Python FramedPlot.ylog方法代码示例

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
    def plot_T(self, k, T, Tc=None, Tb=None):
        from biggles import FramedPlot, Curve, PlotKey

        plt=FramedPlot()

        c=Curve(k, T**2)
        c.label = '$T^2$'
        plt.add(c)
        plist = [c]

        if Tc is not None:
            cc=Curve(k,Tc**2,color='blue')
            cc.label = '$Tc^2$'
            plt.add(cc)
            plist.append(cc)

        if Tb is not None:
            tmp = where(Tb < 1.e-5, 1.e-5, Tb)
            cb=Curve(k,tmp**2,color='red')
            cb.label = '$Tb^2$'
            plt.add(cb)
            plist.append(cb)

        plt.xlog=True
        plt.ylog=True
        plt.ylabel = '$T^2'
        plt.xlabel = 'k'
        plt.yrange = [1.e-8,1.0]
        plt.aspect_ratio=1

        if Tc is not None or Tb is not None:
            key=PlotKey(0.1,0.9,plist)
            plt.add(key)

        plt.show()

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def test_fit_nfw_dsig(rmin=0.01):

    from biggles import FramedPlot,Points,SymmetricErrorBarsY,Curve
    omega_m=0.25
    z=0.25
    n = lensing.nfw.NFW(omega_m, z)

    r200 = 1.0
    c = 5.0

    rmax = 5.0
    log_rmin = log10(rmin)
    log_rmax = log10(rmax)
    npts = 25
    logr = numpy.linspace(log_rmin,log_rmax,npts)
    r = 10.0**logr

    ds = n.dsig(r, r200, c)
    # 10% errors
    dserr = 0.1*ds
    ds += dserr*numpy.random.standard_normal(ds.size)

    guess = numpy.array([r200,c],dtype='f8')
    # add 10% error to the guess
    guess += 0.1*guess*numpy.random.standard_normal(guess.size)

    res = fit_nfw_dsig(omega_m, z, r, ds, dserr, guess)

    r200_fit = res['r200']
    r200_err = res['r200_err']

    c_fit = res['c']
    c_err = res['c_err']

    print 'Truth:'
    print '    r200: %f' % r200
    print '       c: %f' % c
    print 'r200_fit: %f +/- %f' % (r200_fit,r200_err)
    print '   c_fit: %f +/- %f' % (c_fit,c_err)
    print 'Cov:'
    print res['cov']

    logr = numpy.linspace(log_rmin,log_rmax,1000)
    rlots = 10.0**logr
    yfit = n.dsig(rlots,r200_fit,c_fit)

    plt=FramedPlot()
    plt.add(Points(r,ds,type='filled circle'))
    plt.add(SymmetricErrorBarsY(r,ds,dserr))
    plt.add(Curve(rlots,yfit,color='blue'))

    plt.xlabel = r'$r$ [$h^{-1}$ Mpc]'
    plt.ylabel = r'$\Delta\Sigma ~ [M_{sun} pc^{-2}]$'

    plt.xrange = [0.5*rmin, 1.5*rmax]
    plt.yrange = [0.5*(ds-dserr).min(), 1.5*(ds+dserr).max()]

    plt.xlog=True
    plt.ylog=True
    plt.show()

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot_nfwfits_byrun(run, name, prompt=False):
    conf = lensing.files.read_config(run)
    d = lensing.sample_read(type='fit', sample=run, name=name)
    omega_m = conf['omega_m']


    rvals = numpy.linspace(d['r'].min(), d['r'].max(),1000)
    for i in xrange(d.size):
        plt = FramedPlot()  
        lensing.plotting.add_to_log_plot(plt, 
                                          d['r'][i],
                                          d['dsig'][i],
                                          d['dsigerr'][i])

        z = d['z_mean'][i]
        n = lensing.nfw.NFW(omega_m, z)
        yfit = n.dsig(rvals, d['r200_fit'][i],d['c_fit'][i])
        plt.add(Curve(rvals,yfit,color='blue'))
        plt.xlog=True
        plt.ylog=True
        plt.xlabel = r'$r$ [$h^{-1}$ Mpc]'
        plt.ylabel = r'$\Delta\Sigma ~ [M_{sun} pc^{-2}]$'
        if prompt:
            plt.show()
            raw_input('hit a key: ')
        else:
            epsfile='/home/esheldon/tmp/plots/desmocks-nfwfit-%02i.eps' % i
            print 'Writing epsfile:',epsfile
            plt.write_eps(epsfile)

