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From: Virgil Stokes <vs@it...>  20110325 23:46:05

I have used the following code (taken from a matplotlib example) to produce a 3D plot of planar polygons, from mpl_toolkits.mplot3d import Axes3D from matplotlib.collections import PolyCollection from matplotlib.colors import colorConverter import matplotlib.pyplot as plt import numpy as np np.random.seed(40040157) # Used to allow repeatable experiments (plots) fig = plt.figure() ax = fig.gca(projection='3d') cc = [colorConverter.to_rgba(c,alpha=0.6) for c in ('r','g','b','c','y','m','k')] ncc = len(cc) nxs = 5 xs = np.arange(1, nxs+1, 1) # (X's) # Add boundary X's xs = np.insert(xs,0,1); xs = np.append(xs,nxs) # Create array for Z's ys = np.zeros(len(xs)) # Create list for all Y's npolys = 9 zs = [zs+1 for zs in range(npolys)] # Y coordinates (list of integers) # Create list of colors (cyclic) for all polygons colorlist = [cc[j%ncc] for j in range(npolys)] verts = [] # Generate vertices for polygons for j in zs: # loop on polys ys = np.random.rand(len(ys)) ys[0], ys[1] = 0,0 # end points for filled polygons (1,0),(n,0) verts.append(zip(xs, ys)) poly = PolyCollection(verts, facecolors = colorlist) poly.set_alpha(0.7) ax.add_collection3d(poly, zs=zs, zdir='y') # Righthanded coordinate system ax.set_xlabel('X') # points to right (X) ax.set_xlim3d(0, nxs+1) ax.set_ylabel('Y') # points into screen (Y) ax.set_ylim3d(0, npolys+1) ax.set_zlabel('Z') # points up (Z) ax.set_zlim3d(0, 1) plt.show() and this works fine. I then tried to produce a 3D plot of the same form as this one,*but with only the top of the polygons plotted* (4 connected line segments for each of the 9 polygons). I thought this would be easily accomplished, by replacing PolyCollection with LineCollection. However, I have been unable to produce a 3D plot for line segments connecting the tops of the polygons. Note, I am using Python 2.6.6, numpy 1.5.1, and matplotlib 1.0.1. Any help on producing 3D line segment plot would be appreciated. 
From: Lebostein <Lebostein@gm...>  20110325 21:30:52

Hi, if I create an eps from a matplotlib chart with matplot.rc('font', size=fsize, family='serif', serif='Computer Modern Roman') matplot.rc('text', usetex = True) matplot.rc('text.latex', unicode = True) then I can't mark the letters in eps viewer. And I can't search for letters and words in the eps. It seems, the letters are curves in the eps. Why? If I create a pdf, I can mark letters and words an I can search too. How I can create an eps output with embedded font and "real" letters?  View this message in context: http://old.nabble.com/usetex%3DTrue%2Bepsoutput%3Elettersareonlycurvestp31242096p31242096.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: ai1836 <lena1990@li...>  20110325 20:54:26

Hello there I am trying to put together matplotlib1.0.1win32py2.6, numpy1.5.1win32superpackpython2.6 and scipy0.9.0rc1win32superpackpython2.6 for py2.6.6. When I run my file through eclipse I get this error: Traceback (most recent call last): File "C:\Documents and Settings\Colby Student\Desktop\fungi\src\display.py", line 8, in <module> import pylab as pl File "C:\Python26\lib\sitepackages\pylab.py", line 1, in <module> from matplotlib.pylab import * File "C:\Python26\lib\sitepackages\matplotlib\pylab.py", line 220, in <module> from matplotlib import mpl # pulls in most modules File "C:\Python26\lib\sitepackages\matplotlib\mpl.py", line 1, in <module> from matplotlib import artist File "C:\Python26\lib\sitepackages\matplotlib\artist.py", line 6, in <module> from transforms import Bbox, IdentityTransform, TransformedBbox, TransformedPath File "C:\Python26\lib\sitepackages\matplotlib\transforms.py", line 34, in <module> from matplotlib._path import affine_transform ImportError: DLL load failed: The system cannot find the file specified. How can I deal with it? Please, help :(  View this message in context: http://old.nabble.com/importerrorofaffine_transformfrommatplotlib._pathtp31241831p31241831.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: unit <e_redekop@ya...>  20110325 20:20:55

Dear All, I can't figure out how to make the grid and axes lines more apparent in 3D plot created by Axes3D. Similar problem was posted a while ago (http://old.nabble.com/Howtomake3Daxesgridmorevisibletd28917367.html#a28917367) but there was no resolution. I know how to turn the grid on/off. But is there any way to set the width/color of the grid lines? Because when I save the plot with default gray lines, they are almost invisible. Thanks a lot for advice!  View this message in context: http://old.nabble.com/Howtocontrolgridpropertiesin3Dtp31206307p31206307.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Paul Ivanov <pivanov314@gm...>  20110325 19:01:41

