plot.py

@@ -15,14 +15,10 @@ import locale
 import os.path
 import shutil
 import math
-from functools import reduce
 
-from matplotlib.dates import date2num, DateFormatter, WeekdayLocator
+from matplotlib.dates import date2num
-import matplotlib.dates as mdates
 import matplotlib.ticker as mtick
 
-from isoweek import Week
-
 locale.setlocale(locale.LC_ALL, 'de_DE.UTF-8')
 
 site_folder = 'site/'
@@ -37,7 +33,7 @@ print_today = today.isoformat()
 
 filename_now = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
 
-force_renew = True
+
 
 # https://www.tagesschau.de/ausland/europa/ursula-von-der-leyen-zu-corona-impfstoffen-101.html
 target_date_for_herd_immunity = datetime.date(2021, 9, 22)
@@ -65,7 +61,7 @@ raw_data = rki_file['Impfungen_proTag']
 
 impfungen = raw_data[:-1].dropna(subset=['Datum'])#.fillna(0)
 
-impfungen.drop(impfungen.tail(3).index,inplace=True) # remove Gesamt row
+impfungen.drop(impfungen.tail(1).index,inplace=True) # remove Gesamt row
 
 dates = impfungen['Datum']
 
@@ -91,17 +87,6 @@ def calculate_vaccination_data(data):
 	mean_all_time = np.mean(valid_data)
 	mean_seven_days = np.mean(data[-7:])
 
-	vaccinations_by_week_map = map(lambda x: (Week.withdate(x[0]), x[1]), zip(dates, data))
-
-	vaccinations_by_week = {}
-
-	for w, v in vaccinations_by_week_map:
-		if w in vaccinations_by_week:
-			vaccinations_by_week[w] = vaccinations_by_week[w] + v
-		else:
-			vaccinations_by_week[w] = v
-
-
 	def extrapolate(rate, to_be_vaccinated):
 		days_extrapolated = int(np.ceil(to_be_vaccinated / rate))
 		extrapolated_dates = np.array([dates[0] + datetime.timedelta(days=i) for i in range(days_extrapolated)])
@@ -146,7 +131,6 @@ def calculate_vaccination_data(data):
 		'days_since_start': days_since_start_of_vaccination + 1, # Shift from zero to one-based-index
 		'start_of_vaccination_date': start_of_vaccination_date,
 		'start_of_vaccination_date_str': start_of_vaccination_date.strftime('%d. %B %Y'),
-		'vaccinations_by_week': vaccinations_by_week,
 		'extrapolation_mean_all_time': extrapolation_mean_all_time,
 		'extrapolation_last_rate': extrapolation_last_rate,
 		'extrapolation_mean_seven_days': extrapolation_mean_seven_days,
@@ -287,12 +271,90 @@ else:
 
 
 
