What I want to do is take my current array and subtract the previous rows column value from the current rows column value. I also want to take the result and add it to the array as a new dimension.
Example Array:
[[1,2,4,7,9,15], [3, 4,3,5,10,2], [5,6,56,7,20,1]]
Lets say I want to do this with the 4th column so I want the output to be an array that looks like this:
[[1,2,4,7,9,15,0], [3, 4,3,5,10,2,-2], [5,6,56,7,20,1,2]]
Thanks
You can do this using a combination of np.diff
, and concatenate
options, like so:
import numpy as np
myarray = np.array([[1,2,4,7,9,15], [3, 4,3,5,10,2], [5,6,56,7,20,1]])
#your differences appears to be wraparound, so we repeat the last row at the top:
myarray_wrap = np.vstack((myarray[-1],myarray))
#this gets the diffs for all columns:
column_diffs = np.diff(myarray_wrap, axis=0)
#now we add in only the the column_diff that we want, at the end:
print np.hstack((myarray, column_diffs[:,3].reshape(-1,1)))
#Output:
[[ 1 2 4 7 9 15 0]
[ 3 4 3 5 10 2 -2]
[ 5 6 56 7 20 1 2]]
This Python code should solve your problem.
previous = None
for row in rows:
current = row[4]
row.append( 0 if previous == None else current - previous )
previous = current
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.