def qplot(q):
	qpts = [Bra(coherent(x+y*1j)) for x in xs for y in ys]
	A = Matrix(gs, gs, [abs(a*q)**2 for a in qpts])
	conts = pylab.contour(xs, ys, A, colors='brown', alpha=0.5, linewidths=2)
	pylab.clabel(conts, **csty)
	pylab.axis([2-ext,2+ext,-ext,ext])
	pylab.axis('off')

def plotear(xi,yi,zi):
    # mask inner circle
    interior1 = sqrt(((xi+1.5)**2) + (yi**2)) < 1.0 
    interior2 = sqrt(((xi-1.5)**2) + (yi**2)) < 1.0
    zi[interior1] = ma.masked
    zi[interior2] = ma.masked
    p.figure(figsize=(16,10))
    pyplot.jet()
    max=2.8
    min=0.4
    steps = 50
    levels=list()
    labels=list()
    for i in range(0,steps):
	levels.append(int((max-min)/steps*100*i)*0.01+min)
    for i in range(0,steps/2):
	labels.append(levels[2*i])
    CSF = p.contourf(xi,yi,zi,levels,norm=colors.LogNorm())
    CS = p.contour(xi,yi,zi,levels, format='%.3f', labelsize='18')
    p.clabel(CS,labels,inline=1,fontsize=9)
    p.title('electrostatic potential of two spherical colloids, R=lambda/3',fontsize=24)
    p.xlabel('z-coordinate (3*lambda)',fontsize=18)
    p.ylabel('radial coordinate r (3*lambda)',fontsize=18)
    # add a vertical bar with the color values
    cbar = p.colorbar(CSF,ticks=labels,format='%.3f')
    cbar.ax.set_ylabel('potential (reduced units)',fontsize=18)
    cbar.add_lines(CS)
    p.show()

def plotSurface(pt, td, winds, map, stride, title, file_name):
    pylab.figure()
    pylab.axes((0.05, 0.025, 0.9, 0.9))

    u, v = winds

    nx, ny = pt.shape
    gs_x, gs_y = goshen_3km_gs
    xs, ys = np.meshgrid(gs_x * np.arange(nx), gs_y * np.arange(ny))   

    data_thin = tuple([ slice(None, None, stride) ] * 2)

    td_cmap = matplotlib.cm.get_cmap('Greens')
    td_cmap.set_under('#ffffff')
    pylab.contourf(xs, ys, td, levels=np.arange(40, 80, 5), cmap=td_cmap)
    pylab.colorbar()
    CS = pylab.contour(xs, ys, pt, colors='r', linestyles='-', linewidths=1.5, levels=np.arange(288, 324, 4))
    pylab.clabel(CS, inline_spacing=0, fmt="%d K", fontsize='x-small')
    pylab.quiver(xs[data_thin], ys[data_thin], u[data_thin], v[data_thin])

    drawPolitical(map, scale_len=75)

