MizuhoAOKI/python_simple_mppi — GitHub trend

FINDING #2108 · UNIT ID 689511986

MizuhoAOKI/python_simple_mppi

Python implementation of MPPI (Model Predictive Path-Integral) controller to understand the basic idea. Mandatory dependencies are numpy and matplotlib only.

[ JUPYTER NOTEBOOK ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.0121

ENGAGEMENT0.62

FRESHNESS1.00

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

2% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

6.33

ACCEL

-6.50

RETENTION

13.3%

PEAK 2026-09-22 · FORK-RETENTION 40.0% · 19 STARS / WINDOW

Author Audience

AUDIENCE

485

FOLLOWERS

297

OWNER ★

1,883

Engagement Signals

FORKS

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 19 / 19 (DIVERSITY 1.00)

Why This Is A Finding

MizuhoAOKI/python_simple_mppi собрал 19 звёзд за окно, тогда как у автора всего 297 подписчиков — эффективная аудитория ≈ 485. Это даёт surprise-индекс 0.0121 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 40.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

Related Findings

RANKS ABOVE 78% OF 9535 FINDINGS

#1254navaneethkrishnansuresh/Inference-Engineering[ JUPYTER NOTEBOOK ]0.0158 #1351CalvinXKY/InfraTech[ JUPYTER NOTEBOOK ]0.0141 #1479Ahren09/AgentReview[ JUPYTER NOTEBOOK ]0.0125 #1836dbdmg/llm[ JUPYTER NOTEBOOK ]0.00902 #1878Nicolepcx/ai-agents-the-definitive-guide[ JUPYTER NOTEBOOK ]0.00876

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9535 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.010.00+0.01ABOVE 78%

VELOCITY6.335.67+0.67ABOVE 54%

RETENTION13.3%44.1%-30.8 PPABOVE 30%

FORKS81324-243ABOVE 26%

SURPRISE0.010.00+0.01ABOVE 66%