The document discusses various methods for data visualization and analysis in 3D, emphasizing the importance of color representation to accurately convey information. It covers different types of data (nominal, numeric, bimodal) and suggests appropriate colormaps to address issues like color vision deficiency. The document also provides guidance on surface data handling and highlights the necessity of transparent rendering and thorough reporting for reproducibility.

1. DIGGING INTO DATA
ANALYSIS AND VISUALISATION IN 3D
Alex Henderson
University of Manchester
SurfaceSpectra Ltd
http://about.me/henderson.alex
Twitter: @AlexHenderson00

2. SURFACESPECTRA
(XPS)
XPS OF POLYMERS
DATABASE
SURFACE ANALYSIS BY AUGER
AND X-RAY PHOTOELECTRON
SPECTROSCOPY
surfacespectra.com

3. SURFACESPECTRA
(SIMS)
STATIC SIMS
LIBRARY
TOF-SIMS: MATERIALS
ANALYSIS BY MASS
SPECTROMETRY
identity
surfacespectra.com

4. FALSE COLOUR
Colour is used to represent different aspects of our data
• Nominal data (no implied order)
• cancer / non-cancer, clustering etc.
• Numeric data
• intensity of peak X in counts
• Bimodal data
• ratios or PCA scores
• Surface data
• 3D rendering
Different colour scales (colormaps) are required for each type

5. COLOUR INTERPRETATION
Human eye not equally
responsive to each colour
More sensitive to luminance
or brightness than colour
(hue)
Colours exist that we cannot
see

6. COLOUR VISION
DEFICIENCY (CVD)
Often just called colour blindness
Affects ~8% of men, ~0.5% of women
Actually different subclasses
• Anomalous trichromacy (most common)
• Perceive all colours, but differently
• Dichromacy
• Missing one colour
• Monochromacy
• Missing two colours - greyscale

7. COMPUTERS AND COLOUR
Computer monitors work with red-green-blue pixels
(RGB)
Other colour spaces are available
• Hue-saturation-luminance (HSL)
• Used in colour pickers
• CIELAB L*a*b*
• Standardised colour
• CMYK (cyan, magenta, yellow, black)
• Used in the printing industry for lithography

8. NOMINAL DATA
http://colorbrewer2.org

9. NUMERIC DATA
Wish to display a range of ion intensities
For a single ion, options include:
• Different colours depending on intensity
• Different brightness of same colour
Human eye cannot order rainbow colours easily.

10. Ratio Image: m/z 23 / 39
0
2
4
6
8
10
12
14
16
18
20
NUMERIC DATA
MATLAB’s ‘Jet’ colormap is a rainbow
Yellow appears brighter than red or blue
Observer must interpret whether yellow
pixel has higher ion intensity than green or
orange

11. PERCEPTUALLY LINEAR
Need a colormap where trend is easy to interpret
MATLAB now has ‘Parula’ colormap as default

12. PYTHON (MATPLOTLIB)
COLORMAPS
Inferno
Magma
Plasma
Viridis

13. PYTHON (MATPLOTLIB)
COLORMAPS

14. BIMODAL DATA
Principal component scores are bidirectional
Large positive values and large negative values are important
Values around zero are not important
Ideally want black at zero point with different colours for
positive and negative score

15. BIMODAL DATA
Red-green often used, but difficult for colour vision deficient
colleagues to interpret
Use magenta-green instead

16. RATIO DATA
Wish to display the spatial distribution of two ions?
Option 1
• Create two images, one per ion
• OK
Option 2
• Calculate the ratio of the ions and generate a single image
• Problems

17. SINGLE ION IMAGES
m/z 23
0
20
40
60
80
100
m/z 39
0
10
20
30
40
50
60
70
Note that m/z 23 is generally more intense than m/z 39

18. SIMPLE RATIO APPROACH
Ratio Image: m/z 23 / 39
0
2
4
6
8
10
12
14
16
18
20
Ratio Image: m/z 39 / 23
0
10
20
30
40
50
60
Although the ratio has been inverted the display is largely blue.
Poor representation of the ion distribution.

