计算或更新平均值,无需随时间迭代

除了其他答案外,您可能还需要使用IIR筛选器来获取 Exponential moving average : filter that applies weighting factors which decrease exponentially ,因此最后一个值比旧值的影响更大

newAverage = OldAverage * (1-alpha) + NewValue * alpha

alpha 是与递减时间/常数相关的小值,如0.1

from itertools import count

temperature_sum = 0
for temperature_count in count(1):
    temperature_sum += read_from_sensor()
    print("Average: {}".format(temperature_sum / temperature_count))

我们需要两个变量

int count;
float average;

void main() {
   do while(true) {
      float temperature = ReadFromSensor(); //not included
      average = ((average*count) + temperature)/ ++count;
      cout << "average: " << average << endl;
   }
}