Re: memory error with matplot
lisa == lisa engblom [EMAIL PROTECTED] writes:
lisa Hi, I am using matplotlib with python to generate a bunch of
lisa charts. My code works fine for a single iteration, which
lisa creates and saves 4 different charts. The trouble is that
lisa when I try to run it for the entire set (about 200 items) it
lisa can run for 12 items at a time. On the 13th, I get an error
lisa from matplotlib that says it can't access data. However, if
lisa I start the program at the point it failed before it works
lisa fine and will create the charts for the next 12 before
lisa failing. I assume that I am not closing the files properly
lisa somehow or otherwise misallocating memory. I tried just
lisa reimporting pylab each iteration, but that didn't help.
lisa This is the function that creates a chart:
There are a couple of things to try. First, on a long shot, does it
help to do
close(1)
instead if simply close(). I don't think it will but worth a try.
Second, I think there is a small leak in the tkcanvas, but not in
matplotlib proper. Do you need to display the graphs you are
creating, or do you merely want to save them? If the latter, simply
use the Agg backend
import matplotlib
matplotlib.use('Agg')
*before* you import pylab.
Finally, if you are still having troubles, post a complete,
free-standing, script to the matplotlib mailing list and we'll see if
we can replicate it.
You may also want to take a look at the FAQ on memory leaks:
http://matplotlib.sourceforge.net/faq.html#LEAKS
JDH
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Re: Global module variables as default parameters
Christoph == Christoph Haas [EMAIL PROTECTED] writes: Christoph Hi, list... I wondered if it's possible to use global Christoph (module) variables as default parameters. A simple Christoph working example: Christoph Christoph #!/usr/bin/python Christoph globalvar = 123 Christoph def test(foo=globalvar): print foo kwargs defaults are initialized a module load time, not at function call time. The standard idiom is def test(foo=None): if foo is None: foo = globalvar print foo JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: newbie graphing recommendations ?
bearophileHUGS == bearophileHUGS [EMAIL PROTECTED] writes:
bearophileHUGS I think MatPlotLib can do this too, if your
bearophileHUGS computer is fast enough.
i would also like to have the bars and graphs have nice shading
if possible to give it a really attractive look.
bearophileHUGS Remember what Edward Tufte (www.edwardtufte.com)
bearophileHUGS says, often too much elaborations makes graphs
bearophileHUGS them less than useless.
I share Tufte's opinion that you should avoid chart-junk -- stuff
designed to make charts look sexier that don't add information
context. matplotlib can do it (but doesn't go out of it's way to make
it easy). Eg,
from pylab import figure, show, nx, cm
def gbar(ax, x, y, width=0.5, bottom=0):
X = [[.6, .6],[.7,.7]]
for left,top in zip(x, y):
right = left+width
ax.imshow(X, interpolation='bicubic', cmap=cm.Blues,
extent=(left, right, bottom, top), alpha=1)
fig = figure()
xmin, xmax = xlim = 0,10
ymin, ymax = ylim = 0,1
ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
autoscale_on=False)
X = [[.6, .6],[.7,.7]]
ax.imshow(X, interpolation='bicubic', cmap=cm.copper,
extent=(xmin, xmax, ymin, ymax), alpha=1)
N = 10
x = nx.arange(N)+0.25
y = nx.mlab.rand(N)
gbar(ax, x, y, width=0.7)
ax.set_aspect('normal')
show()
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tk filesave dialog triggers unexpected destroy event
The following behavior surprised me. I have a Tk window and launch a
file save dialog from it. When the filesave dialog is finished, it
calls callbacks bound to the destroy event on the main window. Is
this expected, and can I avoid this?
To expose the problem, run this script and click the mouse button over
the application window. When the file save dialog is through, the
function callback is called, which I did not expect because I bound
this callback to the window destroy event.
Thanks for any advice. Using Tk 1.177
JDH
import Tkinter as Tk
from tkFileDialog import asksaveasfilename
def button(event):
fname = asksaveasfilename(
title='Save the figure'
)
window = Tk.Tk()
frame = Tk.Frame(window, width=500,height=500)
frame.bind('Button-1', button)
frame.pack()
def callback(*args):
print 'called callback'
window.bind(Destroy, callback)
window.mainloop()
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Re: image output in matplotlib
mart == mart jeeha [EMAIL PROTECTED] writes: mart Hey folks, I got a problem in printing images from a mart matplotlib - FigureCanvas Object (child of a wxFrame, mart library backend_wx) into jpeg-formatted files. (I like to mart create a sequence of images that I can assemble to an avi) mart self.mycanvas.print_figure(test.jpg) merely gives an error mart stating, that there should be an image handler of type 17, mart which I didn't come across ever :) Was your wx built with jpeg support? You might try png, which matplotlib supports natively. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: numeric/numpy/numarray
Bryan == Bryan [EMAIL PROTECTED] writes: Bryan hi, what is the difference among numeric, numpy and Bryan numarray? i'm going to start using matplotlib soon and i'm Bryan not sure which one i should use. numpy is the successor to numarray and Numeric. All three do basically the same thing. You should use numpy. matplotlib works with all three, you just need to be sure to set your numerix setting to numpy in your matplotlibrc file. numerix : numpy # numpy, Numeric or numarray On unix like OSes, this file is placed in ~/.matplotlib. On windows systems, it is usually found in C:\Documents and Settings\yourname\.matplotlib JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: how not to run out of memory in cursor.execute
[EMAIL PROTECTED] == [EMAIL PROTECTED] com [EMAIL PROTECTED] writes: [EMAIL PROTECTED] whenever you are using a package that leaks memory. [EMAIL PROTECTED] it can be appropriate to use Rpyc [EMAIL PROTECTED] (http://rpyc.wikispaces.com/) to run the leaking [EMAIL PROTECTED] code in a different process, and restart it from [EMAIL PROTECTED] time to time. I've been using this method to avoid [EMAIL PROTECTED] the leaks of matplotlib. The only known leak in matplotlib is in the tkagg backend which we believe comes from tkinter and is not in matplotlib proper. There are a variety of ways to make it look like matplotlib is leaking memory, eg overplotting when you want to first clear the plot, or failing to close figures properly. We have unit tests to check for leaks, and they are passing. Perhaps you can post some code which exposes the problem. JDH -- http://mail.python.org/mailman/listinfo/python-list
curses event handling
I have a curses app that is displaying real time data. I would like
to bind certain keys to certain functions, but do not want to block
waiting for
c = screen.getch()
Is it possible to register callbacks with curses, something like
screen.register('keypress', myfunc)
Thanks,
JDH
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Re: two of pylab.py
Diez == Diez B Roggisch [EMAIL PROTECTED] writes: I use debian/testing linux Linux debian/testing 2.6.15-1-686 I found some duplicate files in my system, I don't if the are both needed, should I delete one of the groups below and which one? site-packages/pylab.py is just there for convenience to import matplotlib.pylab, since it is easier to type import pylab rather than import matplotlib.pylab You should leave all of the file as is, because code will assume both are there. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Non-web-based templating system
Alex == Alex Martelli [EMAIL PROTECTED] writes: Alex I have a certain fondness for the first over-100-lines Alex module I wrote for Python, which eventually resulted in: As well you should! YAPTU powers the entire matplotlib website (screenshots, FAQ, what's new, etc), as evidenced by the Powered by YAPTU co-branding on the bottom of every page http://matplotlib.sf.net with src (*.html.template) at http://svn.sourceforge.net/viewcvs.cgi/matplotlib/trunk/htdocs/ I must confess though that the prehistoric YAPTU version I use comes in at only 78 lines, so it is clearly time for me to upgrade. I rely on it so much I even wrote a debian ubuntu package for local use, as twisted as that may seem. I definitely need to check out the latest version! JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Events in Python?
redefined == redefined horizons [EMAIL PROTECTED] writes:
redefined Here is another non-pythonic question from the Java
redefined Developer. (I beg for forgiveness...)
redefined Does Python have a mechanism for events/event-driven
redefined programming?
The enthought traits package has built-in support for event handling,
among other things
http://code.enthought.com/traits/
Here is an example from the web page:
from enthought.traits import Delegate, HasTraits, Int, Str, Instance
from enthought.traits.ui import View, Item
class Parent(HasTraits):
first_name = Str('') # INITIALIZATION:
last_name = Str('') # 'first_name' and
# 'last_name' are
# initialized to ''
class Child(HasTraits):
age = Int
father = Instance(Parent) # VALIDATION: 'father' must
# be a Parent instance
first_name = Str('')
last_name = Delegate('father') # DELEGATION:
# 'last_name' is
# delegated to
# father's 'last_name'
def _age_changed(self, old, new): # NOTIFICATION:
# This method is
# called when 'age'
# changes
print 'Age changed from %s to %s ' % (old, new)
traits_view = View(Item(name='first_name'), # TRAITS UI: Define
Item(name='last_name', # the default window
style='readonly'),# layout
Item(name='age'),
Item(name='father'))
# Make and manipulate objects from the classes above
joe = Parent()
joe.last_name = 'Johnson'
# DELEGATION in action
moe = Child()
moe.father = joe
print Moe's last name is %s % (moe.last_name)
# NOTIFICATION in action
moe.age = 10
#VISUALIZATION: Display the UI
moe.configure_traits()
The DELEGATION and NOTIFICATION segments in the above example yield
the following command-line output:
Moe's last name is Johnson
Age changed from 0 to 10
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Re: Plotting package?
Andrew == Andrew Koenig [EMAIL PROTECTED] writes:
Andrew This may be a foolish question, but what's the most
Andrew straightforward way to plot a bunch of data in Python?
in matplotlib/pylab
from pylab import figure, show
x = range(10)
y = [val**2 for val in x]
fig = figure()
ax = fig.add_subplot(111)
ax.plot(x,y)
ax.set_title('My first plot')
ax.set_xlabel('x')
ax.set_ylabel('y')
show()
Tutorial: http://matplotlib.sourceforge.net/tutorial.html
Screenshots: http://matplotlib.sourceforge.net/screenshots.html
JDH
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Re: Phython and graphing
mostro == mostro [EMAIL PROTECTED] writes:
mostro Hello, Can someone lead me to an easy way to create a
mostro graph in Python.
mostro For example, I have a script running that creates a list
mostro of dates, times and values. I would like to turn this into
mostro a graph.
mostro I can grep the info into a new file creating two columns
mostro (x,y) but the issue is the graph.
mostro P.S. I'm a Python newbie so keep that in mind.
Here's an example from the matplotlib examples dir
http://matplotlib.sf.net/examples
that does just that. It loads dates and values from a file using the
load function, and then plots them with the plot_date command
The delimiter directive in the load command says to use comma
separated values. The converters arg is a dictionary mapping column
number to a function that converts that column to a float (datestr2num
converts date strings to matplotlib dates using the wonderful
dateutil.parser.parse function that can convert just about any date
string -- the default column converter is 'float'). skiprows
indicates that there is a single line of header to convert, and
usecols says to take the first and third columns.
