From: Nihat <ngdev38@gm...>  20080630 14:22:20
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Hello all, I believe it is an easy thing to do but I haven't figured out how to convert between coordinate systems using transData or transAxes. x = numpy.arange(0.0, 1.0+0.01, 0.01) y = numpy.cos(2*2*numpy.pi*x) pylab.plot(x, y) I want to transform y1 to axis scale between 0 and 1. Also, I want to transform a value in axis scale, say 0.25, to a corresponding y value in the data coordinates. I used ax = gca() (x_screen, y_screen) = ax.transData.transform([x[10], y[10]) (x10, y10) = ax.transAxes.inverted().transform([x_screen, y_screen]) Is it the proper way of doing it? Where can I find more info on transformations in general? Currently I am doing it manually scaling things with axis limits, etc. I believe the neat thing is to use the transforms. Can somebody explain me how it is done with transforms? I am using v0.98.1. Thanks in advance, Nihat 
From: n g <ngdev38@gm...>  20080628 21:08:28
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Hello all, I believe it is an easy thing to do but I haven't figured out how to convert between coordinate systems using transData or transAxes. Here is the simple_plot.py import numpy import pylab x = numpy.arange(0.0, 1.0+0.01, 0.01) y = numpy.cos(2*2*numpy.pi*x) pylab.plot(x, y) Here I want to transform y1 to axis scale between 0 and 1. Also, I want to transform axis scale, say 0.25, to a corresponding y value in the data coordinates. pylab.show() Currently I am doing it manually scaling things with axis limits, etc. I believe the neat thing is to use the transforms api. Can somebody explain me how it is done with transforms? I am using 0.98.1. Thanks in advance, Nihat 
From: Nihat <ngdev38@gm...>  20080630 14:22:20
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Hello all, I believe it is an easy thing to do but I haven't figured out how to convert between coordinate systems using transData or transAxes. x = numpy.arange(0.0, 1.0+0.01, 0.01) y = numpy.cos(2*2*numpy.pi*x) pylab.plot(x, y) I want to transform y1 to axis scale between 0 and 1. Also, I want to transform a value in axis scale, say 0.25, to a corresponding y value in the data coordinates. I used ax = gca() (x_screen, y_screen) = ax.transData.transform([x[10], y[10]) (x10, y10) = ax.transAxes.inverted().transform([x_screen, y_screen]) Is it the proper way of doing it? Where can I find more info on transformations in general? Currently I am doing it manually scaling things with axis limits, etc. I believe the neat thing is to use the transforms. Can somebody explain me how it is done with transforms? I am using v0.98.1. Thanks in advance, Nihat 
Re: [Matplotlibusers] converting data between axis [0,
1] and data coordinates [min data, max data]
From: Tony S Yu <tonyyu@MIT.EDU>  20080630 14:54:32

On Jun 30, 2008, at 10:22 AM, Nihat wrote: > ax = gca() > (x_screen, y_screen) = ax.transData.transform([x[10], y[10]) > (x10, y10) = ax.transAxes.inverted().transform([x_screen, y_screen]) > > Is it the proper way of doing it? Where can I find more info on > transformations in general? I'd really be interested to know the answer to this question, too. I recently wanted to do this exact same transformation. When I tried >>> (x10, y10) = ax.transLimits.transform([x[10], y[10]) I got the desired input for *linear* data. Looking looking at the definitions of the axes transforms in the code (Axes class in axes.py) you see that: >>> self.transData = self.transScale + (self.transLimits + self.transAxes) where `self` is the Axes object. It would seem that your sequence of operations (`transData.transform` followed by `transAxes.inverted().transform`) should be equivalent to: >>> transDesired = self.transScale + self.transLimits But, when I tried using this transform, I didn't get the desired transformation for logarithmic data. Any transform experts out there? Tony 
Re: [Matplotlibusers] converting data between axis [0,
1] and data coordinates [min data, max data]
From: Michael Droettboom <mdroe@st...>  20080630 15:10:25

