pykinetic 0.1.0

A python library and command line apps to write microkinetic models for chemistry

Pykinetic is a project that aims to facilitate the automation and generation of kinetic and microkinetic models. Pykinetic acts as an intermediate layer between the user and the mathematical model that is then simulated to obtain the kinetic data. This functionality can be done either through the use of the pykinetic python library or through the use of the command line apps: “pykinetic-model.py” and “pykinetic-scan.py”. The minimal source code to run the simulation is the output of pykinetic and currently python and c++ are supported. Compiling and executing that code leads to the simulation of the chemical system.

• Getting Started

  • Prerequisites

  • Installing the dependencies

  • Installing pykinetic

  • Running the tests

  • Uninstalling pykinetic

• Developed with

• Examples

• Authors

• License

Getting Started

These instructions will get you a copy of the project up and running on your local machine.

Prerequisites

• python >= 3.6 (3.7.3 or higher recommended)

• python library: setuptools

• python library: numpy (optional, needed to run the generated python scripts)

• python library: scipy (optional, needed to run the generated python scripts)

• c++ library: boost (optional, needed to run the generated c++ scripts)

  Note: proper documentation installation of the c++ library is being currently being reviewed.

Installing the dependencies

python3.7 installation in Ubuntu 18.04 LTS

$ sudo apt-get update
$ sudo apt-get install python3.7 python3.7-dev

If for any reason it is not reachable:

$ sudo add-apt-repository ppa:deadsnakes/ppa
$ sudo apt-get update
$ sudo apt-get install python3.7 python3.7-dev

Now you can skip the next step if you don’t want to set up a virtual environment the lines below correspond to python3.7 but can be also applied to python3.6 or higher (Remember to change “my_venv” for the actual path of the directory where you want the virtual environment)

$ sudo apt-get install python3.7-venv
$ python3.7 -m venv my_venv
$ source my_venv/bin/activate

In the case of creating a virtual environment and running the previous “source” command, anytime you write “python” it will act as an alias for “python3.7” or whichever python executable you used for the virtual environment. (To leave the virtual environment run the “deactivate” command at anytime)

If you have not created a virtual environment, all the following commands must explicitly use the python executable in which you are going to install the the package. Now we install the python default installer pip in our virtual environment

$ python -m pip install pip
$ python -m pip install --upgrade pip
$ python -m pip install setuptools

If it proceeded without any errors (pip and setuptools should already be installed) otherwise please check the pip documentation

Now to install the optional dependencies (Skip if you do not want them):

$ python -m pip install numpy scipy
$ sudo apt-get install libboost-dev

Installing pykinetic

Get the source code from github through git and install it.

$ git clone https://github.com/maserasgroup-repo/pykinetic.git pykinetic
$ python -m pip install pykinetic/

If you do not have git or do prefer to download manually the source code as a .zip or .tar.gz do it install it.

$ python -m pip install pykinetic-0.1.0.tar.gz

Note: If you prefer to unpack it you can do it but it is not needed

Running the tests

After installing you should be able to run the tests:

$ python -m unittest -v pykinetic.tests

Uninstalling pykinetic

$ python -m pip uninstall pykinetic

Developed with

• python 3.7.3

• Ubuntu 16.04 LTS and Ubuntu 18.04 LTS

Examples

Please open the Examples.rst file in github to visualize the basic usage examples or read the documentation.

Authors

List of main developers and contact emails:

• Raúl Pérez-Soto [ ORCID , Github , email ]

• Sergio Pablo-García [ ORCID , Github , email]

• María Besora [ ORCID , Github , email ]

• Feliu Maseras [ ORCID , Github , email]

License

pykinetic is freely available under an MIT License