Skip to main content

A comprehensive package for the analysis of kinetic data.

Project description

Documentation Status License: GPL v3 https://anaconda.org/erdzeichen/kimopack/badges/version.svg https://badge.fury.io/py/KiMoPack.svg https://anaconda.org/erdzeichen/kimopack/badges/latest_release_date.svg https://colab.research.google.com/assets/colab-badge.svg https://mybinder.org/badge_logo.svg https://zenodo.org/badge/400527965.svg

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

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)

These commands are installing only KiMoPack and the absolutely needed dependencies. However, there are several modules that work better if additional packages are installed. In general one should try to install all packages at the same time. Additional packages that I generally recommend are h5py and tables (for saving files), python-pptx (for saving power point slides) and keyboard (Window only, for interrupting the fits). Quite useful is also nbopen that allows you to double click on the notebook files. nbopen requires an activation at the end.

(leave away keyboard for Linux!) .. code-block:: text

$ pip install KiMoPack h5py tables nbopen python-pptx

(windows) python -m nbopen.install_win (Linux) python3 -m nbopen.install_xdg (MacOS) Clone the repository and run ./osx-install.sh

Upgrade if already installed:

$ pip install KiMoPack -U

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 kimokack
$ pip install KiMoPack h5py tables keyboard nbopen python-pptx

Or if you also want make sure to have a later version of python

$ conda create --name kimopack python=3.11 ipython jupyterlab jupyter
$ conda activate kimopack
$ pip install KiMoPack h5py tables keyboard nbopen python-pptx

Error: insufficient rights: If one of the installs complains (error) that the user does not has sufficient rights, this installation can be done attaching “–user”

$ conda create --name kimoPack
$ conda activate kimokack
$ pip install KiMoPack h5py tables keyboard nbopen python-pptx --user
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.

You can try either of these “lazy” oneliners

ipython -c "import KiMoPack; KiMoPack.download_notebooks()"
python -c "import KiMoPack; KiMoPack.download_notebooks()"
python3 -c "import KiMoPack; KiMoPack.download_notebooks()"

If none of these work then 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 published a paper introducing the toolbox under https://doi.org/10.1021/acs.jpca.2c00907

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kimopack-7.11.2.tar.gz (49.1 MB view details)

Uploaded Source

Built Distribution

KiMoPack-7.11.2-py3-none-any.whl (111.5 kB view details)

Uploaded Python 3

File details

Details for the file kimopack-7.11.2.tar.gz.

File metadata

  • Download URL: kimopack-7.11.2.tar.gz
  • Upload date:
  • Size: 49.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for kimopack-7.11.2.tar.gz
Algorithm Hash digest
SHA256 5ff2803da26529bb74642d25ff1b2b2bdfcfb34effd7ef9fe9f7a4784b74d704
MD5 19cbd58c9250a46dd7c7dfc9710e280d
BLAKE2b-256 edfc642f22c19375be08b27ee7f5aff7c0a0d9e707d583c4d76869f5ae73fdc2

See more details on using hashes here.

File details

Details for the file KiMoPack-7.11.2-py3-none-any.whl.

File metadata

  • Download URL: KiMoPack-7.11.2-py3-none-any.whl
  • Upload date:
  • Size: 111.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for KiMoPack-7.11.2-py3-none-any.whl
Algorithm Hash digest
SHA256 fda1f9388f37cb92dcfc5e19b4fc10276263a7b147b32492756eedab6d209425
MD5 64d215364e5078e420bc43bd31762238
BLAKE2b-256 84241a0be3285794714be919d5b635a253af82751ea956946345072f7df496a8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page