matplotlib-users Mailing List for matplotlib (Page 3)

Hi,
I am trying to plot filled paths over a U.S. map. I plot the given paths, but since these are not closed paths, the filling is truncated at a line drawn between last and first point in the path. I want to extend the path to the United States border instead. 
I am no expert in matplotlib or GIS. Could anyone help me find documentation or blogs discussing this type of issue? I am convinced somebody else has already faced this problem although I have not been able to find any paper, documentation, blog on it. 
Thank you

On Mon, Sep 26, 2011 at 12:24 PM, John Hunter <jd...@gm...> wrote:
> On Mon, Sep 26, 2011 at 12:05 PM, Katie Boyle <kat...@gm...> wrote:
>> Hi All,
>>
>> I was wondering how I take a list of 250 discrete values and match up each
>> value in the list to a color in the gist_rainbow colormap. I want the
>> highest value to be red, and the lowest value to be blue. I then want to
>> plot a point for each value in the list, and the point's color should
>> represent its value. I cannot use contourf or any other function that does
>> this automatically on a continuous grid--I need to plot individual points.
>
> I think you are looking for "scatter", with the "c" argument being
> your intensity value. You can pass the gist_rainbow colormap to the
> scatter function via the cmap argument. See these examples
>
> http://matplotlib.sourceforge.net/examples/pylab_examples/scatter_demo.html
> http://matplotlib.sourceforge.net/examples/pylab_examples/scatter_demo2.html
Eg,
In [43]: x, y, c = np.random.randn(3, 100)
In [44]: plt.scatter(x, y, c=c, cmap='gist_rainbow')
Out[44]: <matplotlib.collections.PathCollection object at 0x981b22c>

On Mon, Sep 26, 2011 at 12:05 PM, Katie Boyle <kat...@gm...> wrote:
> Hi All,
>
> I was wondering how I take a list of 250 discrete values and match up each
> value in the list to a color in the gist_rainbow colormap. I want the
> highest value to be red, and the lowest value to be blue. I then want to
> plot a point for each value in the list, and the point's color should
> represent its value. I cannot use contourf or any other function that does
> this automatically on a continuous grid--I need to plot individual points.
I think you are looking for "scatter", with the "c" argument being
your intensity value. You can pass the gist_rainbow colormap to the
scatter function via the cmap argument. See these examples
http://matplotlib.sourceforge.net/examples/pylab_examples/scatter_demo.html
http://matplotlib.sourceforge.net/examples/pylab_examples/scatter_demo2.html

Hi All,
I was wondering how I take a list of 250 discrete values and match up each
value in the list to a color in the gist_rainbow colormap. I want the
highest value to be red, and the lowest value to be blue. I then want to
plot a point for each value in the list, and the point's color should
represent its value. I cannot use contourf or any other function that does
this automatically on a continuous grid--I need to plot individual points.
I have tried creating my own colormap with:
my_colors = matplotlib.colors.Colormap(my_list)
but when I issue a pyplot.plot() command with the argument cmap=my_colors, I
get "TypeError: There is no patch property "cmap"
How do I do this correctly?
Cheers,
Katie

Friends,
I have solved the problem by myself. I gave
if w < 2.0: color = 'red'
if 2.1 < w > 4.0: color='blue' So wherever the value there is a value like
2.03 or 2.05, the color was shown as black instead of red/blue.
Thanks,
Bala
On Mon, Sep 26, 2011 at 9:25 AM, Bala subramanian <bal...@gm...
> wrote:
> Friends,
> In the mpl site, i found the an example code called hinton_demo to plot
> weighted matrix in the following link.
>
>
> http://matplotlib.sourceforge.net/examples/api/hinton_demo.html?highlight=hinton
>
> I used the same script (attached test.py) making a slight modification in
> the following section of the code pasted below. I just included more color
> range and modified the size as np.sqrt(np.abs(w))/5.
>
> However when i run the script with test data (attached test.dat), i found
> that the size of the square and color are not matching. For instance the
> size of the squares at position 4,3 and 7,6 are small but the color (black)
> is not relevant to the size. I am not getting what is going wrong. Kindly
> help to resolve the problem.
>
> The script and test data are attached.
>
> *Section of the code modified*
>
> for (x,y),w in np.ndenumerate(W):
> if w > 0: color = 'white'
> else: color = 'black'
> size = np.sqrt(np.abs(w))
> rect = Rectangle([x - size / 2, y - size / 2], size, size,
> facecolor=color, edgecolor=color)
> ax.add_patch(rect)
>
>

Hi,
 I try to apply contrast to an image with set_cmap() like it's explained
in this page http://matplotlib.sourceforge.net/users/image_tutorial.html
http://matplotlib.sourceforge.net/users/image_tutorial.html but when I
apply a new pseudocolor nothing appends. Please help me! This is my code.
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import matplotlib.cm as cm
import numpy as np
import sys
turno=0
pixel=0
img16=open(sys.argv[1],'r')
r=img16.read(2)
val=[]
i=0
riga=[]
while r !="":
	if (pixel>=0) & (pixel<510):
		r1=ord(r[0])
		r2=(ord(r[1])&15)<<8
		ris=(float(r1|r2))/4095
		riga.append([ris,ris,ris])
	else:
		if pixel==511:
			val.append(riga)
			riga=[]
	pixel=(pixel+1)%512
	r=img16.read(2)
#for i in range(512):
#	print len(val[i])
#	print val[i]
val=np.array(val,dtype=np.float32)
imgplot = plt.imshow(val)
imgplot.set_cmap(cm.binary)
plt.show()
-- 
View this message in context: http://old.nabble.com/contrast-image-tp32503930p32503930.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On 25 September 2011 06:59, fdu...@gm... <fdu...@gm...> wrote:
> Dear all,
>
> Heatmap (like those on the page
> http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/r/heatmap/)
> is a frequently used type of image in microarray data analysis. However,
> it seems there are no convenient functions in matplotlib to plot heatmap
> (please correct me if I was wrong), so I'm planning to write my own.
>
> Let me take the heatmap by the link
> http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/r/heatmap/scaled_color_key.png
> as an example, which is produced by R.
>
> With my limited knowledge and expertise of matplotlib, I have the
> following questions and I hope you guys could help me.
>
> 1) I tend to use pcolor to draw the colormap in the central area.
> However, I've seen a lot of examples draw colormap with imshow.
>
>   What's the difference between pcolor and imshow?
>   Shall I use pcolor or imshow to produce the heatmap in the link above?
One difference between pcolor and imshow is that pcolor lines up the
bottom-left corner of each square with the co-ordinates given, whereas
imshow puts the grid center at those co-ordinates. My guess would be
(not having implemented a heatmap) that pcolor would be the more
useful to you to try first for this reason.
> 2) How to draw the dendrograms on the top and left of the colormap?
>
>   I got hints from
> http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html
> on how to append axes to current plot, but I still have now idea how to
> draw the dengrograms.
A quick google search suggests that scipy-cluster might help you out
with the dendrogram drawing. I think I would try using separate axes
objects for the heatmap and the dendrograms, and switch off the frames
of the dendrogram axes.
> 3) How to draw the column side colormap (the smaller one) between the
> top dendrogram and the big colormap?
This could another axes object too. You can use the sharex keyword to
add_axes to get it to have the same x scale as the big axes.
> 4) I can use colorbar to draw a colorbar, but how to place the colorbar
> on the topleft of the image just as the R heatmap does?
Again, the answer is to manually create the axes for your colorbar,
and then specify those axes in the call to colorbar using the `cax`
keyword.
> 5) Any other suggestions on how to draw the heatmap?
I suggest that you give it a try and post your efforts here if there
are any problems. We'll also be keen to see the final result, if you'd
like to share it.
I hope that helps at least a little. Happy coding,
Angus
-- 
AJC McMorland
Post-doctoral research fellow
Neurobiology, University of Pittsburgh

