Commit 6eafa4c0 authored by Zolnierczuk, Piotr's avatar Zolnierczuk, Piotr
Browse files

new nseplot.py

parent e53cdf5a

pysen/config.py

+0 −1
Original line number Diff line number Diff line
@@ -325,7 +325,6 @@ def coverage(lmax, qmin, **kwargs): 
        for j,y in enumerate(ylims):

            theta1    = get_theta_pix(x,y,L2,sa,ca)

            theta2, _ = pixel_angle(i,j,theta0)

            print(theta1, theta2)

            theta = theta2

            lq      = get_q(lmax, theta)*lmax

            q       = linspace(get_q(lmax, theta), get_q(lmax-dlam, theta), len(tbins)+1)

pysen/revision.py

+4 −4
Original line number Diff line number Diff line
@@ -2,9 +2,9 @@ 
PySEN revision module

"""

import sys

__version__  = "0.7.3"

__version__  = "0.7.4"

__release__  = "dev1"

__date__     = "Feb 13, 2019"

__date__     = "Feb 14, 2019"

#

VERSION  = __version__

RELEASE  = __release__
@@ -28,8 +28,8 @@ def version(full=False): 
    "get pysen version number"

    if full:

        py_ver = "Python %s.%s" % (sys.version_info.major, sys.version_info.minor)

        return "%s.%s (%s) %s" % (__version__, __release__, __date__, py_ver)

    return "%s.%s" % (__version__, __release__)

        return "%s-%s (%s) %s" % (__version__, __release__, __date__, py_ver)

    return "%s-%s" % (__version__, __release__)





# EOF

scripts/nseplot.py

0 → 100755
+476 −0
Original line number Diff line number Diff line 
#!/usr/bin/env python

"Echo plot"



import os.path

import logging



import numpy as np

import h5py

import matplotlib.pyplot as plt



from pysen import ANGSTROM, NANOSECOND, GAUSS, MICRO, OMEGA_N, version

from pysen.plotutil import get_nsubplots

from pysen.io import echo_to_hdf

from pysen.atarilib import fit_echo_current, Spectrum



MAX_CHI2_DEFAULT = 1e-2

def plot_field(ax,t,v,**kwargs):

    "plot mag field"

    label    = kwargs.get('label'  , '')

    max_chi2 = kwargs.get('max_chi2', MAX_CHI2_DEFAULT)

    v0 = np.sqrt(np.sum(v**2,axis=-1))

    #

    a,b  = np.polyfit(t,v0,deg=1)

    v1   = np.polyval([a,b],t)

    chi2 = np.sum((v0-v1)**2)

    cov  = np.cov(t,v0)

    diag = cov[0,0]*cov[1,1]

    r    = cov[1,0]/np.sqrt(diag) if diag>0 else np.nan

    #r    = np.corrcoef(t,v0)[1,0]

    #maxd = max(abs(v0-v1))

    descr1 = r'a=%.2e b=%.3g' % (a, b)

    descr2 = r'$\rho$=%.3g $\chi^2$=%.1e' % (r, chi2)

    #descr2 = r'$\rho$=%.3g $\chi^2$=%.1e $(\Delta B)_{max}$=%.3g' % (r, chi2, maxd)

    #

    va   = np.average(v0)

    vd   = max(abs(v0-va))

    vmin = va-max(vd,0.5)

    vmax = va+max(vd,0.5)

    ax.plot(t,v0, '.--', lw=1, label=label)

    ax.plot(t,v1, '-')

    ax.set_ylim(bottom=vmin, top=vmax)

    ax.text(0.05,0.20,descr1, transform=ax.transAxes, fontsize=7)

    ax.text(0.05,0.10,descr2, transform=ax.transAxes, fontsize=7)

    ax.grid(True, lw=0.5)

    ax.legend(loc='upper left')

    if chi2>max_chi2:

        ax.set_facecolor('yellow')



def magnetic_fields_plot(hdfile, iecho=0, **kwargs):

    "plot magnetic fields"

    #

    max_chi2 = kwargs.get('max_chi2', MAX_CHI2_DEFAULT)

