Matplotlib Figure Generator for Inkscape

Generate and embed matplotlib figures directly in Inkscape

A powerful Inkscape extension that allows you to create matplotlib visualizations and insert them seamlessly into your SVG documents. Perfect for scientific illustrations, data visualization in design projects, and publication-ready graphics.

📺 Demo

Click to watch the full tutorial on YouTube

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📋 Table of Contents

• Features
• Installation
• Quick Start
• Usage Guide
• Dependencies
• Examples
• Troubleshooting
• Script Bank
• Contributing

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✨ Features

• 📊 Multiple Script Sources

  • Inline Code: Write matplotlib code directly in the extension dialog
  • External File: Load scripts from .py files
  • Script Bank: Pre-built templates for common plot types

• 🎨 Flexible Output Formats

  • SVG: Native vector graphics, fully editable in Inkscape
  • PNG: High-resolution raster images
  • PDF: Publication-quality vector output

• 📁 Data Import Support

  • CSV, Excel, JSON, and text file formats
  • Automatic column extraction
  • Pandas DataFrame integration

• 🎯 Customizable Styling

  • Built-in matplotlib styles (seaborn, ggplot, etc.)
  • Font family and size controls
  • Color map selection
  • Grid and legend customization

• 📐 Smart Positioning

  • Center, corners, or cursor-based placement
  • Automatic size calculation based on DPI
  • Preserve aspect ratio

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📦 Installation

Step 1: Locate Your Inkscape Extensions Directory

Windows:

C:\Users\[YourUsername]\AppData\Roaming\inkscape\extensions\

macOS:

~/Library/Application Support/org.inkscape.Inkscape/config/inkscape/extensions/

Linux:

~/.config/inkscape/extensions/

Step 2: Install the Extension

1. Download/Clone the extension:

   git clone https://github.com/YouvenZ/plt_ink.git

2. Copy to extensions directory:

   # Windows (PowerShell)
   Copy-Item -Recurse plt_ink [extensions-directory]\plt_ink
   
   # macOS/Linux
   cp -r plt_ink [extensions-directory]/plt_ink

3. Verify file structure:

   plt_ink/
   ├── plt_ink.py
   ├── plt_ink.inx
   └── plt_ink_scripts/
       ├── line_plots/
       ├── scatter_plots/
       ├── bar_charts/
       ├── statistical/
       ├── scientific/
       ├── time_series/
       └── publication/
   

4. Restart Inkscape

Step 3: Verify Installation

Open Inkscape and check: Extensions → Render → Matplotlib Figure Generator

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🚀 Quick Start

Basic Example (Inline Code)

1. Open your document in Inkscape
2. Go to Extensions → Render → Matplotlib Figure Generator
3. In the Script tab, select Inline Code as source
4. Enter your matplotlib code:

   import numpy as np
   x = np.linspace(0, 10, 100)
   y = np.sin(x)
   plt.plot(x, y, label='sin(x)')
   plt.xlabel('X axis')
   plt.ylabel('Y axis')
   plt.title('Simple Sine Wave')
   if _show_legend:
       plt.legend(loc=_legend_position)
   if _show_grid:
       plt.grid(True)

5. Click Apply

Result: A matplotlib figure appears in your Inkscape document!

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📖 Usage Guide

Script Tab

Inline Code Mode

Click to expand

Write matplotlib code directly in the text area. The extension provides:

Pre-defined Variables:

• _fig_width - Figure width from settings
• _fig_height - Figure height from settings
• _dpi - DPI setting
• _show_grid - Grid toggle
• _show_legend - Legend toggle
• _legend_position - Legend location
• _colormap - Selected colormap

Auto-imported Modules:

• matplotlib.pyplot as plt
• numpy as np

Example:

# Data
x = np.linspace(0, 2*np.pi, 100)
y1 = np.sin(x)
y2 = np.cos(x)

# Plot
plt.plot(x, y1, label='sin(x)', color='blue')
plt.plot(x, y2, label='cos(x)', color='red')

plt.title('Trigonometric Functions')
plt.xlabel('Radians')
plt.ylabel('Value')

if _show_legend:
    plt.legend(loc=_legend_position)
if _show_grid:
    plt.grid(True, alpha=0.3)

External File Mode

Click to expand

Load a Python script from your filesystem:

1. Select External File as source
2. Browse to your .py file
3. Click Apply

File Requirements:

• Must use plt for plotting
• Don't call plt.show() (handled automatically)
• Don't call plt.savefig() (handled automatically)

Script Bank Mode

Click to expand

Use pre-built templates from the script bank:

Available Categories:

Category	Description
line_plots	Basic line and curve plots
scatter_plots	Scatter and bubble charts
bar_charts	Bar and histogram plots
statistical	Box plots, violin plots, etc.
scientific	Contour, vector fields, etc.
time_series	Time-based data visualization
publication	Publication-ready templates

How to use:

1. Select Script Bank as source
2. Choose category
3. Choose script
4. Click Apply

Format Tab

Parameter	Default	Range	Description
Output Format	SVG	SVG/PNG/PDF	Output file format
Figure Width	8.0	1-20	Width in inches
Figure Height	6.0	1-20	Height in inches
DPI	96	72-600	Resolution
Transparent	No	Yes/No	Transparent background
Tight Layout	Yes	Yes/No	Remove extra whitespace

