It is a simple but common task required when trying to fix a colormap according to a 2D matrix of values. To demonstrate consider the problem in **Matlab**, the solution does not need to be in **Matlab** (i.e., the code presented here is only for demonstration purpose).

` x = [0,1,2; 3,4,5; 6,7,8]; imagesc(x) axis square axis off `

So the output is as:

when some values change to over the maximum value it happens like:

` x = [0,1,2; 3,4,5; 6,7,18]; `

which looks logical but makes problems when we wish to compare/trace elements in two maps. Since the colormap association is changed it is almost impossible to find an individual cell for comparison/trace etc.

The solution I implemented is to mask the matrix as:

` x = [0,1,2; 3,4,5; 6,7,18]; m = 8; x(x>=m) = m; `

which works perfectly.

Since the provided code requires searching/filtering (extra time consuming!) I wonder if there is **a general/more efficient way** for this job to be implemented in **Matlab**, **Python** etc?

One of the cases that this issue occurs is when we have many simulations sequentially and wish to make a sense-making animation of the progress; in this case each color should keep its association fixed.

-------------Problems Reply------------

The indexing is pretty quick so I don't think you need worry.

However, in Matlab, you can pass in the `clims`

argument to `imagesc`

:

`imagesc(x,[0 8]);`

This maps all values above 8 to the top colour in the colour scale, and all values below 0 to the bottom colour in the colour scale, and then stretches the scale for colours in-between.

`imagesc documentation`

.

In **Python** using package `MatPlotLib`

the solution is as follows:

import pylab as pl

x = [[0,1,2],[3,4,5],[6,7,18]]

pl.matshow(x, vmin=0, vmax=8)

pl.axis('image')

pl.axis('off')

show()

So `vmin`

and `vmax`

are boundary limits for the full range of colormap.

`f1 = figure;`

x = [0,1,2; 3,4,5; 6,7,8];

imagesc(x)

axis square

axis off

```
```limits = get(gca(f1),'CLim');

`f2 = figure;`

z = [0,1,2; 3,4,5; 6,7,18];

imagesc(z)

axis square

axis off

caxis(limits)