Friends,
In the mpl site, i found the an example code called hinton_demo to plot
weighted matrix in the following link.
http://matplotlib.sourceforge.net/examples/api/hinton_demo.html?highlight=hinton
I used the same script (attached test.py) making a slight modification in
the following section of the code pasted below. I just included more color
range and modified the size as np.sqrt(np.abs(w))/5.
However when i run the script with test data (attached test.dat), i found
that the size of the square and color are not matching. For instance the
size of the squares at position 4,3 and 7,6 are small but the color (black)
is not relevant to the size. I am not getting what is going wrong. Kindly
help to resolve the problem.
The script and test data are attached.
*Section of the code modified*
for (x,y),w in np.ndenumerate(W):
 if w > 0: color = 'white'
 else: color = 'black'
 size = np.sqrt(np.abs(w))
 rect = Rectangle([x - size / 2, y - size / 2], size, size,
 facecolor=color, edgecolor=color)
 ax.add_patch(rect)

Benjamin Root wrote:
> On Sunday, September 25, 2011, Andreas Matthias <and...@gm...>
> wrote:
>> Paul Ivanov wrote:
>> 
>>> On Sat, Sep 24, 2011 at 3:59 AM, Andreas Matthias
>>> <and...@gm...> wrote:
>>>> Hmm. I do not get a reversed list of axes. This is the output of
>>>> the example code below:
>>>> 
>>>> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>,
> <matplotlib.axes.Axes object at 0x8f633ec>]
>>>> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>,
> <matplotlib.axes.Axes object at 0x8f633ec>]
>>> 
>>> This doesn't seem right - for me that code results in:
>>> [<matplotlib.axes.AxesSubplot object at 0x16d7de70>,
>>> <matplotlib.axes.Axes object at 0x1b77c890>]
>>> [<matplotlib.axes.Axes object at 0x1b77c890>,
>>> <matplotlib.axes.AxesSubplot object at 0x16d7de70>]
>>> 
>>> can you try explicitly swapping your axes? f.axes =
>>> [f.axes[1],f.axes[0]] instead of the call to reverse?
>> 
>> Traceback (most recent call last):
>> File "t5.py", line 13, in <module>
>> f.axes = [f.axes[1],f.axes[0]]
>> AttributeError: can't set attribute
>> 
>> 
>> I've tried it with matplotlib 1.0.1 and 1.1.0. Same error message.
>> Python is 2.6.4.
>> I'm stumped ...
> 
> Sometimes installations can get mixed up. What does:
> 
> Import matplotlib
> print matplotlib.__version__
> print matplotlib.__file__
> 
> outputs for your v1.1.0 installation and your v1.0.1 install?
1.1.0
/home/andreas/local/python/lib/python2.6/site-packages/matplotlib/__init__.pyc
This is the right place. Then I removed matplotlib/ and
installed it again. But the error stays the same.
Ciao
Andreas

On Sunday, September 25, 2011, Andreas Matthias <and...@gm...>
wrote:
> Paul Ivanov wrote:
>
>> On Sat, Sep 24, 2011 at 3:59 AM, Andreas Matthias
>> <and...@gm...> wrote:
>>> Hmm. I do not get a reversed list of axes. This is the output of
>>> the example code below:
>>>
>>> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>,
<matplotlib.axes.Axes object at 0x8f633ec>]
>>> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>,
<matplotlib.axes.Axes object at 0x8f633ec>]
>>
>> This doesn't seem right - for me that code results in:
>> [<matplotlib.axes.AxesSubplot object at 0x16d7de70>,
>> <matplotlib.axes.Axes object at 0x1b77c890>]
>> [<matplotlib.axes.Axes object at 0x1b77c890>,
>> <matplotlib.axes.AxesSubplot object at 0x16d7de70>]
>>
>> can you try explicitly swapping your axes? f.axes =
>> [f.axes[1],f.axes[0]] instead of the call to reverse?
>
> Traceback (most recent call last):
> File "t5.py", line 13, in <module>
> f.axes = [f.axes[1],f.axes[0]]
> AttributeError: can't set attribute
>
>
> I've tried it with matplotlib 1.0.1 and 1.1.0. Same error message.
> Python is 2.6.4.
> I'm stumped ...
>
>
> Ciao
> Andreas
>
Sometimes installations can get mixed up. What does:
Import matplotlib
print matplotlib.__version__
print matplotlib.__file__
outputs for your v1.1.0 installation and your v1.0.1 install?
Ben Root

