Numpy using smaller 2D array to map with bigger array with more elements

Question

I have a smaller array as:

A = np.array([2011, 2014, 2015, 2016, 2017])
Aval = np.array([14, 10, 35, 40, 45])

I have another array:

A2 = np.array([2013, 2014, 2015, 2014, 2015, 2016, 2016, 2016, 2017])

I want to create A2val such that:

Arval = np.array([10, 35, 10, 35, 40, 40, 40, 45])

so, I am trying to use the values in array A to map to elements of A2 and generate an extended version of A2val

Please note 2011 is present in A, 2013 is in A2 but not in A2 and A respectively. I can use the following suggested in another thread:

Aval[np.searchsorted(A,A2)]

But it doesn't produce the answer I am looking for.

Kasravnd · Accepted Answer · 2016-07-15 21:25:19Z

4

Here is one way:

>>> Aval[np.searchsorted(A, A2[np.nonzero(np.in1d(A2, A))[0]])]
array([10, 35, 10, 35, 40, 40, 40, 45])

Note that for getting the expected indices in default order the second array that you pass to searchsorted() should be contain the common items with first array.

edited Jul 15, 2016 at 21:25

answered Jul 15, 2016 at 21:04

Kasravnd

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Comments

akuiper · Accepted Answer · 2016-07-15 21:00:00Z

1

You can construct a dictionary from A and Aval and then loop through A2 and find out the corresponding values:

dic = dict(zip(A, Aval))
[dic.get(a) for a in A2 if dic.get(a) != None]
# [10, 35, 10, 35, 40, 40, 40, 45]

edited Jul 15, 2016 at 21:00

answered Jul 15, 2016 at 20:54

akuiper

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