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base repository: aaroncelestian/RamanLab
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base: v1.1.3
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  • 10 commits
  • 52 files changed
  • 1 contributor

Commits on Jul 6, 2025

  1. Fix batch processing peak selection UI: Replace checkboxes with radio… 

    … buttons

- Changed misleading checkboxes to radio buttons for exclusive peak source selection
- Added QButtonGroup for proper radio button behavior
- Updated method names: update_manual_peaks_checkbox_state() → update_manual_peaks_radio_state()
- Added fallback behavior: auto-selects 'Auto-detect Peaks' if selected option becomes unavailable
- Updated all references throughout codebase to use new radio button system
- Peak source options now clearly exclusive: Auto-detect, Use Find Peaks Results, or Use Manual Peaks
- Resolves user confusion about why both auto-found and manual peaks weren't being used together
    Aaron Celestian committed Jul 6, 2025
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  2. Add advanced Jupyter console integration and update documentation 

    - Add advanced_jupyter_console.py with enhanced IPython integration
- Add simple_jupyter_console.py for basic console functionality
- Add launch_jupyter_console.py for standalone console launcher
- Add test_jupyter_console.py for testing console functionality
- Add ADVANCED_JUPYTER_CONSOLE_README.md with comprehensive documentation
- Update README.md with new console features
- Update peak_fitting_qt6.py with latest improvements
    Aaron Celestian committed Jul 6, 2025
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  3. Implement comprehensive Results Analysis plotting system 

    ✨ Features Added:
• 2x2 grid plots for peak features (amplitude, position, FWHM, R²)
• Waterfall plots with color/offset controls and interval skipping
• Heatmap plots with colormap and interpolation options
• Toggle-based plot switching with stacked widgets
• Left panel controls, right panel plotting layout
• Automatic data refresh after batch processing completion

�� Technical Implementation:
• Uses matplotlib_config.py for consistent styling
• Extracts data from batch_results structure
• Supports multi-peak analysis with peak selection
• Interactive controls for all plot parameters
• Error bars option for statistical analysis
• Performance optimized for large datasets

📊 Plot Types:
1. Grid Plot: Peak amplitude, position, FWHM, R² trends
2. Waterfall Plot: Stacked spectra with customizable offset/colors
3. Heatmap Plot: 2D intensity visualization with colorbars

🎯 User Experience:
• Clean left/right panel separation (controls/plotting)
• Real-time plot updates on parameter changes
• Data source information display
• Empty state handling with informative messages
• Professional matplotlib styling throughout
    Aaron Celestian committed Jul 6, 2025
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  4. Move plotting analysis to right panel tab system 

    🚀 Major UI Improvement:
• Moved comprehensive plotting from Results Analysis tab to right panel
• Created tabbed visualization panel: 'Current Spectrum' + 'Plotting Analysis'
• Maintains clean separation: left panel = controls, right panel = visualization
• Users can now switch between current spectrum view and batch analysis plots

✨ Enhanced User Experience:
• More space for plotting analysis in right panel
• Cleaner Results Analysis tab with helpful instructions
• Quick access button to switch to plotting tab
• Better organization of spectrum view vs batch analysis

🔧 Technical Changes:
• Modified create_visualization_panel() to use QTabWidget
• Simplified create_analysis_tab() to informational content
• Added switch_to_plotting_tab() method for navigation
• Preserved all existing plotting functionality (grid, waterfall, heatmap)
• Maintained matplotlib_config.py integration

📊 Plot Features Preserved:
• 2x2 Peak Features Grid (amplitude, position, FWHM, R²)
• Waterfall Plot with color/offset controls
• Heatmap Plot with colormap options
• All interactive controls and data extraction methods
    Aaron Celestian committed Jul 6, 2025
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  5. Add pickle file loading options to Results Analysis tab 

    - Load pickle files directly for analysis plotting
- Use Advanced tab data management integration
- Use current batch results without reprocessing
- Enhanced data source handling in plotting methods
- Clear status indicators and data previews
- Saves time by avoiding repeated peak fitting
    Aaron Celestian committed Jul 6, 2025
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  6. Add Jupyter Console Integration and Enhanced Dependency Management 

    ✨ New Features:
- Interactive Jupyter console integration with qtconsole, jupyter-client, and ipykernel
- Automated dependency update script with interactive and command-line modes
- Enhanced dependency checker with Jupyter package detection

📦 Dependencies:
- Added qtconsole>=5.4.0 for interactive console widget
- Added jupyter-client>=7.0.0 for kernel management
- Added ipykernel>=6.0.0 for enhanced Python environment
- Updated requirements_qt6.txt with comprehensive installation instructions

🛠️ New Scripts:
- update_dependencies.py: Interactive dependency updater with --jupyter, --core, --all flags
- JUPYTER_INTEGRATION_UPDATE.md: Comprehensive user guide for new features

🔧 Enhanced Tools:
- check_dependencies.py: Now detects Jupyter packages and shows Interactive Console status
- Added component availability tracking for all RamanLab features

💡 User Experience:
- Multiple update options (automatic, manual, full)
- Virtual environment detection and warnings
- Graceful fallback - RamanLab works fine without Jupyter packages
- Clear documentation and troubleshooting guides

🎯 Benefits:
- Interactive Python console within RamanLab
- Live data access and custom analysis capabilities
- Enhanced development and educational features
- Improved dependency management for users
    Aaron Celestian committed Jul 6, 2025
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  7. Update version to 1.1.4 

    Version 1.1.4: Jupyter Console Integration & Enhanced Dependency Management

Updated Files:
- version.py: Main version info and detailed changelog
- VERSION.txt: User-facing version documentation
- __init__.py: Package version
- check_dependencies.py: Version in docstring
- launch_ramanlab.py: Version in header
- peak_fitting_backend.py: API version references
- ml_raman_map/__init__.py: Module version
- map_analysis_2d/__init__.py: Module version

Key Features:
- Interactive Jupyter console integration
- Automated dependency update script
- Enhanced dependency checker with Jupyter detection
- Comprehensive user documentation and troubleshooting
- Live data access and interactive analysis capabilities

All version references now consistent across the codebase.
    Aaron Celestian committed Jul 6, 2025
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Commits on Jul 7, 2025

  1. Fix missing tab creation methods in PythonExamplesWindow 

    - Added create_basic_tab() method with safe data exploration examples
- Added create_peak_analysis_tab() method with mineral identification examples
- Added create_plotting_tab() method with visualization examples
- Fixes AttributeError when launching examples from RamanLab Advanced Analysis Console
- All tab methods include comprehensive safe examples with error handling
- Examples use intelligent column detection and proper data validation
    Aaron Celestian committed Jul 7, 2025
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Commits on Jul 9, 2025

  1. Updates and clean up of files 

    Fixed cluster analysis and added UMAP cluster results to file.
Deleted test scripts
Updates to the raman mixtures analysis, but still not working
And other minor debugging.
    Aaron Celestian committed Jul 9, 2025
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  2. Delete test files 

    Delete text files
    Aaron Celestian committed Jul 9, 2025
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