The rest is easy -- just call plot_dates:
from pylab import figure, show, datestr2num, load
dates, closes = load(
'data/msft.csv', delimiter=',',
converters={0:datestr2num}, skiprows=1, usecols=(0,2),
unpack=True)
fig = figure()
ax = fig.add_subplot(111)
ax.plot_date(dates, closes)
show()
Here is a brief look at the data file being plotted:
Date,Open,High,Low,Close,Volume,Adj. Close*
19-Sep-03,29.76,29.97,29.52,29.96,92433800,29.79
18-Sep-03,28.49,29.51,28.42,29.50,67268096,29.34
17-Sep-03,28.76,28.95,28.47,28.50,47221600,28.34
16-Sep-03,28.41,28.95,28.32,28.90,52060600,28.74
15-Sep-03,28.37,28.61,28.33,28.36,41432300,28.20
and many more
JDH
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Re: Using Python To Create An Encrypted Container
Michael == Michael Sperlle [EMAIL PROTECTED] writes: Michael Is it possible? Bestcrypt can supposedly be set up on Michael linux, but it seems to need changes to the kernel before Michael it can be installed, and I have no intention of going Michael through whatever hell that would cause. Michael If I could create a large file that could be encrypted, Michael and maybe add files to it by appending them and putting Michael in some kind of delimiter between files, maybe a homemade Michael version of truecrypt could be constructed. One problem in using a large file which is encrypted is that a single byte error can destroy all your data (see DEDICATION below). I wrote a little python module called hashtar that works like tar, but encrypts every file independently in a flattened dir structure with filename hiding. It stores the file permissions, dir structure, and ownership in an encrypted header of each encrypted file after first padding some random data at the top to reduce the risk of known plaintext attacks. Here is some example usage hashtar.py -cvf numeric.htar numeric Password: Confirm: numeric/__init__.py - numeric.htar/1a/1a9f48d439144d1fa33b186fa49a6b63 numeric/contiguous_demo.py - numeric.htar/8a/8a7757bf6f4a20e6904173f7c597eb45 numeric/diff_dmo.py - numeric.htar/0c/0cea827761aef0ccfc55a869dd2aeb38 numeric/fileio.py - numeric.htar/3e/3e50f59a1d2d87307c585212fb84be6a numeric/find - numeric.htar/b1/b1070de08f4ea531f10abdc58cfe8edc ...snip find numeric.htar|head numeric.htar numeric.htar/1a numeric.htar/1a/1a9f48d439144d1fa33b186fa49a6b63 numeric.htar/8a numeric.htar/8a/8a7757bf6f4a20e6904173f7c597eb45 numeric.htar/8a/8a4343ba60feda855fbaf8132e9b5a6b numeric.htar/8a/8a72457096828c8d509ece6520e49d0b numeric.htar/0c numeric.htar/0c/0cea827761aef0ccfc55a869dd2aeb38 numeric.htar/3e hashtar.py -tvf numeric.htar Password: 131 numeric/__init__.py 594 numeric/contiguous_demo.py 26944 numeric/Quant.pyc 209 numeric/extensions/test/rpm_build.sh 230 numeric/diff_dmo.py 439 numeric/fileio.py It works across platforms (win32, OSX and linux tested), so files encrypted on one will decrypt on others. All the code lives in a single file (hashtar.py) included below. See also the WARNING below (hint -- I am not a cryptographer) #!/usr/bin/env python OVERVIEW hashtar: an encrypted archive utility designed for secure archiving to media vulnerable to corruption. Recursively encrypt the files and directories passed as arguments. Rather than preserving the directory structure, or archiving to a single file as in tar, the files are encrypted to a single dir and named with the hash of their relative path. The file information (filename, permission mode, uid, gid) is encrypted and stored in the header of the file itself, and can be used to restore the original file with dir structure from the archive file. For example, the command hashtar.py -cvf tmp.htar finance/ prompts for a password and generates an encrypted recursive archive of the finance dir in the tmp.htar dir, with filenames mapped like finance/irs/98/f1040.pdf - tmp.htar/e5/e5ed546c0bc0191d80d791bc2f73c890 finance/sale_house/notes - tmp.htar/58/580e89bad7563ae76c295f75aecea030 finance/online/accounts.gz.mcr - tmp.htar/bb/bbf12f06dc3fcee04067d40b9781f4a8 finance/phone/prepaid1242.doc - tmp.htar/c1/c1fe52a9d8cbef55eff8840d379d972a The encrypted files are placed in subdirs based on the first two characters in their hash name because if too many files are placed in one dir, it may not be possible to pass all of them as command line arguments to the restore command. The entire finance dir structure can later be restored with hashtar.py -xvf tmp.htar The advantage of this method of encrypted archiving, as opposed to archiving to a single tar file and encrypting it, is that this method is not sensitive to single byte corruption, which becomes important especially on externally stored archives, such as on CDR, or DVDR. Any individual file contains all the information needed to restore itself, with directory structure, permission bits, etc. So only the specific files that are corrupted on the media will be lost. The alternative strategy, encrypting all the files in place and then archiving to external media, doesn't suffer from single byte corruption but affords less privacy since the filenames, dir structure, and permission bits are available, and less security since a filename may indicate contents and thus expose the archive to a known plaintext attack. A match string allows you to only extract files matching a given pattern. Eg, to only extract pdf and xls files, do hashtar.py -m pdf,xls -xvf tmp.htar Because the filenames are stored in the header, only a small
Re: Calling Python from Matlab
AgenteSegreto == AgenteSegreto [EMAIL PROTECTED] writes: AgenteSegreto I've been a Matlab user for years and have recently AgenteSegreto started using Python with matplotlib and NumPy for AgenteSegreto most of my work. The only thing I found that is AgenteSegreto still lacking is a 3D capability in matplotlib. I There is some progress being made on this front -- in svn are a collection of classes for basic 3d plots (plot3, mesh, surf) but the interface to these is still under development. We hope they will be included in the next major release 0.88. You can see some examples here: http://www.scipy.org/Wiki/Cookbook/Matplotlib/mplot3D Also, there is a master's student who will be working on extending mpl 3d capabilities as part of her master's project, so expect some basic functionality in the near future. We certainly don't aim to compete with VTK or other full-blown 3D solutions like Mayavi http://mayavi.sourceforge.net/ http://www.enthought.com/enthought/wiki/MayaVi http://www.scipy.org/ArndBaecker/MayaVi2 but most agree it would be nice to have some support for basic 3D plotting in matplotlib. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: can I get the index number in for x in y loop?
Scott == Scott David Daniels [EMAIL PROTECTED] writes: Scott I cannot find the distance in meters between Paris and Scott London with: for i in range(10): print i Works for me def range(x): yield '332.8 km' for i in range(10): print i ...may not be considered best practice, though wink JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib: How to set number of ticks on an axis?
Caleb == Caleb Hattingh [EMAIL PROTECTED] writes: Caleb It seems that the locater() classes are where I should Caleb look, and there seem to be some defaults in ticker.py: Caleb class AutoLocator(MaxNLocator): def __init__(self): Caleb MaxNLocator.__init__(self, nbins=9, steps=[1, 2, 5, 10]) Caleb I don't understand what this means :) Caleb I would prefer not to hack this directly in the matplotlib Caleb code. How can I change the number of ticks on an axis Caleb programmatically without messing with the other ticklabel Caleb functionality? Yes, you will want to use a MaxNLocator. Note that the MaxNLocator sets the maximum number of *intervals* so the max number of ticks will be the max number of intervals plus one. from matplotlib.ticker import MaxNLocator from pylab import figure, show, nx fig = figure() ax = fig.add_subplot(111) ax.plot(nx.mlab.rand(1000)) ax.xaxis.set_major_locator(MaxNLocator(4)) show() JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib: Histogram with bars inside grid lines...how??
Enigma == Enigma Curry [EMAIL PROTECTED] writes: Enigma I'm playing around with matplotlib for the first time. I'm Enigma trying to make a very simple histogram of values 1-6 and Enigma how many times they occur in a sequence. However, after Enigma about an hour of searching I cannot make the histogram Enigma stay within the bounds of the grid lines. Enigma Here is my example: Enigma pylab.grid() x_values=[1,1,2,2,2,3,3,3,4,4,4,5,5,6,6,6] Enigma pylab.hist(x_values,6) pylab.show() Enigma This produced the following image: Enigma http://enigmacurry.com/usenet/historgram-bars-not-in-grid-lines.png Enigma Starting with bar number 2, it creeps into grid 1.. and Enigma finally with bar number 5 it's almost entirely in grid Enigma 4.. how do I make the bars stay in their own grid lines? While exactly what you want is something of an enigma to me, I can offer some advice and terminology. The bars of hist make no attempt to stay within the bounds of the grid lines... The bars have as their left most boundary the bins you choose for the histogram. As a first step, I suggest setting these bins explicitly, rather than letting the hist command choose them automatically from pylab import hist, xlim, nx, show x_values= [1,1,2,2,2,3,3,3,4,4,4,5,5,6,6,6] bins = nx.arange(0.5, 7.) hist(x_values, bins) xlim(0,6.5) show() The grid line locations are determined by the xtick locations, which you can set with the xticks command. Good luck! JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib: Histogram with bars inside grid lines...how??
Enigma == Enigma Curry [EMAIL PROTECTED] writes:
Enigma pylab.xlim(0.5,6.5) should be:
Enigma pylab.xlim(min_x-(bar_width/2),max_x+(bar_width/2))
Glad it's working better for you -- just a couple more smallish hints.
You might prefer to have your grid lines behind, rather than above the
bars. In that case create the subplot or axes with the axisbelow=True
kwarg. Despite the fact that you found the kwargs a little annoying
at first, you will probably come to love them. matplotlib makes very
heavy use of them and they are very useful since they allow matplotlib
to usually do the right things while exposing most of the settings to
you. Eg
plot(x, y,
linewidth=2, linestyle='--',
marker='o', markerfacecolor='r', markeredgecolor='g'
markeredgewith=2, markersize=10)
and so on. There are lots of properties you can set on almost every
command. Because noone wants to type all that, you can use aliases
plot(x, y, lw=2, ls='--', marker='o', mfc='r', mec='g', mew=2, ms=10)
Secondly, in your example, you are relying implicitly on matplotlib to
pick integer ticks for the xaxis. It's doing it right in this
example, but might prefer other tick locations for other examples
depending on your x_values. So set xticks explicitly.
Below is a slightly modified example showing these two ideas.
