コード例 #1
0
ファイル: eqarea_magic.py プロジェクト: danielebrandt/PmagPy
def main():
    """
    NAME
        eqarea_magic.py

    DESCRIPTION
       makes equal area projections from declination/inclination data

    SYNTAX
        eqarea_magic.py [command line options]

    INPUT
       takes magic formatted sites, samples, specimens, or measurements

    OPTIONS
        -h prints help message and quits
        -f FILE: specify input magic format file from magic, default='sites.txt'
         supported types=[measurements, specimens, samples, sites]
        -fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
                default='specimens.txt'
        -fsa FILE: specify sample file name, (required if you want to plot specimens by site)
                default='samples.txt'
        -fsi FILE: specify site file name, default='sites.txt'

        -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
    """
    # initialize some default variables
    FIG = {} # plot dictionary
    FIG['eqarea'] = 1 # eqarea is figure 1
    plotE = 0
    plt = 0  # default to not plotting
    verbose = pmagplotlib.verbose
    # extract arguments from sys.argv
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    dir_path = pmag.get_named_arg_from_sys("-WD", default_val=".")
    pmagplotlib.plot_init(FIG['eqarea'],5,5)
    in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
    in_file = pmag.resolve_file_name(in_file, dir_path)
    if "-WD" not in sys.argv:
        dir_path = os.path.split(in_file)[0]
    #full_in_file = os.path.join(dir_path, in_file)
    plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
    spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
    samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
    site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
    if plot_by == 'all':
        plot_key = 'all'
    elif plot_by == 'sit':
        plot_key = 'site'
    elif plot_by == 'sam':
        plot_key = 'sample'
    elif plot_by == 'spc':
        plot_key = 'specimen'
    else:
        plot_by = 'all'
        plot_key = 'all'
    if '-c' in sys.argv:
        contour = 1
    else:
        contour = 0
    if '-sav' in sys.argv:
        plt = 1
        verbose = 0
    if '-ell' in sys.argv:
        plotE = 1
        ind = sys.argv.index('-ell')
        ell_type = sys.argv[ind+1]
        ell_type = pmag.get_named_arg_from_sys("-ell", "F")
        dist = ell_type.upper()
        # if dist type is unrecognized, use Fisher
        if dist not in ['F', 'K', 'B', 'BE', 'BV']:
            dist = 'F'
        if dist == "BV":
            FIG['bdirs'] = 2
            pmagplotlib.plot_init(FIG['bdirs'],5,5)
    crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
    if crd == "s":
        coord = "-1"
    elif crd == "t":
        coord = "100"
    else:
        coord = "0"

    fmt = pmag.get_named_arg_from_sys("-fmt", "svg")

    dec_key = 'dir_dec'
    inc_key = 'dir_inc'
    tilt_key = 'dir_tilt_correction'
    #Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']

    #
    fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
    contribution = nb.Contribution(dir_path, custom_filenames=fnames,
                                   single_file=in_file)

    try:
        contribution.propagate_location_to_samples()
        contribution.propagate_location_to_specimens()
        contribution.propagate_location_to_measurements()
    except KeyError as ex:
        pass

    # the object that contains the DataFrame + useful helper methods:
    table_name = list(contribution.tables.keys())[0]
    data_container = contribution.tables[table_name]
    # the actual DataFrame:
    data = data_container.df

    if plot_key != "all" and plot_key not in data.columns:
        print("-E- You can't plot by {} with the data provided".format(plot_key))
        return

    # add tilt key into DataFrame columns if it isn't there already
    if tilt_key not in data.columns:
        data.loc[:, tilt_key] = None

    if verbose:
        print(len(data), ' records read from ', in_file)

    # find desired dec,inc data:
    dir_type_key = ''
    #
    # get plotlist if not plotting all records
    #
    plotlist=[]
    if plot_key != "all":
        # return all where plot_key is not blank
        if plot_key not in data.columns:
            print('Can\'t plot by "{}".  That header is not in infile: {}'.format(plot_key, in_file))
            return
        plots = data[data[plot_key].notnull()]
        plotlist = plots[plot_key].unique() # grab unique values
    else:
        plotlist.append('All')

    for plot in plotlist:
        if verbose:
            print(plot)
        if plot == 'All':
            # plot everything at once
            plot_data = data
        else:
            # pull out only partial data
            plot_data = data[data[plot_key] == plot]

        DIblock = []
        GCblock = []
        # SLblock, SPblock = [], []
        title = plot
        mode = 1
        k = 0


        if dec_key not in plot_data.columns:
            print("-W- No dec/inc data")
            continue
        # get all records where dec & inc values exist
        plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
        if plot_data.empty:
            continue
        # this sorting out is done in get_di_bock
        #if coord == '0':  # geographic, use records with no tilt key (or tilt_key 0)
        #    cond1 = plot_data[tilt_key].fillna('') == coord
        #    cond2 = plot_data[tilt_key].isnull()
        #    plot_data = plot_data[cond1 | cond2]
        #else:  # not geographic coordinates, use only records with correct tilt_key
        #    plot_data = plot_data[plot_data[tilt_key] == coord]

