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")
def plot_history(history: dict, lbl: str, ax1: Axes, ax2: Axes,
color: str) -> Tuple[Axes, Axes]:
"""
根據給定的history畫圖，左為loss vs epoch，右為accuracy vs epoch
Args:
history (dict): keras中的history dict
lbl (str): 該history對應的legend
ax1 (Axes) 物件，畫線圖 (loss vs epoch)
ax2 (Axes) 物件，畫線圖 (accuracy vs epoch)
color (str) : 該history對應的顏色
Returns:
Tuple[Axes, Axes] : 畫好線的Axes物件
"""
acc_keyword = ['acc', 'accuracy']
val_acc_keyword = ['val_acc', 'val_accuracy']
ax1.plot(history['loss'], label=f'{lbl}_train', c=color)
ax1.plot(history['val_loss'], label=f'{lbl}_val', c=color, linestyle='--')
ax1.set_ylabel('Loss')
ax1.set_xlabel('Epoch')
######### [START] for differenct keras version acc keywords #############
try:
# 'acc' for keras 2.1.6
ax2.plot(history[acc_keyword[0]], label=f'{lbl}_train', c=color)
ax2.plot(history[val_acc_keyword[0]],
label=f'{lbl}_val',
c=color,
linestyle='--')
except KeyError:
# 'accuracy' for keras > 2.1.6
ax2.plot(history[acc_keyword[1]], label=f'{lbl}_train', c=color)
ax2.plot(history[val_acc_keyword[1]],
label=f'{lbl}_val',
c=color,
linestyle='--')
######### [END] for differenct keras version acc keywords #############
ax2.set_ylabel('accuracy')
ax2.set_xlabel('Epoch')
return ax1, ax2