mirror of
https://github.com/bbilly1/aqi_monitor.git
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96 lines
2.6 KiB
Python
96 lines
2.6 KiB
Python
""" creates the PM 2.5 and pm 10 graphs """
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from datetime import datetime
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from matplotlib import pyplot as plt
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import numpy as np
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import pandas as pd
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from app.db_connect import db_connect, db_close
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def get_pm_data(config):
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""" gets last 10 days worth of data"""
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now = datetime.now()
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day_until = int(now.date().strftime('%s'))
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day_from = day_until - 10 * 24 * 60 * 60
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conn, cur = db_connect(config)
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cur.execute(
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f'SELECT epoch_time, pm25, pm10 FROM aqi \
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WHERE epoch_time > {day_from} \
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AND epoch_time < {day_until} \
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ORDER BY epoch_time DESC;'
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)
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rows = cur.fetchall()
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db_close(conn, cur)
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return rows
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def get_pm_axis(rows):
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""" build axis """
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# build dataframe
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x_timeline = [datetime.fromtimestamp(i[0]) for i in rows]
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y_pm25_values = [int(i[1]) for i in rows]
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y_pm10_values = [int(i[2]) for i in rows]
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data = {
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'timestamp': x_timeline,
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'pm25': y_pm25_values,
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'pm10': y_pm10_values
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}
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df = pd.DataFrame(data)
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indexed = df.set_index('timestamp')
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indexed.sort_values(by=['timestamp'], inplace=True, ascending=True)
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mean = indexed.resample('1d').mean()
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mean.reset_index(level=0, inplace=True)
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# axis
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mean['pm25'] = mean['pm25'].round()
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mean['pm10'] = mean['pm10'].round()
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x = mean['timestamp']
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y_1 = mean['pm25']
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y_2 = mean['pm10']
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return x, y_1, y_2
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def build_pm_plot(x, y, y_max, thresh, title):
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""" write plots to file """
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file_name = title.replace('.', '')
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# make ticks
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x_range = np.arange(10).tolist()
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x_date_time = pd.to_datetime(x).dt.date.unique()
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x_dates = [i.strftime('%d %b') for i in x_date_time]
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# color
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col = []
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for val in y:
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if val < thresh:
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col.append('#00cc00')
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else:
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col.append('#cc0000')
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# title
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plt_title = f'PM {title} values for last 10 days'
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# plot
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plt.style.use('seaborn')
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plt.bar(x_dates, y, color=col, width=0.5)
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plt.axhline(y=thresh, color='#00cc00', linestyle=':')
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plt.xticks(ticks=x_range, labels=x_dates)
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plt.yticks(np.arange(0, y_max, step=25))
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plt.title(plt_title)
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plt.tight_layout()
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plt.savefig(f'dyn/pm{file_name}.png', dpi=300)
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plt.close('all')
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plt.figure()
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def rebuild_pm_bar(config):
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""" rebuild pm2.5 and pm10 values """
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rows = get_pm_data(config)
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x, y_1, y_2 = get_pm_axis(rows)
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# max
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y_max = np.ceil(max(y_1.append(y_2))/25)*25 + 25
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# pm 2.5
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build_pm_plot(x, y_1, y_max, thresh=25, title='2.5')
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# pm 10
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build_pm_plot(x, y_2, y_max, thresh=50, title='10')
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# done
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print('recreated PM 2.5 and PM 10 graphs')
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