用于计算液相色谱中线性溶剂强度参数的python包_.zip

# PyLSS PyLSS [1] is a python package useful to calculate linear solvent strength parameters [2] in Liquid Chromatography. PyLSS is able to compute: - LSS parameters (log kw and S) - Build and plot chromatograms from experimental/predicted retention times - A graphical user interface facilitate you to make models and easly estimate LSS parameters  PyLSS include a personalised algorithm to optimise and calculate the LSS parameters in a fast manner. References: ---------- [1] Prediction of retention time in reversed-phase liquid chromatography as a tool for steroid identification G.M. Randazzo, D. Tonoli, S. Hambye, D. Guillarme, F. Jeanneret, A. Nurisso, L. Goracci, J. Boccard, Prof. S. Rudaz Analytica Chimica Acta 2016 doi:10.1016/j.aca.2016.02.014 [2] High-Performance Gradient Elution: The Practical Application of the Linear-Solvent-Strength Model Lloyd R. Snyder, John W. Dolan ISBN: 978-0-471-70646-5 496 pages January 2007 License ============ PyLSS is distributed under LGPLv3 license, this means that: - you can use this library where you want doing what you want. - you can modify this library and commit changes. - you can not use this library inside a commercial software. To know more in details how the licens work please read the file "LICENSE" or go to "http://www.gnu.org/licenses/lgpl-3.0.html" PyLSS is currently property of Giuseppe Marco Randazzo which is also the current package maintainer. Voluntary contributions are welcome. Dependencies ============ The required dependencies to use PyLSS are: - python version 2 or 3 - numpy - scipy - matplotlib - PyQt5 to use the GUI Install ======= To install for all users on Unix/Linux/OSX/Windows: python setup.py install To use the GUI: - install PyQt5: pip install pyqt5 - run python3 pylss-guy.py to visualize the GUI. How to use the command line? ======= See the examples directory. Inside you can find a script runtest.sh which show a simple use of the library to calculate the LSS parameters. If you check also at the bin directory you can find some usefull executables to run your calculations. Development =========== GIT --- You can check the latest sources with the command:: git clone https://github.com/gmrandazzo/PyLSS.git Contributing ------------ To contribute you can fork the project, or if you have already forked the project update to the latest version of PyLSS, make the changes and open a Pull Request. However some recomendation before open a Pull Request: * Be sure that your code it's working. * Use pylint to check your code. The Global Evaluation rate must be >= 9.0 * Comment your code with Parameters, Attribute, Return, Notes and References. * An example is necessary. Probabily your code will be integrated but some quality and goals have to keep in mind.