Starting from a simple array with duplicate values:
a = np.array([2,3,2,2,3,3,2,1])
I'm trying to select a maximum of 2 unique values from this. The resulting array would appear as:
b = np.array([2,3,2,3,1])
no matter the order of the items. So far I tried to find unique values with:
In [20]: c = np.unique(a,return_counts=True)
In [21]: c
Out[21]: (array([1, 2, 3]), array([1, 4, 3]))
which is useful because it returns the frequency of values as well, but I'm stucked in filtering by frequency.
You can use a list comprehension within np.concatenate() and limit the number of items by slicing:
>>> np.concatenate([a[a==i][:2] for i in np.unique(a)])
array([1, 2, 2, 3, 3])
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