        # get metadata for naming the plot file
        locations = data_container.get_name('location', df_slice=plot_data)
        site = data_container.get_name('site', df_slice=plot_data)
        sample = data_container.get_name('sample', df_slice=plot_data)
        specimen = data_container.get_name('specimen', df_slice=plot_data)

        # make sure method_codes is in plot_data
        if 'method_codes' not in plot_data.columns:
            plot_data['method_codes'] = ''

        # get data blocks
        DIblock = data_container.get_di_block(df_slice=plot_data,
                                              tilt_corr=coord, excl=['DE-BFP'])
        #SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
        # get great circles
        great_circle_data = data_container.get_records_for_code('DE-BFP', incl=True,
                                                                use_slice=True, sli=plot_data)

        if len(great_circle_data) > 0:
            gc_cond = great_circle_data[tilt_key] == coord
            GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
            #SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]

        if len(DIblock) > 0:
            if contour == 0:
                pmagplotlib.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 len(DIblock) == 0 and len(GCblock) == 0:
            if verbose:
                print("no records for plotting")
            continue
            #sys.exit()
        if plotE == 1:
            ppars = pmag.doprinc(DIblock) # get principal directions
            nDIs, rDIs, npars, rpars = [], [], [], []
            for rec in DIblock:
                angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
                if angle>90.:
                    rDIs.append(rec)
                else:
                    nDIs.append(rec)
            if dist=='B': # do on whole dataset
                etitle="Bingham confidence ellipse"
                bpars=pmag.dobingham(DIblock)
                for key in list(bpars.keys()):
                    if key!='n' and verbose: print("    ",key, '%7.1f'%(bpars[key]))
                    if key=='n' and verbose: print("    ",key, '       %i'%(bpars[key]))
                npars.append(bpars['dec'])
                npars.append(bpars['inc'])
                npars.append(bpars['Zeta'])
                npars.append(bpars['Zdec'])
                npars.append(bpars['Zinc'])
                npars.append(bpars['Eta'])
                npars.append(bpars['Edec'])
                npars.append(bpars['Einc'])
            if dist=='F':
                etitle="Fisher confidence cone"
                if len(nDIs)>2:
                    fpars=pmag.fisher_mean(nDIs)
                    for key in list(fpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(fpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(fpars[key]))
                    mode+=1
                    npars.append(fpars['dec'])
                    npars.append(fpars['inc'])
                    npars.append(fpars['alpha95']) # Beta
                    npars.append(fpars['dec'])
                    isign=old_div(abs(fpars['inc']),fpars['inc'])
                    npars.append(fpars['inc']-isign*90.) #Beta inc
                    npars.append(fpars['alpha95']) # gamma
                    npars.append(fpars['dec']+90.) # Beta dec
                    npars.append(0.) #Beta inc
                if len(rDIs)>2:
                    fpars=pmag.fisher_mean(rDIs)
                    if verbose: print("mode ",mode)
                    for key in list(fpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(fpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(fpars[key]))
                    mode+=1
                    rpars.append(fpars['dec'])
                    rpars.append(fpars['inc'])
                    rpars.append(fpars['alpha95']) # Beta
                    rpars.append(fpars['dec'])
                    isign=old_div(abs(fpars['inc']),fpars['inc'])
                    rpars.append(fpars['inc']-isign*90.) #Beta inc
                    rpars.append(fpars['alpha95']) # gamma
                    rpars.append(fpars['dec']+90.) # Beta dec
                    rpars.append(0.) #Beta inc
            if dist=='K':
                etitle="Kent confidence ellipse"
                if len(nDIs)>3:
                    kpars=pmag.dokent(nDIs,len(nDIs))
                    if verbose: print("mode ",mode)
                    for key in list(kpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(kpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(kpars[key]))
                    mode+=1
                    npars.append(kpars['dec'])
                    npars.append(kpars['inc'])
                    npars.append(kpars['Zeta'])
                    npars.append(kpars['Zdec'])
                    npars.append(kpars['Zinc'])
                    npars.append(kpars['Eta'])
                    npars.append(kpars['Edec'])
                    npars.append(kpars['Einc'])
                if len(rDIs)>3:
                    kpars=pmag.dokent(rDIs,len(rDIs))
                    if verbose: print("mode ",mode)
                    for key in list(kpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(kpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(kpars[key]))
                    mode+=1
                    rpars.append(kpars['dec'])
                    rpars.append(kpars['inc'])
                    rpars.append(kpars['Zeta'])
                    rpars.append(kpars['Zdec'])
                    rpars.append(kpars['Zinc'])
                    rpars.append(kpars['Eta'])
                    rpars.append(kpars['Edec'])
                    rpars.append(kpars['Einc'])
            else: # assume bootstrap
                if dist=='BE':
                    if len(nDIs)>5:
                        BnDIs=pmag.di_boot(nDIs)
                        Bkpars=pmag.dokent(BnDIs,1.)
                        if verbose: print("mode ",mode)
                        for key in list(Bkpars.keys()):
                            if key!='n' and verbose: print("    ",key, '%7.1f'%(Bkpars[key]))
                            if key=='n' and verbose: print("    ",key, '       %i'%(Bkpars[key]))
                        mode+=1
                        npars.append(Bkpars['dec'])
                        npars.append(Bkpars['inc'])
                        npars.append(Bkpars['Zeta'])
                        npars.append(Bkpars['Zdec'])
                        npars.append(Bkpars['Zinc'])
                        npars.append(Bkpars['Eta'])
                        npars.append(Bkpars['Edec'])
                        npars.append(Bkpars['Einc'])
                    if len(rDIs)>5:
                        BrDIs=pmag.di_boot(rDIs)
                        Bkpars=pmag.dokent(BrDIs,1.)
                        if verbose: print("mode ",mode)
                        for key in list(Bkpars.keys()):
                            if key!='n' and verbose: print("    ",key, '%7.1f'%(Bkpars[key]))
                            if key=='n' and verbose: print("    ",key, '       %i'%(Bkpars[key]))
                        mode+=1
                        rpars.append(Bkpars['dec'])
                        rpars.append(Bkpars['inc'])
                        rpars.append(Bkpars['Zeta'])
                        rpars.append(Bkpars['Zdec'])
                        rpars.append(Bkpars['Zinc'])
                        rpars.append(Bkpars['Eta'])
                        rpars.append(Bkpars['Edec'])
                        rpars.append(Bkpars['Einc'])
                    etitle="Bootstrapped confidence ellipse"
                elif dist=='BV':
                    sym={'lower':['o','c'],'upper':['o','g'],'size':3,'edgecolor':'face'}
                    if len(nDIs)>5:
                        BnDIs=pmag.di_boot(nDIs)
                        pmagplotlib.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)

