What imaging metrics does this skill support?

It primarily handles SNR (Signal-to-Noise Ratio), CV (Coefficient of Variation), and mean intensity distributions across various cycles and channels.

Where are the PDF plots saved?

Plots are automatically saved to a directory named 'qc_plots' within the project root to ensure they are separated from raw data.

How does it handle large numbers of Z-planes?

To prevent file system bloat, the implementation pattern includes logic to save PDF profiles only for the first cycle by default while still displaying plots for others.

Can I use this for different processing stages?

Yes, the skill includes logic to label and differentiate plots from raw, stitched, deconvolved, and EDF stages using a stage_name parameter.

QC Plot PDF Export

Name: QC Plot PDF Export
Author: smith6jt-cop

bysmith6jt-cop

데이터 과학 및 ML

Standardizes the generation and PDF archival of Quality Control (QC) heatmaps and profiles for microscopy quantification workflows.

소개

This skill automates the creation of high-quality PDF reports for Signal-to-Noise Ratio (SNR), Coefficient of Variation (CV), and intensity profiles within the KINTSUGI imaging pipeline. It ensures consistent documentation by establishing a dedicated QC output directory, implementing standardized plotting functions for summary heatmaps and Z-plane profiles, and managing file naming conventions across different processing stages like raw, stitched, and deconvolved data. By enforcing specific export parameters like tight bounding boxes and optimized DPI, it guarantees professional-grade archival for experimental results.

주요 기능

Specialized Z-plane profile plotting for detailed uniformity assessment
0 GitHub stars
Standardized QC_OUTPUT_DIR setup for organized project archival
Automated PDF export for SNR and CV summary heatmaps
Multi-stage support with distinct file naming for raw and processed data
Optimized export settings using 150 DPI for balance of quality and size

사용 사례

Generating archival-ready QC reports for experimental reproducibility
Documenting image quality metrics across large-scale microscopy datasets
Comparing data quality between raw, stitched, and deconvolved processing stages

소개

주요 기능

Specialized Z-plane profile plotting for detailed uniformity assessment
0 GitHub stars
Standardized QC_OUTPUT_DIR setup for organized project archival
Automated PDF export for SNR and CV summary heatmaps
Multi-stage support with distinct file naming for raw and processed data
Optimized export settings using 150 DPI for balance of quality and size

사용 사례

Generating archival-ready QC reports for experimental reproducibility
Documenting image quality metrics across large-scale microscopy datasets
Comparing data quality between raw, stitched, and deconvolved processing stages