On Tue, Feb 14, 2012 at 12:49 PM, Olе Streicher <ole-usenet-s...@gmx.net>wrote:
> Jerzy Karczmarczuk
> <jerzy.karczmarc...@unicaen.fr> writes:
> > Could you provide a /working/ example with the geometry you really want?
> > I believe I thought more or less about it as Tony Yu did. If it is
> > wrong, be more precise, please.
>
> I have a data set that looks like this:
>
> mydata = numpy.copy([
>
> # lambda, data
>
> # First data row
> [[5002., 0.5],
> [5200., 0.34],
> [5251., -1.2],
> # ...
> [8997., 2.4]],
>
> # second data row
> [[5002., 0.72],
> [5251., 0.9],
> # ...
> [8997., 0.1]],
>
> # other data rows to follow
> # ...
> ])
>
> where I want to put the first column (lambda) on the Y axis, which each
> data row as one colorbar (like in your code), and the data as the color
> of that data point -- interpolated vertically.
>
> Best regards
>
> Ole
>
>
OK, I see now.
Unfortunately, this makes it quite a bit more complex, but it's still
doable. Part of the complexity arises because of (what I believe to be) a
quirk in NonUniformImage: You can pass an extent argument, but this only
rescales the data---it doesn't clip the data. You have to manually clip the
borders of each bar.
Here's an example:
#---
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.image import NonUniformImage
width = 0.5
height = 10
ax = plt.gca()
for x0 in np.arange(11):
y = np.sort(np.random.uniform(high=height, size=10))
z = np.random.random(size=(10, 1))
# Note NonUniformImage fails with single column; double up data
z = np.repeat(z, 2, axis=1)
x = [x0, x0]
extent = (x0-width/2., x0+width/2, y[0], y[-1])
im = NonUniformImage(ax, interpolation='bilinear', extent=extent)
im.set_data(x, y, z)
# clip image
x_left = extent[0]
xm = [x_left, x_left + width, x_left + width, x_left]
ym = [0, 0, height, height]
mask, = ax.fill(xm, ym, facecolor='none', edgecolor='none')
im.set_clip_path(mask)
ax.images.append(im)
ax.set_xlim(-width, x0+width)
plt.show()
#---
HTH,
-Tony
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