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Creating a Custom Sankey Plot with Matplotlib's Bezier Curves
In this tutorial, we'll explore how to create a Sankey plot using Matplotlib's Bezier curves, a powerful tool that allows drawing lines in any shape. Although Matplotlib does not directly support Sankey plots with Bezier curves, we can achieve a similar effect by manipulating the curves manually.
Step 1: Understand Bezier Curves
Bezier curves are smooth curves that can be used to create complex, curved shapes. They are defined by a series of control points.
Step 2: Install Necessary Libraries
First, ensure you have Matplotlib and NumPy installed. If not, you can install them using pip:
Step 3: Basic Bezier Curve Implementation
Here's how you can implement a simple Bezier curve:
```python import numpy as np import matplotlib.pyplot as plt
def bezier_curve(points, num_points=100): # ... (code for bezier_curve function)
control_points = [[0, 0], [0.5, 1], [1, 0], [1.5, -1], [2, 0]]
curve_x, curve_y = bezier_curve(control_points)
plt.plot(curve_x, curve_y, label='Bezier Curve') plt.legend() plt.show() ```
Step 4: Adapting for Sankey Plot
Creating a Sankey plot involves designing flow diagrams where the width of each band represents the magnitude of the flow it represents. We can use Bezier curves to create the bands by controlling their width along the curve.
- Define the Flow Bands: Determine the path of each flow band using Bezier curves. Each band should have two parallel curves that define its edges.
- Plotting Bands: Use the Bezier curves to plot the flow bands. You can adjust the width of the bands by manipulating the control points of the parallel curves.
Here's a simplified approach to plotting flow bands using Bezier curves:
```python
inner_control_points = [[0, 0], [0.5, 0.5], [1, 0]] outer_control_points = [[0, 0.2], [0.5, 0.8], [1, 0.2]]
inner_x, inner_y = bezier_curve(inner_control_points) outer_x, outer_y = bezier_curve(outer_control_points)
plt.fill_between(inner_x, inner_y, outer_y, alpha=0.5, label='Flow Band') plt.legend() plt.show() ```
This approach allows you to create smooth, curved bands that resemble the flow segments in a Sankey plot. However, it requires manual adjustment of the Bezier curves to match the typical structure of a Sankey diagram.
Conclusion
While Matplotlib does not provide native support for integrating Bezier curves into Sankey plots, you can achieve a similar effect by using Bezier curves to define the paths of flow bands. This method requires more manual control but can lead to visually appealing and custom Sankey plots.
You can find the complete tutorial and code at this link. The tutorial provides several examples of using Matplotlib's Path Object to draw quadratic and cubic bezier curves, as well as a simple example of using the Path Object to illustrate the concept. Additionally, the tutorial demonstrates how to use Matplotlib's built-in patch to draw the rectangles in a Sankey plot.
Remember, there are several packages available to draw the Sankey plot in one line, such as , , and . These packages can be a more convenient alternative if you prefer a more automated approach.
Happy coding!
Data-and-cloud-computing technologies can facilitate the storage and processing of the vast amounts of data required to manage and analyze the complex Bezier curves used in custom Sankey plot creation. The implementation and manipulation of these curves can be optimized using technology to improve efficiency and visual appeal.
