Frequently Asked Questions (FAQ): Difference between revisions
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== I have loaded | == I have loaded spectral data, but the buttons are still grayed out? == | ||
This is not a bug! It is important to understand that the mat2dcos toolbox was originally developed for heterospectral 2D correlation analysis (2D-COS). This means that spectral series from two different modalities are analyzed. For example, if IR and Raman data are to be analyzed by heterospectral 2D-COS, two different spectral series must be loaded into the toolbox. | This is not a bug! It is important to understand that the mat2dcos toolbox was originally developed for heterospectral 2D correlation analysis (2D-COS). This means that spectral series from two different modalities are analyzed. For example, if IR and Raman data are to be analyzed by heterospectral 2D-COS, two different spectral series must be loaded into the toolbox. |
Latest revision as of 08:25, 22 July 2023
I have loaded spectral data, but the buttons are still grayed out?
This is not a bug! It is important to understand that the mat2dcos toolbox was originally developed for heterospectral 2D correlation analysis (2D-COS). This means that spectral series from two different modalities are analyzed. For example, if IR and Raman data are to be analyzed by heterospectral 2D-COS, two different spectral series must be loaded into the toolbox. For the probably more common case of autocorrelation 2D-COS, this means that the data set to be analyzed has to be loaded twice, once as x- and a second time as y-data set. Only then will the buttons be available for analysis.
Links to other non-commercial 2D-COS software solutions
- 2dshige, free software for two-dimensional correlation analysis developed by Prof. Shigeaki Morita (Osaka Electro-Communication University).
- MIDAS 2010, Matlab-based software tools developed in the Canadian Light Source for 2D spectroscopic analysis and data exploration of time resolved infrared spectra
- corr2D (R), - Implementation of two-dimensional correlation analysis in R, developed by Robert Geitner.
(to be continued)