Discussion of Numerical Python

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Dinesh B Vadhia | 11 Feb 21:56

Want to eliminate direct for-loop

Could the following be written without the direct for-loop?

import numpy
# numpy vector r of any data type and length, eg.

r = numpy.ones(25, dtype='int')
# s is a list of values (of any data type), eg.
s = [47, 27, 67]

# c is a list of (variable length) lists where the sub-list elements are index values of r and len(s) = len(c), eg.

c = [[3, 6, 9], [6, 11, 19, 24], [4, 9, 11, 21 ]]
# for each element in each sub-list c, add corresponding s value to the index value in r, eg.

for i, j in enumerate(c):
r[j] += s[i]

So, we get:

r[[3, 6, 9]] += s[0] = 1 + 47 = 48
r[[6, 11, 19, 24]] += s[1] = 1 + 27 = 28
r[[4, 9, 11, 21]] += s[2] = 1 + 67 = 68

ie. r = array([ 1, 1, 1, 95, 68, 1, 122, 1, 1, 162, 1, 95, 1, 1, 1, 1, 1, 1, 1, 28, 1, 68, 1, 1, 28])

Thank-you!

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eat | 12 Feb 00:12

Re: Want to eliminate direct for-loop

Hi,

On Sat, Feb 11, 2012 at 10:56 PM, Dinesh B Vadhia <dineshbvadhia <at> hotmail.com> wrote:

Could the following be written without the direct for-loop?

import numpy
# numpy vector r of any data type and length, eg.

r = numpy.ones(25, dtype='int')
# s is a list of values (of any data type), eg.
s = [47, 27, 67]

# c is a list of (variable length) lists where the sub-list elements are index values of r and len(s) = len(c), eg.

c = [[3, 6, 9], [6, 11, 19, 24], [4, 9, 11, 21 ]]
# for each element in each sub-list c, add corresponding s value to the index value in r, eg.

for i, j in enumerate(c):
r[j] += s[i]

So, we get:

r[[3, 6, 9]] += s[0] = 1 + 47 = 48
r[[6, 11, 19, 24]] += s[1] = 1 + 27 = 28
r[[4, 9, 11, 21]] += s[2] = 1 + 67 = 68

ie. r = array([ 1, 1, 1, 95, 68, 1, 122, 1, 1, 162, 1, 95, 1, 1, 1, 1, 1, 1, 1, 28, 1, 68, 1, 1, 28])

Thank-you!

Could you describe more detailed manner about why you want to get rid of that loop? Performance wise? If so, do you have profiled what's the bottleneck?

Please provide also a more detailed description of your problem, since now your current spec seems to yield:

r= array([ 1, 1, 1, 48, 68, 1, 75, 1, 1, 115, 1, 95, 1,

1, 1, 1, 1, 1, 1, 28, 1, 68, 1, 1, 28])

My 2 cents,

-eat

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NumPy-Discussion <at> scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion

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Dinesh B Vadhia | 12 Feb 01:04

Re: Want to eliminate direct for-loop

Sorry, I copy and pasted the wrong example r result - it should be as you say:

r = array([ 1, 1, 1, 48, 68, 1, 75, 1, 1, 115, 1, 95, 1, 1, 1, 1, 1, 1, 1, 28, 1, 68, 1, 1, 28])

The reason for looking for an alternative solution is performance as the sizes of r, s and c are very large with the for-loop calculation repeated continuously (with different r, s and c).

From: eat

Sent: Saturday, February 11, 2012 3:12 PM

To: Discussion of Numerical Python

Subject: Re: [Numpy-discussion] Want to eliminate direct for-loop

Hi,

On Sat, Feb 11, 2012 at 10:56 PM, Dinesh B Vadhia <dineshbvadhia <at> hotmail.com> wrote:

Could the following be written without the direct for-loop?

import numpy
# numpy vector r of any data type and length, eg.

r = numpy.ones(25, dtype='int')
# s is a list of values (of any data type), eg.
s = [47, 27, 67]

# c is a list of (variable length) lists where the sub-list elements are index values of r and len(s) = len(c), eg.

c = [[3, 6, 9], [6, 11, 19, 24], [4, 9, 11, 21 ]]
# for each element in each sub-list c, add corresponding s value to the index value in r, eg.

for i, j in enumerate(c):
r[j] += s[i]

So, we get:

r[[3, 6, 9]] += s[0] = 1 + 47 = 48
r[[6, 11, 19, 24]] += s[1] = 1 + 27 = 28
r[[4, 9, 11, 21]] += s[2] = 1 + 67 = 68

ie. r = array([ 1, 1, 1, 95, 68, 1, 122, 1, 1, 162, 1, 95, 1, 1, 1, 1, 1, 1, 1, 28, 1, 68, 1, 1, 28])

Thank-you!

Could you describe more detailed manner about why you want to get rid of that loop? Performance wise? If so, do you have profiled what's the bottleneck?

Please provide also a more detailed description of your problem, since now your current spec seems to yield:

r= array([ 1, 1, 1, 48, 68, 1, 75, 1, 1, 115, 1, 95, 1,

1, 1, 1, 1, 1, 1, 28, 1, 68, 1, 1, 28])

My 2 cents,

-eat

_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion <at> scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion

_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion <at> scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion