Skip to main content

Physioblocks allows the simulation of dynamical models of physiological systems

Project description

PhysioBlocks

PhysioBlocks allows the simulation of dynamical models of physiological systems.

User Levels

They are several use cases for PhysioBlocks depending on the user profile:

  • Level 1: Configure and run physiological systems simulation (for pre-existing systems)
  • Level 2: Create new systems with existing blocks without writing code
  • Level 3: Write and add new blocks to the library.

Principle

  • A Net (system) is built from Nodes and Blocks connected by those nodes.
  • At each node in the net, connected blocks share Degrees of Freedom (ex: pressure) and send Fluxes that verify Kirchhoff Law.
  • ModelComponents concatenate blocks equations to the global system (if necessary, for modularity purposes within the block)

Interactions

Level 1: Configure and run a simulation : JSON

  • Update the model parameters

Level 2: Create Nets : JSON

  • Declare the nodes, the blocks, and the block - nodes connections

Level 3: Write and add models to the library: Python

  • Declare the quantities to use in the model
  • Write the fluxes and equations

Documentation

Here are the links to the sections of the full documentation:

Quick start

Complete instructions are available in the documentation. This instructions will enable you to launch a reference simulation.

Installation

This project requires a recent version of python installed. Then:

    pip install physioblocks

Configuration

To configure PhysioBlocks Launcher:

# Create an empty folder where you want to store simulations results.
mkdir $LAUNCHER_FOLDER_PATH$

# Configure the folder
python -m physioblocks.launcher.configure -d $LAUNCHER_FOLDER_PATH$ -v

Launch a simulation

With a Launcher folder configured:

# Move to your configured launcher folder
cd $LAUNCHER_FOLDER_PATH$

#  Launch a reference simulation
python -m physioblocks.launcher references/spherical_heart_sim.jsonc -v -t -s QuickStart

# This can take some time.

Results will be available in the $LAUNCHER_FOLDER_PATH$/simulations/QuickStart series folder:

  • the csv file contains the simulation results.
  • the html allows you to visualize the results.
  • the log and json files are here for debug purposes.

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

physioblocks-1.1.2.tar.gz (7.5 MB view details)

Uploaded Source

Built Distribution

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

physioblocks-1.1.2-py3-none-any.whl (165.6 kB view details)

Uploaded Python 3

File details

Details for the file physioblocks-1.1.2.tar.gz.

File metadata

  • Download URL: physioblocks-1.1.2.tar.gz
  • Upload date:
  • Size: 7.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for physioblocks-1.1.2.tar.gz
Algorithm Hash digest
SHA256 6d63a859b0ba8c9d23d0dbd201c2463d9cbaddcf9673e3a001532f7afadd92f0
MD5 da84b8b4a4c027044ff25fcace69932c
BLAKE2b-256 866da7ab29090e1b7c43d291492e06c561bb9c01562f2c7db961fbe96923c0e0

See more details on using hashes here.

File details

Details for the file physioblocks-1.1.2-py3-none-any.whl.

File metadata

  • Download URL: physioblocks-1.1.2-py3-none-any.whl
  • Upload date:
  • Size: 165.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for physioblocks-1.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 2bc0b6c62e43025c408641026fc3eacd549da1c969ed3a38cd7f8823e20acf5c
MD5 d3afafd801bd511a07ad59b2b74ba3ae
BLAKE2b-256 c53b07fb12470a3ba7ebdf83b111c01f3059e36a0e7f4843924fef09d2009e78

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