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot_sub_pixel(ellip,theta, show=False):
    import biggles
    from biggles import PlotLabel,FramedPlot,Table,Curve,PlotKey,Points
    from pcolors import rainbow

    f=subpixel_file(ellip,theta,'fits')
    data = eu.io.read(f)
    colors = rainbow(data.size,'hex')

    pltSigma = FramedPlot()
    pltSigma.ylog=1
    pltSigma.xlog=1

    curves=[]
    for j in xrange(data.size):
        sigest2 = (data['Irr'][j,:] + data['Icc'][j,:])/2

        pdiff = sigest2/data['sigma'][j]**2 -1
        nsub=numpy.array(data['nsub'][j,:])

        #pc = biggles.Curve(nsub, pdiff, color=colors[j])
        pp = Points(data['nsub'][j,:], pdiff, type='filled circle',color=colors[j])

        pp.label = r'$\sigma: %0.2f$' % data['sigma'][j]
        curves.append(pp)
        pltSigma.add(pp)
        #pltSigma.add(pc)
        #pltSigma.yrange=[0.8,1.8]
        #pltSigma.add(pp)


    c5 = Curve(linspace(1,8, 20), .005+zeros(20))
    pltSigma.add(c5)

    key=PlotKey(0.95,0.95,curves,halign='right',fontsize=1.7)
    key.key_vsep=1

    pltSigma.add(key)
    pltSigma.xlabel='N_{sub}'
    pltSigma.ylabel=r'$\sigma_{est}^2  /\sigma_{True}^2 - 1$'

    lab=PlotLabel(0.05,0.07,r'$\epsilon: %0.2f \theta: %0.2f$' % (ellip,theta),halign='left')
    pltSigma.add(lab)

    pltSigma.yrange = [1.e-5,0.1]
    pltSigma.xrange = [0.8,20]
    if show:
        pltSigma.show()

    epsfile=subpixel_file(ellip,theta,'eps')

    print("Writing eps file:",epsfile)
    pltSigma.write_eps(epsfile)

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
    def plot_pk(self,k,pk):
        from biggles import FramedPlot, Curve

        plt=FramedPlot()
        plt.add(Curve(k,pk))
        plt.xlog=True
        plt.ylog=True

        plt.xlabel = r'$k [h/Mpc]$'
        plt.ylabel = r'$P_{lin}(k)$'
        plt.aspect_ratio = 1
        plt.show()

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
    def plot_m(self, r200, c):
        from biggles import FramedPlot, Curve
        n=1000
        r = numpy.linspace(0.01, 20.0,n)
        m = self.m(r, r200, c)

        plt=FramedPlot()
        plt.add( Curve(r,m) )
        plt.xlog=True
        plt.ylog=True

        plt.show()

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot_dsig_one(r, dsig, dsigerr, **kw):
    """
    plot delta sigma

    useful if adding to an existing plot

    parameters
    ----------
    r: array
        radius
    dsig: array
        delta sigma
    dsigerr: array
        error on delta sigma
    """

    from biggles import FramedPlot

    nbin=1
    _set_biggles_defs(nbin)

    visible=kw.get('visible',True)
    xlog=kw.get('xlog',True)
    ylog=kw.get('ylog',True)
    aspect_ratio=kw.get('aspect_ratio',1)

    is_ortho=kw.get('is_ortho',False)

    plt=kw.get('plt',None)

    if plt is None:
        plt=FramedPlot()
        plt.aspect_ratio=aspect_ratio
        plt.xlog=xlog
        plt.ylog=ylog

