Antialiasing categorical aggregates

[jbednar]

It doesn't look like antialiasing is supported for categorical aggregates:

import datashader as ds, numpy as np, holoviews as hv
from holoviews.operation.datashader import datashade, dynspread
hv.extension('bokeh')

def time_series(T = 1, N = 100, mu = 0.1, sigma = 0.1, S0 = 20):  
    """Parameterized noisy time series"""
    dt = float(T)/N
    t = np.linspace(0, T, N)
    W = np.random.standard_normal(size = N) 
    W = np.cumsum(W)*np.sqrt(dt)
    X = (mu-0.5*sigma**2)*t + sigma*W 
    S = S0*np.exp(X)
    return S

lines = {i: hv.Curve(time_series(N=10000, S0=200+np.random.rand())) for i in range(6)}
dynspread(datashade(hv.NdOverlay(lines, kdims='k'), line_width=0, aggregator=ds.by('k', ds.count())))

[ianthomas23]

Closed by #1081 and #1083.