v0.14.2

Release v0.14.2 - June 2022

• |feature| |efficiency| (Windows-systems only) Removed the unorthodox default installation procedure of DeerLab based on the installation of Numpy and related packages linked against MKL via the Gohlke repository (:issue:322, :pr:330).

  • As a result the default performance of DeerLab can be affected in some Windows systems. To link the Numpy and related packages against MKL as in previous versions, an automated script upgrade_mkl.py is provided with the package.
  • Fixes the error appearing during installation if the git command was not installed or available in the system (:issue:326).
  • Allows the distribution of DeerLab as wheels.

• |feature| Implemented better options for automated and user-supplied noise estimates to improve bootstrapping approaches (:pr:334, :pr:343).

• |fix| Avoid the installation of (potentially unstable) pre-release versions of Numpy in systems with fresh Python installations (:pr:336).

• |fix| Improved the robustness of several function against non-numerical values due to division-by-zero errors (:pr:335).

• |fix| Corrected the behavior of regularization parameter selection with L-curve methods (:pr:340). Fixes the lc method in selgregparam which was seeking the optimal regularization parameter by minimizing curvature rather than by maximizing it. Prevents failure of the L-curve methods due to the appearance of non-numeric values when evaluating too large regularization parameter values.

• |fix| Fixes the error when specifying a limited excitation bandwidth in dipolarmodel via the excbandwidth argument (:pr:342).

• |fix| Fixes the navigation menu on the documentation that appeared empty on mobile phones or for partially minimized windows on computers, impeding navigation through the documentation (:pr:346).

• |fix| Minor corrections to the documentation and examples.