Volume rendering of temperature data

[Mikegrann]

An existing system is in place to interpolate oxygenation data across a volume given point samples. This system must be integrated with temperature data to allow a similar interpolation across the Catalina cove.

The system is known to generate a 3D Texture from which to sample.

The interpolation should be handled as a depth-dependent equation, as water depth is a massive factor of water temperature. Conner White has an existing interpolation method in 2D from which to start.

Goals:

• [x] Integrate temperature data into the existing volume creation.
• [ ] Current 3D Texture sampling leads to very cubic volumes. Determine a means to fit the volume into the actual cove space, not just some arbitrary cube.
• [x] Port Conner's existing interpolation method into the program and modify it to output a 3D volume instead of a 2D surface. This will likely require an entire new algorithm merely based on the same methods and motivations for the original algorithm.

[Mikegrann]

Commit df467f8f689c2b94834ca9165e6de8e43aec6642 added support for building a volume from a set of discrete sample points. It also included implementation of a new data interpolation, the "Connor Interpolation," which interpolates any given point's temperature as a combination of a polynomial regression on depth and an inverse distance weighting of known sample values.

The volume must still be matched to the cove.