You also might want to consider joining the mailing list at
http://lists.sourceforge.net/mailman/listinfo/matplotlib-users
since you appear to be a little finicky about your figures :-)
def ryan_hist(data, bar_width, min_x, max_x):
Create a frequency histogram over a continuous interval
min_x = the low end of the interval
max_x = the high end of the interval
bar_width = the width of the bars
This will correctly align the bars of the histogram
to the grid lines of the plot
#Make histogram with bars of width .9 and center
#them on the integer values of the x-axis
bins = pylab.nx.arange(1-(bar_width/2),max(data))
pylab.subplot(111, axisbelow=True)
n,bins,patches = pylab.hist(data, bins, width=bar_width)
#Make Y axis integers up to highest n
pylab.yticks(pylab.arange(max(n)))
pylab.xticks(pylab.arange(max(n)+1))
pylab.axis('scaled')
pylab.xlim(min_x-(bar_width/2),max_x+(bar_width/2))
pylab.grid()
pylab.show()
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Re: Computing correlations with SciPy
tkpmep == tkpmep [EMAIL PROTECTED] writes: tkpmep I want to compute the correlation between two sequences X tkpmep and Y, and tried using SciPy to do so without success.l tkpmep Here's what I have, how can I correct it? X = [1, 2, 3, 4, 5] Y = [5, 4, 3, 2, 1] import scipy scipy.corrcoef(X,Y) tkpmep Traceback (most recent call last): File interactive tkpmep input, line 1, in ? File tkpmep C:\Python24\Lib\site-packages\numpy\lib\function_base.py, tkpmep line 671, in corrcoef d = diag(c) File tkpmep C:\Python24\Lib\site-packages\numpy\lib\twodim_base.py, tkpmep line 80, in diag raise ValueError, Input must be 1- or tkpmep 2-d. ValueError: Input must be 1- or 2-d. Hmm, this may be a bug in scipy. matplotlib also defines a corrcoef function, which you may want to use until this problem gets sorted out In [9]: matplotlib.mlab.corrcoef(X,Y) In [10]: X = [1, 2, 3, 4, 5] In [11]: Y = [5, 4, 3, 2, 1] In [12]: matplotlib.mlab.corrcoef(X,Y) Out[12]: array([[ 1., -1.], [-1., 1.]]) -- http://mail.python.org/mailman/listinfo/python-list
Re: FIR filtering
LabWINC == LabWINC [EMAIL PROTECTED] writes: LabWINC Hi all, i'm looking for a module to implement a digital LabWINC FIR filter! Can anyone help me? scipy.org Between scipy and matplotlib, you'll feel quite comfortable with python as a former matlab user help scipy.filter (see FIR filter design below) DESCRIPTION Signal Processing Tools === Convolution: convolve -- N-dimensional convolution. correlate -- N-dimensional correlation. fftconvolve -- N-dimensional convolution using the FFT. convolve2d-- 2-dimensional convolution (more options). correlate2d -- 2-dimensional correlation (more options). sepfir2d -- Convolve with a 2-D separable FIR filter. B-splines: bspline -- B-spline basis function of order n. gauss_spline -- Gaussian approximation to the B-spline basis function. cspline1d -- Coefficients for 1-D cubic (3rd order) B-spline. qspline1d -- Coefficients for 1-D quadratic (2nd order) B-spline. cspline2d -- Coefficients for 2-D cubic (3rd order) B-spline. qspline2d -- Coefficients for 2-D quadratic (2nd order) B-spline. Filtering: order_filter -- N-dimensional order filter. medfilt -- N-dimensional median filter. medfilt2 -- 2-dimensional median filter (faster). wiener-- N-dimensional wiener filter. symiirorder1 -- 2nd-order IIR filter (cascade of first-order systems). symiirorder2 -- 4th-order IIR filter (cascade of second-order systems). lfilter -- 1-dimensional FIR and IIR digital linear filtering. deconvolve-- 1-d deconvolution using lfilter. hilbert --- Compute the analytic signal of a 1-d signal. get_window--- Create FIR window. detrend --- Remove linear and/or constant trends from data. Filter design: remez -- Optimal FIR filter design. firwin--- Windowed FIR filter design. iirdesign --- IIR filter design given bands and gains iirfilter --- IIR filter design given order and critical frequencies freqs --- Analog filter frequency response freqz --- Digital filter frequency response Matlab-style IIR filter design: butter (buttord) -- Butterworth cheby1 (cheb1ord) -- Chebyshev Type I cheby2 (cheb2ord) -- Chebyshev Type II ellip (ellipord) -- Elliptic (Cauer) bessel-- Bessel (no order selection available -- try butterod) Linear Systems: lti -- linear time invariant system object. lsim -- continuous-time simulation of output to linear system. impulse -- impulse response of linear, time-invariant (LTI) system. step -- step response of continous-time LTI system. LTI Reresentations: tf2zpk -- transfer function to zero-pole-gain. zpk2tf -- zero-pole-gain to transfer function. tf2ss -- transfer function to state-space. ss2tf -- state-pace to transfer function. zpk2ss -- zero-pole-gain to state-space. ss2zpk -- state-space to pole-zero-gain. Waveforms: sawtooth -- Periodic sawtooth square -- Square wave gausspulse -- Gaussian modulated sinusoid chirp -- Frequency swept cosine signal Wavelets: daub -- return low-pass filter for daubechies wavelets qmf -- return quadrature mirror filter from low-pass cascade -- compute scaling function and wavelet from coefficients -- http://mail.python.org/mailman/listinfo/python-list
Re: FIR filtering
Terry == Terry Reedy [EMAIL PROTECTED] writes: Terry LabWINC [EMAIL PROTECTED] wrote in message Terry news:[EMAIL PROTECTED] If i type help scipy.filter it give me an error help scipy.filter File input, line 1 help scipy.filter ^ SyntaxError: invalid syntax Terry The respondant left out parens. At interactive prompt: Terry help(scipy.filter) or, in general help(someobject) Sorry, ipython user here -- http://ipython.scipy.org ipython supports autoparens JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib logarithmic scatter plot
Derek == Derek Basch [EMAIL PROTECTED] writes: Derek formatter = FuncFormatter(log_10_product) Derek ax.xaxis.set_major_formatter(formatter) Derek ax.yaxis.set_major_formatter(formatter) I would caution you against using identical objects for the x and y axis *Locators*. For the formatters, it will do no harm, but for the locators you can get screwed up because the locator object reads the axis data and view limits when making it's choices. Ie, do not do this: ax.xaxis.set_major_locator(locator) ax.yaxis.set_major_locator(locator) but rather do this ax.xaxis.set_major_locator(MyLocator()) ax.yaxis.set_major_locator(Mylocator()) Thanks for the example, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib logarithmic scatter plot
Derek == Derek Basch [EMAIL PROTECTED] writes: Derek Great! That worked fine after I played with it for a Derek bit. One last question though. How do I label the ticks Derek with the product of the exponentiation? For instance: Derek 100 Derek instead of Derek 10**2 You can supply your own custom tick formatters (and locators). See http://matplotlib.sf.net/matplotlib.ticker.html and examples http://matplotlib.sourceforge.net/examples/custom_ticker1.py http://matplotlib.sourceforge.net/examples/major_minor_demo1.py http://matplotlib.sourceforge.net/examples/major_minor_demo2.py JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib logarithmic scatter plot
Derek == Derek Basch [EMAIL PROTECTED] writes:
Derek Thanks for the reply. I need a scatter plot though. Can
Derek that be done?
You can set the scale of xaxis and yaxis to either log or linear for
scatter plots
In [33]: ax = subplot(111)
In [34]: ax.scatter( 1e6*rand(1000), rand(1000))
Out[34]: matplotlib.collections.RegularPolyCollection instance at
0x9c32fac
In [35]: ax.set_xscale('log')
In [36]: ax.set_xlim(1e-6,1e6)
Out[36]: (9.9995e-07, 100.0)
In [37]: draw()
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Re: matplotlib legend problem
bwaha == bwaha [EMAIL PROTECTED] writes: bwaha added the location argument. Finally realised it was due to bwaha having a default of 'best' location in my code which meant bwaha it went searching for intersection with lines that don't bwaha exist (outside of the LineCollection). So I disabled the bwaha 'best' location option. Then I figured, since I'd cleaned bwaha up my code a bit, I'd reinstate my earlier pylab.plot based bwaha line drawing code to see if the clean up made any bwaha difference to what was previously abysmal performance. The bwaha lines plotted faster than the LineCollection code! When I bwaha removed the legend hack for LineCollections there was bwaha virtually no difference. (Story is not finshed yet). So I bwaha figured after all that that I'd reinstate my pylab.plot bwaha based code since I could plot a greater range of symbols bwaha than with LineCollections with no speed loss. And I thought bwaha why not go the whole hog and reinstate the 'best' location bwaha option too. Boom! Plotting performance was abysmal bwaha again. Finally I realised that enabling 'best' and having bwaha it as the default meant that as I added new data to plot, bwaha the search time for a good place to put the legend bwaha increased dramtically, and probably became more difficult bwaha with more and more lines filling the canvas. bwaha Anyway now I'm a lot happier than when I started because bwaha I've retained my original range of plot styles and I got bwaha much faster plotting. Hopefully this lesson can help bwaha someone else. Sorry you had to find this out after so much trial and error. For a small number of large length lines (eg 10 at 30k points each), plot will be much faster than line collections as you observed. For a large number of small lines (eg 1000 at 20 points each) line collections will be much faster. And yes, the best optimization for the legend is slow -- I'm on the fence as to whether this should be the default or not. At least clearly flagging this as a performance bottleneck in the docs would be useful. Cheers, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: scipy.plt legend?
gurkesaft == gurkesaft [EMAIL PROTECTED] writes: gurkesaft Thank you, Robert. I noticed how obsolete it is! gurkesaft There is no documentation. gurkesaft Matplotlib freezes my system if I close a plot and make gurkesaft a new one :(. Bah. Windows :) Have you seen the documentation on http://matplotlib.sf.net/installing.html In particular, you need to make sure that your backend, shell, and interactive setting all are harmonious. One suggestion: in your rc file, try setting 'backend : TkAgg' and 'interactive : True' in your http://matplotlib.sf.net/matplotlibrc file. Also, beware of using matplotlib from a GUI IDE which uses a different GUI toolkit than the one you've selected in your rc file. I realize this is complex -- but I think it is part and parcel of the curse of python. python supports 6+ GUI toolkits and so matplotlib does too! If the GUI mainloop and matplotlib mainloop don't agree, bad things can happen. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Creating Pie Chart from Python
Thierry == Thierry Lam [EMAIL PROTECTED] writes:
Thierry Let's say I have the following data: 500 objects: -100
Thierry are red -300 are blue -the rest are green
Thierry Is there some python package which can represen the above
Thierry information in a pie chart?
It looks like in python there is more than one way to make a pie
chart. Here's another
from pylab import figure, pie, show
N, red, blue = 500, 100, 300
green = N - (red + blue)
figure(figsize=(6,6))
pie( (red, blue, green),
labels=('red', 'blue', 'green'),
colors=('red', 'blue', 'green'),)
show()
A screenshot of a slightly more elaborate example is at
http://matplotlib.sourceforge.net/screenshots.html#pie_demo
JDH
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Re: use SciPy with Python 2.4.1?
Robert == Robert Kern [EMAIL PROTECTED] writes: Robert [EMAIL PROTECTED] wrote: Is SciPy usable with Python 2.4.1? At http://www.scipy.org/download/ it says that 2.3.3 is recommended, and I don't see a binary for 2.4.1. Robert It is usable with Python 2.4.1 on Linux and OS X at Robert least. IIRC, mingw-compiled extensions don't work with the Robert standard Python 2.4.1 interpreter, which is, I believe, Robert the largest holdup for Windows binaries for 2.4.1. I routinely compile matplotlib with mingw for 2.4 and haven't had any problems. If I recall correctly, a trivial patch for distutils is needed which is described at http://mail.python.org/pipermail/python-list/2004-December/254826.html JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: while c = f.read(1)
Robert == Robert Kern [EMAIL PROTECTED] writes: Robert Greg McIntyre wrote: The 2nd option has real potential for me. Although the total amount of code is greater, it factors out some complexity away from the actual job, so that code is not obscured by unnecessary compexity. IMHO that's great practice. Robert Please quote the message you are replying to. We have no Robert idea what the 2nd option is. I think he means the second option you presented If you must read one character at a time, def reader(fileobj, blocksize=1): Return an iterator that reads blocks of a given size from a file object until EOF. ...snip With a decent threaded news/mail reader, the thread provides sufficient context, no? JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: GUI tookit for science and education
James == James Sungjin Kim [EMAIL PROTECTED] writes: James Michele Simionato wrote: My vote is for ipython + matplotlib. Very easy and very powerful. James Is it really easier than to use MATLAB(TM)? Do you find matlab easy to use? What aspects are hard or easy? If you provide a little more context, it would be easier to answer your question. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: GUI tookit for science and education
Robert == Robert Kern [EMAIL PROTECTED] writes: RobertH = U*D*V.T Robert then I'm more than happy with that tradeoff. The small Robert syntactic conveniences MATLAB provides are dwarfed by the Robert intrinsic power of Python. Of course, U*D*V (transpose omitted for clarity) is the classic problem for an interpreted language: the creation of temporaries. weave allows you, via blitz, to do chained matrix/matrix operations without multiple passes through the loop and w/o temporaries by run-time compilation and linking of extension code. Perhap's the OP's reference to JIT is referring to a just in time compilation mechanism in matlab, similar to weave's. They've already discovered LAPACK and FFTW; it wouldn't be surprising if they solved blitzm (blitz in matlab), antialiasing, alpha transparency and multiple colormaps per figure in upcoming releases. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Gotchas in user-space matplotlib install?