        plt.xlabel = LABELS['rproj']
        if is_ortho:
            plt.ylabel = LABELS['osig']
        else:
            plt.ylabel = LABELS['dsig']

    xrng, yrng = _add_dsig_to_plot(plt, r, dsig, dsigerr, **kw)
    plt.xrange=xrng
    plt.yrange=yrng

    if visible:
        plt.show()

    return plt

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
    def plot_xi(self, r, xi):
        from biggles import FramedPlot, Curve
        minval = 1.e-4

        xi = where(xi < minval, minval, xi)

        plt=FramedPlot()
        plt.add(Curve(r,xi))
        plt.xlog=True
        plt.ylog=True

        plt.xlabel = r'$r [Mpc/h]$'
        plt.ylabel = r'$\xi_{lin}(r)$'
        plt.aspect_ratio=1
        plt.show()

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def test_xi_converge_nplk(epsfile=None):
    """
    Test how xi converges with the number of k points per log10(k)
    Note we should test other convergence factors too!
    """

    tab=Table(2,1) 
    pltbig = FramedPlot()
    pltzoom = FramedPlot()

    pltbig.xlabel='r'
    pltbig.ylabel='xi(r)'
    pltbig.xlog=True
    pltbig.ylog=True
    pltzoom.xlabel='r'
    pltzoom.ylabel='xi(r)'

    l=Linear()
    r=10.0**linspace(0.0,2.3,1000) 
    nplk_vals  = [20,60,100,140,160]
    color_vals = ['blue','skyblue','green','orange','magenta','red']

    plist=[]
    lw=2.4
    for nplk,color in zip(nplk_vals,color_vals):
        print 'nplk:',nplk
        xi =  l.xi(r, nplk=nplk)

        limxi = where(xi < 1.e-5, 1.e-5, xi)
        climxi = Curve(r,limxi,color=color,linewidth=lw)
        climxi.label = 'nplk: %i' % nplk
        pltbig.add(climxi)

        plist.append(climxi)

        w=where1(r > 50.0)
        cxi = Curve(r[w], xi[w], color=color, linewidth=lw)
        pltzoom.add(cxi)

    key = PlotKey(0.7,0.8, plist)
    pltzoom.add(key)
    tab[0,0] = pltbig
    tab[1,0] = pltzoom
    if epsfile is not None:
        tab.write_eps(epsfile)
    else:
        tab.show()

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot_drho(comb=None, r=None, drho=None, drhoerr=None, 
              color='black',type='filled circle',
              nolabel=False, noshow=False, minval=1.e-5,
              aspect_ratio=1):
    """
    This one stands alone. 
    """

    if comb is not None:
        r=comb['rdrho']
        drho=comb['drho']
        drhoerr=comb['drhoerr']
    else:
        if r is None or drho is None or drhoerr is None:
            raise ValueError("Send a combined struct or r,drho,drhoerr")


    plt=FramedPlot()
    plt.aspect_ratio=aspect_ratio
    plt.xlog=True
    plt.ylog=True

    if not nolabel:
        plt.xlabel = r'$r$ [$h^{-1}$ Mpc]'
        plt.ylabel = r'$\delta\rho ~ [M_{\odot} pc^{-3}]$'


    od=add_to_log_plot(plt, r, drho, drhoerr, 
                       color=color, 
                       type=type,
                       minval=minval)

    # for drho we need even broader yrange
    plt.xrange = od['xrange']

    yr=od['yrange']
    plt.yrange = [0.5*yr[0], 3*yr[1]]

    if not noshow:
        plt.show()
    od['plt'] = plt
    return od

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot_mass(comb=None, r=None, mass=None, masserr=None, 
              color='black',type='filled circle',
              nolabel=False, noshow=False, minval=1.e11,
              aspect_ratio=1):

    if comb is not None:
        r=comb['rmass']
        mass=comb['mass']
        masserr=comb['masserr']
    else:
        if r is None or mass is None or masserr is None:
            raise ValueError("Send a combined struct or r,mass,masserr")


    plt=FramedPlot()
    plt.aspect_ratio=aspect_ratio
    plt.xlog=True
    plt.ylog=True

