The PCA tool runs principal components analysis on an image composed of spectra/diffraction patterns of multiple samples.

# Example

This file contains a sequence of 10 IR absorption spectra ([10,1602] data block), shown here as separate lines. To use the PCA tool to analyse the variance in this data set:

- Plot the data as an image,
- From the tools menu, select PCA
- From the PCA View, Select the number of PCs to calculate and click Run PCA.
- When the calculation is complete, the % variance explained should be plotted against the component number in the Variance Explained tab
- There are other tabs with different ways to explore the PCA results
- The Scores/Loads tab allow the difference PC scores to plotted against each other (or the y-axis data of the image, which might be, for example, Temperature)
- The plot on the left shows the average spectrum/pattern plotted with the loadings vector for the selected PCs
- The Reconstruct tab allows the data to be reconstructed using a limited number of PCs. This can be used to see how many components are needed to explain the variance in each sample.
- The number of PCs to use can be changed by adjusting the PCs spinner, the sample to investigate can be changed using the sample spinner
- The plot shows the sample data, the data constructed from the chosen PCs and the residual (sample - reconstruction)

## 1 Comment

## Luke Keenan

---When the calculation is complete, the % variance explained should be plotted against the component number in the Variance Explained tab.

Can you explain what would be expected in the plot if there are 2 or 3 components present? (i.e. What does the y-axis mean in practise)

---The Scores/Loads tab allow the difference PC scores to be plotted against each other

typo

---The plot on the left shows the average spectrum/pattern plotted with the loadings vector for the selected PCs

The loadings vector means the variation from the mean? If there is a spike in the line then that part of the selected PC is changing (at some point) in the series?