dimanche 5 juin 2011

Structure-like object

I really like the structure variable in IDL. Especially the arrays of structure. It allows to search for elements using the where function and to extract a sub-structure matching a give condition.
I mean, if I have an dataset like this:
IDL> a = replicate({name:'',ra:0.0,dec:0.0},1000)
I can search for all the elements matching for exemple:
IDL> tt = where(a.ra gt 10. and abs(a.dec) gt 5.)
IDL> b = a[tt]

The same (more or less) can be made using numpy (imported as np):

a = np.zeros((1000,),dtype=[('name', str), ('ra', float), ('dec', float)])
tt = ((a['ra'] > 5.) & (abs(a['dec']) < 10.))
b = a[tt]

I don't really know if this is the best way. And also don't know how to access for example the second tag without naming it, like in IDL a.(1)...

I can also create an object:
class obs(object):
    def __init__(self,name='',ra=0.,dec=0.):
And even define an array of objects:
colec = np.empty( (3,3), dtype=object)
And then put the objects in the colec:
colec[:,:] = obs()
BUT this will create a collection of 9 times the same object!!!
colec[0,0].ra = 5.5
Some loop needed here. But the worst is that one will loose all the power of linear algebra from numpy.
So stay with the first approach for now.

1 commentaire:

  1. Your approach will work okay for many uses, but a better approach to my mind is to something like:
    a = np.recarray((1000,),dtype=...)
    then slices of a will also have a record type and you can fill a by statements like:
    a.ra = ra
    a1 = a[2]
    print a1.name