frederik
200 lines
7.3 KiB
Python
Executable File
200 lines
7.3 KiB
Python
Executable File
import argparse
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import os
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import sqlite3
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import textwrap
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from datetime import datetime
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from time import sleep
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import matplotlib.font_manager as font_manager
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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import seaborn as sns
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from matplotlib import rcParams
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from matplotlib.colors import LogNorm
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from utils.helpers import DB_PATH, get_settings
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def get_data(now=None):
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conn = sqlite3.connect(DB_PATH)
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if now is None:
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now = datetime.now()
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df = pd.read_sql_query(f"SELECT * from detections WHERE Date = DATE('{now.strftime('%Y-%m-%d')}')",
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conn)
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# Convert Date and Time Fields to Panda's format
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df['Date'] = pd.to_datetime(df['Date'])
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df['Time'] = pd.to_datetime(df['Time'], unit='ns')
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# Add round hours to dataframe
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df['Hour of Day'] = [r.hour for r in df.Time]
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return df, now
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# Function to show value on bars - from https://stackoverflow.com/questions/43214978/seaborn-barplot-displaying-values
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def show_values_on_bars(ax, label):
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for i, p in enumerate(ax.patches):
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x = p.get_x() + p.get_width() * 0.9
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y = p.get_y() + p.get_height() / 2
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# Species confidence
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# value = '{:.0%}'.format(label.iloc[i])
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# Species Count Total
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value = '{:n}'.format(p.get_width())
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bbox = {'facecolor': 'lightgrey', 'edgecolor': 'none', 'pad': 1.0}
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ax.text(x, y, value, bbox=bbox, ha='center', va='center', size=9, color='darkgreen')
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def create_plot(df_plt_today, now, is_top=None):
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if is_top is not None:
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readings = 10
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if is_top:
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plt_selection_today = (df_plt_today['Com_Name'].value_counts()[:readings])
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else:
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plt_selection_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
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else:
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plt_selection_today = df_plt_today['Com_Name'].value_counts()
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readings = len(df_plt_today['Com_Name'].value_counts())
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df_plt_selection_today = df_plt_today[df_plt_today.Com_Name.isin(plt_selection_today.index)]
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# Set up plot axes and titles
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height = max(readings / 3, 0) + 1.06
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f, axs = plt.subplots(1, 2, figsize=(10, height), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487')
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# generate y-axis order for all figures based on frequency
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freq_order = df_plt_selection_today['Com_Name'].value_counts().index
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# make color for max confidence --> this groups by name and calculates max conf
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confmax = df_plt_selection_today.groupby('Com_Name')['Confidence'].max()
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# reorder confmax to detection frequency order
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confmax = confmax.reindex(freq_order)
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# norm values for color palette
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norm = plt.Normalize(confmax.values.min(), confmax.values.max())
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if is_top or is_top is None:
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# Set Palette for graphics
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pal = "Greens"
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colors = plt.cm.Greens(norm(confmax)).tolist()
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if is_top:
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plot_type = "Top"
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else:
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plot_type = 'All'
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name = "Combo"
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else:
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# Set Palette for graphics
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pal = "Reds"
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colors = plt.cm.Reds(norm(confmax)).tolist()
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plot_type = "Bottom"
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name = "Combo2"
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# Generate frequency plot
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plot = sns.countplot(y='Com_Name', hue='Com_Name', legend=False, data=df_plt_selection_today,
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palette=colors, order=freq_order, ax=axs[0])
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# Prints Max Confidence on bars
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show_values_on_bars(axs[0], confmax)
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# Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
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yticklabels = ['\n'.join(textwrap.wrap(ticklabel.get_text(), 16)) for ticklabel in plot.get_yticklabels()]
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# Next two lines avoid a UserWarning on set_ticklabels() requesting a fixed number of ticks
