Bar Charts

Bar charts compare a metric across discrete categories — useful for final-epoch comparisons between optimizers, architectures, or other hyperparameters.

Basic usage

malet-plot -exp_folder ./experiments/my_exp \
  -mode bar-optimizer-val_accuracy \
  -filter 'step last' \
  -best_at_max

The filter step last selects only the final epoch, so each bar shows the terminal performance.

Error bars

When averaging over seeds, standard error is shown automatically as error bars on each bar. Disable with std_plot: false in the YAML plot config.

Python API

import matplotlib.pyplot as plt
from malet.experiment import ExperimentLog
from malet.plot_utils.data_processor import avgbest_df, select_df
from malet.plot_utils.plot_drawer import ax_draw_bar

log = ExperimentLog.from_tsv('log.tsv')
df = log.melt_and_explode_metric(step=-1)
df = select_df(df, {'metric': 'val_accuracy'})
df = avgbest_df(df, 'metric_value', avg_over={'seed'},
                best_over={'lr'}, best_at_max=True)

# Reduce to single index (the categorical x-field)
drop = [n for n in df.index.names if n != 'optimizer']
df = df.reset_index(drop, drop=True).sort_index()

fig, ax = plt.subplots(figsize=(7, 5))
ax_draw_bar(ax, df, label='Val Accuracy', color='#2ca02c', annotate=True)
ax.set_xlabel('Optimizer')
ax.set_ylabel('Val Accuracy')
fig.savefig('bar.png', dpi=150, bbox_inches='tight')

ax_draw_bar parameters

Parameter	Type	Default	Description
ax	Axes	—	Matplotlib axes to draw on
df	DataFrame	—	Single-index DataFrame with one value column
label	str	—	Legend label
std_plot	bool	True	Show error bars if _std column exists
color	str	'orange'	Bar color
annotate	bool	True	Add value annotations above bars
unif_xticks	bool	False	Uniform x-tick spacing