    #

    base    = os.path.splitext(os.path.basename(hdfile.filename))[0]



    comment = hdfile.attrs['master_comment']

    comment = comment.decode("utf-8")

    sample  = comment.split()[0]



    nph     = hdfile['/'].attrs['point_to_down']



    for echo in list(hdfile['/data'].values()):

        if iecho and echo.attrs['id'] != iecho:

            continue



        phase   = echo['phase']

        physics = echo['phys']

        params  = echo['params']

        tech    = echo['tech']



        tau0    = physics.attrs['fouriertime']/NANOSECOND

        q0      = physics.attrs['hkl'][0]

        lam0    = physics.attrs['lambda']

        cur0    = float(tech.attrs['i5'][0])

        phasesens = float(params['phaseangle'].attrs['sensitivities'][0])





        bfield = phase['bfield']

        cur    = phase['phase_current'][:, 0] # actual value

        dj     = np.radians(phasesens*(cur-cur0))/OMEGA_N/lam0



        nxplot, nyplot = get_nsubplots(len(bfield))



        fig, axes = plt.subplots(nxplot,nyplot, figsize=(9,7))

        fig.subplots_adjust(hspace=0.4, wspace=0.4)

        fig.suptitle(r'%s | %s | $\lambda$=%.2g$\AA$ $Q$=%.3f$\AA^{-1}$ $\tau$=%.3fns' %

                     (sample, base, lam0/ANGSTROM, q0, tau0))



        for iplt, bsensor in enumerate(bfield):

            bmag  = bfield[bsensor]

            label = bsensor.split('.')[-1]

            ax    = axes[iplt//nxplot,iplt%nxplot]

            plot_field(ax, dj[:nph]/MICRO, bmag[:nph,:]*GAUSS/MICRO, label=label, max_chi2=max_chi2)

        for iplt in range(iplt+1, nxplot*nyplot):

            ax  = axes[iplt//nxplot,iplt%nxplot]

            ax.axis('off')



def atari_plot(hdfile, iecho=0, **kwargs):

    "atari plot"

    #

    only_echo = kwargs.pop('only_echo', False)

    #

    tbin1   = kwargs.pop('tbin1',0)      # TOF bins

    tbin2   = kwargs.pop('tbin2',None)

    # FIXME: HARDCODED

    xpix1   = kwargs.pop('xpix1', 10)

    xpix2   = kwargs.pop('xpix2', 22)

    ypix1   = kwargs.pop('ypix1', 10)

    ypix2   = kwargs.pop('ypix2', 22)



    #ntaus   = hdfile.attrs['scan_length']

    n_idx   = { 'dn': hdfile['/'].attrs['point_to_down'],

                'up': hdfile['/'].attrs['point_to_up'] ,

                'nphases': hdfile['/'].attrs['no_of_phases'] }

    nt      = hdfile['/detector'].attrs['no_t_channels']

    ny      = hdfile['/detector'].attrs['no_y_channels']

    nx      = hdfile['/detector'].attrs['no_x_channels']

    nph     = n_idx['dn']

    comment = hdfile.attrs['master_comment']



    for echo in list(hdfile['/data'].values()):

        if iecho and echo.attrs['id'] != iecho:

            continue



        phase   = echo['phase']

        physics = echo['phys']

        params  = echo['params']

        tech    = echo['tech']





        tau0    = physics.attrs['fouriertime']/NANOSECOND

        q0      = physics.attrs['hkl'][0]

        lam0    = physics.attrs['lambda']

        phase0  = float(tech.attrs['i5'][0])



        try:

            lmax = params['lambdatable']

        except KeyError:

            lmax = params['lambdaTable']

        lmax = np.array(lmax).flatten()



        dlam    = np.ones_like(lmax)*(lmax[1]-lmax[0])



        phasesens = float(params['phaseangle'].attrs['sensitivities'][0])



        det  = phase['detector'][...]

        pcha = phase['proton_charge'][...]

        cur  = phase['phase_current'][:, 0] # actual value

        pcha0 = np.average(pcha)

        pcha = np.tile(pcha, (ny, nx, nt)).reshape(n_idx['nphases'],ny,nx,nt)

        pcha = pcha/float(pcha0)

        det  = det/pcha



        #

        plt.figure(figsize=(8,8))

