matplotlib - Python Hexbin marginals offset from image produced -

i have simple question. when using python hexbin plot option on spatial data (ra, , dec x , y) want see marginals on side. happily there simple option 'marginals = true'....

unhappily, can see below... x-axis marginals visibly offset hexagon produced image. have tried adjusting parameters marginals on x-axis appear offset image (and there never seems problem in y), ideas appreciated. please see code , image below, in advance!

fig5=plt.figure(5)  ax=fig5.add_subplot(111)  imageh=plt.hexbin(radeg[corel],                   decdeg[corel],                   extent=[np.min(radeg[corel]), np.max(radeg[corel]), np.min(decdeg[corel]), np.max(decdeg[corel])],                   alpha=0.7,                   gridsize=20,                   marginals=true,                   vmin=5,                   vmax=105,                   cmap=get_cmap("jet"),                   mincnt=5)  ax.axis([305,275,-40,-25])  cbar=plt.colorbar(imageh,extend='max')  cbar.set_label(r'$\mathrm{counts}$',fontsize=18)  ax.set_xlabel(r'$\mathrm{ra}$',fontsize=20)  ax.set_ylabel(r'$\mathrm{dec}$',fontsize=18)  plt.show() 

-- per request add data test with..... data rather lengthy , unwieldily, here standalone version illustrates problem. altered version 'hooked' posted in regard different hexbin question.

def generate_data(n):     """make random, correlated x & y arrays"""     points = np.random.multivariate_normal(mean=(0,0),         cov=[[0.4,9],[9,10]],size=int(n))     return points  if __name__ =='__main__':      color_map = plt.cm.spectral_r     n = 1e4     points = generate_data(n)      xbnds = np.array([-20.0,20.0])     ybnds = np.array([-20.0,20.0])     extent = [xbnds[0],xbnds[1],ybnds[0],ybnds[1]]      fig=plt.figure(figsize=(10,9))     ax = fig.add_subplot(111)     x, y = points.t     image = plt.hexbin(x,y,cmap=color_map,gridsize=20,marginals=true,extent=extent,mincnt=1,bins='log')     ax.set_xlim(xbnds)     ax.set_ylim(ybnds)     plt.grid(true)     cb = plt.colorbar(image,spacing='uniform',extend='max')     plt.show() 

this code gives similar image, time marginals offset in x , y direction, integral should in 1 direction, on other variable, i.e. rows , columns. in theory expect marginal on side every row , column have data in.