speed of python vs matlab.

**Gabriel Genellina** · Dec 14 '06, 10:25 PM

Re: speed of python vs matlab.

At Wednesday 13/12/2006 21:07, Chao wrote:

>I've been trying to develop some numerical codes with python, however
>got disappointed.
>
>A very simple test,
>
>a = 1.0
>
>for i in range(1000):
for j in range(1000):
a = a+1
>
>unfortunatel y, it took 4.5 seconds to finish(my machines is fine. P4
>3.0G, 1G RAM, it varies according to machine configuration, but should
>be in the same level)

How do you measure it? 4.5 secs is far too much. Anyway, try using
xrange instead of range. This is the standard way to do timings:

--- cut ---
def test():
a = 1.0
for i in xrange(1000):
for j in xrange(1000):
a = a+1

if __name__=='__ma in__':
from timeit import Timer
t = Timer("test()", "from __main__ import test")
print t.repeat(repeat =3,number=1)
--- cut ---

I got about 0.24 secs with far less hardware.

For vector-oriented operations the NumArray package is well suited.

--
Gabriel Genellina
Softlab SRL

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**Andrew Sackville-West** · Dec 14 '06, 10:25 PM

Re: speed of python vs matlab.

On Wed, Dec 13, 2006 at 04:07:20PM -0800, Chao wrote:

I've been trying to develop some numerical codes with python, however
got disappointed.

A very simple test,

a = 1.0

for i in range(1000):
for j in range(1000):
a = a+1

unfortunately, it took 4.5 seconds to finish(my machines is fine. P4
3.0G, 1G RAM, it varies according to machine configuration, but should
be in the same level)

somethings not right there.

andrew@debian:~ $ cat pytimetest.py
a=1.0
for i in range (1000):
for j in range (1000):
a=a+1

andrew@debian:~ $ time python pytimetest.py

real 0m0.534s
user 0m0.528s
sys 0m0.000s

andrew@debian:~ $ cat /proc/cpuinfo | grep name
model name : Intel(R) Celeron(R) CPU 2.53GHz

andrew@debian:~ $ uname -a
Linux debian 2.6.18-3-686 #1 SMP Mon Dec 4 16:41:14 UTC 2006 i686
GNU/Linux

A

-----BEGIN PGP SIGNATURE-----
Version: GnuPG v1.4.6 (GNU/Linux)

iD8DBQFFgKK8aIe IEqwil4YRAt8uAK CoEAZAZpIpv8aQ9 JVNDls5yVBH5gCe L4WD
/48x4VpPTrW06O3j jQxSnV0=
=81y7
-----END PGP SIGNATURE-----

**Chao** · Dec 14 '06, 10:25 PM

Re: speed of python vs matlab.

My Bad, the time used by python is 0.46~0.49 sec,
I tried xrange, but it doesn't make things better.

import time
tic = time.time()
a = 1.0

array = range(1000)

for i in array:
for j in array:
a = a + 0.1

toc = time.time()
print toc-tic,' has elapsed'

used by matlab is 0.012sec

tic
a = 1;
for i=1:1000
for j=1:1000
a = a + 1;
end
end
toc

used by ruby is 0.94~0.96sec

a = 1
start = Time.now()

1000.times do
1000.times do
a = a + 1
end
end

finish = Time.now()

puts finish - start

Andrew Sackville-West wrote:

On Wed, Dec 13, 2006 at 04:07:20PM -0800, Chao wrote:

I've been trying to develop some numerical codes with python, however
got disappointed.

A very simple test,

a = 1.0

for i in range(1000):
for j in range(1000):
a = a+1

unfortunately, it took 4.5 seconds to finish(my machines is fine. P4
3.0G, 1G RAM, it varies according to machine configuration, but should
be in the same level)

>
somethings not right there.
>
andrew@debian:~ $ cat pytimetest.py
a=1.0
for i in range (1000):
for j in range (1000):
a=a+1
>
>
andrew@debian:~ $ time python pytimetest.py
>
real 0m0.534s
user 0m0.528s
sys 0m0.000s
>
>
andrew@debian:~ $ cat /proc/cpuinfo | grep name
model name : Intel(R) Celeron(R) CPU 2.53GHz
>
andrew@debian:~ $ uname -a
Linux debian 2.6.18-3-686 #1 SMP Mon Dec 4 16:41:14 UTC 2006 i686
GNU/Linux
>
A
>
--7AUc2qLy4jB3hD7 Z
Content-Type: application/pgp-signature
Content-Disposition: inline;
filename="signa ture.asc"
Content-Description: Digital signature
X-Google-AttachSize: 190

**Jonathan Curran** · Dec 14 '06, 10:25 PM

Re: speed of python vs matlab.

On Wednesday 13 December 2006 18:07, Chao wrote:

I've been trying to develop some numerical codes with python, however
got disappointed.
>
A very simple test,
>
a = 1.0
>
for i in range(1000):
for j in range(1000):
a = a+1
>
unfortunately, it took 4.5 seconds to finish(my machines is fine. P4
3.0G, 1G RAM, it varies according to machine configuration, but should
be in the same level)
>
for matlab, the same operation took 0.1 seconds,
>
I use numpy & scipy, they solve the problem most of the times, but
there are cases you can't avoid loops by vectors. I appreciate the
elegancy of python so much, but I guess I have to gave it up in these
numerical codes.(image processing algorithms), for application
dev/scripting, it's still my first choice.
>
A good news is that the same code takes ruby 9.8 seconds.

