How can I assign slices of one structured Numpy array to another? - arrays

Question

I have two numpy structured arrays arr1, arr2.
arr1 has fields ['f1','f2','f3'].
arr2 has fields ['f1','f2','f3','f4'].
I.e.:
arr1 = [[f1_1_1, f2_1_1, f3_1_1 ], arr2 = [[f1_2_1, f2_2_1, f3_2_1, f4_2_1 ],
[f1_1_2, f2_1_2, f3_1_2 ], [f1_2_2, f2_2_2, f3_2_2, f4_2_2 ],
... , ... ,
[f1_1_N1, f2_1_N1, f3_1_N1]] [f1_2_N2, f2_2_N2, f3_2_N2, f4_2_N2]]
I want to assign various slices of arr1 to the corresponding slice of arr2 (slices in the indexes and in the fields).
See below for the various cases.
From answers I found (to related, but not exactly the same, questions) it seemed to me that the only way to do it is assigning one slice at a time, for a single field, i.e., something like
arr2['f1'][0:1] = arr1['f1'][0:1]
(and I can confirm this works), looping over all source fields in the slice.
Is there a way to assign all intended source fields in the slice at a time?
I mean to assign, say, the elements x in the image
Case 1 (only some fields in arr1)
arr1 = [[ x , x , f3_1_1 ], arr2 = [[ x , x , f3_2_1, f4_2_1 ],
[ x , x , f3_1_2 ], [ x , x , f3_2_2, f4_2_2 ],
... , ... ,
[f1_1_N1, f2_1_N1, f3_1_N1]] [f1_2_N2, f2_2_N2, f3_2_N2, f4_2_N2]]
Case 2 (all fields in arr1)
arr1 = [[ x , x , x ], arr2 = [[ x , x , x , f4_2_1 ],
[ x , x , x ], [ x , x , x , f4_2_2 ],
... , ... ,
[f1_1_N1, f2_1_N1, f3_1_N1]] [f1_2_N2, f2_2_N2, f3_2_N2, f4_2_N2]]
Case 3
arr1 has fields ['f1','f2','f3','f5'].
arr2 has fields ['f1','f2','f3','f4'].
Assign a slice of ['f1','f2','f3']
Sources:
Python Numpy Structured Array (recarray) assigning values into slices
Convert a slice of a structured array to regular NumPy array in NumPy 1.14

Answer 1

You can do it for example like that:
import numpy as np
x = np.array([('Rex', 9, 81.0), ('Fido', 3, 27.0)], dtype=[('name', 'U10'), ('age', 'i4'), ('weight', 'f4')])
y = np.array([('Carl', 10, 75.0), ('Joe', 7, 76.0)], dtype=[('name2', 'U10'), ('age2', 'i4'), ('weight', 'f4')])
print(x[['name', 'age']])
print(y[['name2', 'age2']])
# multiple field indexing
y[['name2', 'age2']] = x[['name', 'age']]
print(y[['name2', 'age2']])
# you can also use slicing if you want specific parts or the size does not match
y[:1][['name2', 'age2']] = x[1:][['name', 'age']]
print(y[:][['name2', 'age2']])
The names field names can be different, I am not sure about the dtypes and if there is (down)casting.
https://docs.scipy.org/doc/numpy/user/basics.rec.html#assignment-from-other-structured-arrays
https://docs.scipy.org/doc/numpy/user/basics.rec.html#accessing-multiple-fields