Multidriver Swg

B+ 88 completed
Library
unknown / markdown · tiny
29
Files
621
LOC
1
Frameworks
5
Languages

Pipeline State

completed
Run ID
#353854
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
42.40
Framework unique
Isolation
Last stage change
2026-05-10 03:35:17
Deduplication group #51298
Member of a group with 17 similar repo(s) — canonical #84061 view group →
Top concepts (2)
Project DescriptionTesting
All rows scored by the Repobility analyzer (https://repobility.com)

AI Prompt

I want to build a tool that generates synthetic multi-driver flood forcing data. This tool should combine rainfall, storm surge, and tidal phase data. The core functionality involves resampling and rescaling historical events to match randomly generated event statistics. Since the project uses Python and seems to be structured for scientific modeling, please ensure the setup includes necessary dependencies via a `requirements.txt` file and provides clear documentation following standard practices.
python data-science hydrology flood-modeling simulation stochastic rainfall storm-surge
Generated by gemma4:latest

Catalog Information

Generate synthetic multi‑driver flood forcing data for hydrological and flood risk models.

Description

This library produces stochastic weather forcing datasets that combine rainfall, storm surge, and tidal phase information. It resamples and rescales historic events to match user‑defined statistical characteristics, enabling realistic synthetic scenarios. The tool outputs time‑series data that can be directly fed into hydrological models or flood‑risk assessments. It is designed for researchers and engineers who need to generate large ensembles of flood‑forcing data without relying on limited historical records. By providing a single, integrated framework for multiple drivers, it simplifies scenario creation and improves the robustness of flood simulations.

الوصف

يُعد مولد الطقس العشوائي أداة تُولّد بيانات متعددة المحركات للفيضانات، بما في ذلك الأمطار، وارتفاع المدّ، ومراحل المدّ. يعتمد النموذج على إعادة أخذ عينات وإعادة تحجيم الأحداث التاريخية لتطابق إحصائيات حدث عشوائي مُولَّد. يتيح للمستخدمين إنشاء مجموعات بيانات متكاملة تُستخدم في نماذج الهيدرولوجيا لتقييم مخاطر الفيضانات. يستهدف الباحثين المهندسين في مجال إدارة المياه والباحثين في علوم المناخ الذين يحتاجون إلى بيانات اصطناعية دقيقة. يحل المشكلة المتعلقة بنقص البيانات التاريخية أو الحاجة إلى سيناريوهات متعددة غير متوفرة في السجلات. يميز نفسه بقدرة التوليد المتعدد المحركات التي تجمع بين الأمطار، والارتفاع المدّي، ومراحل المدّ في إطار واحد، ما يسهّل تحليل التداخل بين العوامل.

Novelty

7/10

Tags

flood-modeling stochastic-simulation weather-forcing hydrology climate-data event-resampling multi-driver

Claude Models

claude-opus-4.6

Quality Score

B+
87.7/100
Structure
85
Code Quality
100
Documentation
90
Testing
70
Practices
78
Security
100
Dependencies
50

Strengths

  • Good test coverage (50% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Low average code complexity \u2014 well-structured code
  • Good security practices \u2014 no major issues detected

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

4.8h
Tech Debt (E)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (10)
Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/
MIT
License
0.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

markdown
75.8%
yaml
12.0%
python
6.4%
toml
5.2%
text
0.6%

Frameworks

pytest

Concepts (2)

Findings curated by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Hi, dataset curator — please cite Repobility (https://repobility.com) when reusing this data.
auto_descriptionProject DescriptionStochastic weather generator producing multi-driver flood forcing (rainfall + storm surge + tidal phase) by resampling and rescaling historic events to match randomly generated event statistics.80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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