
David Herreros Calero contributed to the I2PC/xmipp and I2PC/scipion-em-xmipp repositories by developing and refining backend features and scientific computing workflows. He enhanced data visualization and image processing pipelines, introducing interactive structure mapping and robust volume-shifting algorithms using Python, NumPy, and C++. David focused on improving test reliability and maintainability by addressing flaky tests, clarifying parameter semantics, and reducing external dependencies. His work included CUDA-based performance optimizations, geometry transformation corrections, and code refactoring for clarity and scalability. These efforts strengthened data integrity, reproducibility, and CI stability, demonstrating a thoughtful approach to complex scientific software engineering challenges.

October 2025: Focused on increasing test reliability and reducing external dependencies in the Xmipp test suite. Completed a dependency cleanup for TestXmippDenoiseParticles, removing Relion protocol dependencies and replacing them with Xmipp equivalents to ensure tests exercise Xmipp internal functionality only. This simplification reduces maintenance burden and external coupling, improving test stability and CI run speed.
October 2025: Focused on increasing test reliability and reducing external dependencies in the Xmipp test suite. Completed a dependency cleanup for TestXmippDenoiseParticles, removing Relion protocol dependencies and replacing them with Xmipp equivalents to ensure tests exercise Xmipp internal functionality only. This simplification reduces maintenance burden and external coupling, improving test stability and CI run speed.
Summary for 2025-08: In I2PC/scipion-em-xmipp, delivered a robust volume-shift enhancement and fixed test reliability gaps, driving improved accuracy and release confidence. Key features delivered: Volume Shift feature enhancements including clearer parameter semantics (renamed 'option' to 'useCM') and a weighted center-of-mass calculation for shifts to improve accuracy and reliability. Major bugs fixed: Test reliability improvements by correcting zero-shift expectations in volume/particle shifting tests to (0.0), preventing false failures and increasing release confidence. Overall impact and accomplishments: Increased robustness and accuracy of volume-shifting workflows, reduced test noise, and improved maintainability via clearer naming and traceable commits. Technologies/skills demonstrated: Python-based feature implementation, numerical center-of-mass calculations, test-driven development and test maintenance, and clear commit messaging for traceability across the I2PC/scipion-em-xmipp repository.
Summary for 2025-08: In I2PC/scipion-em-xmipp, delivered a robust volume-shift enhancement and fixed test reliability gaps, driving improved accuracy and release confidence. Key features delivered: Volume Shift feature enhancements including clearer parameter semantics (renamed 'option' to 'useCM') and a weighted center-of-mass calculation for shifts to improve accuracy and reliability. Major bugs fixed: Test reliability improvements by correcting zero-shift expectations in volume/particle shifting tests to (0.0), preventing false failures and increasing release confidence. Overall impact and accomplishments: Increased robustness and accuracy of volume-shifting workflows, reduced test noise, and improved maintainability via clearer naming and traceable commits. Technologies/skills demonstrated: Python-based feature implementation, numerical center-of-mass calculations, test-driven development and test maintenance, and clear commit messaging for traceability across the I2PC/scipion-em-xmipp repository.
June 2025: Delivered enhancements across two repositories that improve data exploration, preprocessing reproducibility, and transformation robustness. Key outcomes: interactive structure-mapping visualization integrated with Flexutils; an optional Center-of-Mass (CM) shift for volumes to simplify preprocessing; corrected reconstruction alignment in the particle shifting protocol to improve reconstruction quality; preserved existing geometric transforms when applying --shift_to to prevent data loss and enhance robustness. Impact: faster, more reliable analyses, reduced manual corrections, and stronger data integrity across workflows. Technologies/skills demonstrated: Python/numpy for numeric calculations, integration with visualization tools (Flexutils), and robust handling of geometry and alignment in imaging pipelines.
June 2025: Delivered enhancements across two repositories that improve data exploration, preprocessing reproducibility, and transformation robustness. Key outcomes: interactive structure-mapping visualization integrated with Flexutils; an optional Center-of-Mass (CM) shift for volumes to simplify preprocessing; corrected reconstruction alignment in the particle shifting protocol to improve reconstruction quality; preserved existing geometric transforms when applying --shift_to to prevent data loss and enhance robustness. Impact: faster, more reliable analyses, reduced manual corrections, and stronger data integrity across workflows. Technologies/skills demonstrated: Python/numpy for numeric calculations, integration with visualization tools (Flexutils), and robust handling of geometry and alignment in imaging pipelines.
