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feat: New detail view plot for vaccination done date plot

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Benedikt Bastin 2021-04-24 12:05:52 +02:00
parent b02d05a1d5
commit 8e99015d77
1 changed files with 50 additions and 8 deletions
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58
plot.py
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@ -757,23 +757,16 @@ def plot_vaccination_done_dates():
)
d = data_first_vaccination
#print(d['cumulative'])
#print(np.sum(d['daily']))
#print((einwohner_deutschland - d['cumulative'])[:-1] - d['to_be_vaccinated'])
days_remaining_daily = np.ceil((einwohner_deutschland * 0.7 - d['cumulative']) / (d['mean_vaccination_rates_daily']))
days_remaining_rolling = np.ceil((einwohner_deutschland * 0.7 - d['cumulative']) / (d['vaccination_rates_daily_rolling_average']))
dates_daily = [today + datetime.timedelta(days) for days in days_remaining_daily]
dates_rolling = [today + datetime.timedelta(days) for days in days_remaining_rolling.dropna()]
#print(dates_rolling)
ax.set_xlim(start_of_reporting_date, today)
ax.set_ylim(today, today + datetime.timedelta(int(np.max(days_remaining_rolling) * 1.05)))
ax.axhline(target_date_for_herd_immunity - datetime.timedelta(21), label='Impfziel Ende Sommer')
ax.add_patch(Rectangle((datetime.date(2021, 4, 6), today), today - datetime.date(2021, 4, 6), target_date_for_herd_immunity - today, edgecolor='darkgrey', lw=3, fill=False, label='Detailansicht (s.u.)'))
ax.plot(dates, dates_daily, label='Durchschnitt Gesamt', linewidth=0.5)
ax.plot(dates[6:], dates_rolling, label='Durchschnitt 7 Tage', linewidth=2)
@ -793,6 +786,51 @@ def plot_vaccination_done_dates():
plot_vaccination_done_dates()
def plot_vaccination_done_dates_detail():
plot_name = 'vaccination_done_dates_detail'
if not check_recreate_plot(plot_name):
return
fig, ax = plt.subplots(1)
plt.title(
'Lin. Extrapolation der Erstimpfungen bis 70 % der Bevölkerung anhand der durchschn. Impfrate (Detail, Datum, Gesamt und 7 Tage)\n'
'Datenquelle: RKI, Stand: {}. Erstellung: {}, Ersteller: Benedikt Bastin, Lizenz: CC BY-SA 4.0\n'.format(
print_stand, print_today
)
)
d = data_first_vaccination
days_remaining_daily = np.ceil((einwohner_deutschland * 0.7 - d['cumulative']) / (d['mean_vaccination_rates_daily']))
days_remaining_rolling = np.ceil((einwohner_deutschland * 0.7 - d['cumulative']) / (d['vaccination_rates_daily_rolling_average']))
dates_daily = [today + datetime.timedelta(days) for days in days_remaining_daily]
dates_rolling = [today + datetime.timedelta(days) for days in days_remaining_rolling.dropna()]
ax.set_xlim(datetime.date(2021, 4, 6), today)
ax.set_ylim(today, target_date_for_herd_immunity)
ax.axhline(target_date_for_herd_immunity - datetime.timedelta(21), label='Impfziel Ende Sommer')
ax.plot(dates, dates_daily, label='Durchschnitt Gesamt', linewidth=0.5)
ax.plot(dates[6:], dates_rolling, label='Durchschnitt 7 Tage', linewidth=2)
ax.grid(True)
ax.legend(loc='upper right')
ax.set_xlabel('Datum')
ax.set_ylabel('Datum, an dem 70 % erreicht sind')
add_annotations(ax)
save_plot(plot_name)
plt.close()
plot_vaccination_done_dates_detail()
def render_dashboard():
dashboard_filename = 'site/index.xhtml'
dashboard_archive_filename = 'site/archive/{}/index.xhtml'.format(filename_stand)
@ -880,6 +918,10 @@ def render_dashboard():
'index': 12,
'filename': 'vaccination_done_dates',
'caption': 'Lineare Extrapolation bis 70 % der Bevölkerung anhand der Erstimpfungen der durchschnittlichen Impfrate (Datum, Gesamt und 7 Tage)'
},{
'index': 13,
'filename': 'vaccination_done_dates_detail',
'caption': 'Lineare Extrapolation bis 70 % der Bevölkerung anhand der Erstimpfungen der durchschnittlichen Impfrate (Datum, Gesamt und 7 Tage)'
}
]
).dump('site/index.xhtml')