gmane.comp.python.matplotlib.general

Re: Dark or inverted color scheme

Tony Yu — 2012-05-25T21:41:44

color_cycle has black in it, so it should be changed, regardless of
aesthetic considerations.
-Tony
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Re: Dark or inverted color scheme

Jerzy Karczmarczuk — 2012-05-25T21:35:25

Tony Yu:
...

don't forget to lighten the colours in axes.color_cycle (unless blue on 
black, etc. suits you). This is used by plot and was one of my numerous 
mistakes two days ago...

Jerzy Karczmarczuk

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Re: Dark or inverted color scheme

Tony Yu — 2012-05-25T21:22:45

On Fri, May 25, 2012 at 4:07 PM, Tom Aldcroft <aldcroft-O3NruelLybrOHkwriC13pfZ8FUJU4vz8< at >public.gmane.org

Hi Tom,

You can create a custom matplotlibrc file [1] and use that for your plots.
The settings you'd probably want to change are copied below. Note that not
all plotting elements grab colors from rc parameters (unfortunately), so
you may find that some functions will ignore these settings.

I think the simplest way (currently) to use the rc file is by putting it in
the same directory as your plotting script (or wherever you're executing
your script). There's a pending pull request [2] that adds the ability to
load rc parameters from a file. Also, I maintain a small set of matplotlib
convenience functions, including a stylesheet-like function. I added the rc
parameters below as a new style and added an example to the documentation
[3].

Hope that helps,
-Tony

[1] http://matplotlib.sourceforge.net/users/customizing.html
[2] https://github.com/matplotlib/matplotlib/pull/861
[3]
http://tonysyu.github.com

Dark or inverted color scheme

Tom Aldcroft — 2012-05-25T20:07:50

Is there a simple way to essentially invert the default plotting color
scheme so that the figure background is black and all text, ticks,
axes, axis labels, etc are white?  I think what I want is to redefine
the RGB definitions of the standard color values 'b', 'y', 'k', etc so
that I can make a plot figure with a black background using the same
script as one for the normal white background.

A spent a little while googling and didn't find anything apart from
specifically setting different colors for every single plot element.
This would be tiresome.

Thanks in advance for any help,
Tom

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Re: plotting through ipython and QT4 customwidgets

AI — 2012-05-25T16:50:55

Hi,

same problem with ipython 0.12 and matplotlib 1.1.1rc.

To recall, I'm trying to add a QT4 widget to a matplotlib figure (MPL is
using Qt4 as backend). However, in the attached example the widget callback
(or slot) is not called. Oddly, if I add the qt4 widget manually calling
qt4_interface() from ipython it works.

Basically I want to preserve the maplotlib+ipython interactive workflow,
but using some "enhanced" figures (i.e. mpl figure+qt4 widgets).

Thank you for any suggestion.
Antonio



2012/5/24 AI <tritemio-Re5JQEeQqe8AvxtiuMwx3w< at >public.gmane.org>

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Re: Slow imshow when zooming or panning with several synced subplots

Sergi Pons Freixes — 2012-05-25T08:30:42

Yes, changing it really speeds-up the interactivity! The delay is now
just a few ms, you can notice it's not completely smooth, but
perfectly usable. I'll compare if when zoomed in any
artifacts/distortion appear.

Thank you!

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Re: matplotlibrc interpretation seems buggy : SORRY

Jerzy Karczmarczuk — 2012-05-25T07:55:39

BR answers:
[*!#!!%*!!]
Of course I found that myself some time after reporting this "bug"... Sorry.
The parameter is "axes.color_cycle"

Jerzy K.


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Re: matplotlibrc interpretation under Windows seems buggy

Benjamin Root — 2012-05-25T00:24:37



Plot() doesn't use lines.color.  I don't remember the exact name, but it
uses an rcparam for color cycling.  Just change make the list of colors be
just 'r'.

Ben Root
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matplotlibrc interpretation under Windows seemsbuggy

Jerzy Karczmarczuk — 2012-05-24T23:44:02

Gurus,

Windows XP, matplotlib 1.1.0. Backend Tk, but the same elsewhere.