        #

        plt.subplot(2,2,1)

        wlen = np.sum(det, axis=(0,1,2))

        plt.step(wlen[tbin1:tbin2], lmax[tbin1:tbin2]/ANGSTROM)

        plt.ylabel(r'$\lambda$ [$\AA$]')

        plt.xlim(left=0)

        plt.grid(True)



        plt.subplot(2,2,2)

        xatari = np.sum(det, axis=(1,2)).T

        extent = (cur[0], cur[nph-1])

        if tbin2 is None:

            extent = extent + (lmax[tbin1]/ANGSTROM, max(lmax)/ANGSTROM)

        else:

            extent = extent + (lmax[tbin1]/ANGSTROM, lmax[tbin2]/ANGSTROM)

        plt.imshow(xatari[tbin1:tbin2,:nph], origin='lower', extent=extent, aspect='auto')



        plt.subplot(2,2,3)

        img = np.sum(det[:,:,:,tbin1:tbin2], axis=(0,-1))

        plt.imshow(img , aspect='auto')

        plt.axvline(xpix1, color='k')

        plt.axvline(xpix2-1, color='k')

        plt.axhline(ypix1, color='k')

        plt.axhline(ypix2-1, color='k')



        plt.subplot(2,2,4)

        pha  = det[:,xpix1:xpix2,ypix1:ypix2,tbin1:tbin2]



        dn   = np.sum(pha[nph:n_idx['up']], axis=(1,2,3))

        up   = np.sum(pha[n_idx['up']:], axis=(1,2,3))

        epha = np.sqrt(np.sum(pha[:nph]**2, axis=(1,2,3)))

        pha  = np.sum(pha[:nph], axis=(1,2,3))



        spectrum =  Spectrum(lam=lmax, dlam=dlam, flux=wlen)

        phase_ef, (xef, yef), res = fit_echo_current(cur[:nph], (pha, epha), spectrum,

                                                     lam0=lam0, phase0=phase0, phasesens=phasesens)

        res['up'] = np.average(up),np.sqrt(np.sum(up)/len(up))

        res['dn'] = np.average(dn),np.sqrt(np.sum(dn)/len(dn))

        #for key in res:

        #    print(key, res[key])



        p = plt.errorbar(cur[:nph], pha, yerr=epha, fmt='.', lw=1)

        dcol = p[0].get_color()

        plt.plot(xef, yef, '--')

        plt.axvline(phase0,   color='blue',  lw=1, ls='--', label='%.3fA' % phase0  )

        plt.axvline(phase_ef, color='red',   lw=2, ls='-',  label='%.3fA' % phase_ef)

        ax = plt.gca()



        if not only_echo:

            R = 2*res['amplitude'][0]/( res['up'][0] - res['dn'][0] )

            plt.errorbar(cur[nph:n_idx['up']], dn, fmt='.', color=dcol)

            plt.errorbar(cur[n_idx['up']:], up, fmt='.', color=dcol)

            plt.text(0.01, 1.01, r'$R(Q,t)$=%.3g' % R, transform=ax.transAxes)

            plt.axhline(np.average(up))

            plt.axhline(np.average(dn))

        plt.xlabel(r'phase current [A]')



        plt.legend(loc='best')

        plt.grid(True)

        plt.suptitle(r'%s    $Q$=%.3f$\AA^{-1}$ $\tau$=%.3gns' % (comment.decode("utf-8"), q0,tau0))



def echo_plot(hdfile, iecho=0, **kwargs):

    "echo plot"

    #

    center_only = kwargs.pop('center_only', False)

    #

    npix    = kwargs.pop('npix', 2)      # pix

    #

    tbin1   = kwargs.pop('tbin1',0)      # TOF bins

    tbin2   = kwargs.pop('tbin2',None)

    #

    min_counts = kwargs.pop('min_counts', 10.0)

    max_chi2   = kwargs.pop('max_chi2'  ,500.0)

    min_amp    = kwargs.pop('min_amp'   ,  0.20)

    # FIXME: HARDCODED

    #xpix1   = kwargs.pop('xpix1', 10)

    #xpix2   = kwargs.pop('xpix2', 22)

    #ypix1   = kwargs.pop('ypix1', 10)