    if not nolabel:
        plt.xlabel = r'$r$ [$h^{-1}$ Mpc]'
        plt.ylabel = r'$M(<r) ~ [h^{-1} M_{\odot}]$'


    od=add_to_log_plot(plt, r, mass, masserr, 
                       color=color, 
                       type=type,
                       minval=minval)

    plt.xrange = od['xrange']
    plt.yrange = od['yrange']

    if not noshow:
        plt.show()
    od['plt'] = plt
    return od

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot_dsig(**keys):
    """
    This one stands alone. 
    """

    comb=keys.get('comb',None)
    r=keys.get('r',None)
    dsig=keys.get('dsig',None)
    dsigerr=keys.get('dsigerr',None)
    color=keys.get('color','black')
    type=keys.get('type','filled circle')
    nolabel=keys.get('nolabel',False)
    show=keys.get('show',True)
    minval=keys.get('minval',1.e-3)
    xlog=keys.get('xlog',True)
    ylog=keys.get('ylog',True)
    aspect_ratio=keys.get('aspect_ratio',1)
    plt=keys.get('plt',None)

    label=keys.get('label',None)

    if comb is not None:
        r=comb['r']
        dsig=comb['dsig']
        dsigerr=comb['dsigerr']
    else:
        if r is None or dsig is None or dsigerr is None:
            raise ValueError("Send a combined struct or r,dsig,dsigerr")

    if plt is None:
        plt=FramedPlot()
        plt.aspect_ratio=aspect_ratio
        plt.xlog=xlog
        plt.ylog=ylog

        if not nolabel:
            plt.xlabel = labels['rproj']
            plt.ylabel = labels['dsig']

    if ylog:
        od=add_to_log_plot(plt, r, dsig, dsigerr, 
                           color=color, 
                           type=type,
                           minval=minval)
        plt.xrange = od['xrange']
        plt.yrange = od['yrange']

        if label:
            od['p'].label=label
    else:
        zpts=Curve(r, dsig*0)
        plt.add(zpts)

        pts=Points(r, dsig, type=type, color=color)

        if label:
            pts.label=label

        plt.add(pts)
        if dsigerr is not None:
            epts=SymErrY(r, dsig, dsigerr, color=color)
            plt.add(epts)

        yrng=keys.get('yrange',None)
        xrng=keys.get('xrange',None)
        if yrng:
            plt.yrange=yrng
        if xrng:
            plt.xrange=xrng
        else:
            if xlog:
                plt.xrange=eu.plotting.get_log_plot_range(r)



    if show:
        plt.show()

    if ylog:
        od['plt'] = plt
        return od
    else:
        return plt

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def plot2dsig_over(r1,dsig1,dsig1err,r2,dsig2, dsig2err, **keys):
    ptype1=keys.get('ptype1','filled circle')
    ptype2=keys.get('ptype2','filled circle')
    size1=keys.get('size1',1)
    size2=keys.get('size2',1)
    color1=keys.get('color1','red')
    color2=keys.get('color2','blue')
    label  = keys.get('label',None)
    label1 = keys.get('label1',None)
    label2 = keys.get('label2',None)
    xrng = keys.get('xrange',None)
    yrng = keys.get('yrange',None)
    show = keys.get('show',True)

    ylog = keys.get('ylog',True)
   
    plt=keys.get('plt',None)

    yall=numpy.concatenate((dsig1, dsig2))
    yerrall=numpy.concatenate((dsig1err, dsig2err))

    if yrng is None:
        if ylog:
            yrng = eu.plotting.get_log_plot_range(yall, err=yerrall, 
                                                  input_range=yrng)

    rr=numpy.concatenate((r1,r2))
    if xrng is None:
        xrng = eu.plotting.get_log_plot_range(rr)

    if plt is None:
        plt=FramedPlot()
    plt.xlog=True
    plt.ylog=ylog
    plt.xrange=xrng
    plt.yrange=yrng
    plt.xlabel = labels['rproj']
    plt.ylabel = labels['dsig']

