# <img src="https://raw.githubusercontent.com/open-atmos/PySDM/main/docs/logos/pysdm_logo.png" width=100 height=146 alt="pysdm logo">
[](https://www.python.org/)
[](https://numba.pydata.org)
[](https://pypi.org/project/ThrustRTC/)
[](https://en.wikipedia.org/wiki/Linux)
[](https://en.wikipedia.org/wiki/macOS)
[](https://en.wikipedia.org/wiki/Windows)
[](https://jupyter.org/)
[](https://github.com/open-atmos/PySDM/graphs/commit-activity)
[](https://www.openhub.net/p/atmos-cloud-sim-uj-PySDM)
[](https://joss.theoj.org/papers/62cad07440b941f73f57d187df1aa6e9)
[](https://zenodo.org/badge/latestdoi/199064632)
[](https://www.fnp.org.pl/en/)
[](https://www.ncn.gov.pl/?language=en)
[](https://asr.science.energy.gov/)
[](https://www.gnu.org/licenses/gpl-3.0.html)
[](https://github.com/open-atmos/PySDM/actions)
[](https://ci.appveyor.com/project/slayoo/pysdm/branch/main)
[](https://app.codecov.io/gh/open-atmos/PySDM)
[](https://pypi.org/project/PySDM)
[](https://open-atmos.github.io/PySDM/)
PySDM is a package for simulating the dynamics of population of particles.
It is intended to serve as a building block for simulation systems modelling
fluid flows involving a dispersed phase,
with PySDM being responsible for representation of the dispersed phase.
Currently, the development is focused on atmospheric cloud physics
applications, in particular on modelling the dynamics of particles immersed in moist air
using the particle-based (a.k.a. super-droplet) approach
to represent aerosol/cloud/rain microphysics.
The package features a Pythonic high-performance implementation of the
Super-Droplet Method (SDM) Monte-Carlo algorithm for representing collisional growth
([Shima et al. 2009](https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.441)), hence the name.
PySDM documentation is maintained at: [https://open-atmos.github.io/PySDM](https://open-atmos.github.io/PySDM)
There is a growing set of [example Jupyter notebooks](https://open-atmos.github.io/PySDM/PySDM_examples.html) exemplifying how to perform
various types of calculations and simulations using PySDM.
Most of the example notebooks reproduce results and plot from literature, see below for
a list of examples and links to the notebooks (which can be either executed or viewed
"in the cloud").
There are also a growing set of [tutorials](https://github.com/open-atmos/PySDM/tree/main/tutorials), also in the form of Jupyter notebooks.
These tutorials are intended for teaching purposes and include short explanations of cloud microphysical
concepts paired with widgets for running interactive simulations using PySDM.
Each tutorial also comes with a set of questions at the end that can be used as homework problems.
Like the examples, these tutorials can be executed or viewed "in the cloud" making it an especially
easy way for students to get started.
PySDM has two alternative parallel number-crunching backends
available: multi-threaded CPU backend based on [Numba](http://numba.pydata.org/)
and GPU-resident backend built on top of [ThrustRTC](https://pypi.org/project/ThrustRTC/).
The [`Numba`](https://open-atmos.github.io/PySDM/PySDM/backends/numba.html) backend (aliased ``CPU``) features multi-threaded parallelism for
multi-core CPUs, it uses the just-in-time compilation technique based on the LLVM infrastructure.
The [`ThrustRTC`](https://open-atmos.github.io/PySDM/PySDM/backends/thrust_rtc.html) backend (aliased ``GPU``) offers GPU-resident operation of PySDM
leveraging the [SIMT](https://en.wikipedia.org/wiki/Single_instruction,_multiple_threads)
parallelisation model.
Using the ``GPU`` backend requires nVidia hardware and [CUDA driver](https://developer.nvidia.com/cuda-downloads).
For an overview of PySDM features (and the preferred way to cite PySDM in papers), please refer to our JOSS papers:
- [Bartman et al. 2022](https://doi.org/10.21105/joss.03219) (PySDM v1).