Paul Ivanov wrote:
> On Sat, Sep 24, 2011 at 3:59 AM, Andreas Matthias
> <and...@gm...> wrote:
>> Hmm. I do not get a reversed list of axes. This is the output of
>> the example code below:
>> 
>> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>, <matplotlib.axes.Axes object at 0x8f633ec>]
>> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>, <matplotlib.axes.Axes object at 0x8f633ec>]
> 
> This doesn't seem right - for me that code results in:
> [<matplotlib.axes.AxesSubplot object at 0x16d7de70>,
> <matplotlib.axes.Axes object at 0x1b77c890>]
> [<matplotlib.axes.Axes object at 0x1b77c890>,
> <matplotlib.axes.AxesSubplot object at 0x16d7de70>]
> 
> can you try explicitly swapping your axes? f.axes =
> [f.axes[1],f.axes[0]] instead of the call to reverse?
Traceback (most recent call last):
 File "t5.py", line 13, in <module>
 f.axes = [f.axes[1],f.axes[0]]
AttributeError: can't set attribute
I've tried it with matplotlib 1.0.1 and 1.1.0. Same error message.
Python is 2.6.4.
I'm stumped ...
Ciao
Andreas

Dear all,
Heatmap (like those on the page 
http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/r/heatmap/) 
is a frequently used type of image in microarray data analysis. However, 
it seems there are no convenient functions in matplotlib to plot heatmap 
(please correct me if I was wrong), so I'm planning to write my own.
Let me take the heatmap by the link 
http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/r/heatmap/scaled_color_key.png 
as an example, which is produced by R.
With my limited knowledge and expertise of matplotlib, I have the 
following questions and I hope you guys could help me.
1) I tend to use pcolor to draw the colormap in the central area. 
However, I've seen a lot of examples draw colormap with imshow.
 What's the difference between pcolor and imshow?
 Shall I use pcolor or imshow to produce the heatmap in the link above?
2) How to draw the dendrograms on the top and left of the colormap?
 I got hints from 
http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html 
on how to append axes to current plot, but I still have now idea how to 
draw the dengrograms.
3) How to draw the column side colormap (the smaller one) between the 
top dendrogram and the big colormap?
4) I can use colorbar to draw a colorbar, but how to place the colorbar 
on the topleft of the image just as the R heatmap does?
5) Any other suggestions on how to draw the heatmap?
Thanks and any help will be greatly appreciated.
Regards,
Jianfeng

 Dear all,
Heatmap (like those on the page 
http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/r/heatmap/) 
is a frequently used type of image in microarray data analysis. However, 
it seems there are no convenient functions in matplotlib to plot heatmap 
(please correct me if I was wrong), so I'm planning to write my own.
Let me take the heatmap by the link 
http://www2.warwick.ac.uk/fac/sci/moac/students/peter_cock/r/heatmap/scaled_color_key.png 
as an example, which is produced by R.
With my limited knowledge and expertise of matplotlib, I have the 
following questions and I hope you guys could help me.
1) I tend to use pcolor to draw the colormap in the central area. 
However, I've seen a lot of examples draw colormap with imshow.
 What's the difference between pcolor and imshow?
 Shall I use pcolor or imshow to produce the heatmap in the link above?
2) How to draw the dendrograms on the top and left of the colormap?
 I got hints from 
http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html 
on how to append axes to current plot, but I still have now idea how to 
draw the dengrograms.
3) How to draw the column side colormap (the smaller one) between the 
top dendrogram and the big colormap?
4) I can use colorbar to draw a colorbar, but how to place the colorbar 
on the topleft of the image just as the R heatmap does?
5) Any other suggestions on how to draw the heatmap?
Thanks and any help will be greatly appreciated.
Regards,
Jianfeng

On Sat, Sep 24, 2011 at 3:59 AM, Andreas Matthias
<and...@gm...> wrote:
> Hmm. I do not get a reversed list of axes. This is the output of
> the example code below:
>
> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>, <matplotlib.axes.Axes object at 0x8f633ec>]
> [<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>, <matplotlib.axes.Axes object at 0x8f633ec>]
This doesn't seem right - for me that code results in:
[<matplotlib.axes.AxesSubplot object at 0x16d7de70>,
<matplotlib.axes.Axes object at 0x1b77c890>]
[<matplotlib.axes.Axes object at 0x1b77c890>,
<matplotlib.axes.AxesSubplot object at 0x16d7de70>]
can you try explicitly swapping your axes? f.axes =
[f.axes[1],f.axes[0]] instead of the call to reverse?
> BTW, what's matplotlib.axes.AxesSubplot? I couldn't find this class.
see SubplotBase class and subplot_class_factory function in matplotlib/axes.py
best,
--
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

Hello,
Please consider my attached examples. hw3.py nicely produces multiple axes
electromagnetic spectrum with solar and terrestrial radiation plotted using
Planck's function. However, the major and minor ticks placements are not
nice in those plots and I have decided to use the new axis_grid1 interface.
In the original hw3.py I do multiple plots of desired unit (e.g. wavelength
to wavenumber etc...) I am quite sure that the units shown in the hw3.py are
correctly converted. Now I am planning to produce these conversions with mpl
transformations. Then test1-hw3.py comes into view once again.
Can someone possibly (JJ) give little hint here as to converting from
wavelength to wavenumber using Affine2D and correctly see the ticks located
as the main x-axis.
I do lots of extra lines to get this one working properly in the hw3.py as
shown below:
# multi x-axes
# first wavenumber in cm^-1
parx = ax1.twiny()
parx.axis["top"].set_visible(False)
offset = 0, -60
new_axisline = parx.get_grid_helper().new_fixed_axis
parx.axis["bottom"] = new_axisline(loc="bottom", axes=parx, offset=offset)
parx.axis["bottom"].label.set_visible(True)
parx.axis["bottom"].label.set_text(u"Wavenumber, cm−1")
parx.axis["bottom"].label.set_fontsize(16)
line1, = parx.plot(1/(wavelength[1:]*100), np.ones(len(wavelength[1:])))
line1.set_visible(0)
parx.set_xlim(xmin=1e10,xmax=1/1e6)
parx.set_xscale('log')
Thanks.
-- 
Gökhan

