Remove unused files to reduce code size

- Delete logos/amd_logo.png and logos/nvidia_logo.png (not needed with text labels)
- Delete time_series.py (316 lines) - unused matplotlib version
- Keep time_series_gradio.py which uses Plotly and is actually used
- Total reduction: ~340 lines of unused code

time_series.py

@@ -1,316 +0,0 @@
-import matplotlib.pyplot as plt
-import pandas as pd
-import numpy as np
-from datetime import datetime
-from data import extract_model_data
-
-COLORS = {
-    'passed': '#4CAF50',
-    'failed': '#E53E3E',
-    'skipped': '#FFD54F',
-    'error': '#8B0000',
-    'amd': '#ED1C24',
-    'nvidia': '#76B900'
-}
-
-FIGURE_WIDTH = 20
-FIGURE_HEIGHT = 12
-
-BLACK = '#000000'
-LABEL_COLOR = '#CCCCCC'
-TITLE_COLOR = '#FFFFFF'
-GRID_COLOR = '#333333'
-
-TITLE_FONT_SIZE = 24
-LABEL_FONT_SIZE = 14
-LEGEND_FONT_SIZE = 12
-
-
-def create_time_series_summary(historical_df: pd.DataFrame) -> plt.Figure:
-    if historical_df.empty or 'date' not in historical_df.columns:
-        fig, ax = plt.subplots(figsize=(FIGURE_WIDTH, FIGURE_HEIGHT), facecolor=BLACK)
-        ax.set_facecolor(BLACK)
-        ax.text(0.5, 0.5, 'No historical data available',
-                horizontalalignment='center', verticalalignment='center',
-                transform=ax.transAxes, fontsize=20, color='#888888',
-                fontfamily='monospace', weight='normal')
-        ax.axis('off')
-        return fig
-    
-    historical_df['date_dt'] = pd.to_datetime(historical_df['date'])
-    historical_df = historical_df.sort_values('date_dt')
-    
-    daily_stats = []
-    dates = []
-    
-    for date in historical_df['date_dt'].unique():
-        date_data = historical_df[historical_df['date_dt'] == date]
-        
-        total_amd_passed = total_amd_failed = total_amd_skipped = 0
-        total_nvidia_passed = total_nvidia_failed = total_nvidia_skipped = 0
-        
-        for _, row in date_data.iterrows():
-            amd_stats, nvidia_stats = extract_model_data(row)[:2]
-            
-            total_amd_passed += amd_stats['passed']
-            total_amd_failed += amd_stats['failed']
-            total_amd_skipped += amd_stats['skipped']
-            total_nvidia_passed += nvidia_stats['passed']
-            total_nvidia_failed += nvidia_stats['failed']
-            total_nvidia_skipped += nvidia_stats['skipped']
-        
-        amd_total = total_amd_passed + total_amd_failed
-        nvidia_total = total_nvidia_passed + total_nvidia_failed
-        
-        amd_failure_rate = (total_amd_failed / amd_total * 100) if amd_total > 0 else 0
-        nvidia_failure_rate = (total_nvidia_failed / nvidia_total * 100) if nvidia_total > 0 else 0
-        
-        daily_stats.append({
-            'amd_failure_rate': amd_failure_rate,
-            'nvidia_failure_rate': nvidia_failure_rate,
-            'amd_passed': total_amd_passed,
-            'amd_failed': total_amd_failed,
-            'amd_skipped': total_amd_skipped,
-            'nvidia_passed': total_nvidia_passed,
-            'nvidia_failed': total_nvidia_failed,
-            'nvidia_skipped': total_nvidia_skipped
-        })
-        dates.append(date)
-    
-    fig = plt.figure(figsize=(FIGURE_WIDTH, FIGURE_HEIGHT + 4), facecolor=BLACK)
-    gs = fig.add_gridspec(3, 2, height_ratios=[1.2, 1, 1], width_ratios=[2, 1], 
-                          hspace=0.3, wspace=0.25)
-    
-    ax1 = fig.add_subplot(gs[0, :])
-    ax2 = fig.add_subplot(gs[1, 0])
-    ax3 = fig.add_subplot(gs[2, 0])
-    ax4 = fig.add_subplot(gs[1:, 1])
-    
-    for ax in [ax1, ax2, ax3, ax4]:
-        ax.set_facecolor(BLACK)
-    
-    dates_array = np.array(dates)
-    amd_rates = [stat['amd_failure_rate'] for stat in daily_stats]
-    nvidia_rates = [stat['nvidia_failure_rate'] for stat in daily_stats]
-    
-    ax1.fill_between(dates_array, 0, amd_rates, color=COLORS['amd'], alpha=0.15)