- [de Jong, Singer et al. 2023](https://doi.org/10.21105/joss.04968) (PySDM v2).
PySDM includes an extension of the SDM scheme to represent collisional breakup described in [de Jong, Mackay et al. 2023](10.5194/gmd-16-4193-2023).
For a list of talks and other materials on PySDM as well as a list of published papers featuring PySDM simulations, see the [project wiki](https://github.com/open-atmos/PySDM/wiki).
## Dependencies and Installation
PySDM dependencies are: [Numpy](https://numpy.org/), [Numba](http://numba.pydata.org/), [SciPy](https://scipy.org/),
[Pint](https://pint.readthedocs.io/), [chempy](https://pypi.org/project/chempy/),
[pyevtk](https://pypi.org/project/pyevtk/),
[ThrustRTC](https://fynv.github.io/ThrustRTC/) and [CURandRTC](https://github.com/fynv/CURandRTC).
To install PySDM using ``pip``, use: ``pip install PySDM``
(or ``pip install git+https://github.com/open-atmos/PySDM.git`` to get updates
beyond the latest release).
Conda users may use ``pip`` as well, see the [Installing non-conda packages](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-pkgs.html#installing-non-conda-packages) section in the conda docs. Dependencies of PySDM are available at the following conda channels:
- numba: [numba](https://anaconda.org/numba/numba)
- conda-forge: [pyevtk](https://anaconda.org/conda-forge/pyevtk), [pint](https://anaconda.org/conda-forge/pint) and []()
- fyplus: [ThrustRTC](https://anaconda.org/fyplus/thrustrtc), [CURandRTC](https://anaconda.org/fyplus/curandrtc)
- bjodah: [chempy](https://anaconda.org/bjodah/chempy)
- nvidia: [cudatoolkit](https://anaconda.org/nvidia/cudatoolkit)
For development purposes, we suggest cloning the repository and installing it using ``pip -e``.
Test-time dependencies can be installed with ``pip -e .[tests]``.
PySDM examples constitute the [``PySDM-examples``](https://github.com/open-atmos/PySDM/blob/main/examples) package.
The examples have additional dependencies listed in [``PySDM_examples`` package ``setup.py``](https://github.com/open-atmos/PySDM/blob/main/examples/setup.py) file.
Running the example Jupyter notebooks requires the ``PySDM_examples`` package to be installed.
The suggested install and launch steps are:
```
git clone https://github.com/open-atmos/PySDM.git
pip install -e PySDM
pip install -e PySDM/examples
jupyter-notebook PySDM/examples/PySDM_examples
```
Alternatively, one can also install the examples package from pypi.org by
using ``pip install PySDM-examples`` (note that this does not apply to notebooks itself,
only the supporting .py files).
## Contributing, reporting issues, seeking support
#### Our technologicial stack:
[](https://www.python.org/)
[](https://numba.pydata.org)
[](https://llvm.org)
[](https://pypi.org/project/ThrustRTC/)
[](https://numpy.org/)
[](https://pytest.org/)
[](https://colab.research.google.com/)
[](https://codecov.io/)
[](https://pypi.org/)
[](https://github.com/features/actions)
[](https://jupyter.org/)
[](https:///)
Submitting new code to the project, please preferably use [GitHub pull requests](https://github.com/open-atmos/PySDM/pulls) - it helps to keep record of code authorship,
track and archive the code review workflow and allows to benefit
from the continuous integration setup which automates execution of tests
with the newly added code.
Code contributions are assumed to imply transfer of copyright.
Should there be a need to make an exception, please indicate it when creating
a pull request or contributing code in any other way. In any case,
the license of the contributed code must be compatible with GPL v3.
Developing the code, we follow [The Way of Python](https://www.python.org/dev/peps/pep-0020/) and
the [KISS principle](https://en.wikipedia.org/wiki/KISS_principle).
The codebase has greatly benefited from [PyCharm code inspections](https://www.jetbrains.com/help/pycharm/code-inspection.html)
and [Pylint](https://pylint.org), [Black](https://black.readthedocs.io/en/stable/) and [isort](https://pycqa.github.io/isort/)
code analysis (which are all part of the CI workflows).
