sabia-group/How-Tos
Nov 2024 – Nov 2024
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisJupyter NotebookMolecular DynamicsPythonScientific ComputingVibrational Spectroscopy
lazerpo
PROFILE
Lazerpo
Paolo Lazzaroni developed a Jupyter Notebook for the sabia-group/How-Tos repository, enabling 2D-VDOS correlation analysis for molecular dynamics trajectory data. His work provided an end-to-end workflow that processes trajectories, computes velocities, and projects them onto normal modes to investigate mode coupling, supporting reproducible and data-driven research. Using Python and scientific computing techniques, Paolo implemented utilities for trajectory processing, mode building, and dynamic spectrum calculation, integrating the notebook into the main branch. While the project spanned one month and focused on feature development rather than bug fixes, the depth of the solution enhanced analytical capabilities for vibrational spectroscopy studies.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
586
Activity Months1
Your Network
11 peopleSame Organization
@mpsd.mpg.de5
Shared Repositories
6
Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024: Delivered a new Jupyter Notebook for 2D-VDOS correlation analysis in sabia-group/How-Tos, enabling end-to-end trajectory processing, velocity computation, and projection onto normal modes to investigate mode coupling. The notebook provides utilities for trajectory processing, mode building, and dynamic spectrum calculation, and was integrated into the main branch to support reproducible analyses. Key deliverables: - Notebook: 2D-VDOS correlation plots for trajectory analysis (commit f748b5184d0bb369bb9136b064ede1f6f55c273e). - Notebook includes end-to-end workflow for processing trajectories, building modes, and computing dynamic spectra. Bugs: - No major bugs fixed this period (based on available data). Impact: - Improves analytical capabilities for trajectory data, enabling faster, reproducible insights into mode coupling; aligns with data-driven research workflows. Technologies/Skills: - Python, Jupyter Notebooks, data processing, mode analysis, dynamic spectra, code integration to main.
1 Commits • 1 Features
Nov 1, 2024November 2024: Delivered a new Jupyter Notebook for 2D-VDOS correlation analysis in sabia-group/How-Tos, enabling end-to-end trajectory processing, velocity computation, and projection onto normal modes to investigate mode coupling. The notebook provides utilities for trajectory processing, mode building, and dynamic spectrum calculation, and was integrated into the main branch to support reproducible analyses. Key deliverables: - Notebook: 2D-VDOS correlation plots for trajectory analysis (commit f748b5184d0bb369bb9136b064ede1f6f55c273e). - Notebook includes end-to-end workflow for processing trajectories, building modes, and computing dynamic spectra. Bugs: - No major bugs fixed this period (based on available data). Impact: - Improves analytical capabilities for trajectory data, enabling faster, reproducible insights into mode coupling; aligns with data-driven research workflows. Technologies/Skills: - Python, Jupyter Notebooks, data processing, mode analysis, dynamic spectra, code integration to main.
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AnalysisJupyter NotebookMolecular DynamicsPythonScientific ComputingVibrational Spectroscopy
Repositories Contributed To
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