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"