        for key in list(FIG.keys()):
            files = {}
            filename = pmag.get_named_arg_from_sys('-fname')
            if filename: # use provided filename
                filename+= '.' + fmt
            elif pmagplotlib.isServer: # use server plot naming convention
                filename='LO:_'+locations+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
            elif plot_key == 'all':
                filename = 'all'
                if 'location' in plot_data.columns:
                    locs = plot_data['location'].unique()
                    loc_string = "_".join([loc.replace(' ', '_') for loc in locs])
                    filename += "_" + loc_string
                filename += "_" + crd + "_" + key
                filename += ".{}".format(fmt)
            else: # use more readable naming convention
                filename = ''
                # fix this if plot_by is location , for example
                use_names = {'location': [locations], 'site': [locations, site],
                             'sample': [locations, site, sample],
                             'specimen': [locations, site, sample, specimen]}
                use = use_names[plot_key]
                use.extend([crd, key])
                for item in use: #[locations, site, sample, specimen, crd, key]:
                    if item:
                        item = item.replace(' ', '_')
                        filename += item + '_'
                if filename.endswith('_'):
                    filename = filename[:-1]
                filename += ".{}".format(fmt)

            files[key]=filename

        if pmagplotlib.isServer:
            black     = '#000000'
            purple    = '#800080'
            titles={}
            titles['eq']='Equal Area Plot'
            FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
            pmagplotlib.saveP(FIG,files)

        if plt:
            pmagplotlib.saveP(FIG,files)
            continue
        if verbose:
            pmagplotlib.drawFIGS(FIG)
            ans=input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
            if ans == "q":
                sys.exit()
            if ans == "a":
                pmagplotlib.saveP(FIG,files)
        continue
コード例 #2
0
ファイル: eqarea_magic.py プロジェクト: jbowles100/PmagPy
def main():
    """
    NAME
        eqarea_magic.py

    DESCRIPTION
       makes equal area projections from declination/inclination data

    SYNTAX 
        eqarea_magic.py [command line options]
    
    INPUT 
       takes magic formatted pmag_results, pmag_sites, pmag_samples or pmag_specimens
    
    OPTIONS
        -h prints help message and quits
        -f FILE: specify input magic format file from magic,default='pmag_results.txt'
         supported types=[magic_measurements,pmag_specimens, pmag_samples, pmag_sites, pmag_results, magic_web]
        -obj OBJ: specify  level of plot  [all, sit, sam, spc], default is all
        -crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
                default is geographic, unspecified assumed geographic
        -fmt [svg,png,jpg] format for output plots
        -ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
        -c plot as colour contour 
        -sav save plot and quit quietly
    NOTE
        all: entire file; sit: site; sam: sample; spc: specimen
    """
    FIG={} # plot dictionary
    FIG['eqarea']=1 # eqarea is figure 1
    in_file,plot_key,coord,crd='pmag_results.txt','all',"0",'g'
    plotE,contour=0,0
    dir_path='.'
    fmt='svg'
    verbose=pmagplotlib.verbose
    if '-h' in sys.argv:
        print main.__doc__
        sys.exit()
    if '-WD' in sys.argv:
        ind=sys.argv.index('-WD')
        dir_path=sys.argv[ind+1]
    pmagplotlib.plot_init(FIG['eqarea'],5,5)
    if '-f' in sys.argv:
        ind=sys.argv.index("-f")
        in_file=dir_path+"/"+sys.argv[ind+1]
    if '-obj' in sys.argv:
        ind=sys.argv.index('-obj')
        plot_by=sys.argv[ind+1]
        if plot_by=='all':plot_key='all'
        if plot_by=='sit':plot_key='er_site_name'
        if plot_by=='sam':plot_key='er_sample_name'
        if plot_by=='spc':plot_key='er_specimen_name'
    if '-c' in sys.argv: contour=1
    plt=0
    if '-sav' in sys.argv: 
        plt=1
        verbose=0
    if '-ell' in sys.argv:
        plotE=1
        ind=sys.argv.index('-ell')
        ell_type=sys.argv[ind+1]
        if ell_type=='F':dist='F' 
        if ell_type=='K':dist='K' 
        if ell_type=='B':dist='B' 
        if ell_type=='Be':dist='BE' 
        if ell_type=='Bv':
            dist='BV' 
            FIG['bdirs']=2
            pmagplotlib.plot_init(FIG['bdirs'],5,5)
    if '-crd' in sys.argv:
        ind=sys.argv.index("-crd")
        crd=sys.argv[ind+1]
        if crd=='s':coord="-1"
        if crd=='g':coord="0"
        if crd=='t':coord="100"
    if '-fmt' in sys.argv:
        ind=sys.argv.index("-fmt")
        fmt=sys.argv[ind+1]
    Dec_keys=['site_dec','sample_dec','specimen_dec','measurement_dec','average_dec','none']
    Inc_keys=['site_inc','sample_inc','specimen_inc','measurement_inc','average_inc','none']
    Tilt_keys=['tilt_correction','site_tilt_correction','sample_tilt_correction','specimen_tilt_correction','none']
    Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
    Name_keys=['er_specimen_name','er_sample_name','er_site_name','pmag_result_name']
    data,file_type=pmag.magic_read(in_file)
    if file_type=='pmag_results' and plot_key!="all":plot_key=plot_key+'s' # need plural for results table
    if verbose:    
        print len(data),' records read from ',in_file
    #
    #
    # find desired dec,inc data:
    #
    dir_type_key=''
    #
    # get plotlist if not plotting all records
    #
    plotlist=[]
    if plot_key!="all":
        plots=pmag.get_dictitem(data,plot_key,'','F')
        for  rec in plots:
            if rec[plot_key] not in plotlist:
                plotlist.append(rec[plot_key])
        plotlist.sort()
    else:
        plotlist.append('All')
    for plot in plotlist:
        #if verbose: print plot
        DIblock=[]
        GCblock=[]
        SLblock,SPblock=[],[]
        title=plot
        mode=1
        dec_key,inc_key,tilt_key,name_key,k="","","","",0
        if plot!="All": 
            odata=pmag.get_dictitem(data,plot_key,plot,'T')
        else: odata=data # data for this obj
        for dec_key in Dec_keys:
            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 plt:
           pmagplotlib.saveP(FIG,files) 
コード例 #3
0
ファイル: eqarea_magic.py プロジェクト: allochthonous/PmagPy
def main():
    """
    NAME
        eqarea_magic.py

    DESCRIPTION
       makes equal area projections from declination/inclination data

    SYNTAX
        eqarea_magic.py [command line options]

    INPUT
       takes magic formatted sites, samples, specimens, or measurements

    OPTIONS
        -h prints help message and quits
        -f FILE: specify input magic format file from magic, default='sites.txt'
         supported types=[measurements, specimens, samples, sites]
        -fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
                default='specimens.txt'
        -fsa FILE: specify sample file name, (required if you want to plot specimens by site)
                default='samples.txt'
        -fsi FILE: specify site file name, default='sites.txt'

