Trend Analysis Module¶

This module includes functionalities related to trend_analysis.py code.

Overview¶

The trend_analysis module provides functions to gap filling and analyze trends in time series data.

Functions¶

1.extract_ts¶

Extracts time series data from the DataFrame for 5-day intervals.

Parameters¶

• df: DataFrame containing the data.
• dt_5days: List of 5-day intervals.

Returns: - Time series data and corresponding dates.

2.gapfill¶

Fills gaps in the time series data.

Parameters¶

• ts: Time series data.
• dates: List of dates corresponding to the time series data.
• season_size: Size of the seasonal period.

Returns: - Filled time series data and updated dates.

3.sm_trend¶

Applies seasonal decomposition and trend smoothing to the time series data.

Parameters¶

• ts: Time series data.
• season_size: Size of the seasonal period.
• seasonal_smooth: Size of the seasonal smoothing.

Returns: - Trend analysis results and column names.

4.run¶

Executes the trend analysis workflow for a given polygon ID.

Parameters¶

• input_file: Input database file.
• id_pol: ID of the polygon.
• dt_5days: List of 5-day intervals.
• season_size: Size of the seasonal period.
• output_file: Output file path.