A comprehensive package for the analysis of kinetic data.
Project description
KiMoPack
KiMoPack is a project for the handling of spectral data measure at multiple time-points. The current design is optimised for the use with optical transient absorption data, but it has been successfully adapted for the use with transient x-ray emission and spectro-electro chemistry data.
It focuses on the main tasks an experimentator has: Loading and shaping of experiments, plotting of experiments, comparing of experiments, analysing experiments with fast and/or advanced fitting routines and saving/exporting/presenting the results.
For typical use a series of juypter notebooks are provided that guide through the a number of different use scenarios, and are suggesting the parameter that are typically set.
Installation
The basis of the program is a module called “plot_func.py” that contains all the necessary functions and classes. We recommend to use a package manager to install the program.
Install using “pip”:
$ pip install KiMoPack
Upgrade if already installed:
$ pip install KiMoPack -U
Install and update using “conda” from the channel erdzeichen:
$ conda install -c erdzeichen kimopack
Hint: the pip version is usually more recent than the conda version The files can also be downloaded from the github directory https://github.com/erdzeichen/KiMoPack or zenodo (see below)
In general it is a good idea to create a local environment to install files in python if you are using python for many tasks. In a local environment only the packages that are needed are installed, which usually avoids that conflicts can appear. It is very easy to do that.
Under Windows: open the anaconda command prompt or power shell (type anaconda under windows start) Under Linuxs: open a console
$ conda create --name KiMoPack
$ conda activate KiMoPack
$ conda install pytables
If you are working with a very old installation it is usually a good idea to also install an updated python
$ conda create --name KiMoPack python=3.10 ipython jupyterlab jupyter
$ conda activate KiMoPack
$ conda install pytables
into this environment KiMoPack can then be installed. We also recommend (optional) to install python-pptx to create power point slides and nbopen (which allows to automatically open a local server) into the environments. If one of the installs complains (error) that the user does not has sufficient rights, this installation can be done attaching “–user” to the following commands
pip install kimopack
pip install python-pptx
pip install nbopen
Finally, while still in the environement, activate nbopen. There are different commands for Windows/Linux/Mac By doing that in the local environment will open and activate the environment. If you left the environement already you can always go back with “conda activate KiMoPack”
python -m nbopen.install_win
python3 -m nbopen.install_xdg
Clone the repository and run ./osx-install.sh
- Error: pytables:
in some versions I have been running in a problem with pytables when loading saved data. Using the conda forge version solved this problem for me
conda install -c conda-forge pytables
Best usage
While KiMoPack is a python library, we facilitate its use with Jupyter notebooks. For the typical analysis tasks we have developed a series of Notebooks that guide through the tasks.n These notebooks can be downloaded from https://github.com/erdzeichen/KiMoPack/tree/main/Workflow_tools or by command line.
To do that start any console (under windows e.g. type “cmd” and hit enter). In the console you then start python by typing “python” and hit enter, lastly you import Kimopack and run a function that downloads the files for you by typing “import KiMoPack; KiMoPack.download_all()” This downloads the notebooks and tutorials from github for you. If you instead use “import KiMoPack; KiMoPack.download_notebooks()” then only the workflow tools are downloaded. Please copy one of these notebooks into your data analysis folder and rename them to create a analysis log of your session. For more information please see the publication https://doi.org/10.1021/acs.jpca.2c00907, the tutorial videos, or the tutorial notebooks under https://github.com/erdzeichen/KiMoPack/tree/main/Tutorial_Notebooks_for_local_use.
Citation
We have written and submitted a paper introducing the toolbox under https://doi.org/10.1021/acs.jpca.2c00907
Links
Publication: https://pubs.acs.org/doi/10.1021/acs.jpca.2c00907
Documentation: https://kimopack.readthedocs.io/
PyPI Releases: https://pypi.org/project/KiMoPack/
Source Code: https://github.com/erdzeichen/KiMoPack
Issue Tracker: https://github.com/erdzeichen/KiMoPack/issues
Website: https://www.chemphys.lu.se/research/projects/kimopack/
Tutorial videos: https://www.youtube.com/channel/UCmhiK0P9wXXjs_PJaitx8BQ
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