        -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
    """
    # initialize some default variables
    FIG = {} # plot dictionary
    FIG['eqarea'] = 1 # eqarea is figure 1
    plotE = 0
    plt = 0  # default to not plotting
    verbose = pmagplotlib.verbose
    # extract arguments from sys.argv
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
    pmagplotlib.plot_init(FIG['eqarea'],5,5)
    in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
    full_in_file = os.path.join(dir_path, in_file)
    plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
    spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
    samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
    site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
    if plot_by == 'all':
        plot_key = 'all'
    elif plot_by == 'sit':
        plot_key = 'site'
    elif plot_by == 'sam':
        plot_key = 'sample'
    elif plot_by == 'spc':
        plot_key = 'specimen'
    else:
        plot_key = 'all'
    if '-c' in sys.argv:
        contour = 1
    else:
        contour = 0
    if '-sav' in sys.argv:
        plt = 1
        verbose = 0
    if '-ell' in sys.argv:
        plotE = 1
        ind = sys.argv.index('-ell')
        ell_type = sys.argv[ind+1]
        ell_type = pmag.get_named_arg_from_sys("-ell", "F")
        dist = ell_type.upper()
        # if dist type is unrecognized, use Fisher
        if dist not in ['F', 'K', 'B', 'BE', 'BV']:
            dist = 'F'
        if dist == "BV":
            FIG['bdirs'] = 2
            pmagplotlib.plot_init(FIG['bdirs'],5,5)
    crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
    if crd == "s":
        coord = "-1"
    elif crd == "t":
        coord = "100"
    else:
        coord = "0"

    fmt = pmag.get_named_arg_from_sys("-fmt", "svg")

    dec_key = 'dir_dec'
    inc_key = 'dir_inc'
    tilt_key = 'dir_tilt_correction'
    #Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']

    #
    fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
    contribution = nb.Contribution(dir_path, custom_filenames=fnames,
                                   single_file=in_file)
    # the object that contains the DataFrame + useful helper methods:
    table_name = list(contribution.tables.keys())[0]
    data_container = contribution.tables[table_name]
    # the actual DataFrame:
    data = data_container.df

    # uses sample infile to add temporary site_name
    # column to the specimen table



    data_container = contribution.tables[table_name]
    data = data_container.df

    if (plot_key != "all") and (plot_key not in data.columns):
        contribution.propagate_location_to_measurements()
        contribution.propagate_location_to_specimens()

    # add tilt key into DataFrame columns if it isn't there already
    if tilt_key not in data.columns:
        data.loc[:, tilt_key] = None

    if verbose:
        print(len(data), ' records read from ', in_file)

    # find desired dec,inc data:
    dir_type_key = ''
    #
    # get plotlist if not plotting all records
    #
    plotlist=[]
    if plot_key != "all":
        # return all where plot_key is not blank
        if plot_key not in data.columns:
            print('Can\'t plot by "{}".  That header is not in infile: {}'.format(plot_key, in_file))
            return
        plots = data[data[plot_key].notnull()]
        plotlist = plots[plot_key].unique() # grab unique values
    else:
        plotlist.append('All')

    for plot in plotlist:
        if verbose:
            print(plot)
        if plot == 'All':
            # plot everything at once
            plot_data = data
        else:
            # pull out only partial data
            plot_data = data[data[plot_key] == plot]

        DIblock = []
        GCblock = []
        # SLblock, SPblock = [], []
        title = plot
        mode = 1
        k = 0


        if dec_key not in plot_data.columns:
            print("-W- No dec/inc data")
            continue
        # get all records where dec & inc values exist
        plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
        if plot_data.empty:
            continue
        # this sorting out is done in get_di_bock
        #if coord == '0':  # geographic, use records with no tilt key (or tilt_key 0)
        #    cond1 = plot_data[tilt_key].fillna('') == coord
        #    cond2 = plot_data[tilt_key].isnull()
        #    plot_data = plot_data[cond1 | cond2]
        #else:  # not geographic coordinates, use only records with correct tilt_key
        #    plot_data = plot_data[plot_data[tilt_key] == coord]

        # get metadata for naming the plot file
        locations = data_container.get_name('location', df_slice=plot_data)
        site = data_container.get_name('site', df_slice=plot_data)
        sample = data_container.get_name('sample', df_slice=plot_data)
        specimen = data_container.get_name('specimen', df_slice=plot_data)

        # make sure method_codes is in plot_data
        if 'method_codes' not in plot_data.columns:
            plot_data['method_codes'] = ''

