Re: [Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
As far as I can see, this is a bug of matplolib, although calling a set_data work around this. Can you open a bug report in our github repo? -JJ 2012. 2. 18. 오후 10:12에 Ray Osborn rosb...@anl.gov님이 작성: You're exactly right. That does fix it. Unfortunately, it means I have to refactor some of my code because the Pyside slot doesn't currently have access to the original data, but that's not a huge deal. Thanks, Ray On Feb 18, 2012, at 4:35 AM, Jerzy Karczmarczuk wrote: Ray Osborn: OK - it turns out I can reproduce it in a simple ipython session using ipython --pylab=qt. I set up an image plot as follows: import numpy as np import matplotlib.pyplot as plt from matplotlib.image import NonUniformImage x=y=np.linspace(0,2*np.pi,101) X,Y=np.meshgrid(x,y) z=sin(X)*sin(Y) ax=plt.gca() extent = (x[0],x[-1],y[0],y[-1]) im = NonUniformImage(ax, extent=extent, origin=None) im.set_data(x,y,z) ax.images.append(im) ax.set_xlim(x[0],x[-1]) ax.set_ylim(y[0],y[-1]) plt.colorbar(im) plt.gcf().canvas.draw() After that, I try to change the color scale using: im.set_clim(0,0.5) plt.gcf().canvas.draw() The colorbar changes scale, but the plot is untouched. Is that the expected behavior? Thanks, Ray Try, perhaps, after set_clim, to reinstall the data: im.set_data(x,y,z) plt.gcf().canvas.draw() = Jerzy Karczmarczuk -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Ray Osborn Materials Science Division Argonne National Laboratory Argonne, IL 60439, USA Phone: +1 (630) 252-9011 Email: rosb...@anl.gov -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
I think you're right. Even if there is a work-around, it can't be right for the colorbar to change without affecting the image. I've filed issue #708. Thanks, Ray On Feb 19, 2012, at 4:37 AM, Jae-Joon Lee wrote: As far as I can see, this is a bug of matplolib, although calling a set_data work around this. Can you open a bug report in our github repo? -JJ 2012. 2. 18. 오후 10:12에 Ray Osborn rosb...@anl.gov님이 작성: You're exactly right. That does fix it. Unfortunately, it means I have to refactor some of my code because the Pyside slot doesn't currently have access to the original data, but that's not a huge deal. Thanks, Ray On Feb 18, 2012, at 4:35 AM, Jerzy Karczmarczuk wrote: Ray Osborn: OK - it turns out I can reproduce it in a simple ipython session using ipython --pylab=qt. I set up an image plot as follows: import numpy as np import matplotlib.pyplot as plt from matplotlib.image import NonUniformImage x=y=np.linspace(0,2*np.pi,101) X,Y=np.meshgrid(x,y) z=sin(X)*sin(Y) ax=plt.gca() extent = (x[0],x[-1],y[0],y[-1]) im = NonUniformImage(ax, extent=extent, origin=None) im.set_data(x,y,z) ax.images.append(im) ax.set_xlim(x[0],x[-1]) ax.set_ylim(y[0],y[-1]) plt.colorbar(im) plt.gcf().canvas.draw() After that, I try to change the color scale using: im.set_clim(0,0.5) plt.gcf().canvas.draw() The colorbar changes scale, but the plot is untouched. Is that the expected behavior? Thanks, Ray Try, perhaps, after set_clim, to reinstall the data: im.set_data(x,y,z) plt.gcf().canvas.draw() = Jerzy Karczmarczuk -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Ray Osborn Materials Science Division Argonne National Laboratory Argonne, IL 60439, USA Phone: +1 (630) 252-9011 Email: rosb...@anl.gov -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Ray Osborn Materials Science Division Argonne National Laboratory Argonne, IL 60439, USA Phone: +1 (630) 252-9011 Email: rosb...@anl.gov -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
Ray Osborn: OK - it turns out I can reproduce it in a simple ipython session using ipython --pylab=qt. I set up an image plot as follows: import numpy as np import matplotlib.pyplot as plt from matplotlib.image import NonUniformImage x=y=np.linspace(0,2*np.pi,101) X,Y=np.meshgrid(x,y) z=sin(X)*sin(Y) ax=plt.gca() extent = (x[0],x[-1],y[0],y[-1]) im = NonUniformImage(ax, extent=extent, origin=None) im.set_data(x,y,z) ax.images.append(im) ax.set_xlim(x[0],x[-1]) ax.set_ylim(y[0],y[-1]) plt.colorbar(im) plt.gcf().canvas.draw() After that, I try to change the color scale using: im.set_clim(0,0.5) plt.gcf().canvas.draw() The colorbar changes scale, but the plot is untouched. Is that the expected behavior? Thanks, Ray Try, perhaps, after set_clim, to reinstall the data: im.set_data(x,y,z) plt.gcf().canvas.draw() = Jerzy Karczmarczuk -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
