yt is an open-source Python package for analyzing and visualizing volumetric data.
yt focuses on driving physically-meaningful inquiry. The toolkit has been applied in fields such as astrophysics, seismology, radio telescope data, nuclear engineering, molecular dynamics, and oceanography.
yt is written almost entirely in Python and it functions as a library that you can import into your Python scripts.
- Supports structured, variable-resolution meshes, unstructured meshes, and discrete or sampled data such as particles.
- Create visualizations of simulation data, derived fields, and the data produced by yt analysis objects.
- Overplotting Contours, Velocities, Particles.
- Provides a number of ways of getting the raw data that goes into a plot to you in the form of a one or two dimensional dataset that you can plot using any plotting method you prefer.
- Create 3D visualizations using a process known as volume rendering.
- Volume render unstructured mesh data like that created by finite element calculations.
- Hardware-accelerated interactive volume renderer. This interactive renderer is based on OpenGL and natively understands adaptive mesh refinement data; this enables (GPU) memory-efficient loading of data.
- Implementation of the Marching Cubes algorithm, which can operate on 3D data objects. Surfaces can be exported in OBJ format, values can be samples at the center of each face of the surface, and flux of a given field could be calculated over the surface.
- Mapserver – a Google-Maps-like interface to your data.
- Several colormaps are available including all of the matplotlib colormaps.
- Supports many different code formats including ART, ARTIO, Athena, Castro, Chombo, Enzo, FITS, FLASH, Gadget, GAMER, Gasoline, Gizmo, Grid Data Format, Maestro, MOAB, Nyx, openPMD, Orion, OWLS/EAGLE, Piernik, Pluto, RAMSES, Tipsy, and WarpX.
There’s an all-in-one installation script that downloads and builds a fully-isolated installation of Python that includes NumPy, Matplotlib, H5py, git, and yt.
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