Reputation: 407
I have an array (lists) which is NxK. However, I want to "filter" is after inputting some constraints based on values in Columns 4 and 6. This is the code I have so far.
minmag = 5
maxmag = 7
mindist = 25
maxdist = 64
filter = np.zeros((1, 7), dtype='object')
add = np.zeros((1, 7), dtype='object')
k = 0
for i in range(0,len(lists)):
if lists[i, 4]>= minmag and lists [i, 4] <= maxmag and lists [i, 6]>=mindist and lists [i, 6]<= maxdist:
if k == 0:
for x in range(0,16):
filter[0, x] = lists[i, x]
k = 1
else:
for x in range(0, 16):
add[0, x] = lists[i, x]
filter = np.append(filter, add, axis=0)
It works, however it is not so neat. Just wondering if anyone has a better solution.
Upvotes: 2
Views: 1841
Reputation: 49805
Simplifying the most repetitive parts:
if k==0:
for x in xrange(1,8):
lists[i,x] = filter[0,x]
k = 1
else:
for x in xrange(1,8):
lists[i,x] = add[0,x]
filter = np.append(filter, add, axis=0)
You could also combine your nested if
s into a single one with the 4 conditions combined with and
s.
I also believe (not seeing how lists
is defined, I'm not sure) you can replace the outer loop with
for row in lists:
and then use row[x]
in place of lists[i,x]
Upvotes: 1