def plot_delta_since(data_adaptor: DataAdaptor,
type_: ValueType,
countries: Iterable[str],
ax: Axes,
rolling: int = 1,
start: Optional[int] = None,
legend: bool = False) -> None:
data_country = data_adaptor.get_time_delta_for_country(
type_, countries, start, rolling)
data_country[data_country <= 0] = np.NAN
if start:
data_country = data_country[data_country.index.days >= 0]
time_data = data_country.index.days if start else data_country.index
ax.plot(time_data, data_country[countries])
if legend:
ax.legend(countries)
ax.set_yscale("log")
ax.set_ylim(data_country.min().min(), data_country.max().max())
ylabel = f"{type_.value} per day"
if rolling > 1:
ylabel += f" ({rolling} day moving average)"
ax.set_ylabel(ylabel)
if start:
ax.set_xlabel(f"Days since {start} {type_.value}")
else:
ax.set_xlabel("Date")
def plot_data_since(data_adaptor: DataAdaptor,
type_: ValueType,
countries: Iterable[str],
ax: Axes,
start: Optional[int] = None,
legend: bool = False) -> None:
data_country = data_adaptor.get_time_series_for_country(
type_, countries, start)
time_data = data_country.index.days if start else data_country.index
ax.plot(time_data, data_country[countries])
if legend:
ax.legend(countries)
ax.set_yscale("log")
if start:
ax.set_xlim(-1.0, data_country.index.days.max())
ax.set_ylim(start, data_country.max().max())
ax.set_ylabel(type_.value)
if start:
ax.set_xlabel(f"Days since {start} {type_.value}")
else:
ax.set_xlabel("Date")