Women in the military

Why don't women in the military have to shave their heads the same as the men do?

Permalink | Comments? | id 2119

23:07 (utc-4)

 

The Sum of All Fears

Just saw The Sum of All Fears (IMDB, Ebert: 3 1/2 stars). See it.

Permalink | 6 Comments | id 2118

22:13 (utc-4)

 

Interview with Paul F. Dubois

Via the Daily Python-URL (they should really have permalinks), Interview of Paul F. Dubois of Numeric Python Fame.

Plain Python is perfectly suitable for all ordinary computations, including floating-point calculations. The place where it has a problem is when you have an array calculation, the sort where you would have a big do-loop in Fortran or a for-loop in C. Then the fact that Python is interpreted shows up because such calculations are not as fast as in a compiled language.

Numerical Python is an add-on module that lets you create and manipulate such arrays. Since the array is now an object, processing such as addition, subtraction, or taking a square root can now be done in Numeric's modules, which are written in C. So the loop is still there, but now it is in C and dealing with raw numbers, not in Python and dealing with objects. You get back to within 10% or so of C, and your expression is actually better, being like modern Fortran's array statements, e.g. z = sqrt(x**2 + y**2), rather than a loop with explicit indexing.

The most important fact about Python and Numeric for science is that the language is simple and easy to learn, and resembles other simple languages such as IDL, Matlab, and Fortran, that scientists have found useful and are familiar with. Similar steering projects where the interpreted language was more "computer sciency", such as Scheme or C, have not proven as attractive. The scientists already have a full-time career and so ease of use and a gentle learning curve are crucial. I think Python is now the standard choice for steering scientific programs.

Permalink | Comments? | id 2117

22:02 (utc-4)
edited: 23:41 (utc-4)

 

It was only a matter of time

I knew that it was only a matter of time before Linux apps will be available for OSX. KDE now runs on top of OSX! Here's the entire release notice from Sourceforge:

The Fink team is happy to announce preliminary support for KDE on MacOS X.

To find out more about the K Desktop Environment, see "What is KDE?" at the KDE web site.

Work has been progressing steadily on getting KDE 3.0.x ported to run in XFree86 on MacOS X. Packages and pre-built binaries are now available for users interested in running KDE on MacOS X via Fink, at:

http://fink.sourceforge.net/

For detailed instructions on installing or building KDE on Fink, and screenshots of KDE running on OSX, see the full announcement at:

http://fink.sourceforge.net/news/kde.php

I had never heard of the Fink project before. Does OSX come with an X server included for KDE to run on, or does this port of KDE include an OSX port of XFree86? Ok, it looks like OSX does come with XFree86 under "Applications -> XDarwin", but you need the Fink version of XFree86 to run this port of KDE -- "These packages will only work with the xfree86-base from the Fink distribution, version 4.2.0-5 or higher."

Finally, a warning:

While a number of us on the Fink team have been running KDE on MacOS X for a couple of weeks now, this is still very definitely a work-in-progress. There are no guarantees that it won't delete your hard drive, kill your dog, put water in your gas tank, or make parts of your body randomly explode. While we've tried to make sure things are at least in a usable state, your mileage may vary, doubly so if you're using the pre-built binaries. If you are not comfortable with working with beta software, or working in the unstable distribution of Fink, you are better off waiting for KDE to move into the stable tree. In other words, don't say we didn't warn you! =)

Permalink | Comments? | id 2116

15:37 (utc-4)
edited: 15:42 (utc-4)