February 2025: Focused work on reliability and correctness of the CudaFFT pathway in I2PC/xmipp. No new features released this month; primary impact came from a critical bug fix that stabilizes FFT and IFFT initialization and reduces floating-point related test flakiness, improving overall module reliability and reducing downstream debugging time.
February 2025: Focused work on reliability and correctness of the CudaFFT pathway in I2PC/xmipp. No new features released this month; primary impact came from a critical bug fix that stabilizes FFT and IFFT initialization and reduces floating-point related test flakiness, improving overall module reliability and reducing downstream debugging time.
January 2025 monthly summary for I2PC/scipion-em-xmipp focusing on reliability and data integrity improvements in the PDB data ingestion workflow. A critical bug fix was implemented to import PDB data from a database using a PDB ID instead of a local file path to prevent incorrect conversions during Chimera processing, with corresponding updates to inputPdbData. This change enhances end-to-end data integrity in the PDB→CIF conversion pipeline and reduces downstream rework. The work is captured in a single, well-documented commit and strengthens the stability of the data ingestion path for downstream analysis.
January 2025 monthly summary for I2PC/scipion-em-xmipp focusing on reliability and data integrity improvements in the PDB data ingestion workflow. A critical bug fix was implemented to import PDB data from a database using a PDB ID instead of a local file path to prevent incorrect conversions during Chimera processing, with corresponding updates to inputPdbData. This change enhances end-to-end data integrity in the PDB→CIF conversion pipeline and reduces downstream rework. The work is captured in a single, well-documented commit and strengthens the stability of the data ingestion path for downstream analysis.
December 2024 monthly summary: Delivered targeted enhancements across two core repositories (I2PC/scipion-em-xmipp and I2PC/xmipp) focused on visualization reliability, algorithm robustness, and code quality. Key outcomes include Matplotlib compatibility updates for the Structure Map Viewer, improved plotting accuracy and image handling, and the addition of symmetry and random projection sorting for ZART reconstruction. These changes reduce maintenance burden, broaden adoption, and enhance the reliability and accuracy of visualization and reconstruction workflows, leveraging Python, Matplotlib, and imaging techniques. Overall impact: improved user experience, more robust analytics, and stronger foundation for future enhancements.
December 2024 monthly summary: Delivered targeted enhancements across two core repositories (I2PC/scipion-em-xmipp and I2PC/xmipp) focused on visualization reliability, algorithm robustness, and code quality. Key outcomes include Matplotlib compatibility updates for the Structure Map Viewer, improved plotting accuracy and image handling, and the addition of symmetry and random projection sorting for ZART reconstruction. These changes reduce maintenance burden, broaden adoption, and enhance the reliability and accuracy of visualization and reconstruction workflows, leveraging Python, Matplotlib, and imaging techniques. Overall impact: improved user experience, more robust analytics, and stronger foundation for future enhancements.
In October 2024, I stabilized the Xmipp test suite in I2PC/xmipp by addressing a resource path issue that caused flaky tests. The fix replaces a hardcoded path with the correct test resource path resolver (getXmippSrcPath), ensuring resources are consistently located. This change, committed as c11d01d9dfbf7758312448ca150f8e3eee59f647, delivered tangible business value by reducing intermittent CI failures and speeding feedback to developers. It also demonstrates strong test hygiene and resource management skills, aligning with ongoing quality and reliability goals.
In October 2024, I stabilized the Xmipp test suite in I2PC/xmipp by addressing a resource path issue that caused flaky tests. The fix replaces a hardcoded path with the correct test resource path resolver (getXmippSrcPath), ensuring resources are consistently located. This change, committed as c11d01d9dfbf7758312448ca150f8e3eee59f647, delivered tangible business value by reducing intermittent CI failures and speeding feedback to developers. It also demonstrates strong test hygiene and resource management skills, aligning with ongoing quality and reliability goals.
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