I would like to take the information from some fields and just write them into another variable using a list.
import numpy as np
var1 = np.array([(1,2,3,4),(11,22,33,44),(111,222,333,444)], dtype=([('field1', 'int32'),('field2','int32'),('field3','int32'),('field4','int32')]))
var2 = np.empty((1), dtype = ([('field1', 'int32'),('field2','int32'),('field5','int32'),('field6','int32')]))
myList = ['field1', 'field2']
I want to write the values from the 1st and 2nd fields and 1st row to var2. I try the following:
var2[(myList)] = var1[(myList)][0]
But I get the following error:
IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
What I want to achieve the same if I perform:
var2['field1'] = var1['field1'][0]
var2['field2'] = var1['field2'][0]
How could I do this in order to able to perform this with higher lists avoiding a for loop over the list?
A list of fields works for fetching a subset of the fields
In [139]: var1[myList]
Out[139]:
array([(1, 2), (11, 22), (111, 222)],
dtype=[('field1', '<i4'), ('field2', '<i4')])
but not when used on the left side as a 'setter' (this may be an area of development).
In [138]: var2[myList]= var1[myList]
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-138-570d16e71a2e> in <module>()
----> 1 var2[myList]= var1[myList]
IndexError: unsupported iterator index
So you need to iterate on the fields.
for name in myList:
var2[name] = var1[name][0]
Iterating on field names is common practice in structured array code (as in np.rec functions). Typically a structured array will have many elements ('rows') but a few fields ('columns'), so iteration over fields is not expensive.
In this case, all fields of var2 are the same int dtype. So I can perform the assignment on the corresponding 2d view
In [160]: var2.view(int)[:2] = var1[myList][0].tolist()
var2 data buffer is all ints, so it can be viewed either as fields or a regular array (2d or 1).
var2.view(int)[:2] = var1[myList][0] assigns var1['field1'][0] to both items of var2. So I have to make it into a list or tuple.
Alternatively I can view var1 as well. With this I found I need to reshape as well. The view produces a 1d array view of the buffer.
var2.view(int)[:2]=var1.view(int).reshape((3,4))[0,:2]
Multifield assignment is under development, but I don't think it is in the official release yet. https://github.com/numpy/numpy/pull/6053
var1.view(int).reshape((3,4)) # or
var1.view(int).reshape((-1,4))
can also be expressed as:
var1.view((int,4))
(the compound view is more compact, though not any faster).
