import numpy as np
import matplotlib.pyplot as plt

# Example data
x = np.random.rand(1000)  # Sample x values
y = np.random.rand(1000)  # Sample y values

# Function to calculate marker size based on the number of points
def calculate_marker_size(num_points):
    # Define the minimum and maximum marker sizes
    min_marker_size = 1.0
    max_marker_size = 10.0
    
    # Define the range of points where marker size varies
    min_points = 1000
    max_points = 100000
    
    # Calculate the marker size based on a linear interpolation
    if num_points <= min_points:
        return min_marker_size
    elif num_points >= max_points:
        return max_marker_size
    else:
        # Linear interpolation between min and max marker sizes
        slope = (max_marker_size - min_marker_size) / (max_points - min_points)
        return min_marker_size + slope * (num_points - min_points)

# Calculate marker size based on the number of points
marker_size = calculate_marker_size(len(x))

# Create the plot with dynamic marker size
plt.figure(figsize=(8, 6))
plt.scatter(x, y, marker='o', s=marker_size, alpha=0.5)
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Scatter Plot with Dynamic Marker Size')
plt.grid(True)
plt.show()

在此示例中，calculate_marker_size函数将点数作为输入，并使用最小和最大标记大小之间的线性插值计算标记大小。您可以调整min_marker_size、max_marker_size、min_points和max_points值，以根据首选项自定义行为。
此方法根据数据中的点数动态调整标记大小，无论数据点数是少还是多，都可以获得更具视觉吸引力的图。