Skip to main content

Control analysis of SBML models

Project description

controlSBML

controlSBML is a python packag that assists with control engineering of biological systems that are characterized by models in the Systems Biology Markup Language (SBML), a community standard for representing models of biological models, especially chemical reaction networks. controlSBML provides the following:

  • Read SBML models, viewing candidate inputs, and outputs, and running simulations.
  • System identification, including the creation of (SISO) transfer function objects from the python control systems library
  • Creating Antimony simulations of closed loop systems
  • Design of closed loop systems

Examples of usage are in this directory

Installation

pip install controlSBML

To find the current version:

import controlSBML as ctl
ctl.__version__

Version History

  • 1.2.1 5/23/2024
    • Eliminated the save_path feature since it conflicted with usage in colab.
  • 1.2.0 5/22/2024
    • Implemented differential control
    • Extended noise model to include lognormal distribution, offset, and slope
    • Implemented several examples, some of which are based on student projects
    • Two algorithms for fitting. gpz fits the transfer function in order by gain (g), poles (p), zeroes (z). poly fits a polynomial in s to the simulations.
  • 1.1.03 1/20/2024
    • Better error checking
    • API uses parameter names kI, kP, kF
  • 1.1.02 12/27/2023
    • Fix bug in dependencies. Update header documentation.
  • 1.1.01 12/27/2023
    • Complete change in the architecture. Instead of using NonlinearIOSystems in the python control package, controlSBML generates Antimony code to implement staircase functions and closed loops.
    • Creation of a consistent API.
  • 1.0.11 3/1/2023
    • Ensure that state variables are never negative.
  • 1.0.10
    • Fixed bug with unequally spaced times
    • Fixed bug so can start a simulate at a time other than 0 and the correct initial state is obtained.
  • 1.0.9 2/14/2023
    • Use temporary directory for plots created in tests
  • 1.0.8 2/14/2023
    • Avoid error if Jacobian cannot be calculated.
    • Better handling of warnings
  • 1.0.7 2/11/2023
    • Add missing dependency (lmfit)
  • 1.0.6 2/11/2023
    • ControlSBML.makeSISOTransferFunctionBuilder creates a SISOTransferFunctionBuilder object. The plotStaircaseResponse method of SISOTransferFuntionBuilder indicates the controlability of an input for the output. fitTransferFunction fits a transfer function to the outputs produced by a staircase input.
    • plotStaircaseResponse shows effect of a staircase input on outputs
    • Remove cruft from effector_dct
    • Added plot option writefig which takes arguments, True, False, str (path)
  • 1.0.5 1/22/2023
    • Fix bugs in NonlinearIOSystem relating to states and calculations in updfcn.
    • Changes to documentation
  • 1.0.4
    • Fix bug so that makeStateSpace honors the time argument
    • Updated Sphinx documentation
    • Fix bug with version
  • 1.0.3
    • Fix bug with file path in _version
  • 1.0.1
    • src directory contains all pcakages
  • 1.0.0
    • Redefined inputs as species adjustment (positive or negative)
    • ControlSBML.equals has an option to do a "quick check"
    • Deprecated the use of an effector dictionary
  • 0.2.23 12/18/2022
    • Updates for using toml files
  • 0.2.22
    • IOSystemFactor.makeStateFilter creates a vector of filters between 2 systems
    • SISOClosedLoopSystem.makeFullStateController creates multiple filters if kf != 0
  • 0.2.21 5/30/2022
    • NonlinearIOSystem creates a logger.
    • SISOClosedLoopSystem.makeFullStateSystem has option for filters
    • Changed legend of step respoinse plot to use "reference" instead of "step"
  • 0.2.20 5/27/2022
    • Fix bug in SISOClosedLoopSystem.evaluateControllability because scipy didn't handle nan values.
  • 0.2.19 5/27/2022
    • Fix bug in SISOClosedLoopSystem.evaluateControllability because scipy didn't handle nan values.
  • 0.2.18 5/26/2022
    • Fix small bug
  • 0.2.17 5/26/2022
    • Deleted the callback_log implemented in 0.2.14.
  • 0.2.16 5/24/2022
    • Refactored SISOClosedLoopSystem
    • Implemented SISOClosedLoopSystem.makeFullStateController
    • Fixed bug with makePIDController where ki, kd are ineffective.
  • 0.2.15 5/21/2022
    • Fix bug in reverting the semantics of control input to be setting the species as a static.
  • 0.2.14 5/11/2022
    • Provide callback for each manufactured IOsystemFactory
    • Reverted semantics of control input to a NonlinearIOSystem to be setting the value rather than adding or subtracting a value.
  • 0.2.13 5/9/2022
    • SISOClosedLoopSystem provides a way to construct a closed loop system for an SBML model. The system has a PID controller and a filter.
    • IOSysemFactory has a log
  • 0.2.12 5/3/2022
    • IOSystemFactory creates IOSystem objects for Adder, Multiplier, Filter, PIDController, Sinusoid, Constant, Passthru
    • State inputs add to state, not replace the state value.
  • 0.2.11 4/25/2022
    • Fix bug in calculating transfer function that incorrectly considered state
  • 0.2.9 4/19/2022
    • Fluxes can be outputs
    • Construction of transfer function includes atol option for simplification
  • 0.2.8 4/17/2022
    • Added options to plotTrueModel
    • Updated Using ControlSBML with an example of doing feedback
  • 0.2.7 4/11/2022
    • Species can be inputs
    • makeStateSpace, makeTransferFunction have timepoint argument
  • 0.2.6 4/10/2020
    • Default for constructor: is_reduced=False
    • makeTransferFunction
  • 0.2.5 4/8/2022
    • Improve performance by not recalculating Jacobian
    • Fix bugs related to implementation of is_reduced as applied on NonlinearIOSystem
  • 0.2.4 3/31/2024 - Create reduced A matrix
    • mat2Df - fixed bug with printing column names
    • Create reduced A matrix for makeStateSpace so that A is non-singular Default output_names is all floating species
  • 0.2.3, 3/22/2022 - Bug fix for mat2DF
  • 0.2.2, 3/22/2022 - Bug fix
  • 0.2.1, 3/22/2022 - Bug fix
  • 0.2.0, 3/22/2022 - Version for class
    • ppMat - pretty print a matrix
    • plotMat - display a heatmap for a matrix
    • mat2TS - convert a matrix to a timeseries
    • mat2DF - convert a matrix to a dataframe
  • 0.1.6, 3/16/2022
    • Using-Control-SBML.ipynb has an example of doing feedback control design with controlSBML.
    • control.NonlinearIOSystem wraps an SBML model. Can be used in the construction of systems using control.interconnect and in simulations using control.input_output_response. One caveat is that this may work poorly for models implemented as SBML rate rules.
  • 0.1.5, 3/5/2022.
    • More options for plotting and simulations
    • plotBode
    • Inputs are identified by reaction Ids
  • 0.1.3, 2/13/2022. First release.

