRec['rmag_result_name']=rec['er_specimen_name']+":"+rec['anisotropy_type']
ResRec["er_analyst_mail_names"]=user
ResRec["tilt_correction"]=CS
ResRec["anisotropy_type"]=rec['anisotropy_type']
ResRec["anisotropy_v1_dec"]='%7.1f'%(Vdirs[0][0])
ResRec["anisotropy_v2_dec"]='%7.1f'%(Vdirs[1][0])
ResRec["anisotropy_v3_dec"]='%7.1f'%(Vdirs[2][0])
ResRec["anisotropy_v1_inc"]='%7.1f'%(Vdirs[0][1])
ResRec["anisotropy_v2_inc"]='%7.1f'%(Vdirs[1][1])
ResRec["anisotropy_v3_inc"]='%7.1f'%(Vdirs[2][1])
ResRec["anisotropy_t1"]='%10.8f'%(tau[0])
ResRec["anisotropy_t2"]='%10.8f'%(tau[1])
ResRec["anisotropy_t3"]='%10.8f'%(tau[2])
ResRec['anisotropy_type']=pmag.makelist(anitypes)
ResRecs.append(ResRec)
if len(Ss)>1:
title="LO:_"+ResRec['er_location_names']+'_SI:_'+site+'_SA:__SP:__CO:_'+crd
ResRec['er_location_names']=pmag.makelist(Locs)
bpars,hpars=pmagplotlib.plotANIS(ANIS,Ss,iboot,ihext,ivec,ipar,title,iplot,comp,vec,Dir,nb)
if len(PDir)>0:
pmagplotlib.plotC(ANIS['data'],PDir,90.,'g')
pmagplotlib.plotC(ANIS['conf'],PDir,90.,'g')
if verbose:pmagplotlib.drawFIGS(ANIS)
ResRec['er_location_names']=pmag.makelist(Locs)
if plots==1:
save(ANIS,fmt,title)
sys.exit()
ResRec={}
ResRec['er_citation_names']=pmag.makelist(Cits)
ResRec['er_location_names']=pmag.makelist(Locs)
ResRec['er_site_names']=pmag.makelist(Sites)
ResRec['er_sample_names']=pmag.makelist(Samples)
ResRec['er_specimen_names']=pmag.makelist(Specimens)
ResRec['rmag_result_name']=pmag.makelist(Sites)+":"+pmag.makelist(anitypes)
ResRec['anisotropy_type']=pmag.makelist(anitypes)
ResRec["er_analyst_mail_names"]=user
ResRec["tilt_correction"]=CS
if isite=="0":ResRec['result_description']="Study average using coordinate system: "+ CS
if isite=="1":ResRec['result_description']="Site average using coordinate system: " +CS
if hpars!=[] and ihext==1:
HextRec={}
for key in ResRec.keys():HextRec[key]=ResRec[key] # copy over stuff
HextRec["anisotropy_v1_dec"]='%7.1f'%(hpars["v1_dec"])
HextRec["anisotropy_v2_dec"]='%7.1f'%(hpars["v2_dec"])
HextRec["anisotropy_v3_dec"]='%7.1f'%(hpars["v3_dec"])
HextRec["anisotropy_v1_inc"]='%7.1f'%(hpars["v1_inc"])
HextRec["anisotropy_v2_inc"]='%7.1f'%(hpars["v2_inc"])
HextRec["anisotropy_v3_inc"]='%7.1f'%(hpars["v3_inc"])
HextRec["anisotropy_t1"]='%10.8f'%(hpars["t1"])
HextRec["anisotropy_t2"]='%10.8f'%(hpars["t2"])
HextRec["anisotropy_t3"]='%10.8f'%(hpars["t3"])
HextRec["anisotropy_hext_F"]='%7.1f '%(hpars["F"])
HextRec["anisotropy_hext_F12"]='%7.1f '%(hpars["F12"])
HextRec["anisotropy_hext_F23"]='%7.1f '%(hpars["F23"])
HextRec["anisotropy_v1_eta_semi_angle"]='%7.1f '%(hpars["e12"])
HextRec["anisotropy_v1_eta_dec"]='%7.1f '%(hpars["v2_dec"])
HextRec["anisotropy_v1_eta_inc"]='%7.1f '%(hpars["v2_inc"])
HextRec["anisotropy_v1_zeta_semi_angle"]='%7.1f '%(hpars["e13"])
HextRec["anisotropy_v1_zeta_dec"]='%7.1f '%(hpars["v3_dec"])
HextRec["anisotropy_v1_zeta_inc"]='%7.1f '%(hpars["v3_inc"])
HextRec["anisotropy_v2_eta_semi_angle"]='%7.1f '%(hpars["e12"])
