From 7d97f96fe7def51ac57e2307c21eb426c97f542e Mon Sep 17 00:00:00 2001
From: Benedikt Bastin <benedikt@benedikt-bastin.de>
Date: Fri, 15 Jan 2021 00:16:40 +0100
Subject: [PATCH] feat: Initial working version

---
 .gitignore |  2 ++
 plot.py    | 88 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 90 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 plot.py

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..3b4fba1
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,2 @@
+*.pdf
+*.xlsx
diff --git a/plot.py b/plot.py
new file mode 100644
index 0000000..239e6e6
--- /dev/null
+++ b/plot.py
@@ -0,0 +1,88 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+
+import datetime
+import re
+
+einwohner_deutschland = 83190556
+
+
+# DIN A4 Plots
+plt.rcParams["figure.figsize"] = [11.69, 8.27]
+
+raw_data = pd.read_excel('Impfquotenmonitoring.xlsx', sheet_name='Impfungen_proTag', engine='openpyxl')
+
+impfungen = raw_data[:-1].dropna()
+
+dates = impfungen['Datum']
+daily = impfungen['Gesamtzahl Impfungen']
+cumulative = np.cumsum(impfungen['Gesamtzahl Impfungen'])
+
+mean_vaccinations_daily = np.mean(daily)
+
+to_be_vaccinated = einwohner_deutschland - np.sum(daily)
+days_extrapolated = int(np.ceil(to_be_vaccinated / mean_vaccinations_daily))
+
+extrapolated_dates = np.array([dates[0] + datetime.timedelta(days=i) for i in range(days_extrapolated)])
+
+extrapolated_vaccinations = mean_vaccinations_daily * range(days_extrapolated)
+
+
+# Stand aus Daten auslesen
+#stand = dates.iloc[-1]
+#print_stand = stand.isoformat()
+
+# Stand aus offiziellen Angaben auslesen
+stand = pd.read_excel('Impfquotenmonitoring.xlsx', sheet_name='Erläuterung', engine='openpyxl').iloc[1][0]
+print(stand)
+
+stand_regex = re.compile('^Datenstand: (\d\d.\d\d.\d\d\d\d, \d\d:\d\d) Uhr$')
+m = stand_regex.match(stand)
+stand_date = datetime.datetime.strptime(m.groups()[0], '%d.%m.%Y, %H:%M')
+print_stand = stand_date.isoformat()
+
+filename_stand = stand_date.strftime("%Y%m%d%H%M%S")
+
+def plot_extrapolation_portion(percentage):
+
+	fig, ax = plt.subplots(1)
+
+	print_percentage = int(percentage * 100)
+	print_today = datetime.date.today().isoformat()
+
+	plt.title(
+		'Tägliche Impfquote, kumulierte Impfungen und lineare Extrapolation bis {} % der Bevölkerung Deutschlands\n'
+		'Erstellung: {}, Datenquelle: RKI, Stand: {}'.format(print_percentage, print_today, print_stand)
+	)
+
+	ax2 = ax.twinx()
+
+	ax.bar(dates, daily, label='Tägliche Impfungen')
+
+	ax2.set_ylim([0, einwohner_deutschland * percentage])
+	ax2.set_xlim(xmax=dates[0] + datetime.timedelta(days=percentage * days_extrapolated))
+	ax2.grid(True)
+	ax2.plot(dates, cumulative, color='red', label='Kumulierte Impfungen')
+	ax2.plot(extrapolated_dates, extrapolated_vaccinations, color='orange', label='Kumulierte Impfungen (linear extrap.)')
+	#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='center right')
+	ax2.get_yaxis().get_major_formatter().set_scientific(False)
+
+	ax2.axline((0, einwohner_deutschland * 0.7), slope=0, color='green')
+
+	ax2.set_ylabel('Kumulierte Impfungen')
+
+	plt.savefig('{}_extrapolated_to_{}_percent.pdf'.format(filename_stand, print_percentage))
+	plt.close()
+
+
+plot_extrapolation_portion(0.1)
+plot_extrapolation_portion(1.0)