HI modified one of the examples and it brings up the chart window with the
custom toolbar. However, nothing happens with the "pickevent"
"""
This demo demonstrates how to embed a matplotlib (mpl) plot
into a PyQt4 GUI application, including:
* Using the navigation toolbar
* Adding data to the plot
* Dynamically modifying the plot's properties
* Processing mpl events
* Saving the plot to a file from a menu
The main goal is to serve as a basis for developing rich PyQt GUI
applications featuring mpl plots (using the mpl OO API).
Eli Bendersky (el...@gm...)
License: this code is in the public domain
Last modified: 19.01.2009
"""
from __future__ import division
import sys, os, random
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import matplotlib
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as
FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QTAgg as
NavigationToolbar
from matplotlib.figure import Figure
import math
import os
import sys
import matplotlib
from matplotlib import verbose
from matplotlib.backend_bases import cursors
from matplotlib.figure import Figure
try:
 from PyQt4 import QtCore, QtGui, Qt
except ImportError:
 raise ImportError("Qt4 backend requires that PyQt4 is installed.")
cursord = {
 cursors.MOVE : QtCore.Qt.SizeAllCursor,
 cursors.HAND : QtCore.Qt.PointingHandCursor,
 cursors.POINTER : QtCore.Qt.ArrowCursor,
 cursors.SELECT_REGION : QtCore.Qt.CrossCursor,
 }
class NavigationToolbarCustom(NavigationToolbar):
 def __init__(self, *args, **kwargs):
 pixmap = QtGui.QPixmap()
 pixmap.load(':/cross.png')
 cursors.SELECT_POINT = pixmap
 super(NavigationToolbar, self).__init__(*args, **kwargs)
 def _init_toolbar(self):
 self.basedir = os.path.join(matplotlib.rcParams[ 'datapath'
],'images')
 a = self.addAction(self._icon('home.svg'), 'Home', self.home)
 a.setToolTip('Reset original view')
 a = self.addAction(self._icon('back.svg'), 'Back', self.back)
 a.setToolTip('Back to previous view')
 a = self.addAction(self._icon('forward.svg'), 'Forward',
self.forward)
 a.setToolTip('Forward to next view')
 self.addSeparator()
 a = self.addAction(self._icon('move.svg'), 'Pan', self.pan)
 a.setToolTip('Pan axes with left mouse, zoom with right')
 a = self.addAction(self._icon('zoom_to_rect.svg'), 'Zoom',
self.zoom)
 a.setToolTip('Zoom to rectangle')
 a = self.addAction(self._icon('hand.svg'), 'Select',
 self.selectPointMode)
 a.setToolTip('Select the nearest data point')
 self.addSeparator()
 a = self.addAction(self._icon('subplots.png'), 'Subplots',
 self.configure_subplots)
 a.setToolTip('Configure subplots')
 a = self.addAction(self._icon('filesave.svg'), 'Save',
 self.save_figure)
 a.setToolTip('Save the figure')
 self.buttons = {}
 # Add the x,y location widget at the right side of the toolbar
 # The stretch factor is 1 which means any resizing of the toolbar
 # will resize this label instead of the buttons.
 if self.coordinates:
 self.locLabel = QtGui.QLabel( "", self )
 self.locLabel.setAlignment(
 QtCore.Qt.AlignRight | QtCore.Qt.AlignTop )
 self.locLabel.setSizePolicy(
 QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding,
 QtGui.QSizePolicy.Ignored))
 labelAction = self.addWidget(self.locLabel)
 labelAction.setVisible(True)
 # reference holder for subplots_adjust window
 self.adj_window = None
 def mouse_move(self, event):
 print 'mouse_move', event.button
 if not event.inaxes or not self._active:
 if self._lastCursor != cursors.POINTER:
 self.set_cursor(cursors.POINTER)
 self._lastCursor = cursors.POINTER
 else:
 if self._active=='ZOOM':
 if self._lastCursor != cursors.SELECT_REGION:
 self.set_cursor(cursors.SELECT_REGION)
 self._lastCursor = cursors.SELECT_REGION
 if self._xypress:
 x, y = event.x, event.y
 lastx, lasty, a, ind, lim, trans = self._xypress[0]
 self.draw_rubberband(event, x, y, lastx, lasty)
 elif (self._active=='PAN' and
 self._lastCursor != cursors.MOVE):
 self.set_cursor(cursors.MOVE)
 self._lastCursor = cursors.MOVE
 elif self._active=='SELECT':
 if self._lastCursor != cursors.SELECT_POINT:
 QtGui.QApplication.restoreOverrideCursor()
 QtGui.QApplication.setOverrideCursor(QtGui.QCursor(cursors.SELECT_POINT))
 self._lastCursor = cursors.SELECT_POINT
 if event.inaxes and event.inaxes.get_navigate():
 try: s = event.inaxes.format_coord(event.xdata, event.ydata)
 except ValueError: pass
 except OverflowError: pass
 else:
 if len(self.mode):
 self.set_message('%s : %s' % (self.mode, s))
 else:
 self.set_message(s)
 else: self.set_message(self.mode)
 def selectPointMode(self, *args):
 if self._active == 'SELECT':
 self._active = None
 else:
 self._active = 'SELECT'
 if self._idPress is not None:
 self._idPress = self.canvas.mpl_disconnect(self._idPress)
 self.mode = ''
 if self._idRelease is not None:
 self._idRelease = self.canvas.mpl_disconnect(self._idRelease)
 self.mode = ''
 if self._active:
 self._idRelease = self.canvas.mpl_connect(
 'button_press_event', self.selectPoint)
 self.mode = 'pixel select mode'
 self.canvas.widgetlock(self)
 else:
 self.canvas.widgetlock.release(self)
 self.set_message(self.mode)
 def selectPoint(self, event):
 if event.inaxes and event.inaxes.get_navigate():
 print 'selectPoint: ', 1
 self.xdatastart=event.xdata
 print 'selectPoint: ', 2
 self.ydatastart=event.ydata
 self.xstart=event.x
 self.ystart=event.y
 print 'selectPoint: ', 3
 self._banddraw = self.canvas.mpl_connect(
 'motion_notify_event',self.drawband)
 print 'selectPoint: ', 4
 self._idRelease = self.canvas.mpl_disconnect(self._idRelease)
 self._idRelease = self.canvas.mpl_connect(
 'button_release_event', self.selectSecondPoint)
 print 'selectPoint: ', 5
 def selectSecondPoint(self, event):
 if event.inaxes and event.inaxes.get_navigate():
 print 'selectSecondPoint: ', 1
 self._banddraw=self.canvas.mpl_disconnect(self._banddraw)
 print 'selectSecondPoint: ', 2
 self._idRelease = self.canvas.mpl_disconnect(self._idRelease)
 print 'selectSecondPoint: ', 3
 self._idRelease = self.canvas.mpl_connect(
 'button_press_event', self.selectPoint)
 self.draw_rubberband(event, 0, 0, 0, 0)
 print 'selectSecondPoint: ', 4
 self.emit(
 QtCore.SIGNAL('pickEvent'),
 self.xdatastart,
 self.ydatastart,
 event.xdata,
 event.ydata
 )
 print 'selectSecondPoint: ', 5
 def drawband(self, event):
 self.draw_rubberband(event,self.xstart, self.ystart, event.x,
event.y)
 def onPick(self, xstart, ystart, xend, yend):
 xstart_i, ystart_i = self.getIndices(xstart, ystart)
 xend_i, yend_i = self.getIndices(xend, yend)
 if xstart_i > xend_i: xstart_i, xend_i = xend_i, xstart_i
 if ystart_i > yend_i: ystart_i, yend_i = yend_i, ystart_i
 try:
 indices = self.indices[ystart_i:yend_i+1, xstart_i:xend_i+1]
 print indices
 self.emit(QtCore.SIGNAL('pickEvent'), indices.flatten())
 except TypeError:
 pass
 def getIndices(self, xdata, ydata):
 xIndex = locateClosest(xdata, self.xPixelLocs)
 yIndex = locateClosest(ydata, self.yPixelLocs)
 return xIndex, yIndex
def locateClosest(point, points):
 compare = numpy.abs(points-point)
 return numpy.nonzero(numpy.ravel(compare==compare.min()))[0]
class AppForm(QMainWindow):
 def __init__(self, parent=None):
 QMainWindow.__init__(self, parent)
 self.setWindowTitle('Demo: PyQt with matplotlib')
 self.create_menu()
 self.create_main_frame()
 self.create_status_bar()
 self.textbox.setText('1 2 3 4')
 self.on_draw()
 def save_plot(self):
 file_choices = "PNG (*.png)|*.png"
 path = unicode(QFileDialog.getSaveFileName(self,
 'Save file', '',
 file_choices))
 if path:
 self.canvas.print_figure(path, dpi=self.dpi)
 self.statusBar().showMessage('Saved to %s' % path, 2000)
 def on_about(self):
 msg = """ A demo of using PyQt with matplotlib:
 * Use the matplotlib navigation bar
 * Add values to the text box and press Enter (or click "Draw")
 * Show or hide the grid
 * Drag the slider to modify the width of the bars
 * Save the plot to a file using the File menu
 * Click on a bar to receive an informative message
 """
 QMessageBox.about(self, "About the demo", msg.strip())
 def on_pick(self, event):
 # The event received here is of the type
 # matplotlib.backend_bases.PickEvent
 #
 # It carries lots of information, of which we're using
 # only a small amount here.
 #
 box_points = event.artist.get_bbox().get_points()
 msg = "You've clicked on a bar with coords:\n %s" % box_points
 QMessageBox.information(self, "Click!", msg)
 def on_draw(self):
 """ Redraws the figure
 """
 str = unicode(self.textbox.text())
 self.data = map(int, str.split())
 x = range(len(self.data))
 # clear the axes and redraw the plot anew
 #
 self.axes.clear()
 self.axes.grid(self.grid_cb.isChecked())
 self.axes.bar(
 left=x,
 height=self.data,
 width=self.slider.value() / 100.0,
 align='center',
 alpha=0.44,
 picker=5)
 self.canvas.draw()
 def create_main_frame(self):
 self.main_frame = QWidget()
 # Create the mpl Figure and FigCanvas objects.
 # 5x4 inches, 100 dots-per-inch
 #
 self.dpi = 100
 self.fig = Figure((5.0, 4.0), dpi=self.dpi)
 self.canvas = FigureCanvas(self.fig)
 self.canvas.setParent(self.main_frame)
 # Since we have only one plot, we can use add_axes
 # instead of add_subplot, but then the subplot
 # configuration tool in the navigation toolbar wouldn't
 # work.
 #
 self.axes = self.fig.add_subplot(111)
 # Bind the 'pick' event for clicking on one of the bars
 #
 self.canvas.mpl_connect('pick_event', self.on_pick)
 self.canvas.mpl_connect('pickevent', self.onPick)
 # Create the navigation toolbar, tied to the canvas
 #
 self.mpl_toolbar = NavigationToolbarCustom(self.canvas,
self.main_frame)
 # Other GUI controls
 #
 self.textbox = QLineEdit()
 self.textbox.setMinimumWidth(200)
 self.connect(self.textbox, SIGNAL('editingFinished ()'),
self.on_draw)
 self.draw_button = QPushButton("&Draw")
 self.connect(self.draw_button, SIGNAL('clicked()'), self.on_draw)
 self.grid_cb = QCheckBox("Show &Grid")
 self.grid_cb.setChecked(False)
 self.connect(self.grid_cb, SIGNAL('stateChanged(int)'),
self.on_draw)
 slider_label = QLabel('Bar width (%):')
 self.slider = QSlider(QtCore.Qt.Horizontal)
 self.slider.setRange(1, 100)
 self.slider.setValue(20)
 self.slider.setTracking(True)
 self.slider.setTickPosition(QSlider.TicksBothSides)
 self.connect(self.slider, SIGNAL('valueChanged(int)'), self.on_draw)
 #
 # Layout with box sizers
 #
 hbox = QHBoxLayout()
 for w in [ self.textbox, self.draw_button, self.grid_cb,
 slider_label, self.slider]:
 hbox.addWidget(w)
 hbox.setAlignment(w, QtCore.Qt.AlignVCenter)
 vbox = QVBoxLayout()
 vbox.addWidget(self.canvas)
 vbox.addWidget(self.mpl_toolbar)
 vbox.addLayout(hbox)
 self.main_frame.setLayout(vbox)
 self.setCentralWidget(self.main_frame)
 def create_status_bar(self):
 self.status_text = QLabel("This is a demo")
 self.statusBar().addWidget(self.status_text, 1)
 def create_menu(self):
 self.file_menu = self.menuBar().addMenu("&File")
 load_file_action = self.create_action("&Save plot",
 shortcut="Ctrl+S", slot=self.save_plot,
 tip="Save the plot")
 quit_action = self.create_action("&Quit", slot=self.close,
 shortcut="Ctrl+Q", tip="Close the application")
 self.add_actions(self.file_menu,
 (load_file_action, None, quit_action))
 self.help_menu = self.menuBar().addMenu("&Help")
 about_action = self.create_action("&About",
 shortcut='F1', slot=self.on_about,
 tip='About the demo')
 self.add_actions(self.help_menu, (about_action,))
 def add_actions(self, target, actions):
 for action in actions:
 if action is None:
 target.addSeparator()
 else:
 target.addAction(action)
 def create_action( self, text, slot=None, shortcut=None,
 icon=None, tip=None, checkable=False,
 signal="triggered()"):
 action = QAction(text, self)
 if icon is not None:
 action.setIcon(QIcon(":/%s.png" % icon))
 if shortcut is not None:
 action.setShortcut(shortcut)
 if tip is not None:
 action.setToolTip(tip)
 action.setStatusTip(tip)
 if slot is not None:
 self.connect(action, SIGNAL(signal), slot)
 if checkable:
 action.setCheckable(True)
 return action
def main():
 app = QApplication(sys.argv)
 form = AppForm()
 form.show()
 app.exec_()
if __name__ == "__main__":
 main()