HextRec["anisotropy_v2_eta_dec"]='%7.1f '%(hpars["v1_dec"])
HextRec["anisotropy_v2_eta_inc"]='%7.1f '%(hpars["v1_inc"])
HextRec["anisotropy_v2_zeta_semi_angle"]='%7.1f '%(hpars["e23"])
HextRec["anisotropy_v2_zeta_dec"]='%7.1f '%(hpars["v3_dec"])
HextRec["anisotropy_v2_zeta_inc"]='%7.1f '%(hpars["v3_inc"])
HextRec["anisotropy_v3_eta_semi_angle"]='%7.1f '%(hpars["e12"])
HextRec["anisotropy_v3_eta_dec"]='%7.1f '%(hpars["v1_dec"])
HextRec["anisotropy_v3_eta_inc"]='%7.1f '%(hpars["v1_inc"])
HextRec["anisotropy_v3_zeta_semi_angle"]='%7.1f '%(hpars["e23"])
HextRec["anisotropy_v3_zeta_dec"]='%7.1f '%(hpars["v2_dec"])
HextRec["anisotropy_v3_zeta_inc"]='%7.1f '%(hpars["v2_inc"])
HextRec["magic_method_codes"]='LP-AN:AE-H'
if verbose:
print "Hext Statistics: "
print " tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I"
print HextRec["anisotropy_t1"], HextRec["anisotropy_v1_dec"], HextRec["anisotropy_v1_inc"], HextRec["anisotropy_v1_eta_semi_angle"], HextRec["anisotropy_v1_eta_dec"], HextRec["anisotropy_v1_eta_inc"], HextRec["anisotropy_v1_zeta_semi_angle"], HextRec["anisotropy_v1_zeta_dec"], HextRec["anisotropy_v1_zeta_inc"]
print HextRec["anisotropy_t2"],HextRec["anisotropy_v2_dec"], HextRec["anisotropy_v2_inc"], HextRec["anisotropy_v2_eta_semi_angle"], HextRec["anisotropy_v2_eta_dec"], HextRec["anisotropy_v2_eta_inc"], HextRec["anisotropy_v2_zeta_semi_angle"], HextRec["anisotropy_v2_zeta_dec"], HextRec["anisotropy_v2_zeta_inc"]
print HextRec["anisotropy_t3"], HextRec["anisotropy_v3_dec"], HextRec["anisotropy_v3_inc"], HextRec["anisotropy_v3_eta_semi_angle"], HextRec["anisotropy_v3_eta_dec"], HextRec["anisotropy_v3_eta_inc"], HextRec["anisotropy_v3_zeta_semi_angle"], HextRec["anisotropy_v3_zeta_dec"], HextRec["anisotropy_v3_zeta_inc"]
HextRec['magic_software_packages']=version_num
ResRecs.append(HextRec)
if bpars!=[]:
BootRec={}
for key in ResRec.keys():BootRec[key]=ResRec[key] # copy over stuff
BootRec["anisotropy_v1_dec"]='%7.1f'%(bpars["v1_dec"])
BootRec["anisotropy_v2_dec"]='%7.1f'%(bpars["v2_dec"])
BootRec["anisotropy_v3_dec"]='%7.1f'%(bpars["v3_dec"])
BootRec["anisotropy_v1_inc"]='%7.1f'%(bpars["v1_inc"])
BootRec["anisotropy_v2_inc"]='%7.1f'%(bpars["v2_inc"])
BootRec["anisotropy_v3_inc"]='%7.1f'%(bpars["v3_inc"])
BootRec["anisotropy_t1"]='%10.8f'%(bpars["t1"])
BootRec["anisotropy_t2"]='%10.8f'%(bpars["t2"])
BootRec["anisotropy_t3"]='%10.8f'%(bpars["t3"])
BootRec["anisotropy_v1_eta_inc"]='%7.1f '%(bpars["v1_eta_inc"])
BootRec["anisotropy_v1_eta_dec"]='%7.1f '%(bpars["v1_eta_dec"])
BootRec["anisotropy_v1_eta_semi_angle"]='%7.1f '%(bpars["v1_eta"])
BootRec["anisotropy_v1_zeta_inc"]='%7.1f '%(bpars["v1_zeta_inc"])
BootRec["anisotropy_v1_zeta_dec"]='%7.1f '%(bpars["v1_zeta_dec"])
BootRec["anisotropy_v1_zeta_semi_angle"]='%7.1f '%(bpars["v1_zeta"])
BootRec["anisotropy_v2_eta_inc"]='%7.1f '%(bpars["v2_eta_inc"])
BootRec["anisotropy_v2_eta_dec"]='%7.1f '%(bpars["v2_eta_dec"])
BootRec["anisotropy_v2_eta_semi_angle"]='%7.1f '%(bpars["v2_eta"])