+
+def plot_extrapolation_portion(percentage):
+
+	print_percentage = int(percentage * 100)
+	archive_plot_filename = '{}/extrapolated_to_{}_percent'.format(archive_folder, print_percentage)
+	latest_plot_filename = '{}/extrapolated_to_{}_percent'.format(site_folder, print_percentage)
+
+	if os.path.isfile(archive_plot_filename + '.pdf'):
+		print('Plot {} already exists'.format(archive_plot_filename))
+		return
+
+	fig, ax = plt.subplots(1)
+
+
+	plt.title(
+		'Tägliche Impfrate (Erst- und Zweitimpfung übereinander), kumulierte Impfungen und lineare Extrapolation bis {:n} % der Bevölkerung Deutschlands\n'
+		'Datenquelle: RKI, Stand: {}. Erstellung: {}, Ersteller: Benedikt Bastin, Lizenz: CC BY-SA 4.0\n'
+		'Erstimpfungen: {:n} ({:n} %), Durchschnittliche Impfrate: {:n} Impfungen/Tag (läuft seit {:n} Tagen)\n'
+		'Zweitimpfungen: {:n} ({:n} %), Durchschnittliche Impfrate: {:n} Impfungen/Tag (läuft seit {:n} Tagen)'.format(
+			print_percentage,
+			print_stand, print_today,
+			data_first_vaccination['total'], np.round(data_first_vaccination['total_percentage'], 2), data_first_vaccination['extrapolation_mean_all_time']['rate'], data_first_vaccination['days_since_start'],
+			data_second_vaccination['total'], np.round(data_second_vaccination['total_percentage'], 2), data_second_vaccination['extrapolation_mean_all_time']['rate'], data_second_vaccination['days_since_start']
+		)
+	)
+
+	ax2 = ax.twinx()
+
+	ax.bar(dates, data_first_vaccination['daily'], label='Tägliche Erstimpfungen', color='blue')
+	ax.bar(dates, data_second_vaccination['daily'], label='Tägliche Zweitimpfungen', color='lightblue', bottom=data_first_vaccination['daily'])
+
+	ax.plot(dates, data_first_vaccination['mean_vaccination_rates_daily'], color='violet', label='Durchschnittliche Erstimpfrate\nbis zu diesem Tag (inkl.)')
+	ax.plot(dates, data_second_vaccination['mean_vaccination_rates_daily'], color='magenta', label='Durchschnittliche Zweitimpfrate\nbis zu diesem Tag (inkl.)')
+
+	ax2.set_ylim([0, einwohner_deutschland * percentage])
+	ax2.set_xlim(xmax=dates[0] + datetime.timedelta(days=percentage * data_first_vaccination['extrapolation_mean_all_time']['days_extrapolated']))
+	ax2.grid(True)
+
+	ax2.plot(dates, data_first_vaccination['cumulative'], color='red', label='Kumulierte Erstimpfungen')
+	ax2.plot(dates, data_second_vaccination['cumulative'], color='indianred', label='Kumulierte Zweitimpfungen')
+
+	ax2.plot(data_first_vaccination['extrapolation_mean_all_time']['dates'], data_first_vaccination['extrapolation_mean_all_time']['extrapolated_vaccinations'], color='orange', label='Extrap. kumulierte Erstimpfungen (Ø gesamt)\n{:n} Impfungen/Tag'.format(data_first_vaccination['extrapolation_mean_all_time']['rate_int']))
+	ax2.plot(data_first_vaccination['extrapolation_mean_seven_days']['dates'], data_first_vaccination['extrapolation_mean_seven_days']['extrapolated_vaccinations'], color='goldenrod', label='Extrap. kumulierte Erstimpfungen (Ø 7 Tage)\n{:n} Impfungen/Tag'.format(data_first_vaccination['extrapolation_mean_seven_days']['rate_int']))
+	ax2.plot()
+
+	ax2.plot(data_second_vaccination['extrapolation_mean_all_time']['dates'], data_second_vaccination['extrapolation_mean_all_time']['extrapolated_vaccinations'], color='orange', label='Extrap. kumulierte Zweitimpfungen (Ø gesamt)\n{:n} Impfungen/Tag'.format(data_second_vaccination['extrapolation_mean_all_time']['rate_int']))
+	ax2.plot(data_second_vaccination['extrapolation_mean_seven_days']['dates'], data_second_vaccination['extrapolation_mean_seven_days']['extrapolated_vaccinations'], color='goldenrod', label='Extrap. kumulierte Zweitimpfungen (Ø 7 Tage)\n{:n} Impfungen/Tag'.format(data_second_vaccination['extrapolation_mean_seven_days']['rate_int']))
+	#ax2.plot()
+
+	ax.legend(loc='upper left')
+	ax.get_yaxis().get_major_formatter().set_scientific(False)
+
+	ax.set_xlabel('Datum')
+	ax.set_ylabel('Tägliche Impfungen')
+
+	ax2.legend(loc='lower right')
+	ax2.get_yaxis().get_major_formatter().set_scientific(False)
+
+	# Estimated percentage for herd immunity
+	#ax2.axline((0, einwohner_deutschland * 0.7), slope=0, color='green')
+
+	ax2.set_ylabel('Kumulierte Impfungen')
+
+	plt.savefig(archive_plot_filename + '.pdf')
+	plt.savefig(archive_plot_filename + '.png')
+	plt.savefig(latest_plot_filename + '.pdf')
+	plt.savefig(latest_plot_filename + '.png')
+	plt.close()
+
+	print('Created plot {} as pdf and png'.format(archive_plot_filename))
+
+
+plot_extrapolation_portion(0.1)
+#plot_extrapolation_portion(0.7)
+plot_extrapolation_portion(1.0)
+
+
+
 def plot_vaccination_bar_graph_total_time():
 