Style Tab

Parameter	Default	Options	Description
Plot Style	default	default, seaborn, ggplot, etc.	Matplotlib style
Color Map	viridis	viridis, plasma, etc.	Default colormap
Show Grid	Yes	Yes/No	Enable grid
Show Legend	Yes	Yes/No	Enable legend
Legend Position	best	best, upper right, etc.	Legend location

Placement Tab

Parameter	Default	Description
Position Mode	center	Where to place the figure
Embed Image	Yes	Embed as data URI vs. link

Position Options:

• center - Center of document
• top_left, top_center, top_right
• bottom_left, bottom_center, bottom_right
• cursor - At selected object position

Advanced Tab

Parameter	Default	Description
Font Family	sans-serif	Plot font family
Font Size	10	Base font size
Line Width	1.5	Default line width
Marker Size	6.0	Default marker size
Use LaTeX	No	LaTeX text rendering
Save Script	No	Save generated script
Keep Temp Files	No	Don't delete temp files

Data Import Tab

Click to expand

Import external data files for plotting:

Supported Formats:

Format	Extension	Description
CSV	.csv	Comma-separated values
Excel	.xlsx, .xls	Excel spreadsheets
JSON	.json	JSON arrays/objects
Text	.txt, .dat	Space/tab-delimited

Parameters:

• Data File Path: Path to your data file
• CSV Delimiter: Separator character (default: ,)
• Skip Header: Skip first row
• X Column: Column index for X data
• Y Column: Column index for Y data

Available Variables (after import):

• x_data - X column as numpy array
• y_data - Y column as numpy array
• data or df - Full DataFrame

Example with CSV:

# x_data and y_data are automatically loaded
plt.scatter(x_data, y_data, c='blue', alpha=0.6)
plt.xlabel('X Values')
plt.ylabel('Y Values')

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🔧 Dependencies

Core Requirements (Required)

Component	Version	Purpose
Inkscape	1.0+	Vector graphics editor
Python	3.6+	Extension runtime
matplotlib	3.0+	Plotting library
numpy	1.15+	Numerical computing

Installation:

pip install matplotlib numpy

Optional Dependencies

Component	Purpose	Installation
pandas	Data file import	pip install pandas
openpyxl	Excel file support	pip install openpyxl
LaTeX	LaTeX text rendering	Install TeX distribution

Check Installation:

python -c "import matplotlib; print(matplotlib.__version__)"
python -c "import numpy; print(numpy.__version__)"

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💡 Examples

Example 1: Simple Line Plot

Inline Code:

x = np.linspace(0, 10, 100)
y = np.sin(x) * np.exp(-x/10)

plt.plot(x, y, 'b-', linewidth=2, label='Damped sine')
plt.fill_between(x, y, alpha=0.3)
plt.xlabel('Time')
plt.ylabel('Amplitude')
plt.title('Damped Oscillation')
plt.legend()
plt.grid(True, alpha=0.3)

Example 2: Multi-Panel Figure

fig, axes = plt.subplots(2, 2, figsize=(_fig_width, _fig_height))

x = np.linspace(0, 2*np.pi, 100)

axes[0,0].plot(x, np.sin(x))
axes[0,0].set_title('sin(x)')

axes[0,1].plot(x, np.cos(x))
axes[0,1].set_title('cos(x)')

axes[1,0].plot(x, np.tan(x))
axes[1,0].set_ylim(-5, 5)
axes[1,0].set_title('tan(x)')

axes[1,1].plot(x, np.sin(x)**2)
axes[1,1].set_title('sin²(x)')

for ax in axes.flat:
    ax.grid(True, alpha=0.3)

Example 3: Scientific Visualization

# Create meshgrid
x = np.linspace(-3, 3, 100)
y = np.linspace(-3, 3, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(X) * np.cos(Y)

# Contour plot
fig, ax = plt.subplots(figsize=(_fig_width, _fig_height))
contour = ax.contourf(X, Y, Z, levels=20, cmap=_colormap)
plt.colorbar(contour, label='Value')
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_title('Contour Plot')

Example 4: Using External Data

CSV file (data.csv):

time,temperature,humidity
0,20.5,65
1,21.2,63
2,22.1,60
3,23.5,58
4,24.0,55

Script:

# x_data and y_data loaded from columns 0 and 1
# df contains full DataFrame

fig, ax1 = plt.subplots()

ax1.plot(df.iloc[:,0], df.iloc[:,1], 'b-', label='Temperature')
ax1.set_xlabel('Time (hours)')
ax1.set_ylabel('Temperature (°C)', color='b')

ax2 = ax1.twinx()
ax2.plot(df.iloc[:,0], df.iloc[:,2], 'r--', label='Humidity')
ax2.set_ylabel('Humidity (%)', color='r')

plt.title('Temperature and Humidity Over Time')

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🐛 Troubleshooting

Common Issues

Extension not appearing in menu

Solutions:

