def METHOD_NAME(name, x, y=None):
	dpi=100.
	fig = plt.figure(dpi=dpi)
	fig.set_size_inches(512./dpi, 512./dpi)
	#plt.figure(figsize=(512/my_dpi, 800/my_dpi), dpi=my_dpi)
	#ax = fig.add_subplot(111)
	ax = plt.Axes(fig, [0., 0., 1., 1.])
	ax.set_axis_off()	
	fig.add_axes(ax)
	Ngrid = 512
	counts = np.zeros((Ngrid, Ngrid), dtype=np.float64)
	dataset = dataset_map[name]
	blockx = dataset.columns[x].astype(np.float64)
	blocky = dataset.columns[y].astype(np.float64)
	sub_i1, sub_i2 = 0, dataset._length
	ranges = [0, 100, 0, 100]
	if "ranges" in request.args:
		ranges = map(float, request.args["ranges"].split(","))
	colormap = request.args.get("colormap", "jet")
	sub_counts = [counts]
	print ranges
	index = 0
	print blockx[sub_i1:sub_i2].shape, blocky[sub_i1:sub_i2].shape, None, sub_counts[index].shape, ranges
	vaexfast.histogram2d(blockx[sub_i1:sub_i2], blocky[sub_i1:sub_i2], None, sub_counts[index], *ranges)
	print "next"
	ax.imshow(np.log10(counts), origin="lower", extent=ranges, cmap=colormap)
	ax.set_aspect('auto')
	#ax.set_axis_off()
	f = StringIO.StringIO()
	fig.savefig(f)
	data = f.getvalue()
	print len(data)
	response = make_response(f.getvalue())
	response.mimetype = 'image/png'
	return response
	#return 'Plot ' +name  +":" + x+ " / " +y