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Riju Dutta

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Riju Dutta

Riju Dutta focused on enhancing the numerical stability of gradient computations in the pyro-kinetics/pyrokinetics repository during November 2024. Addressing a bug in the species module, Riju replaced the use of np.isclose() with np.allclose() to ensure that all elements are near zero before division, thereby reducing the risk of unstable gradients and preventing NaN or Infinity values in downstream workflows. This targeted fix, implemented in Python and leveraging skills in numerical and scientific computing, improved the reliability of simulation and optimization routines. The work demonstrated careful attention to numerical robustness, though no new features were introduced during this period.

Overall Statistics

Feature vs Bugs

0%Features

Repository Contributions

1Total
Bugs
1
Commits
1
Features
0
Lines of code
0
Activity Months1

Your Network

9 people

Work History

November 2024

1 Commits

Nov 1, 2024

November 2024 monthly summary for pyro-kinetics/pyrokinetics focused on numerical stability and reliability in gradient computations. No new feature releases this month; major improvement in numerical robustness for the species module.

Activity

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Quality Metrics

Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

Python

Technical Skills

Numerical ComputingScientific Computing

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

pyro-kinetics/pyrokinetics

Nov 2024 Nov 2024
1 Month active

Languages Used

Python

Technical Skills

Numerical ComputingScientific Computing