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From: John Hunter <jdhunter@ac...> - 2004-09-28 20:04:08
What's new in matplotlib-0.63.0
Announce notes with links available at
* image interpolation works properly. I think I have finally and
for real this time fixed the image interpolation / edge effect
bug. It turns out there was a bug in antigrain (very unusual!)
that was just found, fixed, and released. I've incorporated the
latest release into matplotlib, and after talking with the Maxim
implemented a solution in matplotlib which fixes the edge problem
w/o the view lim hack used previously. Basically, I pad the edges
of the input image. This is described in more detail in the new
examples/image_interp.py. There is still an occasional off by 1
rounding problem that causes a 1 pixel error (this is independent
of the interpolation/edge bug).
* The dates handling is rewritten from the ground up, and now
requires python2.3. It makes extensive use of dateutil for date
ticking. All of your old date code will break, but it's an easy
port. In particular, note that the date tick location
constructors now have a different meaning. See
http://matplotlib.sf.net/matplotlib.dates.html, the updated date
demos in examples/ and the new dates tutorial at
* setup.py now automatically detects Numeric, numarray or both, and
compiles in the appropriate extension code. Thus you can use
matplotlib with either or both packages and still get the optimal
performance. So it is no longer necessary to set NUMERIX in
setup.py, but it is necessary to have the extensions you want
compiled available at the time you compile matplotlib. The win32
build is for numarray 1.1.
* new functions xlim, ylim, xticks and yticks to make setting axis
limits, tick locations and labels more natural and elegant.
* Reorganized all python library code to lib/ subdir
* Added print to file handle for backend agg; see
examples/print_stdout.py. Useful for webapp servers who want to
print to a pipe.
* x and y coords are printed in the toolbar on nouse motion in
backends gtk* and tkagg (not implemented yet in wx*). You can set
the axis attributes ax.fmt_xdata and ax.fmt_ydata with callable
functions to control the formatting of the reported coords
(default uses the major tick formatter). See
examples/coords_report.py and examples/date_demo1.py.
* Added axhline, axvline, axhspan and axvspan for plotting lines and
rectangles (spans) in mixed data/axes coords. This is useful if
for example, you want to provide a threshold line or range where
the x range spans the axes (0-1 in axes coords) and the y range is
given in data units. See example/axhspan_demo.py.
Downloads at https://sourceforge.net/projects/matplotlib/