From: Dr. Phillip M. Feldman <pfeldman@ve...>  20091024 18:02:21

I'd like to create a plot showing motor current, efficiency, speed, and output power versus input power, with all four curves on a single plot and four y axes. I've looked at the example in http://matplotlib.sourceforge.net/examples/api/two_scales.html, and also at the doc string for twinx. It looks as though twinx will let me create two y axes, but in this case I need four. Can this be done with matplotlib?  View this message in context: http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26041500.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Dr. Phillip M. Feldman <pfeldman@ve...>  20091024 18:02:21

I'd like to create a plot showing motor current, efficiency, speed, and output power versus input power, with all four curves on a single plot and four y axes. I've looked at the example in http://matplotlib.sourceforge.net/examples/api/two_scales.html, and also at the doc string for twinx. It looks as though twinx will let me create two y axes, but in this case I need four. Can this be done with matplotlib?  View this message in context: http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26041500.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Gökhan Sever <gokhansever@gm...>  20091024 18:40:38
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On Sat, Oct 24, 2009 at 1:02 PM, Dr. Phillip M. Feldman < pfeldman@...> wrote: > > I'd like to create a plot showing motor current, efficiency, speed, and > output power versus input power, with all four curves on a single plot and > four y axes. I've looked at the example in > http://matplotlib.sourceforge.net/examples/api/two_scales.html, and also > at > the doc string for twinx. It looks as though twinx will let me create two y > axes, but in this case I need four. Can this be done with matplotlib? >  > View this message in context: > http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26041500.html > Sent from the matplotlib  users mailing list archive at Nabble.com. > > > Using axes_grid you can get multiple yaxes. See for example: http://matplotlib.sourceforge.net/examples/axes_grid/demo_parasite_axes2.html > >  > Come build with us! The BlackBerry(R) Developer Conference in SF, CA > is the only developer event you need to attend this year. Jumpstart your > developing skills, take BlackBerry mobile applications to market and stay > ahead of the curve. Join us from November 9  12, 2009. Register now! > http://p.sf.net/sfu/devconference > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers >  Gökhan 
From: JaeJoon Lee <lee.joon@gm...>  20091025 23:42:56

Using axes_grid toolkit is not recommended unless you're familiar with some of the internals of matplotlib. Instead, you should use spines. While the current example gallery does not have such an example, I just added one in the svn. The result should be identical to the axes_grid example. While not tested, I believe the example will work fine with matplotlib 0.99.1. http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup Regards, JJ On Sat, Oct 24, 2009 at 2:40 PM, Gökhan Sever <gokhansever@...> wrote: > > > On Sat, Oct 24, 2009 at 1:02 PM, Dr. Phillip M. Feldman > <pfeldman@...> wrote: >> >> I'd like to create a plot showing motor current, efficiency, speed, and >> output power versus input power, with all four curves on a single plot and >> four y axes. I've looked at the example in >> http://matplotlib.sourceforge.net/examples/api/two_scales.html, and also >> at >> the doc string for twinx. It looks as though twinx will let me create two >> y >> axes, but in this case I need four. Can this be done with matplotlib? >>  >> View this message in context: >> http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26041500.html >> Sent from the matplotlib  users mailing list archive at Nabble.com. >> >> > > Using axes_grid you can get multiple yaxes. See for example: > > http://matplotlib.sourceforge.net/examples/axes_grid/demo_parasite_axes2.html > > > >> >> >>  >> Come build with us! The