pyjams: A general Python package with a wide variety of miscellaneous utility functions.

pyjams is a general Python package offering a wide variety of miscellaneous functions in different categories, such as reading different file formats, date conversion routines, or calculating Elementary Effects. It has several subpackages offering constants, special functions, or objective functions to be used with scipy.optimize.

The package modernises and makes available routines of the JAMS Python library, which was created 2009 by Matthias Cuntz while at the Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany, and continued while at Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), Nancy, France.

The complete documentation of pyjams is available at: https://mcuntz.github.io/pyjams/

This release includes all major routines ported from JAMS. It includes the remaining JAMS routines as a subpackage so that JAMS is now officially deprecated.

Major new routines are:

• Reading ASCII and Excel files, for example fsread and xlsxread.
• Meteorological functions such as saturated vapour pressure or conversions between relative, absolute, and specific humidity, for example esat and eair2rhair.
• Simple TKinter GUIs for choosing files and directories (if Tkinter is installed).
• Facilitating handling of netCDF files, for example ncread and module ncio.
• datetime module to handle non-CF-conform calendars such as Excel dates and decimal years., complementing the package cftime.
• Routines to update files in numpy's npz-format.
• Shuffled-Complex-Evolution algorithm for global optimization sce.
• Median absolute deviation test mad.
• Non-parametric kernel regression kernel_regression.

All (appropriate) routines can handle pandas.Series and pandas.Dataframe now.

Documentation moved from ReadTheDocs to Github.