 	archive_plot_filename = '{}/vaccination_bar_graph_total_time'.format(archive_folder)
 	latest_plot_filename = '{}/vaccination_bar_graph_total_time'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -330,76 +392,12 @@ def plot_vaccination_bar_graph_total_time():
 
 plot_vaccination_bar_graph_total_time()
 
-def plot_vaccination_bar_graph_total_time_by_week():
-
-	archive_plot_filename = '{}/vaccination_bar_graph_total_time_by_week'.format(archive_folder)
-	latest_plot_filename = '{}/vaccination_bar_graph_total_time_by_week'.format(site_folder)
-
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
-		print('Plot {} already exists'.format(archive_plot_filename))
-		return
-
-	fig, ax = plt.subplots(1)
-
-
-	plt.title(
-		'Wöchentliche Impfrate (Erst- und Zweitimpfung übereinander)\n'
-			'Datenquelle: RKI, Stand: {}. Erstellung: {}, Ersteller: Benedikt Bastin, Lizenz: CC BY-SA 4.0\n'.format(
-			print_stand, print_today
-		)
-	)
-
-	ax.grid()
-
-	w = [w.day(3) for w in data_first_vaccination['vaccinations_by_week'].keys()]
-
-	f = list(data_first_vaccination['vaccinations_by_week'].values())
-	s = list(data_second_vaccination['vaccinations_by_week'].values())
-
-	bar1 = ax.bar(w, f, label='Wöchentliche Erstimpfungen', color='blue', width=6.8)
-	bar2 = ax.bar(w, s, label='Wöchentliche Zweitimpfungen', color='lightblue', width=6.8, bottom=f)
-
-	for r1, r2 in zip(bar1, bar2):
-
-		x = r1.get_x() + r1.get_width() / 2.0
-
-		h1 = math.floor(r1.get_height() / 1000)
-		h2 = math.floor(r2.get_height() / 1000)
-		hg = math.floor((r1.get_height() + r2.get_height()) / 1000)
-
-		if h1 > 30:
-			plt.text(x, h1 * 500, f'{h1:5n} k'.replace('.', ' '), ha='center', va='center', color='white')
-
-		if h2 > 30:
-			plt.text(x, h1 * 1000 + h2 * 500, f'{h2:5n} k'.replace('.', ' '), ha='center', va='center', color='black')
-
-		plt.text(x, hg * 1000, f'{hg:5n} k'.replace('.', ' '), ha='center', va='bottom')
-
-	ax.legend(loc='upper left')
-	ax.get_xaxis().set_major_formatter(DateFormatter('%Y-w%W'))
-	ax.get_xaxis().set_major_locator(WeekdayLocator(3, 2))
-	ax.get_yaxis().get_major_formatter().set_scientific(False)
-
-	ax.set_xlabel('Datum')
-	ax.set_ylabel('Wöchentliche Impfungen')
-
-
-	plt.savefig(archive_plot_filename + '.pdf')
-	plt.savefig(archive_plot_filename + '.png')
-	plt.savefig(latest_plot_filename + '.pdf')
-	plt.savefig(latest_plot_filename + '.png')
-	plt.close()
-
-	print('Created plot {} as pdf and png'.format(archive_plot_filename))
-
-plot_vaccination_bar_graph_total_time_by_week()
-
 def plot_vaccination_bar_graph_total_time_two_bars():
 
