Skip to main content

New version of matplotlib out : 3D plotting!

The hard working folks at matplotlib have put out a new release candidate with interesting new features.

Remember - its a release candidate. Not (yet) for production.

Get it from http://drop.io/xortel1#
Install using sudo easy_install ~/Downloads/matplotlib-0.99.0.rc1_r0-py2.5-macosx-10.5-i386.egg
On mac you will hear complaints about
Searching for matplotlib==0.99.0.rc1-r0
Reading http://pypi.python.org/simple/matplotlib/
Reading http://matplotlib.sourceforge.net
Reading https://sourceforge.net/project/showfiles.php?group_id=80706&package_id=278194
Reading https://sourceforge.net/project/showfiles.php?group_id=80706&package_id=82474
Reading http://sourceforge.net/project/showfiles.php?group_id=80706&package_id=82474
Reading http://sourceforge.net/project/showfiles.php?group_id=80706
No local packages or download links found for matplotlib==0.99.0.rc1-r0
error: Could not find suitable distribution for Requirement.parse('matplotlib==0.99.0.rc1-r0')
but it will be installed fine.

Most interesting is the incorporation of 3D plotting.

from mpl_toolkits.mplot3d import axes3d
import pylab

x = y = pylab.arange(-1,1.0,.05)
X, Y = pylab.meshgrid(x,y)
Z = pylab.cos(pylab.pi*X) * pylab.sin(pylab.pi * Y)
fig = pylab.figure(); ax = axes3d.Axes3D(fig); cset = ax.contourf(X, Y, Z, 20);

Comments

Popular posts from this blog

A note on Python's __exit__() and errors

Python's context managers are a very neat way of handling code that needs a teardown once you are done. Python objects have do have a destructor method ( __del__ ) called right before the last instance of the object is about to be destroyed. You can do a teardown there. However there is a lot of fine print to the __del__ method. A cleaner way of doing tear-downs is through Python's context manager , manifested as the with keyword. class CrushMe: def __init__(self): self.f = open('test.txt', 'w') def foo(self, a, b): self.f.write(str(a - b)) def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() return True with CrushMe() as c: c.foo(2, 3) One thing that is important, and that got me just now, is error handling. I made the mistake of ignoring all those 'junk' arguments ( exc_type, exc_val, exc_tb ). I just skimmed the docs and what popped out is that you need to return True or...

Store numpy arrays in sqlite

Use numpy.getbuffer (or sqlite3.Binary ) in combination with numpy.frombuffer to lug numpy data in and out of the sqlite3 database: import sqlite3, numpy r1d = numpy.random.randn(10) con = sqlite3.connect(':memory:') con.execute("CREATE TABLE eye(id INTEGER PRIMARY KEY, desc TEXT, data BLOB)") con.execute("INSERT INTO eye(desc,data) VALUES(?,?)", ("1d", sqlite3.Binary(r1d))) con.execute("INSERT INTO eye(desc,data) VALUES(?,?)", ("1d", numpy.getbuffer(r1d))) res = con.execute("SELECT * FROM eye").fetchall() con.close() #res -> #[(1, u'1d', <read-write buffer ptr 0x10371b220, size 80 at 0x10371b1e0>), # (2, u'1d', <read-write buffer ptr 0x10371b190, size 80 at 0x10371b150>)] print r1d - numpy.frombuffer(res[0][2]) #->[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] print r1d - numpy.frombuffer(res[1][2]) #->[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] Note that for work where data ty...