    pylab.suptitle(title)
    pylab.savefig(file_name)
    pylab.close()
    return

def plotear(xi,yi,zi):
    # mask inner circle
    interior = sqrt((xi**2) + (yi**2)) < 5.0 
    zi[interior] = ma.zeros
    #exterior = sqrt((xi**2) + (yi**2)) > 25.0
    #zi[exterior] = ma.empty
    p.figure(figsize=(16,10))
    levels = [log(.75e-5), log(1.25e-4), log(2.5e-4), log(0.005), log(0.01), log(0.02), log(0.04), log(0.08), log(0.16), log(0.32), log(0.64)]
    scale = list()
    counter = 0
    for i in levels:
      scale.insert(counter, pow(e,i))
      counter = counter + 1
      #scale[i]=10^i
    #  scale[i] = pow(10,levels[i])
    #levels = [0.005, 0.01, 0.02, 0.04, 0.08, 0.16, 0.32, 0.64, 1.28, 2.56]
    #levels = [log(0.005), log(0.01), log(0.02),log(0.04), log(0.08), log(0.16), log(0.32), log(0.64), log(1.28), log(2.56)]
    #levels = [zi.min() , zi.max() , (zi.max()-zi.min())/10]
    #v = np.linspace(0., 1., 25, endpoint=True)
    #v = np.logspace(1e-8,1e-1, num=10, endpoint=True, base=2)
    #levels = (0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.)
    CSF = p.contourf(xi,yi,zi, levels, cmap=cm.jet)
    #CSF = p.contourf(xi,yi,zi)
    CS = p.contour(xi,yi,zi, levels)
    p.clabel(CS,levels, fmt={log(.75e-5):'hallo', log(1.25e-4):'3', log(2.5e-4):'4', log(0.005):'5', log(0.01):'6', log(0.02):'7', log(0.04):'8', log(0.08):'9', log(0.16):'10', log(0.32):'11', log(0.64):'12'})
    p.title('iPBS relative error')
    p.xlabel('x-coordinate',fontsize=12)
    p.ylabel('y-coordinate',fontsize=12)
    # add a vertical bar with the color values
    cbar = p.colorbar(CSF, ticks=levels, format='%g')
    cbar.ax.set_yticklabels(scale)
    cbar.ax.set_ylabel('Relative error in %',fontsize=12)
    cbar.add_lines(CS)
    p.show()

def draw_bandstructure(
    jobname, kspace, band, ext=".csv", format="pdf", filled=True, levels=15, lines=False, labeled=False, legend=False
):
    # clf()
    fig = figure(figsize=fig_size)
    ax = fig.add_subplot(111, aspect="equal")
    x, y, z = loadtxt(jobname + ext, delimiter=", ", skiprows=1, usecols=(1, 2, 4 + band), unpack=True)
    if kspace.dimensions == 1:
        pylab.plot(x, y, z)
    elif kspace.dimensions == 2:
        xi = linspace(-0.5, 0.5, kspace.x_res)
        yi = linspace(-0.5, 0.5, kspace.y_res)
        zi = griddata(x, y, z, xi, yi)
        if filled:
            cs = ax.contourf(xi, yi, zi, levels, **contour_filled)
            legend and colorbar(cs, **colorbar_style)
            cs = lines and ax.contour(xi, yi, zi, levels, **contour_lines)
            labeled and lines and clabel(cs, fontsize=8, inline=1)
        else:
            cs = ax.contour(xi, yi, zi, levels, **contour_plain)
            legend and colorbar(cs, **colorbar_style)
            labeled and clabel(cs, fontsize=8, inline=1)
        ax.set_xlim(-0.5, 0.5)
        ax.set_ylim(-0.5, 0.5)
    savefig(jobname + format, format=format, transparent=True)

def plot_pairwise_contours(theta,nuvec,Cinv,lvls=(2.291,6.158,11.618)):
    """
    > theta is a (3,) vector that contains the model parameters
    > thetavecs is a (n,3) matrix that contains the values of the parameters 
        that will be plotted over
    """
    labels = ['A','nu0','sigma']
    fisher = fisher_matrix(theta,nuvec,Cinv)
    Finv = n.linalg.inv(fisher)
    thetavecs = n.zeros((50,theta.shape[0]))
    for ii in range(theta.shape[0]):
        thetavecs[:,ii] = n.linspace(theta[ii]-5*n.sqrt(Finv[ii,ii]),theta[ii]+5*n.sqrt(Finv[ii,ii]),num=50)
    print thetavecs
    for ii,jj in ((0,1),(0,2),(1,2)):
        print ii,jj
        ts = thetavecs[:,[ii,jj]]
        print thetavecs.shape
        print ts.shape
        fs = fisher_select_pair(fisher,ii,jj)
        print fs.shape
        t0,t1 = n.meshgrid(ts[:,0],ts[:,1])
        print t0.shape