Georges Arsouze, on 20110316 09:48, wrote: > Hello > I'am working with Python3.1 under Mac Os Snow Leopard > I download matplotlib with > http://www.cgl.ucsf.edu/Outreach/pc204/matplotlib.html > > It doesn't work > Can you help me ? Hi Georges, What version of matplotlib are you trying to run? At the moment, there isn't a "stable" release which is compatible with Python 3, and you have to grab it from: https://github.com/matplotlib/matplotlibpy3 Not all of the backends work in py3, mostly because the underlying toolkits have not been ported to Python 3. You can notes about the work in progress, what's been completed, and what's left to do here: https://github.com/matplotlib/matplotlibpy3/wiki (Also, this is more of a matplotlibusers question, so I'm replying to that list) best,  Paul Ivanov 314 address only used for lists, offlist direct email at: http://pirsquared.org  GPG/PGP key id: 0x0F3E28F7 
From: Andre' WalkerLoud <walksloud@gm...>  20110325 16:14:02

Hi Chris, I think I understand what you are asking. I think the key point is I have used "np.histogram" where you are using "np.hist" When I make my plots, I use np.hist, but then to access the data, I use np.histogram. Just to demonstrate, incase this is not what you want, I have found, if I create a bin > bin = np.histogram(binData,range=(ymin,ymax),weights=binQ,bins=np.arange(ymin,ymax,dm0/4)) where > ind = np.argsort(my_data) # list to order the data from low to high > binDat = my_data[ind] > binQ = weights[ind] / np.sum(weights) #ordered list of weight factors for the data (for a weighted distribution. example, if you have data with uncertainties, the weights are given by the inverse uncertainties) and ymin, ymax and dm0 are params I have specified (based on the data) to set the bin size and range of bins The pdf, in this case, is given by pdf[i] = binQ[i]. I can then access this with > bin[0][i] #this is the i'th weight (the pdf at i) also, the data (the x values) can be accessed by > bin[1][i] At the very least, this gives a poorworking man's solution. I couldn't figure out how to get it from np.hist. Andre On Mar 24, 2011, at 8:47 PM, Chris Edwards wrote: > Hi, > > I would like to access values in the bins of a matplotlib histogram. The following example script is an attempt to do this. Clearly pdf contains floating point numbers, but I am unable to access them. > > Help with this problem would be much appreciated. > > Chris > >  > import numpy as np > import matplotlib.pyplot as plt > fig = plt.figure() > ax = fig.add_subplot(111) > > mu, sigma = 100, 15 > x = mu + sigma * np.random.randn(20) > > #Generate the histogram of the data. Example from Matplotlib documentation > > n, bins, patches = plt.hist(x, 50, normed=True, facecolor='g', alpha=0.75) > plt.xlabel('Smarts') > plt.ylabel('Probability') > plt.title('Histogram of IQ') > plt.text(60, .025, r'$\mu=100,\ \sigma=15$') > plt.axis([40, 160, 0, 0.03]) > plt.grid(True) > > #From Matplotlib documentation. > #normed: If True, the first element of the return tuple will be the counts normalized > #to form a probability density, i.e., n/(len(x)*dbin). In a probability density, > #the integral of the histogram should be 1; you can verify that with a trapezoidal > #integration of the probability density function. > > pdf, bins, patches = ax.hist(x, 50, normed=True, facecolor='g', alpha=0.75) > > #print pdf shows pdf contains the value in each bin of the normed histogram > > print "pdf = ", pdf > > print " Integration of PDF = ", np.sum(pdf * np.diff(bins)) > > #How to access values in pdf? Various tries made but none successful. Example attempt shown > > count=0 > for line in open(pdf,'r+'): > x=pdf.readline() > z=('%.10f' % float(x)) > count=count+1 > print "count = ", count > >  >  > Enable your software for Intel(R) Active Management Technology to meet the > growing manageability and security demands of your customers. Businesses > are taking advantage of Intel(R) vPro (TM) technology  will your software > be a part of the solution? Download the Intel(R) Manageability Checker > today! http://p.sf.net/sfu/inteldev2devmar > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers 
From: Giovanni Luca Ciampaglia <junkie.dolphin@gm...>  20110325 16:01:59

Ah, sorry for the duplicate message! Cheers, G On 15/03/2011 11:30, Giovanni Luca Ciampaglia wrote: > Hi all, > I call savefig by passing to it a filelike object but it appears to not > get the graphics format right: > > f = open('not_a_pdf.pdf', 'w') > plot([1,2,3]) > savefig(f) > > but it produces a PNG image. Can anybody confirm this? I am on > matplotlib 0.99.3 > > Cheers, 
From: Jim Ford <jford14685@gm...>  20110325 15:25:36