Nihat wrote: > Hello all, > > I believe it is an easy thing to do but I haven't figured out how to > convert between coordinate systems using transData or transAxes. > > x = numpy.arange(0.0, 1.0+0.01, 0.01) > y = numpy.cos(2*2*numpy.pi*x) > pylab.plot(x, y) > > I want to transform y1 to axis scale between 0 and 1. > Also, I want to transform a value in axis scale, say 0.25, to a > corresponding y value in the data coordinates. > > I used > > ax = gca() > (x_screen, y_screen) = ax.transData.transform([x[10], y[10]) > (x10, y10) = ax.transAxes.inverted().transform([x_screen, y_screen]) > > Is it the proper way of doing it? Where can I find more info on > transformations in general? The new transformations infrastructure is documented in the new docs (which are still in progress...) http://matplotlib.sourceforge.net/doc/html/devel/transformations.html This document, however, doesn't describe what things like transData and transAxes are defined to be. That would probably be a useful thing to document. transAxes places the axes within the figure. transData maps from the data's coordinates all the way to the figure space which is (0, 0) to (1, 1). transData is a composite of the scale (for eg. logarithm), the limits (the currently "zoomed" in portion of the data), and the transAxes. It's the "fast lane" between the data and the screen. In your example, if you expect to go between data and screen coordinates, you would do: (x_screen, y_screen) = ax.transData.transform([x[10], y[10]) (x10, y10) = ax.transData.inverted().transform([x_screen, y_screen]) Note, we use transData both ways. > > Currently I am doing it manually scaling things with axis limits, > etc. I believe the neat thing is to use the transforms. Can somebody > explain me how it is done with transforms? I am using v0.98.1. I hope that answers your question, but it's not entirely clear what you would like to do. Please ask further if the above didn't help. Cheers, Mike 
Re: [Matplotlibusers] converting data between axis [0,
1] and data coordinates [min data, max data]
From: Michael Droettboom <mdroe@st...>  20080630 15:13:35

Tony S Yu wrote: > On Jun 30, 2008, at 10:22 AM, Nihat wrote: > >> ax = gca() >> (x_screen, y_screen) = ax.transData.transform([x[10], y[10]) >> (x10, y10) = ax.transAxes.inverted().transform([x_screen, y_screen]) >> >> Is it the proper way of doing it? Where can I find more info on >> transformations in general? >> > > I'd really be interested to know the answer to this question, too. I > recently wanted to do this exact same transformation. When I tried > > >>> (x10, y10) = ax.transLimits.transform([x[10], y[10]) > > I got the desired input for *linear* data. Looking looking at the > definitions of the axes transforms in the code (Axes class in axes.py) > you see that: > > >>> self.transData = self.transScale + (self.transLimits + > self.transAxes) > > where `self` is the Axes object. It would seem that your sequence of > operations (`transData.transform` followed by > `transAxes.inverted().transform`) should be equivalent to: > > >>> transDesired = self.transScale + self.transLimits > > But, when I tried using this transform, I didn't get the desired > transformation for logarithmic data. > > Any transform experts out there? > transScale is where all of the (optionally) logarithmic transformation takes place. I'm surprised >>> transDesired = self.transScale + self.transLimits didn't work for going from data to a (0, 0)  (1, 1) bounding box. Can you provide a small, yet complete, example that illustrates the bug so I can look at it further? Cheers, Mike  Michael Droettboom Science Software Branch Operations and Engineering Division Space Telescope Science Institute Operated by AURA for NASA 
Re: [Matplotlibusers] converting data between axis [0,
1] and data coordinates [min data, max data]
From: Tony S Yu <tonyyu@MIT.EDU>  20080630 16:16:09
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On Jun 30, 2008, at 11:13 AM, Michael Droettboom wrote: > transScale is where all of the (optionally) logarithmic > transformation takes place. I'm surprised > > >>> transDesired = self.transScale + self.transLimits > > didn't work for going from data to a (0, 0)  (1, 1) bounding box. > Can you provide a small, yet complete, example that illustrates the > bug so I can look at it further? I tried to put together a simple example showing my problem, but the example worked properly! Doh! It turns out that my problem was specific to using a bounding box as an input to transform: ========= from numpy.random import rand import matplotlib.pyplot as plt ax = plt.subplot(111) xy = rand(5,2) ax.loglog(xy[:, 0], xy[:, 1], 'ro') trans = ax.transScale + ax.transLimits result = trans.transform(ax.dataLim) ========= The above command gives me: TypeError: 'Bbox' object is unsubscriptable (Note, if I call `plot` instead of `loglog` I don't have problems). The quick solution is to replace the last line with >>> result = trans.transform(ax.dataLim._points) I guess I was confused because the transform worked fine with `plot`. Is the TypeError above expected behavior? Thanks for your help. Tony 
