Metadata-Version: 2.4
Name: teUtils
Version: 3.1
Summary: Utilities for Tellurium
Home-page: https://github.com/sys-bio/teUtils
Author: Herbert M Sauro
Author-email: hsauro@uw.edu
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE.txt
Requires-Dist: tabulate
Requires-Dist: numpy>=1.20
Requires-Dist: tellurium
Requires-Dist: python-libsbml>=5.19.0
Requires-Dist: python-libsbml
Requires-Dist: pandas
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
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# Additional Utilities for Tellurium that we have found useful in our work

Updated to 3.0 New verison updates matplotlib supoprt, fixes some typos in docs

Updated to 2.9. New version adds 'ei*(' terms to mass actions rate laws, eg

```S1 -> S2; e1*(k1*S1 - k2*S2)```

This makes it easier to compute control coefficients with repect to 'e'

Also added a new mass-action rate of the form:

```v = k1*A(1 - (B/A)/Keq1)```

These can be generated using the call:

```model = teUtils.buildNetworks.getLinearChain(10, rateLawType="ModifiedMassAction")```

Useful if you want to more easily control the equilbrium constant for a reaction.

This repo includes a number of useful utilities for Tellurium users. These include:

# Installation
You can install teUtils using pip:

``pip install teUtils``

# Documenation

The documentation can be found at: http://teUtils.readthedocs.io/en/latest/

## buildNetworks
This modules provides two methods to build a linear chain of reactions using either mass-action or Michaelis-Menten
kinetics or a random network using uniuni, unibi, biuni or bibi mass-action governed reactions. 

## odePrint
This provides a number of methods to convert SBML into the equations representing the model. 
   
## plotting
This modules contains a variety of additional plotting methods, include 3D, heatmaps for control coefficients, ascii plots, phase plots and more.

## prettyTabular
This modules provides two methods to display fluxes and concentrations in a neat tabular format using jsut ascii characters.

## fileUtils
File utilties that simply some operation whch for some reason are not available in Python

## parameterScanning
This package only has one method currently which is a single method to make time course parameter scanning easier