We also use [pre-commit hooks](https://pre-commit.com).
In our case, the hooks modify files and re-format them.
The pre-commit hooks can be run locally, and then the resultant changes need to be staged before committing.
To set up the hooks locally, install pre-commit via `pip install pre-commit` and
set up the git hooks via `pre-commit install` (this needs to be done every time you clone the project).
To run all pre-commit hooks, run `pre-commit run --all-files`.
The `.pre-commit-config.yaml` file can be modified in case new hooks are to be added or
existing ones need to be altered.
Further hints addressed at PySDM developers are maintained in the [open-atmos/python-dev-hints Wiki](https://github.com/open-atmos/python-dev-hints/wiki)
and in [PySDM HOWTOs](https://github.com/open-atmos/PySDM/tree/main/examples/PySDM_examples/_HOWTOS).
Issues regarding any incorrect, unintuitive or undocumented bahaviour of
PySDM are best to be reported on the [GitHub issue tracker](https://github.com/open-atmos/PySDM/issues/new).
Feature requests are recorded in the "Ideas..." [PySDM wiki page](https://github.com/open-atmos/PySDM/wiki/Ideas-for-new-features-and-examples).
We encourage to use the [GitHub Discussions](https://github.com/open-atmos/PySDM/discussions) feature
(rather than the issue tracker) for seeking support in understanding, using and extending PySDM code.
We look forward to your contributions and feedback.
## Licensing:
copyright: [Jagiellonian University](https://en.uj.edu.pl/en) (2019-2023) & [AGH University of Krakow](https://agh.edu.pl/en) (2023-...)
licence: [GPL v3](https://www.gnu.org/licenses/gpl-3.0.html)
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"description": "# <img src=\"https://raw.githubusercontent.com/open-atmos/PySDM/main/docs/logos/pysdm_logo.png\" width=100 height=146 alt=\"pysdm logo\">\n\n[](https://www.python.org/)\n[](https://numba.pydata.org)\n[](https://pypi.org/project/ThrustRTC/)\n[](https://en.wikipedia.org/wiki/Linux)\n[](https://en.wikipedia.org/wiki/macOS)\n[](https://en.wikipedia.org/wiki/Windows)\n[](https://jupyter.org/)\n[](https://github.com/open-atmos/PySDM/graphs/commit-activity)\n[](https://www.openhub.net/p/atmos-cloud-sim-uj-PySDM)\n[](https://joss.theoj.org/papers/62cad07440b941f73f57d187df1aa6e9)\n[](https://zenodo.org/badge/latestdoi/199064632) \n[](https://www.fnp.org.pl/en/)\n[](https://www.ncn.gov.pl/?language=en)\n[](https://asr.science.energy.gov/)\n\n[](https://www.gnu.org/licenses/gpl-3.0.html)\n\n[](https://github.com/open-atmos/PySDM/actions)\n[](https://ci.appveyor.com/project/slayoo/pysdm/branch/main)\n[](https://app.codecov.io/gh/open-atmos/PySDM) \n[](https://pypi.org/project/PySDM)\n[](https://open-atmos.github.io/PySDM/)\n\nPySDM is a package for simulating the dynamics of population of particles. \nIt is intended to serve as a building block for simulation systems modelling\n fluid flows involving a dispersed phase,\n with PySDM being responsible for representation of the dispersed phase.\nCurrently, the development is focused on atmospheric cloud physics\n applications, in particular on modelling the dynamics of particles immersed in moist air \n using the particle-based (a.k.a. super-droplet) approach \n to represent aerosol/cloud/rain microphysics.\nThe package features a Pythonic high-performance implementation of the \n Super-Droplet Method (SDM) Monte-Carlo algorithm for representing collisional growth \n ([Shima et al. 2009](https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.441)), hence the name. \n\nPySDM documentation is maintained at: [https://open-atmos.github.io/PySDM](https://open-atmos.github.io/PySDM) \n\nThere is a growing set of [example Jupyter notebooks](https://open-atmos.github.io/PySDM/PySDM_examples.html) exemplifying how to perform \n various types of calculations and simulations using PySDM.\nMost of the example notebooks reproduce results and plot from literature, see below for \n a list of examples and links to the notebooks (which can be either executed or viewed \n \"in the cloud\").\n\nThere are also a growing set of [tutorials](https://github.com/open-atmos/PySDM/tree/main/tutorials), also in the form of Jupyter notebooks.\nThese tutorials are intended for teaching purposes and include short explanations of cloud microphysical \n concepts paired with widgets for running interactive simulations using PySDM.\nEach tutorial also comes with a set of questions at the end that can be used as homework problems.\nLike the examples, these tutorials can be executed or viewed \"in the cloud\" making it an especially \n easy way for students to get started.\n\nPySDM has two alternative parallel number-crunching backends \n available: multi-threaded CPU backend based on [Numba](http://numba.pydata.org/) \n and GPU-resident backend built on top of [ThrustRTC](https://pypi.org/project/ThrustRTC/).\nThe [`Numba`](https://open-atmos.github.io/PySDM/PySDM/backends/numba.html) backend (aliased ``CPU``) features multi-threaded parallelism for \n multi-core CPUs, it uses the just-in-time compilation technique based on the LLVM infrastructure.\nThe [`ThrustRTC`](https://open-atmos.github.io/PySDM/PySDM/backends/thrust_rtc.html) backend (aliased ``GPU``) offers GPU-resident operation of PySDM\n leveraging the [SIMT](https://en.wikipedia.org/wiki/Single_instruction,_multiple_threads) \n parallelisation model. \nUsing the ``GPU`` backend requires nVidia hardware and [CUDA driver](https://developer.nvidia.com/cuda-downloads).\n\nFor an overview of PySDM features (and the preferred way to cite PySDM in papers), please refer to our JOSS papers:\n- [Bartman et al. 2022](https://doi.org/10.21105/joss.03219) (PySDM v1).\n- [de Jong, Singer et al. 2023](https://doi.org/10.21105/joss.04968) (PySDM v2).\n \nPySDM includes an extension of the SDM scheme to represent collisional breakup described in [de Jong, Mackay et al. 2023](10.5194/gmd-16-4193-2023). \nFor a list of talks and other materials on PySDM as well as a list of published papers featuring PySDM simulations, see the [project wiki](https://github.com/open-atmos/PySDM/wiki).\n\n## Dependencies and Installation\n\nPySDM dependencies are: [Numpy](https://numpy.org/), [Numba](http://numba.pydata.org/), [SciPy](https://scipy.org/), \n[Pint](https://pint.readthedocs.io/), [chempy](https://pypi.org/project/chempy/), \n[pyevtk](https://pypi.org/project/pyevtk/),\n[ThrustRTC](https://fynv.github.io/ThrustRTC/) and [CURandRTC](https://github.com/fynv/CURandRTC).\n\nTo install PySDM using ``pip``, use: ``pip install PySDM`` \n(or ``pip install git+https://github.com/open-atmos/PySDM.git`` to get updates\nbeyond the latest release).\n\nConda users may use ``pip`` as well, see the [Installing non-conda packages](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-pkgs.html#installing-non-conda-packages) section in the conda docs. Dependencies of PySDM are available at the following conda channels:\n- numba: [numba](https://anaconda.org/numba/numba)\n- conda-forge: [pyevtk](https://anaconda.org/conda-forge/pyevtk), [pint](https://anaconda.org/conda-forge/pint) and []()\n- fyplus: [ThrustRTC](https://anaconda.org/fyplus/thrustrtc), [CURandRTC](https://anaconda.org/fyplus/curandrtc)\n- bjodah: [chempy](https://anaconda.org/bjodah/chempy)\n- nvidia: [cudatoolkit](https://anaconda.org/nvidia/cudatoolkit)\n\nFor development purposes, we suggest cloning the repository and installing it using ``pip -e``.\nTest-time dependencies can be installed with ``pip -e .[tests]``.\n\nPySDM examples constitute the [``PySDM-examples``](https://github.com/open-atmos/PySDM/blob/main/examples) package.\nThe examples have additional dependencies listed in [``PySDM_examples`` package ``setup.py``](https://github.com/open-atmos/PySDM/blob/main/examples/setup.py) file.