Thanks to Tim and Chris. Just what I was looking for!
I tested both along with some other tries that I had made.
For 10000 points -
G:\GPS\Python\GUI_Test\Filter>speed.py
time for <function listComp at 0x007AE4D8> is 0.022809
time for <function arraykludge at 0x0092AFF0> is 0.060303
time for <function arrayComp at 0x0092AFB0> is 0.055692
time for <function arrayTimH at 0x0092B030> is 0.003652
time for <function arrayChrisB at 0x0092B070> is 0.003561
For 100 points -
G:\GPS\Python\GUI_Test\Filter>speed.py
time for <function listComp at 0x007AE4D8> is 0.000238
time for <function arraykludge at 0x00804BD8> is 0.000784
time for <function arrayComp at 0x00804B98> is 0.000678
time for <function arrayTimH at 0x00804C18> is 0.000376
time for <function arrayChrisB at 0x00804C58> is 0.000153
They scale slightly differently between Tim's and Chris' methods.
Thanks again,
Gordon Williams
Here is the code (since someone will ask):
'''Test the speed of different methods of getting points out of a list'''
import time
import Numeric as n
size= 100
maxNum=size/10.
#data
a= n.array(n.arange(0,maxNum,.05))
a.shape= (size,2)
#list
l= a.tolist()
(xMin,yMin)= (3,2)
(xMax,yMax)= (4,6)
def listComp(seq):
'''using list comprehension'''
return [(x,y) for x,y in seq if xMin < x <xMax and yMin< y <yMax]
def arrayComp(seq):
'''using list comprehension'''
return n.array([(x,y) for x,y in seq if xMin < x <xMax and yMin< y
<yMax])
def arraykludge(seq):
'''using numeric stuff'''
res= n.copy.deepcopy(seq)
i=0 #index
for x,y in seq:
if xMin < x <xMax and yMin< y <yMax:
res[i]= [x,y]
i+=1
return res[:i]
def arrayTimH(seq):
'''using Tim Hochberg suggestions'''
cond = (xMin < seq[:,0]) & (seq[:,0] < xMax) & (yMin < seq[:,1]) &
(seq[:,1] < yMax)
return n.compress(cond, seq, 0)
def arrayChrisB(seq):
'''using Chris Barker suggestions'''
valid = (seq[:,0] > xMin) & (seq[:,0] < xMax) & (seq[:,1] > yMin) &
(seq[:,1] < yMax)
return n.take(a,n.nonzero(valid))
#Tests
tests= [(listComp,l), (arraykludge,a),(arrayComp,a), (arrayTimH,a),
(arrayChrisB,a)]
for fun,seq in tests:
t=time.clock()
apply(fun,(seq,))
dt= time.clock()-t
print "time for %s is %f" %(str(fun),dt)
----- Original Message -----
From: "Gordon Williams" <g_...@cy...>
To: <num...@li...>
Sent: Thursday, February 27, 2003 2:05 PM
Subject: filtering numeric arrays
> Hi All,
>
> I have an 2D numeric array of x,y points eg [(1,3),(2,4),(5,6)] and I
would
> like to remove all the points in the array that don't meet the min/max
point
> criteria. I will have several thousand points. With lists I can do it
like
>
> [(x,y) for x,y in seq if xMin < x <xMax and yMin< y <yMax]
>
> How do I get the same functionality and better speed using numeric. I
have
> tried a bunch of things using compress and take but I am running up
against
> a brick wall.
>
>
> Any ideas?
>
> Thanks
>
> Gordon Williams
>
>
>
>
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