Skip to main content

Generalized Kinetic Modeler: A Python package for modeling arbitrary kinetic schemes.

Project description

GeKiM (Generalized Kinetic Modeler)

Description

GeKiM (Generalized Kinetic Modeler) is a Python package designed for creating, interpreting, and modeling arbitrary kinetic schemes. Schemes are defined by the user in a dictionary of species and transitions, which is used to initialize an instance of the NState class. Choose (or make) and initialize a simulator for the instance and run it. Field-specific practices are found in gekim/fields.

Installation

With pip:

pip install gekim

Or directly from the source code (recommended):

git clone https://github.com/kghaby/GeKiM.git
cd GeKiM
pip install .

Usage

Here is a basic example of how to use GeKiM to create and simulate a kinetic system:

import gekim as gk
from gekim.fields.bio.enzyme.inhib import irrev as ii 

# Define your kinetic scheme in a configuration dictionary
concI0,concE0 = 100,1
scheme = {
    'species': {
        "I": {"y0": concI0, "label": "I"},
        "E": {"y0": concE0, "label": "E"},
        "EI": {"y0": 0, "label": "EI"},
    },    
    'transitions': {
        "kon": {"k": 0.01, "source": ["2E","I"], "target": ["EI"]},
        "koff": {"k": 0.1, "source": ["EI"], "target": ["2E","I"]},
    }
}

# Initialize a system with your schematic dictionary
system = gk.schemes.NState(scheme,quiet=False)

# Choose a simulator and go. In this example we're doing a deterministic 
# simulation of the concentrations of each species over time.
# Note that `system.simulator() = gk.simulators.ODESolver(system)` may be more doc-hint friendly
system.set_simulator(gk.simulators.ODESolver)
system.simulator.simulate() 

# Fit the data to experimental models to extract mock-experimental measurements
final_state = system.species["EI"].simout["y"]
all_bound = system.sum_species_simout(blacklist=["E","I"])

fit_output = ii.kobs_uplim_fit_to_occ_final_wrt_t(
    t,final_state,nondefault_params={"Etot":{"value":concE0,"vary":False}})

For more detailed examples, please refer to the examples directory.

Documentation

Documentation and example notebook(s) are pending.

Contributing

If you have suggestions or want to contribute code, please feel free to open an issue or a pull request.

License

GeKiM is licensed under the GPL-3.0.

Contact

kyleghaby@gmail.com

Project details


Download files

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

Source Distribution

gekim-0.5.4.tar.gz (49.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

GeKiM-0.5.4-py3-none-any.whl (52.0 kB view details)

Uploaded Python 3

File details

Details for the file gekim-0.5.4.tar.gz.

File metadata

  • Download URL: gekim-0.5.4.tar.gz
  • Upload date:
  • Size: 49.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for gekim-0.5.4.tar.gz
Algorithm Hash digest
SHA256 7e104039fed412b45917b7fc72c54b3d02065bc4b05b241fa3f4128e9b544d4b
MD5 b79079057c200c9d9583cd21b948a2b4
BLAKE2b-256 850c812a768f034bb233cc638b14e9746cc0ca98b049e68c71131066777ef3c1

See more details on using hashes here.

File details

Details for the file GeKiM-0.5.4-py3-none-any.whl.

File metadata

  • Download URL: GeKiM-0.5.4-py3-none-any.whl
  • Upload date:
  • Size: 52.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for GeKiM-0.5.4-py3-none-any.whl
Algorithm Hash digest
SHA256 f8aae2fb28c38206b8112c979c69536f6f801829826f0e3f5185310c5c3b7820
MD5 8a68b106bab22652d3a2146e4bb3971b
BLAKE2b-256 5e4829ee337c97cdb63a1757af51c53ff9df43efdb943211a57de0cd980bb826

See more details on using hashes here.

Supported by

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