"""File to execute to show results"""
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime, timedelta
from parameters import SESSION


def execute_query(query):
    for row in SESSION.execute(query):
        yield row


def ask_q(possibilities, text=">>> "):
    answer = None
    while answer not in possibilities:
        answer = input(text)
    return answer


class Manager:
    table = None  # table name use by the function

    def run(self):
        """Chose"""
        print("Choisissez ce que vous voulez faire")
        print("\t1 - Pour un point donné de l’espace, je veux pouvoir avoir un historique du passé")
        print("\t2 - À un instant donné je veux pouvoir obtenir une carte me représentant n’importe quel indicateur")
        print("\t3 - Pour une période de temps donnée, je veux pouvoir obtenir clusteriser l’espace, et représenter "
              "cette clusterisation")

        decision = {
            "1": "historic",
            "2": "map",
            "3": "cluster"
        }
        answer = ask_q(decision.keys())
        getattr(self, decision[answer])()

    def historic(self):
        self.table = "TABLE_SPACE"

        # Search station
        stations = []
        print("Choisissez une station parmis celles-ci:")
        query = "SELECT DISTINCT station FROM {}".format(self.table)
        for i, row in enumerate(execute_query(query), 1):
            end = "\n" if i % 3 == 0 else ""
            print("\t", row.station, end=end)
            stations.append(row.station)
        print()

        station = ask_q(stations)

        # Search element
        decision = {
            "tmpf": "La témparature",
            "relh": "L'humidité"
        }
        print("Choisissez un élément parmis les suivant :")
        for code, text in decision.items():
            print("\t-", text, ":", code)
        attr = ask_q(decision.keys())

        x = []
        y = []
        saisons = {
            'spring': {
                'n': 0,
                'somme': 0,
                'month': [3, 4, 5],  # March - May
                'end': lambda dt: datetime(dt.year, 6, 1) - timedelta(days=1),
                'legend': False,
                'color': 'r'
            },
            'summer': {
                'n': 0,
                'somme': 0,
                'month': [6, 7, 8],  # June - August
                'end': lambda dt: datetime(dt.year, 9, 1) - timedelta(days=1),
                'legend': False,
                'color': 'y'
            },
            'automne': {
                'n': 0,
                'somme': 0,
                'month': [9, 10, 11],  # September - November
                'end': lambda dt: datetime(dt.year, 12, 1) - timedelta(days=1),
                'legend': False,
                'color': 'm'
            },
            'winter': {
                'n': 0,
                'somme': 0,
                'month': [12, 1, 2],  # December - Febrarie
                'end': lambda dt: datetime(dt.year + 1, 3, 1) - timedelta(days=1),
                'legend': False,
                'color': 'k'
            }
        }
        query = "SELECT * FROM {} WHERE station={}".format(self.table, station.__repr__())
        for row in execute_query(query):
            value = getattr(row, attr)
            if value is None:
                continue
            x.append(datetime(*list(row.time)))
            y.append(value)
            # For saison
            for saison, d in saisons.items():
                if row.time[1] in d['month']:
                    d['n'] += 1
                    d['somme'] += value
                    break

        date, last_date = x[0], x[-1]  # first date and last date, initialisation
        x = np.array(x)
        y = np.array(y)
        plt.plot(x, y, label=attr)

        # Mark saison
        while date < last_date:
            for saison, d in saisons.items():
                if date.month in d['month']:
                    next_date = min(last_date, d['end'](date))
                    moyenne = d['somme'] / d['n']
                    if d['legend']:
                        plt.plot([date, next_date], [moyenne, moyenne], d['color'], linewidth=4)
                    else:
                        plt.plot([date, next_date], [moyenne, moyenne], d['color'], label=saison, linewidth=4)
                        d['legend'] = True
                    date = next_date + timedelta(days=1)
                    break
        plt.title(station)
        plt.legend()
        plt.show()

    def map(self):
        print("Cette fonction n'est pas implémentée")

    def cluster(self):
        print("Cette fonction n'est pas implémentée")


if __name__ == "__main__":
    Manager().run()