Well, what do you know? For once, the call of the noob, "Hey! there must be a bug" speaks truth. Thanks, Angus! I added a little code to duplicate the last point until the array length is at least 5, and everything looks just fine. On 03/25/2011 01:10 PM, Angus McMorland wrote: > On 25 March 2011 07:31, jford14685<jford14685@...> wrote: >> I am a newbie Python programmer trying to make 3d barplots like >> http://matplotlib.sourceforge.net/examples/mplot3d/bars3d_demo.html this >> one on the Matplotlib site. >> >> When I run the demo source (python bars3d_demo.py) it works fine. I then >> changed the way xs and ys are assigned, to >> xs = np.array([1.,2.,3.]) # was xs = np.arange(20) >> ys = np.array([1.,2.,3.]) # was ys = np.random.rand(20) >> ax.bar(xs, ys, zs=1, zdir='y', color='r', alpha=0.8) >> (ditto for two other data sets) >> >> Now the bars are triangles. The right side of each bar is of the correct >> height, but the left side of each bar starts at zero. > Here's another data point. My guess is this is a bug with Axes3D: I > can recreate the problem with 3 bars, but with>4 bars everything > works okay. On my setup, with exactly 4 bars, the leftmost edge of the > bars doesn't get a border, so something possibly related is going on > there too. > > Angus. 
From: Fabrice Silva <silva@lm...>  20110325 15:21:13

Le mardi 15 mars 2011 à 11:30 +0100, Giovanni Luca Ciampaglia a écrit : > Hi all, > I call savefig by passing to it a filelike object but it appears to not > get the graphics format right: > > f = open('not_a_pdf.pdf', 'w') > plot([1,2,3]) > savefig(f) > > but it produces a PNG image. Can anybody confirm this? I am on > matplotlib 0.99.3 > > Cheers, You may give savefig a filename (string 'tmp.pdf') instead of the file descriptor (file object f), or use the format keyword argument. Automatic format selection is not handled for file object (as visible in backend_bases.py:FigureCanvasBase.print_figure method).  Fabrice 
From: Mike Kaufman <mckauf@gm...>  20110325 12:13:39

What the best way to to use data coordinates rather than axes coordinates for xmin and xmax with axhline? Here's my kludgy solution, but it's not elegant: plot(arange(20)) ax = gca() inv = ax.transAxes.inverted() x = inv.transform(ax.transData.transform([10,0])) ax.axhline(10, xmax=x[0]) I tried doing this: ax.axhline(15, xmax=15, transform=ax.transData) but I get: ValueError: 'transform' is not allowed as a kwarg;axhline generates its own transform. which is a bit strange since transform is listed in the kwargs in the help, though there is also this: Valid kwargs are :class:`~matplotlib.lines.Line2D` properties, with the exception of 'transform': which could have two meanings: one is that all the kwargs listed are Line2D properties except 'transform' which is a valid kwarg, but not a Line2D property, OR even though 'transform' is listed, it's not a valid kwarg. Somewhat confusing especially given the ValueError... M 
From: Angus McMorland <amcmorl@gm...>  20110325 12:11:14

On 25 March 2011 07:31, jford14685 <jford14685@...> wrote: > I am a newbie Python programmer trying to make 3d barplots like > http://matplotlib.sourceforge.net/examples/mplot3d/bars3d_demo.html this > one on the Matplotlib site. > > When I run the demo source (python bars3d_demo.py) it works fine. I then > changed the way xs and ys are assigned, to > xs = np.array([1.,2.,3.]) # was xs = np.arange(20) > ys = np.array([1.,2.,3.]) # was ys = np.random.rand(20) > ax.bar(xs, ys, zs=1, zdir='y', color='r', alpha=0.8) > (ditto for two other data sets) > > Now the bars are triangles. The right side of each bar is of the correct > height, but the left side of each bar starts at zero. Here's another data point. My guess is this is a bug with Axes3D: I can recreate the problem with 3 bars, but with >4 bars everything works okay. On my setup, with exactly 4 bars, the leftmost edge of the bars doesn't get a border, so something possibly related is going on there too. Angus.  AJC McMorland Postdoctoral research fellow Neurobiology, University of Pittsburgh 
From: Angus McMorland <amcmorl@gm...>  20110325 11:53:12