Hi,
I'm looking at Darren's example of extending matplotlib's toolbar from 2008.
Any ideal where I can find the base class MplToolbar? Can some just help me
with figuring out which example in matplotlib 1.01 I should start with to
use his cutom ToolBar?
http://www.mailinglistarchive.com/html/mat...@li.../2008-11/msg00107.html
Here is his custom toolbar: (copied from above link)
--------------------------------------------------------------------------------------------------------------------------------------------------------
I have a Toolbar subclass that adds a button to graphically select a subset
from the data, its sort of similar to the zoom tool only it doesnt zoom. This
is specific to Qt4, but maybe you will find it useful. Toolbar._init_toolbar
adds a "Select" action, which is wired so that one corner of a rectangle is
defined by the mouse press, the opposite by the mouse release:
class Toolbar(MplToolbar):
 def __init__(self, *args, **kwargs):
 pixmap = QtGui.QPixmap()
 pixmap.load(':/cross.png')
 mplCursors.SELECT_POINT = pixmap
 super(Toolbar, self).__init__(*args, **kwargs)
 def _init_toolbar(self):
 self.basedir = os.path.join(mpl.rcParams[ 'datapath' ],'images')
 a = self.addAction(self._icon('home.svg'), 'Home', self.home)
 a.setToolTip('Reset original view')
 a = self.addAction(self._icon('back.svg'), 'Back', self.back)
 a.setToolTip('Back to previous view')
 a = self.addAction(self._icon('forward.svg'), 'Forward', self.forward)
 a.setToolTip('Forward to next view')
 self.addSeparator()
 a = self.addAction(self._icon('move.svg'), 'Pan', self.pan)
 a.setToolTip('Pan axes with left mouse, zoom with right')
 a = self.addAction(self._icon('zoom_to_rect.svg'), 'Zoom', self.zoom)
 a.setToolTip('Zoom to rectangle')
 a = self.addAction(QtGui.QIcon(':/crosshairs.svg'), 'Select',
 self.selectPointMode)
 a.setToolTip('Select the nearest data point')
 self.addSeparator()
 a = self.addAction(self._icon('subplots.png'), 'Subplots',
 self.configure_subplots)
 a.setToolTip('Configure subplots')
 a = self.addAction(self._icon('filesave.svg'), 'Save',
 self.save_figure)
 a.setToolTip('Save the figure')
 self.buttons = {}
 # Add the x,y location widget at the right side of the toolbar
 # The stretch factor is 1 which means any resizing of the toolbar
 # will resize this label instead of the buttons.
 if self.coordinates:
 self.locLabel = QtGui.QLabel( "", self )
 self.locLabel.setAlignment(
 QtCore.Qt.AlignRight | QtCore.Qt.AlignTop )
 self.locLabel.setSizePolicy(
 QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding,
 QtGui.QSizePolicy.Ignored))
 labelAction = self.addWidget(self.locLabel)
 labelAction.setVisible(True)
 # reference holder for subplots_adjust window
 self.adj_window = None
 def mouse_move(self, event):
 #print 'mouse_move', event.button
 if not event.inaxes or not self._active:
 if self._lastCursor != mplCursors.POINTER:
 self.set_cursor(mplCursors.POINTER)
 self._lastCursor = mplCursors.POINTER
 else:
 if self._active=='ZOOM':
 if self._lastCursor != mplCursors.SELECT_REGION:
 self.set_cursor(mplCursors.SELECT_REGION)
 self._lastCursor = mplCursors.SELECT_REGION
 if self._xypress:
 x, y = event.x, event.y
 lastx, lasty, a, ind, lim, trans = self._xypress[0]
 self.draw_rubberband(event, x, y, lastx, lasty)
 elif (self._active=='PAN' and
 self._lastCursor != mplCursors.MOVE):
 self.set_cursor(mplCursors.MOVE)
 self._lastCursor = mplCursors.MOVE
 elif self._active=='SELECT':
 if self._lastCursor != mplCursors.SELECT_POINT:
 QtGui.QApplication.restoreOverrideCursor()
 QtGui.QApplication.setOverrideCursor(
QtGui.QCursor(mplCursors.SELECT_POINT))
 self._lastCursor = mplCursors.SELECT_POINT
 if event.inaxes and event.inaxes.get_navigate():
 try: s = event.inaxes.format_coord(event.xdata, event.ydata)
 except ValueError: pass
 except OverflowError: pass
 else:
 if len(self.mode):
 self.set_message('%s : %s' % (self.mode, s))
 else:
 self.set_message(s)
 else: self.set_message(self.mode)
 def selectPointMode(self, *args):
 if self._active == 'SELECT':
 self._active = None
 else:
 self._active = 'SELECT'
 if self._idPress is not None:
 self._idPress = self.canvas.mpl_disconnect(self._idPress)
 self.mode = ''
 if self._idRelease is not None:
 self._idRelease = self.canvas.mpl_disconnect(self._idRelease)
 self.mode = ''
 if self._active:
 self._idRelease = self.canvas.mpl_connect(
 'button_press_event', self.selectPoint)
 self.mode = 'pixel select mode'
 self.canvas.widgetlock(self)
 else:
 self.canvas.widgetlock.release(self)
 self.set_message(self.mode)
 def selectPoint(self, event):
 if event.inaxes and event.inaxes.get_navigate():
 self.xdatastart=event.xdata
 self.ydatastart=event.ydata
 self.xstart=event.x
 self.ystart=event.y
 self._banddraw = self.canvas.mpl_connect(
 'motion_notify_event',self.drawband)
 self._idRelease = self.canvas.mpl_disconnect(self._idRelease)
 self._idRelease = self.canvas.mpl_connect(
 'button_release_event', self.selectSecondPoint)
 def selectSecondPoint(self, event):
 if event.inaxes and event.inaxes.get_navigate():
 self._banddraw=self.canvas.mpl_disconnect(self._banddraw)
 self._idRelease = self.canvas.mpl_disconnect(self._idRelease)
 self._idRelease = self.canvas.mpl_connect(
 'button_press_event', self.selectPoint)
 self.draw_rubberband(event, 0, 0, 0, 0)
 self.emit(
 QtCore.SIGNAL('pickEvent'),
 self.xdatastart,
 self.ydatastart,
 event.xdata,
 event.ydata
 )
 def drawband(self, event):
 self.draw_rubberband(event,self.xstart, self.ystart, event.x, event.y)
The mouse release calls selectSecondPoint, which emits a signal containing the
x and y start and end data. That gets routed to the onPick method on my
Qt4Canvas instance:
 def onPick(self, xstart, ystart, xend, yend):
 xstart_i, ystart_i = self.getIndices(xstart, ystart)
 xend_i, yend_i = self.getIndices(xend, yend)
 if xstart_i > xend_i: xstart_i, xend_i = xend_i, xstart_i
 if ystart_i > yend_i: ystart_i, yend_i = yend_i, ystart_i
 try:
 indices = self.indices[ystart_i:yend_i+1, xstart_i:xend_i+1]
 self.emit(QtCore.SIGNAL('pickEvent'), indices.flatten())
 except TypeError:
 pass
which determines the indices of my data that are contained within the region
defined by the user:
 def getIndices(self, xdata, ydata):
 xIndex = locateClosest(xdata, self.xPixelLocs)
 yIndex = locateClosest(ydata, self.yPixelLocs)
 return xIndex, yIndex
def locateClosest(point, points):
 compare = numpy.abs(points-point)
 return numpy.nonzero(numpy.ravel(compare==compare.min()))[0]

