jjrbfi
I used image_int[::8]
That works but I have to do it in a for loop
Hey,
wanted to ask here before opening an issue.
Is there a numpy function to get the Pooled Standard Deviation
?
as shown here
https://www.statisticshowto.com/pooled-standard-deviation/
Hi friend, I'm trying to fit postgresql max CUBE by reducing numpy nd array, but the results are not as expected
the code for reducing dimension :
pca = PCA(1)
feature = feature.reshape(-1, 1)
feature = pca.fit_transform(feature)
i think the code still wrong and do not reduce the "feature" dimension
.93/np.exp(-20*10**3/(1.98*373))
some_numpy_array[:] = some_iterable
andsome_numpy_array[...] = some_iterable
, for a 1D array?
[...]
refers to "all axes" while [:]
means the first axis, which is the same in this case :)
axis=(-2, -1)
. :facepalm: