Hello,

with the following code partly taken from http://holoviews.org/user_guide/Large_Data.html

```
import datashader as ds
import numpy as np
import holoviews as hv
from holoviews import opts
from holoviews.operation.datashader import datashade, shade, dynspread, spread, rasterize
from holoviews.operation import decimate
hv.extension('bokeh','matplotlib')
def random_cov():
"""Random covariance for use in generating 2D Gaussian distributions"""
A = np.random.randn(2,2)
return np.dot(A, A.T)
np.random.seed(3)
kdims=['d1','d2']
num_ks=8
def rand_gauss2d(value=0, n=100000):
"""Return a randomly shaped 2D Gaussian distribution with an associated numeric value"""
g = 100*np.random.multivariate_normal(np.random.randn(2), random_cov(), (n,))
return np.hstack((g,value*np.ones((g.shape[0],1))))
gaussians = {i: hv.Points(rand_gauss2d(i), kdims, "i") for i in range(num_ks)}
dynspread(datashade(hv.NdOverlay(gaussians, kdims='k'), aggregator=ds.by('k', ds.any())))
```

If i zoom into the resulting plot, the data points stay really really small.

Using the ds.count function like this

```
dynspread(datashade(hv.NdOverlay(gaussians, kdims='k'), aggregator=ds.by('k', ds.count())))
```

i the points do get bigger when zooming in.

I kind of understand i guess, that the dynspreading is counting nearby non empty pixels (?), and i guess with ds.any(), those are never non empty maybe?

Is there somehow a way to enable dynspread with ds.any aggregation?