Thanks Paul, On 24 March 2011 19:23, Paul Ivanov <pivanov314@...> wrote: > I think you can get the desired functionality with gridspec > alone. Take a look at > doc/users/plotting/examples/demo_gridspec06.py which you can find > here > > https://github.com/matplotlib/matplotlib/blob/f1c8/doc/users/plotting/examples/demo_gridspec06.py I've played around with this example, and it seems like I'm not quite there yet. I should add that I'm using imshow rather than plot here. In this case, the interinnergrid spacing becomes dependent on the figure aspect ratio. I presume this is because it is trying to maintain (as it should) the aspect ratio of the images, but it would be nice for it do this my manipulating only the outside margins, and honour the wspace=0., hspace=0. as requested. Here's a simplified version of the above script to illustrate my point: import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec import numpy as np from itertools import product f = plt.figure(figsize=(9, 9)) # gridspec inside gridspec outer_grid = gridspec.GridSpec(2, 3, wspace=0.0, hspace=0.0) for i in xrange(6): inner_grid = gridspec.GridSpecFromSubplotSpec(3, 3, subplot_spec=outer_grid[i], wspace=0.0, hspace=0.0) for j, (c, d) in enumerate(product(range(1, 4), repeat=2)): ax = plt.Subplot(f, inner_grid[j]) ax.imshow(np.ones((10,10)) * c * d, vmin=1, vmax=9) ax.set_xticks([]) ax.set_yticks([]) f.add_subplot(ax) all_axes = f.get_axes() #show only the outside spines for ax in all_axes: for sp in ax.spines.values(): sp.set_visible(False) if ax.is_first_row(): ax.spines['top'].set_visible(True) if ax.is_last_row(): ax.spines['bottom'].set_visible(True) if ax.is_first_col(): ax.spines['left'].set_visible(True) if ax.is_last_col(): ax.spines['right'].set_visible(True) plt.show() Of course, it is relatively trivial to calculate the correct figure aspect ratio in this case, but after adding in other elements like labels, this can become problematic. Is it possible to specify exactly the inner spacing, and make the outer margins automatically adjusted to get everything to fit nicely? Thanks, Angus  AJC McMorland Postdoctoral research fellow Neurobiology, University of Pittsburgh 
From: jford14685 <jford14685@gm...>  20110325 11:31:59

I am a newbie Python programmer trying to make 3d barplots like http://matplotlib.sourceforge.net/examples/mplot3d/bars3d_demo.html this one on the Matplotlib site. When I run the demo source (python bars3d_demo.py) it works fine. I then changed the way xs and ys are assigned, to xs = np.array([1.,2.,3.]) # was xs = np.arange(20) ys = np.array([1.,2.,3.]) # was ys = np.random.rand(20) ax.bar(xs, ys, zs=1, zdir='y', color='r', alpha=0.8) (ditto for two other data sets) Now the bars are triangles. The right side of each bar is of the correct height, but the left side of each bar starts at zero. Python version 2.6.5 Matplotlib version 1.0.1 Ubuntu 10.04 Thanks in advance! Complete source of my (misbehaving) program: from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') xs = np.array([1.,2.,3.]) ys = np.array([1.,2.,3.]) ax.bar(xs, ys, zs=1, zdir='y', color='r', alpha=0.8) ys = np.array([1.,4.,9.]) ax.bar(xs, ys, zs=2, zdir='y', color='r', alpha=0.8) ys = np.array([2.,1.,2.]) ax.bar(xs, ys, zs=3, zdir='y', color='r', alpha=0.8) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') plt.show()  View this message in context: http://old.nabble.com/rampshapedbarstp31236873p31236873.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Chris Edwards <cbhe@oz...>  20110325 03:48:08

Hi, I would like to access values in the bins of a matplotlib histogram. The following example script is an attempt to do this. Clearly pdf contains floating point numbers, but I am unable to access them. Help with this problem would be much appreciated. Chris  import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(111) mu, sigma = 100, 15 x = mu + sigma * np.random.randn(20) #Generate the histogram of the data. Example from Matplotlib documentation n, bins, patches = plt.hist(x, 50, normed=True, facecolor='g', alpha=0.75) plt.xlabel('Smarts') plt.ylabel('Probability') plt.title('Histogram of IQ') plt.text(60, .025, r'$\mu=100,\ \sigma=15$') plt.axis([40, 160, 0, 0.03]) plt.grid(True) #From Matplotlib documentation. #normed: If True, the first element of the return tuple will be the counts normalized #to form a probability density, i.e., n/(len(x)*dbin). In a probability density, #the integral of the histogram should be 1; you can verify that with a trapezoidal #integration of the probability density function. pdf, bins, patches = ax.hist(x, 50, normed=True, facecolor='g', alpha=0.75) #print pdf shows pdf contains the value in each bin of the normed histogram print "pdf = ", pdf print " Integration of PDF = ", np.sum(pdf * np.diff(bins)) #How to access values in pdf? Various tries made but none successful. Example attempt shown count=0 for line in open(pdf,'r+'): x=pdf.readline() z=('%.10f' % float(x)) count=count+1 print "count = ", count  