<｜begin▁of▁sentence｜>### Instruction:
You have a list of numerical values representing the measurements of a certain variable over time. How can you continuously update and calculate the running mean and standard deviation as new measurements are added without having to recalculate from scratch each time?
### Response:
from RunningMean import RunningMean

# Initialize the running mean with a list of items
items = [2.3, 3.5, 4.7, 5.9]
running_mean = RunningMean(items=items)

# Display the current state of the running mean
print(f'Mean: {running_mean.mean}, SD: {running_mean.sd}, N: {running_mean.n}')

# If you want to initialize the running mean with precomputed values:
n = 4  # Number of elements
mean = 4.1  # Presumed mean
sd = 1.2   # Presumed standard deviation
running_mean = RunningMean(n=n, mean=mean, sd=sd)

# Display the re-initialized state
print(f'Mean: {running_mean.mean}, SD: {running_mean.sd}, N: {running_mean.n}')
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