    dsig1_p = Points(r1, dsig1, color=color1, type=ptype1, size=size1)
    dsig1err_p = SymErrY(r1, dsig1, dsig1err, color=color2)
    dsig1_p.label=label1

    dsig2_p = Points(r2, dsig2, color=color2, type=ptype2, size=size2)
    dsig2err_p = SymErrY(r2, dsig2, dsig2err, color=color2)
    dsig2_p.label=label2

    plt.add(dsig1_p, dsig2_p)

    if ylog:
        # biggles chokes if you give it negative data for a log plot
        eu.plotting.add_log_error_bars(plt,'y',r1,dsig1,dsig1err,yrng,
                                       color=color1)
        eu.plotting.add_log_error_bars(plt,'y',r2,dsig2,dsig2err,yrng,
                                       color=color2)
    else:
        err1 = biggles.SymmetricErrorBarsY(r1,dsig1,dsig1err,color=color1)
        err2 = biggles.SymmetricErrorBarsY(r2,dsig2,dsig2err,color=color2)
        plt.add(err1,err2)

        zerop = biggles.Curve(xrng, [0,0])
        plt.add(zerop)

    if label is not None:
        plt.add(PlotLabel(0.9,0.9,label,halign='right'))

    if label1 is not None or label2 is not None:
        key = PlotKey(0.9,0.15, [dsig1_p,dsig2_p], halign='right')
        plt.add(key)

    if show:
        plt.show()
    return plt

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def compare_idl(ratios=False, epsfile=None):
    from biggles import FramedPlot,Points, Table
    omega_m=0.25
    omega_b=0.055
    sigma_8=1.0
    h=1.0
    ns=0.98

    r=eu.recfile.Open('/home/esheldon/tmp/linear-compare/pkidl.dat',
                      delim=' ',dtype=[('k','f8'),('pk','f8')])
    pkidlst = r.read()
    r.close()

    k,pkidl = pkidlst['k'],pkidlst['pk']

    r=eu.recfile.Open('/home/esheldon/tmp/linear-compare/xiidl.dat',
                      delim=' ',dtype=[('r','f8'),('xi','f8')])
    xiidlst = r.read()
    r.close()

    r,xiidl = xiidlst['r'],xiidlst['xi']

    l = Linear(omega_m=omega_m,omega_b=omega_b,sigma_8=sigma_8,h=h,ns=ns)

    pk = l.pk(k)
    xi = l.xi(r, nplk=1000)
    #xi = l.xi(r)

    pkrat = pk/pkidl
    xirat = xi/xiidl

    tab=Table(2,1)

    symsize=1

    if ratios:

        pkplt = FramedPlot()
        pkplt.xlabel='k'
        pkplt.xlog=True
        pkplt.ylabel='P(k)/P(k) dave'
        pkplt.add( Points(k,pkrat,type='filled circle',size=symsize) )
        pkplt.add( Curve(k,pkrat,color='blue') )

        tab[0,0] = pkplt

 
    if ratios:

        xiplt = FramedPlot()
        xiplt.xlabel='r'
        xiplt.xlog=True

        xiplt.ylabel='xi(r)/xi(r) dave'
        xiplt.add( Points(r,xirat,type='filled circle',size=symsize) )
        xiplt.add( Curve(r,xirat,color='blue') )

        tab[1,0] = xiplt
    else:

        # big log-log plot
        limxi = where(xi < 1.e-5, 1.e-5, xi)
        #pxi = Points(r,limxi,type='filled circle',size=symsize)
        cxi = Curve(r,limxi,color='blue')

        limxiidl = where(xiidl < 1.e-5, 1.e-5, xiidl)
        #pxiidl = Points(r,limxiidl,type='filled circle',size=symsize)
        cxiidl = Curve(r,limxiidl,color='red')

        xipltall = FramedPlot()
        xipltall.xlabel='r'
        xipltall.xlog=True
        xipltall.ylog=True
        xipltall.ylabel='xi(r)'

