Getting Attributes From Arrays Of Objects In Numpy

Let's say I have an class called Star which has an attribute color. I can get color with star.color. But what if I have a NumPy array of these Star objects. What is the preferred w

Solution 1:

The closest thing to what you want is to use a recarray instead of an ndarray of Python objects:

num_stars = 10
dtype = numpy.dtype([('x', float), ('y', float), ('colour', float)])
a = numpy.recarray(num_stars, dtype=dtype)
a.colour = numpy.arange(num_stars)
print a.colour

prints

[ 0.  1.  2.  3.  4.  5.  6.  7.  8.  9.]

Using a NumPy array of Python objects usually is less efficient than using a plain list, while a recarray stores the data in a more efficient format.

Solution 2:

You could use numpy.fromiter(s.color for s in stars) (note lack of square brackets). That will avoid creating the intermediate list, which I imagine you might care about if you are using numpy.

(Thanks to @SvenMarnach and @DSM for their corrections below).

Solution 3:

In case star is a more complicated class, here is an approach to get and set the attributes with a helper class on top.

import numpy as np

classstar:
    def__init__(self, mass=1, radius=1):
        self.mass = mass
        self.radius = radius

classStars(list):

    __getattr__ = lambda self, attr: np.array([getattr(s, attr) for s in self])

    def__setattr__(self, attr, vals):
        ifhasattr(vals, '__len__'):
            [s.__setattr__(attr, val) for (s,val) inzip(self,vals)]
        else:
            [s.__setattr__(attr, vals) for s in self]


s1 = star(1, 1.1)
s2 = star(2, 3)

S = Stars([s1, s2])

print(S.mass)
print(S.radius)

S.density = S.mass / S.radius**3print(S.density)
print(s1.density)

Of course, if the class can be reimplemented into a recarray, it should be more efficient. Yet, such a reimplementaion might be undesirable.

Note, outer computations, like the density calculation, are still vectorised. And often those could be bottleneck, rather than setting and getting attributes.