    #ypix2   = kwargs.pop('ypix2', 22)



    base    = os.path.splitext(os.path.basename(hdfile.filename))[0]



    comment = hdfile.attrs['master_comment']

    comment = comment.decode("utf-8")

    sample  = comment.split()[0]



    n_idx   = { 'dn': hdfile['/'].attrs['point_to_down'],

                'up': hdfile['/'].attrs['point_to_up'] ,

                'nphases': hdfile['/'].attrs['no_of_phases'] }

    nt      = hdfile['/detector'].attrs['no_t_channels']

    ny      = hdfile['/detector'].attrs['no_y_channels']

    nx      = hdfile['/detector'].attrs['no_x_channels']

    nph     = n_idx['dn']



    if  center_only:

        ntaus = 1

        for echo in list(hdfile['/data'].values()):

            if not iecho or echo.attrs['id'] == iecho:

                ntaus = ntaus + 1

        nxtau, nytau = get_nsubplots(ntaus)

        fig0 = plt.figure(figsize=(8,8))

        fig0.suptitle(r'%s | %s' % (sample, base))



    itau = 0

    resolution = []

    for echo in list(hdfile['/data'].values()):

        if iecho and echo.attrs['id'] != iecho:

            continue



        itau = itau + 1



        phase   = echo['phase']

        physics = echo['phys']

        params  = echo['params']

        tech    = echo['tech']





        tau0    = physics.attrs['fouriertime']/NANOSECOND

        q0      = physics.attrs['hkl'][0]

        lam0    = physics.attrs['lambda']

        phase0  = float(tech.attrs['i5'][0])



        try:

            lmax = params['lambdatable']

        except KeyError:

            lmax = params['lambdaTable']

        lmax = np.array(lmax).flatten()



        dlam    = np.ones_like(lmax)*(lmax[1]-lmax[0])



        phasesens = float(params['phaseangle'].attrs['sensitivities'][0])



        det  = phase['detector'][...]

        pcha = phase['proton_charge'][...]

        cur  = phase['phase_current'][:, 0] # actual value

        pcha0 = np.average(pcha)

        pcha = np.tile(pcha, (ny, nx, nt)).reshape(n_idx['nphases'],ny,nx,nt)

        pcha = pcha/float(pcha0)

        det  = det/pcha

        wlen = np.sum(det, axis=(0,1,2))



        spectrum =  Spectrum(lam=lmax, dlam=dlam, flux=wlen)



        y  = np.sum(det[:,:,:,tbin1:tbin2], axis=(1,2,3))

        ey = np.sqrt(y)

        dn = y[nph:n_idx['up']]

        up = y[n_idx['up']:]

        phase_ef0, (xef,yef), res = fit_echo_current(cur[:nph], (y[:nph], ey[:nph]), spectrum,

                                                     lam0=lam0, phase0=phase0, phasesens=phasesens)



        if center_only:

            ax = fig0.add_subplot(nxtau, nytau, itau)

            fig0.suptitle(r'%s | %s | $\lambda$=%.2g$\AA$ $Q$=%.3f$\AA^{-1}$ ' %

                          (sample, base, lam0/ANGSTROM, q0))

            ax.errorbar(cur[:nph], y[:nph], yerr=ey[:nph], fmt='k.', lw=2, ms=3)

            ax.plot(xef, yef, 'r-', label=r'$\tau$=%.3gns' % tau0)

            ax.axvline(phase_ef0, color='blue',   lw=1, ls='--')

            ax.errorbar(cur[nph:n_idx['up']], dn, fmt='k.', ms=3)

            ax.errorbar(cur[n_idx['up']:   ], up, fmt='k.', ms=3)

            upave = np.average(up)

            dnave = np.average(dn)

            udave = (upave+dnave)/2

            res['up'] = upave, np.sqrt(np.sum(up)/len(up))

            res['dn'] = dnave, np.sqrt(np.sum(dn)/len(dn))

            R = 2*res['amplitude'][0]/( res['up'][0] - res['dn'][0] )

            resolution.append((tau0, R))

            ax.legend()

            ax.grid()

            #ax.set_xticklabels([])

            if itau%nytau!=1:

                ax.set_yticklabels([])

            continue



        npx, nx, ny, nt = det.shape

        nyy = ny//npix

        nxx = nx//npix

        pha = det.reshape(npx, nyy, npix, nxx, npix, nt)

        pha = pha.sum(axis=(2, 4)) # pixel rebin

        pha = np.sum(pha[:,:,:,tbin1:tbin2],axis=-1) # tof summation





        fig, axes = plt.subplots(nxx,nyy, figsize=(8,8))



        fig.subplots_adjust(hspace=0.05, wspace=0.05)



        ymax = np.amax(pha)

        ymin = np.amin(pha)



        for j in range(nyy):

            for i in range(nxx):

                ax = axes[i,j]

                ax.set_xticklabels([])

                ax.set_yticklabels([])



                y  = pha[:,i,j]

                ey = np.sqrt(pha[:,i,j])

                dn = y[nph:n_idx['up']]

                up = y[n_idx['up']:]

