Skip to main content

Re-Addition Modeler

A python based GUI to model kinetic data that contains re-additions.

Install

  • make sure COPASI is installed (https://copasi.org/Download/)

  • Create and activate a dedicated environment

  • pip install re_add_modeler

  • download and unzip 'python implementation of COPASI': https://drive.google.com/file/d/1cVNLU4SBsz0JhC48MO69wVSLH-RpyIt6/view?usp=sharing

  • OR clone github repo of 'python implementation of COPASI' https://gitlab.com/heingroup/py_copasi

  • create a text file named copasi_path.txt in the folder you want to run the GUI from

  • add the path to the previously downloaded 'python implementation of COPASI' to copasi_path.txt

  • create a folder named output in the folder you want to run the GUI from

  • open cmd in the folder you want to run the GUI from

  • python

  • import re_add_modeler

This should open the GUI. All relevant information will be stored in the previously created output folder sorted by date and time.

How to use

  • drag and drop csv files to be modeled into the csv field

  • for re-additions either manually or from json click the additions button for the correct csv file

  • type out mechanisms the names of the species must match the names in the csv file

  • all non-zero starting concentrations need to be defined in the csv file (for unknow concentrations such as catalyst only give it the initial value and leave all other entries blank)

  • to exclude a k-value from optimization (remove backwards reaction for irreversible processes) add a "$" in front of the known value

  • add complete mechanisms with the "+" button on the top right

  • switch to modeling tab on the top

  • confirm the text box on the left does not indicate an error (it is red)

  • set the species COPASI uses for fitting on the bottom right. Species names must match the names in the csv file separated by a comma (",")

  • set number of generations and population size for COPASI to use on the bottom left

  • click "Run Evaluation"

  • wait for optimization to finish

  • swap to results tab on the top

  • click through data and mechanisms

Known issues

  • only accepts csv files and not excel for now
  • deleting files you want to model on requires a restart of the GUI

Metadata

Release files for re-add-modeler 0.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for re-add-modeler 0.0.2
File Size Uploaded
re_add_modeler-0.0.2.tar.gz 31.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for re-add-modeler 0.0.2
File Interpreter ABI Platform
re_add_modeler-0.0.2-py3-none-any.whl Python 3 none any Details

Total release size: 69.6 kB

Release files / re_add_modeler-0.0.2.tar.gz

Download URL re_add_modeler-0.0.2.tar.gz
Size 31.2 kB
Tags Source
SHA-256 checksum
How to use checksums
4a1fdeec2e396767ba5b48e5d11cebc4f54893582fefe85eb1c17ce45c0c53da
BLAKE2b-256 checksum
How to use checksums
5a5f1981cc375aa949512b9f552445169ca8c791f07709dbe898a8ff1c1747b9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.13

Release files / re_add_modeler-0.0.2-py3-none-any.whl

Download URL re_add_modeler-0.0.2-py3-none-any.whl
Size 38.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
70e343a62c83da76994b2458dc565c5310adf3a86ec7e390df3f8549800ac22f
BLAKE2b-256 checksum
How to use checksums
e6c19dae47396989543d0bd649b29d6703184788d75c935c4854d17eed8beec0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.13

Release history Release notifications | RSS feed

This release

0.0.2 This release

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page