Re: [Matplotlib-users] Eye patterns (Heat plot?)
On Mon, Jan 23, 2012 at 3:19 PM, Paul Ivanov pivanov...@gmail.com wrote: Paul Ivanov, on 2012-01-23 13:07, wrote: the quick and dirty way to get close to what you want is to add an alpha value to the lines you're already plotting. Here's a small example: x = np.arange(0,3,.01) y = np.sin(x**2) all_x,all_y = [],[] ax = plt.gca() for i in range(100): noisex = np.random.randn(1)*.04 noisey = (np.random.randn(x.shape[0])*.2)**3 ax.plot(x+noisex,y+noisey, color='b', alpha=.01) all_x.append(x+noisex) all_y.append(y+noisey) To get a heat diagram, as was suggested, you can use a 2d histogram. plt.figure() all_x =np.array(all_x) all_y = np.array(all_y) all_x.shape = all_y.shape = -1 H, yedges, xedges = np.histogram2d(all_y, all_x, bins=100) extent = [xedges[0], xedges[-1], yedges[-1], yedges[0]] ax = plt.gca() plt.hot() ax.imshow(H, extent=extent, interpolation='nearest') ax.invert_yaxis() For completeness, attached is what the hexbin version of the same data looks like: plt.hexbin(all_x, all_y) You may want to play with the 'bins' (for histogram2d) and 'griddata' (for hexbin) parameters to get the appropriate level of detail for the amount of data you have. To get a proper count of the 2D bins that each curve crosses, you could parameterize the curve by arclength and resample it use a small step size. Or, you could linearly interpolate between the curve's discretized data points using Bresenham's line algorithm. The latter seemed like a straightforward approach, so I wrote it up and added it to the SciPy Cookbook: http://www.scipy.org/Cookbook/EyeDiagram Warren -- Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Eye patterns (Heat plot?)
From: Russ Dill [mailto:russ.d...@gmail.com] Sent: Saturday, January 21, 2012 16:31 I'm using matplotlib from pylab to generate eye patterns for signal simulations. ... Is there any way within matplotlib to do that right now? One way combines Numpy's histogram2d and matplotlib's imshow, as in the example in the histogram2d docs [1]. The example's x array should become all of the time samples in your traces, strung together in one dimension; the y array, the corresponding voltage samples. If you have certain structure, such as a regular and consistent grid of times, you might instead construct a series of vertical, 1-d histograms (paying attention to normalization); column-stack them into the final 2-d histogram; and again plot with imshow. [1] http://docs.scipy.org/doc/numpy-1.6.0/reference/generated/numpy.histogram2d.ht ml -- Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Eye patterns (Heat plot?)
On Mon, Jan 23, 2012 at 11:17 AM, Stan West stan.w...@nrl.navy.mil wrote: From: Russ Dill [mailto:russ.d...@gmail.com] Sent: Saturday, January 21, 2012 16:31 I'm using matplotlib from pylab to generate eye patterns for signal simulations. ... Is there any way within matplotlib to do that right now? One way combines Numpy's histogram2d and matplotlib's imshow, as in the example in the histogram2d docs [1]. The example's x array should become all of the time samples in your traces, strung together in one dimension; the y array, the corresponding voltage samples. I'll try it out and see what I get, but I don't think it will work so well. The problem is that while the data is made up of x/y samples, it actually represents a line. The samples should be evenly distributed not along the x or y axis, but along the length of the line. I feel like I'll need a line drawing algorithm. (For example, if samples are evenly distributed along the x axis, a 89 degree line is highly under-represented, but a 1 degree line is highly over-represented. The number of samples should be sqrt(dx^2 + dy^2), but with evenly spaced x samples, its just dx. -- Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Eye patterns (Heat plot?)
On 1/23/2012 1:55 PM, Russ Dill wrote: On Mon, Jan 23, 2012 at 11:17 AM, Stan Weststan.w...@nrl.navy.mil wrote: From: Russ Dill [mailto:russ.d...@gmail.com] Sent: Saturday, January 21, 2012 16:31 I'm using matplotlib from pylab to generate eye patterns for signal simulations. ... Is there any way within matplotlib to do that right now? One way combines Numpy's histogram2d and matplotlib's imshow, as in the example in the histogram2d docs [1]. The example's x array should become all of the time samples in your traces, strung together in one dimension; the y array, the corresponding voltage samples. I'll try it out and see what I get, but I don't think it will work so well. The problem is that while the data is made up of x/y samples, it actually represents a line. The samples should be evenly distributed not along the x or y axis, but along the length of the line. I feel like I'll need a line drawing algorithm. (For example, if samples are evenly distributed along the x axis, a 89 degree line is highly under-represented, but a 1 degree line is highly over-represented. The number of samples should be sqrt(dx^2 + dy^2), but with evenly spaced x samples, its just dx. I don't know of a way to directly produce the LeCroy heatmap in Python, so here's my idea for a hack: *Each sample point you have from the trace represents a point in XY coordinates. *Similarly, the plot area is filled with regularly spaced XY coordinates. *Every trace sample will fall within a square bounding box with four points. *Each plot area point gets a membership value, based on distance between centers of the sample point and the plot area point. *To construct the heat diagram, sum the membership values of all sample points for all traces. *Display it with a contour plot, but without the isovalue lines. -Ethan -- Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Eye patterns (Heat plot?)