\nRunning the example Jupyter notebooks requires the ``PySDM_examples`` package to be installed.\nThe suggested install and launch steps are:\n```\ngit clone https://github.com/open-atmos/PySDM.git\npip install -e PySDM\npip install -e PySDM/examples\njupyter-notebook PySDM/examples/PySDM_examples\n```\nAlternatively, one can also install the examples package from pypi.org by \nusing ``pip install PySDM-examples`` (note that this does not apply to notebooks itself,\nonly the supporting .py files).\n\n## Contributing, reporting issues, seeking support \n\n#### Our technologicial stack: \n[](https://www.python.org/)\n[](https://numba.pydata.org)\n[](https://llvm.org)\n[](https://pypi.org/project/ThrustRTC/)\n[](https://numpy.org/)\n[](https://pytest.org/) \n[](https://colab.research.google.com/)\n[](https://codecov.io/)\n[](https://pypi.org/)\n[](https://github.com/features/actions)\n[](https://jupyter.org/)\n[](https:///)\n\nSubmitting new code to the project, please preferably use [GitHub pull requests](https://github.com/open-atmos/PySDM/pulls) - it helps to keep record of code authorship, \ntrack and archive the code review workflow and allows to benefit\nfrom the continuous integration setup which automates execution of tests \nwith the newly added code. \n\nCode contributions are assumed to imply transfer of copyright.\nShould there be a need to make an exception, please indicate it when creating\na pull request or contributing code in any other way. In any case, \nthe license of the contributed code must be compatible with GPL v3.\n\nDeveloping the code, we follow [The Way of Python](https://www.python.org/dev/peps/pep-0020/) and \nthe [KISS principle](https://en.wikipedia.org/wiki/KISS_principle).\nThe codebase has greatly benefited from [PyCharm code inspections](https://www.jetbrains.com/help/pycharm/code-inspection.html)\nand [Pylint](https://pylint.org), [Black](https://black.readthedocs.io/en/stable/) and [isort](https://pycqa.github.io/isort/)\ncode analysis (which are all part of the CI workflows).\n\nWe also use [pre-commit hooks](https://pre-commit.com). \nIn our case, the hooks modify files and re-format them.\nThe pre-commit hooks can be run locally, and then the resultant changes need to be staged before committing.\nTo set up the hooks locally, install pre-commit via `pip install pre-commit` and\nset up the git hooks via `pre-commit install` (this needs to be done every time you clone the project).\nTo run all pre-commit hooks, run `pre-commit run --all-files`.\nThe `.pre-commit-config.yaml` file can be modified in case new hooks are to be added or\n existing ones need to be altered. \n\nFurther hints addressed at PySDM developers are maintained in the [open-atmos/python-dev-hints Wiki](https://github.com/open-atmos/python-dev-hints/wiki)\n and in [PySDM HOWTOs](https://github.com/open-atmos/PySDM/tree/main/examples/PySDM_examples/_HOWTOS).\n\nIssues regarding any incorrect, unintuitive or undocumented bahaviour of\nPySDM are best to be reported on the [GitHub issue tracker](https://github.com/open-atmos/PySDM/issues/new).\nFeature requests are recorded in the \"Ideas...\" [PySDM wiki page](https://github.com/open-atmos/PySDM/wiki/Ideas-for-new-features-and-examples).\n\nWe encourage to use the [GitHub Discussions](https://github.com/open-atmos/PySDM/discussions) feature\n(rather than the issue tracker) for seeking support in understanding, using and extending PySDM code.\n\nWe look forward to your contributions and feedback.\n\n## Licensing:\n\ncopyright: [Jagiellonian University](https://en.uj.edu.pl/en) (2019-2023) & [AGH University of Krakow](https://agh.edu.pl/en) (2023-...) \nlicence: [GPL v3](https://www.gnu.org/licenses/gpl-3.0.html)\n\n \n",
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