Example of plotting points with associated probabilities

Currently, datashader's scatterplot/heatmap approach for points data partitions the set of points, allocating each one into non-overlapping pixel-shaped bins. Some types of data come with associated probabilities, such as a known measurement error bound or an estimated uncertainty per point.

It would be good to have an example of how to aggregate such data, such that the value of each datapoint is assigned to multiple bins in the aggregate array, according to some kernel function (e.g. a 2D Gaussian, where errors are specified as stddevs).

For the special case of a square error kernel, this approach is equivalent to implementing support for raster data (see #86), where each raster datapoint represents a specified area of the X,Y plane with equal probability or weighting within that square.

We'll need a suitable dataset of this type, preferably one with widely varying error estimates across the datapoints, such that some points have tight bounds and others are less constrained.