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Visualize data on structured meshes in python

Project description

Viscid

Python framework to visualize scientific data on structured meshes. At the moment, only rectilinear meshes are supported, and support for other mesh types will be added as needed.

File types:

  • XDMF + HDF5
  • OpenGGCM jrrle (3df, p[xyz], iof)
  • OpenGGCM binary (3df, p[xyz], iof)
  • Athena (bin, hst, tab)
  • VPIC
  • ASCII

There is also preliminary support for reading and plotting AMR datasets from XDMF files.

Documentation

Both the master and dev branches should make every attempt to be usable (thanks to continuous integration), but the obvious caveats exist, i.e. the dev branch has more cool new features but it isn't as tested.

Branch Docs Test Status
master html, test summary Build Status
dev html, test summary Build Status

Install

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PyPI Version

Dependencies:

  • Required
    • Python 2.6, 2.7, or 3.3+
    • Numpy 1.9+
    • Argparse (Python 2.6 only)
  • Recommended
    • IPython (better interactive interpreter)
    • Matplotlib 1.4+ (if you want to make 2d plots using viscid.plot.vpyplot)
    • Scipy (enables nonlinear interpolation and curve fitting)
    • Numexpr (for faster math on large grids)
    • H5py (enables hdf5 reader)
  • Optional
    • Seaborn
    • Mayavi2 [1] (if you want to make 3d plots using viscid.plot.vlab)
    • PyYaml (rc file and plot options can parse using yaml)
  • Optional for developers
    • Cython 0.28+ (if you change pyx / pxd files)
    • Sphinx 1.3+

Detailed installation instructions are available here.

[1] Installing Mayavi can be tricky. Please read this before you try to install it.

Development

Please, if you edit the code, use PEP 8 style. Poor style is more than just aesthetic; it tends to lead to bugs that are difficult to spot. Check out the documentation for a more complete developer's guide (inculding exceptions to PEP 8 that are ok).

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Source Distribution

viscid-1.0.0.tar.gz (31.2 MB view hashes)

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viscid-1.0.0-cp37-cp37m-win_amd64.whl (31.5 MB view hashes)

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viscid-1.0.0-cp37-cp37m-manylinux1_x86_64.whl (35.3 MB view hashes)

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viscid-1.0.0-cp37-cp37m-macosx_10_6_intel.whl (33.7 MB view hashes)

Uploaded CPython 3.7m macOS 10.6+ intel

viscid-1.0.0-cp36-cp36m-win_amd64.whl (31.5 MB view hashes)

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viscid-1.0.0-cp36-cp36m-manylinux1_x86_64.whl (35.4 MB view hashes)

Uploaded CPython 3.6m

viscid-1.0.0-cp36-cp36m-macosx_10_6_intel.whl (33.7 MB view hashes)

Uploaded CPython 3.6m macOS 10.6+ intel

viscid-1.0.0-cp35-cp35m-win_amd64.whl (31.4 MB view hashes)

Uploaded CPython 3.5m Windows x86-64

viscid-1.0.0-cp35-cp35m-manylinux1_x86_64.whl (35.2 MB view hashes)

Uploaded CPython 3.5m

viscid-1.0.0-cp35-cp35m-macosx_10_6_intel.whl (33.4 MB view hashes)

Uploaded CPython 3.5m macOS 10.6+ intel

viscid-1.0.0-cp27-cp27mu-manylinux1_x86_64.whl (34.9 MB view hashes)

Uploaded CPython 2.7mu

viscid-1.0.0-cp27-cp27m-win_amd64.whl (31.5 MB view hashes)

Uploaded CPython 2.7m Windows x86-64

viscid-1.0.0-cp27-cp27m-manylinux1_x86_64.whl (34.9 MB view hashes)

Uploaded CPython 2.7m

viscid-1.0.0-cp27-cp27m-macosx_10_6_intel.whl (33.6 MB view hashes)

Uploaded CPython 2.7m macOS 10.6+ intel

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