AvianVisitors/scripts/daily_plot.py

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

import sqlite3
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

conn = sqlite3.connect('/home/pi/BirdNET-Pi/scripts/birds.db')
df = pd.read_sql_query("SELECT * from detections", conn)
cursor = conn.cursor()
cursor.execute('SELECT * FROM detections')

table_rows = 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()