playing sound in mac osx

[tooru honda]

Hi,

I am a newbie to mac and python.

Is there an easy way to play wav or mp3 sound file ?  I used to use
winsound module before switching to mac, but that only works for windows.

Thanks

Tooru

P.S. I am using Mac OSX 10.4.8 and Python 2.5
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Does shuffle() produce uniform result ?

[tooru honda]

Hi,

I have read the source code of the built-in random module, random.py.  
After also reading Wiki article on Knuth Shuffle algorithm, I wonder if 
the shuffle method implemented in random.py produces results with modulo 
bias.

The reasoning is as follows: Because the method random() only produces 
finitely many possible results, we get modulo bias when the number of 
possible results is not divisible by the size of the shuffled list.

1. Does shuffle() produce uniform result ?

2. If not, is there a fast and uniform shuffle() available somewhere ?

Thanks !

-tooru honda
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Re: Does shuffle() produce uniform result ?

[tooru honda]

Hi, First of all, my thanks to all of you who replied.

I am writing a gamble simulation to convince my friend that his "winning 
strategy" doesn't work.  I use shuffle method from a random.SystemRandom 
instance to shuffle 8 decks of cards.

As the number of cards is quite small (number of cards is 416), the 
nonuniformity doesn't matter as most of you have already said.  Just to 
avoid argument from my friend, I am considering writing my own randint 
and shuffle methods based on os.urandom() though.

-tooru honda
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Re: Does shuffle() produce uniform result ?

[tooru honda]

At the end, I think it is worthwhile to implement my own shuffle and 
random methods based on os.urandom.  Not only does the resulting code 
gets rid of the minuscule bias, but the program also runs much faster.

When using random.SystemRandom.shuffle, posix.open and posix.close from 
calling os.urandom account for almost half of the total execution time 
for my program.  By implementing my own random and getting a much larger 
chunk of random bytes from os.urandom each time, I am able to reduce the 
total execution time by half.

-tooru honda

P.S. I use python 2.5.1 on MacOSX 10.4.10 (PowerPC).
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Re: Does shuffle() produce uniform result ?

[tooru honda]

By incorporating Alex's code, I got another performance boost of 20%.  
It is mostly due to Alex's more efficient implementation of block random 
than my own version.

-tooru honda

Below is the code I have now:


from binascii import hexlify
from os import urandom

class rcRandomC(random.SystemRandom):

def __init__(self):
random.SystemRandom.__init__(self)

def rand2():

while True:
randata = urandom(2*1024)
for i in xrange(0, 2*1024, 2):
yield int(hexlify(randata[i:i+2]),16)# integer 
in [0,65535]

self.rand2_M = rand2().next 


# modified from random._randbelow
def randrange(self,startN,stopN):

"""Choose a random integer from range(startN, stopN).
widthN<=65536

"""

widthN=stopN-startN


left_over_N=65536%widthN
upper_bound_N= 65535-left_over_N

random_number=self.rand2_M()

while random_number>upper_bound_N:

random_number=self.rand2_M()

r = random_number%widthN
   
return startN+r

def shuffle(self, x):
"""x, random=random.random -> shuffle list x in place; return 
None.

"""

randrange=self.randrange

for i in reversed(xrange(1, len(x))):
# pick an element in x[:i+1] with which to exchange x[i]
j = randrange(0,i+1)
x[i], x[j] = x[j], x[i]
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Re: Does shuffle() produce uniform result ?

[tooru honda]

Thanks to everyone who replied, (and special thanks to Alex Martelli,) I 
was able to accomplish what I originally asked for: a shuffle() which is 
both fast and without bias.  It is the first time I try to optimize 
python code, and it is definitely a very rewarding experience.


To bring closure to this thread, I will provide below some statistics 
obtained from cProfile:


1. using random.SystemRandom

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)

  4182879   35.1540.000  211.0060.000 os.py:724(urandom)
  4182879   31.9810.000  248.2910.000 random.py:767(random)
40578   17.9770.000  266.3000.007 random.py:250(shuffle)
  4182879   29.4870.000   29.4870.000 {posix.close}
  4182879   99.4600.000   99.4600.000 {posix.open}
  4182879   41.7940.000   41.7940.000 {posix.read}

2. my original optimization

 82680.1330.0002.5770.000 os.py:724(urandom)
  4134322   15.0940.000   21.6060.000 baccarat.py:70(get2bytes)
  4131441   17.2210.000   41.7220.000 baccarat.py:85(randrange)
405907.0590.000   48.7950.001 baccarat.py:112(shuffle)

3. using Alex's generator with string

 41170.0580.0002.0480.000 os.py:724(urandom)
  4214795   10.1860.000   14.8800.000 baccarat.py:93(rand2)
  42117908.8830.000   23.7630.000 baccarat.py:106(randrange)
407396.1010.000   29.8780.001 baccarat.py:131(shuffle)


4. using Alex's generator with array

 20810.0290.0001.7360.001 os.py:724(urandom)
  41615691.7240.0003.4730.000 baccarat.py:100(rand2new)
  41584748.3150.000   11.7880.000 baccarat.py:113(randrange)
405145.7260.000   17.5280.000 baccarat.py:138(shuffle)
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