On Mon, Jan 23, 2012 at 1:46 PM, Ethan Swint esw...@vt.edu wrote: On 1/23/2012 1:55 PM, Russ Dill wrote: On Mon, Jan 23, 2012 at 11:17 AM, Stan Weststan.w...@nrl.navy.mil wrote: From: Russ Dill [mailto:russ.d...@gmail.com] Sent: Saturday, January 21, 2012 16:31 I'm using matplotlib from pylab to generate eye patterns for signal simulations. ... Is there any way within matplotlib to do that right now? One way combines Numpy's histogram2d and matplotlib's imshow, as in the example in the histogram2d docs [1]. The example's x array should become all of the time samples in your traces, strung together in one dimension; the y array, the corresponding voltage samples. I'll try it out and see what I get, but I don't think it will work so well. The problem is that while the data is made up of x/y samples, it actually represents a line. The samples should be evenly distributed not along the x or y axis, but along the length of the line. I feel like I'll need a line drawing algorithm. (For example, if samples are evenly distributed along the x axis, a 89 degree line is highly under-represented, but a 1 degree line is highly over-represented. The number of samples should be sqrt(dx^2 + dy^2), but with evenly spaced x samples, its just dx. I don't know of a way to directly produce the LeCroy heatmap in Python, so here's my idea for a hack: *Each sample point you have from the trace represents a point in XY coordinates. *Similarly, the plot area is filled with regularly spaced XY coordinates. *Every trace sample will fall within a square bounding box with four points. *Each plot area point gets a membership value, based on distance between centers of the sample point and the plot area point. *To construct the heat diagram, sum the membership values of all sample points for all traces. *Display it with a contour plot, but without the isovalue lines. -Ethan matplotlib also has hexbin() if that helps. http://matplotlib.sourceforge.net/api/axes_api.html?highlight=hexbin#matplotlib.axes.Axes.hexbin Ben Root -- Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Eye patterns (Heat plot?)
Hi Russ, Russ Dill, on 2012-01-21 13:30, wrote: I'm using matplotlib from pylab to generate eye patterns for signal simulations. My output pretty much looks like this: http://www.flickr.com/photos/31208937@N06/6079131690/ Its pretty useful as it allows one to quickly see the size of the eye opening, the maximum/minimum voltage, etc. I'd really like to be able to create a heat diagram, like these: http://www.lecroy.com/images/oscilloscope/series/waveexpert/opening-spread2_lg.jpg http://www.lecroy.com/images/oscilloscope/series/waveexpert/opening-spread1_lg.jpg http://www.iec.org/newsletter/august07_2/imgs/bb2_fig_1.gif http://www.altera.com/devices/fpga/stratix-fpgas/stratix-ii/stratix-ii-gx/images/s2gx-rollout-6g-eye.jpg Is there any way within matplotlib to do that right now? the quick and dirty way to get close to what you want is to add an alpha value to the lines you're already plotting. Here's a small example: x = np.arange(0,3,.01) y = np.sin(x**2) all_x,all_y = [],[] ax = plt.gca() for i in range(100): noisex = np.random.randn(1)*.04 noisey = (np.random.randn(x.shape[0])*.2)**3 ax.plot(x+noisex,y+noisey, color='b', alpha=.01) all_x.append(x+noisex) all_y.append(y+noisey) To get a heat diagram, as was suggested, you can use a 2d histogram. plt.figure() all_x =np.array(all_x) all_y = np.array(all_y) all_x.shape = all_y.shape = -1 H, yedges, xedges = np.histogram2d(all_y, all_x, bins=100) extent = [xedges[0], xedges[-1], yedges[-1], yedges[0]] ax = plt.gca() plt.hot() ax.imshow(H, extent=extent, interpolation='nearest') ax.invert_yaxis() I'm attaching the two images for reference best, -- Paul Ivanov 314 address only used for lists, off-list direct email at: http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 attachment: heatmap.pngattachment: alpha-poorman.png-- Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