 	archive_plot_filename = '{}/vaccination_bar_graph_total_time_two_bars'.format(archive_folder)
 	latest_plot_filename = '{}/vaccination_bar_graph_total_time_two_bars'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -445,7 +443,7 @@ def plot_vaccination_bar_graph_compare_both_vaccinations():
 	archive_plot_filename = '{}/vaccination_bar_graph_compare_both_vaccinations'.format(archive_folder)
 	latest_plot_filename = '{}/vaccination_bar_graph_compare_both_vaccinations'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -491,7 +489,7 @@ def plot_cumulative_two_vaccinations():
 	archive_plot_filename = '{}/cumulative_two_vaccinations'.format(archive_folder)
 	latest_plot_filename = '{}/cumulative_two_vaccinations'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -538,7 +536,7 @@ def plot_cumulative_two_vaccinations_percentage():
 	archive_plot_filename = '{}/cumulative_two_vaccinations_percentage'.format(archive_folder)
 	latest_plot_filename = '{}/cumulative_two_vaccinations_percentage'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -587,7 +585,7 @@ def plot_people_between_first_and_second():
 	archive_plot_filename = '{}/people_between_first_and_second'.format(archive_folder)
 	latest_plot_filename = '{}/people_between_first_and_second'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -637,7 +635,7 @@ def plot_vaccination_rate():
 	archive_plot_filename = '{}/vaccination_rate'.format(archive_folder)
 	latest_plot_filename = '{}/vaccination_rate'.format(site_folder)
 
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
+	if os.path.isfile(archive_plot_filename + '.pdf'):
 		print('Plot {} already exists'.format(archive_plot_filename))
 		return
 
@@ -681,117 +679,13 @@ def plot_vaccination_rate():
 
 plot_vaccination_rate()
 
-def plot_vaccination_done_days():
-
-	archive_plot_filename = '{}/vaccination_done_days'.format(archive_folder)
-	latest_plot_filename = '{}/vaccination_done_days'.format(site_folder)
-
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
-		print('Plot {} already exists'.format(archive_plot_filename))
-		return
-
-	fig, ax = plt.subplots(1)
-
-
-	plt.title(
-		'Lin. Extrapolation der Erstimpfungen bis 70 % der Bevölkerung anhand der durchschn. Impfrate (Anzahl Tage, 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']))
-
-	ax.set_ylim(0, 2500)
-
-	ax.plot(dates, days_remaining_daily, label='Durchschnitt Gesamt', linewidth=0.5)
-	ax.plot(dates, days_remaining_rolling, label='Durchschnitt 7 Tage', linewidth=2)
-
-	ax.grid(True)
-
-
-	ax.legend(loc='upper right')
-	ax.get_yaxis().get_major_formatter().set_scientific(False)
-
-	ax.set_xlabel('Datum')
-	ax.set_ylabel('Tage, bis 70 % erreicht sind')
-
-	plt.savefig(archive_plot_filename + '.pdf')
-	plt.savefig(archive_plot_filename + '.png')
-	plt.savefig(latest_plot_filename + '.pdf')
-	plt.savefig(latest_plot_filename + '.png')
-	plt.close()
-
-	print('Created plot {} as pdf and png'.format(archive_plot_filename))
-
-plot_vaccination_done_days()
-
-def plot_vaccination_done_dates():
-
-	archive_plot_filename = '{}/vaccination_done_dates'.format(archive_folder)
-	latest_plot_filename = '{}/vaccination_done_dates'.format(site_folder)
-
-	if os.path.isfile(archive_plot_filename + '.pdf') and not force_renew:
-		print('Plot {} already exists'.format(archive_plot_filename))
-		return
-
-	fig, ax = plt.subplots(1)
-
-
-	plt.title(
-		'Lin. Extrapolation der Erstimpfungen bis 70 % der Bevölkerung anhand der durchschn. Impfrate (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
-
-	#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_ylim(today, today + datetime.timedelta(int(np.max(days_remaining_rolling) * 1.05)))
-
-	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')
-
-	plt.savefig(archive_plot_filename + '.pdf')
-	plt.savefig(archive_plot_filename + '.png')
-	plt.savefig(latest_plot_filename + '.pdf')
-	plt.savefig(latest_plot_filename + '.png')
-	plt.close()
-
-	print('Created plot {} as pdf and png'.format(archive_plot_filename))
-
-plot_vaccination_done_dates()
-
 def render_dashboard():
 	dashboard_filename = 'site/index.xhtml'
 	dashboard_archive_filename = 'site/archive/{}/index.xhtml'.format(filename_stand)
 	stylesheet_filename = 'site/rki-dashboard.css'
 	stylesheet_archive_filename = 'site/archive/{}/rki-dashboard.css'.format(filename_stand)
 