You're exactly right. That does fix it. Unfortunately, it means I have to refactor some of my code because the Pyside slot doesn't currently have access to the original data, but that's not a huge deal. Thanks, Ray On Feb 18, 2012, at 4:35 AM, Jerzy Karczmarczuk wrote: Ray Osborn: OK - it turns out I can reproduce it in a simple ipython session using ipython --pylab=qt. I set up an image plot as follows: import numpy as np import matplotlib.pyplot as plt from matplotlib.image import NonUniformImage x=y=np.linspace(0,2*np.pi,101) X,Y=np.meshgrid(x,y) z=sin(X)*sin(Y) ax=plt.gca() extent = (x[0],x[-1],y[0],y[-1]) im = NonUniformImage(ax, extent=extent, origin=None) im.set_data(x,y,z) ax.images.append(im) ax.set_xlim(x[0],x[-1]) ax.set_ylim(y[0],y[-1]) plt.colorbar(im) plt.gcf().canvas.draw() After that, I try to change the color scale using: im.set_clim(0,0.5) plt.gcf().canvas.draw() The colorbar changes scale, but the plot is untouched. Is that the expected behavior? Thanks, Ray Try, perhaps, after set_clim, to reinstall the data: im.set_data(x,y,z) plt.gcf().canvas.draw() = Jerzy Karczmarczuk -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Ray Osborn Materials Science Division Argonne National Laboratory Argonne, IL 60439, USA Phone: +1 (630) 252-9011 Email: rosb...@anl.gov -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
I am embedding a matplotlib canvas in a Pyside GUI and wanted to attach a slider to adjust the color scale of a 2D plot made using NonUnitformImage. I am connecting the slider value to im.set_clim([vmin,vmax]). I have got my axis sliders to work, but the intensity slider only adjusts the colorbar without touching the image itself. Is there some trick to making this work with NonUniformImage? My plotting routine has the following code: ax = plt.gca() im = NonUniformImage(ax, extent=extent, origin=None, **opts) im.set_data(x,y,z) ax.images.append(im) self.imgplot = im plt.colorbar(im) while the Pyside slot has: zhi = self.zmin + (self.ztab.maxslider.value() * range / 100) im = self.imgplot im.set_clim([zlo,zhi]) The slider dynamically adjusts the colorbar beautifully, but leaves the color plot untouched. Any suggestions welcome. Thanks in advance, Ray -- Ray Osborn Materials Science Division Argonne National Laboratory Argonne, IL 60439, USA Phone: +1 (630) 252-9011 Email: rosb...@anl.gov -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
On Friday, February 17, 2012, Ray Osborn wrote: I am embedding a matplotlib canvas in a Pyside GUI and wanted to attach a slider to adjust the color scale of a 2D plot made using NonUnitformImage. I am connecting the slider value to im.set_clim([vmin,vmax]). I have got my axis sliders to work, but the intensity slider only adjusts the colorbar without touching the image itself. Is there some trick to making this work with NonUniformImage? My plotting routine has the following code: ax = plt.gca() im = NonUniformImage(ax, extent=extent, origin=None, **opts) im.set_data(x,y,z) ax.images.append(im) self.imgplot = im plt.colorbar(im) while the Pyside slot has: zhi = self.zmin + (self.ztab.maxslider.value() * range / 100) im = self.imgplot im.set_clim([zlo,zhi]) The slider dynamically adjusts the colorbar beautifully, but leaves the color plot untouched. Any suggestions welcome. Thanks in advance, Ray Without a more complete example, it is hard to say. Can you make a small stand-alone example that we can try out? Ben Root -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Dynamically adjusting the color scale in NonUniformImage
OK - it turns out I can reproduce it in a simple ipython session using ipython --pylab=qt. I set up an image plot as follows: import numpy as np import matplotlib.pyplot as plt from matplotlib.image import NonUniformImage x=y=np.linspace(0,2*np.pi,101) X,Y=np.meshgrid(x,y) z=sin(X)*sin(Y) ax=plt.gca() extent = (x[0],x[-1],y[0],y[-1]) im = NonUniformImage(ax, extent=extent, origin=None) im.set_data(x,y,z) ax.images.append(im) ax.set_xlim(x[0],x[-1]) ax.set_ylim(y[0],y[-1]) plt.colorbar(im) plt.gcf().canvas.draw() After that, I try to change the color scale using: im.set_clim(0,0.5) plt.gcf().canvas.draw() The colorbar changes scale, but the plot is untouched. Is that the expected behavior? Thanks, Ray On Feb 17, 2012, at 9:05 PM, Benjamin Root wrote: On Friday, February 17, 2012, Ray Osborn wrote: I am embedding a matplotlib canvas in a Pyside GUI and wanted to attach a slider to adjust the color scale of a 2D plot made using NonUnitformImage. I am connecting the slider value to im.set_clim([vmin,vmax]). I have got my axis sliders to work, but the intensity slider only adjusts the colorbar without touching the image itself. Is there some trick to making this work with NonUniformImage? My plotting routine has the following code: ax = plt.gca() im = NonUniformImage(ax, extent=extent, origin=None, **opts) im.set_data(x,y,z) ax.images.append(im) self.imgplot = im plt.colorbar(im) while the Pyside slot has: zhi = self.zmin + (self.ztab.maxslider.value() * range / 100) im = self.imgplot im.set_clim([zlo,zhi]) The slider dynamically adjusts the colorbar beautifully, but leaves the color plot untouched. Any suggestions welcome. Thanks in advance, Ray Without a more complete example, it is hard to say. Can you make a small stand-alone example that we can try out? Ben Root -- Ray Osborn Materials Science Division Argonne National Laboratory Argonne, IL 60439, USA Phone: +1 (630) 252-9011 Email: rosb...@anl.gov -- Virtualization Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
