SIO 221C:  Color Maps and Images

Images:  The Matlab image functions order arrays like mathematical matrices with coordinate (1,1) in the upper left corner.  Data tend to start with the smallest latitude and longitude values, which should be mapped in the lower left corner.  To make your Matlab image plot look correct, you can use axis xy, or you can flip the matrix top-to-bottom:  imagesc(lon_t,lat_t,flipud(T));

Colormaps:  In Matlab, the default colormap for contour and image plots is a blue to red spectrum, but you can override this.  To change the colormap used for contour or image plots, you can specify a different basic color map by typing, for example, colormap(cool).  Other colormaps include hsv, prism, gray, hot, cool, copper, flag, pink, bone, and jet (the default).

Sometimes, you want to make sure that NaNs don't end up shaded the same color as useful data points, so you can force values at the end of your range to be white or black, for example.
cmap2=[[1 1 1]; colormap; [1 1 1]];
You might have to fix the limits of your colors to keep real data from also being whited out.  To get black where you had no data, you'd use [0 0 0].

Colormaps and color  blindness:   About 8% of men and 0.5% of women have color-impaired vision.  Often this means that red and green are difficult to distinguish, which means that the Matlab default 'jet' colormap can be difficult to interpret.  Better choices are single color schemes (such as Matlab's 'hot') that increase in intensity, or diverging schemes that extend from blue to red.  For a reprint of the recent EOS article, comments, and reply see:
For general information see:
or for tools to check your graphics:

Colormaps and the branch cut:  We can also compute the angular direction of the current and plot that as an image:
Here we use atan2 rather than atan, because we want our angles to go from 0 to 360 degrees. Since 0 and 360 degrees are equivalent, it's good to choose a colorscale where the colors are 0 and 360 are nearly the same.  The clrscl.m function (written by Matt Dzieciuch of IGPP)  provides one way to fix a colorscale appropriately.  Compare:
imagesc(lon_t,lat_t,theta); axis xy; colorbar
imagesc(lon_t,lat_t,theta); axis xy; colorbar