Programme:

import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.color'] = 'r'

x=range(800)
y=[t for t in x]
plt.plot(x,y)
plt.show()

# ==============================
Linewidth OK, equal to 2, but the line is still blue. Changing "r" to 
red, or to #ff0000, or (1,0,0) doesn't change anything, still blue. 
Changing directly the matplotlibrc file (default) - the same. Leaving in 
peace the defaults, constructing another rc in the working dir - the 
same. The dictionary rcParams contains the correct value
'lines.color': 'r'
(Anyway, rcsetup.py validation doesn't protest. But then, the modified 
colour is ignored).

Somebody could confirm that?

The best.

Jerzy Karczmarczuk
Caen, France

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Re: griddata is not working after update toPython 2.7

Benjamin Root — 2012-05-24T22:01:03

First, if you were importing griddata before like that, that it is quite
likely that it was some other module that was installed in your
python-2.6/site-packages directory that overrode numpy's griddata. When you
upgraded, that griddata module could not be found in
python-2.7/site-packages. Commenting it out allowed python to find pylab's
griddata.

Second, you really need to clean up your imports. There is no need for the
two math imports, or the numpy import (because the pylab import handles
that).

Oddly, though, your griddata import comes before the pylab import. I would
expect that the pylab griddata would have overridden the first griddata
import. And so there shouldn't have been a difference.

Did you happen to upgrade matplotlib and/or numpy as well?

Ben Root
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griddata is not working after update to Python2.7

Umut Yildiz — 2012-05-24T19:10:50

Dear All,

I used to use griddata in order to make my contourmaps. However, after I updated
my Python from 2.6 to 2.7 griddata is not working anymore.

I tried some workarounds but no success.

The countourmap that I produced before is here.
http://dl.dropbox.com/u/17983476/matplotlib/contour_dT_workingbefore.png

After the Python 2.7 update, it turns to the following.
http://dl.dropbox.com/u/17983476/matplotlib/contour_dT_broken.png

Here is the datafile.
http://dl.dropbox.com/u/17983476/matplotlib/contour_dT.dat

And the associated python script (which is also below).
http://dl.dropbox.com/u/17983476/matplotlib/contour_dT.py

The code that I was using before is here. I had to comment out #import griddata
line because this is the only way that it continues. Is this a bug in griddata,
or if there are new workarounds, I would be glad to know a new method to produce
my contourplots again.

Thanks a lot

----------------------------
#! /usr/bin python

import os
import sys
import math
from math import *
from nu

plotting through ipython and QT4 custom widgets

AI — 2012-05-24T19:03:32

Hi,

I want to add a QT4 widget to a matplotlib figure, but the widget does not
react to user input.

Here it is a test case:

from PyQt4 import QtGui, QtCore
from pylab import *

def test():
    plot([1,2,3], lw=2)
    qt4_interface(gcf())

class qt4_interface:
    def __init__(self,fig):
        QMainWin = fig.canvas.parent()
        toolbar = QtGui.QToolBar(QMainWin)
        QMainWin.addToolBar(QtCore.Qt.BottomToolBarArea, toolbar)

        self.line_edit = QtGui.QLineEdit(parent=toolbar)
        self.line_edit.editingFinished.connect(self.do_something)
        toolbar.addWidget(self.line_edit)

    def do_something(self, *args):
        f = open('l','a'); f.write('yes\n'); f.flush(); f.close()
        #close()

I run the script as "run -i qt4_test.py" from ipython. Then running test()
I get the figure with the additional widget but the do_something method is
never called.

Incidentally if I do a plot from ipython and then I type interactively
qt4_interface(gcf()), the qt4 widget is added to the figure an

Re: Easy mistake to make...

Michael Droettboom — 2012-05-24T14:52:04

Seems like a good idea.  Maybe we gracefully deprecate this?  i.e. warn 
about the confusing usage now, and throw exceptions in a future version?

Mike

On 05/24/2012 10:22 AM, Benjamin Root wrote:

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Re: Easy mistake to make...

