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Investigate VOACAP prediction performance issues#121

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skyelaird merged 1 commit intomainfrom
claude/investigate-voacap-performance-01Vf4WAjrj7sPHuuj2RQbzBV
Nov 18, 2025
Merged

Investigate VOACAP prediction performance issues#121
skyelaird merged 1 commit intomainfrom
claude/investigate-voacap-performance-01Vf4WAjrj7sPHuuj2RQbzBV

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@skyelaird skyelaird commented Nov 18, 2025

Summary

Investigated claims in the Known Issues wiki page and found MAJOR inaccuracies in performance and memory usage documentation.

Key Findings

Performance Claims - COMPLETELY WRONG

  • Wiki claims: 60-90 seconds for dashboard (840 predictions)
  • Actual measured: 5.31 seconds
  • Reality: 11-17x FASTER than documented

Performance details:

  • Single prediction: 5-6 ms (wiki claimed 200-500 ms)
  • Dashboard generation: 5.3s (wiki claimed 60-90s)
  • Throughput: 158 predictions/second

Memory Claims - COMPLETELY WRONG

  • Wiki claims: ~50 MB for CCIR/URSI maps
  • Actual on-disk size: 556 KB total
  • Reality: 50-100x LOWER than documented

Memory details:

  • CCIR/URSI data: 556 KB on disk, ~1 MB in memory
  • Single prediction: ~10-20 MB total process (wiki claimed 60 MB)
  • Dashboard: ~20-30 MB peak (wiki claimed 100 MB)

Antenna Support - PARTIALLY WRONG

  • Wiki claims Yagi antennas are "Not Yet Supported"
  • Reality: ThreeElementYagi class EXISTS and is functional
  • Only complex multi-element Yagi arrays are unsupported

Accurate Claims

  • ✓ Es (Sporadic E) modeling not implemented (confirmed)
  • ✓ 86.6% validation pass rate (appears accurate)

Files Added

  1. WIKI_ACCURACY_REPORT.md - Detailed analysis of wiki inaccuracies
  2. KNOWN_ISSUES_CORRECTED.md - Corrected version of Known Issues
  3. test_dashboard_performance.py - Benchmark for dashboard scenario
  4. test_memory_usage.py - Memory profiling test

Recommendations

The Known Issues wiki page requires immediate correction:

  • Remove "Performance Limitations" as a major issue
  • Update all timing claims to reflect actual performance
  • Correct memory usage claims (50MB → 1MB)
  • Move Yagi from "not supported" to "supported"
  • Reframe performance as a STRENGTH, not a weakness

Test Results

Dashboard Scenario (10 regions × 7 bands × 12 hours = 840 predictions):
Total time: 5.31 seconds
Average: 6.32 ms per prediction
Rate: 158.3 predictions/second
Wiki claim: 60-90 seconds
Speedup: 11-17x faster than claimed

Issue: None (investigation only)

Description

A clear and concise description of what this PR does.

Type of Change

  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • Documentation update
  • Performance improvement
  • Code refactoring
  • Test coverage improvement

Related Issues

Closes #(issue number)
Related to #(issue number)

Changes Made

  • Change 1
  • Change 2
  • Change 3

Testing

Describe the tests you've run to verify your changes:

Test Configuration

  • Python version:
  • Operating System:
  • NumPy/SciPy versions:

Test Results

# Command used to test
python -m pytest tests/

# Or validation command
python test_voacap_reference.py
  • All existing tests pass
  • New tests added for new functionality
  • Validation pass rate maintained or improved
  • No performance regression

Validation Checklist

  • Code follows PEP 8 style guidelines
  • Docstrings added/updated for public functions
  • Type hints added where appropriate
  • Comments added for complex logic
  • Documentation updated (README, USAGE, etc.)
  • CHANGELOG.md updated
  • No new warnings or errors introduced

Performance Impact

  • No performance impact
  • Performance improved (provide benchmarks)
  • Minor performance regression (justified because...)
  • Not applicable

Benchmarks (if applicable)

Before: X seconds
After: Y seconds
Change: Z% improvement/regression

Breaking Changes

If this PR introduces breaking changes, describe:

  1. What breaks
  2. Migration path for users
  3. Why this change is necessary

Screenshots/Output (if applicable)

For dashboard changes or output format changes, include before/after screenshots or sample output.

Additional Notes

Any additional information that reviewers should know:

  • Assumptions made
  • Trade-offs considered
  • Future work needed
  • Dependencies added/removed

Reviewer Checklist

For maintainers reviewing this PR:

  • Code quality is acceptable
  • Tests are comprehensive
  • Documentation is clear
  • Validation results are acceptable
  • No security issues introduced
  • Backward compatibility maintained (or breaking changes justified)

## Summary
Investigated claims in the Known Issues wiki page and found MAJOR
inaccuracies in performance and memory usage documentation.

## Key Findings

### Performance Claims - COMPLETELY WRONG
- Wiki claims: 60-90 seconds for dashboard (840 predictions)
- Actual measured: 5.31 seconds
- **Reality: 11-17x FASTER than documented**

Performance details:
- Single prediction: 5-6 ms (wiki claimed 200-500 ms)
- Dashboard generation: 5.3s (wiki claimed 60-90s)
- Throughput: 158 predictions/second

### Memory Claims - COMPLETELY WRONG
- Wiki claims: ~50 MB for CCIR/URSI maps
- Actual on-disk size: 556 KB total
- **Reality: 50-100x LOWER than documented**

Memory details:
- CCIR/URSI data: 556 KB on disk, ~1 MB in memory
- Single prediction: ~10-20 MB total process (wiki claimed 60 MB)
- Dashboard: ~20-30 MB peak (wiki claimed 100 MB)

### Antenna Support - PARTIALLY WRONG
- Wiki claims Yagi antennas are "Not Yet Supported"
- **Reality: ThreeElementYagi class EXISTS and is functional**
- Only complex multi-element Yagi arrays are unsupported

### Accurate Claims
- ✓ Es (Sporadic E) modeling not implemented (confirmed)
- ✓ 86.6% validation pass rate (appears accurate)

## Files Added

1. **WIKI_ACCURACY_REPORT.md** - Detailed analysis of wiki inaccuracies
2. **KNOWN_ISSUES_CORRECTED.md** - Corrected version of Known Issues
3. **test_dashboard_performance.py** - Benchmark for dashboard scenario
4. **test_memory_usage.py** - Memory profiling test

## Recommendations

The Known Issues wiki page requires immediate correction:
- Remove "Performance Limitations" as a major issue
- Update all timing claims to reflect actual performance
- Correct memory usage claims (50MB → 1MB)
- Move Yagi from "not supported" to "supported"
- Reframe performance as a STRENGTH, not a weakness

## Test Results

```
Dashboard Scenario (10 regions × 7 bands × 12 hours = 840 predictions):
Total time: 5.31 seconds
Average: 6.32 ms per prediction
Rate: 158.3 predictions/second
Wiki claim: 60-90 seconds
Speedup: 11-17x faster than claimed
```

Issue: None (investigation only)
@skyelaird skyelaird merged commit eeca754 into main Nov 18, 2025
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2 participants