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pymolresponse berquist/pymolresponse

Molecular frequency-dependent response properties for arbitrary operators

HEALTH 81 / Healthy
// solo builder// hidden gem// legacy hero// under pressure pythonquantum-chemistrycomputational-chemistrypython-chemistry

// readme

pymolresponse

Molecular frequency-dependent response properties for arbitrary operators.

For documentation, go to https://berquist.github.io/pymolresponse/.

Currently, the goal is to provide:

  1. a pedagogical example of a working molecular orbital response program as an almost direct translation from equations to code,
  2. an implementation that gives “exact” results for testing, and
  3. an example of testing and documenting scientific code using modern software development tools.

Installation

To set up a conda environment with all dependencies for running, testing, and building the documentation, look under devtools.

Requirements

  • Python >= 3.9 (because of type annotations)
  • pyscf
  • Psi4

Testing

just test

Caveats

  • RHF and UHF references only; no ROHF yet.
  • Hartree-Fock and DFT only; no post-HF methods yet.
  • Real orbitals only; no complex or generalized orbitals yet.
  • Because the dimensioning of all arrays is based around the ov/vo space, methods that have non-zero contributions from the oo space (specifically derivatives of GIAOs/London orbitals w.r.t. the B-field) are not…
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score  = signal / reach

signal = 0.25·commit_velocity   // commits in last 90 days (cap 30)
       + 0.20·contributor_work  // unique authors × velocity (cap 100)
       + 0.20·issue_resolution  // closed ÷ total issues
       + 0.20·fork_ratio        // forks ÷ stars (proxy for real usage)
       + 0.10·release_cadence   // releases in 90 days (cap 3)
       + age_bonus              // +0 to +0.30 after 6 months
       + homepage_bonus         // +0.05 if homepage is set

reach  = log₁₀(stars + watchers + 10)█
♥ The Health Score +

Is the project alive and maintained right now? A 0–100 pulse recomputed nightly from commit recency, rhythm, how fast issues close, and how quickly PRs get merged.

health = 0.35·recency       // days since last commit (90d decay)
       + 0.25·cadence       // commit rhythm consistency
       + 0.20·issue_health  // closed ÷ total issues
       + 0.20·pr_health     // merged ÷ total PRs█
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The colour and label on every card come straight from the health score.

Healthy   80 – 100   active, responsive, regular releases
Stable    60 – 79    maintained, steady, no alarms
Quiet     40 – 59    slowing down — watch this one
At Risk    0 – 39    going dark · candidate for rescue█
// Tags — what each label means +

Tags are independent behavioral signals computed nightly. A project can hold multiple at once. They drive the home page sections.

solo_builder      one person holds > 80% of commits (last 180d)
needs_contributors has open "help wanted" or "good first issue" labels
hidden_gem        < 100 stars · active in last 3 months · documented
legacy_hero       repo > 5 years old · committed this year
fork_magnet       forks/stars > 0.5 · used as template or dependency
release_machine   5+ releases in the last 90 days
under_pressure    > 10 open issues · ≤ 2 contributors · health ≥ 60
community_watch   watchers > stars · devs tracking before the public
community_hub     GitHub Discussions enabled · > 20 discussions
funded            maintainer has active funding channel█
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Stars are an outcome, not effort. A project with 8 stars and daily commits is doing more interesting work than one coasting on 8k. We measure the building, then divide by the attention already received — so the genuinely undervalued rise to the top.

// stars   = lagging indicator
// commits = leading indicator
// we rank by the leading one█