Apologies if this has been asked many times before, but I'm having
trouble even coming up with the right terms to search on.
I have an x,y,date stack of satellite images from which I need to know
on what date the max and min values occur. I can calculate the index at
which the min/max values occur, but how do I join that back to the date?
A simple example case:
import numpy as np
#Date when image was captured,
#images are in the stack in this order
days=[10, 20, 31, 41, 51, 59, 69, 79, 90, 100]
#dummy array representing something like
#"stackofimages.argmin(axis=2)"
indexmin=np.array([[0, 2, 1],
[6, 7, 3],
[5, 5, 8]])
#I want to convert indexmin to "daymin" i.e
#[[10, 31, 20],
# [69, 79, 41],
# [59, 59, 90]]
#Where the each element of indexmin represent the value
#at the corresponding index in the days list/array.
#What I am currently doing is below,
#which is _rather_ slow on large arrays
#as I'm calling np.where len(days) times
daymin=np.zeros(indexmin.shape).astype(np.int)
for i,d in enumerate(days):
daymin[np.where(indexmin==i)]=d
Any better suggestions?
Regards
Luke Pinner
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