Finite Sampling Corrected 3D Noise with Confidence Intervals

Analysis of imager noise through the use of 3D Noise model

The 3D noise model is a white noise approximation consisting of 7 independent contributions that span the 3D correlation space (1 one dimensional uncorrelated processes, 3 two dimensional uncorrelated processes, and one three dimensional uncorrelated process). These scripts allow the user to simulate a noise cube, calculate the 7 independent variances, and calculate the confidence intervals. An additional script provides examples of how the functions can be called under different circumstances, for example correcting a past measurement, or iteratively calculating the noise cube by chunking the data.
This code is in support of a journal article "Finite Sampling Corrected 3D Noise with Confidence Intervals" https://www.osapublishing.org/ao/abstract.cfm?uri=ao-54-15-4907