Add more decimate options

Right now, the HoloViews decimate operator randomly samples from the available data, dynamically on each zoom or pan. This is often a useful behavior, particularly for disconnected plots like Scatter, but for connected plots like Curve (e.g. timeseries) and Path, the results are chaotic and not a particularly good representation of the underlying data. For such cases, other options would be more useful:

• Regular sampling: Regularly spaced downsampling (slicing with a stride) should be trivial to implement and would give a good approximation to the shape of smooth curves.
• Outlier preserving: Some algorithms like Largest Triangle are better at preserving outliers, but may be slower and definitely would take more work to implement.
• Mean aggregation: It would be slower than sampling, but one could aggregate over the data points in each stride chunk to take the mean, so that all data points at least affect the result.

If we implemented multiple types of sampling, the policy could be selected by mode='random', mode='regular', etc. We might want the default to be mode=None, where a mode appropriate to that Element type (e.g. random for Scatter and Points) would be selected.

[jbednar]

Looks like I duplicated my own issue 4 years later: https://github.com/holoviz/holoviews/issues/5359

5359 includes links to LTTB sample code; please see that for details.

[jbednar]

No, it’s wide open for any interested user to dive into, and should be an easy win!