                #



                upave = np.average(up)

                dnave = np.average(dn)

                udave = (upave+dnave)/2

                ave   = np.average(y[:nph])

                std   = np.std(y[:nph])



                if udave<min_counts or ave<min_counts:

                    continue

                if udave<min_counts and std/ave<min_wiggle:

                    continue

                res = fit_echo_current(cur[:nph], (y[:nph], ey[:nph]), spectrum,

                                       lam0=lam0, phase0=phase0,

                                       phasesens=phasesens, phase_pf=phase_ef0)

                phase_ef, (xef, yef), res = res

                #

                if res['chi2']>max_chi2:

                    continue

                res['up'] = upave, np.sqrt(np.sum(up)/len(up))

                res['dn'] = dnave, np.sqrt(np.sum(dn)/len(dn))

                R = 2*res['amplitude'][0]/( res['up'][0] - res['dn'][0] )

                if abs(R)<min_amp:

                    continue



                ax.errorbar(cur[:nph], y[:nph], yerr=ey[:nph], fmt='k.',

                            lw=1, ms=1, label='(%s,%s)' % (i,j))

                ax.set_ylim(bottom=ymin, top=ymax)

                ax.plot(xef, yef, 'r-')

                ax.axvline(phase_ef, color='blue',   lw=1, ls='--')

                ax.errorbar(cur[nph:n_idx['up']], dn, fmt='k.', ms=1)

                ax.errorbar(cur[n_idx['up']:   ], up, fmt='k.', ms=1)

                if R<0:

                    ax.set_facecolor('yellow')

                #ax.legend()

                #    plt.text(0.01, 1.01, r'$R(Q,t)$=%.3g' % R, transform=ax.transAxes)

                #ax.axhline(np.average(up))

                #ax.axhline(np.average(dn))

        #plt.xlabel(r'ephase current [A]')



        #plt.legend(loc='best')

        #plt.grid(True)

        fig.suptitle(r'%s | %s | $\lambda$=%.2g$\AA$ $Q$=%.3f$\AA^{-1}$ $\tau$=%.3gns' %

                     (sample, base, lam0/ANGSTROM, q0,tau0))



    if center_only:

        #   figr = plt.figure(figsize=(8,8))

        #      figr.suptitle(r'%s | %s' % (sample, base))

        ax = fig0.add_subplot(nxtau,nytau,ntaus)

        res = np.asarray(resolution)

        print(res)

        ax.plot(res[:,0],res[:,1], '.--')

        ax.set_xscale('log')

        ax.set_yscale('log')

        ax.set_ylim(top=1.1)

        ax.grid(True)





def main():

    "the main"

    import argparse



    plot_action = dict(echo=echo_plot,atari=atari_plot, bfield=magnetic_fields_plot)



    parser = argparse.ArgumentParser(description='echo plot')

    parser.set_defaults(loglevel=logging.INFO, outdir='.', plot='echo',

                        tbin1=0, tbin2=None, tau=0)

    parser.add_argument('file', metavar='filename', help='file to process', nargs='+')

    parser.add_argument('--plot',   '-p', dest='plot', choices=['echo', 'atari', 'bfield'])

    parser.add_argument('--atari',  dest='plot', action='store_const', const='atari')

    parser.add_argument('--bfield', dest='plot', action='store_const', const='bfield')

    parser.add_argument('--echo' ,  dest='plot', action='store_const', const='echo')



    grp_echo = parser.add_argument_group('echo', 'echo plotting')

    grp_echo.add_argument('--center-only', '-C', dest='center_only', action='store_true',

                          default=False, help='show only center patch')

    grp_echo.add_argument('--only-echo', dest='only_echo', action='store_true',

                          default=False, help='show only echo (no up/down)')



    parser.add_argument('--tau', '-t',  dest='tau', type=int,

                        help='set tau to display (default=%(default)s)')

    parser.add_argument('--t1' , '-b',  dest='tbin1', type=int,

                        help='set min TOF bin (default=%(default)s)')

    parser.add_argument('--t2' , '-B',  dest='tbin2', type=int,

                        help='set max TOF bin (default=%(default)s)')

    parser.add_argument('--save-file', '-s', dest='savefile',

                        help='save figure to a file (do not show)')

