Skip to main content

Weave

Weave is a python module that includes a method of including C and C++ code inline with python. Has a slightly bigger overhead than the swig approach but is a lot easier to implement. And the code can be any dynamically created string. For example this block of python code calculates the fixed point multiplication of var1 and var2. The code is modified from a matlab algorithm worked on during my summer internship at Tait Electronics.

from scipy.weave import inline as inlineC

r = rounding and 1 or 0 # Blatent hack to convert from pythons True/False to 1/0 for C/C++

exp = """
signed int K,result;
signed long int temp;
temp = (long int)var1 * (long int)var2;
signed int sign = temp/abs(temp);
if(r) {
K = 1 << (numBits-1); temp = temp + K; } result = sign*(abs(temp) >> numBits);
if(result > fp_Max){
result = fp_Max;
}
if(result < result =" fp_Min;" return_val =" result;">

result = inlineC(exp,['var1','var2','numBits','fp_Min','fp_Max','r'])

It must be noted the C code is just a string to python, the string is then passed to scipy.weave.inline along with any variables required by the code. The only non standard piece of c is assigning return_val, this is set up by weave and can be assigned with any type to return into python. Also note the commented out printf statement in the C code – was very useful for debugging as it still outputs to standard out.

Weave is a quick and powerful way to include c code or optimize a bottleneck in an algorithm. The above example is probably to simple to get any speed up as its a very trivial problem and the overhead of calling C must be factored in. Weave is pretty awesome for when you have a loop in python you cannot get rid of that MUST go faster.

As with all optimization tho, ask yourself if you really need it?

Here is another example...

The original code:

from numpy import *
def
wastedLoop(n):

"""wastedLoop does alot of looping adding up the numbers 1 + 2 + ... N
wastedLoop(n) loops n times"""
p =
0

for
k in range(n+1):
p = p + k

print
p

Then at an ipython prompt do a quick timing test:

>>> %timeit wastedLoop(1000000)
10
loops, best of 3: 464 ms per loop

Ok so now lets use numpy functions instead of looping:

def numpySumMethod(n):
return
sum(arange(n+1))

>>> %timeit numpySumMethod(1000000)
100
loops, best of 3: 12.9 ms per loop
So we already have achieved a 35 times faster run time than the original. And have clearer code!

from scipy import weave
def
wastedLoop(n):
"""
wastedLoop does alot of looping adding up the numbers 1 + 2 + ... N

wastedLoop(n) loops n times

"""

p = int(0)

exp = """

int i;
for(i=0;i

weave.inline(exp,['p','n'])
return
p

%timeit wastedLoop(1000000)
10
loops, best of 3: 2.8 ms per loop



We see an improvement here but its not amazing... Just one more example, doing the same thing but with the knowledge about the problem. Using the algorithm:

def efficientMethod(n):
"""Return sum of 1+2+3...+N"""

return
n*(n+1)/2.0

>>> timeit efficientMethod(1000000)
1000000
loops, best of 3: 0.00000173 s per loop

And there we have it: 1.73┬Ás There is a lesson in that! A bit of math goes a long way! For the cases where you don't have insider knowledge however, it is clear numpy alone can suffice in most situations.

Stay tuned for a look at python extensions with swig.

P.S: What is with this editor for blogger? It is crap!!!

Popular posts from this blog

Driveby contribution to Python Cryptography

While at PyConAU 2016 I attended the Monday sprints and spent some time looking at a proposed feature I hoped would soon be part of cryptography. As most readers of this blog will know, cryptography is a very respected project within the Python ecosystem and it was an interesting experience to see how such a prominent open source project handles contributions and reviews.

The feature in question is the Diffie-Hellman Key Exchange algorithm used in many cryptography applications. Diffie-Helman Key Exchange is a way of generating a shared secret between two parties where the secret can't be determined by an eavesdropper observing the communication. DHE is extremely common - it is one of the primary methods used to provide "perfect forward secrecy" every time you initiate a TLS connection to an HTTPS website. Mathematically it is extremely elegant and the inventors were the recipients of the 2015 Turing award.

I wanted to write about this particular contribution because man…

My setup for downloading & streaming movies and tv

I recently signed up for Netflix and am retiring my headless home media pc. This blog will have to serve as its obituary. The box spent about half of its life running FreeNAS, and half running Archlinux. I’ll briefly talk about my experience with FreeNAS, the migration, and then I’ll get to the robust setup I ended up with.

The machine itself cost around $1000 in 2014. Powered by an AMD A4-7300 3.8GHz cpu with 8GB of memory. A SilverStone DS380 case is both functional, quiet and looks great. The hard drives have been updated over the last two years until it had a full compliment of 6 WD Green 4TiB drives - all spinning bits of metal though.

Initially I had the BSD based FreeNAS operating system installed. I had a single hard drive in its own ZFS pool for TV and Movies, and a second ZFS pool comprised of 5 hard drives for documents and photos.

FreeNAS is straight forward to use and setup, provided you only want to do things supported out of the box or by plugins. Each plugin is install…

Markdown Editor Component for Angular2

Thought I'd share a component I've been hacking on for angular2: a syntax highlighted markdown editor with rendered preview.

The code including a basic example is available on github. Because Angular2 hasn't yet been released this is really just me kicking the tyres.



This component relies on two libraries:

- marked for rendering markdown as html
- and ace editor for editing markdown
Basic Usage Example Add to your html template:
<markdown-editor (save)="updatedText($event)" [initial-text]="markdownContent"></markdown-editor> Remember to include the Markdowndirective in your @Component annotation:
@Component({ selector:'about', directives: [CORE_DIRECTIVES, Markdown] }) Another Example You can also control the component with external ui:
<button (click)="md.editMode = true">Custom Edit Button</button><markdown-editor [initial-text]="myMarkdownText" [show-edit-but…