mirror of
https://github.com/bbilly1/aqi_monitor.git
synced 2024-08-02 16:03:33 +00:00
94 lines
3.2 KiB
Python
94 lines
3.2 KiB
Python
""" makes the nice plots """
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from datetime import datetime, timedelta
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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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import psycopg2
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from app.db_connect import db_connect, db_close
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def create_current(config):
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""" recreate current graph """
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# last three hours
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now = datetime.now()
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now_human = now.strftime('%c')
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now_epoch = int(now.strftime('%s'))
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last_3h = now_epoch - 3 * 60 * 60
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last_3h_limit = int(60 * 3)
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# connect
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conn, cur = db_connect(config)
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# get data
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cur.execute(
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f'SELECT epoch_time, aqi_value FROM aqi \
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WHERE epoch_time > {last_3h} ORDER BY epoch_time DESC \
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LIMIT {last_3h_limit};')
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rows = cur.fetchall()
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# close db
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db_close(conn, cur)
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# set title
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data_from = now.strftime("%Y-%m-%d")
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time_from = datetime.fromtimestamp(rows[-1][0]).strftime('%H:%M')
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time_until = datetime.fromtimestamp(rows[0][0]).strftime('%H:%M')
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plt_title = f'AQI values from: {data_from} {time_from} - {time_until}'
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# parse rows
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sample_rate = '3min'
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x, y = build_plt(rows, sample_rate)
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# calc x_ticks
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x_ticks = []
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for num, i in enumerate(x):
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minute = int(i.split(':')[1])
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if minute % 15 == 0:
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x_ticks.append(num)
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# write plt
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file_name = 'current'
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write_plt(x, y, plt_title, x_ticks, file_name)
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message = f'recreated current graph: {now_human}'
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print(message)
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def build_plt(rows, sample_rate):
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""" parse rows returns axis"""
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# build x y
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x_timeline = [datetime.fromtimestamp(i[0]) for i in rows]
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y_aqi_values = [int(i[1]) for i in rows]
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# build dataframe
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data = {'timestamp': x_timeline, 'aqi': y_aqi_values}
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df = pd.DataFrame(data)
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# reindex as timeseries
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indexed = df.set_index('timestamp')
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indexed.sort_values(by=['timestamp'], inplace=True)
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mean = indexed.resample(sample_rate).mean()
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mean.reset_index(level=0, inplace=True)
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mean['timestamp'] = mean['timestamp'].dt.strftime('%H:%M')
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mean['aqi'] = mean['aqi'].round()
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# set axis
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x = mean['timestamp']
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y = mean['aqi']
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# build title
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return x, y
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def write_plt(x, y, plt_title, x_ticks, file_name):
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""" save plot to file """
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# calc ticks
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y_max = np.ceil(y.max()/50)*50 + 50
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# setup plot
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plt.style.use('seaborn')
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plt.plot(x, y, color='#313131',)
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plt.fill_between(x, y, y2=0, where=(y > 0), color='#85a762', interpolate=True) # good
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plt.fill_between(x, y, y2=50, where=(y > 50), color='#d4b93c', interpolate=True) # moderate
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plt.fill_between(x, y, y2=100, where=(y > 100), color='#e96843', interpolate=True) # ufsg
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plt.fill_between(x, y, y2=150, where=(y > 150), color='#d03f3b', interpolate=True) # unhealthy
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plt.fill_between(x, y, y2=200, where=(y > 200), color='#be4173', interpolate=True) # vunhealthy
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plt.fill_between(x, y, y2=300, where=(y > 300), color='#714261', interpolate=True) # hazardous
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plt.fill_between(x, y, y2=0, where=(y > 0), color='#ffffff', alpha=0.1, interpolate=True) # soft
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plt.xticks(x_ticks)
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plt.yticks(np.arange(0, y_max, step=50))
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plt.title(plt_title)
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plt.tight_layout()
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plt.savefig(f'dyn/{file_name}.png', dpi = 300)
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plt.figure()
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