        #xipltall.add(pxi,cxi,pxiidl,cxiidl)
        xipltall.add(cxi,cxiidl)
       
        tab[0,0] = xipltall

        # zoomed in plot
        xiplt = FramedPlot()
        xiplt.xlabel='r'
        xiplt.xlog=True
        xiplt.ylabel='xi(r)'

        pxi = Points(r,xi,type='filled circle',size=symsize) 
        cxi = Curve(r,xi,color='blue')
        cxi.label = 'Mine'

        pxiidl = Points(r,xiidl,type='filled circle',size=symsize)
        cxiidl = Curve(r,xiidl,color='red')
        cxiidl.label = 'Dave'

        key=PlotKey(0.8,0.9, [cxi,cxiidl])

        xiplt.add(pxi,cxi,pxiidl,cxiidl)
        xiplt.xrange = [50.0,r.max()]
        xiplt.yrange=[-2.e-3,1.e-2]
        xiplt.add(key)
#.........这里部分代码省略.........

# 需要导入模块: from biggles import FramedPlot [as 别名]
# 或者: from biggles.FramedPlot import ylog [as 别名]
def test_fit_nfw_lin_dsig(rmin=0.01):

    from biggles import FramedPlot,Points,SymmetricErrorBarsY,Curve,PlotKey
    omega_m=0.25
    z=0.25


    r200 = 1.0
    c = 5.0
    B=10.0

    rmax = 50.0
    log_rmin = log10(rmin)
    log_rmax = log10(rmax)
    npts = 30
    r = 10.0**linspace(log_rmin,log_rmax,npts)

    fitter = NFWBiasFitter(omega_m,z,r)
    ds = fitter.dsig(r, r200, c, B)
    # 10% errors
    dserr = 0.1*ds
    ds += dserr*numpy.random.standard_normal(ds.size)

    guess = numpy.array([r200,c,B],dtype='f8')
    # add 10% error to the guess
    guess += 0.1*guess*numpy.random.standard_normal(guess.size)

    res = fitter.fit(ds,dserr,guess, more=True)

    r200_fit=res['r200']
    r200_err = res['r200_err']
    c_fit=res['c']
    c_err = res['c_err']
    B_fit=res['B']
    B_err = res['B_err']


    print 'Truth:'
    print '    r200: %f' % r200
    print '       c: %f' % c
    print '       B: %f' % B
    print 'r200_fit: %f +/- %f' % (r200_fit,r200_err)
    print '   c_fit: %f +/- %f' % (c_fit,c_err)
    print '   B_fit: %f +/- %f' % (B_fit,B_err)
    print 'Cov:'
    print res['cov']

 
    rfine = 10.0**linspace(log_rmin,log_rmax,100)
    fitter2 = NFWBiasFitter(omega_m,z,rfine)

    yfit = fitter2.dsig(rfine, r200_fit, c_fit, B_fit)
    yfit_nfw = fitter2.nfw.dsig(rfine, r200_fit, c_fit)
    yfit_lin = fitter2.lin_dsig(rfine,B_fit)

    plt=FramedPlot()
    plt.add(Points(r,ds,type='filled circle'))
    plt.add(SymmetricErrorBarsY(r,ds,dserr))

    cyfit = Curve(rfine,yfit,color='blue')
    cyfit_nfw = Curve(rfine,yfit_nfw,color='red')
    cyfit_lin = Curve(rfine,yfit_lin,color='orange')

    cyfit.label = 'Best Fit'
    cyfit_nfw.label = 'NFW'
    cyfit_lin.label = 'linear'

    key=PlotKey(0.1,0.3,[cyfit,cyfit_nfw,cyfit_lin])
    plt.add(cyfit,cyfit_nfw,cyfit_lin,key)

    plt.xlabel = r'$r$ [$h^{-1}$ Mpc]'
    plt.ylabel = r'$\Delta\Sigma ~ [M_{sun} pc^{-2}]$'

    plt.xrange = [0.5*rmin, 1.5*rmax]
    plt.yrange = [0.5*(ds-dserr).min(), 1.5*(ds+dserr).max()]

    plt.xlog=True
    plt.ylog=True
    plt.show()