BootRec["anisotropy_v2_zeta_inc"]='%7.1f '%(bpars["v2_zeta_inc"])
BootRec["anisotropy_v2_zeta_dec"]='%7.1f '%(bpars["v2_zeta_dec"])
BootRec["anisotropy_v2_zeta_semi_angle"]='%7.1f '%(bpars["v2_zeta"])
BootRec["anisotropy_v3_eta_inc"]='%7.1f '%(bpars["v3_eta_inc"])
BootRec["anisotropy_v3_eta_dec"]='%7.1f '%(bpars["v3_eta_dec"])
BootRec["anisotropy_v3_eta_semi_angle"]='%7.1f '%(bpars["v3_eta"])
BootRec["anisotropy_v3_zeta_inc"]='%7.1f '%(bpars["v3_zeta_inc"])
BootRec["anisotropy_v3_zeta_dec"]='%7.1f '%(bpars["v3_zeta_dec"])
BootRec["anisotropy_v3_zeta_semi_angle"]='%7.1f '%(bpars["v3_zeta"])
BootRec["anisotropy_hext_F"]=''
BootRec["anisotropy_hext_F12"]=''
BootRec["anisotropy_hext_F23"]=''
BootRec["magic_method_codes"]='LP-AN:AE-H:AE-BS' # regular bootstrap
if ipar==1:BootRec["magic_method_codes"]='LP-AN:AE-H:AE-BS-P' # parametric bootstrap
if verbose:
print "Boostrap Statistics: "
print " tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I"
print BootRec["anisotropy_t1"], BootRec["anisotropy_v1_dec"], BootRec["anisotropy_v1_inc"], BootRec["anisotropy_v1_eta_semi_angle"], BootRec["anisotropy_v1_eta_dec"], BootRec["anisotropy_v1_eta_inc"], BootRec["anisotropy_v1_zeta_semi_angle"], BootRec["anisotropy_v1_zeta_dec"], BootRec["anisotropy_v1_zeta_inc"]
print BootRec["anisotropy_t2"],BootRec["anisotropy_v2_dec"], BootRec["anisotropy_v2_inc"], BootRec["anisotropy_v2_eta_semi_angle"], BootRec["anisotropy_v2_eta_dec"], BootRec["anisotropy_v2_eta_inc"], BootRec["anisotropy_v2_zeta_semi_angle"], BootRec["anisotropy_v2_zeta_dec"], BootRec["anisotropy_v2_zeta_inc"]
print BootRec["anisotropy_t3"], BootRec["anisotropy_v3_dec"], BootRec["anisotropy_v3_inc"], BootRec["anisotropy_v3_eta_semi_angle"], BootRec["anisotropy_v3_eta_dec"], BootRec["anisotropy_v3_eta_inc"], BootRec["anisotropy_v3_zeta_semi_angle"], BootRec["anisotropy_v3_zeta_dec"], BootRec["anisotropy_v3_zeta_inc"]
BootRec['magic_software_packages']=version_num
ResRecs.append(BootRec)
k+=1
goon=1
while goon==1 and iplot==1 and verbose:
if iboot==1: print "compare with [d]irection "
print " plot [g]reat circle, change [c]oord. system, change [e]llipse calculation, s[a]ve plots, [q]uit "
if isite==1: print " [p]revious, [s]ite, [q]uit, <return> for next "
ans=raw_input("")
if ans=="q":
sys.exit()
if ans=="e":
iboot,ipar,ihext,ivec=1,0,0,0
e=raw_input("Do Hext Statistics 1/[0]: ")
if e=="1":ihext=1
e=raw_input("Suppress bootstrap 1/[0]: ")
if e=="1":iboot=0
if iboot==1:
e=raw_input("Parametric bootstrap 1/[0]: ")
if e=="1":ipar=1
e=raw_input("Plot bootstrap eigenvectors: 1/[0]: ")
if e=="1":ivec=1
if iplot==1:
if inittcdf==0:
ANIS['tcdf']=3
pmagplotlib.plot_init(ANIS['tcdf'],5,5)
inittcdf=1
bpars,hpars=pmagplotlib.plotANIS(ANIS,Ss,iboot,ihext,ivec,ipar,title,iplot,comp,vec,Dir,nb)
pmagplotlib.drawFIGS(ANIS)
if ans=="c":
print "Current Coordinate system is: "
if CS=='-1':print " Specimen"
if CS=='0':print " Geographic"
