Version 1.0.0 (2022-10-26)

This is a major version with new features, bug fixes, deprecations, and documentation improvements.

New Features

• Added a new class-based api for all algorithms, which can be accessed by using the pybaselines.api.Baseline class. All algorithms are available as methods of the Baseline class. The functional api from earlier versions is also maintained for backwards compatibility.
• All functions now allow inputting an x_data keyword, even if it is not used within the function, to allow for a more consistent api. Likewise, pybaselines.misc.interp_pts added an unused data keyword. Now, all algorithms can be called with the signature baseline_algorithm(data=y_data, x_data=x_data, ...).
• Added a function for Whittaker smoothing to pybaselines.utils, pybaselines.utils.whittaker_smooth.
• whittaker.iasls and spline.psline_iasls now allow inputting a diff_order parameter.

Bug Fixes

• Fixed the addition of the penalty difference diagonals in spline.pspline_drpls, which was incorrectly treating the penalty diagonals as lower banded rather than fully banded.

Other Changes

• Officially list Python 3.11 as supported.
• Added default half_window values for snip and noise_median.
• collab_pls accomodates alpha for aspls and pspline_aspls; the alpha parameter is calculated for the entire dataset in the same way as the weights and is then fixed when fitting each of the individual data entries.
• Improved input validation.
• Improved testing base classes to reduce copied code and improve test coverage.
• Improved code handling for banded systems and penalized splines to simplify internal code.

Deprecations/Breaking Changes

• Removed the ability to pass addtional keyword arguments to algorithms in pybaselines.optimizers, which was deprecated in version 0.8.0.
• Removed the deprecated pybaselines.window module, which was formally deprecated in version 0.8.
• Moved the PENTAPY_SOLVER constant from pybaselines.utils to the new pybaselines.config module.

Documentation/Examples

• Added citation guidelines to make it easier to cite pybaselines.
• Added new examples showing how to use the new Baseline class.
• Added a new example examining the beads algorithm.