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