I have a class in which I have properties that are returning arrays. For simplicity, let's consider them constant:
import numpy as np
class MyClass:
def __init__(self):
self._time = np.array([0, 1, 2, 3])
self._a = np.array([0, 1, 2, 3])
self._b = np.array([4, 5, 6, 7])
@property
def a(self):
return self._a
@property
def b(self):
return self._b
Now, I have another class which is inheriting MyClass
and it is interpolating the data, for example:
class Interpolator(MyClass):
def __init__(self, vector):
super().__init__()
self._vector = np.array(vector)
@property
def a(self):
return np.interp(self._vector, self._time, self._a)
@property
def b(self):
return np.interp(self._vector, self._time, self._b)
Now, the issue is that I have 2 classes like MyClass
and each one of them consists of ~30 properties.
Is there a way to override all properties without doing it one by one? I was having a look also at this solution but I am not sure if/how I can apply it to my problem.
Refactor your superclass to "proxy"/"trampoline" those properties via a function you can override in a subclass:
import numpy as np
class MyClass:
def __init__(self):
self._time = np.array([0, 1, 2, 3])
self._a = np.array([0, 1, 2, 3])
self._b = np.array([4, 5, 6, 7])
def _get_property(self, v):
return v
@property
def a(self):
return self._get_property(self._a)
@property
def b(self):
return self._get_property(self._b)
class Interpolator(MyClass):
def __init__(self, vector):
super().__init__()
self._vector = np.array(vector)
def _get_property(self, v):
return np.interp(self._vector, self._time, v)