-    ax1.fill_between(dates_array, 0, nvidia_rates, color=COLORS['nvidia'], alpha=0.15)
-    ax1.plot(dates_array, amd_rates, color=COLORS['amd'], linewidth=3, 
-             label='AMD', marker='o', markersize=7, markeredgewidth=2, markeredgecolor=BLACK)
-    ax1.plot(dates_array, nvidia_rates, color=COLORS['nvidia'], linewidth=3, 
-             label='NVIDIA', marker='s', markersize=7, markeredgewidth=2, markeredgecolor=BLACK)
-    
-    if len(amd_rates) > 2:
-        z_amd = np.polyfit(range(len(amd_rates)), amd_rates, 1)
-        p_amd = np.poly1d(z_amd)
-        ax1.plot(dates_array, p_amd(range(len(amd_rates))), 
-                color=COLORS['amd'], linestyle='--', alpha=0.5, linewidth=2)
-        
-        z_nvidia = np.polyfit(range(len(nvidia_rates)), nvidia_rates, 1)
-        p_nvidia = np.poly1d(z_nvidia)
-        ax1.plot(dates_array, p_nvidia(range(len(nvidia_rates))), 
-                color=COLORS['nvidia'], linestyle='--', alpha=0.5, linewidth=2)
-    
-    ax1.set_title('Overall Failure Rates Over Time', fontsize=TITLE_FONT_SIZE, 
-                  color=TITLE_COLOR, fontfamily='monospace', fontweight='bold', pad=20)
-    ax1.set_ylabel('Failure Rate (%)', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax1.grid(True, color=GRID_COLOR, alpha=0.3, linestyle='-', linewidth=0.5)
-    ax1.legend(fontsize=LEGEND_FONT_SIZE, loc='upper right', frameon=False, 
-               labelcolor=LABEL_COLOR, prop={'family': 'monospace'})
-    ax1.tick_params(colors=LABEL_COLOR, labelsize=LABEL_FONT_SIZE, axis='x', rotation=45)
-    
-    amd_passed = [stat['amd_passed'] for stat in daily_stats]
-    amd_failed = [stat['amd_failed'] for stat in daily_stats]
-    amd_skipped = [stat['amd_skipped'] for stat in daily_stats]
-    
-    ax2.stackplot(dates_array, amd_passed, amd_failed, amd_skipped,
-                  colors=[COLORS['passed'], COLORS['failed'], COLORS['skipped']],
-                  alpha=0.8, labels=['Passed', 'Failed', 'Skipped'])
-    
-    ax2.set_title('AMD Test Results', fontsize=TITLE_FONT_SIZE - 2, 
-                  color=TITLE_COLOR, fontfamily='monospace', fontweight='bold', pad=15)
-    ax2.set_ylabel('Tests', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax2.grid(True, color=GRID_COLOR, alpha=0.3, linestyle='-', linewidth=0.5)
-    ax2.tick_params(colors=LABEL_COLOR, labelsize=LABEL_FONT_SIZE - 1, axis='x', rotation=45)
-    
-    nvidia_passed = [stat['nvidia_passed'] for stat in daily_stats]
-    nvidia_failed = [stat['nvidia_failed'] for stat in daily_stats]
-    nvidia_skipped = [stat['nvidia_skipped'] for stat in daily_stats]
-    
-    ax3.stackplot(dates_array, nvidia_passed, nvidia_failed, nvidia_skipped,
-                  colors=[COLORS['passed'], COLORS['failed'], COLORS['skipped']],
-                  alpha=0.8, labels=['Passed', 'Failed', 'Skipped'])
-    
-    ax3.set_title('NVIDIA Test Results', fontsize=TITLE_FONT_SIZE - 2, 
-                  color=TITLE_COLOR, fontfamily='monospace', fontweight='bold', pad=15)
-    ax3.set_ylabel('Tests', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax3.set_xlabel('Date', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax3.grid(True, color=GRID_COLOR, alpha=0.3, linestyle='-', linewidth=0.5)
-    ax3.tick_params(colors=LABEL_COLOR, labelsize=LABEL_FONT_SIZE - 1, axis='x', rotation=45)
-    
-    latest = daily_stats[-1]
-    metrics = [
-        ('Latest AMD Failure Rate', f"{latest['amd_failure_rate']:.1f}%", COLORS['amd']),
-        ('Latest NVIDIA Failure Rate', f"{latest['nvidia_failure_rate']:.1f}%", COLORS['nvidia']),
-        ('', '', None),
-        ('Total AMD Tests', str(latest['amd_passed'] + latest['amd_failed'] + latest['amd_skipped']), '#888888'),
-        ('Total NVIDIA Tests', str(latest['nvidia_passed'] + latest['nvidia_failed'] + latest['nvidia_skipped']), '#888888'),
-    ]
-    
-    ax4.axis('off')
-    y_pos = 0.9
