Project: 039_A_Theoretically-Principled_Sparse_Connected_and_Ri | Function: get_chull_graph (iclr)

system: You are an expert Python programmer implementing algorithms from scientific papers.
Complete the masked function based on the algorithm description.
Follow Python best practices and maintain consistent code style.
Return **only** the complete Python function code.

user: Complete this Python function:

**DESCRIPTION:** Constructs convex hull graph from projected points on unit sphere, implementing Step 2 of SCHull algorithm with theoretical sparsity guarantees

**KEY TERMS:** {
  "ConvexHull(data,qhull_options='QJ')": "Conv ({px(xi) | i ∈ V})",
  "hull.simplices": "polyhedral graph edges and faces",
  "edges": "SCHull graph edge connections"
}

**CONTEXT CODE:** from abc import ABCMeta

import numpy as np
from scipy.spatial import ConvexHull

class Qhull(metaclass=ABCMeta):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)

    def get_chull_graph(self, data, rank, n, *args, **kwargs):
        raise NotImplementedError("Function implementation has been masked for testing")

Complete the function implementation replacing "raise NotImplementedError".