        # get data blocks
        DIblock = data_container.get_di_block(df_slice=plot_data,
                                              tilt_corr=coord, excl=['DE-BFP'])
        #SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
        # get great circles
        great_circle_data = data_container.get_records_for_code('DE-BFP', incl=True,
                                                                use_slice=True, sli=plot_data)

        if len(great_circle_data) > 0:
            gc_cond = great_circle_data[tilt_key] == coord
            GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
            #SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]

        if len(DIblock) > 0:
            if contour == 0:
                pmagplotlib.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 len(DIblock) == 0 and len(GCblock) == 0:
            if verbose:
                print("no records for plotting")
            continue
            #sys.exit()
        if plotE == 1:
            ppars = pmag.doprinc(DIblock) # get principal directions
            nDIs, rDIs, npars, rpars = [], [], [], []
            for rec in DIblock:
                angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
                if angle>90.:
                    rDIs.append(rec)
                else:
                    nDIs.append(rec)
            if dist=='B': # do on whole dataset
                etitle="Bingham confidence ellipse"
                bpars=pmag.dobingham(DIblock)
                for key in list(bpars.keys()):
                    if key!='n' and verbose: print("    ",key, '%7.1f'%(bpars[key]))
                    if key=='n' and verbose: print("    ",key, '       %i'%(bpars[key]))
                npars.append(bpars['dec'])
                npars.append(bpars['inc'])
                npars.append(bpars['Zeta'])
                npars.append(bpars['Zdec'])
                npars.append(bpars['Zinc'])
                npars.append(bpars['Eta'])
                npars.append(bpars['Edec'])
                npars.append(bpars['Einc'])
            if dist=='F':
                etitle="Fisher confidence cone"
                if len(nDIs)>2:
                    fpars=pmag.fisher_mean(nDIs)
                    for key in list(fpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(fpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(fpars[key]))
                    mode+=1
                    npars.append(fpars['dec'])
                    npars.append(fpars['inc'])
                    npars.append(fpars['alpha95']) # Beta
                    npars.append(fpars['dec'])
                    isign=old_div(abs(fpars['inc']),fpars['inc'])
                    npars.append(fpars['inc']-isign*90.) #Beta inc
                    npars.append(fpars['alpha95']) # gamma
                    npars.append(fpars['dec']+90.) # Beta dec
                    npars.append(0.) #Beta inc
                if len(rDIs)>2:
                    fpars=pmag.fisher_mean(rDIs)
                    if verbose: print("mode ",mode)
                    for key in list(fpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(fpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(fpars[key]))
                    mode+=1
                    rpars.append(fpars['dec'])
                    rpars.append(fpars['inc'])
                    rpars.append(fpars['alpha95']) # Beta
                    rpars.append(fpars['dec'])
                    isign=old_div(abs(fpars['inc']),fpars['inc'])
                    rpars.append(fpars['inc']-isign*90.) #Beta inc
                    rpars.append(fpars['alpha95']) # gamma
                    rpars.append(fpars['dec']+90.) # Beta dec
                    rpars.append(0.) #Beta inc
            if dist=='K':
                etitle="Kent confidence ellipse"
                if len(nDIs)>3:
                    kpars=pmag.dokent(nDIs,len(nDIs))
                    if verbose: print("mode ",mode)
                    for key in list(kpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(kpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(kpars[key]))
                    mode+=1
                    npars.append(kpars['dec'])
                    npars.append(kpars['inc'])
                    npars.append(kpars['Zeta'])
                    npars.append(kpars['Zdec'])
                    npars.append(kpars['Zinc'])
                    npars.append(kpars['Eta'])
                    npars.append(kpars['Edec'])
                    npars.append(kpars['Einc'])
                if len(rDIs)>3:
                    kpars=pmag.dokent(rDIs,len(rDIs))
                    if verbose: print("mode ",mode)
                    for key in list(kpars.keys()):
                        if key!='n' and verbose: print("    ",key, '%7.1f'%(kpars[key]))
                        if key=='n' and verbose: print("    ",key, '       %i'%(kpars[key]))
                    mode+=1
                    rpars.append(kpars['dec'])
                    rpars.append(kpars['inc'])
                    rpars.append(kpars['Zeta'])
                    rpars.append(kpars['Zdec'])
                    rpars.append(kpars['Zinc'])
                    rpars.append(kpars['Eta'])
                    rpars.append(kpars['Edec'])
                    rpars.append(kpars['Einc'])
            else: # assume bootstrap
                if dist=='BE':
                    if len(nDIs)>5:
                        BnDIs=pmag.di_boot(nDIs)
                        Bkpars=pmag.dokent(BnDIs,1.)
                        if verbose: print("mode ",mode)
                        for key in list(Bkpars.keys()):
                            if key!='n' and verbose: print("    ",key, '%7.1f'%(Bkpars[key]))
                            if key=='n' and verbose: print("    ",key, '       %i'%(Bkpars[key]))
                        mode+=1
                        npars.append(Bkpars['dec'])
                        npars.append(Bkpars['inc'])
                        npars.append(Bkpars['Zeta'])
                        npars.append(Bkpars['Zdec'])
                        npars.append(Bkpars['Zinc'])
                        npars.append(Bkpars['Eta'])
                        npars.append(Bkpars['Edec'])
                        npars.append(Bkpars['Einc'])
                    if len(rDIs)>5:
                        BrDIs=pmag.di_boot(rDIs)
                        Bkpars=pmag.dokent(BrDIs,1.)
                        if verbose: print("mode ",mode)
                        for key in list(Bkpars.keys()):
                            if key!='n' and verbose: print("    ",key, '%7.1f'%(Bkpars[key]))
                            if key=='n' and verbose: print("    ",key, '       %i'%(Bkpars[key]))
                        mode+=1
                        rpars.append(Bkpars['dec'])
                        rpars.append(Bkpars['inc'])
                        rpars.append(Bkpars['Zeta'])
                        rpars.append(Bkpars['Zdec'])
                        rpars.append(Bkpars['Zinc'])
                        rpars.append(Bkpars['Eta'])
                        rpars.append(Bkpars['Edec'])
                        rpars.append(Bkpars['Einc'])
                    etitle="Bootstrapped confidence ellipse"
                elif dist=='BV':
                    sym={'lower':['o','c'],'upper':['o','g'],'size':3,'edgecolor':'face'}
                    if len(nDIs)>5:
                        BnDIs=pmag.di_boot(nDIs)
                        pmagplotlib.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)

