Is it possible to alias multiple names in a numpy record array? - numpy

Question

Suppose I construct a numpy record array like this
num_rows = <whatever>
data = np.zeros(
(num_rows,),
dtype={
'names':['apple', 'banana'],
'formats': ['f8', 'f8']
}
Now I can access data either by name or index.
For example, the following are the same:
data['banana'][0]
and
data[0]['banana']
etc.
Is there a way to alias different names?
For example, can I set things up so that there's another name manzana such that
data['manzana']
is the same thing as
data['apple']
?

Answer 1

['offsets' and 'titles' are 2 mechanisms for giving different names to fields]
There is an offset parameter that can function in this way. Usually it is used to split another field into several pieces (e.g. an int into bytes). But it also works with identical fields. In effect it defines several fields with overlapping data.
In [743]: dt=np.dtype({'names':['apple','manzana','banana','guineo'],
'formats':['f8','f8','f8','f8'],
'offsets':[0,0,8,8]})
In [745]: np.zeros((3,),dtype=dt)
Out[745]:
array([(0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 0.0, 0.0)],
dtype={'names':['apple','manzana','banana','guineo'],
'formats':['<f8','<f8','<f8','<f8'],
'offsets':[0,0,8,8], 'itemsize':16})
In [746]: A=np.zeros((3,),dtype=dt)
In [747]: A['banana']=[1,2,3]
In [748]: A
Out[748]:
array([(0.0, 0.0, 1.0, 1.0),
(0.0, 0.0, 2.0, 2.0),
(0.0, 0.0, 3.0, 3.0)],
dtype={'names':['apple','manzana','banana','guineo'], 'formats':['<f8','<f8','<f8','<f8'], 'offsets':[0,0,8,8], 'itemsize':16})
In [749]: A['guineo']
Out[749]: array([ 1., 2., 3.])
In [750]: A['manzana']=[.1,.2,.3]
In [751]: A['apple']
Out[751]: array([ 0.1, 0.2, 0.3])
In [752]: A
Out[752]:
array([(0.1, 0.1, 1.0, 1.0),
(0.2, 0.2, 2.0, 2.0),
(0.3, 0.3, 3.0, 3.0)],
dtype={'names':['apple','manzana','banana','guineo'], 'formats':['<f8','<f8','<f8','<f8'], 'offsets':[0,0,8,8], 'itemsize':16})
There's another dtype parameter, titles that is better suited to your needs, and easier to understand:
http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
In [792]: dt1=np.dtype({'names':['apple','banana'],'formats':['f8','f8'], 'titles':['manzana', 'guineo'], 'offsets':[0,8]})
In [793]: A1=np.zeros((3,),dtype=dt1)
In [794]: A1
Out[794]:
array([(0.0, 0.0), (0.0, 0.0), (0.0, 0.0)],
dtype=[(('manzana', 'apple'), '<f8'), (('guineo', 'banana'), '<f8')])
In [795]: A1['apple']=[1,2,3]
In [796]: A1['guineo']=[.1,.2,.3]
In [797]: A1
Out[797]:
array([(1.0, 0.1), (2.0, 0.2), (3.0, 0.3)],
dtype=[(('manzana', 'apple'), '<f8'), (('guineo', 'banana'), '<f8')])
In [798]: A1['banana']
Out[798]: array([ 0.1, 0.2, 0.3])

Answer 2

I have put the answer of #hpaulj into a simple method and share it here in case someone wants to use it.
def add_alias(arr, original, alias):
"""
Adds an alias to the field with the name original to the array arr.
Only one alias per field is allowed.
"""
if arr.dtype.names is None:
raise TypeError("arr must be a structured array. Use add_name instead.")
descr = arr.dtype.descr
try:
index = arr.dtype.names.index(original)
except ValueError:
raise ValueError("arr does not have a field named '" + str(original)
+ "'")
if type(descr[index][0]) is tuple:
raise ValueError("The field " + str(original) +
" already has an alias.")
descr[index] = ((alias, descr[index][0]), descr[index][1])
arr.dtype = np.dtype(descr)
return arr
def add_name(arr, name):
"""
Adds a name to the data of an unstructured array.
"""
if arr.dtype.names is not None:
raise TypeError("arr must not be a structured array. "
+ "Use add_alias instead.")
arr.dtype = np.dtype([(name, arr.dtype.name)])
return arr