Custom data transformations with log ticks

Hello All,

I have data that I need to apply log-based transformations to followed
by plotting. Ideally I would like the plot to display the nicely
formatted log-scale major/minor ticks as when setting xscale('log').
Of course, doing that applies the default log transformation to
already log-transformed data.

I played around with the matplotlib.ticker classes, but the LogLocator
only seems to work properly when applied to a plot with axes set to
log scale or plotted with something like semilog (as in
http://old.nabble.com/ticks---labels-td18931344.html).

An example:

import matplotlib.pyplot as plt
import matplotlib.ticker as mt
import numpy as np

x = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600,
700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000]
xlog = np.log10(x) #or some other more complex transform
y = [1 for i in x]

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(xlog,y, '.', c='blue', ms=2)
ax.xaxis.set_major_locator(mt.LogLocator())
plt.show()

Resulting in: http://imgur.com/MtsLE.png
As opposed to what I would like: http://imgur.com/QELVD.png (plotting
x instead of xlog, and ax.set_xscale('log'))

I'm probably missing something simple, but I haven't been able to
figure it out as of yet.

Thanks in advance for any suggestions/help.
Shareef

The problem is that the LogLocator expects the data to be non-log-transformed, since it is providing the log transform itself. It actually is doing the right thing since the data passed to plot ranges from 1 to 4.

As a workaround, you can manually set the ticks with set_xticks, set_xmajorticklabels and set_xminorticklabels -- you will need to set the tick positions and their display separately since you are trying to print values that are not the actual values of the data you're passing in.

If you want your graph to be interactive, however, you will probably want to look into writing a custom scale. See this document:

   http://matplotlib.sourceforge.net/devel/add_new_projection.html

and this example:

   http://matplotlib.sourceforge.net/examples/api/custom_scale_example.html?highlight=custom_scale_example

Mike

···

On 06/07/2010 09:46 PM, Shareef Dabdoub wrote:

Hello All,

I have data that I need to apply log-based transformations to followed
by plotting. Ideally I would like the plot to display the nicely
formatted log-scale major/minor ticks as when setting xscale('log').
Of course, doing that applies the default log transformation to
already log-transformed data.

I played around with the matplotlib.ticker classes, but the LogLocator
only seems to work properly when applied to a plot with axes set to
log scale or plotted with something like semilog (as in
http://old.nabble.com/ticks---labels-td18931344.html).

An example:

import matplotlib.pyplot as plt
import matplotlib.ticker as mt
import numpy as np

x = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600,
700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000]
xlog = np.log10(x) #or some other more complex transform
y = [1 for i in x]

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(xlog,y, '.', c='blue', ms=2)
ax.xaxis.set_major_locator(mt.LogLocator())
plt.show()

Resulting in: http://imgur.com/MtsLE.png
As opposed to what I would like: http://imgur.com/QELVD.png (plotting
x instead of xlog, and ax.set_xscale('log'))

I'm probably missing something simple, but I haven't been able to
figure it out as of yet.

Thanks in advance for any suggestions/help.
Shareef

------------------------------------------------------------------------------
ThinkGeek and WIRED's GeekDad team up for the Ultimate
GeekDad Father's Day Giveaway. ONE MASSIVE PRIZE to the
lucky parental unit. See the prize list and enter to win:
http://p.sf.net/sfu/thinkgeek-promo
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
   
--
Michael Droettboom
Science Software Branch
Space Telescope Science Institute
Baltimore, Maryland, USA