R

```
"""
The Simple Moving Average (SMA) is a statistical calculation used to analyze data points
by creating a constantly updated average price over a specific time period.
In finance, SMA is often used in time series analysis to smooth out price data
and identify trends.
Reference: https://en.wikipedia.org/wiki/Moving_average
"""
from collections.abc import Sequence
def simple_moving_average(
data: Sequence[float], window_size: int
) -> list[float | None]:
"""
Calculate the simple moving average (SMA) for some given time series data.
:param data: A list of numerical data points.
:param window_size: An integer representing the size of the SMA window.
:return: A list of SMA values with the same length as the input data.
Examples:
>>> sma = simple_moving_average([10, 12, 15, 13, 14, 16, 18, 17, 19, 21], 3)
>>> [round(value, 2) if value is not None else None for value in sma]
[None, None, 12.33, 13.33, 14.0, 14.33, 16.0, 17.0, 18.0, 19.0]
>>> simple_moving_average([10, 12, 15], 5)
[None, None, None]
>>> simple_moving_average([10, 12, 15, 13, 14, 16, 18, 17, 19, 21], 0)
Traceback (most recent call last):
...
ValueError: Window size must be a positive integer
"""
if window_size < 1:
raise ValueError("Window size must be a positive integer")
sma: list[float | None] = []
for i in range(len(data)):
if i < window_size - 1:
sma.append(None) # SMA not available for early data points
else:
window = data[i - window_size + 1 : i + 1]
sma_value = sum(window) / window_size
sma.append(sma_value)
return sma
if __name__ == "__main__":
import doctest
doctest.testmod()
# Example data (replace with your own time series data)
data = [10, 12, 15, 13, 14, 16, 18, 17, 19, 21]
# Specify the window size for the SMA
window_size = 3
# Calculate the Simple Moving Average
sma_values = simple_moving_average(data, window_size)
# Print the SMA values
print("Simple Moving Average (SMA) Values:")
for i, value in enumerate(sma_values):
if value is not None:
print(f"Day {i + 1}: {value:.2f}")
else:
print(f"Day {i + 1}: Not enough data for SMA")
```