Matt == Matt Feinstein [EMAIL PROTECTED] writes: Matt All in all, not actually excruciating-- and now I have a Matt working version of matplotlib! Matt Feinstein Great! While this is all fresh in your mind, would you be able to add a wiki entry at http://www.scipy.org/wikis/topical_software/MatplotlibCookbook Thanks, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Gotchas in user-space matplotlib install?
Matt == Matt Feinstein [EMAIL PROTECTED] writes: Matt Hi all-- I'm planning to try to do a completely local Matt install of matplotlib (in Fedora Core 1)-- the system Matt administrator isn't going to stop me-- but he isn't going to Matt cooperate either. I've got the tarballs for python, numeric, Matt numarray, matplotlib, ipython, wxpython and freetype-- which Matt I think covers the various pre-requisites and Matt post-requisites. One semi-obvious question is where to put Matt the freetype library (the system version in FC1 is not up to Matt the required level)-- but I can only wonder what other Matt trouble I'm going to get into. Any advice before I take the Matt plunge would be appreciated. TIA... If you do a --prefix=~/usr for all 'configure' and 'python setup.py install' commands, and set your PATH, C_INCLUDE_PATH, CPLUS_INCLUDE_PATH, LIBRARY_PATH, and LD_LIBRARY_PATH variables accordingly, and set the MATPLOTLIBDATA environment variable to point to ~/usr/share/matplotlib, it should work. When debugging your setup, you might want to run your test matplotlib/pylab script with python myscript.py --verbose-helpful OR python myscript.py --verbose-debug to get extra information about where matplotlib is looking for things. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Passing a variable number of arguments to a wrapped function.
stephen == stephen [EMAIL PROTECTED] writes:
stephen Is there a better way of doing this so that I don't have
stephen to go through every permutation of possible arguments
stephen (the example here from the matplotlib 'plot' function):
You can make linecolor=None and linewidth=None, and then use
matplotlib's rc defaults
from matplotlib import rcParams
def makeplot(self, xvalues, yvalues, linecolor=None, linewidth=None):
if linecolor is None: linecolor = rcParams['lines.color']
if linewidth is None: linewidth = rcParams['lines.linewidth']
plot(xvalues, yvalues, color=linecolor, linewidth=linewidth)
Then you can customize the defaults in the rc file
(http://matplotlib.sf.net/matplotlibrc) any way you want.
Alternatively, you can also set the defaults in your script
from matplotlib import rc
rc('lines', linewidth=1.0, color='red')
JDH
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ANN: matplotlib 0.83.2
matplotlib is a 2D plotting package for python. This is a summary of recent developments in matplotlib since 0.80. For detailed notes, see http://matplotlib.sf.net/whats_new.html, http://matplotlib.sf.net/CHANGELOG and http://matplotlib.sf.net/API_CHANGES == Whats New == matplotlib wiki: this was just launched a few days ago and only has two entries to date, but we hope this will grow into a useful site with tutorials, howtos, installation notes, recipes, etc. Please contribute! Thanks to scipy.org and Enthought for hosting. http://www.scipy.org/wikis/topical_software/MatplotlibCookbook CocoaAgg: New CocoaAgg backend for native GUI on OSX, 10.3 and 10.4 compliant, contributed by Charles Moad. TeX support : Now you can (optionally) use TeX to handle all of the text elements in your figure with the rc param text.usetex in the antigrain and postscript backends; see http://www.scipy.org/wikis/topical_software/UsingTex. Thanks to Darren Dale for hard work on the TeX support. Reorganized config files: Made HOME/.matplotlib the new config dir where the matplotlibrc file, the ttf.cache, and the tex.cache live. Your .matplotlibrc file, if you have one, should be renamed to .matplotlib/matplotlibrc. Masked arrays: Support for masked arrays in line plots, pcolor and contours. Thanks Eric Firing and Jeffrey Whitaker. New image resize options interpolation options. See help(imshow) for details, particularly the interpolation, filternorm and filterrad kwargs. New values for the interp kwarg are: 'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos', 'blackman' Byte images: Much faster imaeg loading for MxNx4 or MxNx3 UInt8 images, which bypasses the memory and CPU intensive integer/floating point conversions. Thanks Nicolas Girard. Fast markers on win32: The marker cache optimization is finally available for win32, after an agg bug was found and fixed (thanks Maxim!). Line marker plots should be considerably faster now on win32. Qt in ipython/pylab: You can now use qt in ipython pylab mode. Thanks Fernando Perez and the Orsay team! Agg wrapper proper: Started work on a proper agg wrapper to expose more general agg functionality in mpl. See examples/agg_test.py. Lots of wrapping remains to be done. Subplot configuration: There is a new toolbar button on GTK*, WX* and TkAgg to launch the subplot configuration tool. GUI neutral widgets: Matplotlib now has cross-GUI widgets (buttons, check buttons, radio buttons and sliders). See examples/widgets/*.py and http://matplotlib.sf.net/screenshots.html#slider_demo. This makes it easier to create interactive figures that run across backends. Full screen mode in GTK*: Use 'f' to toggle full screen mode in the GTK backends. Thanks Steve Chaplin. Downloads available from http://matplotlib.sf.net -- http://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations.html
ANN: matplotlib 0.83.2
matplotlib is a 2D plotting package for python. This is a summary of recent developments in matplotlib since 0.80. For detailed notes, see http://matplotlib.sf.net/whats_new.html, http://matplotlib.sf.net/CHANGELOG and http://matplotlib.sf.net/API_CHANGES == Whats New == matplotlib wiki: this was just launched a few days ago and only has two entries to date, but we hope this will grow into a useful site with tutorials, howtos, installation notes, recipes, etc. Please contribute! Thanks to scipy.org and Enthought for hosting. http://www.scipy.org/wikis/topical_software/MatplotlibCookbook CocoaAgg: New CocoaAgg backend for native GUI on OSX, 10.3 and 10.4 compliant, contributed by Charles Moad. TeX support : Now you can (optionally) use TeX to handle all of the text elements in your figure with the rc param text.usetex in the antigrain and postscript backends; see http://www.scipy.org/wikis/topical_software/UsingTex. Thanks to Darren Dale for hard work on the TeX support. Reorganized config files: Made HOME/.matplotlib the new config dir where the matplotlibrc file, the ttf.cache, and the tex.cache live. Your .matplotlibrc file, if you have one, should be renamed to .matplotlib/matplotlibrc. Masked arrays: Support for masked arrays in line plots, pcolor and contours. Thanks Eric Firing and Jeffrey Whitaker. New image resize options interpolation options. See help(imshow) for details, particularly the interpolation, filternorm and filterrad kwargs. New values for the interp kwarg are: 'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos', 'blackman' Byte images: Much faster imaeg loading for MxNx4 or MxNx3 UInt8 images, which bypasses the memory and CPU intensive integer/floating point conversions. Thanks Nicolas Girard. Fast markers on win32: The marker cache optimization is finally available for win32, after an agg bug was found and fixed (thanks Maxim!). Line marker plots should be considerably faster now on win32. Qt in ipython/pylab: You can now use qt in ipython pylab mode. Thanks Fernando Perez and the Orsay team! Agg wrapper proper: Started work on a proper agg wrapper to expose more general agg functionality in mpl. See examples/agg_test.py. Lots of wrapping remains to be done. Subplot configuration: There is a new toolbar button on GTK*, WX* and TkAgg to launch the subplot configuration tool. GUI neutral widgets: Matplotlib now has cross-GUI widgets (buttons, check buttons, radio buttons and sliders). See examples/widgets/*.py and http://matplotlib.sf.net/screenshots.html#slider_demo. This makes it easier to create interactive figures that run across backends. Full screen mode in GTK*: Use 'f' to toggle full screen mode in the GTK backends. Thanks Steve Chaplin. Downloads available from http://matplotlib.sf.net -- http://mail.python.org/mailman/listinfo/python-list
Re: Is there a better interactive plotter then pylab?