        Z = fs[0,0]*(t0-theta[ii])*(t0-theta[ii]) + (fs[0,1]+fs[1,0])*(t0-theta[ii])*(t1-theta[jj]) + fs[1,1]*(t1-theta[jj])*(t1-theta[jj])

        p.pcolor(t0,t1,Z)
        p.colorbar()
        CS = p.contour(t0,t1,Z,levels=lvls) #levels=lvls
        p.clabel(CS, inline=1, fontsize=10)
        #p.contour(t0,t1,Z,lvls)
        p.xlabel(labels[ii])
        p.ylabel(labels[jj])
        p.savefig('./figures/fisher/contours_{0}_{1}.pdf'.format(labels[ii],labels[jj]))
        p.clf()

def graficaIntensidad(Z):

    'grafica curvas de nivel'

    #Se dibuja la funcion

    im = imshow(Z,cmap=cm.RdBu)

    

    #Se agrega el contorno de lineas con sus etiquetas

    cset = contour(Z,n.arange(-2.0,2.0,0.1),linewidths=2,cmap=cm.Set2)

    clabel(cset,inline=True,fmt='%1.1f',fontsize=10)

    

    #Se agrega la barra de colores a la derecha

    colorbar(im)



    show()

def plotear(xi,yi,zi):
    # mask inner circle
    interior = sqrt((xi**2) + (yi**2)) < 1.0 
    zi[interior] = ma.zeros
    pylab.figure(figsize=(16,10))
    levels = [log(1e-9), log(5e-9), log(1e-8), log(5e-8), log(1e-7), log(5e-7), log(1e-6), log(5e-6), log(1e-5), log(5e-5), log(1e-4), log(2e-4), log(4e-4), log(8e-4), log(1.2e-3), log(2.4e-3), log(4.8e-3), log(9.6e-3)]
    matplotlib.rcParams['contour.negative_linestyle'] = 'solid'
    rc('text', usetex=True)
    scale = list()
    counter = 0
    labels = dict()
    for i in levels:
      scale.insert(counter,str(pow(e,i)))
      labels[levels[counter]] = scale[counter]
      counter = counter + 1
    matplotlib.rcParams['contour.negative_linestyle'] = 'solid'
    CS = pylab.contour(xi,yi,zi, levels, colors='black', lynestiles='solid')
    print str(labels)
    pylab.clabel(CS,levels[0::2], fmt=labels, fontsize=20, inline=1)
    #p.clabel(CS,levels[1::2], fmt={log(1e-9):'1e-9', log(5e-9):'5e-9', log(1e-8):'1e-8', log(5e-8):'5e-8', log(1e-7):'1e-7', log(5e-7):'5e-7', log(1e-6):'1e-6', log(5e-6):'5e-8', log(1e-5):'1e-5', log(5e-5):'5e-5', log(1e-4):'1e-4', log(2e-4):'2e-4', log(4e-4):'4e-4', log(8e-4):'8e-4', log(1.2e-3):'1.2e-3', log(2.4e-3):'2.4e-3', log(4.8e-3):'4.8e-3'}, fontsize=9, inline=1)
    pylab.xlim((-7.0,7.0))
    pylab.ylim((0, 7.0))
    pylab.title('iPBS absolute error', fontsize=25)
    pylab.xlabel(r'$\displaystyle z/\lambda_D$',fontsize=20)
    pylab.ylabel(r'$\displaystyle r/\lambda_D$',fontsize=20)
    #pylab.show()
    savefig('ipbs_abs_far')
    return xi, yi, zi