        for key in list(FIG.keys()):
            files = {}
            filename = pmag.get_named_arg_from_sys('-fname')
            if filename: # use provided filename
                filename+= '.' + fmt
            elif pmagplotlib.isServer: # use server plot naming convention
                filename='LO:_'+locations+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
            else: # use more readable naming convention
                filename = ''
                for item in [locations, site, sample, specimen, crd, key]:
                    if item:
                        item = item.replace(' ', '_')
                        filename += item + '_'
                if filename.endswith('_'):
                    filename = filename[:-1]
                filename += ".{}".format(fmt)

            files[key]=filename

        if pmagplotlib.isServer:
            black     = '#000000'
            purple    = '#800080'
            titles={}
            titles['eq']='Equal Area Plot'
            FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
            pmagplotlib.saveP(FIG,files)

        if plt:
            pmagplotlib.saveP(FIG,files)
            continue
        if verbose:
            pmagplotlib.drawFIGS(FIG)
            ans=input(" S[a]ve to save plot, [q]uit, Return to continue:  ")
            if ans == "q":
                sys.exit()
            if ans == "a":
                pmagplotlib.saveP(FIG,files)
        continue
コード例 #4
0
ファイル: eqarea_magic3.0.py プロジェクト: lfairchild/PmagPy
def main():
    """
    NAME
        eqarea_magic.py

    DESCRIPTION
       makes equal area projections from declination/inclination data

    SYNTAX
        eqarea_magic.py [command line options]

    INPUT
       takes magic formatted sites, samples, specimens, or measurements

    OPTIONS
        -h prints help message and quits
        -f FILE: specify input magic format file from magic, default='sites.txt'
         supported types=[measurements, specimens, samples, sites]
        -fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
                default='specimens.txt'
        -fsa FILE: specify sample file name, (required if you want to plot specimens by site)
                default='samples.txt'
        -fsi FILE: specify site file name, default='sites.txt'

        -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
    """
    # initialize some default variables
    FIG = {}  # plot dictionary
    FIG["eqarea"] = 1  # eqarea is figure 1
    plotE = 0
    plt = 0  # default to not plotting
    verbose = pmagplotlib.verbose
    # extract arguments from sys.argv
    if "-h" in sys.argv:
        print main.__doc__
        sys.exit()
    dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
    pmagplotlib.plot_init(FIG["eqarea"], 5, 5)
    in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
    full_in_file = os.path.join(dir_path, in_file)
    plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
    spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
    samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
    site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
    if plot_by == "all":
        plot_key = "all"
    elif plot_by == "sit":
        plot_key = "site"
    elif plot_by == "sam":
        plot_key = "sample"
    elif plot_by == "spc":
        plot_key = "specimen"
    else:
        plot_key = "all"
    if "-c" in sys.argv:
        contour = 1
    else:
        contour = 0
    if "-sav" in sys.argv:
        plt = 1
        verbose = 0
    if "-ell" in sys.argv:
        plotE = 1
        ind = sys.argv.index("-ell")
        ell_type = sys.argv[ind + 1]
        ell_type = pmag.get_named_arg_from_sys("-ell", "F")
        dist = ell_type.upper()
        # if dist type is unrecognized, use Fisher
        if dist not in ["F", "K", "B", "BE", "BV"]:
            dist = "F"
        if dist == "BV":
            FIG["bdirs"] = 2
            pmagplotlib.plot_init(FIG["bdirs"], 5, 5)
    crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
    if crd == "s":
        coord = "-1"
    elif crd == "t":
        coord = "100"
    else:
        coord = "0"

    fmt = pmag.get_named_arg_from_sys("-fmt", "svg")

    dec_key = "dir_dec"
    inc_key = "dir_inc"
    tilt_key = "dir_tilt_correction"
    # Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']

