updated config defaults

improve modularity of the model

refactiring rest of code base and adding checkpoints

continuing to simplify code so that it is easier to work with. Removing extras...

simplifying code structure

cleaning foxes config

updated config

- Modified inference.py to streamline dataset loading and configuration handling.

foxes-lite update... made for easy inference and evaluation.... removed data preprocessing and downloading pipeline pieces.

updated FOXES model file so that the attention mask can be local, inverted local, or global attention!

slight bug fixes!

refactor configuration files and update paths

add flux map analysis script and configuration for detecting and tracking active regions

updated noise so that it scales globally (doesn't use individual std)

enhance multi-GPU support

enhance multi-GPU support

refactor ablation configuration handling and improve DataLoader cleanup

refine noise application in SDOAIA_dataloader and simplify GPU usage message

enhance inference configuration for improved performance

trying to speed up inference!

trying to speed up inference!

trying to speed up inference!

trying to speed up inference!

trying to speed up inference!

Add ablation study and spatial performance scripts; update pipeline configuration and dataset handling

Fixed normalization of timestamp names

Fixed normalization of timestamp names

Add evaluation configuration and update inference pipeline

Refactor pipeline configuration and update data processing scripts

Refactor configuration parameters and update model architecture references

Update learning rate scheduler parameters and clean up loss calculation notes

Rename localpatch.yaml to train_config.yaml and update notes; modify learning rate scheduler parameters and rename attention mask creation method

Updated model to include inverted attention naming scheme

Added checkpointing

Moved around some files

Update data processing workflows

Enhance plotting themes for poster analysis, refine regression plot scaling, and add data cleanup utilities

Implement dynamic theme-based plotting for regression output and tweak default parameters

updates

Refactor code structure for improved readability and maintainability

Refined flare analysis parameters and detection logic, including adjustments to validation thresholds for peak detection, enhanced configuration settings for baseline calculations, and improved visualization in the plotting functions. Updated YAML configuration for time range and detection parameters to optimize flare event identification.

Enhanced flare analysis with new multi-scale peak detection, improved prominence filtering, and additional configuration parameters for baseline quantile and minimum peak distance. Updated detection logic to support adaptive thresholds in log space for better accuracy in flare event identification.

Updated flare analysis configuration and detection parameters, including time range adjustments and modifications to baseline calculations for improved accuracy in flare event detection.

more improvements... significantly better

watershed test

more updates for improving analysis

updates to flare catalog generator

additional changes

major updates for flare catalog creation

fixes to patch analysis