RasterizeGaussians
===================================
.. currentmodule:: gsplat
Given 2D gaussians that are parametrized by their means :math:`μ'` and covariances :math:`Σ'` as well as their radii and conic parameters,
the :func:`gsplat.rasterize_gaussians` function first sorts each gaussian such that all gaussians within the bounds of a tile are grouped and sorted by increasing depth :math:`z`,
and then renders each pixel within a tile with alpha-compositing.
The discrete rendering equation is given by:
.. math::
\sum_{t=n}^{N}c_{n}·α_{n}·T_{n}
Where
.. math::
T_{n} = \prod_{t=m}^{M}(1-α_{m})
And
.. math::
α_{n} = o_{n} \exp(-σ_{n})
σ_{n} = \frac{1}{2} ∆^{⊤}_{n} Σ'^{−1} ∆_{n}
:math:`σ ∈ R^{2}` is the Mahalanobis distance (here referred to as sigma) which measures how many standard deviations away the center of a gaussian and the rendered pixel center is which is denoted by delta :math:`∆.`
The python bindings support conventional 3-channel RGB rasterization as well as N-dimensional rasterization with :func:`gsplat.rasterize_gaussians`.
.. autofunction:: rasterize_gaussians