Added antialiasing and thick lines to categorical example
"outputs": [],
"source": [
"lines = {i: hv.Curve(time_series(N=10000, S0=200+np.random.rand())) for i in range(num_ks)}\n",
- "linespread = dynspread(datashade(hv.NdOverlay(lines, kdims='k'), aggregator=ds.by('k', ds.count())))\n",
- "linespread.opts(opts.RGB(width=800))"
+ "lineoverlay = hv.NdOverlay(lines, kdims='k')\n",
+ "datashade(lineoverlay, pixel_ratio=2, line_width=4, aggregator=ds.by('k', ds.count())).opts(width=800)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
+ "As you can see, overlapping colors yield color mixtures that indicate that the given pixels contain data from multiple curves, which helps users realize where they need to zoom in to see further detail.\n",
+ "\n",
"Note that Bokeh only ever sees an image come out of `datashade`, not any of the actual data. As a result, providing legends and keys has to be done separately, though we are hoping to make this process more seamless. For now, you can show a legend by adding a suitable collection of \"fake\" labeled points (size zero and thus invisible):"
]
},