def Contour(X,Y,Z, label='', levels=None, cmapidx=0, colors=None, fmt='%g', lwd=1, fsz=10,
        inline=0, wire=True, cbar=True, zorder=None, markZero='', clabels=True):
    """
    Plot contour
    ============
    """
    L = None
    if levels != None:
        if not hasattr(levels, "__iter__"): # not a list or array...
            levels = linspace(Z.min(), Z.max(), levels)
    if colors==None:
        c1 = contourf (X,Y,Z, cmap=Cmap(cmapidx), levels=levels, zorder=None)
    else:
        c1 = contourf (X,Y,Z, colors=colors, levels=levels, zorder=None)
    if wire:
        c2 = contour (X,Y,Z, colors=('k'), levels=levels, linewidths=[lwd], zorder=None)
        if clabels:
            clabel (c2, inline=inline, fontsize=fsz)
    if cbar:
        cb = colorbar (c1, format=fmt)
        cb.ax.set_ylabel (label)
    if markZero:
        c3 = contour(X,Y,Z, levels=[0], colors=[markZero], linewidths=[2])
        if clabels:
            clabel(c3, inline=inline, fontsize=fsz)

def plot_contour(Z):    
    fig2 = plt.figure(2)
    im = pl.imshow(Z)
    cset = pl.contour(Z)
    pl.clabel(cset,inline=True)
    pl.colorbar(im)
    plt.title('Contour')
    return fig2

def runanalysis():
    filename = ourgui.openFile(type="npz")

    data = np.load(filename, mmap_mode="r")
    Y = data["Y"]
    Z = data["Z"]
    BY = data["BY"]
    BZ = data["BZ"]
    coilpos = getdata(data, "coilpos")
    coilwidth = getdata(data, "coilwidth")
    nturns = getdata(data, "nturns")
    coilsize = getdata(data, "coilsize")

    infopiece = []
    if coilpos:
        infopiece += ['Cpos: %g"' % coilpos]
    if coilwidth:
        infopiece += ['Cwidth: %g"' % coilwidth]
    if coilsize:
        infopiece += ['Csize: %g"' % coilsize]
    if nturns:
        infopiece += ["Turns: %d" % nturns]
    infotitle = ", ".join(infopiece)

    fig = pl.figure(figsize=(11.69, 8.27), dpi=100)
    fig.text(0.4, 0.95, infotitle)

    pl.subplot(2, 2, 1)
    pl.quiver(Z, Y, BZ, BY)
    pl.xlabel("Z")
    pl.ylabel("Y")
    pl.title("Magnetic field direction")

    pl.subplot(2, 2, 2)
    CS = pl.contour(Z, Y, BY / BZ)
    pl.xlabel("Z")
    pl.ylabel("Y")
    pl.title("Y-strength/Z-strength")
    pl.clabel(CS, inline=1, fontsize=10)

    pl.subplot(2, 2, 3)
    zpos = Z[:, 0]
    zfield = BZ[:, 0] / BZ[0, 0]
    pl.plot(zpos, zfield)
    pl.xlabel("Z position")
    pl.ylabel("On axis field strength")

    pl.subplot(2, 2, 4)
    fieldstrength = np.sqrt(BY ** 2 + BZ ** 2)
    CS = pl.contour(Z, Y, fieldstrength)
    pl.xlabel("Z")
    pl.ylabel("Y")
    pl.title("Field strength", fontsize=10)
    pl.clabel(CS, inline=1, fontsize=10)

    pl.show()

def Contour (X,Y,Z, label='', nlevels=None, cmapidx=0, fmt='%g', wire=True, cbar=True):
    L = None
    if nlevels!=None: L = linspace(Z.min(), Z.max(), nlevels)
    c1 = contourf (X,Y,Z, cmap=Cmap(cmapidx), levels=L)
    if wire:
        c2 = contour (X,Y,Z, nlevels=nlevels, colors=('k'), levels=L)
        clabel (c2, inline=0)
    if cbar:
        cb = colorbar (c1, format=fmt)
        cb.ax.set_ylabel (label)

def plot_contour(name, l, a, Z, ax=None):
    if ax is None:
        fig = pb.figure(name)
        ax = fig.add_subplot(111)
    extent = [l.min(),l.max(),a.min(),a.max()]
    c = ax.contour(l,a,Z,colors='k', linestyles='solid')
    pb.clabel(c)
    ax.imshow(Z, extent=extent, origin='lower', interpolation='bilinear')
    ax.set_xlabel('$\log(l)$')
    ax.set_ylabel('$\log(a)$')
    ax.figure.tight_layout()    

