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50 changes: 50 additions & 0 deletions maths/autocorrelation.py
Original file line number Diff line number Diff line change
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"""
Autocorrelation measures the correlation of a signal with a delayed
copy of itself. It is widely used in time series analysis, signal
processing, and statistics.

Reference: https://en.wikipedia.org/wiki/Autocorrelation
"""


def autocorrelation(data: list[float], lag: int) -> float:
"""
Calculate the autocorrelation of a time series at a given lag.

:param data: A list of numerical values representing the time series.
:param lag: The number of time steps to shift the series.
:return: The autocorrelation coefficient at the given lag.

>>> round(autocorrelation([1, 2, 3, 4, 5], 1), 4)
0.4
>>> round(autocorrelation([1, 2, 3, 4, 5], 0), 4)
1.0
>>> autocorrelation([1, 2, 3], 5)
Traceback (most recent call last):
...
ValueError: Lag must be less than the length of the data.
"""
if lag >= len(data):
raise ValueError("Lag must be less than the length of the data.")

n = len(data)
mean = sum(data) / n
variance = sum((x - mean) ** 2 for x in data) / n

if variance == 0:
raise ValueError("Variance of data is zero, autocorrelation undefined.")

covariance = (
sum((data[i] - mean) * (data[i - lag] - mean) for i in range(lag, n)) / n
)

return covariance / variance


if __name__ == "__main__":
import doctest

doctest.testmod()
data = [1, 2, 3, 4, 5, 4, 3, 2, 1]
for lag in range(5):
print(f"Lag {lag}: {autocorrelation(data, lag):.4f}")