Charles == Charles Krug [EMAIL PROTECTED] writes: Charles List: I'm trying to us pylab to see what I'm doing with Charles some DSP algorithms, in case my posts about convolution Charles and ffts weren't giving it away. Charles I've been using pylab's plot function, but I'm finding it Charles a bit cumbersome. Charles It works, but if I switch from the interactive window to Charles the plot window and back, the plot window gets trashed. Charles Is there a better alternative for interactive use? You are probably not using pylab interactive mode properly. matplotlib has several GUI backends (gtk, tk, qt, etc...). Most GUIs take control with their mainloop and prevent further interaction. From what you describe, I'm pretty sure you haven't setup your configuration properly for interactive use. Fortunately, there are a couple of solutions. For the standard python shell, you need to use the TkAgg backend. Tkinter is the only python GUI that plays nicely with the standard python shell. You will need to set backend : TkAgg and interactive : True in the matplotlib rc file. See http://matplotlib.sf.net/interactive.html for details and http://matplotlib.sf.net/.matplotlibrc for information on the configuration file. If you want to use another GUI backend, eg GTKAgg (the default on linux and also the fastest backend), you need to use a custom python interpreter which runs the GUI in a thread. The best choice here is to use ipython (http://ipython.scipy.org) with the -pylab option. ipython is aware of matplotlib and its rc file, and will read the rc file, set the interactive mode, detect the GUI backend, and make the proper threading calls. Basically it *just works*. If you are on linux, it's an easy install (sudo python setup.py install). On windows it's a bit harder, and you may want to look at the 1069 release candidate of enthought python at http://www.enthought.com/downloads/downloads.htm#download, which comes with ipython and matplotlib and lots of other goodies. Again, you'll need to start ipythhon with ipython -pylab In addition to the links above, see also http://matplotlib.sf.net/faq.html#SHOW. Hope this helps, JDH -- http://mail.python.org/mailman/listinfo/python-list
ANN: matplotlib-0.80
matplotlib is a 2D graphics package that produces plots from python scripts, the python shell, or embeds them in your favorite python GUI -- wx, gtk, tk, fltk and qt. Unlike many python plotting alternatives is written in python, so it is easy to extend. matplotlib is used in the finance industry, web application servers, and many scientific and enginneering disciplines. With a large community of users and developers, matplotlib is approaching the goal of having a full featured, high quality, 2D plotting library for python. A lot of development has gone into matplotlib since the last major release, which I'll summarize here. For details, see the notes for the incremental releases at http://matplotlib.sf.net/whats_new.html. Improvements since 0.70 -- contouring: Lots of new contour funcitonality with line and polygon contours provided by contour and contourf. Automatic inline contour labeling with clabel. See http://matplotlib.sourceforge.net/screenshots.html#pcolor_demo -- QT backend Sigve Tjoraand, Ted Drain and colleagues at the JPL collaborated on a QTAgg backend -- Unicode strings are rendered in the agg and postscript backends. Currently, all the symbols in the unicode string have to be in the active font file. In later releases we'll try and support symbols from multiple ttf files in one string. See examples/unicode_demo.py -- map and projections A new release of the basemap toolkit - See http://matplotlib.sourceforge.net/screenshots.html#plotmap -- Auto-legends The automatic placement of legends is now supported with loc='best'; see examples/legend_auto.py. We did this at the matplotlib sprint at pycon -- Thanks John Gill and Phil! Note that your legend will move if you interact with your data and you force data under the legend line. If this is not what you want, use a designated location code. -- Quiver (direction fields) Ludovic Aubry contributed a patch for the matlab compatible quiver method. This makes a direction field with arrows. See examples/quiver_demo.py -- Performance optimizations Substantial optimizations in line marker drawing in agg -- Robust log plots Lots of work making log plots just work. You can toggle log y Axes with the 'l' command -- nonpositive data are simply ignored and no longer raise exceptions. log plots should be a lot faster and more robust -- Many more plotting functions, bugfixes, and features, detailed in the 0.71, 0.72, 0.73 and 0.74 point release notes at http://matplotlib.sourceforge.net/whats_new.html http://matplotlib.sourceforge.net JDH -- http://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations.html
ANN: matplotlib-0.80
matplotlib is a 2D graphics package that produces plots from python scripts, the python shell, or embeds them in your favorite python GUI -- wx, gtk, tk, fltk and qt. Unlike many python plotting alternatives it is written in python, so it is easy to extend. matplotlib is used in the finance industry, web application servers, and many scientific and engineering disciplines. With a large community of users and developers, matplotlib is approaching the goal of having a full featured, high quality, 2D plotting library for python. A lot of development has gone into matplotlib since the last major release, which I'll summarize here. For details, see the incremental release notes at http://matplotlib.sf.net/whats_new.html. Improvements since 0.70 -- contouring: Lots of new contour functionality with line and polygon contours provided by contour and contourf. Automatic inline contour labeling with clabel. See http://matplotlib.sourceforge.net/screenshots.html#pcolor_demo -- QT backend Sigve Tjoraand, Ted Drain and colleagues at the JPL collaborated on a QTAgg backend -- Unicode strings are rendered in the agg and postscript backends. Currently, all the symbols in the unicode string have to be in the active font file. In later releases we'll try and support symbols from multiple ttf files in one string. See examples/unicode_demo.py -- map and projections A new release of the basemap toolkit - See http://matplotlib.sourceforge.net/screenshots.html#plotmap -- Auto-legends The automatic placement of legends is now supported with loc='best'; see examples/legend_auto.py. We did this at the matplotlib sprint at pycon -- Thanks John Gill and Phil! Note that your legend will move if you interact with your data and you force data under the legend line. If this is not what you want, use a designated location code. -- Quiver (direction fields) Ludovic Aubry contributed a patch for the matlab compatible quiver method. This makes a direction field with arrows. See examples/quiver_demo.py -- Performance optimizations Substantial optimizations in line marker drawing in agg -- Robust log plots Lots of work making log plots just work. You can toggle log y Axes with the 'l' keypress -- nonpositive data are simply ignored and no longer raise exceptions. log plots should be a lot faster and more robust -- Many more plotting functions, bugfixes, and features, detailed in the 0.71, 0.72, 0.73 and 0.74 point release notes at http://matplotlib.sourceforge.net/whats_new.html Downloads at http://matplotlib.sourceforge.net JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Gnuplot.py and, _by far_, the weirdest thing I've ever seen on my computer
syd == syd [EMAIL PROTECTED] writes: syd As for matplotlib, I checked it out. Looks amazing! I syd really, really like what demos I tried. syd HOWEVER, I could not find a good way to do smoothing. I like syd the gnuplot bezier smoothing. This wouldn't be the hardest syd thing in the world to code, but I was a little disappointed. syd If yall have any ideas, bring em on! :) What is the gnuplot interface to use smoothing? When I want to do something like this, I use scipy's interpolate module and pass the reults to matplotlib for plotting. from scipy import arange, sin, pi, interpolate from pylab import plot, show t = arange(0, 2.0, 0.1) y = sin(2*pi*t) tck = interpolate.splrep(t, y, s=0) tnew = arange(0, 2.0, 0.01) ynew = interpolate.splev(tnew, tck, der=0) plot(t, y, 'o', tnew, ynew) show() -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib question-- Numeric or numarray?
Matt == Matt Feinstein [EMAIL PROTECTED] writes: Matt I'm working my way through the matplotlib documentation Matt there's a point that's ambiguous-- the pdf file (dated Matt Mar. 1, 2005) warns of dire consequences if I use the Matt 'wrong' array package-- e.g., put numarray in the .matlabrc Matt file if the compile-time package is Numeric. But there's Matt only one current, unlabeled, windows installer and there Matt seems to have been a change, some time back before version Matt 0.7, in how this question is dealt with. Can someone Matt clarify? thnksndvnc Hi Matt -- it looks like the documentation is out of data. matplotlib can now be built to support Numeric and numarray simultaneously, and which one you are using is controlled at runtime by the numerix setting in your rc file. The windows installers now have support for both Numeric and numarray built in. I recommend you use the matplotlib.numerix module to import your Numeric/numarray symbols in matplotlib scripts, rather than using Numeric/numarray directly. The reason is that it is still important that the arrays you create match the type in your rc file, and the numerix module insures that this happens. One good way to do this is import matplotlib.numerix as nx a = nx.array(blah) The matplotlib numerix package structure mirros numarray. Eg to import mean, you would do from matplotlib.numerix.mlab import mean which in numarray is located in numarray.mlab and in Numeric is in MLab. If trying to figure out where all the various numerix functions live makes your head hurt, you can use the pylab module which aggregates all the numerix and plotting functions into a single namespace import pylab as p a = p.array([1,2,3]) n = p.randn(1) mu, sigma = p.mean(n), p.std(n) p.hist(n, 1000) p.show() Hope this helps, JDH -- http://mail.python.org/mailman/listinfo/python-list
using distutils.command.config
I am trying to utilize the config module in distutils to test for certain headers and libraries and fail elegantly if they are not found with a helpful message. The typical gcc error message when a header is missing is inscrutable to many. I have subclassed config and can use my class with python setup.py config The config class finds all the module specific path and library information, but I am not clear on the best way to get this to the build process. One option is to save the information to a config file, eg using a plain text format, creating a python module, or using pickle, but it seems artificial to me to have to use an intermediate file. Is there a way to get the config information on a call to python setup.py build My config class looks like from distutils.command.config import config class config_mpl(config): def run (self): # make sure you can find the headers, link with the libraries, # etc, and collect per module include_dirs, library_dirs, # libraries information One idea is to dump the information from the config call to a config.pickle, but ideally I would like the config file to be human readable Thanks, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: generic text read function
les == les ander [EMAIL PROTECTED] writes:
les Hi, matlab has a useful function called textread which I am
les trying to reproduce in python.
les two inputs: filename, format (%s for string, %d for integers,
les etc and arbitary delimiters)
les variable number of outputs (to correspond to the format given
les as input);
les So suppose your file looked like this str1 5 2.12 str1 3 0.11
les etc with tab delimited columns. then you would call it as
les c1,c2,c3=textread(filename, '%s\t%d\t%f')
les Unfortunately I do not know how to read a line from a file
les using the line format given as above. Any help would be much
les appreciated les
Not an answer to your question, but I use a different approach to
solve this problem. Here is a simple example
converters = (str, int, float)
results = []
for line in file(filename):
line = line.strip()
if not len(line): continue # skip blank lines
values = line.split('\t')
if len(values) != len(converters):
raise ValueError('Illegal line')
results.append([func(val) for func, val in zip(converters, values)])
c1, c2, c3 = zip(*results)
If you really need to emulate the matlab command, perhaps this example
will give you an idea about how to get started. Eg, set up a dict
mapping format strings to converter functions
d = {'%s' : str,
'%d' : int,
'%f' : float,
}
and then parse the format string to set up your converters and split function.
If you succeed in implementing this function, please consider sending
it to me as a contribution to matplotlib -- http://matplotlib.sf.net
Cheers,
JDH
--
http://mail.python.org/mailman/listinfo/python-list
Re: Minor, but annoying legend problem in matplotlib
Jorl == Jorl Shefner [EMAIL PROTECTED] writes: JorlThe obvious solution is to plot the lines and symbols in Jorl two different commands: ___ You want to explicitly pass the lines you want to legend into the legend command, as in Symb= ['wo','ws','w^'] LineType= ['k-','k--','k-.'] leglines = [] for index,d in enumerate(DataSets): plot(x,DataSets[index],LineType[index]) lines = plot(x,DataSets[index],Symb[index]) leglines.extend(lines) legend(leglines, [a,b,c]) Jorl to have it available for the second loop. I've gotten Jorl around this before for somewhat similar cases using Jorl suggestions from this group of explicitly defining the Jorl values the legend will use: Jorl L1= plot(x,y,... Jorl but I can't figure how to do this here because of the Jorl looping over the data sets. Hope the above example helps here. JorlOn a related note, is there any way to increase the size Jorl of the markers within the legend? You can access the lines of the legend instance leg = legend(lines, labels) lines = leg.get_lines() set(lines, markersize=10, markeredgewidth=2) # etc See http://matplotlib.sourceforge.net/examples/legend_demo.py JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: MatPlotLib.MatLab troubles (how to install/run matplotlib.PyLab?)
Colombes == Colombes [EMAIL PROTECTED] writes: ColombesNow I only need to figure out how to install the Colombes correct Numeric module(s). I'm making progress, Colombes almost have my home laptop fully capable with the Colombes MatLab-like (PyLab) graphs, plots. You can get either Numeric or numarray from http://sourceforge.net/projects/numpy. matplotlib works transparently with either (and provides a unified interface to both), but if you choose numarray you need to change the numerix variable to numarray in your matplotlib configuration file, which is described at http://matplotlib.sf.net/.matplotlibrc Good luck! JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: MatPlotLib.MatLab troubles (how to install/run matplotlib.PyLab?)
