Capture current mission, AI, map and administration development

Include the current addon, terrain integrations, tools, regression tests and recorded development evidence.
2026-10-13 22:52:53 +02:00
parent a951a96edc
commit 6a667d8deb
8104 changed files with 2124945 additions and 2061 deletions
@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+"""Summarize ERR PERF windows from performance logs (also accepts older console logs).
+
+Script wall_ms_per_s measures scoped elapsed time, not CPU utilization.
+Parent/child scopes overlap; engine values are sampled gauges, not scopes.
+"""
+import argparse
+import csv
+import math
+import re
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+FIELDS = (
+    'run', 'window', 'elapsed_ms', 'final', 'phase_start', 'phase_end',
+    'metric', 'samples', 'sum', 'min', 'max', 'zero', 'over50', 'over100',
+)
+INTEGER_FIELDS = ('window', 'elapsed_ms', 'phase_start', 'phase_end',
+                  'samples', 'zero', 'over50', 'over100')
+SCRIPT_METRICS = {
+    'mission_tick_ms', 'maintenance_ms', 'civilians_ms', 'forces_ms',
+    'observers_ms', 'hq_tick_ms', 'listeners_ms', 'hq_prep_ms',
+    'hq_hunters_ms', 'hq_garrisons_ms', 'hq_convoys_ms', 'hq_bodies_ms',
+    'hq_radio_index_ms', 'hq_reports_ms', 'hq_planner_ms', 'hq_support_ms',
+    'hq_journal_ms', 'garrison_work_ms', 'performance_flush_ms',
+}
+
+
+def read_rows(paths):
+    seen = {}
+    for path in paths:
+        with path.open(encoding='utf-8', errors='replace') as stream:
+            for number, line in enumerate(stream, 1):
+                marker = line.find('ERR PERF run=')
+                if marker < 0:
+                    continue
+                values = dict(re.findall(r'(\w+)=([^\s]+)', line[marker:]))
+                try:
+                    row = {key: values[key] for key in FIELDS}
+                    for key in INTEGER_FIELDS:
+                        row[key] = int(row[key])
+                        if row[key] < 0:
+                            raise ValueError(f'negative {key}')
+                    for key in ('sum', 'min', 'max'):
+                        row[key] = float(row[key])
+                        if not math.isfinite(row[key]) or row[key] < 0:
+                            raise ValueError(f'invalid {key}')
+                    if row['elapsed_ms'] == 0 or row['samples'] == 0:
+                        raise ValueError('empty window/sample count')
+                    if row['min'] > row['max']:
+                        raise ValueError('min exceeds max')
+                    if not 0 <= row['over100'] <= row['over50'] <= row['samples']:
+                        raise ValueError('invalid threshold counts')
+                    if row['zero'] > row['samples']:
+                        raise ValueError('invalid zero count')
+                except (KeyError, ValueError) as error:
+                    raise ValueError(f'{path}:{number}: malformed performance row: {error}') from error
+                key = row['run'], row['window'], row['metric']
+                if key in seen:
+                    if seen[key] != row:
+                        raise ValueError(f'{path}:{number}: conflicting duplicate {key}')
+                    continue
+                seen[key] = row
+    return list(seen.values())
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('logs', nargs='+', type=Path)
+    parser.add_argument('--csv', action='store_true', help='output individual window rows as CSV')
+    args = parser.parse_args()
+    try:
+        rows = read_rows(args.logs)
+        if not rows:
+            raise ValueError('no ERR PERF measurement rows found')
+    except (OSError, ValueError) as error:
+        parser.error(str(error))
+    if args.csv:
+        writer = csv.DictWriter(sys.stdout, fieldnames=FIELDS)
+        writer.writeheader()
+        writer.writerows(rows)
+        return
+    grouped = defaultdict(list)
+    for row in rows:
+        grouped[row['run'], row['metric']].append(row)
+    print('Scope times overlap: do not add mission_tick, hq_tick and HQ children.')
+    print('Wall timings have 1 ms resolution; zero does not prove zero cost.')
+    print('Engine metrics are ~1 Hz samples of engine-reported values, NOT AI-only time.')
+    previous_run = None
+    for (run, metric), items in sorted(grouped.items()):
+        if run != previous_run:
+            print(f'\nRun {run}')
+            print(f'{"metric":26s} {"samples":>8s} {"mean":>10s} {"max":>10s} {"zero":>8s} {"wall_ms/s":>10s}')
+            previous_run = run
+        count = sum(item['samples'] for item in items)
+        total = sum(item['sum'] for item in items)
+        elapsed = sum(item['elapsed_ms'] for item in items)
+        maximum = max(item['max'] for item in items)
+        zero = sum(item['zero'] for item in items)
+        rate = f'{1000 * total / elapsed:.3f}' if metric in SCRIPT_METRICS else '-'
+        print(f'{metric:26s} {count:8d} {total / count:10.3f} {maximum:10.3f} {zero:8d} {rate:>10s}')
+    print('\nMeans/rates include only windows containing that metric; use --csv to compare matching windows and player counts.')
+    print('No native-AI timing or predicted offload speedup is inferred.')
+
+
+if __name__ == '__main__':
+    main()