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From: Bruce Sherwood <Bruce_S<herwood@nc...>  20071231 19:21:16

I repeated my own timings and then remembered why I didn't use try/except. The try/except scheme does give the fastest square root of a scalar (1.2 microsec on my 1 GHz laptop) but doubles the time for sqrt(array([1,2,3,4,5,6,7,8,9,10])), from about 10 microsec to about 20 microsec. So I've settled for the following, which gives sqrt(scalar) of 1.7 microsec and almost no change in sqrt(array): def sqrt(x): t = type(x) if t is float or t is int or t is long: return _m_sqrt(x) return _n_sqrt(x) Thanks again for thinking about this issue, and for alerting me to check not just for float. Bruce Sherwood P.S. What's in the justreleased 4.beta22 only checks for float, but the correction is now in CVS. Scott David Daniels wrote: > Bruce Sherwood wrote: > >> In a test version not yet released I've implemented essentially the >> scheme suggested by Scott David Daniels, and it works very well. Thanks! >> >> I found by timing measurements that a faster scheme with less penalty >> for the case of sqrt(array) looks like this: >> >> def sqrt(x): >> if type(x) is float: return mathsqrt(x) >> return numpysqrt(x) >> >> This scheme not only solves the problem but actually yields faster >> square roots of scalar arguments than numpy, by about a factor of 3. So >> what was conceived as a workaround is actually a performance enhancement. >> > > I actually did a bit of timing before I suggested the try/except version. > I use subclasses of ints and floats in some of the code I write. > A simple example (to make values more obvious): > class Float(float): > def __repr__(self): > return '%s(%s)' % (self.__class__.__name__, > float.__repr__(self)) > class Meters(Float): pass > class Grams(Float): pass > ... > Then I can make physical constants a little more obvious interactively. > > My first version was: > def sqrt(x): > if isinstance(x, (int, long, float)): > return mathsqrt(x) > else: > return numpysqrt(x) > > I then realized math.sqrt was already doing this check. Since the check > is already there, I decided not to slow down the more common scalar > case. That was when I switched to the "try: ... except TypeError: ..." > form (to use math.sqrt's type checks). I then made sure performance on > a short (tenelement) vector was not too severely impacted. If you > still want to exact match on types, I'd suggest accepting at least > floats and ints, since you'll otherwise get performance reports about > how much slower sqrt(4) is than sqrt(4.0). > > Something more like: > def sqrt(x): > t = type(x) > if t is float or t is int: > return mathsqrt(x) > else: > return numpysqrt(x) > > Scott David Daniels > Scott.Daniels@... > > >  > This SF.net email is sponsored by: Microsoft > Defy all challenges. Microsoft(R) Visual Studio 2005. > http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ > _______________________________________________ > Visualpythonusers mailing list > Visualpythonusers@... > https://lists.sourceforge.net/lists/listinfo/visualpythonusers > 
From: Bruce Sherwood <Bruce_S<herwood@nc...>  20071231 18:46:34

4.beta22 now available for Windows and Linux at sourceforge. Fixed a bug which made rendering of spheres very slow. When doing some experiments on adjusting the level of detail for spheres, Arthur Siegel in December 2006 commented out the statement that used a cached description of a sphere. The effect was to recompute a 3D model of every sphere in every render cycle. There are still some issues with slow rendering in the beta version, but this was certainly the most serious bug. The recently contributed program vspace.py now runs on the beta version, though not as well as on the production version of VPython. Bruce Sherwood 
From: Bruce Sherwood <Bruce_S<herwood@nc...>  20071231 05:25:42

Good points. Thanks. Bruce Sherwood Scott David Daniels wrote: > Bruce Sherwood wrote: > >> In a test version not yet released I've implemented essentially the >> scheme suggested by Scott David Daniels, and it works very well. Thanks! >> >> I found by timing measurements that a faster scheme with less penalty >> for the case of sqrt(array) looks like this: >> >> def sqrt(x): >> if type(x) is float: return mathsqrt(x) >> return numpysqrt(x) >> >> This scheme not only solves the problem but actually yields faster >> square roots of scalar arguments than numpy, by about a factor of 3. So >> what was conceived as a workaround is actually a performance enhancement. >> > > I actually did a bit of timing before I suggested the try/except version. > I use subclasses of ints and floats in some of the code I write. > A simple example (to make values more obvious): > class Float(float): > def __repr__(self): > return '%s(%s)' % (self.__class__.__name__, > float.__repr__(self)) > class Meters(Float): pass > class Grams(Float): pass > ... > Then I can make physical constants a little more obvious interactively. > > My first version was: > def sqrt(x): > if isinstance(x, (int, long, float)): > return mathsqrt(x) > else: > return numpysqrt(x) > > I then realized math.sqrt was already doing this check. Since the check > is already there, I decided not to slow down the more common scalar > case. That was when I switched to the "try: ... except TypeError: ..." > form (to use math.sqrt's type checks). I then made sure performance on > a short (tenelement) vector was not too severely impacted. If you > still want to exact match on types, I'd suggest accepting at least > floats and ints, since you'll otherwise get performance reports about > how much slower sqrt(4) is than sqrt(4.0). > > Something more like: > def sqrt(x): > t = type(x) > if t is float or t is int: > return mathsqrt(x) > else: > return numpysqrt(x) > > Scott David Daniels > Scott.Daniels@... > > >  > This SF.net email is sponsored by: Microsoft > Defy all challenges. Microsoft(R) Visual Studio 2005. > http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ > _______________________________________________ > Visualpythonusers mailing list > Visualpythonusers@... > https://lists.sourceforge.net/lists/listinfo/visualpythonusers > 
From: Ron Adam <rrr@ro...>  20071231 04:01:27

Bruce Sherwood wrote: > That's a spectacular demonstration of work that needs to be done on the > beta version, as it takes 5 seconds (!) to render the scene on my > laptop, whereas the display and motion are completely smooth in the > production version of VPython. I could possibly change it to add the asteroid objects after the main loop is started until a desired frame rate is achieved. It will still run smoothly on slower computers that way. And display the object count in a corner for comparisons. > I've added this to the contributed section of vpython.org. Thanks! You're welcome, it was fun to figure out how to do it too. Ron > I deleted the unnecessary line that made the mouse cursor visible, since > that's the default and this feature is as yet missing from the beta > version, should someone wish to see the extreme slowness of the rendering. > > Bruce Sherwood > Ron Adam wrote: >> >> Bruce Sherwood wrote: >>> Questions were asked recently about looking outward from the origin >>> (or other location) and rotating the view of the surrounding scene. >>> As an example of this kind of viewing, see look_around.py in the >>> contributed section of vpython.org. >>> >>> Bruce Sherwood >> Here's a fun demo that uses rotating and spin I meant to submit some >> time ago and never did. >> >> Enjoy, >> Ron Adam >>  >> >>  >> This SF.net email is sponsored by: Microsoft >> Defy all challenges. Microsoft(R) Visual Studio 2005. >> http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ >>  >> >> _______________________________________________ >> Visualpythonusers mailing list >> Visualpythonusers@... >> https://lists.sourceforge.net/lists/listinfo/visualpythonusers > >  > This SF.net email is sponsored by: Microsoft > Defy all challenges. Microsoft(R) Visual Studio 2005. > http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ 