Skip to contents

Changelog

Source: NEWS.md

animovement 0.7.3

  • Added here and signal to Suggests, and circular for summarise_aniframe().
  • Suggested packages can now be installed from the r-universe and Bioconductor (rhdf5) r-universe mirrors.
  • Documentation overhaul: articles converted to Quarto (.qmd), trackball articles modernised to the current API, and shared pkgdown theming inherited from animovementtemplate.
  • Added webR / r-wasm support so the package can run in the browser.

animovement 0.7.2

  • Added anispace to the bundled suite, bringing spatial analysis functionality into animovement.

animovement 0.7.1

  • Added animovement_install_suggested() to help users install the optional packages used by some functions.
  • Updated CI workflows, README and citation metadata.

animovement 0.7.0

animovement is now a metapackage. The codebase has been split into a suite of focused packages that animovement bundles and re-exports:

  • aniframe — the standardised ani_df data class
  • aniread — data readers
  • aniprocess — cleaning, filtering and processing
  • anicheck — quality-control checks
  • animetric — movement metrics
  • anivis — visualisation

Other changes:

  • New ani_df class with accompanying improvements and tests.
  • Continued metadata improvements.
  • frame rate terminology replaced with sampling rate throughout.
  • Removed the classify_ functions.
  • Switched to Air for code formatting.

animovement 0.6.0

A large feature release focused on filtering, calculations and movement classification:

  • Added Kalman filters and improved bandwidth filters for smoothing.
  • Added replace_na()/NA-handling functions and classify_low_periods().
  • Added coordinate rotation and egocentric transformation, plus centroid and coordinate transformations.
  • Added peak/trough (extrema) detection and timeseries alignment, with improved detection of active periods.
  • Added kinematics calculations and a filter_by_speed() fix.
  • Added set_individual()/set_framerate() helpers and a return_type parameter to several functions.
  • Many new tests and documentation improvements.

animovement 0.5.1

Previously, smooth_track was only built to smoothen trackball data. In this fix, we fixed it by doing the following: - Changed the name to smooth_movement - Added parameter use_derivatives (default: FALSE) which is how trackball data should be smoothed - Written the non-derivative code

So now smooth_movement should be able to smooth all your movement data!

animovement 0.5.0

A big update! There are three major updates: - We finally stabilised on a data format and implemented it for all readers! - We’ve introduced metadata. It’s still experimental, but an important step in the right direction. - We added tests to ensure the output data frames from readers always contain the expected columns and column classes. - We also added tests to ensure metadata is present after reading a data frame.

We are not nearly done with the work on metadata, but are exited to finally get it started.

animovement 0.4.1

Changed parameter in read_animalta().

animovement 0.4.0

Added readers for AnimalTA (read_animalta) and idtracker.ai (read_idtracker).

animovement 0.3.0

Has added the ability to read centroid tracking from Bonsai files through read_bonsai().

animovement 0.2.0

Package name changed to animovement! To reflect the change in scope of the package to now cover a wide variety of movement data, the package has changed its name. This was a conscious decision as maintaining two packages with similar functionality wouldn’t be feasible long-term. The new update brings with it a wealth of new functionality, but also a lot of breaking changes. With this update, the package aligns much closer to my vision for it, and I expect no more major breaking changes in the near future. So let’s delve in to all the new stuff!

  • Much improved documentation
  • Added new readers read_deeplabcut(), read_sleap(), read_trex()…
  • Standardised data cleaning with smooth_tracks()
  • More tests

Although this is annoying to current users, it was a necessity to ensure proper testing of all the various functions which have now been broken into smaller subsets. If you still need the former trackballr package functionality, you can download the source files in Github and install from source.

If you encounter bugs, please report them in the Github issues.