>>>>> "seberino" == seberino <seb...@sp...> writes:
seberino> Stephen Thanks for the help. The format of the data is
seberino> ASCII files and/or Python arrays that contain (x, y)
seberino> coordinates or (x, y, z) coordinates for 3D.
seberino> For starters, what is best way to plot triples in this
seberino> list?...
seberino> [ (0, 0, 3.3), (0, 1, 4.4), (1, 0, 2.2), (1, 1, 2.34)]
seberino> I want to duplicate color plot on screenshots page:
seberino> http://matplotlib.sourceforge.net/screenshots/pcolor_demo_large.png
You have a 2x2 grid. pcolor is a bit funny in that for an MxN grid it
only plots M-1 x N-1 rectangles since it doesn't know how to handle
the edges. So it's a bit of a pathalogical case for pcolor.
Basically you need to transform your list of 3 tuples into 3 arrays
x,y,z, and then reshape the array. Here I'll use imshow which
doesn't have the edge problem
from matplotlib.matlab import *
data = [ (0, 0, 3.3), (0, 1, 4.4), (1, 0, 2.2), (1, 1, 2.34)]
x,y,z = zip(*data)
z = array(z); z.shape = 2,2
imshow(z, interpolation='nearest', extent=(0,1,0,1))
show()
If you had a longer data sequence, say 5x5, you would use pcolor like
from matplotlib.matlab import *
data = ....
x,y,z = zip(*data)
x = array(x); x.shape = 5,5
y = array(y); y.shape = 5,5
z = array(z); z.shape = 5,5
pcolor(x,y,z)
show()
In short, there is nothing special about plotting "data" versus
"functions". Both are simply cases of plotting 1-D or 2-D arrays as
far as matplotlib is concerned. Your task is to get your data in to
the right array shape.
JDH
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