import argparse

import os

import sqlite3

import textwrap

from datetime import datetime

from time import sleep

import matplotlib.font_manager as font_manager

import matplotlib.pyplot as plt

import numpy as np

import pandas as pd

import seaborn as sns

from matplotlib import rcParams

from matplotlib.colors import LogNorm

from utils.helpers import DB_PATH, FONT_DIR, get_settings, get_font

def get_data(now=None):

uri = f"file:{DB_PATH}?mode=ro"

conn = sqlite3.connect(uri, uri=True)

if now is None:

now = datetime.now()

df = pd.read_sql_query(f"SELECT * from detections WHERE Date = DATE('{now.strftime('%Y-%m-%d')}')",

conn)

# 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]

return df, now

# Function to show value on bars - from https://stackoverflow.com/questions/43214978/seaborn-barplot-displaying-values

def show_values_on_bars(ax, label):

conf = get_settings()

for i, p in enumerate(ax.patches):

x = p.get_x() + p.get_width() * 0.9

y = p.get_y() + p.get_height() / 2

# Species confidence

# value = '{:.0%}'.format(label.iloc[i])

# Species Count Total

value = '{:n}'.format(p.get_width())

bbox = {'facecolor': 'lightgrey', 'edgecolor': 'none', 'pad': 1.0}

if conf['COLOR_SCHEME'] == "dark":

color = 'black'

else:

color = 'darkgreen'

ax.text(x, y, value, bbox=bbox, ha='center', va='center', size=9, color=color)

def wrap_width(txt):

# try to estimate wrap width

w = 16

for c in txt:

if c in ['M', 'm', 'W', 'w']:

w -= 0.33

if c in ['I', 'i', 'j', 'l']:

w += 0.33

return round(w)

def create_plot(df_plt_today, now, is_top=None):

if is_top is not None:

readings = 10

if is_top:

plt_selection_today = (df_plt_today['Com_Name'].value_counts()[:readings])

else:

plt_selection_today = (df_plt_today['Com_Name'].value_counts()[-readings:])

else:

plt_selection_today = df_plt_today['Com_Name'].value_counts()

readings = len(df_plt_today['Com_Name'].value_counts())

df_plt_selection_today = df_plt_today[df_plt_today.Com_Name.isin(plt_selection_today.index)]

conf = get_settings()

# Set up plot axes and titles

height = max(readings / 3, 0) + 1.06

if conf['COLOR_SCHEME'] == "dark":

facecolor = 'darkgrey'

else:

facecolor = '#77C487'

f, axs = plt.subplots(1, 2, figsize=(10, height), gridspec_kw=dict(width_ratios=[3, 6]), facecolor=facecolor)

# generate y-axis order for all figures based on frequency

freq_order = df_plt_selection_today['Com_Name'].value_counts().index

# make color for max confidence --> this groups by name and calculates max conf

confmax = df_plt_selection_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())

if is_top or is_top is None:

# Set Palette for graphics

if conf['COLOR_SCHEME'] == "dark":

pal = "Greys"

colors = plt.cm.Greys(norm(confmax)).tolist()

else:

pal = "Greens"

colors = plt.cm.Greens(norm(confmax)).tolist()

if is_top:

plot_type = "Top"

else:

plot_type = 'All'

name = "Combo"

else:

# Set Palette for graphics

pal = "Reds"

colors = plt.cm.Reds(norm(confmax)).tolist()

plot_type = "Bottom"

name = "Combo2"

# Generate frequency plot

plot = sns.countplot(y='Com_Name', hue='Com_Name', legend=False, data=df_plt_selection_today,

palette=dict(zip(confmax.index, colors)), order=freq_order, ax=axs[0], edgecolor='lightgrey')

# Prints Max Confidence on bars

show_values_on_bars(axs[0], confmax)

# Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars

yticklabels = ['\n'.join(textwrap.wrap(ticklabel.get_text(), wrap_width(ticklabel.get_text()))) for ticklabel in plot.get_yticklabels()]

# Next two lines avoid a UserWarning on set_ticklabels() requesting a fixed number of ticks

yticks = plot.get_yticks()

plot.set_yticks(yticks)

plot.set_yticklabels(yticklabels, fontsize=10)

plot.set(ylabel=None)

plot.set(xlabel="Detections")

# Generate crosstab matrix for heatmap plot

heat = pd.crosstab(df_plt_selection_today['Com_Name'], df_plt_selection_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)

# mask out zeros, so they do not show up in the final plot. this happens when max count/h is one

heat[heat == 0] = np.nan

# Generatie heatmap plot

plot = sns.heatmap(heat, norm=LogNorm(), annot=True, annot_kws={"fontsize": 7}, fmt="g", cmap=pal, square=False,

cbar=False, linewidths=0.5, linecolor="Grey", ax=axs[1], yticklabels=False)

# Set color and weight of tick label for current hour

for label in plot.get_xticklabels():

if int(label.get_text()) == now.hour:

if conf['COLOR_SCHEME'] == "dark":

label.set_color('white')

else:

label.set_color('yellow')

plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=8)

# 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

y = 1 - 8 / (height * 100)

plt.suptitle(f"{plot_type} {readings} Last Updated: {now.strftime('%Y-%m-%d %H:%M')}", y=y)

f.tight_layout()

top = 1 - 40 / (height * 100)

f.subplots_adjust(left=0.125, right=0.9, top=top, wspace=0)

# Save combined plot

save_name = os.path.expanduser(f"~/BirdSongs/Extracted/Charts/{name}-{now.strftime('%Y-%m-%d')}.png")

plt.savefig(save_name)

plt.show()

plt.close()

def load_fonts():

# Add every font at the specified location

font_dir = [FONT_DIR]

for font in font_manager.findSystemFonts(font_dir, fontext='ttf'):

font_manager.fontManager.addfont(font)

# Set font family globally

rcParams['font.family'] = get_font()['font.family']

def main(daemon, sleep_m):

load_fonts()

last_run = None

while True:

now = datetime.now()

# now = datetime.strptime('2023-12-13T23:59:59', "%Y-%m-%dT%H:%M:%S")

# now = datetime.strptime('2024-01-02T23:59:59', "%Y-%m-%dT%H:%M:%S")

# now = datetime.strptime('2024-02-26T23:59:59', "%Y-%m-%dT%H:%M:%S")

# now = datetime.strptime('2024-04-03T23:59:59', "%Y-%m-%dT%H:%M:%S")

# now = datetime.strptime('2024-04-07T23:59:59', "%Y-%m-%dT%H:%M:%S")

if last_run and now.day != last_run.day:

print("getting yesterday's dataset")

yesterday = last_run.replace(hour=23, minute=59)

data, time = get_data(yesterday)

else:

data, time = get_data(now)

if not data.empty:

create_plot(data, time)

else:

print('empty dataset')

if daemon:

last_run = now

sleep(60 * sleep_m)

else:

break

if __name__ == '__main__':

parser = argparse.ArgumentParser()

parser.add_argument('--daemon', action='store_true')

parser.add_argument('--sleep', default=2, type=int, help='Time between runs (minutes)')

args = parser.parse_args()

main(args.daemon, args.sleep)