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

controlsbml-1.2.1.tar.gz (120.1 kB view details)

Uploaded Source

Built Distribution

controlSBML-1.2.1-py3-none-any.whl (119.6 kB view details)

Uploaded Python 3

File details

Details for the file controlsbml-1.2.1.tar.gz.

File metadata

  • Download URL: controlsbml-1.2.1.tar.gz
  • Upload date:
  • Size: 120.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.6

File hashes

Hashes for controlsbml-1.2.1.tar.gz
Algorithm Hash digest
SHA256 7b5f4c761b5fb9b5b304d0edfe085224edcbb2d1af3f246adda3713d0d73db1d
MD5 e580142c275c718e9247b38c50fd3176
BLAKE2b-256 052dae35e4d948d3182dcf31d8679a319971fc89f41c788c1a233d61a0c1c5c4

See more details on using hashes here.

File details

Details for the file controlSBML-1.2.1-py3-none-any.whl.

File metadata

  • Download URL: controlSBML-1.2.1-py3-none-any.whl
  • Upload date:
  • Size: 119.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.6

File hashes

Hashes for controlSBML-1.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 449a5d69e159d4d41c216b4044c29608fd545aea2470cec8172bb9fcae46e388
MD5 9671fadc567bd87767d0a4d6d3c62b24
BLAKE2b-256 d1019a1e8620e78fc21d6acafba5ffc39f944858e3a8ec7827bf3644fef19aa4

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