Paul Ivanov wrote:
> On Fri, Sep 23, 2011 at 2:08 PM, Andreas Matthias
> <and...@gm...> wrote:
>> In the following example the coordinates of the mouse
>> cursor displayed in the pylab window belong to the
>> second y-axis. But I would prefer to have the coordinates
>> of the first y-axis to be displayed. Is this possible?
> 
> yes it is.
> 
>> import pylab as mpl
>> 
>> mpl.plot([1,3,2])
>> mpl.twinx()
>> mpl.plot([400,50,100])
>> mpl.show()
> 
> # get the current figure
> f = mpl.gcf()
> 
> # Hide the "background" for the first axes, otherwise it will block
> the second one when we swap
> f.axes[0].set_frame_on(False)
> 
> # Swap the axes
> f.axes.reverse()
> 
> # Turn on the "background" for the *new* first axes (the one that was
> created second)
> f.axes[0].set_frame_on(False)
Hmm. I do not get a reversed list of axes. This is the output of
the example code below:
[<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>, <matplotlib.axes.Axes object at 0x8f633ec>]
[<matplotlib.axes.AxesSubplot object at 0x8d8fb4c>, <matplotlib.axes.Axes object at 0x8f633ec>]
BTW, what's matplotlib.axes.AxesSubplot? I couldn't find this class.
Ciao
Andreas
import pylab as mpl
mpl.plot([1,3,2])
mpl.twinx()
mpl.plot([400,50,100])
f = mpl.gcf()
print f.axes
f.axes[0].set_frame_on(False)
f.axes.reverse()
f.axes[0].set_frame_on(True)
print f.axes
mpl.show()

