Giter VIP home page Giter VIP logo

open-atmos / pysdm Goto Github PK

View Code? Open in Web Editor NEW
51.0 5.0 28.0 29.73 MB

Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab

Home Page: https://open-atmos.github.io/PySDM/

License: GNU General Public License v3.0

Python 96.79% TeX 1.17% Shell 0.01% Jupyter Notebook 2.03%
physics-simulation monte-carlo-simulation gpu-computing atmospheric-modelling particle-system numba thrust nvrtc pint atmospheric-physics

pysdm's People

Contributors

abulenok avatar agnieszkamakulska avatar bhiogade avatar bradybhalla avatar claresinger avatar codacy-badger avatar dependabot[bot] avatar edejong-caltech avatar jb-mackay avatar kagrski avatar kaitlyn-loftus avatar kyetuur avatar mikhailmints avatar piotrbartman avatar rlhycd avatar sajjadazimi avatar slayoo avatar trontrytel avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar

pysdm's Issues

add checks for mass conservation in dry radius discretisation

we are discretising number distribution, in the example (or even within initialisation logic) we should be able to impose a threshold on the acceptable level of incurred mass difference (between the one obtainable via moments of dry volume and the analytical value stemming from lognormal distribution parameters)

more sliders/checkboxes etc in the ICMW example

  • spin-up process set control
  • dt
  • ventilation effects
  • continuum regime corrections
  • random seed
  • terminal velocity choice
  • kernel choice
  • backend choice
  • aerosol spectrum parameters
  • parallelisation controls
  • products
  • initialisation controls (constant multiplicity, ...)
  • condensation options: coord, adaptivity
  • coalescence adaptivity on/of + settings

implement sister algorithms

  • Riemer et al. 2009
  • Zsom & Dullemond 2008
  • Ormel & Spaans_2008
  • Maisels et al. 2004
  • Kolodko and Sabelfeld 2003
@article{Kolodno_and_Sabelfeld_2003,
  author = {Kolodko, A. and Sabelfeld, K.},
  title = {Stochastic particle methods for Smoluchowski coagulation equation: Variance reduction and error estimations},
  journal = {Monte Carlo Methods and Applications}
  doi = {10.1163/156939603322601950}, 
  year = {2003}
}
@article{Maisels_et_al_2004,
  author = {Maisels, A., Einar Kruis, F., and Fissan, H.},
  title = {Direct simulation Monte Carlo for simultaneous nucleation, coagulation, and surface growth in dispersed systems},
  journal = {Chem. Eng. Sci.}
  doi = {10.1016/j.ces.2004.02.015}
  year = {2004}
}
@article{Ormel_and_Spaans_2008,
  author = {Ormel, C.W. and Spaans, M.},
  title = {Monte  Carlo  Simulation  of  Particle Interactions at high dynamic range: Advancing beyond the Googol},
  journal = {Astrophys. J.}, 
  year = {2008},
  doi = {10.1086/590052}
}
@article{Zsom_and_Dullemond_2008,
  title = {A representative particle approach to coagulation and  fragmentation of dust aggregates and fluid droplets},
  author = {Zsom, A. and Dullemond, C.P.},
  year = {2008},
  doi = {10.1051/0004-6361:200809921},
  journal = {Astron. Astrophys.}
}
@article{Riemer_et_al_2009,
  author = {Riemer, N. and West, M. and Zaveri, R.A. and Easter, R.C.},
  year = {2009},
  title = {Simulating the Evolution of Soot Mixing State with a Particle-Resolved Aerosol Model},
  journal = {J. Geophy. Res.},
  doi = {10.1029/2008JD011073}
}

segmentation

requires:

  • intensive attributes
  • position-changing dynamics
  • terminal velocity
  • periodic boundary conditions
  • new example setup

more backends

  • Numba parallel
  • PyPy
  • Pythran
  • ThrustRTC (serial, threads, CUDA, ...)
  • Numba CUDA
  • Numpy noloops
  • CPython
  • Dask
  • numexpr

toss_pairs improvement plan

  • understand what numba's prange does (i.e., when sync happens?)
  • replace current sort_by_cell_id with something around a parallel counting sort
  • do unsort per segment (like in Shima, per-segment parallelism) - would include find_pairs?
  • try some parallelism within segment
  • some custom thread-pool logic for find_pairs (as well as condensation!)?

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.