Hi Friedrich,
Many thanks for your detailed response. I've had to turn my attention
to other things in the past few weeks, but I am back to this task now.
I've implemented the Norm that you suggested by subclassing Normalize;
that was a great suggestion. Now I have a two dimensional array
2010/11/1 Timothy W. Hilton hil...@meteo.psu.edu:
[...]
I want to have blue water, some other (bright) color for missing data,
and a nice-looking color transition (matplotlib.cm.Blues or something
similar) for the valid data over land (values from 0 to 50). The
Cookbook example at
Hello,
I have a 2D numpy masked array of geo-located data -- with some data
missing -- that I wish to plot on a map. Basemap provides a nice tool
to do this, but I am stumped trying to get the colorscheme I want.
My data are only physically meaningful on land, so I am using
Basemap.maskoceans()
2010/3/14 David Arnold dwarnol...@suddenlink.net:
All,
I am having difficulty with a line on: http://scipy.org/LoktaVolterraTutorial
Here are the lines:
values = linspace(0.3, 0.9, 5)
vcolors = p.cm.autumn_r(linspace(0.3, 1., len(values)))
First of all, I can find no reference to
All,
I am having difficulty with a line on: http://scipy.org/LoktaVolterraTutorial
Here are the lines:
values = linspace(0.3, 0.9, 5)
vcolors = p.cm.autumn_r(linspace(0.3, 1., len(values)))
First of all, I can find no reference to autumn_r in the Matplotlib
documentation. Also, using
