hmbp 0.1.1

Simple matplotlib plotting with consistent, publication-ready styling

hmbp

A simple matplotlib wrapper with consistent, publication-ready styling.

Installation

pip install hmbp

Style

• Font: Helvetica
• Colormap: RdPu (primary), PiYG (secondary/diverging)
• 400 DPI output
• Consistent sizing: title 15pt, labels 14pt, ticks 13pt, legend 12pt

Usage

import hmbp

fig, ax = hmbp.new_figure()
hmbp.line_plot(y_values, x_values, label="Model A")
hmbp.set_labels("Title", "X Label", "Y Label")
hmbp.save("output.png")

Available Functions

Function	Description
line_plot	Line with optional fill
scatter_plot	Scatter with optional color mapping
histogram	Color-mapped histogram
bar_plot	Vertical/horizontal bars
box_plot	Box plot distributions
violin_plot	Violin plot distributions
heatmap	2D heatmap with colorbar
line_plot_with_error	Line with shaded error region
confusion_matrix	Annotated confusion matrix
roc_curve	ROC curve with AUC
precision_recall_curve	PR curve with AP
residual_plot	Regression residuals
learning_curve	Train/val learning curves
metric_comparison	Horizontal bar comparison
volcano_plot	Volcano plot for differential analysis

Helpers

• new_figure(figsize) - Create figure and axes
• set_labels(title, xlabel, ylabel) - Apply labels
• save(path, fig, close) - Save with auto-legend

Quick API

Single-call functions that create, label, and save in one step:

import hmbp

hmbp.quick_histogram(data, title="Scores", xlabel="Value", path="hist.png")
hmbp.quick_bar(values, labels, title="Comparison", ylabel="F1", path="bars.png")
hmbp.quick_confusion_matrix(cm, class_names=["A", "B"], path="cm.png")

Available: quick_line, quick_scatter, quick_histogram, quick_bar, quick_heatmap, quick_confusion_matrix, quick_roc, quick_volcano