Hi Eric,
On Wed, Sep 21, 2011 at 9:11 AM, Eric O LEBIGOT (EOL)
<Eri...@no...> wrote:
> With the Mac OS X backend (at least...), error messages are repeatedly printed
> when the mouse leaves the axes rectangle:
>
> File
> "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/backend_macosx.py",
> line 420, in draw_rubberband
>  self.canvas.set_rubberband(x0, y0, x1, y1)
> TypeError: integer argument expected, got float
>
> This problem is annoying because the error messages clutter the terminal,
> and useful printed information leaves the screen. :)
This problem was fixed by 2c924046 (Jim Radford 2011年03月08日 15:07:23 -0800 459)
and now reads:
 self.canvas.set_rubberband(int(x0), int(y0), int(x1), int(y1))
Please update either that line alone, or checkout the latest
matplotlib sources from GitHub.
best,
-- 
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

[Reposting this because it has been "pending" for 2 days]
With the Mac OS X backend (at least...), when zooming (with the rubberband
rectangle), error messages are repeatedly printed when the mouse leaves
(goes outside) the axes rectangle: 
Traceback (most recent call last): 
 File
"/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backend_bases.py",
line 1625, in motion_notify_event 
 self.callbacks.process(s, event) 
 File
"/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/cbook.py",
line 265, in process 
 proxy(*args, **kwargs) 
 File
"/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/cbook.py",
line 191, in __call__ 
 return mtd(*args, **kwargs) 
 File
"/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backend_bases.py",
line 2573, in drag_zoom 
 self.draw_rubberband(event, x, y, lastx, lasty) 
 File
"/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backends/backend_macosx.py",
line 420, in draw_rubberband 
 self.canvas.set_rubberband(x0, y0, x1, y1) 
TypeError: integer argument expected, got float 
This problem is annoying because the error messages clutter the terminal,
and useful printed information leaves the screen. :) 
Configuration: Mac OS X 10.7, latest MacPort's Python and modules,
Matplotlib 1.0.1 with Mac OS X backend.
-- 
View this message in context: http://old.nabble.com/Bug-error-when-zooming-tp32503898p32503898.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Hi Andreas,
On Fri, Sep 23, 2011 at 2:08 PM, Andreas Matthias
<and...@gm...> wrote:
> In the following example the coordinates of the mouse
> cursor displayed in the pylab window belong to the
> second y-axis. But I would prefer to have the coordinates
> of the first y-axis to be displayed. Is this possible?
yes it is.
> import pylab as mpl
>
> mpl.plot([1,3,2])
> mpl.twinx()
> mpl.plot([400,50,100])
> mpl.show()
# get the current figure
f = mpl.gcf()
# Hide the "background" for the first axes, otherwise it will block
the second one when we swap
f.axes[0].set_frame_on(False)
# Swap the axes
f.axes.reverse()
# Turn on the "background" for the *new* first axes (the one that was
created second)
f.axes[0].set_frame_on(False)
you can also achieve the same effect by changing the zorder of axes -
provided that you remember to have turn the frame on for the one that
is the furthest back, and turn it off for all others lying on top of
it. You can see what happens if you don't do this by omitting the
calls to set_frame_on, and then verifying that the second line does
not show up (because the original axes' frame patch is blocking it.
best,
-- 
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