19. Ratio Image: m/z 23 / 39
0
2
4
6
8
10
12
14
16
18
20
SIMPLE RATIO APPROACH
Colour mapped from smallest value to
largest.
Latter case is all same colour
Range is one to infinity
Range is zero to one
𝑙𝑎𝑟𝑔𝑒 𝑣𝑎𝑙𝑢𝑒
𝑠𝑚𝑎𝑙𝑙 𝑣𝑎𝑙𝑢𝑒
𝑠𝑚𝑎𝑙𝑙 𝑣𝑎𝑙𝑢𝑒
𝑙𝑎𝑟𝑔𝑒 𝑣𝑎𝑙𝑢𝑒

20. NORMALISED TO +/- 100%
Relative amounts of m/z 23 and 39
-100
-80
-60
-40
-20
0
20
40
60
80
100
Relative amounts of m/z 39 and 23
-100
-80
-60
-40
-20
0
20
40
60
80
100
Ion images are now mirror images of each other

21. PROPORTIONAL SCALING
BA
A

Result
Calculating the proportion, rather
than a ratio, produces a more
stable result
All pixels now range 0 to 1
Colour spread evenly across all
outcomes
Should use colormap with two colour gradients
No black in centre eg MATLAB’s ‘Cool’

22. JCV ratio: m/z 39/(23+39)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
JCV ratio: m/z 23/(23+39)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
PROPORTIONAL SCALING
Proportion Na / (Na + K) Proportion K / (Na + K)
Data now mirror images of one another

23. SURFACE DATA
Need to light the object to define 3D structure
Where light strikes colour is brighter
Therefore, can’t plot a range of concentration
Rendered isosurface at single intensity
Any single colour will suffice

24. TRANSPARENCY
Need to be able to see inside
our 3D data
Create multiple isosurfaces at
different intensity values
Set transparency (alpha
channel) higher at outside

27. REPORTING REQUIREMENTS
Sharing 3D data is difficult
Need to record parameters:
• Orientation (top-left-front, bottom-right-back)
• Direction of ion beam erosion (L-R, flyback or meander)
• Angles of incidence and detection
• Intensity values for isosurfaces (including alpha channel)
• Interpolation / smoothing parameters (helps to prevent
isosurface disconnect)
• Shift correction (layers, direction, amount etc.)
• ‘Stretching’ of z-dimension for visualisation (voxel
dimensions)

28. SUMMARY
• Nominal data
• http://colorbrewer2.org/
• Numeric data
• MATLAB’s ‘Perula’, Python’s, ‘Viridis’
• Bimodal data
• PCA scores use magenta/green with black mid-point
• Plot proportions not ratios. Two colour colormap without black
centre eg. MATLAB’s ‘Cool’
• Surface data
• Single intensity and colour
• Use transparency
• Report what you did!
• Don’t forget our colour vision deficient colleagues!

29. ACKNOWLEDGEMENTS
Bead data – Nick Winograd
Frog egg data – John Fletcher
HeLa cell data – John Fletcher, Sadia (Rabbani) Sheraz
Rendered isosurface – Greg Fisher
More detailed background – Alan Race and Josephine Bunch’s review: Anal Bioanal
Chem (2015) 407:2047–2054
Movies available from http://www.sarc.manchester.ac.uk/gallery/
Image credits
SurfaceSpectra products: http://surfacespectra.com
Human eye spectral response: https://en.wikipedia.org/wiki/Color_vision
CIELAB colour space: https://en.wikipedia.org/wiki/Lab_color_space
Colour ordering: http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they-good-for-
absolutely-nothing/
Matplotlib colormaps: http://medvis.org/2016/02/23/better-than-the-rainbow-the-matplotlib-
alternative-colormaps/