summary_page.py

import matplotlib.pyplot as plt
import pandas as pd

def create_summary_page(df: pd.DataFrame, available_models: list[str]) -> plt.Figure:
    """Create a summary page with model names and both AMD/NVIDIA test stats bars."""
    if df.empty:
        fig, ax = plt.subplots(figsize=(16, 8), facecolor='#000000')
        ax.set_facecolor('#000000')
        ax.text(0.5, 0.5, 'No data available', 
                horizontalalignment='center', verticalalignment='center',
                transform=ax.transAxes, fontsize=20, color='#888888',
                fontfamily='monospace', weight='normal')
        ax.axis('off')
        return fig
    
    fig, ax = plt.subplots(figsize=(16, len(available_models) * 2.5 + 2), facecolor='#000000')
    ax.set_facecolor('#000000')
    
    colors = {
        'passed': '#4CAF50',
        'failed': '#E53E3E', 
        'skipped': '#FFD54F',
        'error': '#8B0000',
        'empty': "#5B5B5B"
    }
    
    visible_model_count = 0
    max_y = 0
    
    for i, model_name in enumerate(available_models):
        if model_name not in df.index:
            continue
            
        row = df.loc[model_name]
        
        # Get values directly from dataframe
        success_amd = int(row.get('success_amd', 0)) if pd.notna(row.get('success_amd', 0)) else 0
        success_nvidia = int(row.get('success_nvidia', 0)) if pd.notna(row.get('success_nvidia', 0)) else 0
        failed_multi_amd = int(row.get('failed_multi_no_amd', 0)) if pd.notna(row.get('failed_multi_no_amd', 0)) else 0
        failed_multi_nvidia = int(row.get('failed_multi_no_nvidia', 0)) if pd.notna(row.get('failed_multi_no_nvidia', 0)) else 0
        failed_single_amd = int(row.get('failed_single_no_amd', 0)) if pd.notna(row.get('failed_single_no_amd', 0)) else 0
        failed_single_nvidia = int(row.get('failed_single_no_nvidia', 0)) if pd.notna(row.get('failed_single_no_nvidia', 0)) else 0
        
        # Calculate stats
        amd_stats = {
            'passed': success_amd,
            'failed': failed_multi_amd + failed_single_amd,
            'skipped': 0,
            'error': 0
        }
        
        nvidia_stats = {
            'passed': success_nvidia,
            'failed': failed_multi_nvidia + failed_single_nvidia,
            'skipped': 0,
            'error': 0
        }
        
        amd_total = sum(amd_stats.values())
        nvidia_total = sum(nvidia_stats.values())
        
        if amd_total == 0 and nvidia_total == 0:
            continue
            
        # Position for this model - use visible model count for spacing
        y_base = (2.2 + visible_model_count) * 1.8
        y_model_name = y_base    # Model name above AMD bar
        y_amd_bar = y_base + 0.45       # AMD bar
        y_nvidia_bar = y_base + 0.97    # NVIDIA bar
        max_y = max(max_y, y_nvidia_bar + 0.5)
        
        # Model name centered above the AMD bar
        left_0 = 8
        bar_length = 92
        ax.text(bar_length / 2 + left_0, y_model_name, f"{i} - {y_model_name} - {model_name.lower()}", 
               ha='center', va='center', color='#FFFFFF', 
               fontsize=20, fontfamily='monospace', fontweight='bold')
        
        # AMD label and bar on the same level
        ax.text(left_0 - 2, y_amd_bar, "amd", ha='right', va='center', color='#CCCCCC', fontsize=18, fontfamily='monospace', fontweight='normal')
        if amd_total > 0:           
            # AMD bar starts after labels
            left = left_0
            for category in ['passed', 'failed', 'skipped', 'error']:
                if amd_stats[category] > 0:
                    width = amd_stats[category] / amd_total * bar_length
                    ax.barh(y_amd_bar, width, left=left, height=0.405, 
                           color=colors[category], alpha=0.9)
                    if width > 4:
                        ax.text(left + width/2, y_amd_bar, str(amd_stats[category]), 
                               ha='center', va='center', color='black', 
                               fontweight='bold', fontsize=12, fontfamily='monospace')
                    left += width
        else:
            ax.barh(y_amd_bar, bar_length, left=left_0, height=0.405, color=colors['empty'], alpha=0.9)
            ax.text(left_0 + bar_length/2, y_amd_bar, "No data", ha='center', va='center', color='black', fontweight='bold', fontsize=12, fontfamily='monospace')
        
        # NVIDIA label and bar on the same level
        ax.text(left_0 - 2, y_nvidia_bar, "nvidia", ha='right', va='center', color='#CCCCCC', fontsize=18, fontfamily='monospace', fontweight='normal')

        if nvidia_total > 0:            
            # NVIDIA bar starts after labels
            left = left_0
            for category in ['passed', 'failed', 'skipped', 'error']:
                if nvidia_stats[category] > 0:
                    width = nvidia_stats[category] / nvidia_total * bar_length
                    ax.barh(y_nvidia_bar, width, left=left, height=0.405, 
                           color=colors[category], alpha=0.9)
                    if width > 4:
                        ax.text(left + width/2, y_nvidia_bar, str(nvidia_stats[category]), 
                               ha='center', va='center', color='black', 
                               fontweight='bold', fontsize=12, fontfamily='monospace')
                    left += width
        else:
            ax.barh(y_nvidia_bar, bar_length, left=left_0, height=0.405, color=colors['empty'], alpha=0.9)
            ax.text(left_0 + bar_length/2, y_nvidia_bar, "No data", ha='center', va='center', color='black', fontweight='bold', fontsize=12, fontfamily='monospace')
        
        # Increment counter for next visible model
        visible_model_count += 1
    
    # Style the axes to be completely invisible and span full width
    ax.set_xlim(0, 100)
    ax.set_ylim(0, max_y)
    ax.set_xlabel('')
    ax.set_ylabel('')
    ax.spines['bottom'].set_visible(False)
    ax.spines['left'].set_visible(False)
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    ax.set_xticks([])
    ax.set_yticks([])
    ax.yaxis.set_inverted(True)
    
    # Remove all margins to make bars span full width
    plt.tight_layout()
    plt.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02)
    
    return fig