Note: Posted to matplotlib-devel and debian-science.
Sandro,
Firstly, good luck with the book.
The sort of book I'd buy would explain how to use the combination of
matplotlib/ipython/scipy/numpy to analyse data.
> - what are you using matplotlib for?
I want to use matplotlib/ipython/numpy/scipy for analysis of
experimental data - plotting and fitting models to it. Also perhaps
simulation of the data.
I have also wanted to use matplotlib to plot data as it was acquired -
see below.
I've not really used matplotlib in anger - but am likely to do so in
the future (and it would have been useful during my PhD had it been
around then).
> - what are the things you like the most of matplotlib, that you want
> to give emphasis to? And why?
Quality plots. The ability to add TeX labels.
I've been keeping an eye on matplotlib for several years - it looks
good. I really must spend some time exploring it.
> - 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.
Often, several scans are in the same data file. An elegant solution to
reading data something like this example would be useful.
# Scan: 1
# Time: 18:00
# Temperature: 21
# t data
1 12
2 33
3 14
4 40
5 60
# Scan: 2
# Time: 18:02
# Temperature: 30
# t data
1 22
2 33
3 44
4 55
And so on.
Fitting a function to several data sets - with some of the parameters
fitted to both sets of data and some not would be useful.
> - what are some those advanced feature that made you yell "WOW!!" ?
> - what are the things you'd like to explore of matplotlib and never
> had time to do?
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.
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.
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.
Some discussion of plotting non gridded 2d data should also be in
there.
>
> Your suggestions are really appreciated :) And wish me good luck!
I don't think it is the thrust of your book, but another book I was
looking for is "A cookbook of Numerical simulations of classic
physics/engineering problems". For use by physicists/engineers who
don't want to rewrite things from scratch.
Good luck.
Chris
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