94 lines
3.0 KiB
Python
94 lines
3.0 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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# Fix the random seed for reproducibility
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np.random.seed(0)
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# 1. Generate NORMAL DATA (e.g. points roughly around the origin)
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# We'll keep them relatively close together so that a circle can enclose them easily.
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normal_data = np.random.randn(50, 2) * 0.75
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# 2. Generate ANOMALOUS DATA
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# - Cluster 1: 3 points close together
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anomaly_cluster_1 = np.array([[3.0, 3.0], [3.2, 3.1], [2.8, 2.9], [0.4, 4.0]])
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# - Cluster 2: A single point
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# 3. Compute the center and radius for a boundary circle around normal data
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center = normal_data.mean(axis=0)
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distances = np.linalg.norm(normal_data - center, axis=1)
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radius = (
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np.max(distances) + 0.2
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) # Add a small margin to ensure all normal points are inside
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# Create coordinates for plotting the circular boundary
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theta = np.linspace(0, 2 * np.pi, 200)
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circle_x = center[0] + radius * np.cos(theta)
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circle_y = center[1] + radius * np.sin(theta)
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# 4. Plot the data
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plt.figure(figsize=(7, 7))
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# Scatter normal points with 'o'
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plt.scatter(
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normal_data[:, 0], normal_data[:, 1], marker="o", color="blue", label="Normal Data"
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)
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# Scatter anomalous points with 'x', but separate them by cluster for clarity
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plt.scatter(
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anomaly_cluster_1[:, 0],
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anomaly_cluster_1[:, 1],
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marker="x",
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color="red",
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label="Anomalies",
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)
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# Plot the boundary (circle) around the normal data
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plt.plot(circle_x, circle_y, linestyle="--", color="black", label="Boundary")
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# 5. Annotate/label the clusters
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# Label the normal cluster near its center
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# plt.text(center[0], center[1],
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# 'Normal Cluster',
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# horizontalalignment='center',
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# verticalalignment='center',
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# fontsize=9,
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# bbox=dict(facecolor='white', alpha=0.7))
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#
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# # Label anomaly cluster 1 near its centroid
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# ac1_center = anomaly_cluster_1.mean(axis=0)
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# plt.text(ac1_center[0], ac1_center[1],
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# 'Anomaly Cluster 1',
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# horizontalalignment='center',
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# verticalalignment='center',
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# fontsize=9,
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# bbox=dict(facecolor='white', alpha=0.7))
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#
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# # Label anomaly cluster 2
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# ac2_point = anomaly_cluster_2[0]
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# plt.text(ac2_point[0]+0.2, ac2_point[1],
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# 'Anomaly Cluster 2',
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# horizontalalignment='left',
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# verticalalignment='center',
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# fontsize=9,
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# bbox=dict(facecolor='white', alpha=0.7))
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# Add legend and make plot look nice
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plt.legend(loc="upper left")
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# plt.title('2D Scatter Plot Showing Normal and Anomalous Clusters')
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plt.xlabel("x")
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plt.ylabel("y")
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plt.tick_params(
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axis="both", # changes apply to the x-axis
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which="both", # both major and minor ticks are affected
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bottom=False, # ticks along the bottom edge are off
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top=False, # ticks along the top edge are off
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left=False, # ticks along the top edge are off
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right=False, # ticks along the top edge are off
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labelbottom=False,
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labelleft=False,
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) #
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# plt.grid(True)
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plt.axis("equal") # Makes circles look circular rather than elliptical
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plt.savefig("scatter_plot.png")
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