BlackBerry(R) Developer Conference in SF, CA >> is the only developer event you need to attend this year. Jumpstart your >> developing skills, take BlackBerry mobile applications to market and stay >> ahead of the curve. Join us from November 9  12, 2009. Register now! >> http://p.sf.net/sfu/devconference >> _______________________________________________ >> Matplotlibusers mailing list >> Matplotlibusers@... >> https://lists.sourceforge.net/lists/listinfo/matplotlibusers > > > >  > Gökhan > >  > Come build with us! The BlackBerry(R) Developer Conference in SF, CA > is the only developer event you need to attend this year. Jumpstart your > developing skills, take BlackBerry mobile applications to market and stay > ahead of the curve. Join us from November 9  12, 2009. Register now! > http://p.sf.net/sfu/devconference > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers > > 
From: Dr. Phillip M. Feldman <pfeldman@ve...>  20091028 00:05:31

I've noticed that make_patch_spines_invisible does not use the input argument `ax`. Shouldn't the body of the function def be using `ax` instead of `par2`? Thanks! Phillip <snip> http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup Regards, JJ  View this message in context: http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26087257.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Dr. Phillip M. Feldman <pfeldman@ve...>  20091028 02:07:59

JaeJoon and Gokhan Thanks very much to both of you for the help with this! I've been trying to create a template plotting program for the students in the Engineering Academy at Dos Pueblos High School. This program has to be able to create plots with 2, 3, or 4 y axes. The idea is that the students would only have to insert their data into the code and change the variable names to be able to generate plots. I've created something that does almost exactly what they need, except that there is glitch that I have not been able to fix. In the attached plot, not that the tick marks and labels for the first y axis appear on both the right and the left. I have tried various things, but have not been able to suppress the copy on the right without also suppressing the ones on the left. Any suggestions will be appreciated. Phillip http://www.nabble.com/file/p26088227/multiple_yaxes_with_spines.py multiple_yaxes_with_spines.py http://www.nabble.com/file/p26088227/multiple_yaxes_with_spines.png multiple_yaxes_with_spines.png JaeJoon Lee wrote: > > Using axes_grid toolkit is not recommended unless you're familiar with > some of the internals of matplotlib. Instead, you should use spines. > While the current example gallery does not have such an example, I > just added one in the svn. > The result should be identical to the axes_grid example. While not > tested, I believe the example will work fine with matplotlib 0.99.1. > > http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup > > Regards, > > JJ > > > On Sat, Oct 24, 2009 at 2:40 PM, Gökhan Sever <gokhansever@...> > wrote: >> >> >> On Sat, Oct 24, 2009 at 1:02 PM, Dr. Phillip M. Feldman >> <pfeldman@...> wrote: >>> >>> I'd like to create a plot showing motor current, efficiency, speed, and >>> output power versus input power, with all four curves on a single plot >>> and >>> four y axes. I've looked at the example in >>> http://matplotlib.sourceforge.net/examples/api/two_scales.html, and also >>> at >>> the doc string for twinx. It looks as though twinx will let me create >>> two >>> y >>> axes, but in this case I need four. Can this be done with matplotlib? >>>  >>> View this message in context: >>> http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26041500.html >>> Sent from the matplotlib  users mailing list archive at Nabble.com. >>> >>> >> >> Using axes_grid you can get multiple yaxes. See for example: >> >> http://matplotlib.sourceforge.net/examples/axes_grid/demo_parasite_axes2.html >> >> >> >>> >>> >>>  >>> Come build with us! The BlackBerry(R) Developer Conference in SF, CA >>> is the only developer event you need to attend this year. Jumpstart your >>> developing skills, take BlackBerry mobile applications to market and >>> stay >>> ahead of the curve. Join us from November 9  12, 2009. Register now! >>> http://p.sf.net/sfu/devconference >>> _______________________________________________ >>> Matplotlibusers mailing list >>> Matplotlibusers@... >>> https://lists.sourceforge.net/lists/listinfo/matplotlibusers >> >> >> >>  >> Gökhan >> >>  >> Come build with us! The BlackBerry(R) Developer Conference in SF, CA >> is the only developer event you need to attend this year. Jumpstart your >> developing skills, take BlackBerry mobile applications to market and stay >> ahead of the curve. Join us from November 9  12, 2009. Register now! >> http://p.sf.net/sfu/devconference >> _______________________________________________ >> Matplotlibusers mailing list >> Matplotlibusers@... >> https://lists.sourceforge.net/lists/listinfo/matplotlibusers >> >> > >  > Come build with us! The BlackBerry(R) Developer Conference in SF, CA > is the only developer event you need to attend this year. Jumpstart your > developing skills, take BlackBerry mobile applications to market and stay > ahead of the curve. Join us from November 9  12, 2009. Register now! > http://p.sf.net/sfu/devconference > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers > >  View this message in context: http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26088227.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Dr. Phillip M. Feldman <pfeldman@ve...>  20091028 02:09:29

Here's my code (now nicely organized and documented, but still buggy): # multiple_yaxes_with_spines.py # This is a template Python program for creating plots (line graphs) with 2, 3, # or 4 yaxes. (A template program is one that you can readily modify to meet # your needs). Almost all usermodifiable code is in Section 2. For most # purposes, it should not be necessary to modify anything else. # Dr. Phillip M. Feldman, 27 Oct, 2009 # Acknowledgment: This program is based on code written by JaeJoon Lee, # URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/ # examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup # Section 1: Import modules, define functions, and allocate storage. import matplotlib.pyplot as plt from numpy import * def make_patch_spines_invisible(ax): ax.set_frame_on(True) ax.patch.set_visible(False) for sp in ax.spines.itervalues(): sp.set_visible(False) def make_spine_invisible(ax, direction): if direction in ["right", "left"]: ax.yaxis.set_ticks_position(direction) ax.yaxis.set_label_position(direction) elif direction in ["top", "bottom"]: ax.xaxis.set_ticks_position(direction) ax.xaxis.set_label_position(direction) else: raise ValueError("Unknown Direction : %s" % (direction,)) ax.spines[direction].set_visible(True) # Create list to store dependent variable data: y= [0, 0, 0, 0, 0] # Section 2: Define names of variables and the data to be plotted. # `labels` stores the names of the independent and dependent variables). The # first (zeroth) item in the list is the xaxis label; remaining labels are the # first yaxis label, second yaxis label, and so on. There must be at least # two dependent variables and not more than four. labels= ['Indep. Variable', 'Dep. Variable #1', 'Dep. Variable #2', 'Dep. Variable #3', 'Dep. Variable #4'] # Plug in your data here, or code equations to generate the data if you wish to # plot mathematical functions. x stores values of the independent variable; # y[1], y[2], ... store values of the dependent variable. (y[0] is not used). # All of these objects should be NumPy arrays. # If you are plotting mathematical functions, you will probably want an array of # uniformly spaced values of x; such an array can be created using the # `linspace` function. For example, to define x as an array of 51 values # uniformly spaced between 0 and 2, use the following command: # x= linspace(0., 2., 51) # Here is an example of 6 experimentally measured y1values: # y[1]= array( [3, 2.5, 7.3e4, 4, 8, 3] ) # Note that the above statement requires both parentheses and square brackets. # With a bit of work, one could make this program read the data from a text file # or Excel worksheet. # Independent variable: x = linspace(0., 2., 51) # First dependent variable: y[1]= sqrt(x) # Second dependent variable: y[2]= 0.2 + x**0.3 y[3]= 30.