Re: [Matplotlibusers] converting data between axis [0,
1] and data coordinates [min data, max data]
From: Michael Droettboom <mdroe@st...>  20080630 17:03:28

Tony S Yu wrote: > > On Jun 30, 2008, at 11:13 AM, Michael Droettboom wrote: >> transScale is where all of the (optionally) logarithmic >> transformation takes place. I'm surprised >> >> >>> transDesired = self.transScale + self.transLimits >> >> didn't work for going from data to a (0, 0)  (1, 1) bounding box. >> Can you provide a small, yet complete, example that illustrates the >> bug so I can look at it further? > > I tried to put together a simple example showing my problem, but the > example worked properly! Doh! > > It turns out that my problem was specific to using a bounding box as > an input to transform: > > ========= > from numpy.random import rand > import matplotlib.pyplot as plt > > ax = plt.subplot(111) > xy = rand(5,2) > ax.loglog(xy[:, 0], xy[:, 1], 'ro') > > trans = ax.transScale + ax.transLimits > result = trans.transform(ax.dataLim) > ========= > > The above command gives me: > * TypeError:* 'Bbox' object is unsubscriptable > (Note, if I call `plot` instead of `loglog` I don't have problems). > The quick solution is to replace the last line with > > >>> result = trans.transform(ax.dataLim._points) > > I guess I was confused because the transform worked fine with `plot`. > Is the TypeError above expected behavior? > Yes. The "transform" method is meant to take an Nx2 array, it doesn't take a bounding box. I think it probably works with nonlog plots only by accident because bounding boxes can cast to arrays in some cases. It may be worth taking that out to avoid confusion, but I'll have to think on it some. Thanks for looking into this! Mike  Michael Droettboom Science Software Branch Operations and Engineering Division Space Telescope Science Institute Operated by AURA for NASA 
Re: [Matplotlibusers] converting data between axis [0,
1] and data coordinates [min data, max data]
From: Nihat <ngdev38@gm...>  20080702 23:48:32
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Mike, Thanks for the help. It worked. I have another question but I will send it as a new thread. Nihat On Mon, Jun 30, 2008 at 12:02 PM, Michael Droettboom <mdroe@...> wrote: > > > Tony S Yu wrote: > >> >> On Jun 30, 2008, at 11:13 AM, Michael Droettboom wrote: >> >>> transScale is where all of the (optionally) logarithmic transformation >>> takes place. I'm surprised >>> >>> >>> transDesired = self.transScale + self.transLimits >>> >>> didn't work for going from data to a (0, 0)  (1, 1) bounding box. Can >>> you provide a small, yet complete, example that illustrates the bug so I can >>> look at it further? >>> >> >> I tried to put together a simple example showing my problem, but the >> example worked properly! Doh! >> >> It turns out that my problem was specific to using a bounding box as an >> input to transform: >> >> ========= >> from numpy.random import rand >> import matplotlib.pyplot as plt >> >> ax = plt.subplot(111) >> xy = rand(5,2) >> ax.loglog(xy[:, 0], xy[:, 1], 'ro') >> >> trans = ax.transScale + ax.transLimits >> result = trans.transform(ax.dataLim) ========= >> >> The above command gives me: >> * TypeError:* 'Bbox' object is unsubscriptable >> (Note, if I call `plot` instead of `loglog` I don't have problems). The >> quick solution is to replace the last line with >> >> >>> result = trans.transform(ax.dataLim._points) >> >> I guess I was confused because the transform worked fine with `plot`. Is >> the TypeError above expected behavior? >> >> Yes. The "transform" method is meant to take an Nx2 array, it doesn't > take a bounding box. I think it probably works with nonlog plots only by > accident because bounding boxes can cast to arrays in some cases. It may be > worth taking that out to avoid confusion, but I'll have to think on it some. > > Thanks for looking into this! > > > Mike > >  > Michael Droettboom > Science Software Branch > Operations and Engineering Division > Space Telescope Science Institute > Operated by AURA for NASA > > 