def plot_all(n, gext, grid, data0, data1, g0, g1, gavg):
    Z = np.exp(g0)+np.exp(g1)
    eg0 = np.exp(g0)/Z
    eg1 = np.exp(g1)/Z
    err = np.minimum(eg0,eg1)
    err = err.reshape(-1,n)

    lx,hx,ly,hy = gext
    asp = float(hx-lx) / (hy-ly)
    alp = 1.0
    ms = 8

    p.figure()
    p.subplot(2,2,1)
    p.plot(data0[:,0], data0[:,1], 'g^',label='0', markersize=ms, alpha=alp)
    p.plot(data1[:,0], data1[:,1], 'ro',label='1', markersize=ms, alpha=alp)
    p.legend(fontsize=8, loc='best')
    #p.contour(gavg, extent=gext, aspect=1, origin='lower', cmap = p.cm.gray)
    #p.contour(gavg, [0.0], extent=gext, aspect=1, origin='lower', cmap = p.cm.gray)
    #p.imshow(gavg, extent=gext, aspect=1, origin='lower')
    #p.imshow(g0.reshape(-1,n), extent=gext, aspect=asp, origin='lower')
    #p.colorbar()
    p.contour(g0.reshape(-1,n), extent=gext, aspect=asp, origin='lower', cmap = p.cm.Greens)

    p.subplot(2,2,2)
    p.plot(data0[:,0], data0[:,1], 'g^',label='0', markersize=ms, alpha=alp)
    p.plot(data1[:,0], data1[:,1], 'ro',label='1', markersize=ms, alpha=alp)
    p.legend(fontsize=8, loc='best')
    #p.contour(g0.reshape(-1,n), extent=gext, aspect=1, origin='lower', cmap = p.cm.Greens)
    #p.contour(g1.reshape(-1,n), extent=gext, aspect=1, origin='lower', cmap = p.cm.Reds)
    #p.contour((g1-g0).reshape(-1,n), [0.0], extent=gext, aspect=1, origin='lower', cmap = p.cm.gray)
    #p.imshow((g1-g0).reshape(-1,n), extent=gext, aspect=1, origin='lower')
    #p.imshow(g1.reshape(-1,n), extent=gext, aspect=asp, origin='lower')
    #p.colorbar()
    p.contour(g1.reshape(-1,n), extent=gext, aspect=asp, origin='lower', cmap = p.cm.Reds)

    p.subplot(2,2,3)
    p.plot(data0[:,0], data0[:,1], 'g^',label='0', markersize=ms, alpha=alp)
    p.plot(data1[:,0], data1[:,1], 'ro',label='1', markersize=ms, alpha=alp)
    p.legend(fontsize=8, loc='best')
    #p.imshow(err, extent=gext, origin='lower', aspect=asp)
    #p.colorbar()
    p.contour((g1-g0).reshape(-1,n), [0.0], extent=gext, aspect=asp, origin='lower', cmap = p.cm.gray)
    #p.contour(eg0.reshape(-1,n), extent=gext, aspect=1, origin='lower', cmap = p.cm.Greens)
    #p.contour(eg1.reshape(-1,n), extent=gext, aspect=1, origin='lower', cmap = p.cm.Reds)

    p.subplot(2,2,4)
    p.plot(data0[:,0], data0[:,1], 'g^',label='0', markersize=ms)
    p.plot(data1[:,0], data1[:,1], 'ro',label='1', markersize=ms)
    p.legend(fontsize=8, loc='best')
    p.contour((g1-g0).reshape(-1,n), [0.0], extent=gext, aspect=asp, origin='lower', cmap = p.cm.gray)
    CS = p.contour(err, [0.4, 0.3, 0.2, 0.1, 0.05], extent=gext, aspect=asp, origin='lower')
    p.clabel(CS, inline=1, fontsize=10, aspect=asp)
    p.show()

def TS_diagram(ss,ts,ax,dlev=0.1):
    from seawater import csiro as sw
    from numpy import linspace,meshgrid,arange
    from pylab import clabel
    t= linspace(ts.min(), ts.max(), 30)
    s= linspace(ss.min(), ss.max(), 30)
    s2d,t2d = meshgrid(s,t)
    
