Project: s41467-024-51555-8 | Function: hindcast (python)

system: You are an expert Python programmer implementing algorithms from scientific papers.
Complete the masked function based on the algorithm description.
Follow Python best practices and maintain consistent code style.
Return **only** the complete Python function code.

user: Complete this Python function:

**DESCRIPTION:** Implements the comprehensive crop yield forecasting system that orchestrates the entire preseason forecast workflow including crop calendar processing, ENSO forecast integration, spatial masking, cross-validation, and multi-lead time forecast generation for global maize and wheat yield predictions

**KEY TERMS:** {
  "yldArrW": "wheat yield anomaly array Ya_i",
  "yldArrM": "maize yield anomaly array Ya_i",
  "ccwMsk": "crop calendar masks for wheat vegetative period",
  "ccmMsk": "crop calendar masks for maize vegetative period",
  "ensoProbs": "ENSO forecast probabilities from model-analog system",
  "quantile": "tercile threshold (1/3) for below-normal classification",
  "haFracTh": "harvested area fraction threshold (50%) for in-season determination",
  "fcst": "core forecast function call for each country/crop combination"
}

**CONTEXT CODE:** #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct  4 14:02:29 2021

Code to accompany the manuscript: "Preseason maize and wheat yield forecasts for early warning" by Anderson et al.

"""
import multiprocessing
import xarray as xr
import numpy as np
import pandas as pd
import _pickle as cPickle
from matplotlib import pyplot as plt
import matplotlib.cm as cm
from matplotlib.colors import Normalize
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cartopy.io.shapereader as shpreader
from scipy.stats import percentileofscore
import os
import warnings
warnings.filterwarnings("ignore",category=RuntimeWarning) #ignore the warnings about taking the mean of an empty slice
warnings.filterwarnings("ignore")
plt.ioff()

codePath = '/discover/nobackup/wanders7/Code/General'
savePath1 = '/discover/nobackup/wanders7/Research'
dataPath1 = '/discover/nobackup/wanders7'
dataPath2 = '/discover/nobackup/wanders7'


exec(open(codePath+'/Forecasts/forecast_functions/regions_and_seasons.py').read())
exec(open(codePath+'/Forecasts/forecast_functions/ForecastEstimate_hypergeom_wNans.py').read())
exec(open(codePath+'/Forecasts/yield_forecasts/fao/FAO_ensoYrShift.py').read())

fcstMons = [1,2,3,4,5,6,7,8,9,10,11,12]#running 1,2,3 and 4,5,6.  #[1,2,3,4,5,6,7,8,9,10,11,12]#[9,10,11,12] #[5,6,7,8] #[1,2,3,4] #halfway through

def hindcast(fcstMon):
    """
    Implements the comprehensive crop yield forecasting system.
    """
    # MASKED: Implements the comprehensive crop yield forecasting system that orchestrates the entire preseason forecast workflow including crop calendar processing, ENSO forecast integration, spatial masking, cross-validation, and multi-lead time forecast generation for global maize and wheat yield predictions
    raise NotImplementedError("Function has been masked for testing purposes")
with multiprocessing.Pool() as pool:
    pool.map(hindcast,fcstMons)
    
    


Complete the function implementation replacing "raise NotImplementedError".