*sin(1.5*x) y[4]= 30.*abs(cos(1.5*x)) # Set line colors here; each color can be specified using a singleletter color # identifier ('b'= blue, 'r'= red, 'g'= green, 'k'= black, 'y'= yellow, # 'm'= magenta, 'y'= yellow), an RGB tuple, or almost any standard English color # name written without spaces, e.g., 'darkred'. The first element of this list # is not used. colors= [' ', 'b', 'darkred', 'g', 'magenta'] # Set the line width here. linewidth=2 is recommended. linewidth= 2 # Section 3: Generate the plot. N_dependents= len(labels)  1 if N_dependents > 4: raise Exception, \ 'This code currently handles a maximum of four independent variables.' # Open a new figure window, setting the size to 10by7 inches and the facecolor # to white: fig= plt.figure(figsize=(10,7), dpi=120, facecolor=[1,1,1]) host= fig.add_subplot(111) host.set_xlabel(labels[0]) # Use twinx() to create extra axes for all dependent variables except the first # (we get the first as part of the host axes). The first element of y_axis is # not used. y_axis= (N_dependents+2) * [0] y_axis[1]= host for i in range(2,len(labels)+1): y_axis[i]= host.twinx() if N_dependents >= 3: # The following statement positions the third yaxis to the right of the # frame, with the space between the frame and the axis controlled by the # numerical argument to set_position; this value should be between 1.10 and # 1.2. y_axis[3].spines["right"].set_position(("axes", 1.15)) make_patch_spines_invisible(y_axis[3]) make_spine_invisible(y_axis[3], "right") plt.subplots_adjust(left=0.0, right=0.8) if N_dependents >= 4: # The following statement positions the fourth yaxis to the left of the # frame, with the space between the frame and the axis controlled by the # numerical argument to set_position; this value should be between 1.10 and # 1.2. y_axis[4].spines["left"].set_position(("axes", 0.15)) make_patch_spines_invisible(y_axis[4]) make_spine_invisible(y_axis[4], "left") plt.subplots_adjust(left=0.2, right=0.8) p= (N_dependents+1) * [0] # Plot the curves: for i in range(1,N_dependents+1): p[i], = y_axis[i].plot(x, y[i], colors[i], linewidth=linewidth, label=labels[i]) # Set axis limits. Use ceil() to force upper yaxis limits to be round numbers. host.set_xlim(x.min(), x.max()) host.set_xlabel(labels[0], size=16) for i in range(1,N_dependents+1): y_axis[i].set_ylim(0.0, ceil(y[i].max())) y_axis[i].set_ylabel(labels[i], size=16) y_axis[i].yaxis.label.set_color(colors[i]) for obj in y_axis[i].yaxis.get_ticklines(): # `obj` is a matplotlib.lines.Line2D instance obj.set_color(colors[i]) obj.set_markeredgewidth(3) for obj in y_axis[i].yaxis.get_ticklabels(): obj.set_color(colors[i]) obj.set_size(12) obj.set_weight(600) # To get rid of the legend, comment out the following two lines: lines= p[1:] host.legend(lines, [l.get_label() for l in lines]) plt.draw(); plt.show()  View this message in context: http://www.nabble.com/Possibletogetfouryaxesonasingleplottp26041500p26088240.html Sent from the matplotlib  users mailing list archive at Nabble.com. 
From: Phillip M. Feldman <pfeldman@ve...>  20091027 23:18:26
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multiple_yaxes_with_spines.png

# The following sample code can be used to create a plot (line graph) with # 2, 3, or 4 yaxes. All usermodifiable code is in Section 2. Modify # anything else only if you know what you are doing or are feeling very lucky! # Dr. Phillip M. Feldman, 27 Oct, 2009 # Section 1: Import statements and function defs. import matplotlib.pyplot as plt from numpy import * def make_patch_spines_invisible(ax): ax.set_frame_on(True) ax.patch.set_visible(False) for sp in ax.spines.itervalues(): sp.set_visible(False) def make_spine_invisible(ax, direction): if direction in ["right", "left"]: ax.yaxis.set_ticks_position(direction) ax.yaxis.set_label_position(direction) elif