[icicled@A3200 ~]$ time python foo # where foo contained your exact code

real 0m0.469s
user 0m0.443s
sys 0m0.017s

4.5 seconds? ouch. I've got somewhere near 1 second. Something sounds a little
fishy b/c my machine is an AMD 3200+ (2.2GHz) w/ 1GB RAM. Yours is a lot
faster in terms of clock speed.

Anyway, do take a look at some of the available python compilers. They should
help considerably.

- Jonathan

**Christophe** · Dec 14 '06, 10:26 PM

Re: speed of python vs matlab.

Chao a écrit :

My Bad, the time used by python is 0.46~0.49 sec,
I tried xrange, but it doesn't make things better.
>
import time
tic = time.time()
a = 1.0
>
array = range(1000)
>
for i in array:
for j in array:
a = a + 0.1
>
toc = time.time()
print toc-tic,' has elapsed'

Place all your code inside functions please. IIRC, local variable access
is much faster that way, and you do a lot of lookup for the a local
variable in that code.

import time

def main():
a = 1.0

array = range(1000)

for i in array:
for j in array:
a = a + 0.1

tic = time.time()
main()
toc = time.time()
print toc-tic,' has elapsed'

**Roberto Bonvallet** · Dec 14 '06, 10:26 PM

Re: speed of python vs matlab.

Chao wrote:

My Bad, the time used by python is 0.46~0.49 sec,
I tried xrange, but it doesn't make things better.

Actually it does: it doesn't waste time and space to create a big list.

--
Roberto Bonvallet

**bearophileHUGS@lycos.com** · Dec 14 '06, 10:26 PM

Re: speed of python vs matlab.

Chao, you can also try Psyco, applied on functions, and when necessary
using its metaclass too.

Bye,
bearophile

**Chao** · Dec 14 '06, 10:26 PM

Re: speed of python vs matlab.

Thank you guys for your interest,

I tried two things 1) put code into a function 2) use psyco.

1) by putting them into a function, there is a significant improvement,
around 30%
the running time will be around 0.3sec

2) by using psyco, it really does a great job, the running time is
around 0.045sec.

While trying this another question comes up,
psyco seems to be able to optimize built-in functions & user's code, if
I call a function from an external library, it seems doesn't help.
A simple thing is I placed a = numpy.sin(a) in the loop rather than a =
a+1, in this case,
psyco doesn't have any improvement(or very little). if I put a =
math.sin(a) which is from an built-in function, it can achieve a
improvement around 3~4. Could the reason be that numpy.sin is
actually calling a C library ?

Actually Python does show comparable/better performance than other
scripting languages. but I'm just surprised that matlab does a great
job compared to python/perl, since matlab is also a interpreted
language, I'm expecting it has silimar performance with python.

I did some search, in previous discussion, people has compared
python/numpy vs matlab,
but it is actually comparison between numpy(which is implemented in c)
vs matlab.

Chao.

import psyco
#psyco.bind(fun ctest)
psyco.full()

import numpy
import time,math

def functest(a):
array = xrange(1000)

for i in array:
for j in array:
a = a + 1

tic = time.time()

a = 1.0
functest(a)

toc = time.time()
print toc-tic,' has elapsed'

bearophileHUGS@ lycos.com wrote:

Chao, you can also try Psyco, applied on functions, and when necessary
using its metaclass too.
>
Bye,
bearophile

**Robert Kern** · Dec 14 '06, 10:26 PM

Re: speed of python vs matlab.

Chao wrote:

While trying this another question comes up,
psyco seems to be able to optimize built-in functions & user's code, if
I call a function from an external library, it seems doesn't help.
A simple thing is I placed a = numpy.sin(a) in the loop rather than a =
a+1, in this case,
psyco doesn't have any improvement(or very little). if I put a =
math.sin(a) which is from an built-in function, it can achieve a
improvement around 3~4. Could the reason be that numpy.sin is
actually calling a C library ?

The reason for the difference is that psyco recognizes math.sin() and replaces
it with equivalent machine code to call the standard C library function sin().
It does not recognize numpy.sin(), and it is implemented in C, not Python, so it
does not do optimization.

Actually Python does show comparable/better performance than other
scripting languages. but I'm just surprised that matlab does a great
job compared to python/perl, since matlab is also a interpreted
language, I'm expecting it has silimar performance with python.

Matlab uses a JIT compiler along the lines of psyco for simple operations like
the one you are doing.

--
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco

**greg** · Dec 15 '06, 06:35 AM

Re: speed of python vs matlab.

Chao wrote:

I did some search, in previous discussion, people has compared
python/numpy vs matlab,
but it is actually comparison between numpy(which is implemented in c)
vs matlab.

Yes, matlab is operating on whole arrays at a time,
like numpy. So it's not surprising that they have
comparable performance.

--
Greg

speed of python vs matlab.

speed of python vs matlab.

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