add metadata from new columns and make every module fit to use this. add stringence of local measures as background of plot, add vaccination status to plots, mute unreasonable warnings

all_countries.py

@@ -6,6 +6,8 @@ from mpl_toolkits.axisartist.parasite_axes import HostAxes, ParasiteAxes
 import numpy as np
 import time as time_module
 import pickle
+import warnings
+warnings.filterwarnings("ignore", category=UserWarning)
 basename="all_"
 
 # manual y adjustments for new cases
@@ -28,10 +30,11 @@ def plot(data, countries, pop, **kwargs):
             if loc == "International":
                 continue
             name = basename+loc
-            time, new_cases, new_deaths, total_cases, total_deaths = data[loc]
+            time, new_cases, new_deaths, total_cases, total_deaths, total_vaccinations, stringency_index = data[loc]['time'], data[loc]['new_cases'], data[loc]['new_deaths'], data[loc]['total_cases'], data[loc]['total_deaths'], data[loc]['total_vaccinations'], data[loc]['stringency_index']
             
             fig, ax1 = pp.subplots(num=name, figsize=figsize)
 
+
             ax2 = ax1.twinx()
             ax2.plot(time, np.array(total_deaths)*10, label="Total deaths (x10)", marker="", linestyle="--", color="green")
             ax2.plot(time, total_cases, label=f"Total cases", marker="", linestyle="-", color="blue")
@@ -42,6 +45,10 @@ def plot(data, countries, pop, **kwargs):
             ax1.plot(time, new_cases, label="raw new cases", color="grey", linestyle="-")
             ax1.plot(time[3:-3], np.convolve(new_cases, np.ones((7,))/7, mode="valid"), label="new cases 7day mean", color="orange", linestyle="-", linewidth=2)
 
+            if not np.isnan(total_vaccinations[-1]):
+                print(f"{loc} has vaccines, adding to plot")
+                ax2.plot(time, np.array(total_vaccinations), label=f"Total vaccinations", marker="", linestyle="-.", color="crimson")
+
             # fix lower bound of plot
             for ax in (ax1, ax2):
                 axis = ax.axis()
@@ -50,6 +57,12 @@ def plot(data, countries, pop, **kwargs):
                         axis = [axis[0], axis[1], axis[2], corr[loc]]
                 ax.axis([axis[0], axis[1], -1, axis[3]])
 
+            # fix population
+            #try:
+            #    print(loc, pop[loc]['pop'] - metadata[loc]['population'])
+            #except:
+            #    pop[loc]['pop'] = metadata[loc]['population']
+
             # if we know population: plot 500 new cases / 1million inhabitants as a rough measure for comparison
             # also set color for infection level indicator
             infection_level_indicator = "grey"
@@ -82,6 +95,12 @@ def plot(data, countries, pop, **kwargs):
                 print(f"=====> population unknown for {loc}, skipping plot enhancements")
                 
 
+            # stringency of countermeasures as background contourf
+            axbounds = ax1.axis()
+            ax1.contourf(time, [-1, 1e10], [stringency_index]*2, cmap="Greys", alpha=0.3, levels=99)
+            ax1.axis(axbounds)
+
+
             # disabled for now: put second total-cases-per-million-inhabitants axis besides total-cases-axis
             if loc in pop and False:
                 # according to https://matplotlib.org/3.2.2/gallery/axisartist/demo_parasite_axes.html
@@ -107,6 +126,8 @@ def plot(data, countries, pop, **kwargs):
             if loc in pop:
                 #pp.title(f"{loc}", population = "+f"{pop[loc]['pop']:,}".replace(",","."))
                 title += ", population = "+f"{pop[loc]['pop']:,}".replace(",",".")
+            if not np.isnan(total_vaccinations[-1]):
+                title += ", vac rate: "+f"{total_vaccinations[-1]/pop[loc]['pop']*100:1.3f}%"
             ax1.set_title(title)
             fig.tight_layout()
             pp.text(0.002,0.005, f"plot generated {time_module.strftime('%Y-%m-%d %H:%M')}, CC-by-sa-nc, origin: dukun.de/corona, datasource: ourworldindata.org/coronavirus-source-data", color="dimgrey", fontsize=8, transform=fig.transFigure)