array manipulation without for loops
Sheldon
shejo284 at gmail.com
Sun Jun 25 20:54:40 CEST 2006
The following script (using your function) raised no exception so it
worked! Elegant Alex, thanx.
res = equalize_arrays(msgtmp,ppstmp,255) # class
(ppstmp,msgtmp) = res.equalize() # class method
for i in range(int(main.xsize)):
for j in range(int(main.ysize)):
if msgtmp[i,j] == 255 and ppstmp[i,j] != 255:
raise "equalize error!"
if ppstmp[i,j] == 255 and msgtmp[i,j] != 255:
raise "equalize error!"
I read up on the putmask function and I don't understand this part:
>>> print x
[10 1 30 3 50]
>>> putmask(x, [1,0,1,0,1], [-1,-2])
>>> print x
[-1 1 -1 3 -1]
Can you explain why the -2 didn't factor in?
/Sheldon
Sheldon wrote:
> Hi Alex,
>
> I will code this in a little while and get back to you. Terrific! I saw
> this function but I skipped over it without realizing what it could do.
>
> The Numeric doc is not very good and I am just getting into Python so
> your book sounds great especially since it covers Numeric. I will look
> into it when I get back to work tomorrow.
>
> Bye for now,
> Sheldon
>
> Alex Martelli wrote:
>
> > Sheldon <shejo284 at gmail.com> wrote:
> >
> > > Alex,
> > >
> > > I am using Numeric and have created 3 arrays: zero((1215,1215),Float)
> > > Two arrays are compared and one is used to hold the mean difference
> > > between the two compared arrays. Then I compare 290 or 340 pairs of
> > > arrays. I know that memory is a problem and that is why I don't open
> > > all of these arrays at the same time. I cannot install Numpy due to my
> > > working conditions. Sorry I should have made it clear that is was
> > > Numeric I was working with.
> >
> > It's OK, even if the hard-core numeric-python people are all
> > evangelizing for migration to numpy (for reasons that are of course
> > quite defensible!), I think it's quite OK to stick with good old Numeric
> > for the moment (and that's exactly what I do for my own personal use!).
> >
> > So, anyway, I'll assume you mean your 1215 x 1215 arrays were created by
> > calling Numeric.zeros, not "zero" (with no trailing s) which is a name
> > that does not exists in Numeric.
> >
> > Looking back to your original post, let's say that you have two such
> > arrays, a and b, both 1215x1215 and of Numeric.Float type, and the
> > entries of each array are all worth 1, 2, or 255 (that's how I read your
> > original post; if that's not the case, please specify). We want to
> > write a function that alters both a and b, specifically setting to 255
> > all entries in each array whose corresponding entries are 255 in the
> > other array.
> >
> > Now that's pretty easy -- for example:
> >
> > import Numeric
> >
> > def equalize(a, b, v=255):
> > Numeric.putmask(a, b==v, v)
> > Numeric.putmask(b, a==v, v)
> >
> > if __name__ == '__main__':
> > a = Numeric.zeros((5,5), Numeric.Float)
> > b = Numeric.zeros((5,5), Numeric.Float)
> > a[1,2]=a[2,1]=b[3,4]=b[0,2]=255
> > a[3,0]=a[0,0]=1
> > b[0,3]=b[4,4]=2
> > print "Before:"
> > print a
> > print b
> > equalize(a, b)
> > print "After:"
> > print a
> > print b
> >
> >
> > brain:~/pynut alex$ python ab.py
> > Before:
> > [[ 1. 0. 0. 0. 0.]
> > [ 0. 0. 255. 0. 0.]
> > [ 0. 255. 0. 0. 0.]
> > [ 1. 0. 0. 0. 0.]
> > [ 0. 0. 0. 0. 0.]]
> > [[ 0. 0. 255. 2. 0.]
> > [ 0. 0. 0. 0. 0.]
> > [ 0. 0. 0. 0. 0.]
> > [ 0. 0. 0. 0. 255.]
> > [ 0. 0. 0. 0. 2.]]
> > After:
> > [[ 1. 0. 255. 0. 0.]
> > [ 0. 0. 255. 0. 0.]
> > [ 0. 255. 0. 0. 0.]
> > [ 1. 0. 0. 0. 255.]
> > [ 0. 0. 0. 0. 0.]]
> > [[ 0. 0. 255. 2. 0.]
> > [ 0. 0. 255. 0. 0.]
> > [ 0. 255. 0. 0. 0.]
> > [ 0. 0. 0. 0. 255.]
> > [ 0. 0. 0. 0. 2.]]
> > brain:~/pynut alex$
> >
> > Of course I'm using tiny arrays here, for speed of running and ease of
> > display and eyeball-checking, but everything should work just as well in
> > your case. Care to check and let us know?
> >
> > Numeric has pretty good documentation (numpy's is probably even better,
> > but it is not available for free, so I don't know!), and if you don't
> > find that documentation sufficient you might want to have a look to my
> > book "Python in a Nutshell" which devotes a chapter to Numeric (it also
> > is not available for free, but you can get a subscription to O'Reilly's
> > Safari online-books repository, which is free for the first two weeks,
> > and lets you look at many books including Python in a Nutshell -- if you
> > don't want to pay monthly subscription fees, make sure you cancel your
> > trial subscription before two weeks have passed!!!).
> >
> > I strongly recommend that, in some way or other, you DO get a taste of
> > the huge amount of functionality that Numeric provides for you -- with
> > the size of computational tasks you're talking about, an investment of
> > 2-3 hours spent becoming deeply familiar with everything Numeric offers
> > may well repay itself in savings of ten times as much execution time,
> > and what other investments offer such ROI as 1000%?-)
> >
> >
> > Alex
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