NoisySignalIntegration.jl
NoisySignalIntegration.jl – A tool to determine uncertainty in numeric integrals of noisy x-y data.
NoisySignalIntegration
implements a method to determine the uncertainty in numeric integrals of noisy x-y data on the basis of a Monte-Carlo process. It can include uncertainty due to noise, baseline subtraction, and placement in integration bounds. To do this, the integration is repeated many times while the noise of the data, baseline, and integration bounds are varied based on a noise model and user supplied probability distributions.
A predecessor of this package was originally intended to estimate uncertainties of band signals in FTIR spectra (see G. Karir et al., 2019), which is reflected in the example given in the Usage Guide.
Table of Contents
- Package Overview
- Usage Guide
- Cropping the spectrum
- Noise analysis
- Preparing the spectrum for integration
- Integration bounds
- Defining an
UncertainBound
using a start and end point - Defining an
UncertainBound
using a position, width, andUncertainCurve
(symmetric bands) - Defining an
UncertainBound
using several positions, a width, andUncertainCurve
(several symmetric bands with same width) - Plotting Monte-Carlo draws
- Running the integration algorithm
- Case studies
- Baseline Handling
- API Reference
- Internals