Thank you for the help, I never knew what the symlog flag did actually.
However, there is still a slight problem:
=====================================================
x = array([0,1,2,4,6,9,12,24])
y = array([1000000, 500000, 100000, 100, 5, 1, 1, 1])
subplot(111)
plot(x, y)
yscale('symlog')
xscale=('linear')
ylim(-1,10000000)
show()
=====================================================
The plot looks exactly like I want it, the problem is when I change
the "1"'s to "0"'s in the y-array, then I get a:
File "C:\Python26\lib\site-packages\matplotlib\ticker.py", line 1029,
in is_decade
lx = math.log(x)/math.log(base)
ValueError: math domain error
I suppose that means somewhere a log(0) is attempted. This kind of
defeats the purpose...
/C
Quoting Eric Firing <efir...@hawaii.edu>:
> On 05/19/2010 10:28 AM, Benjamin Root wrote:
>> Maybe I am misunderstanding your problem, but you can select
'semilog'
>> for the x/yscale parameter.
>
> You mean "symlog".
>
> See
>
http://matplotlib.sourceforge.net/examples/pylab_examples/symlog_demo.html
>
> Although the example doesn't show it, the axis limits don't have to be
> symmetric. For example, on the top plot, you can use
>
> gca().set_xlim([0, 100])
>
> to show only the right-hand side.
>
> Eric
>
>
>>
>> Ben Root
>>
>> On Wed, May 19, 2010 at 7:03 AM, Christer Malmberg
>> <christer.malmberg.0...@student.uu.se
>> <mailto:christer.malmberg.0...@student.uu.se>> wrote:
>>
>> Hi,
>>
>> my problem is that I need a graph with a discontinous y-axis. Let
me
>> explain the problem: in my field (microbiology) the data
generated
>> from for example growth assays have a huge range (10^0-10^9),
which
>> has to be plotted on a semilogy style plot (cell concentration
vs.
>> time). The problem is that 0 cells is a useful number to plot
>> (indicates cell concentration lower than detection limit), but of
>> course not possible to show in a log diagram. This is easily
solved on
>> old-style logarithmic graph paper; since the data will be either
0, or
>> >1 it is customary just to draw a zero x-axis at 10^-1 on the
paper
>> and that's that. On the computer, this is extremely hard. Most
people
>> I know resort to various tricks in Excel, such as entering a
small
>> number (0.001 etc) and starting the y-axis range from 10^1 to
hide the
>> problem. This makes excel draw a line, instead of leaving out the
dot
>> and line entirely. The part of the curve below the x-axis is then
>> manually cut off in a suitable image editor. Needless to say,
this is
>> extremely kludgy. Even professional graphing packages like
Graphpad
>> Prism resort to similar kludges (re-define 0 values to 0.1,
change the
>> y-axis tick label to "0" etc.) This problem of course exists in
other
>> fields, while investigating a solution I found a guy who worked
with
>> aerosol contamination in clean rooms, and he needed to plot
values
>> logarithmically, at the same time as showing detector noise
around
>> 1-10 particles. He solved it by the same trick I would like to do
in
>> Matplotlib, namely plotting a standard semilogy plot but with the
>> 10^-1 to 10^0 decade being replaced by a 0-1 linear axis on the
same
>> side.
>>
>> The guy in this post has the same problem and a useful example:
>> http://ubuntuforums.org/showthread.php?t=394851
>>
>> His partial solution is quite bad though, and I just got stuck
while
>> trying to improve it. I looked around the gallery for useful
examples,
>> and the closest I could find is the twinx/twiny function, but I
didn't
>> manage a plot that put one data curve across both axes.
>>
>> This code gives an image that maybe explains what I'm trying to
do:
>>
>> =======================================
>> t = array([0,1,2,4,6,9,12,24])
>> y = array([1000000, 500000, 100000, 100, 5, 1, 0, 0])
>> subplot(111, xscale="linear", yscale="log")
>> errorbar(x, y, yerr=0.4*y)
>> linbit = axes([0.125, 0.1, 0.775, 0.1],frameon=False)
>> linbit.xaxis.set_visible(False)
>> for tl in linbit.get_yticklabels():
>> tl.set_color('r')
>> show()
>> =======================================
>>
>> (the y=0 points should be plotted and connected to the line in
the
>> log part)
>>
>> Is this possible to do in matplotlib? Could someone give me a
pointer
>> on how to go on?
>>
>> Sorry for the long mail,
>>
>> /C
>>
>>
>>
>>
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