Implement modular GUI architecture with embedded matplotlib

Major refactor from popup-based to persistent PyQt5 interface:
- Extract plotting logic from AudioFile class into separate PlottingEngine
- Create AudioVisualizationWidget with embedded matplotlib canvas
- Add AnalysisResultsManager as bridge between processing and GUI
- Replace simple drag-drop widget with professional splitter layout
- Preserve legacy batch processing mode with execution guard

Features:
- Drag-and-drop audio analysis (.mp3/.wav/.flac support)
- File list with metadata display (BPM, amplitudes, track info)
- Persistent visualization area (no more matplotlib popups)
- Multi-file support with click-to-view functionality
- Threading-ready architecture for future background processing

Technical improvements:
- Clean separation of concerns (analysis/visualization/GUI)
- Qt signal-slot communication pattern
- Modular component design ready for multithreading
- Proper import guards prevent legacy code interference

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

audio_visualization_widget.py

@@ -0,0 +1,126 @@
+"""
+Audio visualization widget with embedded matplotlib canvas.
+Pure display responsibility - receives plotting data and shows graphs.
+"""
+
+from PyQt5.QtWidgets import QWidget, QVBoxLayout, QLabel
+from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
+from matplotlib.figure import Figure
+import matplotlib.pyplot as plt
+
+
+class AudioVisualizationWidget(QWidget):
+    """Widget for displaying audio analysis graphs with embedded matplotlib."""
+    
+    def __init__(self, parent=None):
+        super().__init__(parent)
+        self.initUI()
+        
+    def initUI(self):
+        """Initialize the UI components."""
+        layout = QVBoxLayout()
+        
+        # Create matplotlib canvas
+        self.figure = Figure(figsize=(10, 4), facecolor='white')
+        self.canvas = FigureCanvas(self.figure)
+        
+        # Add canvas to layout
+        layout.addWidget(self.canvas)
+        
+        # Status label for feedback
+        self.status_label = QLabel("Ready for audio analysis...")
+        layout.addWidget(self.status_label)
+        
+        self.setLayout(layout)
+        
+        # Initialize with empty plot
+        self._create_empty_plot()
+        
+    def _create_empty_plot(self):
+        """Creates an empty placeholder plot."""
+        self.figure.clear()
+        ax = self.figure.add_subplot(111)
+        ax.text(0.5, 0.5, 'Drop an audio file to see analysis', 
+                ha='center', va='center', transform=ax.transAxes,
+                fontsize=14, alpha=0.7)
+        ax.set_xlim(0, 1)
+        ax.set_ylim(0, 1)
+        ax.set_xticks([])
+        ax.set_yticks([])
+        self.canvas.draw()
+    
+    def display_analysis_figure(self, figure):
+        """
+        Display a matplotlib figure in the widget.
+        
+        Args:
+            figure: matplotlib.figure.Figure to display
+        """
+        # Clear current figure
+        self.figure.clear()
+        
+        # Copy the provided figure to our canvas
+        # Get the subplot from the provided figure
+        source_ax = figure.get_axes()[0]
+        
+        # Create new subplot in our figure
+        ax = self.figure.add_subplot(111)
+        
+        # Copy all the plot elements
+        for child in source_ax.get_children():
+            if hasattr(child, 'get_data'):
+                # Copy line plots
+                try:
+                    x_data, y_data = child.get_data()
+                    ax.plot(x_data, y_data, color=child.get_color(), 
+                           linewidth=child.get_linewidth())
+                except:
+                    pass
+        
+        # Copy collections (fill_between creates PolyCollection)
+        for collection in source_ax.collections:
+            ax.add_collection(collection)
+        
+        # Copy axis properties
+        ax.set_xlim(source_ax.get_xlim())
+        ax.set_ylim(source_ax.get_ylim())
+        ax.set_xlabel(source_ax.get_xlabel())
+        ax.set_ylabel(source_ax.get_ylabel())
+        ax.set_title(source_ax.get_title())
+        
+        # Copy colorbar if it exists
+        if hasattr(figure, '_colorbar') or len(figure.get_axes()) > 1:
+            # Try to copy colorbar
+            try:
+                cbar = figure.colorbar(source_ax.collections[-1], ax=ax, label='RMS Power')
+            except:
+                pass
+        
+        self.figure.tight_layout()
+        self.canvas.draw()
+        self.status_label.setText("Analysis complete - displaying power graph")
+    
+    def display_figure_direct(self, figure):
+        """
+        Display a figure by replacing our canvas figure entirely.
+        More reliable than copying elements.
+        
+        Args:
+            figure: matplotlib.figure.Figure to display
+        """
+        # Remove old canvas
+        layout = self.layout()
+        layout.removeWidget(self.canvas)
+        self.canvas.deleteLater()
+        
+        # Create new canvas with the provided figure
+        self.figure = figure
+        self.canvas = FigureCanvas(self.figure)
+        layout.insertWidget(0, self.canvas)  # Insert at position 0 (before status label)
+        
+        self.canvas.draw()
+        self.status_label.setText("Analysis complete - displaying power graph")
+    
+    def set_status(self, message):
+        """Update the status label."""
+        self.status_label.setText(message)