code to implement our sequential monte carlo (smc) algorithm to perform optimal optical spike inference (oopsi) for individual neurons
Star History
Add Live Star History & Verified Badges to README.md
Keep your repository README looking professional and dynamic. As our continuous crawler records new stars, these official SVG badges update in real time with zero maintenance.
Renders your high-resolution star trajectory chart right inside your GitHub README or project docs.
[](https://githubrepo.cloud/repo/jovo/smc-oopsi?utm_source=readme_chart)Compact Shields-style badges for your README header. Shows real-time stars and global ranking.
[](https://githubrepo.cloud/repo/jovo/smc-oopsi?utm_source=readme_badge) [](https://githubrepo.cloud/repo/jovo/smc-oopsi?utm_source=readme_badge) [](https://githubrepo.cloud/repo/jovo/smc-oopsi?utm_source=readme_badge)Momentum
+10
STARS · LAST 30 DAYS
1
PER DAY
#5
MOST-STARRED Matlab
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +0 | +3 | +10 |
smc-oopsi gained 10 stars in the last 30 days, about 1 a day, and now has 16. It is about 18 years old and has averaged roughly 1 stars a year. It ranks #5 among Matlab repositories and #19,902 across all languages on GitHubRepo.
Trending Record
19
DAYS ON TRENDING
#6011
BEST RANK
Sep 26, 2026
FIRST APPEARANCE
Active
STATUS TODAY
smc-oopsi has maintained a continuous presence across global trending indexes, peaking at #6011. Below is the 30-day activity profile:
💡 Overview
smc-oopsi is an open-source project written in Matlab: code to implement our sequential monte carlo (smc) algorithm to perform optimal optical spike inference (oopsi) for individual neurons.
Engineered for speed, consistency, and developer ease, it solves common hurdles in Matlab. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Matlab for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/jovo/smc-oopsi.git
cd smc-oopsi⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Matlab environment and standard tooling
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
smc-oopsi coordinates its core functionality through a modular Matlab pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Production System Integration
Embed smc-oopsi into Matlab backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open Apache-2.0 license.
🚀 Getting Started
Install smc-oopsi using your package manager: `git clone https://github.com/jovo/smc-oopsi.git`
Initialize your project workspace or configuration file for smc-oopsi.
Import smc-oopsi into your codebase or invoke it directly from your terminal.
Execute your test suite or run `smc-oopsi --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Matlab, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
jovo/smc-oopsi is currently ranked #19,902 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #19,779 | tigusigalpa/socialkit-php | PHP | ★ 17 | Compare ↗ |
| #19,779 | tigusigalpa/goldsky-php | PHP | ★ 17 | Compare ↗ |
| #19,779 | scadavide55/SwiftPlayer | Swift | ★ 17 | Compare ↗ |
| #19,779 | SvenGDK/unjail-ps5app-payload | C# | ★ 17 | Compare ↗ |
| #19,779 | codetivsro/upgates-php-sdk | PHP | ★ 17 | Compare ↗ |
| #19,902 | jovo/smc-oopsi This Project | Matlab | ★ 16 | |
| #19,902 | defunkt/ambitious_activeldap | Ruby | ★ 16 | Compare ↗ |
| #19,902 | rabble/icalico | Ruby | ★ 16 | Compare ↗ |
| #19,902 | defunkt/fixture_scenarios_builder | Ruby | ★ 16 | Compare ↗ |
| #19,902 | hallski/loudmouth-ruby | C | ★ 16 | Compare ↗ |
| #19,902 | defunkt/ambitious_activerecord | Ruby | ★ 16 | Compare ↗ |
Frequently Asked Questions
What does smc-oopsi do? +
code to implement our sequential monte carlo (smc) algorithm to perform optimal optical spike inference (oopsi) for individual neurons
What language is smc-oopsi written in? +
The primary language is Matlab. Topics include: software.
Is smc-oopsi actively maintained? +
Yes, the last recorded push was on Nov 28, 2016 with 0 open issues being tracked.
How many stars does smc-oopsi have? +
smc-oopsi has 16 stars and 5 forks on GitHub.
How does smc-oopsi rank among GitHub repositories? +
With 16 stars, jovo/smc-oopsi is ranked #19,902 globally across all repositories tracked on GitHubRepo and #5 among Matlab projects.
What license is smc-oopsi distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
