On Aug 14, 2008, at 4:51 PM, Jae-Joon Lee wrote:
> Hi Mathieu,
>
> It seems to me that you're confused with the meaning of the transAxes.
> It is a transform from the Axes coordinate to the Canvas(?)
> coordinate.
> As far as I can see, what you seemed to want is a transform between
> Data coordinate and Axes coordinate, and that would be transScale +
> transLimits (from Data to Axes).
>
> So, try
>
> trans = (ax.transScale + ax.transLimits).inverted()
> # trans = ax.transLimits.inverted() will also work in this case.
>
> and you will get 2.0, 2.0 as you expected.
>
> The "transform" argument should be transAxes still.
>
> ax.text(valx, valy, actualcoords, transform=ax.transAxes)
>
> As far as your original question is concerned, I have little idea what
> you are trying to do, so I'll leave that question to others.
>
> Regards,
>
> -JJ
>
>
> On Thu, Aug 14, 2008 at 3:43 PM, Mathieu Leplatre
> <[EMAIL PROTECTED]> wrote:
>> I am still investigating and I am stuck at converting transAxes
>> values to data.
>>
>> If my axes goes from 10.0 to 20.0 then transAxes 0.5 should give me
>> 15.0.
>>
>> This would allow me to compute bar width and space, since I am able
>> to
>> convert inches to transAxes values.
>>
>> I tried many combinations of transAxes, transData, ...,
>> inverse_xy_tup, xy_tup, inverted(), transform(), ... without success
>> :(
>>
>> Any ideas please ?
Hi Mathieu,
I just wanted to add a little bit to Jae-Joon's example. I feel like I
have to relearn the axes transformations every time I deal with them.
Your email reminded me to write things down, and I thought I'd share
it, in case others find it useful. Let me know if anything is wrong/
unclear.
Best,
-Tony
=============================
Axes Transformations Tutorial
=============================
The new transformations infrastructure is documented in the `new
docs`_ (still
in progress...), which talks about transformations *in general*. This
document
talks about transforms that are pre-defined attributes of `axes`. The
following
explanation is partially stolen from a mailing list reply by Michael
Droettboom.
In the following,
data space
the actual `x, y` input data coordinates
axes space
the axes coordinates which are `([0, 0], [1, 1])` at
`([xmin,ymin], [xmax,
ymax])`
figure space
the screen pixel coordinates.
.. _new docs:
http://matplotlib.sourceforge.net/doc/html/devel/
transformations.html
`matplotlib.axes` transforms
============================
`transScale`
scales data to account for nonlinearities (non-affine) in the
axis scales,
e.g. log-log and semi-log scales. For example,
`transScale.transform` would
convert `x = [1, 10, 100, 1000]` to `[1, 2, 3, 4]` (powers of
ten) if the
x-axis is logarithmically spaced.
`transLimits`
scales the data to the currently "zoomed" in portion of the data.
`transScale + transLimits`
maps data space to axes space.
`transAxes`
maps axes space to figure space.
`transData`
maps data space to the figure space. `transData` is a composite of
`transScale`, `transLimits`, and `transAxes`. It's the "fast
lane" between
the data and the screen.
Transforms example
==================
If you want to draw a dot in the middle of the plot, you know that
>>> x = y = 0.5
in axes space.
Since the default transform for `matplotlib.pyplot.plot` is
`transData`, you can
either either change the transform of the plot operation
>>> import matplotlib.pyplot as plt
>>> ax = plt.subplot(111)
>>> ax.plot([x], [y], 'ro', transform=ax.transAxes)
Or you can transform the midpoint to data coordinates then plot them
>>> trans_data2axes = ax.transScale + ax.transLimits
>>> trans_axes2data = trans_data2axes.inverted()
>>> mid_point = trans_axes2data.transform([x, y])
>>> x_trans, y_trans = mid_point
>>> ax.plot([x_trans], [y_trans], 'gs')
It's important to note that these are two **very different**
approaches. The
first point (red dot) above is always referenced to axes space and
will remain
in the center of the plot, even if you change the axes limits (try
panning in
interactive mode).
On the other hand, the second point (green square) is referenced to
the data
space and will move with the data if the axes limits are changed.
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