How to plot scatter masked points and add a line demarking masked regions in Matplotlib?

To plot scattered masked points and add a line to demark the masked regions, we can use matplotlib's masking capabilities along with the scatter() and plot() methods. This technique is useful for visualizing data that falls within or outside specific boundaries.

Steps

• Set the figure size and adjust the padding between and around the subplots
• Create N, r0, x, y, area, c, r, area1 and area2 data points using NumPy
• Plot x and y data points using scatter() method with different markers for masked regions
• To demark the masked regions, plot the boundary curve using plot() method
• Display the figure using show() method

Example

Let's create a scatter plot with points masked based on their distance from the origin ?

import matplotlib.pyplot as plt
import numpy as np

# Set figure parameters
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Generate random data
N = 100
r0 = 0.6
x = 0.9 * np.random.rand(N)
y = 0.9 * np.random.rand(N)
area = (20 * np.random.rand(N))**2
c = np.sqrt(area)

# Calculate distance from origin
r = np.sqrt(x ** 2 + y ** 2)

# Create masked arrays based on distance threshold
area1 = np.ma.masked_where(r < r0, area)  # Points outside radius
area2 = np.ma.masked_where(r >= r0, area)  # Points inside radius

# Plot scattered points with different markers
plt.scatter(x, y, s=area1, marker='^', c=c, label='Outside radius')
plt.scatter(x, y, s=area2, marker='o', c=c, label='Inside radius')

# Draw the boundary line (quarter circle)
theta = np.arange(0, np.pi / 2, 0.01)
plt.plot(r0 * np.cos(theta), r0 * np.sin(theta), 'k-', linewidth=2, label='Boundary')

plt.legend()
plt.xlabel('X')
plt.ylabel('Y')
plt.title('Scatter Plot with Masked Regions')
plt.show()

How It Works

The masking process works by:

• Distance calculation: r = np.sqrt(x ** 2 + y ** 2) computes the distance of each point from the origin
• Conditional masking: np.ma.masked_where() creates masked arrays where certain conditions are met
• Different markers: Points inside the radius use circles ('o'), while points outside use triangles ('^')
• Boundary visualization: A quarter circle is drawn using parametric equations to show the demarcation line

Key Parameters

Conclusion

Using np.ma.masked_where() with different markers effectively visualizes data regions. The boundary line helps clearly separate the masked areas, making the plot both informative and visually appealing.