-	if os.path.isfile(dashboard_archive_filename) and not force_renew:
+	if os.path.isfile(dashboard_archive_filename):
 		print('Dashboard {} already exists'.format(dashboard_archive_filename))
 		return
 
@@ -826,44 +720,44 @@ def render_dashboard():
 		figures = [
 			{
 				'index': 1,
+				'filename': 'extrapolated_to_10_percent',
+				'caption': 'Tägliche Impfquote, kumulierte Impfungen und lineare Extrapolation bis 10 % der Bevölkerung Deutschlands'
+			},{
+				'index': 2,
+				'filename': 'extrapolated_to_70_percent',
+				'caption': 'Tägliche Impfquote, kumulierte Impfungen und lineare Extrapolation bis 70 % der Bevölkerung Deutschlands'
+			},{
+				'index': 3,
+				'filename': 'extrapolated_to_100_percent',
+				'caption': 'Tägliche Impfquote, kumulierte Impfungen und lineare Extrapolation bis 100 % der Bevölkerung Deutschlands'
+			},{
+				'index': 4,
 				'filename': 'vaccination_bar_graph_total_time',
 				'caption': 'Tägliche Impfrate (Erst- und Zweitimpfung übereinander)'
 			},{
-				'index': 2,
+				'index': 5,
-				'filename': 'vaccination_bar_graph_total_time_by_week',
-				'caption': 'Wöchentliche Impfrate (Erst- und Zweitimpfung übereinander)'
-			},{
-				'index': 3,
 				'filename': 'vaccination_bar_graph_total_time_two_bars',
 				'caption': 'Tägliche Impfrate (Erst- und Zweitimpfung nebeneinander)'
 			},{
-				'index': 4,
+				'index': 6,
 				'filename': 'vaccination_bar_graph_compare_both_vaccinations',
 				'caption': 'Tägliche Impfrate (Erst- und Zweitimpfung nebeneinander)'
 			},{
-				'index': 5,
+				'index': 7,
 				'filename': 'cumulative_two_vaccinations',
 				'caption': 'Kumulative Impfrate (Erst- und Zweitimpfung)'
 			},{
-				'index': 6,
+				'index': 8,
 				'filename': 'cumulative_two_vaccinations_percentage',
 				'caption': 'Kumulative Impfrate (Erst- und Zweitimpfung) in Prozent der Bevölkerung Deutschlands'
 			},{
-				'index': 7,
+				'index': 9,
 				'filename': 'people_between_first_and_second',
 				'caption': 'Anzahl der Personen zwischen Erst- und Zweitimpfung, also Personen, die die erste Impfung erhalten haben, die zweite aber noch nicht'
 			},{
-				'index': 8,
+				'index': 10,
 				'filename': 'vaccination_rate',
 				'caption': 'Tägliche Impfrate sowie durchschnittliche Impfrate'
-			},{
-				'index': 9,
-				'filename': 'vaccination_done_days',
-				'caption': 'Lineare Extrapolation bis 70 % der Bevölkerung anhand der Erstimpfungen der durchschnittlichen Impfrate (Anzahl Tage, Gesamt und 7 Tage)'
-			},{
-				'index': 10,
-				'filename': 'vaccination_done_dates',
-				'caption': 'Lineare Extrapolation bis 70 % der Bevölkerung anhand der Erstimpfungen der durchschnittlichen Impfrate (Datum, Gesamt und 7 Tage)'
 			}
 		]
 	).dump('site/index.xhtml')

requirements.txt

@@ -4,5 +4,4 @@ pandas
 openpyxl
 requests
 jinja2
-isoweek