    parser.add_argument('--verbose', '-v', dest='loglevel', action='store_const',

                        const=logging.DEBUG,  help='verbose output')

    parser.add_argument('--quiet', '-q', dest='loglevel', action='store_const',

                        const=logging.WARNING,  help='verbose output')

    parser.add_argument('--version', '-V', action='version',

                        version='%(prog)s pysen={version}'.format(version=version(full=True)))

    args = parser.parse_args()



    if args.loglevel>=logging.INFO:

        log_format=r'%(message)s'

    else:

        log_format=r'%(levelname)s: %(funcName)s: %(message)s'



    logging.basicConfig(level=args.loglevel, format=log_format)

    log = logging.getLogger()



    if args.savefile:

        plt.switch_backend('Agg')



    kwargs = vars(args)

    for filename in args.file:

        basename , ext = os.path.splitext(os.path.basename(filename))

        if ext==".echo":

            log.info('converting %s to HDF', basename)

            hfile = echo_to_hdf(filename, args.outdir)

        else:

            hfile = filename

        with h5py.File(hfile, 'r') as hdf5file:

            plot_action[args.plot](hdf5file, iecho=args.tau, **kwargs)

        if args.savefile:

            plt.savefig(basename+'-'+args.savefile)

    if not args.savefile:

        plt.show()



if __name__ == "__main__":

    main()

scripts/qtau.py

+13 −13
Original line number Diff line number Diff line
@@ -52,37 +52,37 @@ def main(): 
    group1 = parser.add_argument_group('script', 'input data are read from the script')

    group1.add_argument('--file', '-f', dest='file', help='read input data from a file')



    group2 = parser.add_argument_group('command line options',

    group2 = parser.add_argument_group('shell',

                                       'input data are taken from command line options')

    group2.add_argument('taus', metavar='tau', type=float, nargs='*',

                        help='select list of taus')

    group2.add_argument('--lmax', '-l', dest='lmax', type=float,

                        help='set max wavelength, lambda_max (default %(default)s)')

    group2.add_argument('--qmin', '-q', dest='qmin', type=float,

                        help='set min q (default %(default)s)')

    group2.add_argument('--tbin', '-t', dest='tbins', type=int, action='append',

                        help='set tbin  (default %(default)s)')

                        help='set TOF binning') #  (default %(default)s)')

    group2.add_argument('--pos' , '-p', dest='pos' ,

                        help='set instrument position: p1, p2, p3 or p4 (default %(default)s)')

    group2.add_argument('--mode', '-m', dest='mode',

                        help=('set instrument mode: standard, shorty_2'

                              ' or mixed (default %(default)s)'))

    group2.add_argument('--full', '-F', dest='full', action='store_true',

                        help='plot full coverage (default it for the center of the detector)')

    group2.add_argument('--lint',  dest='logscalex', action='store_false',

    parser.add_argument('--full', '-F', dest='full', action='store_true',

                        help='full detecor coverage (default: only for the center)')

    parser.add_argument('--lint',  dest='logscalex', action='store_false',

                        help='plot t in linear scale')

    group2.add_argument('--logt',  dest='logscalex', action='store_true',

    parser.add_argument('--logt',  dest='logscalex', action='store_true',

                        help='plot t in log scale')

    group2.add_argument('--linq',  dest='logscaley', action='store_false',

    parser.add_argument('--linq',  dest='logscaley', action='store_false',

                        help='plot q in linear scale')

    group2.add_argument('--logq',  dest='logscaley', action='store_true',

    parser.add_argument('--logq',  dest='logscaley', action='store_true',

                        help='plot q in log scale')

    group2.add_argument('--no-errors', '-e', dest='errors', action='store_false',

    parser.add_argument('--no-errors', '-e', dest='errors', action='store_false',

                        help='do not plot errors on q/tau averages')

    group2.add_argument('--no-legend', dest='legend', action='store_false',

    parser.add_argument('--no-legend', dest='legend', action='store_false',

                        help='do not show plot legend')

    group2.add_argument('--color-map', '-c', dest='cmap',

    parser.add_argument('--color-map', '-c', dest='cmap',

                        help='set colormap to use (default=%(default)s)')

    group2.add_argument('taus', metavar='tau', type=float, nargs='*',

                        help='select list of taus')

    parser.add_argument('--verbose', '-v', dest='verbose', action='store_true',

                        help='verbose output')

    parser.add_argument('--version', action='version',

scripts/the_cube.py

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