If you want the indexes, check out the np.where command, e.g.
idx = np.where(dat <= limit)
If you want the values, use:
val = dat[dat <= limit]
Lane
Michael wrote:
Hi list,
been playing around with stride_tricks and find it terrifically
productive; thankyou to everyone who has worked on this.
I need to filter some data, getting the indices of all entries which are
less than or equal to 'limit'. How do i best go about that?
Can you enumerate an array using broadcasting?
dat=np.array([ 0. 1.61803399 3.23606798 4.85410197
6.47213595
8.09016994 9.70820393 11.32623792 12.94427191 14.5623059 1.
0.61803399 2.23606798 3.85410197 5.47213595 7.09016994
8.70820393 10.32623792 11.94427191 13.5623059 2.
0.38196601
1.23606798 2.85410197 4.47213595 6.09016994 7.70820393
9.32623792 10.94427191 12.5623059 3. 1.38196601
0.23606798 1.85410197 3.47213595 5.09016994 6.70820393
8.32623792 9.94427191 11.5623059 4. 2.38196601
0.76393202 0.85410197 2.47213595 4.09016994 5.70820393
7.32623792 8.94427191 10.5623059 5. 3.38196601
1.76393202 0.14589803 1.47213595 3.09016994 4.70820393
6.32623792 7.94427191 9.5623059 6. 4.38196601
2.76393202 1.14589803 0.47213595 2.09016994 3.70820393
5.32623792 6.94427191 8.5623059 7. 5.38196601
3.76393202 2.14589803 0.52786405 1.09016994 2.70820393
4.32623792 5.94427191 7.5623059 8. 6.38196601
4.76393202 3.14589803 1.52786405 0.09016994 1.70820393
3.32623792 4.94427191 6.5623059 9. 7.38196601
5.76393202 4.14589803 2.52786405 0.90983006 0.70820393
2.32623792 3.94427191 5.5623059 ])
limit=1.30901699437
for i in dat:
if i <=limit:
print i
Michael
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