NDMI-plot.py

import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path

# --- CONFIG ---
INDEX = "NDMoI"
AOI = "mangrove_recovery_RB"
# AOI = "mangrove_recovery_JB"
# AOI = "mangrove_death_JB"
# AOI = "mangrove_death_RB"

files = {
    "MODIS"     : f"{AOI}_mo.csv",
    "Landsat-8" : f"{AOI}_l8.csv",
    "Sentinel-2": f"{AOI}_s2.csv"
}
date_col = "system:time_start"

# Colorblind-friendly choices (blue & orange)
colors = {
    "MODIS"     : "#0072B2",  # blue
    "Landsat-8" : "#E69F00",   # orange
    "Sentinel-2": "#009E73"  # green    
}

def makePlot(value_col):
    plt.figure(figsize=(12, 6))
    
    for label, fpath in files.items():
        f = Path(fpath)
        df = pd.read_csv(f, thousands=",")
        
        # Parse and clean
        df[date_col] = pd.to_datetime(df[date_col], errors="coerce")
        df[value_col] = pd.to_numeric(df[value_col], errors="coerce")
        df = df.dropna(subset=[date_col, value_col]).sort_values(date_col)
        
        # Raw points
        plt.plot(
            df[date_col], df[value_col], "x",
            alpha=1, color=colors[label], label=f"{label} raw"
        )
        
        # 1-month moving average
        monthly = df.set_index(date_col)[value_col].resample("QS").mean()  # QS = quarterly
        ma = monthly.rolling(window=3).mean()
        plt.plot(
            ma.index, ma.values, "-",
            linewidth=4, color=colors[label], label=f"{label} moving avg"
        )
    
    plt.title(f"{value_col} Time Series ({AOI}) with 3-Month Moving Average")
    plt.xlabel("Date")
    plt.ylabel(value_col)
    plt.legend()
    plt.grid(True, linestyle="--", alpha=0.6)
    plt.tight_layout()
    plt.show()

makePlot("NDMoI")
makePlot("NDMaI")
makePlot("NDVI")