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What is the preferred method to do the equivalent of plot_date with log scaling for the non-date values? Thanks, Alan Isaac
Colleagues, I am trying to follow the http://matplotlib.sourceforge.net/users/pyplot_tutorial.html tutorial with little success. The very first import fails with either 64 or 32-bit python. Any hints I have missed? $ python Python 2.6.1 (r261:67515, Feb 11 2010, 00:51:29) [GCC 4.2.1 (Apple Inc. build 5646)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import matplotlib.pyplot as plt Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Library/Python/2.6/site-packages/matplotlib-0.99.1.1-py2.6-macosx-10.3-fat.egg/matplotlib/pyplot.py", line 6, in <module> from matplotlib.figure import Figure, figaspect File "/Library/Python/2.6/site-packages/matplotlib-0.99.1.1-py2.6-macosx-10.3-fat.egg/matplotlib/figure.py", line 16, in <module> import artist File "/Library/Python/2.6/site-packages/matplotlib-0.99.1.1-py2.6-macosx-10.3-fat.egg/matplotlib/artist.py", line 5, in <module> from transforms import Bbox, IdentityTransform, TransformedBbox, TransformedPath File "/Library/Python/2.6/site-packages/matplotlib-0.99.1.1-py2.6-macosx-10.3-fat.egg/matplotlib/transforms.py", line 34, in <module> from matplotlib._path import affine_transform ImportError: /Library/Python/2.6/site-packages/matplotlib-0.99.1.1-py2.6-macosx-10.3-fat.egg/matplotlib/_path.so: no appropriate 64-bit architecture (see "man python" for running in 32-bit mode) >>> exit() $ defaults write com.apple.versioner.python Prefer-32-Bit -bool yes $ python Python 2.6.1 (r261:67515, Feb 11 2010, 00:51:29) [GCC 4.2.1 (Apple Inc. build 5646)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import matplotlib.pyplot as plt Bus error $ Sincerely, Vlad This e-mail and its attachments are intended only for the individual or entity to whom it is addressed and may contain information that is confidential, privileged, inside information, or subject to other restrictions on use or disclosure. Any unauthorized use, dissemination or copying of this transmission or the information in it is prohibited and may be unlawful. If you have received this transmission in error, please notify the sender immediately by return e-mail, and permanently delete or destroy this e-mail, any attachments, and all copies (digital or paper). Unless expressly stated in this e-mail, nothing in this message should be construed as a digital or electronic signature.
On Wed, May 12, 2010 at 5:58 AM, Yannick Copin <yan...@la...> wrote: > gs = gridspec.GridSpec(3, 3) > ax1 = gs[0, :] > I'm inclined to leave the GridSpec as it is and I prefer to have a separate class for this (if we go for it). My inclination is to modify subplot2grid to return such an instance. e.g., grid = gridspec.subplot2grid((2,2)) ax1 = grid[0,:] Regards, -JJ
On Tue, May 11, 2010 at 1:38 PM, John Hunter <jd...@gm...> wrote: > This looks sufficiently general and useful that we may simply want it > to live in the main tree (not as a toolkit) and have subplot2grd > helper functionality available directly from pyplot. > Okay. I'll merge this into the main tree and commit. Regards, -JJ
Hi, Jae-Joon Lee <lee.j.joon@...> writes: > gridspec is a module that implements matplotlib’s Subplot slightly > differently. Current matplotlib’s Subplot only allows a Subplot to > occupy a single cell of the n x m grid. gridspec enables a Subplot to > occupy multiple cells. Very interesting indeed. If I may comment on the usability, I wish function gridspec.subplot could become directly a method of Gridspec. The current example: gs = gridspec.GridSpec(3, 3) ax1 = gridspec.subplot(gs[0, :]) ax2 = gridspec.subplot(gs[1,:-1]) ax3 = gridspec.subplot(gs[1:, -1]) ax4 = gridspec.subplot(gs[-1,0]) ax5 = gridspec.subplot(gs[-1,-2]) could be written in a much simpler way then, such as: gs = gridspec.GridSpec(3, 3) ax1 = gs[0, :] ax2 = gs[1,:-1] ax3 = gs[1:, -1] ax4 = gs[-1,0] ax5 = gs[-1,-2] I would LOVE it! +1 for getting these functionnalities straight in matplotlib: subplot management always take a decent part of my scripts... Cheers,