if CS=='100':print " Tilt corrected"
key=raw_input(" Enter desired coordinate system: [s]pecimen, [g]eographic, [t]ilt corrected ")
if key=='s':CS='-1'
if key=='g':CS='0'
if key=='t': CS='100'
if CS not in orlist:
if len(orlist)>0:
CS=orlist[0]
else:
CS='-1'
if CS=='-1':crd='s'
if CS=='0':crd='g'
if CS=='100':crd='t'
print "desired coordinate system not available, using available: ",crd
k-=1
goon=0
if ans=="":
if isite==1:
goon=0
else:
print "Good bye "
sys.exit()
if ans=='d':
if initcdf==0:
initcdf=1
ANIS['vxcdf'],ANIS['vycdf'],ANIS['vzcdf']=4,5,6
pmagplotlib.plot_init(ANIS['vxcdf'],5,5)
pmagplotlib.plot_init(ANIS['vycdf'],5,5)
pmagplotlib.plot_init(ANIS['vzcdf'],5,5)
Dir,comp=[],1
print """
Input: Vi D I to compare eigenvector Vi with direction D/I
where Vi=1: principal
Vi=2: major
Vi=3: minor
D= declination of comparison direction
I= inclination of comparison direction"""
con=1
while con==1:
try:
vdi=raw_input("Vi D I: ").split()
vec=int(vdi[0])-1
Dir=[float(vdi[1]),float(vdi[2])]
con=0
except IndexError:
print " Incorrect entry, try again "
bpars,hpars=pmagplotlib.plotANIS(ANIS,Ss,iboot,ihext,ivec,ipar,title,iplot,comp,vec,Dir,nb)
Dir,comp=[],0
if ans=='g':
con,cnt=1,0
while con==1:
try:
print " Input: input pole to great circle ( D I) to plot a great circle: "
di=raw_input(" D I: ").split()
PDir.append(float(di[0]))
PDir.append(float(di[1]))
con=0
except:
cnt+=1
if cnt<10:
print " enter the dec and inc of the pole on one line "
else:
print "ummm - you are doing something wrong - i give up"
sys.exit()
pmagplotlib.plotC(ANIS['data'],PDir,90.,'g')
pmagplotlib.plotC(ANIS['conf'],PDir,90.,'g')
if verbose:pmagplotlib.drawFIGS(ANIS)
if ans=="p":
k-=2
goon=0
if ans=="q":
k=plt
goon=0
if ans=="s":
keepon=1
site=raw_input(" print site or part of site desired: ")
while keepon==1:
try:
k=sitelist.index(site)
keepon=0
except:
tmplist=[]
for qq in range(len(sitelist)):
if site in sitelist[qq]:tmplist.append(sitelist[qq])
print site," not found, but this was: "
print tmplist
site=raw_input('Select one or try again\n ')
k=sitelist.index(site)
goon,ans=0,""
if ans=="a":
locs=pmag.makelist(Locs)
title="LO:_"+locs+'_SI:__'+'_SA:__SP:__CO:_'+crd
save(ANIS,fmt,title)
goon=0
else:
if verbose:print 'skipping plot - not enough data points'
k+=1
# put rmag_results stuff here
if plots==0:
if len(ResRecs)>0:
pmag.magic_write(outfile,ResRecs,'rmag_results')
if verbose:print "Anisotropy results saved in ",outfile
if verbose:
print " Good bye "
def main():
"""
NAME
ANI_depthplot.py
DESCRIPTION
plots tau, V3_inc versus core_depth
SYNTAX
ANI_depthplot.py [command line optins]
OPTIONS
-h prints help message and quits
-f FILE: specify input rmag_anisotropy format file from magic
-fb FILE: specify input magic_measurements format file from magic
-fsa FILE: specify input er_samples format file from magic
-d min max [in m] depth range to plot
DEFAULTS:
Anisotropy file: rmag_anisotropy.txt
Bulk susceptibility file: magic_measurements.txt
