#!/home/pi/BirdNET-Pi/birdnet/bin/python3

import mysql.connector as sql
import os
import configparser

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from datetime import datetime
import textwrap

#Extract DB_PWD from thisrun.txt
with open('/home/pi/BirdNET-Pi/thisrun.txt', 'r') as f:
     this_run = f.readlines()
     db_pwd = str(str(str([i for i in this_run if i.startswith('DB_PWD')]).split('=')[1]).split('\\')[0])


db_connection = sql.connect(host='localhost',
                 database='birds',
                 user='birder',
                 password=db_pwd)

                    
db_cursor=db_connection.cursor(dictionary=True)

db_cursor.execute('SELECT * FROM detections')

table_rows = db_cursor.fetchall()

df=pd.DataFrame(table_rows)

#Convert Date and Time Fields to Panda's format
df['Date']=pd.to_datetime(df['Date'])
df['Time']=pd.to_datetime(df['Time'], unit='ns')


#Add round hours to dataframe
df['Hour of Day'] = [r.hour for r in df.Time]

#Create separate dataframes for separate locations
df_plt=df #Default to use the whole Dbase

#Get todays readings
now = datetime.now()
df_plt_today = df_plt[df_plt['Date']==now.strftime("%Y-%m-%d")]

#Set number of species to report
readings=10

plt_top10_today = (df_plt_today['Com_Name'].value_counts()[:readings])
df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.index)]

#Set Palette for graphics
pal = "Greens"

#Set up plot axes and titles
f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487')
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)

#generate y-axis order for all figures based on frequency
freq_order = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index

#make color for max confidence --> this groups by name and calculates max conf
confmax = df_plt_top10_today.groupby('Com_Name')['Confidence'].max()
#reorder confmax to detection frequency order
confmax = confmax.reindex(freq_order)

# norm values for color palette
norm = plt.Normalize(confmax.values.min(), confmax.values.max())
colors = plt.cm.Greens(norm(confmax))

#Generate frequency plot
plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = colors,  order=freq_order, ax=axs[0])




#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
z=plot.get_ymajorticklabels()
plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for ticklabel in plot.get_yticklabels()], fontsize = 10)
plot.set(ylabel=None)
plot.set(xlabel="Detections")


#Generate crosstab matrix for heatmap plot

heat = pd.crosstab(df_plt_top10_today['Com_Name'],df_plt_top10_today['Hour of Day'])
#Order heatmap Birds by frequency of occurrance
heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
heat.sort_index(level=0, inplace=True)


hours_in_day = pd.Series(data = range(0,24))
heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day)
heat=(heat+heat_frame).fillna(0)

#Generatie heatmap plot
plot = sns.heatmap(heat, norm=LogNorm(),  annot=True,  annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)

# Set heatmap border
for _, spine in plot.spines.items():
    spine.set_visible(True)

plot.set(ylabel=None)
plot.set(xlabel="Hour of Day")
#Set combined plot layout and titles
f.subplots_adjust(top=0.9)
plt.suptitle("Top 10 Last Updated: "+ str(now.strftime("%Y-%m-%d %H:%M")))

#Save combined plot
savename='/home/pi/BirdSongs/Extracted/Charts/Combo-'+str(now.strftime("%Y-%m-%d"))+'.png'
plt.savefig(savename)
plt.show()
plt.close()


# Get Bottom detection frequency
plt_Bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_Bot10_today.index)]

#Set Palette for graphics
pal = "Reds"

#Set up plot axes and titles

f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487')
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)

#generate y-axis order for all figures based on frequency
freq_order = pd.value_counts(df_plt_Bot10_today['Com_Name']).iloc[-readings:].index

#make color for max confidence --> this groups by name and calculates max conf
confmax = df_plt_Bot10_today.groupby('Com_Name')['Confidence'].max()
confmax = confmax.reindex(freq_order)
# probably wrong order . . . how to sort by no. of detections ?
# norm values for color palette
norm = plt.Normalize(confmax.values.min(), confmax.values.max())
colors = plt.cm.Reds(norm(confmax))

#Generate frequency plot
plot=sns.countplot(y='Com_Name', data = df_plt_Bot10_today, palette = colors,  order=freq_order, ax=axs[0])




#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
z=plot.get_ymajorticklabels()
plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for ticklabel in plot.get_yticklabels()], fontsize = 10)
plot.set(ylabel=None)
plot.set(xlabel="Detections")

#Generate crosstab matrix for heatmap plot

heat = pd.crosstab(df_plt_Bot10_today['Com_Name'],df_plt_Bot10_today['Hour of Day'])
#Order heatmap Birds by frequency of occurrance
heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
heat.sort_index(level=0, inplace=True)


hours_in_day = pd.Series(data = range(0,24))
heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day)
heat=(heat+heat_frame).fillna(0)

#Generatie heatmap plot
plot = sns.heatmap(heat, norm=LogNorm(),  annot=True,  annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)

# Set heatmap border
for _, spine in plot.spines.items():
    spine.set_visible(True)

plot.set(ylabel=None)
plot.set(xlabel="Hour of Day")
#Set combined plot layout and titles
f.subplots_adjust(top=0.9)
plt.suptitle("Bottom 10 Last Updated: "+ str(now.strftime("%Y-%m-%d %H:%M")))

#Save combined plot
savename='/home/pi/BirdSongs/Extracted/Charts/Combo2-'+str(now.strftime("%Y-%m-%d"))+'.png'
plt.savefig(savename)
plt.show()
plt.close()