Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

blobmodel

Package Overview
Dependencies
Maintainers
2
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

blobmodel

Two dimensional model of propagating blobs

  • 1.0.1
  • PyPI
  • Socket score

Maintainers
2

blobmodel

Python version Pypi codecov Tests Checked with mypy Code style: black License: MIT Documentation Status

This package provides realizations of advecting and dissipating blobs in up to two dimensions.

All blob parameters can be choosen freely, and multiple blob shapes are implemented. Originally, the model is developed for studying the scrape-off layer of fusion experiments, but it can be applicable to many 1d or 2d systems. See the blobmodel documentation for further details.

Examples for one and two dimensions are shown below:

1D 2D
Density evolution Density evolution

Installation

The package is published to PyPI and can be installed with

pip install blobmodel

If you want the development version you must first clone the repo to your local machine, then install the project in development mode:

git clone https://github.com/uit-cosmo/blobmodel.git
cd blobmodel
python -m pip install -e .

Usage

Create a grid on which the blobs are discretized using the Model class. The make_realization() method computes the output as an xarray dataset which can also be written out as a netcdf file if the argument file_name is specified. A simple example is shown below:

from blobmodel import Model, show_model

bm = Model(Nx=200, Ny=100, Lx=10, Ly=10, dt=0.1, T=20, blob_shape='gauss',num_blobs=100)

ds = bm.make_realization(file_name="example.nc")

The data can be shown as an animation using the show_model function:

show_model(ds)

You can specify the blob parameters with a BlobFactory class. The DefaultBlobFactory class has some of the most common distribution functions implemented. An example would look like this:

from blobmodel import Model, DefaultBlobFactory

# use DefaultBlobFactory to define distribution functions of random variables
bf = DefaultBlobFactory(A_dist="exp", wx_dist="uniform", vx_dist="deg", vy_dist="normal")

# pass on bf when creating the Model
tmp = Model(
    Nx=100,
    Ny=1,
    Lx=10,
    Ly=0,
    dt=1,
    T=1000,
    blob_shape="exp",
    t_drain=2,
    periodic_y=False,
    num_blobs=10000,
    blob_factory=bf,
)

Alternatively, you can specify all blob parameters exactly as you want by writing your own class which inherits from BlobFactory. See examples/custom_blobfactory.py as an example or take a look at the blobmodel documentation.

Contributing

Feel free to raise issues about anything. Contributions through pull requests are also very welcome. Please take a look at our Contributor guide for further details.

FAQs


Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc