v1.1.1

What's Changed

• Automate consistent code style by @michaelosthege in #19
• Updated notebook 4 by @Y0dler in #20
• Update citation instructions by @michaelosthege in #21
• Fix import and compatibility with PyMC v4.0.0b6 by @michaelosthege in #22

New Contributors

• @Y0dler made their first contribution in #20

Full Changelog: v1.1.0...v1.1.1

v1.1.0

What's Changed

• Refactored the bletl.growth submodule for compatibility with PyMC 4.0.0b2 by @michaelosthege in #15

Full Changelog: v1.0.5...v1.1.0

v1.0.5

What's Changed

• BioLector II/Pro measurement rows with REFOVERLD are now skipped in parsing (see #13).

Full Changelog: v1.0.4...v1.0.5

v1.0.4

Fixes a bug in parsing of BioLector Pro result files where metadata of custom-named filtersets was not correctly extracted.

See #9 for details.

v1.0.3

This release brings bugfixes and a tiny breaking change related to the bletl.growth.fit_mu_t function:

• The model was refactored to describe µ only for the segments inbetween the data points. This removes a bias introduced by incorrectly shifting the prediction by 1 timestep. Unfortunately this also means that X and mu have different lengths, so the GrowthRateResult.t was removed in favor of GrowthRateResult.t_data and GrowthRateResult.t_segments.
• A mu_prior kwarg was added to fit_mu_t. This allows the user to predefine where the random walk should start and can greatly improve the result on datasets that don't start with a lag phase.
• The σ kwarg was renamed to drift_scale and is no longer optional.
• The probability threshold used for switchpoint detection can now be user-configured.
• Two bugs in filtering detected switchpoints were fixed.
• Initial growh rate guesses are now clipped to the interval [-0.5, 0.5].

See #4 and #5 for more information.

v1.0.2

• Fixes a bug in the bletl.growth._make_random_walk helper function that caused the nu kwarg to be ignored.
• Also adds a nu kwarg to the fit_mu_t function to allow for fine-tuning of switchpoint prior probability.

Also see 29bf6db.

v1.0.1

• Fixes a bug where fit_mu_t without predefined switchpoints ran into an error
• Increases robustness of fit_mu_t initialization with non-linear calibration models.

See 1fd14a0 for details.

v1.0.0

This is the first public release.

Changes w.r.t. previous internal releases:

• bletl_analysis was merged into the bletl package.
• Sphinx-based documentation was added (see https://bletl.readthedocs.io).
• fit_mu_t now initializes with a growth rate vector calculated by a smoothing approach. This results in more robust optimization.
• Unit tests were refactored to use pytest.
• Docstring were converted to NumpyDoc style.
• Example notebooks were updated.
• The bletl.core submodule was refactored into bletl.types and logic from bletl/__init__.py was moved to bletl.core.