Colombes == Colombes [EMAIL PROTECTED] writes: Colombes matplotlib.matlab deprecated, please import Colombes matplotlib.pylab or simply pylab instead. See Colombes http://matplotlib.sf.net/matplotlib_to_pylab.py for a Colombes script which explains this change and will automatically Colombes convert your python scripts that use matplotlib.matlab. Colombes This change was made because we were concerned about Colombes trademark infringement on The Mathwork's trademark of Colombes matlab. Colombes Unfortunately, the above URL does not exist. Oops -- that should be http://matplotlib.sourceforge.net/matlab_to_pylab.py In a nutshell, wherever you previously imported matplotlib.matlab you can import matplotlib.pylab or equivalently, simply pylab OLD: from matplotlib.matlab import plot NEW: from pylab import plot The script linked above will recursively search and replace these strings for you in your scripts directory. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Matplotlib, py2exe and pytz
scott == scott [EMAIL PROTECTED] writes: scott I am trying to convert a python app that uses matplotlib to scott a standalone executable using py2exe. scott After running py2exe and executing my app I get the scott following stack trace: scott Traceback (most recent call last): File gcToCsv.py, line scott 5, in ? File plot_output.pyc, line 1, in ? File scott pylab.pyc, line 1, in ? File matplotlib\pylab.pyc, scott line 194, in ? File matplotlib\axes.pyc, line 46, in ? scott File matplotlib\dates.pyc, line 94, in ? File scott pytz\__init__.pyc, line 53, in timezone KeyError: 'UTC' scott It appears that the instructions on the matplotlib web site scott and wiki are incomplete and the pytz.zoneinfo package is scott not being included in the finished dist directory. In your script that you are trying to freeze, do, import pytz import dateutil as a hint to py2exe that you want these modules. Does this help? Does the script you are trying to freeze explicitly use matplotlib date functionality? JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Getting milliseconds in Python
mjs7231 == mjs7231 [EMAIL PROTECTED] writes: mjs7231 This is no good, I am looking for milliseconds, not mjs7231 seconds.. as stated above. Well seconds/1000.0 = millseconds -- or are you worries about floating point error? 7 from datetime import datetime 8 dt = datetime.now() 9 dt.microsecond Out[9]: 20222 Converting to milliseconds is left as an exercise for the reader... See also the timeit module... JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Commerical graphing packages?
Francis == Francis Girard [EMAIL PROTECTED] writes: Francis PyX might also be interesting, depending on your needs. While pyx is a very nice package, it is probably not a good choice for web app developers simply because it generates postscript, which is not very browser friendly. Once could send the PS through a converter such as ImageMagick, but it would probably be better to use a library that generates browser friendly output natively. matplotlib on the other hand, *does* work in web app servers, and generates PNG/SVG natively. See http://matplotlib.sourceforge.net/faq.html#APPSERVER Although it is a free and open source package, I think that the image quality and support is on par with if not superior to what you find in many commercial solutions. If the OP wants commercial support, he might consider contacting the developer off-list :-) JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Variable size plot symbols, variable hue plot colors in Python (MatPlotLib) ?
Colombes == Colombes [EMAIL PROTECTED] writes: Colombes Using MatPlotLib plot function, is there a way to get Colombes variable size plot symbols? For example, using symbol Colombes strings like 'o' (circle), 's' (square), 'x' (cross), Colombes etc., is there a way to specify other plot symbols such Colombes a small circle, Medium square, LARGE cross, etc.? plot(x, y, 'o', markersize=10) # big plot(x, y, 'o', markersize=20) # bigger Colombes Similarly, using the MatPlotLib plot function, is there Colombes a way to get variable hue (RGB-specified) plot colors? Colombes For example, using symbol strings like 'b' (blue), 'g' Colombes (green), 'red' (red), etc., is there a way to specify Colombes other colors such as light blue, dark green, pink, etc.? All legal html color names are supported plot(x, y, 'o', markersize=10, markerfacecolor='green', markeredgecolor='red') Eg lightblue: #ADD8E6 lightcoral : #F08080 lightcyan: #E0 lightgoldenrodyellow : #FAFAD2 lightgreen : #90EE90 lightgrey: #D3D3D3 lightpink: #FFB6C1 lightsalmon : #FFA07A lightseagreen: #20B2AA lightskyblue : #87CEFA lightslategray : #778899 lightsteelblue : #B0C4DE lightyellow : #E0 # or use aliases for less typing plot(x, y, 'o', ms=10, mfc='green', mec='red') # or rgba or hex plot(x, y, 'o', ms=10, mfc='#008000, mec=(1,0,0,1) ) Colombes Or perhaps is there some other Python MatPlotLib or Colombes other Python module functions that allow variable size Colombes plot symbols and variable hue plot colors in Python ? The scatter command supports markers with varying sizes and colors. screenshot with example code at http://matplotlib.sourceforge.net/screenshots.html#scatter_demo2 . Docs at http://matplotlib.sourceforge.net/matplotlib.pylab.html#-scatter. You might want to check out the tutorial and/or the user's guide. Most of these issues are touched on there. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Medical GUI Application With Python
Evrim == Evrim Ozcelik [EMAIL PROTECTED] writes: Evrim We are developing a medical software about PSG Evrim (PolySomnoGraphy) analysis. The application takes signal Evrim data from an electronic device and we will show this Evrim continious signal function on the interfaces. There are Evrim about 20-30 signal channels and the user selected channels Evrim are shown. We want to run this application over different Evrim platforms. Evrim My question is: Evrim1. What must be our IDE 2. What class library for GUI Evrim must be use (wxWindows, Qt, GTK, etc.) 3. Is there any GUI Evrim package for visulazing signal functions (like sinozodial Evrim functions) in real time; this module will behave as an Evrim oscilloscope I wrote an EEG viewer in python using pygtk for the GUI and matplotlib for the 2D plotting (and VTK for the 3D). It runs unchanged on OSX, linux and win32. You can see a few screenshots at http://pbrain.sf.net . The underlying 2D plotting library, matplotlib, does handle animations (dynamic plots) and can be embedded in the GUI of your choice (Tk, WX, GTK, FLTK and QT). I also wrote matplotlib, as a first step in developing the application above. The performance of dynamic animated plots (what you call real time) varies for different backends. GTK is typically fastest: on a modern P4 you can do about 50 frames/sec for simple plots and 10-15 frames/sec for more complicated plots (images, larger data sets). The performance for the Tk GUI is considerably slower. Most people who say real time don't really mean it, they mean they want frequent updates and should assess whether the plotting library can support refresh rates (frames/sec) that are fast enough to be visually pleasing and to be true to the signal plotted. matplotlib is not the fastest 2D python plotting library, but it is one of the most feature complete and may be fast enough for your purposes -- http://matplotlib.sf.net . My guess is that for 20-30 channels the refresh rate in the current implementation will be slower than you want, but these things are always improving since matplotlib is under active development and there are some performance bottlenecks that could be removed with a little work. The examples directory which is in the src distributions has a number of examples illustrating dynamic plots: anim.py, system_monitor.py, dynamic_image_gtkagg.py, dynamic_image_wxagg.py, dynamic_demo.py. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: exporting mesh from image data
Fernando == Fernando Perez [EMAIL PROTECTED] writes: Fernando I hope you posted this on the VTK list with a CC to Fernando Prabhu as well... The hopes of a positive reply there Fernando are, I suspect, a fair bit higher. The scipy list would Fernando be a good idea, too. Hey Fernando, I did get some help from Prabu off list. The suggestion was to use a vtkDelaunay3D to mesh the isosurface points into a volume, which returns an unstructured grid, and then iterate over this structure to get the volume, face, vertex and connectivity information out. I've implemented this and we're in the process of testing it with some simple geometries. If/when I get something tested and working, I'll post it. Thanks for the links, JDH -- http://mail.python.org/mailman/listinfo/python-list
exporting mesh from image data
I am trying to generate a mesh for a finite volume solver (gambit, fluent) from 3D image data (CT, MRI). To generate the fluent msh file, you need not only a list of vertices and polygons, much like what is available in the vtk file format, but also the volume elements in the mesh that the polygons abut. Eg for a given triangle in the mesh, you would have a line like 3 3 2 1 11 0 which is numfaces vert0 vert1 vert2 vol1 vol2 where vol1 and vol2 are indices that indicate the volume in the mesh that the triangle belongs to (vol2 is 0 for triangles on the surface). The specific problem at hand involves building a mesh for ventricles in the brain. I have no trouble building the isosurface that surrounds the ventricles using the marching cubes and connectivity filters in VTK, but now need to be able to generate a mesh over the interior and assign volumes to faces. Does such capability exist in VTK? and if so I would be thankful for pointers to class docs or examples. Are there other algorithms in the world of python 3D libraries that can provide 3D meshes for 2D surface isocontours, assigning volume elements from the mesh to the surfaces that surround the volume. Thanks! JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: barchart for webpage needed
dimitri == dimitri pater [EMAIL PROTECTED] writes: dimitri Hello, I am looking for a Python tool to create graphs dimitri and charts on a webpage. Chartdirector is too expensive dimitri for me. A simple script for creating a barchart should be dimitri sufficient as a starting point. matplotlib does barcharts, errorbars, stacked bars, and more (and its free). See the following links # matplotlib with web app servers: http://matplotlib.sourceforge.net/faq.html#APPSERVER # a barchart screenshot with example code http://matplotlib.sourceforge.net/screenshots.html#barchart_demo # the bar command for making bar charts http://matplotlib.sourceforge.net/matplotlib.pylab.html#-bar JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Python's idiom for function overloads
Frans == Frans Englich [EMAIL PROTECTED] writes: Frans Hello, Frans Since Python doesn't have static typing, how is the same Frans result as traditional function overloads results in Frans acheived? With function overloads the selection of code Frans path depending on data type is transparent and automatic Frans since the typing system figure out what goes to what. Frans But in Python, when one wants to be able to pass different Frans data types into a single entry point for functionality, Frans how is that best done? To in a function do an if statement Frans with the type() function? Using type or isinstance is one way to do it. The other way is duck typing. If it walks like a duck and talks like a duck, it probably is a duck. The core idea is that we care less about what type an object is, and more about what services the object provides. Eg def myoverload(x): try: noise = x.quack() except AttributeError: # do something else... else: # do something with noise Variants to the try/except approach include hasattr, getattr and so on.. googling python duck typing should speed you on your way. JDH -- http://mail.python.org/mailman/listinfo/python-list
python and gpl
I have a question about what it takes to trigger GPL restrictions in python code which conditionally uses a GPL library. Here is the context of my question. matplotlib, which I develop, is a plotting module which is distributed under a PSF compatible license, and hence we avoid using GPLd code so as to not trigger the GPL requirements. matplotlib has rigid segregation between the front end (plotting commands, figure objects, etc) and backends (gtk, wx, ps, svg, etc). The backend is chosen dynamically at runtime -- eg the same python script could trigger the import gtk, wx, or ps, depending an some rc settings or command line opts. The question is: does shipping a backend which imports a module that links with GPL code make some or all of the library GPL. This question is complicated, in my mind at least, by several factors. Here are some sub-questions: * If a backend module somebackend does import somelib where somelib is a python wrapper of GPL code, is somebackend GPLd? * Assuming the answer to the above question is yes, is matplotlib GPLd if it distributes somebackend? I think this is a nuanced situation because matplotlib would work just fine w/o somemodule, and only uses somemodule's code if it is selected at runtime by the user. Ie, no other part of the code depends on it since it is one of many interchangeable backends. * To further complicate the question, the backend in question is qt, which is dual licensed, commercial and GPL. The qt backend code just needs to 'import qt', and neither the backend writer nor the matplotlib frontend knows whether the deployed qt on the system is commercial or GPLd. To date, the only GPL-like backend is GTK, which is LGPL. Since we're only linking and not using the src, we're protected from the GPL requirements. With QT, which has a pure (non L) GPL variant, the situation is less clear to me. Thoughts, links, etc, appreciated... JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Installing Numeric with ATLAS and LAPACK
