"""
Hedonodon toot sentiment analyzer.

This programm fetches toots from the fedihum.org Mastodon instance, calculates
the frequencies of the sentiments (positive, neutral, negative) and the mean
from these nominal values (even this is not statistical correct (;-_-)!, but
not all analyzer return compounds).
It also calculates the word count of the nouns per sentiment.

It uses germansentiment for german toots, twitter-roberta-base-sentiment for
english toots, and vaderSentiment for other languages.

For the word counts I translate the toots to english with the GoogleTranslator
first.
"""

from CRUDManager import CRUDManager, calculateSentimentCount, calculateSentimentMean, getYesterdaysToots
from datetime import datetime, date
from DbSetup import init_db
import locale
from MastodonAccountManager import MastodonAccountManager
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from TootCrawler import TootCrawler
from SentiTooter import translateToots, createWordFrequenciesPerSentiment

locale.setlocale(locale.LC_TIME, "en_US.UTF-8")
init_db()

print('Initialize Mastodon...')
mastodonAccountManager = MastodonAccountManager()
mastodonInstance = mastodonAccountManager.instance
"""
mastodonInstance.log_in(
    'USER-EMAIL',
    'PW',
    to_file = 'hedonodon_usercred.secret'
)
"""
print('done!')

print('Fetching recent toots...')
tootCrawler = TootCrawler(mastodonInstance)
crudManager = CRUDManager()
lastTootId = crudManager.getLastToot()
tootsDataframe = tootCrawler.buildTootsDataframe(lastTootId)
print('done!')

print('Save toots to database...')
if not tootsDataframe.empty:
    crudManager.saveToDatabase(tootsDataframe, 'Toots', useIndex=False)
    print('done!')
else:
    print('nothing changed since last database insert!')

print('Calculate word counts...')
yesterdaysToots = getYesterdaysToots()
translatedToots = translateToots(yesterdaysToots)
wordCountsPerSentiment = createWordFrequenciesPerSentiment(translatedToots)
print('done!')

print(wordCountsPerSentiment);

print('Calculate sentiment counts...')
sentimentsYesterday = calculateSentimentCount()
print('done!')

print('Calculate sentiment mean...')
sentimentMeansYesterday = calculateSentimentMean(sentimentsYesterday)
print('done!')

print('Save calculations to database...')
if not tootsDataframe.empty:
    crudManager.saveToDatabase(dataframe=sentimentsYesterday, table='SentimentCounts', useIndex=True)
    crudManager.saveToDatabase(dataframe=sentimentMeansYesterday, table='SentimentMeans', useIndex=True)
    print('done!')
else:
    print('nothing changed since last database insert!')

print('Create figure...')
colormap = {
    'negative': '#ff9999',
    'neutral': '#ffcc99',
    "positive": '#99ff99'
}

todaysColors = []
for sentiment in sentimentsYesterday['sentiment'].to_numpy():
    todaysColors.append(colormap[sentiment])



TodayDate = datetime.strptime(sentimentsYesterday['date'][0], '%Y-%m-%d').strftime('%d.%m.%Y')
dataframe4PieChart = sentimentsYesterday.drop('date', axis=1).set_index('sentiment')
dataframe4LineChart = crudManager.loadFromDatabase('SentimentMeans', 'date').drop('index', axis=1)

fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(10, 10))

# Pie chart.
pieChartlabels = dataframe4PieChart.index.to_numpy()
pieChart = dataframe4PieChart.plot.pie(
    ax=axes[0],
    y='sentimentCount',
    ylabel="",
    labels=dataframe4PieChart['sentimentCount'],
    title=f'Moods of the toots on {TodayDate} of the local timeline on fedihum.org',
    colors=todaysColors,
    wedgeprops=dict(linewidth=3, edgecolor='w'),
    startangle=90
)

axes[0].axis('equal')
centre_circle = plt.Circle((0, 0), 0.6, fc='white')
axes[0].add_patch(centre_circle)
chartBox = axes[0].get_position()
axes[0].legend(pieChartlabels, loc='upper right', bbox_to_anchor=(0.9, 0.9))

# Line chart.
lineChart = dataframe4LineChart.plot.line(
    ax=axes[1],
    title='"Mean" of sentiments, calculated from nominal values, pos(1), neu (0), neg (-1)!'
)
axes[1].grid(True)
axes[1].set_xlim([date(2023, 1, 1), date(2023, 12, 31)])
axes[1].set_ylim([-1, 1])
axes[1].xaxis.set_major_locator(mdates.MonthLocator())
axes[1].xaxis.set_minor_locator(mdates.MonthLocator(bymonthday=15))
axes[1].xaxis.set_major_formatter(plt.NullFormatter())
axes[1].xaxis.set_minor_formatter(mdates.DateFormatter('%h'))
axes[1].tick_params(which='minor', length=0)
plotFileUrl = f'./plots/{TodayDate}.png'
plt.savefig(plotFileUrl)
print('done!')

print('Send toot...')
#media = mastodonInstance.media_post(plotFileUrl, mime_type="image/png", description=f"Sentiment analysis of local timeline on fedihum.org, showing the moods of the toots on, and the sentiment mean up to {TodayDate}.")
#mastodonInstance.status_post(f'The moods of the toots on and up to {TodayDate}.\nWord counts per sentiment:\n{wordCountsPerSentiment}', media_ids=media, language='en')
print('done!')