    #ax.scatter(ss,ts,c=colors, s=size, facecolor=facecolor, edgecolor = 'none', marker = marker)
    h=ax.contour(s2d,t2d,sw.pden(s2d,t2d,s2d*0)-1000,levels=arange(20,30,dlev),colors='k')
    clabel(h,inline=1,fontsize=9,fmt='%3.1f')
    return

def contour_plot(f, xdomain, ydomain, color=True):
    "Contour plot of a function of two variables."
    [xmin, xmax, _] = xdomain; [ymin, ymax, _] = ydomain
    X, Y = np.meshgrid(np.linspace(*xdomain), np.linspace(*ydomain))
    Z = np.array([f([x,y]) for (x,y) in zip(X.flat, Y.flat)]).reshape(X.shape)
    contours = pl.contour(X, Y, Z, 20, colors='black')
    pl.clabel(contours, inline=True, fontsize=8)
    if color:
        pl.imshow(Z, extent=[xmin, xmax, ymin, ymax], origin='lower', cmap='RdGy', alpha=0.5)
        pl.axis(aspect='scalar')
    pl.gcf().tight_layout()
    pl.xlim(xmin,xmax); pl.ylim(ymin,ymax)

def graficaIntensidad(Z):

    'grafica curvas de nivel'

    im = imshow(Z,cmap=cm.RdBu)

    cset = contour(Z,n.arange(-2.0,2.0,0.1),linewidths=2,cmap=cm.Set2)

    clabel(cset,inline=True,fmt='%1.1f',fontsize=10)

    colorbar(im)

    show()

 def plot(self):
     if self.X.shape[1]==1:
         pb.figure()
         Xtest, xmin, xmax = GPy.util.plot.x_frame1D(self.X)
         mu = self.predict(Xtest)
         pb.plot(Xtest.flatten(), mu.flatten(), 'b')
         pb.plot(self.X, self.Y, 'kx', mew=1)
     elif self.X.shape[1]==2:
         pb.figure()
         Xtest,xx,yy, xymin, xymax = GPy.util.plot.x_frame2D(self.X)
         p = self.predict(Xtest)
         c = pb.contour(xx,yy,p.reshape(*xx.shape), colors='k')
         pb.clabel(c)

def contour_plot(f, xdomain, ydomain, color='viridis', alpha=0.5, levels=None):
    "Contour plot of a function of two variables."
    from arsenal import iterview
    [xmin, xmax, _] = xdomain; [ymin, ymax, _] = ydomain
    X, Y = np.meshgrid(np.linspace(*xdomain), np.linspace(*ydomain))
    Z = np.array([f(np.array([x,y])) for (x,y) in iterview(zip(X.flat, Y.flat), length=len(X.flat))]).reshape(X.shape)
    contours = pl.contour(X, Y, Z, 20, colors='black', levels=levels)
    pl.clabel(contours, inline=True, fontsize=8)
    if color is not None:
        pl.imshow(Z, extent=[xmin, xmax, ymin, ymax], origin='lower', cmap=color, alpha=alpha)
        pl.axis(aspect='scalar')
    pl.gcf().tight_layout()
    pl.xlim(xmin,xmax); pl.ylim(ymin,ymax)

