RRepoGEO

REPOGEO REPORT · LITE

rlabbe/filterpy

Default branch master · commit 3b51149e · scanned 5/22/2026, 2:52:56 PM

GitHub: 3,829 stars · 671 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
88 /100
Healthy
Category recall
2 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface rlabbe/filterpy, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    kalman-filter, bayesian-filters, state-estimation, python, optimal-estimation, signal-processing, control-systems, data-science
  • mediumhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://filterpy.readthedocs.io/en/latest/
  • mediumreadme#3
    Refine README's opening sentence to highlight pedagogical focus and book connection

    Why:

    CURRENT
    FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python.
    COPY-PASTE FIX
    FilterPy is a Python library providing pedagogically-driven implementations of Kalman filters and other optimal and non-optimal estimation filters, designed as a direct companion to the book 'Kalman and Bayesian Filters in Python'.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
2 / 2
100% of queries surface rlabbe/filterpy
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
20%
Of all named tools, what % are you?
Top rival
pykalman/pykalman
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. pykalman/pykalman · recommended 2×
  2. scikit-learn/scikit-learn · recommended 1×
  3. NumPy/SciPy · recommended 1×
  4. scipy/scipy · recommended 1×
  5. pymc-devs/pymc · recommended 1×
  • CATEGORY QUERY
    What Python library helps implement Kalman filters for state estimation?
    you: #1
    AI recommended (in order):
    1. FilterPy (rlabbe/filterpy) ← you
    2. PyKalman (pykalman/pykalman)
    3. scikit-learn (scikit-learn/scikit-learn)
    4. NumPy/SciPy
    Show full AI answer
  • CATEGORY QUERY
    Need a Python tool for optimal state estimation and Bayesian filtering techniques.
    you: #1
    AI recommended (in order):
    1. FilterPy (rlabbe/filterpy) ← you
    2. PyKalman (pykalman/pykalman)
    3. SciPy.signal (scipy/scipy)
    4. PyMC (pymc-devs/pymc)
    5. Stan (pystan/pystan)
    6. Statsmodels (statsmodels/statsmodels)
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of rlabbe/filterpy?
    pass
    AI named rlabbe/filterpy explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts rlabbe/filterpy in production, what risks or prerequisites should they evaluate first?
    pass
    AI named rlabbe/filterpy explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo rlabbe/filterpy solve, and who is the primary audience?
    pass
    AI named rlabbe/filterpy explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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rlabbe/filterpy — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite