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v0.9.0

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@jonasvdd jonasvdd released this 12 Jul 08:36
· 36 commits to main since this release

Major changes:

Even faster aggregation 🐎

We switched our aggregation backend to tsdownsample, which alleviates the need to compile our C code on non-supported devices, and has parallelization capabilities.
tsdownsample leverages the argminmax crate, which has SIMD-optimized instruction to find vertical extrema really fast!

With parallelization enabled, you should clearly see a bump in perfomance when visualizing (multiple) large traces! 🐎

Versioned docs! :party:

We restyled our documentation and added versioning! πŸŽ‰

https://predict-idlab.github.io/plotly-resampler/latest/

Go check it out! ☝️

Other Features

  • Support for log-scale axes (and thus log-bin-based aggregators) - check this pull-request

The above image shows how the log aggregator (row2) will use log-scale bins. This can be seen in the 1-1000 range when comparing both subplots.
Note: the shown data has a fixed delta-x of 1. Hence, here are no exact equally spaced bins for the left part of the LogLTTB.

  • Add a fill-value option to gap handlers

The above image shows how the fill_value option can be used to fill gaps with a specific value.
This can be of greate use, when you use the fill='tozeroy' option in plotly and gaps occur in your data, as this will, combined with line_shape='vh', fill the area between the trace and the x-axis and gaps will be a flat zero-line.

Bugfixes

  • support for pandas2.0 intricacies

What's Changed (generated)

Full Changelog: v0.8.3.2...v0.9.0