One more update, before heading to the bed.
I have managed to adjust my ticks to get what I was asking originally. See
the code at http://pastebin.com/XjkDZ486
1-) ax1.yaxis.set_minor_locator(ticker.LogLocator(subs=np.arange(2.0, 10.0))
)
with this line I can get the desired number of minor ticks at the correct
positions
2-) #ax1.xaxis.set_ticks(10.**np.arange(np.log10(xmin),np.log10(xmax)+1,1))
this line puts major at every decade but minors aren't printed correctly due
to striding at major ticks.
3-) To get this one working I needed to modify the code within the
ticker.LogLocator()
particularly the two lines starting at
https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/ticker.py#L1311
decades = np.arange(math.floor(vmin),
 math.ceil(vmax)+stride, stride)
edited to
decades = np.arange(math.floor(vmin),
 math.ceil(vmax)+1, 1)
previously I was getting a major tick at every other decade. With this
change I get a major tick at every decade plus the minor ticks look nicer.
So my opinion is this stride should be parameter to the LogLocator(), so
based on what people wants to plot it can be easily adjusted.
Any comments/other solutions?
Thanks.
*
*
On Fri, Sep 23, 2011 at 10:47 PM, Gökhan Sever <gok...@gm...>wrote:
> OK,
>
> This fixes the minor locations on y-axis
>
> ax1.yaxis.set_minor_locator(ticker.LogLocator(subs=np.arange(2.0, 10.0)))
>
> Independent of the data-range. It seems like ticker.LogLocator is trying to
> adjust the minor locs internally.
>
>
> On Fri, Sep 23, 2011 at 7:18 PM, Gökhan Sever <gok...@gm...>wrote:
>
>> Hi,
>>
>> Another question is, what sets the tick-location on a log scaled axis?
>> (that 10^-5, 10^-3, 10^-1, 10^1) It seems as if the range is greater than
>> certain value ticks are located this way. Also in a similar way, the
>> location of minor ticks are decided. (If the range is big, no minor ticks,
>> if the range is not too big, put 4 minor ticks --which is
>> very inconvenient to eye, if range is small then nicely locate 9 minor
>> ticks.)
>>
>> Hah, the next probably will be manually forcing the _ticks or ticklocator
>> functions.
>>
>> Anyone else experiencing similar behavior in mpl?
>>
>> On Fri, Sep 23, 2011 at 1:07 PM, Gökhan Sever <gok...@gm...>wrote:
>>
>>> Hello,
>>>
>>> Considering this example plot:
>>> http://imageshack.us/photo/my-images/27/imagefki.png/
>>>
>>> How can I get the minor ticks showing correctly? (ie., 9 minor ticks per
>>> decade likewise for the x-axis)
>>>
>>> For some reason
>>>
>>> axis.set_minor_locator(LogLocator(numdecs=9) is not producing the desired
>>> output.
>>>
>>> Any hints?
>>>
>>> Thanks.
>>>
>>> --
>>> Gökhan
>>>
>>
>>
>>
>> --
>> Gökhan
>>
>
>
>
> --
> Gökhan
>
-- 
Gökhan

OK,
This fixes the minor locations on y-axis
ax1.yaxis.set_minor_locator(ticker.LogLocator(subs=np.arange(2.0, 10.0)))
Independent of the data-range. It seems like ticker.LogLocator is trying to
adjust the minor locs internally.
On Fri, Sep 23, 2011 at 7:18 PM, Gökhan Sever <gok...@gm...> wrote:
> Hi,
>
> Another question is, what sets the tick-location on a log scaled axis?
> (that 10^-5, 10^-3, 10^-1, 10^1) It seems as if the range is greater than
> certain value ticks are located this way. Also in a similar way, the
> location of minor ticks are decided. (If the range is big, no minor ticks,
> if the range is not too big, put 4 minor ticks --which is
> very inconvenient to eye, if range is small then nicely locate 9 minor
> ticks.)
>
> Hah, the next probably will be manually forcing the _ticks or ticklocator
> functions.
>
> Anyone else experiencing similar behavior in mpl?
>
> On Fri, Sep 23, 2011 at 1:07 PM, Gökhan Sever <gok...@gm...>wrote:
>
>> Hello,
>>
>> Considering this example plot:
>> http://imageshack.us/photo/my-images/27/imagefki.png/
>>
>> How can I get the minor ticks showing correctly? (ie., 9 minor ticks per
>> decade likewise for the x-axis)
>>
>> For some reason
>>
>> axis.set_minor_locator(LogLocator(numdecs=9) is not producing the desired
>> output.
>>
>> Any hints?
>>
>> Thanks.
>>
>> --
>> Gökhan
>>
>
>
>
> --
> Gökhan
>
-- 
Gökhan

Hi,
Another question is, what sets the tick-location on a log scaled axis? (that
10^-5, 10^-3, 10^-1, 10^1) It seems as if the range is greater than certain
value ticks are located this way. Also in a similar way, the location of
minor ticks are decided. (If the range is big, no minor ticks, if the range
is not too big, put 4 minor ticks --which is very inconvenient to eye, if
range is small then nicely locate 9 minor ticks.)
Hah, the next probably will be manually forcing the _ticks or ticklocator
functions.
Anyone else experiencing similar behavior in mpl?
On Fri, Sep 23, 2011 at 1:07 PM, Gökhan Sever <gok...@gm...> wrote:
> Hello,
>
> Considering this example plot:
> http://imageshack.us/photo/my-images/27/imagefki.png/
>
> How can I get the minor ticks showing correctly? (ie., 9 minor ticks per
> decade likewise for the x-axis)
>
> For some reason
>
> axis.set_minor_locator(LogLocator(numdecs=9) is not producing the desired
> output.
>
> Any hints?
>
> Thanks.
>
> --
> Gökhan
>
-- 
Gökhan

In the following example the coordinates of the mouse
cursor displayed in the pylab window belong to the
second y-axis. But I would prefer to have the coordinates
of the first y-axis to be displayed. Is this possible?
import pylab as mpl
mpl.plot([1,3,2])
mpl.twinx()
mpl.plot([400,50,100])
mpl.show()
Ciao
Andreas