ESTIMATION OF A CONSTANT | A basic simulation code

ConstantEstimation.py

# -*- coding: utf-8 -*-
"""
Created on Thu Jun 23 21:45:31 2022

@author: personF
"""
import numpy as np
import matplotlib.pyplot as plt

class Resistor:
    def __init__(self,ohm):
        self.ohm = ohm

class Sensor:
    def __init__(self,mean,std):
        self.inputVal = []
        self.outputVal = []
        self.err_std = std
        self.mean = mean        
    
    def measure(self,realVal):
        self.inputVal.append(realVal)
        self.outputVal.append(realVal+np.random.normal(self.mean,self.err_std))
        
    def meanOfResult(self):
        return np.sum(self.outputVal)/len(self.outputVal)
    

resistor = Resistor(355)

sensorCheap = Sensor(0,25)
sensorExpensive = Sensor(0,4)

for i in range(1,501):
    sensorCheap.measure(resistor.ohm)
    sensorExpensive.measure(resistor.ohm)

# The histograph of the measurements
fig, axs = plt.subplots(2)
axs[0].hist(sensorCheap.outputVal)
axs[0].set_title("Cheap Multimeter")
axs[1].hist(sensorExpensive.outputVal)
axs[1].set_title("Expensive Multimeter")
plt.setp(axs, xlim=axs[0].get_xlim())
plt.show()

# The mean of the measurements
cheapRes = sensorCheap.meanOfResult()
expensiveRes = sensorExpensive.meanOfResult()