Re: [Matplotlib-users] Feature Request: RectangleSelector BlockingInput
Hi, Sorry for the long delay - I have been on vacation. I don't use the imcrop function, but it looks fairly easy to implement using ginput. I am heading off for vacation again for another two weeks and I want to get in some of the changes I proposed a long while ago before working on this, so it might be a while, but if no one can take it on first, I can give a look next month. Cheers, David On Tue, 2008-08-05 at 19:51 -0500, John Hunter wrote: On Tue, Aug 5, 2008 at 6:26 PM, Elfnor [EMAIL PROTECTED] wrote: This would be really useful for implementing a user image crop function, similar to matlab's imcrop for example. David, since you are a recent matlab user and are deeply versed in the blocking code: how hard would it be to simply provide a (mostly) matlab compatible imcrop function, and is this something you are interested in doing? JDH -- ** David M. Kaplan Charge de Recherche 1 Institut de Recherche pour le Developpement Centre de Recherche Halieutique Mediterraneenne et Tropicale av. Jean Monnet B.P. 171 34203 Sete cedex France Phone: +33 (0)4 99 57 32 27 Fax: +33 (0)4 99 57 32 95 http://www.ur097.ird.fr/team/dkaplan/index.html ** - This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100url=/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Control space between bars
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 ?
-
import pylab as P
import matplotlib.transforms as T
x = P.arange(5)
y = P.rand(5) * 4
ax = P.subplot(1,1,1)
P.plot(x,y)
ax.set_ylim(0.0, 4.0)
trans = ax.transAxes
valx = valy = 0.5
actualcoords = %s % trans.transform([valx, valy])
#Gives me [328, 240] instead of [2.0, 2.0]
ax.text(valx, valy, actualcoords, transform=trans)
P.show()
-
On Wed, Aug 13, 2008 at 10:34 AM, Mathieu Leplatre [EMAIL PROTECTED] wrote:
Hi all,
I've searched in examples and archives and could not find anything
about manual control of space between bars.
By default, the bars in the following script overlap.
So I guess the behaviour is :
specify chart width (8in) + bar width (0.8) = auto bar space
And I would like to know how to do :
specify chart width + bar space = auto bar width
specify bar space + bar width = auto chart width (fixed margins)
But I can't figure it out, especially the latter. Can
matplotlib.transforms help me about the former ?
Do you have documentation reference or some hints about that please ?
Thanks!
I am plotting a chronological bar chart like this one :
#!/usr/bin/env python
import matplotlib, pylab, numpy
import datetime
def rangedates( hourstep ):
dates = []
for d in range(1,31):
for h in range(0,24,hourstep):
dt = datetime.datetime(2008,06,d,h)
dates.append(dt)
return pylab.date2num(dates)
# Plot value every 12H
abscissa = rangedates(12)
barstep = abscissa[1] - abscissa[0]
barspace = 0.5 * barstep
barwidth = barstep - barspace
fig = pylab.figure()
ax = fig.add_subplot(111)
fmt = matplotlib.dates.DateFormatter('%b %d')
ax.xaxis.set_major_formatter( fmt )
fig.autofmt_xdate()
pylab.bar( abscissa, numpy.random.randn( len(abscissa) ),
width = barwidth)
pylab.show()
-
This SF.Net email is sponsored by the Moblin Your Move Developer's challenge
Build the coolest Linux based applications with Moblin SDK win great prizes
Grand prize is a trip for two to an Open Source event anywhere in the world
http://moblin-contest.org/redirect.php?banner_id=100url=/
___
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
-
This SF.Net email is sponsored by the Moblin Your Move Developer's challenge
Build the coolest Linux based applications with Moblin SDK win great prizes
Grand prize is a trip for two to an Open Source event anywhere in the world
http://moblin-contest.org/redirect.php?banner_id=100url=/
___
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] Arrow Questions
I am trying to implement a dynamic graph in mpl, where users can drag around the nodes, and the edges follow the nodes like rubber bands. I have this working with regular edges, but I want to give the option of putting arrows on the edges. I am running into some issues with the Arrow classes. With my Text, Rectangle, and Line2D objects I can get and set their locations with methods such as get_position(), get_x(), and get_xdata() respectively. But there are no such methods for any of the Arrow classes. (By the way, it seems like these sorts of things would be in the base classes, and much more standard). What is the difference between Arrow, YAArrow, and FancyArrow anyway? (Besides drastically different scales). Some other features of the Arrow class that I would like very much are: * double headed arrows (one line with an arrow head on each end) * the ability to turn the arrow head on and off easily (Boolean parameter function) Does anyone have any ideas on how to work around these issues? Thanks, -Ben - This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100url=/___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Scaling axes not data?