-    ax4.text(0.5, 0.95, 'SUMMARY', ha='center', va='top', fontsize=TITLE_FONT_SIZE - 2,
-             color=TITLE_COLOR, fontfamily='monospace', fontweight='bold',
-             transform=ax4.transAxes)
-    
-    for label, value, color in metrics:
-        if label:
-            ax4.text(0.1, y_pos, label, ha='left', va='center', fontsize=LABEL_FONT_SIZE,
-                    color=LABEL_COLOR, fontfamily='monospace', transform=ax4.transAxes)
-            ax4.text(0.9, y_pos, value, ha='right', va='center', fontsize=LABEL_FONT_SIZE + 2,
-                    color=color or LABEL_COLOR, fontfamily='monospace', fontweight='bold',
-                    transform=ax4.transAxes)
-        y_pos -= 0.15
-    
-    handles = [plt.Rectangle((0,0),1,1, fc=COLORS['passed'], alpha=0.8),
-               plt.Rectangle((0,0),1,1, fc=COLORS['failed'], alpha=0.8),
-               plt.Rectangle((0,0),1,1, fc=COLORS['skipped'], alpha=0.8)]
-    ax4.legend(handles, ['Passed', 'Failed', 'Skipped'], 
-              loc='lower center', fontsize=LEGEND_FONT_SIZE,
-              frameon=False, labelcolor=LABEL_COLOR, prop={'family': 'monospace'})
-    
-    plt.close('all')
-    return fig
-
-
-def create_model_time_series(historical_df: pd.DataFrame, model_name: str) -> plt.Figure:
-    if historical_df.empty or 'date' not in historical_df.columns:
-        fig, ax = plt.subplots(figsize=(FIGURE_WIDTH, FIGURE_HEIGHT), facecolor=BLACK)
-        ax.set_facecolor(BLACK)
-        ax.text(0.5, 0.5, f'No historical data available for {model_name}',
-                horizontalalignment='center', verticalalignment='center',
-                transform=ax.transAxes, fontsize=20, color='#888888',
-                fontfamily='monospace', weight='normal')
-        ax.axis('off')
-        return fig
-    
-    model_data = historical_df[historical_df.index.str.lower() == model_name.lower()]
-    
-    if model_data.empty:
-        fig, ax = plt.subplots(figsize=(FIGURE_WIDTH, FIGURE_HEIGHT), facecolor=BLACK)
-        ax.set_facecolor(BLACK)
-        ax.text(0.5, 0.5, f'No data found for model: {model_name}',
-                horizontalalignment='center', verticalalignment='center',
-                transform=ax.transAxes, fontsize=20, color='#888888',
-                fontfamily='monospace', weight='normal')
-        ax.axis('off')
-        return fig
-    
-    model_data = model_data.copy()
-    model_data['date_dt'] = pd.to_datetime(model_data['date'])
-    model_data = model_data.sort_values('date_dt')
-    
-    dates = model_data['date_dt'].values
-    amd_stats_list = []
-    nvidia_stats_list = []
-    
-    for _, row in model_data.iterrows():
-        amd_stats, nvidia_stats = extract_model_data(row)[:2]
-        amd_stats_list.append(amd_stats)
-        nvidia_stats_list.append(nvidia_stats)
-    
-    fig = plt.figure(figsize=(FIGURE_WIDTH, FIGURE_HEIGHT), facecolor=BLACK)
-    gs = fig.add_gridspec(2, 2, height_ratios=[1, 1], width_ratios=[3, 1], 
-                          hspace=0.3, wspace=0.2)
-    
-    ax1 = fig.add_subplot(gs[0, 0])
-    ax2 = fig.add_subplot(gs[1, 0])
-    ax3 = fig.add_subplot(gs[:, 1])
-    
-    for ax in [ax1, ax2, ax3]:
-        ax.set_facecolor(BLACK)
-    
-    amd_passed = [stats['passed'] for stats in amd_stats_list]
-    amd_failed = [stats['failed'] for stats in amd_stats_list]
-    amd_skipped = [stats['skipped'] for stats in amd_stats_list]
-    
-    ax1.stackplot(dates, amd_passed, amd_failed, amd_skipped,
-                  colors=[COLORS['passed'], COLORS['failed'], COLORS['skipped']],
-                  alpha=0.7, labels=['Passed', 'Failed', 'Skipped'])
-    
-    ax1.plot(dates, amd_failed, color=COLORS['failed'], linewidth=2.5, 
-             marker='o', markersize=7, markeredgewidth=2, markeredgecolor=BLACK,
-             linestyle='-', label='_nolegend_')
-    
-    ax1.set_title(f'{model_name.upper()} - AMD Results', fontsize=TITLE_FONT_SIZE, 
