def plot_average(df: pd.DataFrame,
sweep_vars: Sequence[str] = None) -> gg.ggplot:
"""Plots the average regret at 1k episodes by optimal_horizon."""
df = dc_preprocess(df_in=df)
p = plotting.plot_regret_average(
df_in=df,
group_col='optimal_horizon',
episode=sweep.NUM_EPISODES,
sweep_vars=sweep_vars
)
p += gg.geom_hline(gg.aes(yintercept=BASE_REGRET),
linetype='dashed', alpha=0.4, size=1.75)
return p
def plot_average(df: pd.DataFrame,
sweep_vars: Optional[Sequence[str]] = None,
group_col: str = 'noise_scale') -> gg.ggplot:
"""Plots the average regret through time by noise_scale."""
p = plotting.plot_regret_average(df_in=df,
group_col=group_col,
episode=sweep.NUM_EPISODES,
sweep_vars=sweep_vars)
p += gg.geom_hline(gg.aes(yintercept=mnist_analysis.BASE_REGRET),
linetype='dashed',
alpha=0.4,
size=1.75)
return p
def plot_average(df: pd.DataFrame,
sweep_vars: Sequence[Text] = None,
group_col: Text = 'noise_scale') -> gg.ggplot:
"""Plots the average regret through time by noise_scale."""
df = cartpole_analysis.cartpole_preprocess(df)
p = plotting.plot_regret_average(df_in=df,
group_col=group_col,
episode=sweep.NUM_EPISODES,
sweep_vars=sweep_vars)
p += gg.geom_hline(gg.aes(yintercept=cartpole_analysis.BASE_REGRET),
linetype='dashed',
alpha=0.4,
size=1.75)
return p
def plot_average(df: pd.DataFrame,
sweep_vars: Sequence[str] = None,
group_col: str = 'delay') -> gg.ggplot:
"""Plots the average regret through time by delay."""
df = mdpp_preprocess_delay(df)
p = plotting.plot_regret_average(df_in=df,
group_col=group_col,
episode=sweep.NUM_EPISODES,
sweep_vars=sweep_vars)
p += gg.geom_hline(gg.aes(yintercept=BASE_REGRET),
linetype='dashed',
alpha=0.4,
size=1.75)
return p
def plot_average(df: pd.DataFrame,
sweep_vars: Sequence[Text] = None,
group_col: Text = 'noise_scale') -> gg.ggplot:
"""Plots the average regret through time by noise_scale."""
p = plotting.plot_regret_average(
df_in=df,
group_col=group_col,
episode=sweep.NUM_EPISODES,
sweep_vars=sweep_vars
)
p += gg.scale_y_continuous(breaks=np.arange(0, 1.1, 0.1).tolist())
p += gg.theme(panel_grid_major_y=gg.element_line(size=2.5),
panel_grid_minor_y=gg.element_line(size=0),)
p += gg.geom_hline(gg.aes(yintercept=bandit_analysis.BASE_REGRET),
linetype='dashed', alpha=0.4, size=1.75)
p += gg.coord_cartesian(ylim=(0, 1))
return p