drife == drife [EMAIL PROTECTED] writes: drife Hello, Could someone please provide instructions for drife install Numeric with ATLAS and LAPACK? Locate libcblas.a and add that dir to the setup.py library_dirs_list. Eg on my system, /usr/local/lib/ATLAS/lib/Linux_P4SSE2_2/libcblas.a setup.py: library_dirs_list = ['/usr/local/lib/ATLAS/lib/Linux_P4SSE2_2'] Do the same for cblas.h and add it to the include_dirs var in setup.py, on my system it is /usr/local/lib/ATLAS/include/cblas.h, so in setup.py include_dirs = ['/usr/local/lib/ATLAS/include/', '/usr/include/atlas'] Then python setup.py install *should* work. JDH -- http://mail.python.org/mailman/listinfo/python-list
handling xls with pyuno
Does anyone have any example scripts using the OpenOffince python-bridge module pyuno to load xls, extract the data, and/or save to another format such as xsc or csv. Thanks, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Installing Numeric with ATLAS and LAPACK
drife == drife [EMAIL PROTECTED] writes: drife Thanks John. Those are the steps I followed, and to no drife avail. Make sure you get a clean build by rm -rf ing the build dir before you build again. Then capture the output of your build to a file. When you say to no avail what do you mean -- that the calculation was slower. If you still have troubles, post again to the numpy-discussion list listing what you did and the output of the build process. Good luck! JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: LinearAlgebra incredibly slow for eigenvalue problems
drife == drife [EMAIL PROTECTED] writes: drife Hi David, I performed the above check, and sure enough, drife Numeric is --not-- linked to the ATLAS libraries. drife I followed each of your steps outlined above, and Numeric drife still is not linking to the ATLAS libraries. drife My setup.py file is attached below. Are you sure that you 1) 'rm -rf build' before rebuilding 2) are using the python / Numeric that you think you are, eg, might you have one python in /usr/bin and another in /usr/local. root paths can differ from user paths which may effect which python is used at install time versus run time -- http://mail.python.org/mailman/listinfo/python-list
detect tk mainloop
In matplotlib using the tkagg backend, the tk mainloop is started at the end of a python script by issuing a call to a show function, which realizes all the created figure windows and the calls Tkinter.mainloop(). This can cause problems if the mainloop was started by another module (eg idle). Is there a way to query tkinter to detect whether the mainloop has already been called? Thanks, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: python without OO
Davor == Davor [EMAIL PROTECTED] writes: Davor not really - it was not my intention at all - but it seems Davor people get upset whenever this OO stuff is mentioned - and Davor what I did not expect at all at this forum as I believed Davor Python people should not be so OO hardcore (seems not all Davor as quite a few have indicated in their Davor replies)... Nevertheless, I think the discussion has Davor several quite good points! -- Davor http://mail.python.org/mailman/listinfo/python-list Consider the case of a list, say x = [1,2,3,4] suppose you wanted to reverse the list, so that x becomes [4,3,2,1]. In a procedural language, one might do x = reverse(x) In an OO language such as python, one might do x.reverse() Is the OO way more obscure and complicated, etc? Not really -- it's only a minor syntactical difference. One of the core ideas behind OO programming is that data (the contents of the list 1,2,3,4) and methods (sorting, reversing) are bound together into a single entity, the object. On the face of it, this is rather sensible. You may rightly recoil against unnecessary abstraction and complexity, abuse of multiple inheritance and so on. That's perfectly sensible. But object orientation is probably not the bogey man here. python values readable code that is as simple as possible (but no simpler!) as you seem to. Focus on the actual problem, which is probably not OO programming, but colleagues who are making a design more complex than need be. Indeed, the third chant in the mantra of python is Simple is better than complex. John-Hunters-Computer:~ python Python 2.3 (#1, Sep 13 2003, 00:49:11) [GCC 3.3 20030304 (Apple Computer, Inc. build 1495)] on darwin Type help, copyright, credits or license for more information. import this The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those! -- http://mail.python.org/mailman/listinfo/python-list
Re: python without OO
beliavsky == beliavsky [EMAIL PROTECTED] writes: beliavsky I think the OO way is slightly more obscure. It's beliavsky obvious what x = reverse(x) does, but it is not clear beliavsky unless you have the source code whether x.reverse() You don't need to read the src, you just need to read the docs help([].reverse) Help on built-in function reverse: reverse(...) L.reverse() -- reverse *IN PLACE* beliavsky reverses x or if it returns a reversed list. If beliavsky x.reverse() does the former, a disadvantage relative to beliavsky the procedural approach is that a function can be used beliavsky in an expression. It is clearer and more concise to beliavsky write beliavsky z = reverse(x) + reverse(y) The distinction is not OO versus procedural, it is a decision about how you choose to write reverse. The python list implementers of the reverse object method could have decided to return a new reversed list rather than do the reverse in place and return None. Then you could have done z = x.reverse() + y.reverse() They could have chosen to reverse the list *in place* and also returned a reference to self rather than None, in which case you could do the above as well. w/o digging up the transcripts from the python-dev mailing list, my guess is that they choose to do it in place for efficiency in memory and cpu, and chose not to return self to prevent user confusion. Ie, if a user was allowed to do 'z = x.reverse() + y.reverse()' they might be surprised to find the side effect of in place modification. Likewise, I could easily write a procedural in place reverse that returns None, in which case 'z = reverse(x) + reverse(y)' would not do what you suggest. My point is that whether a function/method such as reverse operates in place or on a copy, and whether it returns None or a reference to a list is independent of OO vs procedural style and is motivated by considerations of efficiency, readability, and usability. beliavsky Furthermore, if in Python the algorithm for the reverse beliavsky function applies to many kinds of objects, it just beliavsky needs to be coded once, whereas a reverse method would beliavsky have to provided for each class that uses it (perhaps beliavsky through inheritance). True, a generic reverse procedure/function can be applied to any data structure that supports iteration. In the case of python, however, some iterable data structures are mutable (lists, dicts) and some are not (strings, tuples). For mutable sequences, an in place reverse is likely to be more efficient in memory and perhaps CPU than a generic reverse which returns a new copy. So a specialized method reverse applicable to lists (but not strings and tuples) can be a big win. Fortunately, python supports both, allowing you to define a general reverse that works for any object that supports the sequence protocol, as well as to define an object specific reverse method that may be faster in time and space. JDH -- http://mail.python.org/mailman/listinfo/python-list
ANN: matplotlib-0.71
matplotlib is a 2D graphics package that produces plots from python
scripts, the python shell, or embeds them in your favorite python GUI
-- wx, gtk, tk, fltk currently supported with qt in the works. Unlike
many python plotting alternatives is written in python, so it is
easy to extend. matplotlib is used in the finance industry, web
application servers, and many scientific and enginneering disciplines.
With a large community of users and developers, matplotlib is
approaching the goal of having a full featured, high quality, 2D
plotting library for python.
http://matplotlib.sourceforge.net
What's new in matplotlib 0.71
numerix refactor
The organization of the numerix module was refactored to be mindful
of namespaces. See http://matplotlib.sf.net/API_CHANGES. pylab no
longer overrides the built-ins min, max, and sum, and provides amin,
amax and asum as the numerix/mlab versions of these. pylab defines
__all__ to prevent surprises when doing from pylab import *. To see
the complete list of symbols provided
import matplotlib.pylab
matplotlib.pylab.__all__
contour zigzag bug fixed
Thanks Nadia for the blood, sweat and tears, and Dominique for the
report.
contour colormaps
Contour now uses the current colormap if colors is not provided, and
works with colorbars. See examples/contour_demo2.py
colorbar enhancements
Horizontal colorbars supported with keyword arg
orientation='horizontal' and colorbars can be placed in an arbitrary
axes with keyword arg cax.
accents in mathtext
Added accents to mathtext: \hat, reve, \grave, ar, cute, ilde, ec,
\dot, \ddot. All of them have the same syntax, eg to make an overbar
you do ar{o} or to make an o umlaut you do \ddot{o}. The shortcuts
are also provided, eg: o 'e \`e \~n \.x \^y . See
examples/accent_demo.py
fixed super/subscript parsing in mathtext
Widowed superscripts now work, eg r'$^12 m{CO}$'
little bugs and enhancements
Plugged some memory leaks in wx and image module, fixed x,y args in
contour, added latex symbol kappa, fixed a yticklabel problem under
change in clim, fixed colorbar number of color bug, fixed
set_clip_on bug, reverted pythoninspect in tkagg, fixed event
handling bugs, fixed matlab-compatible load function, exposed vbox
attr in FigureManagerGTK.
Downloads at http://matplotlib.sourceforge.net
JDH
--
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Re: how to write a tutorial
Xah == Xah Lee [EMAIL PROTECTED] writes: Xah at places often a whole paragraph on some so called computer Xah science jargons should be deleted. They are there more to Xah showcase inane technicality than do help the Xah reader. (related, many passages with jargons should be Xah rewritten sans inane jargon. e.g. mutable object.) The concept of mutable objects is extremely important in python, and understanding is the key to answering two recurring newbie questions * Why can't lists or dictionaries be keys to dictionaries? * Why does using a list as a default value for a keyword argument in a function definition often lead to unexpected results? So it is definitely appropriate material in a tutorial. As for jargon, it is hard to argue that object is inane jargon in python. In fact, the base class for new-styled classes is indeed object, and if you want to write one of these classes yourself, you need to do 'class MyClass(object)'. So object is not inane jargon in an object oriented programming language. You still with me? OK, now on to mutable. mutable means changeable, albeit it's a little more of an obscure word than changeable, but it does roll off the tongue a bit more easily. Perhaps 'changeable object' would be more accessible to some readers, but it doesn't flow as well. So the python tutorial should perhaps define mutable when it introduces it. Which it does somewhat implicitly; the first time mutable is mentioned in the docs, in the context of strings Unlike strings, which are immutable, it is possible to change individual elements of a list: And now for my last musing on a new topic How to write a critique: It is much more constructive to suggest new text for documentation than to brand it inane. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Graph and Table implementation
Jan == Jan Rienyer Gadil [EMAIL PROTECTED] writes: Jan could anyone please help me! what and how is the best Jan implementation of creating a table based on data coming from Jan the serial port ? and also how would i be able to create Jan graphs (2D) based on these data? Jan opinions and suggestion are most highly welcome. thanks. matplotlib can handle most kinds of 2D plots -- it even has a table command for including simple tabular data in your graph http://matplotlib.sourceforge.net/screenshots.html#table_demo so for heavy duty tables you'll probably want to use a GUI widget. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: problem with import pylab from a website
jean == jean rossier [EMAIL PROTECTED] writes: jean Hello All, I am facing a problem while importing pylab jean library(in a .py program file) via web browser however the jean same program works when I execute it from the command jean prompt. jean Error message we get: Permission denied: '/usr/share/matplotlib/.ttffont.cache', referer: One solution is to give yourself write permission to /usr/share/matplotlib. If this is not possible or in unpalatable for sysadmin reasons, you have a couple of options. matplotlib creates a font cache .ttffont.cache of the ttf files it finds on your system. If the HOME environment variable is set, it places the cache file in the HOME dir. So if setting HOME is a viable option for you, simply set this to a writable directory on your system and you are good to go. This is the approach I recommend. If HOME does not exist, matplotlib falls back on its data path: this is where fonts, icons and other goodies live. You can also customize this directory by setting the MATPLOTLIBDATA environment variable. If you go this route, more all the files currently in /usr/share/matplotlib to some other directory, say /my/dir, and make sure it is writable, and then set MATPLOTLIBDATA to point to it. Note matplotlib has a configuration file that controls all of the default settings for the plot. If you want to edit these, the edited file can also be placed in the HOME directory. See http://matplotlib.sf.net/.matplotlibrc . Hope this helps, JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Unbinding multiple variables
Johnny == Johnny Lin [EMAIL PROTECTED] writes:
Johnny Hi! Is there a way to automate the unbinding of multiple
Johnny variables? Say I have a list of the names of all
Johnny variables in the current scope via dir(). Is there a
Johnny command using del or something like that that will iterate
Johnny the list and unbind each of the variables?
