Consider the following Python code (Python 3):
- I have a class
Signal
comprising all the functions signals of all different kinds should be able to perform. - For each kind of signal, I create a new class, where the data is “sampled”, meaning an array with signal data is specified.
If I now want to plot the signal, the plot
method of the super()
class is called. However, in order to plot the data, the Signal
class must somehow access it. Now my question is: What is the cleanest way to pass the signal data to the Signal
class?
I have the feeling that there must be a better way than the super().write_data(self.sample())
approach.
# -*- coding: utf-8 -*- """ Created on Thu Jun 23 14:13:14 2022 @author: ilja """ from matplotlib import pyplot as plt import math import numpy as np class Signal: def __init__(self, length): self.length = length self.data = None def write_data(self,data): self.data = data def plot(self): plt.figure(1) x = [i for i in range(self.length)] plt.plot(x, self.data) plt.show() def integrate(self): # TODO pass class Harmonic(Signal): def __init__(self, periods, amplitude, frequency): super().__init__(int(2*math.pi*periods)) self.amplitude = amplitude self.frequency = frequency super().write_data(self.sample()) def sample(self): return [self.amplitude * math.sin(i*self.frequency) for i in range(self.length)] if __name__ == '__main__': sig = Harmonic(7,3,1/2) sig.plot()
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Answer
Well, since Harmonics is “based” on Signal, you can acces the attributes defined in Signal. You can simply write:
class Harmonic(Signal): def __init__(self, periods, amplitude, frequency): super().__init__(int(2*math.pi*periods)) self.amplitude = amplitude self.frequency = frequency self.data = self.sample()
So, instead of
super().write_data(self.sample())
you write only
self.data = self.sample()