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yticks = plot.get_yticks()
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plot.set_yticks(yticks)
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plot.set_yticklabels(yticklabels, fontsize=10)
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plot.set(ylabel=None)
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plot.set(xlabel="Detections")
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# Generate crosstab matrix for heatmap plot
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heat = pd.crosstab(df_plt_selection_today['Com_Name'], df_plt_selection_today['Hour of Day'])
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# Order heatmap Birds by frequency of occurrance
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heat.index = pd.CategoricalIndex(heat.index, categories=freq_order)
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heat.sort_index(level=0, inplace=True)
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hours_in_day = pd.Series(data=range(0, 24))
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heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day)
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heat = (heat+heat_frame).fillna(0)
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# mask out zeros, so they do not show up in the final plot. this happens when max count/h is one
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heat[heat == 0] = np.nan
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# Generatie heatmap plot
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plot = sns.heatmap(heat, norm=LogNorm(), annot=True, annot_kws={"fontsize": 7}, fmt="g", cmap=pal, square=False,
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cbar=False, linewidths=0.5, linecolor="Grey", ax=axs[1], yticklabels=False)
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# Set color and weight of tick label for current hour
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for label in plot.get_xticklabels():
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if int(label.get_text()) == now.hour:
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label.set_color('yellow')
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plot.set_xticklabels(plot.get_xticklabels(), rotation=0, size=8)
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# Set heatmap border
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for _, spine in plot.spines.items():
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spine.set_visible(True)
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plot.set(ylabel=None)
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plot.set(xlabel="Hour of Day")
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# Set combined plot layout and titles
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y = 1 - 8 / (height * 100)
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plt.suptitle(f"{plot_type} {readings} Last Updated: {now.strftime('%Y-%m-%d %H:%M')}", y=y)
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f.tight_layout()
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top = 1 - 40 / (height * 100)
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f.subplots_adjust(left=0.125, right=0.9, top=top, wspace=0)
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# Save combined plot
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save_name = os.path.expanduser(f"~/BirdSongs/Extracted/Charts/{name}-{now.strftime('%Y-%m-%d')}.png")
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plt.savefig(save_name)
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plt.show()
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plt.close()
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def load_fonts():
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conf = get_settings()
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# Add every font at the specified location
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font_dir = [os.path.expanduser('~/BirdNET-Pi/homepage/static')]
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for font in font_manager.findSystemFonts(font_dir, fontext='ttf'):
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font_manager.fontManager.addfont(font)
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# Set font family globally
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if conf['DATABASE_LANG'] in ['ja', 'zh']:
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rcParams['font.family'] = 'Noto Sans JP'
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elif conf['DATABASE_LANG'] == 'th':
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rcParams['font.family'] = 'Noto Sans Thai'
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else:
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rcParams['font.family'] = 'Roboto Flex'
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def main(daemon, sleep_m):
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load_fonts()
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last_run = None
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while True:
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now = datetime.now()
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# now = datetime.strptime('2023-12-13T23:59:59', "%Y-%m-%dT%H:%M:%S")
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# now = datetime.strptime('2024-01-02T23:59:59', "%Y-%m-%dT%H:%M:%S")
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# now = datetime.strptime('2024-02-26T23:59:59', "%Y-%m-%dT%H:%M:%S")
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# now = datetime.strptime('2024-04-03T23:59:59', "%Y-%m-%dT%H:%M:%S")
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# now = datetime.strptime('2024-04-07T23:59:59', "%Y-%m-%dT%H:%M:%S")
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if last_run and now.day != last_run.day:
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print("getting yesterday's dataset")
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yesterday = last_run.replace(hour=23, minute=59)
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data, time = get_data(yesterday)
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else:
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data, time = get_data(now)
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if not data.empty:
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create_plot(data, time)
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else:
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print('empty dataset')
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if daemon:
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last_run = now
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sleep(60 * sleep_m)
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else:
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break
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--daemon', action='store_true')
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parser.add_argument('--sleep', default=2, type=int, help='Time between runs (minutes)')
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args = parser.parse_args()
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main(args.daemon, args.sleep)
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