Hi Johnny
I assume you are the one and only Johnny Lin at the U of C, no?
John-Hunters-Computer:~ python
Python 2.3 (#1, Sep 13 2003, 00:49:11)
[GCC 3.3 20030304 (Apple Computer, Inc. build 1495)] on darwin
Type help, copyright, credits or license for more information.
x = 1
y = 2
locals()
{'__builtins__': module '__builtin__' (built-in), '__name__':
'__main__', 'y': 2, '__doc__': None, 'x': 1}
print x,y
1 2
del locals()['x']
print x,y
Traceback (most recent call last):
File stdin, line 1, in ?
NameError: name 'x' is not defined
locals()
{'__builtins__': module '__builtin__' (built-in), '__name__':
'__main__', 'y': 2, '__doc__': None}
--
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Re: problems with duplicating and slicing an array
Yun == Yun Mao [EMAIL PROTECTED] writes: Yun 2. Is there a way to do Matlab style slicing? e.g. if I have Yun i = array([0, 2]) x = array([1.1, 2.2, 3.3, 4.4]) I wish y = Yun x(i) would give me [1.1, 3.3] Now I'm using map, but it gets Yun a little annoying when there are two dimensions. Any ideas Yun would be deeply appreciated! numarray supports matlab style indexing if you pass the ind as an array or list of indices (but not a tuple, I found to my surprise). As pointed out already, for Numeric you need to use the take function from numarray import array x = array([1,2,3,4,5,6,7,8,9]) ind = [3,5,7] inda = array(ind) indt = tuple(ind) x[ind] array([4, 6, 8]) x[inda] array([4, 6, 8]) x[indt] Traceback (most recent call last): File stdin, line 1, in ? IndexError: too many indices. I'm sure the tuple surprise is a documented feature. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: [OT] Good C++ book for a Python programmer
Philippe == Philippe C Martin [EMAIL PROTECTED] writes: Philippe I suggest you google 'C++ tutorial' Regards, Stroustup's The C++ Programming Language is the best C++ book I've read. It is at a fairly high level, and I already had read several C++ books before reading it, so it may be tough sledding. But I would try this first since you are an experienced programmer and know OO concepts, and if it fails to satisfy try something lighter. Unfortunately, I didn't like any of the other kinder, gentler overview books I read on C++, so can't really recommend anything along those lines, though I'm sure they are out there. JDH -- http://mail.python.org/mailman/listinfo/python-list
ANN: matplotlib-0.70
matplotlib is a 2D graphics package that produces plots from python scripts, the python shell, or embeds them in your favorite python GUI -- wx, gtk, tk, fltk currently supported with qt in the works. Unlike many python plotting alternatives is written in python, so it is easy to extend. matplotlib is used in the finance industry, web application servers, and many scientific and enginneering disciplines. With a large community of users and developers, matplotlib is approaching the goal of having a full featured, high quality, 2D plotting library for python. A lot of development has gone into matplotlib since the last major release, which I'll summarize here. For details, see the notes for the incremental releases at http://matplotlib.sf.net/whats_new.html. Major changes since matplotlib-0.60 - The alpha version of the users guide - http://matplotlib.sf.net/users_guide.pdf. There are still a number of sections to be completed, but it's a start! - The matlab namespace renamed pylab - if you are upgrading from a version older than 0.64, please remove site-packages/matplotlib before upgrading. See http://matplotlib.sourceforge.net/matlab_to_pylab.py - New plot types: contour plots (contour), polar charts (polar), horizontal bar charts (barh), pie charts (pie), sparse matrix visualization (spy and spy2). Eg, http://matplotlib.sf.net/screenshots.html#polar_demo - Full ipython http://ipython.scipy.org integration in the pylab mode for interactive control of matplotlib plots from the python shell. - A significantly improved interactive toolbar for panning, zooming, zoom to rect - see http://matplotlib.sf.net/tutorial.html#toolbar2. - New backends: FLTK, Cairo, GTKCairo - Text - rotated mathtext, mathtext for postscript, text bounding boxes - Colormaps - 14 colormaps built-in http://matplotlib.sf.net/screenshots.html#pcolor_demo - Images - performance optimizations for 4x faster large image handling, PIL support, interpolation and colorbar improvements, imread - Event handling for capturing mouse clicks, movements, keypresses, etc. - same pylab interface works across GUIs. See examples/keypress_demo.py, examples/picker_demo.py, examples/coords_demo.py - set and get matlab style property introspection - http://matplotlib.sf.net/examples/set_and_get.py - improved dates handling for dates and date string formatting from -, eg http://matplotlib.sf.net/screenshots.html#finance_work - Be sure to check out the 120 examples at http://matplotlib.sf.net/examples Home page : http://matplotlib.sourceforge.net Downloads : http://sourceforge.net/projects/matplotlib Screenshots : http://matplotlib.sourceforge.net/screenshots.html Tutorial: http://matplotlib.sourceforge.net/tutorial.html Credits : http://matplotlib.sourceforge.net/credits.html John Hunter -- http://mail.python.org/mailman/listinfo/python-list
Re: Using Python in my programs
Squirrel == Squirrel Havoc [EMAIL PROTECTED] (takeout) (takeout) writes: Squirrel Hello. I am sorry if this has been asked before, but I Squirrel am new here. Welcome Squirrel If I recall correctly, Python can be used as a scripting Squirrel language for other programs, as if the program had a Squirrel builtin Python interpreter. I wish to extend my Squirrel programs by making them scriptable with Python scripts. Squirrel Is this possible? If so, does anyone know where I can Squirrel find documentation on it? I searched the python.org site Squirrel and didnt find anything useful Google embedding python. First link is a good place to start -- http://docs.python.org/ext/ext.html -- the official docs for extending and embedding python. Extending python is when you want to write or wrap some library, typically C, C++ or FORTRAN, and expose its functionality to python. Embedding python is when you want to use the python interpreter in your own program. Start with the official docs mentioned above, and then check out SWIG and boost::python. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Legend problems in MatPlotLib
Jorl == Jorl Shefner [EMAIL PROTECTED] writes:
JorlI've only been able to plot data with both symbols and
Jorl lines by issuing two plot commands, one for markers and one
Jorl for lines. That's perfectly fine, but it creates a problem
Jorl when I try to create a legend for it. For some reason, the
Jorl legend command by default alternates between using symbols
Jorl and lines, grabbing displaying the symbol from the first
Jorl plot command for the first series, then displaying a line
Jorl type from the second plot for the next series, etc. This
Jorl behavior is a bit strange, and in fact unacceptable when the
Jorl same line type is used for each series.
Example code always helps, but note you can plot a line with lines and
markers like this
plot(x, y, '--s') # dashed line with square markers.
In this case matplotlib will recognize this as one line and should do
the legending properly.
However, if you do, which I infer you are from your post
plot(x, y, 's') # square markers.
plot(x, y, '--s') # square markers.
the plot will look the same but matplotlib considers this to be two
different lines and the legend will be messed up.
Note you can explicitly control what gets added to the legend, eg with
l1, l2 = plot(x, y, '--s', x1, y1, 'go')
p = bar(x3,y2)
legend((l1, p), ('My lines', 'My bars'))
In other words, if you don't like the way the autolegend is setup, you
can explicitly control the process.
Hope this helps.
JDH
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building extension modules under 2.4 / cygwin
For the first time, I am trying to compile a matplotlib installer for win32 / python2.4 under cygwin. I tested this earlier with one of the pre-release candidates and had no troubles. But when I compile with python2.4, I get the following error when I try and import my extension code the procedure entry point _ctype could not be located in the dynamic link libary msvcr71.dll This DLL resides in C:\Windows\System32 on my system If I edit the distutils/cygwincompiler.py file and remove the line that add this lib elif msc_ver == '1310': # MSVC 7.1 #self.dll_libraries = ['msvcr71'] self.dll_libraries = [] My code compiles, links and runs fine, at least in initial tests Any reason I shouldn't be doing this? JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Looking for a coder to do some work
Cameron == Cameron Laird [EMAIL PROTECTED] writes: Cameron I don't understand the last sentence; in particular, Cameron fort hsi is beyond my power to decode unambiguously. for this, clearly wink JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Python 3.0
duane == duane osterloth [EMAIL PROTECTED] writes: duane I'm looking for a stand alone email program which is not duane browser based. I simply want to write, send and receive duane email without accessing the internet. Is Python 3.0 that duane kind of program? I'd appreciate your response. Hi Duane, I'm a little confused by your request to send and receive email without accessing the internet, since email generally travels over the internet. Do you only want to handle email over an internal network? Or did you mean that you wanted to do this without accessing an internet browser such as Internet Explorer? I'm guessing the latter. In any case, python has a full complement of internet ready modules to send and receive email, so it will serve your purposes well. Go to http://groups.google.com and search for python email and read through some of the responses. Consider also reading the book Foundations of Python Network Programming, and take a look at the documentation for some of the modules related to email handling in the internet protocols sections of the python standard library reference at http://www.python.org/doc/current/lib/internet.html. Note that python 2.3.4 is the latest official release. python 3.0 does not exist, though some people have spoken of python 3.0 and python 3000 generically in terms of a future python release that will include certain language constructs not available today. JDH -- http://mail.python.org/mailman/listinfo/python-list
Re: Ideas for projects
Phillip == Phillip Bowden [EMAIL PROTECTED] writes: Phillip I feel that I've learned the language pretty well, but Phillip I'm having trouble thinking of a medium to large project Phillip to start. Some of these may be on the large side, but - Provide a full-feature, mostly specification complete python pdf parser. - Write a proper python package manager that recursively handles dependencies across platforms (CPAN/apt-get for python). - Enhance GUI integration. Ie, allow python code targetting one GUI environment to be used in a different one (contribute to anygui?) - Add 3D graphics to matplotlib (nudge, nudge, my own project). Integrate VTK? - Contribute a full-featured wavelets analysis package for python - Add internationalization support to your favorite python package which lacks it. - Add client side python support to mozilla and/or XUL - Write a python app that crawls python-list USENET posts looking for book or GUI-toolkit recommendations and automatically responds with links to FAQs and google groups. Be sure to include google is your friend in every response. - Contribute to the ipython rewrite effort so that python finally has an interactive shell across platforms worth its salt that has a chance of being included in the standard library. - Solve the problems with the global interpreter lock and give python a proper security model that will satisfy everyone with a hardcore Java and C++ background. Implement a proper Rational class and support date string formatting over the range of dates that the datetime module supports. Provide a full featured timezone module for the standard library. Support compile time type identification for runtime optimizations. If any or all of these have already been done, my apologies to the respective authors. JDH -- http://mail.python.org/mailman/listinfo/python-list
