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Add "↑/↓ better" direction annotations to all metric y-axes #3

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Merged
kjappelbaum merged 2 commits into from
Apr 12, 2026
Merged

Add "↑/↓ better" direction annotations to all metric y-axes #3

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Initial plan
Copilot Apr 2, 2026
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Add good/bad direction annotations to all metric axes
Copilot Apr 2, 2026
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40 changes: 40 additions & 0 deletions src/scripts/plotting_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,31 @@
'recall_macro': 'Recall (Macro)'
}

# Metrics where lower values are better
_LOWER_IS_BETTER_METRICS = {'mae', 'mape', 'rmse', 'mse'}


def _is_lower_better(metric: str) -> bool:
"""Return True if lower values are better for this metric."""
return metric.lower() in _LOWER_IS_BETTER_METRICS
Comment on lines +64 to +66

@sourcery-ai sourcery-ai Bot Apr 12, 2026

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suggestion: Normalize metric strings more defensively to avoid subtle mismatches.

_is_lower_better currently requires an exact lowercase match. If callers pass names with whitespace or minor decoration (e.g. 'rmse ', 'RMSE\n', 'rmse (val)'), it will incorrectly fall back to higher-is-better. Consider normalizing more aggressively (e.g. metric.strip().lower()) and, if relevant, handling simple aliases/suffixes before the membership check to avoid wrong arrow directions from small naming differences.

Suggested change
def _is_lower_better(metric: str) -> bool:
"""Return True if lower values are better for this metric."""
return metric.lower() in _LOWER_IS_BETTER_METRICS
def _is_lower_better(metric: str) -> bool:
"""Return True if lower values are better for this metric.
Normalizes common formatting variations (whitespace, case, and
simple parenthetical decorations like "rmse (val)").
"""
# Normalize whitespace and case
normalized = metric.strip().lower()
# Drop simple parenthetical decorations, e.g. "rmse (val)" -> "rmse"
if "(" in normalized:
normalized = normalized.split("(", 1)[0].rstrip()
return normalized in _LOWER_IS_BETTER_METRICS



def _add_good_direction_annotation(ax: plt.Axes, metric: str, compact: bool = False) -> None:
"""Add a small annotation near the y-axis indicating the direction of improvement.

Plots '↓ better' for error metrics (MAE, MAPE) where lower is better,
and '↑ better' for score metrics (F1, Accuracy, R²) where higher is better.
"""
arrow = '↓' if _is_lower_better(metric) else '↑'
fontsize = 6 if compact else 7
ax.text(
0, 1.02, f'{arrow} better',
transform=ax.transAxes,
fontsize=fontsize,
ha='left', va='bottom',
color='gray', fontstyle='italic',
)


def plot_performance_comparison(results: Dict[str, Any],
target_type: str = 'regression',
Expand Down Expand Up @@ -133,6 +158,9 @@ def plot_performance_comparison(results: Dict[str, Any],
ax.set_ylabel(metric_label, fontsize=10, labelpad=15)
ax.yaxis.set_label_coords(-0.45, 0.5) # Fixed position with better padding

# Indicate which direction is better
_add_good_direction_annotation(ax, metric)

# Apply range frame
if len(valid_means) > 0:
range_frame(ax, x_positions, valid_means)
Expand Down Expand Up @@ -445,6 +473,9 @@ def plot_parameter_sweep_results(sweep_results: List[Dict[str, Any]],
ax.legend(fontsize=8)
ax.set_xscale('log')

# Indicate which direction is better
_add_good_direction_annotation(ax, metric)

# Apply range frame
if all_x and all_y:
range_frame(ax, np.array(all_x), np.array(all_y))
Expand Down Expand Up @@ -594,6 +625,9 @@ def _plot_meta_prediction_panel(ax, results: Dict[str, Any], meta_type: str,
else:
ax.set_ylabel(ylabel_text, fontsize=fontsize_tick+1, labelpad=10)

# Indicate which direction is better
_add_good_direction_annotation(ax, metric, compact=compact)

ax.set_xticks(x_pos)
ax.set_xticklabels(labels_list, rotation=30, ha='right', fontsize=fontsize_tick)

Expand Down Expand Up @@ -746,6 +780,9 @@ def create_main_figure_panel(results: Dict[str, Any],
# Use manual ylabel for better control
ax_perf.set_ylabel(metric_label, fontsize=10, labelpad=12)

# Indicate which direction is better
_add_good_direction_annotation(ax_perf, main_metric)

# Add panel label D
ax_perf.text(-0.03, 1.05, 'D', transform=ax_perf.transAxes,
fontsize=12, fontweight='bold', ha='center')
Expand Down Expand Up @@ -974,6 +1011,9 @@ def plot_meta_comparison(comparison_results: Dict[str, Any],
metric_label = metric_labels.get(primary_metric, primary_metric.upper()) if metric_labels else primary_metric.upper()
ax_property.set_ylabel(metric_label)

# Indicate which direction is better
_add_good_direction_annotation(ax_property, primary_metric)

# Add baseline reference if applicable
if not np.isnan(means[1]): # dummy baseline
range_frame(ax_property, np.array([0]), np.array([means[1]]))
Expand Down
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