import operator
import os
import sys
from collections import defaultdict
from datetime import timedelta
from math import ceil

import matplotlib.pyplot as plt
import numpy as np
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

from common import calc_intervals, imprt, FigSaver
from loader import load, dmt, cms

printnoln = lambda text: print(text, end='', flush=True)
rprint = lambda text: print('\r' + text)

DAYS_NEW_USER = 7
OLD_USER_YEAR = 3
OLD_USER_PERCENTILE = 0.95

analyser = SentimentIntensityAnalyzer()
figsaver = FigSaver()
colors = ['red', 'green', 'blue', 'orange', 'deeppink']


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

    intervals = calc_intervals(posts)
    cachedsentiments = imprt(folder + "/output/sentiments.py").answers

    outfolder = folder + "/output/batch/"
    os.system("mkdir -p " + outfolder)

    postcounts = range(1, 5 + 1)
    for (option_date_from, option_date_to) in intervals:
        # get questions for option_date_from <= creation date < option_date_to
        newposts = dmt(posts).filter(lambda p: option_date_from <= p['CreationDate'] < option_date_to, "filter posts by dates").getresults()
        if len(newposts) == 0:
            continue
        print("computing toxic levels: " + option_date_from.strftime("%d-%m-%Y") + " to " + option_date_to.strftime("%d-%m-%Y"))
        gfig, gaxs = plt.subplots(2, 2, figsize=(16, 12))
        gaxs[0, 0].set_title('Neg')
        gaxs[1, 0].set_title('Neu')
        gaxs[0, 1].set_title('Pos')
        gaxs[1, 1].set_title('Compound')

        gneg = []
        gneu = []
        gpos = []
        gcom = []

        goutfilenamenewusers = outfolder + "batch_newusers_" + folder.split("/")[-1] + "_" + option_date_from.strftime("%d-%m-%Y") + "_" + option_date_to.strftime("%d-%m-%Y")
        goutfilenameoldusers = outfolder + "batch_oldusers_" + folder.split("/")[-1] + "_" + option_date_from.strftime("%d-%m-%Y") + "_" + option_date_to.strftime("%d-%m-%Y")

        for option_posts in postcounts:
            # print(option_date_from.strftime("%d-%m-%Y") + " to " + option_date_to.strftime("%d-%m-%Y") + " - #posts: " + str(option_posts))

            # computer toxic levels
            start = cms()
            printnoln("computing toxic levels: filtering")
            toxlevels = []
            searchedposts = defaultdict(int)
            filteredposts = []
            for (i, post) in enumerate(newposts):
                userid = post['OwnerUserId']

                # check first contribution
                if firstcontrib[userid] + timedelta(days=DAYS_NEW_USER) < post['CreationDate']:
                    continue

                # no more than option_posts posts from one user
                searchedposts[userid] += 1
                if searchedposts[userid] > option_posts:
                    continue

                filteredposts.append(post)

            for (i, post) in enumerate(filteredposts):
                printnoln("\rcomputing toxic levels: post " + str(i + 1) + "/" + str(len(filteredposts)))
                for a in post['Answers']:
                    if a['Id'] in cachedsentiments.keys():
                        toxlevel = cachedsentiments[a['Id']]
                    else:
                        print("Sentiment not found for " + a['Id'])
                    toxlevels.append(toxlevel)
            printnoln("\rcomputing toxic levels: post " + str(len(filteredposts)) + "/" + str(len(filteredposts)) + " ... plotting ...")

            outfilename = goutfilenamenewusers + "_" + str(option_posts)
            dumptoxlevels(toxlevels, outfilename + ".py")

            neglevelsflat = [item['neg'] for item in toxlevels]
            neulevelsflat = [item['neu'] for item in toxlevels]
            poslevelsflat = [item['pos'] for item in toxlevels]
            comlevelsflat = [item['compound'] for item in toxlevels]

            gneg.append(neglevelsflat)
            gneu.append(neulevelsflat)
            gpos.append(poslevelsflat)
            gcom.append(comlevelsflat)

            fig, axs = plt.subplots(2, 2, figsize=(16, 12))
            axs[0, 0].set_title('Neg')
            axs[1, 0].set_title('Neu')
            axs[0, 1].set_title('Pos')
            axs[1, 1].set_title('Compound')
            axs[0, 0].hist(neglevelsflat, np.linspace(0, 1, 1 * 100))
            axs[1, 0].hist(neulevelsflat, np.linspace(0, 1, 1 * 100))
            axs[0, 1].hist(poslevelsflat, np.linspace(0, 1, 1 * 100))
            axs[1, 1].hist(comlevelsflat, np.linspace(-1, 1, 2 * 100))
            axs[0, 0].set_yscale('log')
            axs[1, 0].set_yscale('log')
            axs[0, 1].set_yscale('log')
            axs[1, 1].set_yscale('log')

            # plt.show()
            fig.suptitle("Sentiment of answers to the first " + str(option_posts) + " (max) posts within 1 week of 1st contribution\nPosts created between "
                         + option_date_from.strftime("%d-%m-%Y") + " to " + option_date_to.strftime("%d-%m-%Y"))
            # figsaver.save(fig, outfilename + ".png", bbox_inches='tight')
            printnoln("\rcomputing toxic levels: post " + str(len(filteredposts)) + "/" + str(len(filteredposts)) + " ... plotting ... saving ...")
            fig.savefig(outfilename + ".png", bbox_inches='tight')
            plt.close(fig)
            rprint("computing toxic levels: post " + str(len(filteredposts)) + "/" + str(len(filteredposts)) + " ... plotting ... saving ... took " + str(cms() - start) + "ms")

