fading line plot

Hi everyone,

I've been looking into making an animation of a mechanical system. In its first incarnation, my plan was as follows:
1) Make a fading line plot of two variables (say, x and y)
2) Run a series of such plots through ffmpeg/avencode to generate an animation

First, I'm wondering whether there's a built-in way of making a fading line plot, i.e. a plot where one end of the line is plotted with high alpha, the other end with low alpha, and intermediate line segments with linearly scaled alpha. For now, I've done this by manually "chunking" the x and y arrays and plotting each chunk with different alpha. Is there a better way? Is there interest in creating such a plotting function and adding it to matplotlib?

Second, is there a way of integrating the "chunked" generation of fading lines with the animation generating features of matplotlib? It seems possible, although a bit clunky, at present, but maybe someone has a better idea at what overall approach to take than I do.

Cheers
Paul

I remember this http://www.johndcook.com/blog/2013/02/20/python-animation-for-mechanical-vibrations/ from a few days back, HTH.

···

On 24/02/2013 18:28, Paul Anton Letnes wrote:

Hi everyone,

I've been looking into making an animation of a mechanical system. In its first incarnation, my plan was as follows:
1) Make a fading line plot of two variables (say, x and y)
2) Run a series of such plots through ffmpeg/avencode to generate an animation

First, I'm wondering whether there's a built-in way of making a fading line plot, i.e. a plot where one end of the line is plotted with high alpha, the other end with low alpha, and intermediate line segments with linearly scaled alpha. For now, I've done this by manually "chunking" the x and y arrays and plotting each chunk with different alpha. Is there a better way? Is there interest in creating such a plotting function and adding it to matplotlib?

Second, is there a way of integrating the "chunked" generation of fading lines with the animation generating features of matplotlib? It seems possible, although a bit clunky, at present, but maybe someone has a better idea at what overall approach to take than I do.

Cheers
Paul
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Cheers.

Mark Lawrence

Paul,

I've had to do something similar to what you need, and I found the following example from the Gallery quite helpful:
http://matplotlib.org/examples/pylab_examples/multicolored_line.html
I think the second plot in particular is pretty close to what you want; however, you'll need to set the alpha values manually. This is what I've done for line collections, scatter plots, etc.

···

On 2/24/2013 1:28 PM, Paul Anton Letnes wrote:

Hi everyone,

I've been looking into making an animation of a mechanical system. In its first incarnation, my plan was as follows:
1) Make a fading line plot of two variables (say, x and y)
2) Run a series of such plots through ffmpeg/avencode to generate an animation

First, I'm wondering whether there's a built-in way of making a fading line plot, i.e. a plot where one end of the line is plotted with high alpha, the other end with low alpha, and intermediate line segments with linearly scaled alpha. For now, I've done this by manually "chunking" the x and y arrays and plotting each chunk with different alpha. Is there a better way? Is there interest in creating such a plotting function and adding it to matplotlib?

Second, is there a way of integrating the "chunked" generation of fading lines with the animation generating features of matplotlib? It seems possible, although a bit clunky, at present, but maybe someone has a better idea at what overall approach to take than I do.

Cheers
Paul
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_________________________________
import numpy as np
import matplotlib.pyplot as plt

norm_data = np.random.rand(20)
xs = np.random.rand(20)

# Pick a colormap and generate the color array for your data
cmap = plt.cm.spectral
colors = cmap(norm_data)
# Reset the alpha data using your desired values
colors[:,3] = norm_data

# Adding a colorbar is a bit of a pain here, need to use a mappable
fig = plt.figure()
plt.scatter(xs, norm_data, c=colors, s=55)
mappable = plt.cm.ScalarMappable(cmap=cmap)
mappable.set_array(norm_data)
fig.colorbar(mappable)
plt.show()
_________________________________

Hope that helps a little.

Ryan