Function time_line

benchmark/plotters.py:97–146

Creates a plot of performance over time.

(
    ax: Axes,
    file_key: Tuple[str, ...],
    column_key: Tuple[str, ...],
    row_key: Tuple[str, ...],
    line_by: GroupingSpec,
    metrics_df: pd.DataFrame,
    metadata: Collection[BenchmarkMetadata],
)

@make_plotter
def time_line(
    ax: Axes,
    file_key: Tuple[str, ...],
    column_key: Tuple[str, ...],
    row_key: Tuple[str, ...],
    line_by: GroupingSpec,
    metrics_df: pd.DataFrame,
    metadata: Collection[BenchmarkMetadata],
) -> None:
    """
    Creates a plot of performance over time.
    """
    assert GroupingKey.PLOTTER not in line_by.by
    metric = _get_metric(metrics_df)
    line_by = replace(line_by, by=[k for k in line_by.by if k != GroupingKey.TIMESTAMP])
    line_groups = group(metrics_df, [], metadata, line_by)
    for key, df, _ in line_groups:
        line_xs = []
        line_y_means = []
        line_y_uppers = []
        line_y_lowers = []

        scatter_xs = []
        scatter_ys = []

        timestamp_by = GroupingSpec([GroupingKey.TIMESTAMP], minimise=False)
        timestamp_groups = group(df, [], metadata, timestamp_by)
        for (timestamp,), timestamp_df, _ in timestamp_groups:
            parsed_timestamp = date2num(parse_timestamp(timestamp))
            line_xs.append(parsed_timestamp)
            y_mean = timestamp_df.value.mean()
            y_std = timestamp_df.value.std()
            if isnan(y_std):
                y_std = 0.0
            line_y_means.append(y_mean)
            line_y_uppers.append(y_mean + 1.96 * y_std)
            line_y_lowers.append(y_mean - 1.96 * y_std)

            scatter_xs.extend(len(timestamp_df) * [parsed_timestamp])
            scatter_ys.extend(timestamp_df.value)

        (mean_line,) = ax.plot(line_xs, line_y_means, label=_join_key(key))
        color = mean_line.get_color()
        ax.fill_between(line_xs, line_y_lowers, line_y_uppers, color=color, alpha=0.3)
        ax.scatter(scatter_xs, scatter_ys, color=color)

    if len(line_groups) > 1:
        ax.legend()

    _shared_ax_config(ax, file_key, column_key, row_key, metric)