dudong-v2/ui/panels/system_info.py

"""
System Information Panel

Displays performance metrics and model accuracy statistics.
"""

from PyQt5.QtWidgets import QGroupBox, QHBoxLayout, QVBoxLayout, QLabel
from PyQt5.QtGui import QFont

from resources.styles import GROUP_BOX_STYLE, HEADER_LABEL_STYLE, STATUS_LABEL_STYLE


class SystemInfoPanel(QGroupBox):
    """
    Panel displaying system information and statistics.
    
    Shows:
    - Performance metrics (processing time, throughput, uptime)
    - Model accuracy statistics (calculated from confidence scores)
    
    Note: Memory usage is displayed in SystemStatusPanel, not here.
    """
    
    def __init__(self):
        """Initialize the system information panel."""
        super().__init__("System Information")
        self.setStyleSheet(GROUP_BOX_STYLE)
        self.init_ui()
    
    def init_ui(self):
        """Initialize the UI components."""
        layout = QHBoxLayout()
        
        # Performance Metrics (left side)
        perf_layout = QVBoxLayout()
        perf_label = QLabel("Performance Metrics:")
        perf_label.setFont(QFont("Arial", 16, QFont.Bold))
        perf_label.setStyleSheet(HEADER_LABEL_STYLE)
        perf_layout.addWidget(perf_label)
        
        # Performance metrics
        self.metrics = {
            'processing_time': QLabel("• Average Processing Time: --"),
            'throughput': QLabel("• Daily Throughput: 0 fruits analyzed"),
            'uptime': QLabel("• System Uptime: 0h 0m")
        }
        
        for metric_label in self.metrics.values():
            metric_label.setStyleSheet(STATUS_LABEL_STYLE)
            perf_layout.addWidget(metric_label)
        
        layout.addLayout(perf_layout)
        
        # Model Accuracy (right side)
        accuracy_layout = QVBoxLayout()
        accuracy_header = QLabel("Model Accuracy (Last 100 Tests):")
        accuracy_header.setFont(QFont("Arial", 16, QFont.Bold))
        accuracy_header.setStyleSheet(HEADER_LABEL_STYLE)
        accuracy_layout.addWidget(accuracy_header)
        
        # Accuracy metrics (mapped from model_type returned by DataManager)
        # Model types: 'audio', 'defect', 'locule', 'maturity', 'shape'
        self.accuracies = {
            'audio': QLabel("• Ripeness Classification: --"),
            'defect': QLabel("• Defect Detection: --"),
            'locule': QLabel("• Locule Detection: --"),
            'maturity': QLabel("• Maturity Assessment: --"),
            'shape': QLabel("• Shape Analysis: --")
        }
        
        for accuracy_label in self.accuracies.values():
            accuracy_label.setStyleSheet(STATUS_LABEL_STYLE)
            accuracy_layout.addWidget(accuracy_label)
        
        layout.addLayout(accuracy_layout)
        self.setLayout(layout)
    
    def update_processing_time(self, avg_time: float):
        """
        Update average processing time.
        
        Args:
            avg_time: Average processing time in seconds
        """
        self.metrics['processing_time'].setText(f"• Average Processing Time: {avg_time:.1f}s per fruit")
    
    def update_throughput(self, count: int):
        """
        Update daily throughput.
        
        Args:
            count: Number of fruits analyzed today
        """
        self.metrics['throughput'].setText(f"• Daily Throughput: {count:,} fruits analyzed")
    
    def update_uptime(self, hours: int, minutes: int):
        """
        Update system uptime.
        
        Args:
            hours: Uptime hours
            minutes: Uptime minutes
        """
        self.metrics['uptime'].setText(f"• System Uptime: {hours}h {minutes}m")
    
    
    def update_accuracy(self, model: str, accuracy: float):
        """
        Update model accuracy.
        
        Args:
            model: Model name from DataManager ('audio', 'defect', 'locule', 'maturity', 'shape')
            accuracy: Accuracy percentage (0-100)
        """
        if model in self.accuracies:
            label_map = {
                'audio': f"• Ripeness Classification: {accuracy:.1f}%",
                'defect': f"• Defect Detection: {accuracy:.1f}%",
                'locule': f"• Locule Detection: {accuracy:.1f}%",
                'maturity': f"• Maturity Assessment: {accuracy:.1f}%",
                'shape': f"• Shape Analysis: {accuracy:.1f}%"
            }
            self.accuracies[model].setText(label_map[model])