fix&perf: correct power law R² calculation in structure evaluator

[CHERRY-ui8]

This PR implements a crucial fix and performance improvement in the _calculate_powerlaw_r2 function within the structure evaluator. The previous implementation incorrectly applied the power law fitting, potentially leading to inaccurate R² values. The updated approach now correctly models the relationship between degree and frequency on a log-log scale, ensuring a more statistically sound evaluation of power law distributions in graph structures. Additionally, it includes a robustness check to handle cases with insufficient unique degrees.

[gemini-code-assist]

Summary of Changes

Hello @CHERRY-ui8, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request implements a crucial fix and performance improvement in the _calculate_powerlaw_r2 function within the structure evaluator. The previous implementation incorrectly applied the power law fitting, potentially leading to inaccurate R² values. The updated approach now correctly models the relationship between degree and frequency on a log-log scale, ensuring a more statistically sound evaluation of power law distributions in graph structures. Additionally, it includes a robustness check to handle cases with insufficient unique degrees.

Highlights

• Corrected Power Law R² Calculation: The methodology for calculating the R² value for power law distributions has been fundamentally corrected to align with standard statistical practices.
• Improved Fitting Model: The power law fit now correctly models the relationship between the logarithm of frequency and the logarithm of degree, rather than an arbitrary index.
• Robustness Check Added: A new check has been introduced to ensure a sufficient number of unique degrees are present before attempting power law fitting, preventing erroneous calculations for uniform graphs.

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[gemini-code-assist]

Code Review

This pull request correctly refactors the power law R² calculation by fitting the degree distribution's frequency against degree values on a log-log scale, which is the standard method. The previous implementation was incorrect. The change also improves performance by using collections.Counter instead of sorting the entire list of degrees. I have one suggestion to further simplify the code.

[gemini-code-assist]

This block for populating degree_values and frequencies can be made more concise and efficient. The if deg > 0 and freq > 0: check is redundant because degrees are already filtered for positive values on line 78, and Counter does not store items with a frequency of zero. You can use the zip(*...) idiom for a more Pythonic and performant one-liner to replace this entire block.

Suggested change

	degree_values = []
	frequencies = []
	for deg, freq in sorted(degree_counts.items()):
	if deg > 0 and freq > 0:
	degree_values.append(deg)
	frequencies.append(freq)
	degree_values, frequencies = zip(*sorted(degree_counts.items()))