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What’s new in revision 0.6.8

These are the changes in SpectroChemPy-0.6.8. See Release notes for a full changelog including other versions of SpectroChemPy.

New features

  • Compatibility with Python 3.12

  • Add the possibility to pass a colormap normalization to the plot method.

  • Add the possibility to use several sets of experimental conditions in ActionMassKinetics class.

  • Add the possibility to read Thermo high speed series files

  • Add Stejskal-Tanner kernel for 2D IRIS

  • Fancy indexing using location now supported.

  • Add an example for NMR processing of a series of CP-MAS spectra.

  • Add an example for processing NMR relaxation data

  • Add an option to read_topspin to create y coordinates of pseudo-2D NMR spectra from a file (e.g. vdlist ).

  • Add option to plot to add markers on curves

  • Add a new method to the Optimize class to perform a least-square fitting. It is based on the scipy.optimize.least_squares function, allowing much faster operation for simple curve fitting

  • Add the possibility to define user-defined functions in the Optimize class.

  • Traceback are now fully displayed when an error occurs in a script.

Bug fixes

  • Sorting coordinates now work with multi-coordinates axis.

  • Fix a bug when concatenating datasets with multi-coordinates axis.

  • Fix a bug in coordset definition for integration methods.

  • Fix coordinates definitions in Analysis methods.

  • Fix a bug in write_csv when the filename was provided as a string (issue #706)

  • Fix issue #716

  • Fix issue #714 : show versions of dependencies now working

Breaking changes

  • Changed the default QP solver (quadprog -> osqp): The new solver is compatible with python 3.11 and later. Fastness and robustness are improved. The quadprog solver can still be used if available

  • Change the default value of the whiten parameter in the FastICA class to unit-variance instead of arbitrary-variance for compatibility with ScikitLearn 1.3 and later

  • Colormap normalization for surface, image and map plot methods has been changed for consistency with matplotlib default. The former behaviour can be obtained by passing a norm parameter to the plot method (see userguide/plotting).