Eric and John, Thanks for the information. You are right that this probably would have been a premature optimisation, even if it weren't rendered useless by matplotlib using doubles internally (which I hadn't realised). The thought just occurred to me as I was writing the data-scaling part of my script. The script is intended to be somewhat interactive. Initial tests suggest that plotting or updating several subplots from memory does take a quite noticeable time (e.g. 1.2 -- 1.5 seconds for 3 subplots of 1 points) that will probably become annoying in routine use. As you indicated, basically all that time is spent within matplotlib. I'm just using standard default calls: for i in subplot subplot plot xlabel ylabel title Each of these calls seems to take roughly the same time (60--100ms). If anybody has pointers on speeding things up significantly, I'm all ears. (Predefining data limits? Using lower-level commands? Use of a non-default backend?) Boris - This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100url=/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Scaling axes not data?
Boris Barbour wrote:
Eric and John,
Thanks for the information. You are right that this probably would have been a
premature optimisation, even if it weren't rendered useless by matplotlib
using doubles internally (which I hadn't realised). The thought just occurred
to me as I was writing the data-scaling part of my script.
The script is intended to be somewhat interactive. Initial tests suggest that
plotting or updating several subplots from memory does take a quite
noticeable time (e.g. 1.2 -- 1.5 seconds for 3 subplots of 1 points) that
will probably become annoying in routine use. As you indicated, basically all
that time is spent within matplotlib. I'm just using standard default calls:
for i in subplot
subplot
plot
xlabel
ylabel
title
Each of these calls seems to take roughly the same time (60--100ms). If
It sounds like you have interactive mode on, in which case each pylab
function redraws the figure. The solution is to use the object-oriented
interface for almost everything. See the attached example.
anybody has pointers on speeding things up significantly, I'm all ears.
(Predefining data limits? Using lower-level commands? Use of a non-default
backend?)
If the suggestion above is not enough, we will need to know more about
what your script looks like, the environment in which it is running
(e.g., ipython? embedded in wx? straight command line? what operating
system? what backend?), your constraints, and what you are trying to
accomplish. The best thing would be if you could post a very short
self-contained script, typically using fake random data, that shows your
present approach and that illustrates the speed problem; then we can try
to figure out what the bottlenecks are, and whether there are simple
ways to speed up the script or to modify mpl for better speed.
Eric
import time
import numpy as np
import matplotlib.pyplot as plt
npts = 1
xx = np.arange(npts)
plt.ion()
t0 = time.time()
fig1 = plt.figure()
ax = fig1.add_subplot(1,1,1)
# Try again, commenting out the following three lines;
# you will see no significant difference in the plotting time.
ax.set_title('A title')
ax.set_xlabel('This is X')
ax.set_ylabel('This is Y')
lines = ax.plot(xx, np.random.rand(npts))
plt.draw()
t1 = time.time()
print t1-t0
for ii in range(10):
t0 = time.time()
lines[0].set_data(xx, np.random.rand(npts))
plt.draw()
t1 = time.time()
print t1-t0
-
This SF.Net email is sponsored by the Moblin Your Move Developer's challenge
Build the coolest Linux based applications with Moblin SDK win great prizes
Grand prize is a trip for two to an Open Source event anywhere in the world
http://moblin-contest.org/redirect.php?banner_id=100url=/___
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
