On Sun, Feb 01, 2009 at 11:59:06PM +0100, Sandro Tosi wrote:
Hi Chris,
thanks for your reply, helpful as usual :)
On Fri, Jan 30, 2009 at 18:59, Chris Walker
chr...@chiark.greenend.org.uk wrote:
Firstly, good luck with the book.
cheers :)
The sort of book I'd buy would explain how to use the combination of
matplotlib/ipython/scipy/numpy to analyse data.
Sadly, that would not the book I'll write :( The editor wanted to
target another audience for the book: experienced python developers,
with no knowledge of matplotlib; so an introductionary book, that will
show even how to integrate mpl on GTK/WX application and on the web.
I pushed to have something about science, and a chapter will be about
that, but I need your (all) inputs, because my science days are long
back in the past ;)
Sure - though anyone wanting to use matplotlib is likely to be
acquiring, manipulating and then plotting data.
- what are the (basic) things that, when you were beginning to use
matplotlib, you wanted to see grouped up but couldn't find?
- what would you like to see in a book about matplotlib?
Start off by reading data from a file, plotting it and fitting a
function to that data.
That sounds something that could land in the science chapter.
Indeed.
Plotting with related scales
Sometimes it is useful to plot related scales on x1 and x2 axes. I've
come across this several times in different contexts. In its simplest
form, there is a linear relationship between the axes. In a mechanical
test, you might want extension on the x1 axis and strain on the x2 axis
(for example).
Sometimes there is not a linear relationship. For example you might
want to plot frequency (or photon energy) on x1 and wavelength on x2.
An even more complex example is a Hall-Petch plot:
(Yield Stress) = k/sqrt(Grain Size)
So plotting 1/Sqrt(Grain Size) on the X1 axis gives a linear
plot, but it would be useful to plot the grain size on the X2 scale.
Err, I think I lost you ;)
Figure 3b/3c at
http://dcwww.camd.dtu.dk/~schiotz/papers/risoesymp/html/node3.html
is an example - note that the y2 scale is not linear.
What you want is 2 plots on the same figure? so not 2 Ys for the same
X
2 scales on the same figure, yes.
(let's say X is time, and Y1 is stock price variation, and Y2 is the
percentage change), you want X1-Y1 (let's say on the bottom-left) and
X2-Y2 (on the upper-right): did I get you?
Exactly. http://en.wikipedia.org/wiki/File:Body_mass_index_chart.svg
is the sort of thing I had in mind.
ipython and emacs
-
Suppose I want to write a script to analyse some data (perhaps I want
a record of what I've done, or perhaps I'd like to perform the same
analysis on several data sets). I'd probably do so in emacs - but it
is useful to do some experimentation in ipython - tab completion is
particularly useful. I feel there must be a good way to do my
experimentation in ipython and save the important bits in emacs - but
I've not sat down and worked out an efficient way of doing this.
I think the preferred way to do so it using ipython, and for now I
plan only to show it on the book.
Whether or not this make it into the book, I'm interested in how
people do this. Surely you don't write your application using just
ipython do you?
Data aqcuisition and experimental control:
-
Writing a simple application to acquire data - ideally from multiple
sources and plot the data as it is acquired. In my case I wanted to
combine mechanical with electrical tests. A couple of interesting
articles by G Varoquaux are listed at
http://wiki.debian.org/DebianScience/DataAcquisition
This is perhaps beyond the scope of the book, but it has come up on
the mailing lists a couple of times. The ideal application would have
a gui for simple use, but a command line (probably ipython) for more
more complex use - perhaps performing a series of tests under
different conditions.
I thought about an example for this already! :)
Excellent.
I thought to develop a
sample application for GTK/WX that display some system value (like cpu
usage or so, in this way everyone can run the example) plotting the
information as it comes (for 30 secs, for example).
One of the things I liked about Gael's article was its discussion of
threading - separating the gui from the calculations from the data
acquisition.
Some discussion of plotting non gridded 2d data should also be in
there.
for example?
Something like:
http://matplotlib.sourceforge.net/examples/pylab_examples/griddata_demo.html
It is something I have encountered several times.
Another example I had in mind is:
http://www.sci.muni.cz/~mikulik/gallery.html#GaAlAsFishAtPM
http://www.sci.muni.cz/~mikulik/gnuplot.html
I've taken similar measurements in the past - and one often takes