1. Check file locations match the expected structure
2. Verify file permissions:

   # Linux/macOS
   chmod +x plt_ink.py

3. Check Inkscape error console: View → Messages
4. Restart Inkscape completely
5. Verify Python path in extension settings

"Python not found" error

Solutions:

1. In the extension dialog, set Python Path to your Python executable:

   # Windows
   C:\Python39\python.exe
   
   # macOS/Linux
   /usr/bin/python3
   

2. Check Python installation:

   python --version
   python3 --version

"Matplotlib not installed" error

Solutions:

1. Install matplotlib for your Python version:

   pip install matplotlib
   # or
   pip3 install matplotlib

2. Verify installation:

   python -c "import matplotlib; print(matplotlib.__version__)"

3. Ensure you're using the same Python that Inkscape uses

Script execution fails

Debug Steps:

1. Enable Keep Temp Files in Advanced tab
2. Check the log file:

   # Windows
   %TEMP%\matplotlib_inkscape_debug.log
   
   # macOS/Linux
   /tmp/matplotlib_inkscape_debug.log
   

3. Check the generated script in temp directory
4. Run the script manually to see errors:

   python /tmp/matplotlib_output_*.py

Figure not appearing or wrong size

Solutions:

1. Check output format (SVG recommended for vector graphics)
2. Verify figure dimensions aren't too large
3. Check document units match expectations
4. Try enabling Embed Image option

Debug Tips

Check Log File: The extension writes detailed logs to:

[temp-directory]/matplotlib_inkscape_debug.log

Test Inline Code: Start with a minimal example:

plt.plot([1, 2, 3], [1, 4, 9])
plt.title('Test Plot')

Verify Script Generation:

1. Enable Save Script option
2. Set Script Save Path to a known location
3. Examine the generated script for issues

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📚 Script Bank

Available Scripts

Line Plots (line_plots/)

• basic_line.py - Simple line plot
• multi_line.py - Multiple lines with legend
• styled_line.py - Custom line styles

Scatter Plots (scatter_plots/)

• basic_scatter.py - Simple scatter plot
• bubble_chart.py - Size-coded scatter
• colored_scatter.py - Color-mapped scatter

Bar Charts (bar_charts/)

• basic_bar.py - Vertical bar chart
• horizontal_bar.py - Horizontal bars
• grouped_bar.py - Grouped comparison
• stacked_bar.py - Stacked bars

Statistical (statistical/)

• histogram.py - Histogram with density
• box_plot.py - Box and whisker
• violin_plot.py - Violin plot

Scientific (scientific/)

• contour.py - Contour plot
• heatmap.py - 2D heatmap
• vector_field.py - Quiver plot

Time Series (time_series/)

• time_plot.py - Time-indexed data
• financial.py - OHLC/candlestick

Publication (publication/)

• paper_figure.py - Journal-ready styling
• subplot_grid.py - Multi-panel figures

Creating Custom Scripts

Add scripts to plt_ink_scripts/[category]/:

"""
My Custom Plot Template
Description of what this plot does
"""

import numpy as np
import matplotlib.pyplot as plt

# Use pre-defined variables
fig, ax = plt.subplots(figsize=(_fig_width, _fig_height))

# Your plotting code here
x = np.linspace(0, 10, 100)
y = np.sin(x)

ax.plot(x, y)
ax.set_title('My Custom Plot')

if _show_grid:
    ax.grid(True, alpha=0.3)
if _show_legend:
    ax.legend(loc=_legend_position)

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📝 File Structure

plt_ink/
├── plt_ink.py              # Main extension code
├── plt_ink.inx             # Inkscape extension definition
├── README.md               # This file
├── LICENSE                 # MIT License
└── plt_ink_scripts/        # Script bank directory
    ├── line_plots/
    │   ├── basic_line.py
    │   └── ...
    ├── scatter_plots/
    ├── bar_charts/
    ├── statistical/
    ├── scientific/
    ├── time_series/
    └── publication/

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🤝 Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

Adding Scripts to Bank:

• Create your script in the appropriate category folder
• Include docstring with description
• Use pre-defined variables (_fig_width, _show_grid, etc.)
• Test with the extension before submitting

Development Setup:

git clone https://github.com/YouvenZ/plt_ink.git
cd plt_ink
# Symlink to extensions directory for testing
# Windows (PowerShell as Admin)
New-Item -ItemType Junction -Path "$env:APPDATA\inkscape\extensions\plt_ink" -Target "$(Get-Location)"

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📄 License

This project is licensed under the MIT License - see LICENSE file for details.

Copyright (c) 2026 Rachid, Youven ZEGHLACHE

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📧 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: youvenz.pro@gmail.com

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🔄 Changelog

v1.0.0 (2026-02-19)

• ✨ Initial release
• ✅ Inline code execution
• ✅ External file loading
• ✅ Script bank with templates
• ✅ SVG, PNG, PDF output formats
• ✅ Data import (CSV, Excel, JSON, Text)
• ✅ Multiple matplotlib styles
• ✅ Custom positioning options
• ✅ LaTeX support
• ✅ Comprehensive logging