def plotear(xi, yi, zi):
    # mask inner circle
    interior = sqrt((xi ** 2) + (yi ** 2)) < 5.0
    zi[interior] = ma.empty
    # exterior = sqrt((xi**2) + (yi**2)) > 15.0
    # zi[exterior] = ma.empty
    p.figure(figsize=(16, 10))
    levels = [
        log(1.1e-3),
        log(1.12e-3),
        log(1.14e-3),
        log(1.18e-3),
        log(1.26e-3),
        log(1.42e-3),
        log(1.74e-3),
        log(1.29e-3),
    ]
    # levels = [log(3.25e-3),log(3.5e-3), log(4.0e-3), log(4.1e-3),log(4.2e-3),log(4.4e-3), log(4.6e-3)]
    # levels = [8e-4, 1e-3, 1.15e-3, 1.20e-3, 1.25e-3, 1.3e-3, 1.4e-3, 1.5e-3, 2e-3, 2.5e-3, 3e-3, 3.5e-3, 4e-3, 4.5e-3, 5e-3, 6e-3, 7e-3, 8e-3, 9e-3, 1e-2]
    # levels = [7e-4, 8e-4, 9e-4, 1e-3, 1.1e-3, 1.12e-3, 1.125e-3, 1.13e-3 ,1.14e-3, 1.16e-3, 1.2e-3, 1.22e-3, 1.24e-3, 1.26e-3, 1.28e-3, 1.3e-3, 1.4e-3, 1.5e-3, 2e-3, 2.5e-3, 3e-3, 3.5e-3, 4e-3, 4.5e-3, 5e-3, 6e-3, 7e-3, 8e-3, 9e-3, 1e-2]
    # levels = [log(2.8125e-7),log(5.625e-7), log(1.125e-6) , log(3.25e-6), log(.75e-5), log(1.25e-4), log(2.5e-4), log(0.005), log(0.01), log(0.02), log(0.04), log(0.08), log(0.16), log(0.32), log(0.64)]
    # levels = [log(.64), log(.32), log(.16), log(.08), log(.04), log(.02), log(.01), log(0.005), log(0.0025)]
    # levels = np.linspace(7.e-4, 1e-2, num=15, endpoint=True)
    # levels = np.logspace(-8,-1, num=20, endpoint=True, base=10)
    scale = list()
    counter = 0
    labels = dict()
    for i in levels:
        scale.insert(counter, str("%1.2e" % pow(e, i)))
        # scale.insert(counter,str(i))
        labels[levels[counter]] = scale[counter]
        counter = counter + 1
    # CSF = p.contourf(xi,yi,zi, levels, cmap=cm.jet)
    mp.rcParams["contour.negative_linestyle"] = "solid"
    CS = p.contour(xi, yi, zi, levels, colors="black", lynestiles="solid")
    print str(labels)
    p.clabel(CS, levels, fmt=labels, fontsize=12, inline=1, color="black")
    # p.clabel(CS)
    p.xlim((-6, 6))
    p.ylim((0, 6))
    # p.clabel(CS,levels[1::2], fmt='%1.1e', fontsize=14, inline=1, color='black')
    # p.clabel(CS,levels[1::2], fmt={log(1e-9):'1e-9', log(5e-9):'5e-9', log(1e-8):'1e-8', log(5e-8):'5e-8', log(1e-7):'1e-7', log(5e-7):'5e-7', log(1e-6):'1e-6', log(5e-6):'5e-8', log(1e-5):'1e-5', log(5e-5):'5e-5', log(1e-4):'1e-4', log(2e-4):'2e-4', log(4e-4):'4e-4', log(8e-4):'8e-4', log(1.2e-3):'1.2e-3', log(2.4e-3):'2.4e-3', log(4.8e-3):'4.8e-3'}, fontsize=9, inline=1)
    p.title("iPBS relative error")
    p.xlabel("z-coordinate", fontsize=14)
    p.ylabel("radial coordinate", fontsize=14)
    # add a vertical bar with the color values
    # cbar = p.colorbar(CSF, ticks=levels, format='%e')
    # cbar.ax.set_yticklabels(scale)
    # cbar.ax.set_ylabel('iPBS relative error',fontsize=12)
    # cbar.add_lines(CS)
    return xi, yi, zi