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 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 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.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 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 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)