list of custom class converted to numpy array

Question

I have such a class

class Point:
    def __init__(self, x,y,z):
        self.x = x
        self.y = y
        self.z = z

where x,y,z are float

and I want to do this:

p = Point(0,0,0)
arr_p = np.array(p)
arr_pts = np.array([p])

what I expect:

>>> arr_p
array([0., 0., 0.])
>>> arr_pts
array([[0., 0., 0.]])

and both have dtype=np.float64

How can I customize my class to achieve this?

What I've tried: I saw some comments in numpy.array

        object : array_like
            An array, any object exposing the array interface, an object whose
            __array__ method returns an array, or any (nested) sequence.

so I simply added

    def __array__(self):
        return [self.x, self.y, self.z]

But it doesn't work....I don't know what does it mean by array, is it C level thing that we need to manage the memory layout?

it is not clear to me exactly what you are trying to achieve. Can you give example input/output? — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Jun 5, 2019 at 22:27

HYRY · Accepted Answer · 2019-06-06 02:39:43Z

2

You can define the __len__ and __getitem__ method:

class Point:
    def __init__(self, x,y,z):
        self.x = x
        self.y = y
        self.z = z

    def __len__(self):
        return 3

    def __getitem__(self, idx):
        return (self.x, self.y, self.z)[idx]

answered Jun 6, 2019 at 2:39

HYRY

97.8k28 gold badges197 silver badges192 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

list of custom class converted to numpy array

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related