import matplotlib.pyplot as plt import pandas as pd from utils import generate_underlined_line from data import extract_model_data # Figure dimensions FIGURE_WIDTH_DUAL = 18 FIGURE_HEIGHT_DUAL = 9 # Colors COLORS = { 'passed': '#4CAF50', # Medium green 'failed': '#E53E3E', # More red 'skipped': '#FFD54F', # Medium yellow 'error': '#8B0000' # Dark red } # Styling constants BLACK = '#000000' LABEL_COLOR = '#AAAAAA' TITLE_COLOR = '#FFFFFF' # Font sizes DEVICE_TITLE_FONT_SIZE = 28 # Layout constants SEPARATOR_LINE_Y_END = 0.85 SUBPLOT_TOP = 0.85 SUBPLOT_WSPACE = 0.4 PIE_START_ANGLE = 90 BORDER_LINE_WIDTH = 0.5 SEPARATOR_ALPHA = 0.5 SEPARATOR_LINE_WIDTH = 1 DEVICE_TITLE_PAD = 2 MODEL_TITLE_Y = 1 # Processing constants MAX_FAILURE_ITEMS = 10 def _create_pie_chart(ax: plt.Axes, device_label: str, filtered_stats: dict) -> None: """Create a pie chart for device statistics.""" if not filtered_stats: ax.text(0.5, 0.5, 'No test results', horizontalalignment='center', verticalalignment='center', transform=ax.transAxes, fontsize=14, color='#888888', fontfamily='monospace', weight='normal') ax.set_title(device_label, fontsize=DEVICE_TITLE_FONT_SIZE, weight='bold', pad=DEVICE_TITLE_PAD, color=TITLE_COLOR, fontfamily='monospace') ax.axis('off') return chart_colors = [COLORS[category] for category in filtered_stats.keys()] # Create minimal pie chart - full pie, no donut effect wedges, texts, autotexts = ax.pie( filtered_stats.values(), labels=[label.lower() for label in filtered_stats.keys()], # Lowercase for minimal look colors=chart_colors, autopct=lambda pct: f'{round(pct * sum(filtered_stats.values()) / 100)}', startangle=PIE_START_ANGLE, explode=None, # No separation shadow=False, wedgeprops=dict(edgecolor='#1a1a1a', linewidth=BORDER_LINE_WIDTH), # Minimal borders textprops={'fontsize': 12, 'weight': 'normal', 'color': LABEL_COLOR, 'fontfamily': 'monospace'} ) # Enhanced percentage text styling for better readability for autotext in autotexts: autotext.set_color(BLACK) # Black text for better contrast autotext.set_weight('bold') autotext.set_fontsize(14) autotext.set_fontfamily('monospace') # Minimal category labels for text in texts: text.set_color(LABEL_COLOR) text.set_weight('normal') text.set_fontsize(13) text.set_fontfamily('monospace') # Device label closer to chart and bigger ax.set_title(device_label, fontsize=DEVICE_TITLE_FONT_SIZE, weight='normal', pad=DEVICE_TITLE_PAD, color=TITLE_COLOR, fontfamily='monospace') def plot_model_stats(df: pd.DataFrame, model_name: str) -> tuple[plt.Figure, str, str]: """Draws pie charts of model's passed, failed, skipped, and error stats for AMD and NVIDIA.""" # Handle case where the dataframe is empty or the model name could not be found in it if df.empty or model_name not in df.index: # Create empty stats for both devices amd_filtered = {} nvidia_filtered = {} failures_amd = failures_nvidia = {} else: row = df.loc[model_name] # Extract and process model data amd_stats, nvidia_stats = extract_model_data(row)[:2] # Filter out categories with 0 values for cleaner visualization amd_filtered = {k: v for k, v in amd_stats.items() if v > 0} nvidia_filtered = {k: v for k, v in nvidia_stats.items() if v > 0} # Generate failure info directly from dataframe failures_amd = dict(row.get('failures_amd', {})) failures_nvidia = dict(row.get('failures_nvidia', {})) # failure_xxx = {"single": [test, ...], "multi": [...]} # test = {"line": test_name. "trace": error_msg} # Always create figure with two subplots side by side with padding fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(FIGURE_WIDTH_DUAL, FIGURE_HEIGHT_DUAL), facecolor=BLACK) ax1.set_facecolor(BLACK) ax2.set_facecolor(BLACK) # Create both pie charts with device labels _create_pie_chart(ax1, "amd", amd_filtered) _create_pie_chart(ax2, "nvidia", nvidia_filtered) # Add subtle separation line between charts - stops at device labels level line_x = 0.5 fig.add_artist(plt.Line2D([line_x, line_x], [0.0, SEPARATOR_LINE_Y_END], color='#333333', linewidth=SEPARATOR_LINE_WIDTH, alpha=SEPARATOR_ALPHA, transform=fig.transFigure)) # Add central shared title for model name fig.suptitle(f'{model_name.lower()}', fontsize=32, weight='bold', color='#CCCCCC', fontfamily='monospace', y=MODEL_TITLE_Y) # Clean layout with padding and space for central title plt.tight_layout() plt.subplots_adjust(top=SUBPLOT_TOP, wspace=SUBPLOT_WSPACE) amd_failed_info = prepare_textbox_content(failures_amd, 'AMD', bool(amd_filtered)) nvidia_failed_info = prepare_textbox_content(failures_nvidia, 'NVIDIA', bool(nvidia_filtered)) return fig, amd_failed_info, nvidia_failed_info def prepare_textbox_content(failures: dict[str, list], device: str, data_available: bool) -> str: """Extract failure information from failures object.""" # Catch the case where there is no data if not data_available: return generate_underlined_line(f"No data for {device}") # Catch the case where there are no failures if not failures: return generate_underlined_line(f"No failures for {device}") # Summary of failures single_failures = failures.get("single", []) multi_failures = failures.get("multi", []) info_lines = [ generate_underlined_line(f"Failure summary for {device}:"), f"Single GPU failures: {len(single_failures)}", f"Multi GPU failures: {len(multi_failures)}", "" ] # Add single-gpu failures if single_failures: info_lines.append(generate_underlined_line("Single GPU failures:")) for test in single_failures: name = test.get("line", "::*could not find name*") name = name.split("::")[-1] info_lines.append(name) info_lines.append("\n") # Add multi-gpu failures if multi_failures: info_lines.append(generate_underlined_line("Multi GPU failures:")) for test in multi_failures: name = test.get("line", "::*could not find name*") name = name.split("::")[-1] info_lines.append(name) return "\n".join(info_lines)