tudat-team/tudatpy
Aug 2025 – Mar 2026
3 Months active
Languages Used
C++Python
Technical Skills
C++PythonSoftware DevelopmentSoftware EngineeringData ProcessingDocumentation
Michael Plumaris
PROFILE
Michael Plumaris
Michael Plumaris contributed to the tudat-team/tudatpy repository by delivering three feature enhancements over three months, focusing on simulation modeling and data processing in C++ and Python. He exposed a new API for configuring custom transmitted frequency calculators, enabling precise onboard frequency modeling and improved environmental simulations. Michael also integrated ILRS SINEX data processing for station configuration, adding robust file I/O and documentation updates to support accurate satellite tracking. In addition, he expanded the unit testing framework for ILRS/SLR observation models, introducing comprehensive tests for correction types and dependent variables to ensure simulation reliability and maintainability across the codebase.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
2,961
Activity Months3
Your Network
15 peopleShared Repositories
15
alfonsoMember
DominicDirkxMember
Suvayu AliMember
Luigi GisolfiMember
Space JonasMember
MarieFayolleMember
MarkusMember
mcontariniMember
Michael PlumarisMember
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026 (2026-03) TudatPy monthly summary focused on strengthening test coverage for ILRS/SLR observation models. Key feature delivered: Testing Framework Enhancement for ILRS/SLR Observation Models, adding unit tests for ILRS/SLR functionality, including tests for various correction types and handling of dependent variables to ensure robustness in simulation of light time corrections and observation-dependent variables.
1 Commits • 1 Features
Mar 1, 2026March 2026 (2026-03) TudatPy monthly summary focused on strengthening test coverage for ILRS/SLR observation models. Key feature delivered: Testing Framework Enhancement for ILRS/SLR Observation Models, adding unit tests for ILRS/SLR functionality, including tests for various correction types and handling of dependent variables to ensure robustness in simulation of light time corrections and observation-dependent variables.
March 2026
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026: Delivered ILRS SINEX integration for TudatPy station configuration and SINEX data processing, enabling ILRS bindings to handle SINEX data end-to-end for station configurations. Added new reading/processing functions for SINEX files and improved management of station states and eccentricities to support more accurate satellite tracking and positioning. Documentation updates accompany the workflow changes to ensure clear usage and reproducibility.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026: Delivered ILRS SINEX integration for TudatPy station configuration and SINEX data processing, enabling ILRS bindings to handle SINEX data end-to-end for station configurations. Added new reading/processing functions for SINEX files and improved management of station states and eccentricities to support more accurate satellite tracking and positioning. Documentation updates accompany the workflow changes to ensure clear usage and reproducibility.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 (tudatpy): Delivered an API enhancement to improve frequency modeling and simulation fidelity. Exposed a new configurability point in VehicleSystems to support a custom transmitted frequency calculator, enabling precise onboard frequency modeling and more realistic environmental simulations.
2 Commits • 1 Features
Aug 1, 2025August 2025 (tudatpy): Delivered an API enhancement to improve frequency modeling and simulation fidelity. Exposed a new configurability point in VehicleSystems to support a custom transmitted frequency calculator, enabling precise onboard frequency modeling and more realistic environmental simulations.
August 2025
Activity
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Quality Metrics
Correctness95.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage25.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++Data ProcessingDocumentationFile I/OPythonSoftware DevelopmentSoftware Engineeringsimulation modelingsoftware testingunit testing
Repositories Contributed To
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