    #
    fnames = {"specimens": spec_file, "samples": samp_file, "sites": site_file}
    contribution = nb.Contribution(dir_path, custom_filenames=fnames, single_file=in_file)
    # the object that contains the DataFrame + useful helper methods:
    table_name = contribution.tables.keys()[0]
    data_container = contribution.tables[table_name]
    # the actual DataFrame:
    data = data_container.df

    # uses sample infile to add temporary site_name
    # column to the specimen table

    data_container = contribution.tables[table_name]
    data = data_container.df

    if (plot_key != "all") and (plot_key not in data.columns):
        data = contribution.propagate_name_down(plot_key, table_name)

    # add tilt key into DataFrame columns if it isn't there already
    if tilt_key not in data.columns:
        data.loc[:, tilt_key] = None

    if verbose:
        print len(data), " records read from ", in_file

    # find desired dec,inc data:
    dir_type_key = ""
    #
    # get plotlist if not plotting all records
    #
    plotlist = []
    if plot_key != "all":
        # return all where plot_key is not blank
        if plot_key not in data.columns:
            print 'Can\'t plot by "{}".  That header is not in infile: {}'.format(plot_key, in_file)
            return
        plots = data[data[plot_key].notnull()]
        plotlist = plots[plot_key].unique()  # grab unique values
    else:
        plotlist.append("All")

    for plot in plotlist:
        if verbose:
            print plot
        if plot == "All":
            # plot everything at once
            plot_data = data
        else:
            # pull out only partial data
            plot_data = data[data[plot_key] == plot]

        DIblock = []
        GCblock = []
        # SLblock, SPblock = [], []
        title = plot
        mode = 1
        k = 0

        if dec_key not in plot_data.columns:
            print "-W- No dec/inc data"
            continue
        # get all records where dec & inc values exist
        plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
        if plot_data.empty:
            continue
        # this sorting out is done in get_di_bock
        # if coord == '0':  # geographic, use records with no tilt key (or tilt_key 0)
        #    cond1 = plot_data[tilt_key].fillna('') == coord
        #    cond2 = plot_data[tilt_key].isnull()
        #    plot_data = plot_data[cond1 | cond2]
        # else:  # not geographic coordinates, use only records with correct tilt_key
        #    plot_data = plot_data[plot_data[tilt_key] == coord]

        # get metadata for naming the plot file
        locations = data_container.get_name("location", df_slice=plot_data)
        site = data_container.get_name("site", df_slice=plot_data)
        sample = data_container.get_name("sample", df_slice=plot_data)
        specimen = data_container.get_name("specimen", df_slice=plot_data)

        # make sure method_codes is in plot_data
        if "method_codes" not in plot_data.columns:
            plot_data["method_codes"] = ""

        # get data blocks
        DIblock = data_container.get_di_block(df_slice=plot_data, tilt_corr=coord, excl=["DE-BFP"])
        # SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
        # get great circles
        great_circle_data = data_container.get_records_for_code("DE-BFP", incl=True, use_slice=True, sli=plot_data)

        if len(great_circle_data) > 0:
            gc_cond = great_circle_data[tilt_key] == coord
            GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
            # SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]

        if len(DIblock) > 0:
            if contour == 0:
                pmagplotlib.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, 90.0, "g")
        if len(DIblock) == 0 and len(GCblock) == 0:
            if verbose:
                print "no records for plotting"
            continue
            # sys.exit()
        if plotE == 1:
            ppars = pmag.doprinc(DIblock)  # get principal directions
            nDIs, rDIs, npars, rpars = [], [], [], []
            for rec in DIblock:
                angle = pmag.angle([rec[0], rec[1]], [ppars["dec"], ppars["inc"]])
                if angle > 90.0:
                    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 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 * 90.0)  # Beta inc
                    npars.append(fpars["alpha95"])  # gamma
                    npars.append(fpars["dec"] + 90.0)  # Beta dec
                    npars.append(0.0)  # Beta inc
                if len(rDIs) > 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 * 90.0)  # 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 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, 1.0)
                        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, 1.0)
                        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)

        for key in FIG.keys():
            files = {}
            filename = pmag.get_named_arg_from_sys("-fname")
            if filename:
                filename += "." + fmt
            else:
                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)

        if plt:
            pmagplotlib.saveP(FIG, files)
            continue
        if verbose:
            pmagplotlib.drawFIGS(FIG)
            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)
        continue