v0.6.0
This release focuses on fixing bugs and some inconsistencies in the prediction
capabilities. Some existing code that used prediction may now fail to run until
a (minor) update is made.
This release includes contributions by @magnunor, @freemansw1, @crisp-snakey,
@rbnvrw, @caspervdw, @tacaswell, and @nkeim.
Enhancements
- Linking can now use any
DistanceMetric
class from sklearn to compute
distances (#692 by @freemansw1) - Several documentation fixes by @magnunor and @nkeim
API Changes
- When supplying an initial velocity guess to NearestVelocityPredict or
DriftPredict, you must also supply the pos_columns argument to identify
the names of the columns in your array. (For example,
"pos_columns = ['y', 'x']".) Otherwise, creating the predictor will
raise an exception that explains this change. If you provide pos_columns
when creating the predictor, you do not have to supply it when subsequently
using the link_df() or link_df_iter() methods to link your features.
(@nkeim, #710) reconnect_traj_patch()
is now available astrackpy.reconnect_traj_patch
and is described in the API documentation. (@nkeim, #648)
Bug Fixes
- When linking with prediction, the predictor now correctly uses the same
position columns as the linker, and correctly handles the pos_columns
argument if specified. (@nkeim, #710) - The link_df() method of predictor objects now works correctly. (@nkeim, #710)
Dependencies
- trackpy is now being tested in conda environments with Python 3.10.
- trackpy is no longer tested with Python 3.6.
- trackpy now requires the
looseversion
package to work with newer scipy
(@crisp-snakey, #706) - Much work on testing and packaging infrastructure by @tacaswell and @caspervdw
Note: This release is tagged v0.6.0.1
on GitHub to address an issue with Zenodo DOI generation. There are no other differences between the GitHub version and the v0.6.0
packages.