diff --git a/dashboard_template.xhtml b/dashboard_template.xhtml
index 35a6eb7..5bc636a 100644
--- a/dashboard_template.xhtml
+++ b/dashboard_template.xhtml
@@ -173,21 +173,124 @@
diff --git a/plot.py b/plot.py
index 906462f..bdf325f 100644
--- a/plot.py
+++ b/plot.py
@@ -14,7 +14,6 @@ import requests as req
import locale
import os.path
import shutil
-import math
from matplotlib.dates import date2num
import matplotlib.ticker as mtick
@@ -68,6 +67,7 @@ dates = impfungen['Datum']
start_of_reporting_date = dates.iloc[0].date()
def calculate_vaccination_data(data):
+ cumulative = np.cumsum(data)
total = int(np.sum(data))
total_percentage = float(total) / einwohner_deutschland * 100
@@ -80,11 +80,7 @@ def calculate_vaccination_data(data):
days_since_start_of_vaccination = (last_date - start_of_vaccination_date).days
days_since_start_of_reporting = (last_date - start_of_reporting_date).days
- valid_data = data[start_of_vaccination_index:]
-
- cumulative = np.concatenate(([math.nan] * (days_since_start_of_reporting - days_since_start_of_vaccination), np.cumsum(valid_data)))
-
- mean_all_time = np.mean(valid_data)
+ mean_all_time = np.mean(data[start_of_vaccination_index:])
mean_seven_days = np.mean(data[-7:])
def extrapolate(rate, to_be_vaccinated):
@@ -114,7 +110,7 @@ def calculate_vaccination_data(data):
extrapolation_mean_seven_days = extrapolate(mean_seven_days, to_be_vaccinated)
mean_vaccination_rates_daily = np.round(cumulative / range(1, len(cumulative) + 1))
- vaccination_rates_daily_rolling_average = data.rolling(7).mean()
+
vaccinations_missing_until_target = einwohner_deutschland * 0.7 - total
vaccination_rate_needed_for_target = vaccinations_missing_until_target / days_until_target
@@ -135,7 +131,6 @@ def calculate_vaccination_data(data):
'extrapolation_last_rate': extrapolation_last_rate,
'extrapolation_mean_seven_days': extrapolation_mean_seven_days,
'mean_vaccination_rates_daily': mean_vaccination_rates_daily,
- 'vaccination_rates_daily_rolling_average': vaccination_rates_daily_rolling_average,
'vaccinations_missing_until_target': int(np.floor(vaccinations_missing_until_target)),
'vaccination_rate_needed_for_target': int(np.floor(vaccination_rate_needed_for_target)),
'vaccination_rate_needed_for_target_percentage': vaccination_rate_needed_for_target_percentage
@@ -511,7 +506,7 @@ def plot_cumulative_two_vaccinations():
ax.fill_between(dates, first_vaccinations_cumulative, label='Erstimpfungen', color='blue')
ax.fill_between(dates, second_vaccinations_cumulative, label='Zweitimpfungen', color='lightblue')
- ax.set_ylim([0, first_vaccinations_cumulative[-1]])
+ ax.set_ylim([0, first_vaccinations_cumulative.iloc[-1]])
ax.legend(loc='upper left')
ax.xaxis_date()
@@ -602,7 +597,7 @@ def plot_people_between_first_and_second():
ax.grid()
first_vaccinations_cumulative = data_first_vaccination['cumulative']
- second_vaccinations_cumulative = np.nan_to_num(data_second_vaccination['cumulative'], nan=0)
+ second_vaccinations_cumulative = data_second_vaccination['cumulative']
people_between = first_vaccinations_cumulative - second_vaccinations_cumulative
@@ -630,54 +625,6 @@ def plot_people_between_first_and_second():
plot_people_between_first_and_second()
-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'):
- #print('Plot {} already exists'.format(archive_plot_filename))
- #return
-
- fig, ax = plt.subplots(1)
-
-
- plt.title(
- 'Tägliche Impfrate sowie durchschnittliche Impfrate\n'
- 'Datenquelle: RKI, Stand: {}. Erstellung: {}, Ersteller: Benedikt Bastin, Lizenz: CC BY-SA 4.0\n'.format(
- print_stand, print_today
- )
- )
-
- ax.plot(dates, data_first_vaccination['daily'], label='Tägliche Erstimpfrate', color='blue', linewidth=0.5)
- ax.plot(dates, data_second_vaccination['daily'], label='Tägliche Zweitimpfrate', color='lightblue', linewidth=0.5)
-
- ax.plot(dates, data_first_vaccination['vaccination_rates_daily_rolling_average'], color='blue', linewidth=2, label='Erstimpfrate über sieben Tage')
- ax.plot(dates, data_second_vaccination['vaccination_rates_daily_rolling_average'], color='lightblue', linewidth=2, label='Zweitimpfrate über sieben Tage')
-
-
- 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.)')
-
-
- ax.grid(True)
-
-
- ax.legend(loc='upper left')
- ax.get_yaxis().get_major_formatter().set_scientific(False)
-
- ax.set_xlabel('Datum')
- ax.set_ylabel('Impfrate [Impfungen/Tag]')
-
- 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_rate()
def render_dashboard():
dashboard_filename = 'site/index.xhtml'
@@ -717,49 +664,6 @@ def render_dashboard():
data_second_vaccination = data_second_vaccination,
#details_per_land = dict(sorted(details_per_land_formatted.items(), key=lambda item: item[0])),
#details_total = details_total_formatted
- 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': 5,
- 'filename': 'vaccination_bar_graph_total_time_two_bars',
- 'caption': 'Tägliche Impfrate (Erst- und Zweitimpfung nebeneinander)'
- },{
- 'index': 6,
- 'filename': 'vaccination_bar_graph_compare_both_vaccinations',
- 'caption': 'Tägliche Impfrate (Erst- und Zweitimpfung nebeneinander)'
- },{
- 'index': 7,
- 'filename': 'cumulative_two_vaccinations',
- 'caption': 'Kumulative Impfrate (Erst- und Zweitimpfung)'
- },{
- 'index': 8,
- 'filename': 'cumulative_two_vaccinations_percentage',
- 'caption': 'Kumulative Impfrate (Erst- und Zweitimpfung) in Prozent der Bevölkerung Deutschlands'
- },{
- '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': 10,
- 'filename': 'vaccination_rate',
- 'caption': 'Tägliche Impfrate sowie durchschnittliche Impfrate'
- }
- ]
).dump('site/index.xhtml')
shutil.copyfile(dashboard_filename, dashboard_archive_filename)
![{{ fig['caption'] }}](extrapolated_to_10_percent.png)
+ src="extrapolated_to_10_percent.png"
+ alt="" />
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