fast_fig 0.8.1

FaSt_Fig is a wrapper for matplotlib with templates.

FaSt_Fig

FaSt_Fig is a wrapper for matplotlib that provides a simple interface for fast and easy plotting.

Key features:

• Predefined templates for consistent styling
• Figure instantiation in a class object
• Simplified plotting methods with smart defaults
• Automatic handling of DataFrames
• Context manager support for clean resource management
• Type hints and logging for better development experience

Installation

pip install fast_fig

Basic Usage

from fast_fig import FFig
x = [1,2,3,4,5]
y1 = [2,4,5,6,10]
y2 = [1,3,2,6,9]

# Simple plot example
fig = FFig()
fig.plot(x,y1)
fig.show()

# Use large template and save figure to multiple formats
fig = FFig('l')
fig.plot(x,y)
fig.save('plot.png', 'pdf')

Context Manager

FaSt_Fig can be used as a context manager for automatic resource cleanup:

with FFig('l', nrows=2, sharex=True) as fig:  # Large template, 2 rows sharing x-axis
    fig.plot([1, 2, 2.5], label="First")  # Plot in first axis/subplot
    fig.set_title("First plot")
    fig.next_axis()  # Switch to second axis/subplot
    fig.plot([0, 1, 2], [0, 1, 4], label="Second")  # Plot with x,y data
    fig.legend()  # Add legend
    fig.grid()  # Add grid
    fig.set_xlabel("X values")  # Label x-axis
    fig.save("plot.png", "pdf")  # Save as PNG and PDF
    # Figure automatically closed when exiting the with block

Plot Types

FaSt_Fig supports all plots of matplotlib. The following plots have adjusted settings to improve their use.

# Bar plots
fig.bar_plot(x, height)

# Logarithmic scales
fig.semilogx(x, y)  # logarithmic x-axis
fig.semilogy(x, y)  # logarithmic y-axis

# 2D plots
x, y = np.meshgrid(np.linspace(-2, 2, 100), np.linspace(-2, 2, 100))
z = np.exp(-(x**2 + y**2))

fig.pcolor(z)  # pseudocolor plot
fig.colorbar(label='Values')  # add colorbar


fig.pcolor_log(z)  # pseudocolor with logarithmic color scale

fig.contour(z, levels=[0.2, 0.5, 0.8])  # contour plot

# Scatter plots
fig.scatter(x, y, c=colors, s=sizes)  # scatter plot with colors and sizes

DataFrame Support

FaSt_Fig has built-in support for pandas DataFrames:

import pandas as pd

# Create a DataFrame with datetime index
df = pd.DataFrame({
    'A': [1, 2, 3, 4],
    'B': [2, 4, 6, 8]
}, index=pd.date_range('2024-01-01', periods=4))

fig = FFig()
fig.plot(df)  # Automatic handling:
              # - Each column becomes a line
              # - Column names become labels
              # - Index used as x-axis
              # - Date index sets x-label to "Date"

Matplotlib interaction

FaSt_Fig provides direct access to matplotlib objects through these handlers:

• fig.current_axis: Current axes instance for active subplot
• fig.handle_fig: Figure instance for figure-level operations
• fig.handle_plot: Current plot instance(s)
• fig.handle_axis: All axes instances for subplot access

fig.current_axis.set_yscale('log')  # Direct matplotlib axis methods
fig.handle_fig.tight_layout()  # Adjust layout
fig.handle_plot[0].set_linewidth(2)  # Modify line properties
fig.handle_axis[0].set_title('First subplot')  # Access any subplot

These handles provide full access to matplotlib's functionality when needed.

Presets

FaSt_Fig comes with built-in presets that control figure appearance. Available preset templates:

• m (medium): 15x10 cm, sans-serif font, good for general use
• s (small): 10x8 cm, sans-serif font, suitable for small plots
• l (large): 20x15 cm, sans-serif font, ideal for presentations
• ol (Optics Letters): 8x6 cm, serif font, optimized for single line plots
• oe (Optics Express): 12x8 cm, serif font, designed for equation plots
• square: 10x10 cm, serif font, perfect for square plots

Each preset defines:

• width: Figure width in cm
• height: Figure height in cm
• fontfamily: Font family (serif or sans-serif)
• fontsize: Font size in points
• linewidth: Line width in points

You can use presets in three ways:

1. Use a built-in preset:

fig = FFig('l')  # Use large preset

2. Load custom presets from a file:

fig = FFig('m', presets='my_presets.yaml')  # YAML format
fig = FFig('m', presets='my_presets.json')  # or JSON format

3. Override specific preset values:

fig = FFig('m', width=12, fontsize=14)  # Override width and fontsize

The preset system also includes color sequences and line styles that cycle automatically when plotting multiple lines:

• Default colors: blue, red, green, orange
• Default line styles: solid (-), dashed (--), dotted (:), dash-dot (-.)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

Licensed under MIT License. See LICENSE for details.

Author

Written by Fabian Stutzki ([e-mail])

For more information, visit www.fast-apps.de