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import cdsapi
from datetime import datetime, timedelta



def get_monthsdays(start =[2019,1,1],end=[2019,12,31]):
    # reforecast time index
    start, end = datetime(*start),datetime(*end)
    days = [start + timedelta(days=i) for i in range((end - start).days + 1)]
    monthday = [d.strftime("%B-%d").split("-")  for d in days if d.weekday() in [0,3] ]   

    return monthday

# get date index
MONTHSDAYS = get_monthsdays() 

if __name__ == '__main__':
    c = cdsapi.Client()


    # set station coordinates (lat,lon)
    COORDS = {
            "Thames":[51.35,-0.45],
            "Po":[44.85, 11.65]
            }
        
    # select all years
    YEARS  = ['%d'%(y) for y in range(1999,2019)]
    
    # select all leadtime hours
    LEADTIMES = ['%d'%(l) for l in range(24,1128,24)]
    
    # loop over date index
    for md in MONTHSDAYS:

        month = md[0].lower()
        day = md[1]
        
		# loop over coordinates
        for station in COORDS:

            station_point_coord = COORDS[station]*2 # coordinates input for the area keyword
            
            c.retrieve(
                'cems-glofas-reforecast',
                {
                    'system_version': 'version_2_2',
                    'variable': 'river_discharge_in_the_last_24_hours',
                    'format': 'grib',
                    'hydrological_model': 'htessel_lisflood',
                    'product_type': 'control_reforecast',
                    'area':station_point_coord, 
                    'hyear': YEARS,
                    'hmonth': month ,
                    'hday': day ,
                    'leadtime_hour': LEADTIMES,
                },
                f'glofas_reforecast_{station}_{month}_{day}.grib')

import xarray as xr
import numpy as np
import matplotlib.pyplot as plt

YEARS = range(1999,2019)

# read dataset
ds = xr.open_dataset("glofas_reforecast_Po_january_03.grib",engine="cfgrib")
da = ds.isel(latitude=0,longitude=0).dis24

# plotting parameters
n = len(YEARS) 
colors = plt.cm.jet(np.linspace(0,1,n))
ls = ["-","--",":"]

# plot
fig,ax = plt.subplots(1,1,figsize=(16,8))

steps = list(range(24,dsa.shape[1]*24+24,24))

for i,year in enumerate(YEARS):
    y = da.sel(time=f"{year}-01-03").values
    ax.plot(steps,y,label=f"{year}-01-03",color=colors[i],ls=ls[i%3])
    plt.legend(bbox_to_anchor=(0.9,-0.1),ncol=7)

ax.set_xlim([0,steps[-1]])
ax.set_xlabel("leadtime hours")
ax.set_ylabel("m**3 s**-1")

plt.title(f"Po river discharge at {float(ds.latitude.values),round(float(ds.longitude.values),2)}")