MDock

A Python package for creating dockable matplotlib figures using PyQt6. MDock provides a professional docking interface where matplotlib figures can be dynamically arranged, resized, and managed as draggable dock widgets.

Overview

MDock integrates matplotlib's figure rendering capabilities with PyQt6's powerful docking system (via PyQt6Ads). This allows you to create sophisticated multi-figure applications where figures can be:

• Docked and undocked - freely arrange figure windows
• Organized in layouts - organize multiple figures in a tabbed or side-by-side interface
• Saved and restored - persist window layouts between sessions
• Controlled programmatically - manage figures from Python with a simple API

Installation

Install MDock using pip:

pip install mdock

Requirements

• Python 3.9 or higher
• matplotlib
• PyQt6Ads

Quick Start

import matplotlib.pyplot as plt
import mdock

# Set the dock window title (optional)
mdock.title("My Application")

# Create some matplotlib figures
fig1, ax1 = plt.subplots()
ax1.plot([1, 2, 3, 4], [1, 4, 2, 3])
ax1.set_title("Figure 1")

fig2, ax2 = plt.subplots()
ax2.scatter([1, 2, 3, 4], [1, 4, 2, 3])
ax2.set_title("Figure 2")

Features

• Docking Interface: Dock multiple matplotlib figures in a professional Qt interface
• Persistent Layouts: Save and restore dock configurations between sessions
• Toolbar Controls: Built-in toolbar for managing dock states
• Easy API: Simple functions for common operations

API Reference

Module Functions

show()

Display the MDock window containing all docked figures.

import mdock
mdock.show()

drawnow()

Redraw all canvas figures in the dock and flush events. Use this to update all visible plots.

import mdock
mdock.drawnow()

title(t)

Set the title of the MDock window.

Parameters:

• t (str): The window title

import mdock
mdock.title("My Dock Window")

store_state()

Save the current dock layout, window geometry, and perspective to persistent storage.

import mdock
mdock.store_state()

restore_state()

Restore the previously saved dock layout and window geometry.

import mdock
mdock.restore_state()

Usage Examples

Example 1: Basic Multi-Figure Application

import matplotlib.pyplot as plt
import mdock

# Set window title
mdock.title("Data Visualization")

# Create multiple figures
for i in range(3):
    fig, ax = plt.subplots(num=f'Data Visualization number {i+1}')
    ax.plot(range(10), [x**i for x in range(10)])
    ax.set_title(f"Plot {i+1}")

Example 2: Saving and Restoring Layouts

import matplotlib.pyplot as plt
import mdock

# Create some plots
fig1, ax1 = plt.subplots(num="Plot 1")
ax1.plot([1, 2, 3], [1, 2, 3])

fig2, ax2 = plt.subplots(num="Plot 2")
ax2.plot([1, 2, 3], [3, 2, 1])

# Show the docking interface
mdock.show()

# Restore previous layout (after figures are created). 
# If a layout for these figures has been saved, it will be restored.
mdock.restore_state()

# (...)

# Later, after manually modifying the figure layout, save the current layout
mdock.store_state()

Example 3: Real-time Updates

import matplotlib.pyplot as plt
import mdock
import numpy as np

# Enable interactive mode
plt.ion()

# Plot data interactively - updates appear immediately
for i in range(100):
    plt.figure("My Real-Time Plot")
    plt.clf()
    x = np.linspace(0, 10, 100)
    y = np.sin(x + i/10)
    plt.plot(x, y)   
    # Update the plot     
    mdock.drawnow()

Notes

• Dock perspectives and window geometry are stored using Qt's QSettings, which automatically uses the appropriate storage location for your OS (Registry on Windows, plist on macOS, etc.)
• The MDock class uses class variables to maintain a single shared docking interface across all figures
• The first time a figure is created, the MDock window and docking manager are initialized
• Toolbar buttons allow manual storage and restoration of dock states

License

MIT License - See LICENSE file for details

Author

Mikkel N. Schmidt (mnsc@dtu.dk)