Samples file: er_samples.txt
"""
fmt='.svg'
dir_path="./"
pcol=2
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
ani_file=dir_path+'/rmag_anisotropy.txt'
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')
ani_file=dir_path+'/'+sys.argv[ind+1]
if '-fb' in sys.argv:
ind=sys.argv.index('-fb')
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]
dmin,dmax=-1,-1
if '-d' in sys.argv:
ind=sys.argv.index('-d')
dmin=float(sys.argv[ind+1])
dmax=float(sys.argv[ind+2])
#
# get data read in
isbulk=0
AniData,file_type=pmag.magic_read(ani_file)
Samps,file_type=pmag.magic_read(samp_file)
Meas,file_type=pmag.magic_read(meas_file)
if file_type=='magic_measurements':isbulk=1
Data=[]
Bulks=[]
BulkDepths=[]
bmin,bmax=1e6,-1e6
for rec in AniData:
for samp in Samps:
if samp['er_sample_name'].upper()== rec['er_sample_name'].upper() and 'sample_core_depth' in samp.keys() and samp['sample_core_depth']!="":
rec['core_depth'] = samp['sample_core_depth']
if dmax==-1 or float(rec['core_depth'])<dmax and float(rec['core_depth'])>dmin:
Data.append(rec) # fish out data with core_depth
if isbulk:
thisbulk=[]
for meas in Meas:
if meas['er_specimen_name']== rec['er_specimen_name'] and 'measurement_chi_volume' in meas.keys() and meas['measurement_chi_volume'].strip()!="" :
Bulks.append(1e6*float(meas['measurement_chi_volume']))
if Bulks[-1]<bmin:bmin=Bulks[-1]
if Bulks[-1]>bmax:bmax=Bulks[-1]
BulkDepths.append(float(samp['sample_core_depth']))
xlab="Depth (m)"
if len(Data)>0:
location=Data[0]['er_location_name']
else:
print 'no data to plot'
sys.exit()
# collect the data for plotting tau and V3_inc
Depths,Tau1,Tau2,Tau3,V3Incs=[],[],[],[],[]
tau_min,tau_max=1,0
if len(Bulks)>0: pcol+=1
for rec in Data:
s=[]
Depths.append(float(rec['core_depth']))
s.append(float(rec['anisotropy_s1']))
s.append(float(rec['anisotropy_s2']))
s.append(float(rec['anisotropy_s3']))
s.append(float(rec['anisotropy_s4']))
s.append(float(rec['anisotropy_s5']))
s.append(float(rec['anisotropy_s6']))
tau,Vdirs=pmag.doseigs(s)
Tau1.append(tau[0])
Tau2.append(tau[1])
Tau3.append(tau[2])
if tau[0]>tau_max:tau_max=tau[0]
if tau[2]<tau_min:tau_min=tau[2]
V3Incs.append(Vdirs[2][1])
if len(Depths)>0:
if dmax==-1:
dmax=max(Depths)
dmin=min(Depths)
#dmax=dmax+.05*dmax
#dmin=dmin-.05*dmax
pylab.figure(1,figsize=(10,8))
version_num=pmag.get_version()
pylab.figtext(.02,.01,version_num)
pylab.subplot(1,pcol,1)
pylab.plot(Tau1,Depths,'rs')
pylab.plot(Tau2,Depths,'b^')
pylab.plot(Tau3,Depths,'ko')
pylab.axis([tau_min,tau_max,dmax,dmin])
pylab.xlabel('Eigenvalues')
pylab.ylabel('Depth (m)')
pylab.subplot(1,pcol,2)
pylab.plot(V3Incs,Depths,'ko')
pylab.axis([0,90,dmax,dmin])
pylab.xlabel('V3 Inclination')
pylab.title(location)
if pcol==3:
pylab.subplot(1,pcol,3)
pylab.plot(Bulks,BulkDepths,'bo')
pylab.axis([bmin-1,bmax+1,dmax,dmin])
pylab.xlabel('Bulk Susc. (uSI)')
pylab.draw()
ans=raw_input("Press return to quit ")
sys.exit()
else:
print "No data points met your criteria - try again"