        # global
        start = cms()
        printnoln("\rglobal plot post ... plotting ...")
        gaxs[0, 0].hist(gneg, np.linspace(0, 1, 1 * 100), color=colors[:len(postcounts)], label=[str(option_posts) + " posts" for option_posts in postcounts])
        gaxs[1, 0].hist(gneu, np.linspace(0, 1, 1 * 100), color=colors[:len(postcounts)], label=[str(option_posts) + " posts" for option_posts in postcounts])
        gaxs[0, 1].hist(gpos, np.linspace(0, 1, 1 * 100), color=colors[:len(postcounts)], label=[str(option_posts) + " posts" for option_posts in postcounts])
        gaxs[1, 1].hist(gcom, np.linspace(-1, 1, 2 * 100), color=colors[:len(postcounts)], label=[str(option_posts) + " posts" for option_posts in postcounts])
        gaxs[0, 0].legend(loc="upper right")
        gaxs[1, 0].legend(loc="upper right")
        gaxs[0, 1].legend(loc="upper right")
        gaxs[1, 1].legend(loc="upper right")
        gaxs[0, 0].set_yscale('log')
        gaxs[1, 0].set_yscale('log')
        gaxs[0, 1].set_yscale('log')
        gaxs[1, 1].set_yscale('log')
        gfig.suptitle(
            "Sentiment of answers to the first X (max) posts within 1 week of 1st contribution\nPosts created between " + option_date_from.strftime("%d-%m-%Y") + " to " + option_date_to.strftime(
                "%d-%m-%Y"))
        # figsaver.save(gfig, goutfilenamenewusers + ".png", bbox_inches='tight')
        printnoln("\rglobal plot post ... plotting ... saving ...")
        gfig.savefig(goutfilenamenewusers + ".png", bbox_inches='tight')
        plt.close(gfig)
        rprint("global plot post ... plotting ... saving ... took " + str(cms() - start) + "ms")

        # for old users ---------------------------------------------------------------------------------
        start = cms()
        newuserids = set(dmt(newposts).map(lambda p: p['OwnerUserId']).getresults())
        userposts = {u: 0 for u in newuserids}
        for p in newposts:
            userposts[p['OwnerUserId']] += 1
        userposts = sorted(userposts.items(), key=operator.itemgetter(1))
        oldusers = [k for k, v in userposts]
        oldusers = set(oldusers[ceil(len(oldusers) * OLD_USER_PERCENTILE):])
        filteredposts = dmt(newposts).filter(lambda p: p['OwnerUserId'] in oldusers).getresults()

        toxlevels = []
        for (i, post) in enumerate(filteredposts):
            printnoln("\rcomputing toxic levels: post " + str(i + 1) + "/" + str(len(filteredposts)))
            for a in post['Answers']:
                if a['Id'] in cachedsentiments.keys():
                    toxlevel = cachedsentiments[a['Id']]
                else:
                    print("Sentiment not found for " + a['Id'])
                toxlevels.append(toxlevel)
        printnoln("\rcomputing toxic levels: post " + str(len(filteredposts)) + "/" + str(len(filteredposts)) + " ... plotting ...")

        dumptoxlevels(toxlevels, goutfilenameoldusers + ".py")

        neglevelsflat = [item['neg'] for item in toxlevels]
        neulevelsflat = [item['neu'] for item in toxlevels]
        poslevelsflat = [item['pos'] for item in toxlevels]
        comlevelsflat = [item['compound'] for item in toxlevels]

        fig, axs = plt.subplots(2, 2, figsize=(16, 12))
        axs[0, 0].set_title('Neg')
        axs[1, 0].set_title('Neu')
        axs[0, 1].set_title('Pos')
        axs[1, 1].set_title('Compound')
        axs[0, 0].hist(neglevelsflat, np.linspace(0, 1, 1 * 100))
        axs[1, 0].hist(neulevelsflat, np.linspace(0, 1, 1 * 100))
        axs[0, 1].hist(poslevelsflat, np.linspace(0, 1, 1 * 100))
        axs[1, 1].hist(comlevelsflat, np.linspace(-1, 1, 2 * 100))
        axs[0, 0].set_yscale('log')
        axs[1, 0].set_yscale('log')
        axs[0, 1].set_yscale('log')
        axs[1, 1].set_yscale('log')

        # plt.show()
        fig.suptitle("Sentiment of answers to posts by most posting users (95%tile)\nPosts created between " + option_date_from.strftime("%d-%m-%Y") + " to " + option_date_to.strftime("%d-%m-%Y"))
        # figsaver.save(fig, goutfilenameoldusers + ".png", bbox_inches='tight')
        printnoln("\rcomputing toxic levels: post " + str(len(filteredposts)) + "/" + str(len(filteredposts)) + " ... plotting ... saving ...")
        fig.savefig(goutfilenameoldusers + ".png", bbox_inches='tight')
        plt.close(fig)
        rprint("computing toxic levels: post " + str(len(filteredposts)) + "/" + str(len(filteredposts)) + " ... plotting ... saving ... took " + str(cms() - start) + "ms")

        figsaver.join()
    figsaver.join()


def computeToxLevel(text):
    return analyser.polarity_scores(text)


def dumptoxlevels(lvls, filename):
    with open(filename, "w") as file:
        file.write("from collections import defaultdict\n\n")
        file.write("toxlevels = " + str(lvls).replace("<class 'list'>", "list", 1) + "\n")


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)

    main(folder)