diff --git a/all_countries.py b/all_countries.py index e96fdc0..fac96c2 100644 --- a/all_countries.py +++ b/all_countries.py @@ -23,91 +23,94 @@ def plot(data, countries, pop): figsize = (10,5) for loc in data: - if loc == "International": - continue - name = basename+loc - time, new_cases, new_deaths, total_cases, total_deaths = data[loc] - - 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") - - ax1.plot(time, np.array(new_deaths)*10, label="raw new deaths (x10)", color="grey", linestyle=":") - ax1.plot(time[3:-3], np.convolve(new_deaths, np.ones((7,))/7, mode="valid")*10, label="new deaths 7day mean (x10)", color="black", linestyle="--", linewidth=2) - - 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) - - # fix lower bound of plot - for ax in (ax1, ax2): - axis = ax.axis() - if ax is ax1: # adjust left (new cases) axes upper boundary for given countries - if loc in corr: - axis = [axis[0], axis[1], axis[2], corr[loc]] - ax.axis([axis[0], axis[1], -1, axis[3]]) - - # 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" try: - #if False: - warn_thresh = 500e-6 * pop[loc]['pop']/7 - info_thresh = 50e-6 * pop[loc]['pop']/7 - low_thresh = 5e-6 * pop[loc]['pop']/7 - actual_level = np.mean(new_cases[-7:]) - infection_level_indicator = "green" - if actual_level > low_thresh: - infection_level_indicator = "gold" - if actual_level > info_thresh: - infection_level_indicator = "peru" - if actual_level > warn_thresh: - infection_level_indicator = "r" - bounds = ax1.axis() - # for small population numbers, give floats instead of ints - if pop[loc]['pop'] < 5e6: - ax1.plot([bounds[0], bounds[1]], [warn_thresh]*2, color="red", linestyle=":", label=f"500 new cases / week / 1M inh.: {warn_thresh:1.2f}".replace(",", ".")) - ax1.plot([bounds[0], bounds[1]], [info_thresh]*2, color="peru", linestyle=":", label=f"50 new cases / week / 1M inh.: {info_thresh:1.2f}".replace(",", ".")) - ax1.plot([bounds[0], bounds[1]], [low_thresh]*2, color="gold", linestyle=":", label=f"5 new cases / week / 1M inh.: {low_thresh:1.2f}".replace(",", ".")) - else: # but not for big populations - ax1.plot([bounds[0], bounds[1]], [warn_thresh]*2, color="red", linestyle=":", label=f"500 new cases / week / 1M inh.: {int(warn_thresh):,}".replace(",", ".")) - ax1.plot([bounds[0], bounds[1]], [info_thresh]*2, color="peru", linestyle=":", label=f"50 new cases / week / 1M inh.: {int(info_thresh):,}".replace(",", ".")) - ax1.plot([bounds[0], bounds[1]], [low_thresh]*2, color="gold", linestyle=":", label=f"5 new cases / week / 1M inh.: {int(low_thresh):,}".replace(",", ".")) - - ax1.axis(bounds) - except: - print(f"=====> population unknown for {loc}, skipping plot enhancements") + if loc == "International": + continue + name = basename+loc + time, new_cases, new_deaths, total_cases, total_deaths = data[loc] + fig, ax1 = pp.subplots(num=name, figsize=figsize) - # 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 - host1 = HostAxes(ax1, [0.15, 0.1, 0.65, 0.8]) - par1 = ParasiteAxes(host1, sharex=host1) - host1.append(par1) - host2 = HostAxes(ax2, [0.15, 0.1, 0.65, 0.8]) - par2 = ParasiteAxes(host2, sharex=host1) - host2.append(par2) - ax3 = ax1.twinx() - ax3.plot(time, total_cases*1e6/pop[loc]['pop'], linestyle="", marker="") - ax3.set_ylabel("total cases per 1M inhabitants") + 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") - # plot infection level indicator - ax1.annotate('Infection status:', xy=(0.85, 1.02), xycoords="axes fraction") - ax1.annotate('•', xy=(0.99, 1.02), xycoords="axes fraction", color=infection_level_indicator, fontsize="x-large") - #ax1.xticks(rotation=45) - #ax1.set_xlabel("date") - ax1.set_ylabel("new cases") - ax2.set_ylabel("total cases") - fig.legend(frameon=False, loc="upper left", bbox_to_anchor=(0,1), bbox_transform=ax1.transAxes) - title = loc - if loc in pop: - #pp.title(f"{loc}", population = "+f"{pop[loc]['pop']:,}".replace(",",".")) - title += ", population = "+f"{pop[loc]['pop']:,}".replace(",",".") - 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) + ax1.plot(time, np.array(new_deaths)*10, label="raw new deaths (x10)", color="grey", linestyle=":") + ax1.plot(time[3:-3], np.convolve(new_deaths, np.ones((7,))/7, mode="valid")*10, label="new deaths 7day mean (x10)", color="black", linestyle="--", linewidth=2) - pp.savefig("ac_"+name+".png") - pp.close(fig) + 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) + + # fix lower bound of plot + for ax in (ax1, ax2): + axis = ax.axis() + if ax is ax1: # adjust left (new cases) axes upper boundary for given countries + if loc in corr: + axis = [axis[0], axis[1], axis[2], corr[loc]] + ax.axis([axis[0], axis[1], -1, axis[3]]) + + # 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" + try: + #if False: + warn_thresh = 500e-6 * pop[loc]['pop']/7 + info_thresh = 50e-6 * pop[loc]['pop']/7 + low_thresh = 5e-6 * pop[loc]['pop']/7 + actual_level = np.mean(new_cases[-7:]) + infection_level_indicator = "green" + if actual_level > low_thresh: + infection_level_indicator = "gold" + if actual_level > info_thresh: + infection_level_indicator = "peru" + if actual_level > warn_thresh: + infection_level_indicator = "r" + bounds = ax1.axis() + # for small population numbers, give floats instead of ints + if pop[loc]['pop'] < 5e6: + ax1.plot([bounds[0], bounds[1]], [warn_thresh]*2, color="red", linestyle=":", label=f"500 new cases / week / 1M inh.: {warn_thresh:1.2f}".replace(",", ".")) + ax1.plot([bounds[0], bounds[1]], [info_thresh]*2, color="peru", linestyle=":", label=f"50 new cases / week / 1M inh.: {info_thresh:1.2f}".replace(",", ".")) + ax1.plot([bounds[0], bounds[1]], [low_thresh]*2, color="gold", linestyle=":", label=f"5 new cases / week / 1M inh.: {low_thresh:1.2f}".replace(",", ".")) + else: # but not for big populations + ax1.plot([bounds[0], bounds[1]], [warn_thresh]*2, color="red", linestyle=":", label=f"500 new cases / week / 1M inh.: {int(warn_thresh):,}".replace(",", ".")) + ax1.plot([bounds[0], bounds[1]], [info_thresh]*2, color="peru", linestyle=":", label=f"50 new cases / week / 1M inh.: {int(info_thresh):,}".replace(",", ".")) + ax1.plot([bounds[0], bounds[1]], [low_thresh]*2, color="gold", linestyle=":", label=f"5 new cases / week / 1M inh.: {int(low_thresh):,}".replace(",", ".")) + + ax1.axis(bounds) + except: + print(f"=====> population unknown for {loc}, skipping plot enhancements") + + + # 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 + host1 = HostAxes(ax1, [0.15, 0.1, 0.65, 0.8]) + par1 = ParasiteAxes(host1, sharex=host1) + host1.append(par1) + host2 = HostAxes(ax2, [0.15, 0.1, 0.65, 0.8]) + par2 = ParasiteAxes(host2, sharex=host1) + host2.append(par2) + ax3 = ax1.twinx() + ax3.plot(time, total_cases*1e6/pop[loc]['pop'], linestyle="", marker="") + ax3.set_ylabel("total cases per 1M inhabitants") + + # plot infection level indicator + ax1.annotate('Infection status:', xy=(0.85, 1.02), xycoords="axes fraction") + ax1.annotate('•', xy=(0.99, 1.02), xycoords="axes fraction", color=infection_level_indicator, fontsize="x-large") + #ax1.xticks(rotation=45) + #ax1.set_xlabel("date") + ax1.set_ylabel("new cases") + ax2.set_ylabel("total cases") + fig.legend(frameon=False, loc="upper left", bbox_to_anchor=(0,1), bbox_transform=ax1.transAxes) + title = loc + if loc in pop: + #pp.title(f"{loc}", population = "+f"{pop[loc]['pop']:,}".replace(",",".")) + title += ", population = "+f"{pop[loc]['pop']:,}".replace(",",".") + 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) + + pp.savefig("ac_"+name+".png") + pp.close(fig) + except Exception as e: + print(f"=====> plotting failed for {loc}, skipping plot. Error: {e}") diff --git a/index.html b/index.html index b693bba..7f69498 100644 --- a/index.html +++ b/index.html @@ -12,7 +12,7 @@

Idee

-Automatisierte Übersichtsplots für die ganze Welt, analog zu dieser Seite. +Automatisierte Übersichtsplots für die ganze Welt, analog zu dieser Seite.

Achtung: Die hier dargestellten Daten sind zwischen den Ländern kaum vergleichbar, da überall unterschiedliche Kriterien für Testung, Zählung und Meldung von Daten existieren. Ohne genaue Kenntnis der Situationen in den einzelnen Ländern ist ein aussagekräftiger Vergleich nicht möglich!