-                  color=TITLE_COLOR, fontfamily='monospace', fontweight='bold', pad=20)
-    ax1.set_ylabel('Number of Tests', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax1.grid(True, color=GRID_COLOR, alpha=0.3, linestyle='-', linewidth=0.5)
-    ax1.legend(fontsize=LEGEND_FONT_SIZE, loc='upper left', frameon=False, 
-               labelcolor=LABEL_COLOR, prop={'family': 'monospace'})
-    ax1.tick_params(colors=LABEL_COLOR, labelsize=LABEL_FONT_SIZE, axis='x', rotation=45)
-    
-    nvidia_passed = [stats['passed'] for stats in nvidia_stats_list]
-    nvidia_failed = [stats['failed'] for stats in nvidia_stats_list]
-    nvidia_skipped = [stats['skipped'] for stats in nvidia_stats_list]
-    
-    ax2.stackplot(dates, nvidia_passed, nvidia_failed, nvidia_skipped,
-                  colors=[COLORS['passed'], COLORS['failed'], COLORS['skipped']],
-                  alpha=0.7, labels=['Passed', 'Failed', 'Skipped'])
-    
-    ax2.plot(dates, nvidia_failed, color=COLORS['failed'], linewidth=2.5, 
-             marker='s', markersize=7, markeredgewidth=2, markeredgecolor=BLACK,
-             linestyle='-', label='_nolegend_')
-    
-    ax2.set_title(f'{model_name.upper()} - NVIDIA Results', fontsize=TITLE_FONT_SIZE, 
-                  color=TITLE_COLOR, fontfamily='monospace', fontweight='bold', pad=20)
-    ax2.set_ylabel('Number of Tests', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax2.set_xlabel('Date', fontsize=LABEL_FONT_SIZE, color=LABEL_COLOR, fontfamily='monospace')
-    ax2.grid(True, color=GRID_COLOR, alpha=0.3, linestyle='-', linewidth=0.5)
-    ax2.tick_params(colors=LABEL_COLOR, labelsize=LABEL_FONT_SIZE, axis='x', rotation=45)
-    
-    ax3.axis('off')
-    latest_amd = amd_stats_list[-1]
-    latest_nvidia = nvidia_stats_list[-1]
-    
-    amd_total = latest_amd['passed'] + latest_amd['failed']
-    nvidia_total = latest_nvidia['passed'] + latest_nvidia['failed']
-    amd_fail_rate = (latest_amd['failed'] / amd_total * 100) if amd_total > 0 else 0
-    nvidia_fail_rate = (latest_nvidia['failed'] / nvidia_total * 100) if nvidia_total > 0 else 0
-    
-    ax3.text(0.5, 0.95, 'LATEST RESULTS', ha='center', va='top', 
-             fontsize=TITLE_FONT_SIZE - 4, color=TITLE_COLOR, fontfamily='monospace',
-             fontweight='bold', transform=ax3.transAxes)
-    
-    y = 0.80
-    sections = [
-        ('AMD', [
-            ('Pass Rate', f"{(latest_amd['passed']/amd_total*100) if amd_total > 0 else 0:.1f}%", COLORS['passed']),
-            ('Fail Rate', f"{amd_fail_rate:.1f}%", COLORS['failed']),
-            ('Total', str(latest_amd['passed'] + latest_amd['failed'] + latest_amd['skipped']), '#888888'),
-        ]),
-        ('NVIDIA', [
-            ('Pass Rate', f"{(latest_nvidia['passed']/nvidia_total*100) if nvidia_total > 0 else 0:.1f}%", COLORS['passed']),
-            ('Fail Rate', f"{nvidia_fail_rate:.1f}%", COLORS['failed']),
-            ('Total', str(latest_nvidia['passed'] + latest_nvidia['failed'] + latest_nvidia['skipped']), '#888888'),
-        ])
-    ]
-    
-    for section_name, metrics in sections:
-        ax3.text(0.5, y, section_name, ha='center', va='center',
-                fontsize=LABEL_FONT_SIZE + 2, color=TITLE_COLOR,
-                fontfamily='monospace', fontweight='bold', transform=ax3.transAxes)
-        y -= 0.08
-        
-        for label, value, color in metrics:
-            ax3.text(0.15, y, label, ha='left', va='center',
-                    fontsize=LABEL_FONT_SIZE - 1, color=LABEL_COLOR,
-                    fontfamily='monospace', transform=ax3.transAxes)
-            ax3.text(0.85, y, value, ha='right', va='center',
-                    fontsize=LABEL_FONT_SIZE, color=color,
-                    fontfamily='monospace', fontweight='bold', transform=ax3.transAxes)
-            y -= 0.07
-        y -= 0.05
-    
-    plt.close('all')
-    return fig