import sys

import matplotlib.pyplot as plt
import numpy as np
import os
import statsmodels.api as sm
from datetime import datetime
from datetime import timedelta
from dateutil.relativedelta import relativedelta

from common import calc_intervals, printnoln, rprint, DAYS_NEW_USER
from loader import load, dmt, cms, readVotes
from sentiments import readtoxleveltxt

colors = ['red', 'green', 'blue', 'orange', 'deeppink']
thresholds = [3, 4, 5, 6]
changedate = datetime.fromisoformat("2018-09-01T00:00:00")


def main(folder, intervl):
    users, posts, firstcontrib, sumcontrib = load(folder)

    intervals = calc_intervals(posts, intervl)

    start = cms()
    printnoln("reading sentiments ...")
    (_, cachedsentiments) = readtoxleveltxt(folder + "/output/sentiments.txt")
    rprint("reading sentiments ... took " + str(cms() - start) + "ms")

    outputdir = folder + "/output/votes/"
    os.system("mkdir -p " + outputdir)

    datasingle = []
    scoresingle = []
    for (option_date_from, option_date_to) in intervals:
        print(option_date_from.strftime("%d-%m-%Y") + " to " + option_date_to.strftime("%d-%m-%Y"))
        # avg sentiments
        scores = (dmt(posts).filter(lambda p: option_date_from <= p['CreationDate'] < option_date_to
                                              and firstcontrib[p['OwnerUserId']] + timedelta(days=DAYS_NEW_USER) <= p['CreationDate'])
                  .map(lambda p: int(p['Score']))
                  .getresults())
        filtered = (dmt(posts).map(lambda p: [cachedsentiments[a['Id']]['compound']
                                              for a in p['Answers'] if option_date_from <= a['CreationDate'] < option_date_to
                                              and firstcontrib[p['OwnerUserId']] + timedelta(days=DAYS_NEW_USER) <= a['CreationDate']])
                    .filter(lambda p: p != [])
                    .reduce(lambda a, b: a + b, lambda a, b: a + b, lambda: [])
                    .getresults())
        scoresingle.append(scores)
        datasingle.append(filtered)

    # filter nan entries
    for i in range(len(datasingle)):
        if len(datasingle[i]) == 0:
            datasingle[i] = float("nan")
        if len(scoresingle[i]) == 0:
            scoresingle[i] = float("nan")

    print("Plotting ...")
    fig, ax = plt.subplots(figsize=(16, 12))
    data = [np.mean(x) for x in datasingle]
    l1 = ax.plot([i[0] for i in intervals], data, label="average sentiment")
    ax2 = ax.twinx()
    l2 = ax2.plot([i[0] for i in intervals], [np.mean(x) for x in scoresingle], label="average score (votes)", color="red")
    plt.grid(True)
    for i in range(len(data)):
        va = "center"
        if 0 < i < len(data) - 1:
            if data[i - 1] < data[i] and data[i + 1] < data[i]:
                va = "bottom"
            elif data[i - 1] > data[i] and data[i + 1] > data[i]:
                va = "top"
        elif i == 0:
            if data[i + 1] < data[i]:
                va = "bottom"
            else:
                va = "top"
        elif i == len(data) - 1:
            if data[i - 1] < data[i]:
                va = "bottom"
            else:
                va = "top"
        ax.text(intervals[i][0], data[i], ("n=" if i == 0 else "") + (str(len(datasingle[i])) if str(datasingle[i]) != "nan" else ""), ha="center", va=va)
    plt.title("Average sentiments and score for new users")
    plt.xticks(rotation=90)
    ax.set_xlabel("months")
    ax.set_ylabel("sentiment")
    ax2.set_ylabel("score (votes)")
    plt.legend(l1 + l2, [l.get_label() for l in l1 + l2], loc="upper right")
    outfile = outputdir + "/average_votes-i" + str(intervl) + ".png"
    plt.savefig(outfile, bbox_inches='tight')
    plt.close(fig)

    # votes over time
    votes = readVotes(folder)
    fig = plt.figure(figsize=(16, 12))
    ivs = [(datetime.fromisoformat("2010-01-01T00:00:00"), datetime.fromisoformat(str(y) + "-01-01T00:00:00")) for y in range(2011, 2020)]
    for interval in ivs:
        print(interval[0].strftime("%d-%m-%Y") + " to " + interval[1].strftime("%d-%m-%Y"))
        ivvotes = dmt(votes).filter(lambda v: interval[0] <= v['CreationDate'] < interval[1]).getresults()
        scores = []
        for (option_date_from, option_date_to) in intervals:
            if option_date_to > interval[1]:
                continue
            intervalposts = dmt(posts).filter(lambda p: option_date_from <= p['CreationDate'] < option_date_to
                                                        and firstcontrib[p['OwnerUserId']] + timedelta(days=DAYS_NEW_USER) <= p['CreationDate']).getresults()
            intervalpostsids = set(dmt(intervalposts).map(lambda p: p['Id']).getresults())
            intervalvotes = dmt(ivvotes).filter(lambda v: v['PostId'] in intervalpostsids).getresults()
            intervalscore = sum(dmt(intervalvotes).map(lambda v: 1 if v['VoteTypeId'] == "2" else (-1 if v['VoteTypeId'] == "3" else 0)).getresults())
            intervalscore = intervalscore / len(intervalpostsids) if len(intervalpostsids) != 0 else float("nan")
            scores.append(((option_date_from, option_date_to), intervalscore))
        # if all(str(score) == "nan" for iv, score in scores)
        #     continue
        plt.plot([iv[0] for iv, score in scores], [score for iv, score in scores], label=str(interval[0].year) + " - " + str(interval[1].year))
    plt.title("Average score for new users over time")
    plt.xlabel("months")
    plt.ylabel("score")
    plt.legend(loc="upper right")
    plt.grid(True)
    outfile = outputdir + "/average_votes_over_time-i" + str(intervl) + ".png"
    plt.savefig(outfile, bbox_inches='tight')
    plt.close(fig)


if __name__ == "__main__":
    # execute only if run as a script
    usage = sys.argv[0] + " <folder>"
    if len(sys.argv) < 2:
        print(usage)
        sys.exit(1)
    folder = sys.argv[1]
    if not os.path.isdir(folder):
        print(folder + " is not a folder")
        sys.exit(1)
    interval = 1
    if len(sys.argv) >= 3:
        if sys.argv[2].startswith("-i"):
            interval = sys.argv[2][2:]
            try:
                interval = int(interval)
            except ValueError:
                print("-i: int required")
                sys.exit(1)
            if interval < 1 or interval > 12:
                print("-i: only 1 - 12")
                sys.exit(1)
        else:
            print("unknown parameter: " + sys.argv[2])
            sys.exit(1)

    main(folder, interval)