direction in ["top", "bottom"]: ax.xaxis.set_ticks_position(direction) ax.xaxis.set_label_position(direction) else: raise ValueError("Unknown Direction : %s" % (direction,)) ax.spines[direction].set_visible(True) # Section 2: Define the names of the independent and dependent variables and the # data to be plotted. # Define axis labels. The first (zeroth) item in the list is the xaxis label; # remaining labels are the first yaxis label, second yaxis label, and so on. # There must be at least one dependent variable and not more than four. labels= ['Indep. Variable', 'Dep. Variable #1', 'Dep. Variable #2', 'Dep. Variable #3', 'Dep. Variable #4'] # ### DO NOT MODIFY THIS BLOCK OF CODE. ### N_dependents= len(labels)  1 if N_dependents > 4: raise Exception, \ 'This code currently handles a maximum of four independent variables.' # The following statement allocates storage: y= [0, 0, 0, 0, 0] # ### END OF BLOCK THAT SHOULD NOT BE MODIFIED ### # Plug in your data here, or plug in equations to generate the data. With a bit # of work, one could make this program read the data from a text file or Excel # worksheet. x = linspace(0., 2., 51) # First dependent variable: y[1]= sqrt(x) # Example of 6 experimentally measured y1values: # y[1] = array( [3, 2.5, 7.3e4, 4, 8, 3] ) # Second dependent variable: y[2]= 0.2 + x**0.3 y[3]= 30.*sin(1.5*x) y[4]= 30.*abs(cos(1.5*x)) # Set line colors here; each color can be specified using a singleletter color # identifier ('b'= blue, 'r'= red, 'g'= green, 'k'= black, 'y'= yellow, # 'm'= magenta, 'y'= yellow), an RGB tuple, or almost any standard English color # name. The first element of this list is not used. colors= [' ', 'b', 'red', 'g', 'magenta'] # Set the line width here. linewidth=2 is recommended. linewidth= 2 # Section 3: Generate the plot. # Open a new figure window, setting the size to 10by7 inches and the facecolor # to white: fig= plt.figure(figsize=(10,7), dpi=120, facecolor=[1,1,1]) host= fig.add_subplot(111) host.set_xlabel(labels[0]) # Use twinx() to create extra axes for all dependent variables except the first # (we get the first as part of the host axes). The first element of y_axis is # not used. y_axis= (N_dependents+2) * [0] y_axis[1]= host for i in range(2,len(labels)+1): y_axis[i]= host.twinx() if N_dependents >= 3: # The following statement positions the third yaxis to the right of the # frame, with the space between the frame and the axis controlled by the # numerical argument to set_position; this value should be between 1.10 and # 1.2. y_axis[3].spines["right"].set_position(("axes", 1.15)) make_patch_spines_invisible(y_axis[3]) make_spine_invisible(y_axis[3], "right") plt.subplots_adjust(left=0.0, right=0.8) if N_dependents >= 4: # The following statement positions the fourth yaxis to the left of the # frame, with the space between the frame and the axis controlled by the # numerical argument to set_position; this value should be between 1.10 and # 1.2. y_axis[4].spines["left"].set_position(("axes", 0.15)) make_patch_spines_invisible(y_axis[4]) make_spine_invisible(y_axis[4], "left") plt.subplots_adjust(left=0.2, right=0.8) p= (N_dependents+1) * [0] # Plot the curves: for i in range(1,N_dependents+1): p[i], = y_axis[i].plot(x, y[i], colors[i], linewidth=linewidth, label=labels[i]) # Set axis limits. Use ceil() to force upper yaxis limits to be round numbers. host.set_xlim(x.min(), x.max()) host.set_xlabel(labels[0], size=16) for i in range(1,N_dependents+1): y_axis[i].set_ylim(0.0, ceil(y[i].max())) y_axis[i].set_ylabel(labels[i], size=16) y_axis[i].yaxis.label.set_color(colors[i]) for obj in y_axis[i].yaxis.get_ticklines(): # `obj` is a matplotlib.lines.Line2D instance obj.set_color(colors[i]) obj.set_markeredgewidth(3) for obj in y_axis[i].yaxis.get_ticklabels(): obj.set_color(colors[i]) obj.set_size(12) obj.set_weight(600) # To get rid of the legend, comment out the following two lines: lines= p[1:] host.legend(lines, [l.get_label() for l in lines]) # Do not modify the following statement: plt.draw(); plt.show() 