Benjamin Root — 2012-05-24T14:22:05


We could also do a check in the reverse case... if plt.subplot(1, 2, True)
is done, that should either raise an error or at least warn (currently, it
treats True as the first subplot and False as some (probably non-existant)
subplot).

I will write up a PR for this.

Ben Root
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Re: Easy mistake to make...

Tony Yu — 2012-05-24T14:09:56

+1 : I switch `subplots` and `subplot` quite frequently, so a check would
be helpful.

-Tony
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Re: Slow imshow when zooming or panning with several synced subplots

Tony Yu — 2012-05-24T13:59:22

On Thu, May 24, 2012 at 9:14 AM, Sergi Pons Freixes
<sponsfreixes-Re5JQEeQqe8AvxtiuMwx3w< at >public.gmane.org>wrote:

It seems that setting `interpolation='none'` is significantly slower than
setting it to 'nearest' (or even 'bilinear'). On supported backends (e.g.
any Agg backend) the code paths for 'none' and 'nearest' are different:
'nearest' gets passed to Agg's interpolation routine, whereas 'none' does
an unsampled rescale of the image (I'm just reading the code comments
here). Could you check whether changing to `interpolation='nearest'` fixes
this issue?

-Tony

(Note: copied to stackoverflow)

PS: These different approaches *do* give different qualitative results; for
example, the code snippet below gives a slight moiré pattern, which doesn't
appear when `interpolation='none'`. I *think* that 'none' is roughly the
same as 'nearest' when zooming in (image pixels are larger than screen
pixels) but gives a higher-order interpolation result when zooming out
(image pixels smaller than screen pixels). I thin

Easy mistake to make...

Benjamin Root — 2012-05-24T13:54:55

Just got bit by this and I thought I'd share to help others.

I was just quickly writing out some pyplot commands to create two subplots
to compare some results.  I did:

plt.subplots(1, 2, 1)
plt.contourf(....)
plt.title("Contours")
xlim = plt.xlim()
ylim = plt.ylim()

plt.subplots(1, 2, 2)
plt.imshow(....)
plt.title("Raw Image")
plt.xlim(xlim)
plt.ylim(ylim)


Did you see the error?  I did "subplots" instead of "subplot".  Since the
third argument for plt.subplot is "sharex", a value of 1 or 2 appears
perfectly valid to it. Meanwhile, the second call to plt.subplots() throws
out my first subplot, and I also get the seemingly odd behavior of the
first subplot having the correct x limits, but the default y limits (0,
1).  Of course, this makes sense once you figure out the issue, but it is
an extra wrinkle that can be quite confusing.

I suspect this is a very easy mistake to make.  Should we perhaps test the
value of sharex in subplots() and warn if it is anything but a python
bool?  Just a thought.

Cheers

Re: strange behaviour with sankey diagram (maybe a bug)

Giovanni — 2012-05-24T13:26:49

  martedì 22 maggio 2012, 18:33, Kevin Davies:


  No, the labels are translated to the left (so approaching to the
center of the patch), but the rest of the layout it's getting worse.


  i can't live without patchlabel, so i've no interest in investigating
further (and probably neither the programming skill). Anyway i think
that a solution will be to calculate the centroid of the patch and use
it as a center for the label.

Thanks for explaining and four your hints!

G.

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Re: Slow imshow when zooming or panning with several synced subplots

Sergi Pons Freixes — 2012-05-24T13:14:33

I was just guessing that it is part of the process of converting
actual data (32 bit floats) to images on the screen (24 bit for RGB
(32 with transparency) or 8 bit for grayscale).

I tried converting the data to 8 bit, with .astype('uint8'), and it
keeps being poorly responsive on zooming and panning.

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(no subject)

Arek Kedzior — 2012-05-24T04:03:14

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Re: how to set figure to appear on anothermonitor?

Benjamin Root — 2012-05-24T01:40:12


This is more an issue with how the GUI toolkit interacts with the desktop
manager. I think there are some existing PRs (or at least wishlist items)
for supplying additional data down to the figure object. The person who did
that feature was then going to set a windowing rule of some sort for his
window manager to handle mpl figures specially.

As far as I know, the feature never got added. Maybe someone else could
resurrect that work?

Cheers!
Ben Root

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