# Pole Figure Color Coding

Explains how to control color coding across multiple plots.

A central issue when interpreting plots is to have a consistent color coding among all plots. In MTEX this can be achieved in two ways. If the minimum and maximum values are known then one can specify the color range directly using the options colorrange or contourf, or the command setcolorrange is used which allows setting the color range afterward.

 On this page ... A sample ODFs and Simulated Pole Figure Data Setting a Colormap Tight Colorcoding Equal Colorcoding Setting an Explicit Colorrange Setting the Contour Levels Modifying the Color range After Plotting Logarithmic Plots

## A sample ODFs and Simulated Pole Figure Data

Let us first define some model ODF_index.html ODFs> to be plotted later on.

```cs = crystalSymmetry('-3m');
odf = fibreODF(Miller(1,1,0,cs),zvector)
pf = calcPoleFigure(odf,[Miller(1,0,0,cs),Miller(1,1,1,cs)],...
equispacedS2Grid('points',500,'antipodal'));```
```
odf = ODF
crystal symmetry : -3m1, X||a*, Y||b, Z||c*
specimen symmetry: 1

Fibre symmetric portion:
kernel: de la Vallee Poussin, halfwidth 10°
fibre: (11-20) - 0,0,1
weight: 1

```

## Setting a Colormap

By default, MTEX uses the default MATLAB colormap jet, which varies from blue to red for increasing values.

`plot(pf)` However, sometimes more simple colormaps are preferred, like the LaboTeX colormap

`mtexColorMap LaboTeX` or a gray scale colormap.

`mtexColorMap white2black` One can set a default colormap adding the following command to the configuration file mtex_settings.m

`setMTEXpref('defaultColorMap',LaboTeXColorMap);`

## Tight Colorcoding

When the plot is called without any other option, the chosen color coding is the one called tight, which ranges the data independently from the other plots, i.e., for each subplot the largest value is assigned to the maximum color and the smallest value is assigned to the minimum color from the colormap.

```close all
plot(pf)``` ## Equal Colorcoding

The tight colorcoding makes the reading and comparison between pole figures hard. If you want to have one colorcoding for all plots within one figure use the option colorrange to equal.

`plot(pf,'colorrange','equal')` ## Setting an Explicit Colorrange

If you want to have a unified colorcoding for several figures you can set the colorrange directly in the plot command

```close all
plotPDF(odf,[Miller(1,0,0,cs),Miller(1,1,1,cs)],...
'colorrange',[0 4],'antipodal');
figure
plotPDF(.5*odf+.5*uniformODF(cs),[Miller(1,0,0,cs),Miller(1,1,1,cs)],...
'colorrange',[0 4],'antipodal');```  ## Setting the Contour Levels

In the case of contoured plots, you can also specify the contour levels directly

```close all
plotPDF(odf,[Miller(1,0,0,cs),Miller(1,1,1,cs)],...
'contourf',0:1:5,'antipodal')``` ## Modifying the Color range After Plotting

The color range of the figures can also be adjusted afterward using the command setcolorrange

`CLim(gcm,[0.38,3.9])` ## Logarithmic Plots

Sometimes logarithmic scaled plots are of interest. For this case all plots in MTEX understand the option logarithmic, e.g. TODO:

```%close all;
%plotPDF(odf,[Miller(1,0,0,cs),Miller(1,1,1,cs)],'antipodal','logarithmic')
%setcolorrange([0.01 12]);
%mtexColorbar```

Finally, lets set back the default colormap.

`setMTEXpref('defaultColorMap',WhiteJetColorMap);`