So I have an array I am trying to slice and index using two other boolean arrays and then set a value on that subset of the array. I saw this post: Setting values in a numpy arrays indexed by a slice and two boolean arrays
and suspect I am getting a copy instead of a view of my array so it isn't saving the values I am setting on the array. I think I managed to reproduce the problem with a much shorter code, but am a very out of my depth.
#first array
a = np.arange(0,100).reshape(10,10)
#conditional array of same size
b = np.random.rand(10,10)
b = b < 0.8
#create out array of same size as a
out = np.zeros(a.shape)
#define neighborhood to slice values from
nhood = tuple([slice(3,6),slice(5,7)])
#define subset where b == True in neighborhood
subset = b[nhood]
#define values in out that are in the neighborhood but not excluded by b
candidates = out[nhood][subset]
#get third values from neighborhood using math
c = np.random.rand(len(candidates))
#this is in a for loop so this is checking to see a value has already been changed earlier - returns all true now
update_these = candidates < c
#set sliced, indexed subset of array with the values from c that are appropriate
out[nhood][subset][update_these] = c[update_these]
print(out) ##PRODUCES - ARRAY OF ALL ZEROS STILL
I have also tried chaining the boolean index with
out[nhood][(subset)&(update_these)] = c[update_these]
But that made an array of the wrong size.
Help?
out[nhood][subset].nhoodis a slice, and produces aview, but[subset]is boolean indexing, and produces a 1d copy.out[nhood][subset]=...can set those values. But you can't use the added[update_these]layer of indexing.cis one-dimensional array,update_thisis a 10-by-10 boolean mask. Therefore,c[update_this]is not compatible. You can reshapecor write a loop to determine which entries to consider.out[nhood][subset]and then use boolean indexing to change that copy and that edit the original out dataframe. I suspect there is a smoother way to do that, but it seems to be working?