# Plot Parameters ## Overview The **Plot Parameters** node creates visual graphs and plots from sampler parameters, enabling data-driven analysis of generation settings. Adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode), this tool helps visualize the relationship between parameters and output quality. ## Attribution This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows. ## Features - **Multi-Parameter Plotting**: Visualize multiple parameters simultaneously - **Comparison Graphs**: Compare settings across batch runs - **Statistical Analysis**: Calculate means, deviations, and trends - **Export Capabilities**: Save plots as images or data files - **Real-time Updates**: Dynamic graph generation during workflow execution ## Node Properties - **Category**: `ComfyAssets/🧰 xyz-helpers` - **Node Name**: `PlotParameters` - **Function**: `plot` ## Inputs ### Required | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `sampler_params` | SAMPLER_PARAMS | - | Parameters to plot | | `plot_type` | DROPDOWN | line | [line, bar, scatter, heatmap] | | `x_axis` | DROPDOWN | steps | Parameter for X axis | | `y_axis` | DROPDOWN | quality | Metric for Y axis | ### Optional | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `title` | STRING | "Parameter Analysis" | Graph title | | `show_grid` | BOOLEAN | True | Display grid lines | | `show_legend` | BOOLEAN | True | Display legend | | `color_scheme` | DROPDOWN | default | Color palette selection | ## Outputs | Name | Type | Description | |------|------|-------------| | `plot_image` | IMAGE | Generated plot as image | | `data_csv` | STRING | Plot data in CSV format | | `statistics` | STRING | Statistical summary | ## Usage Examples ### Basic Parameter Visualization ``` FluxSamplerParams → PlotParameters → Display Image plot_type: line x_axis: steps y_axis: guidance ``` ### Batch Comparison Plot ``` LoRAFolderBatch → PlotParameters → Save Image plot_type: scatter x_axis: lora_strength y_axis: quality_score ``` ### Heatmap Analysis ``` Parameter Grid → PlotParameters → Analysis Display plot_type: heatmap x_axis: cfg y_axis: steps ``` ## Plot Types Explained ### Line Plot - Best for continuous parameter changes - Shows trends and relationships - Ideal for time series or progression ### Bar Chart - Compares discrete values - Good for categorical comparisons - Shows distribution clearly ### Scatter Plot - Reveals correlations - Identifies outliers - Best for large datasets ### Heatmap - Two-dimensional parameter analysis - Color-coded intensity values - Perfect for grid searches ## Best Practices ### Parameter Selection - Choose related parameters for meaningful plots - Use consistent scales for comparison - Consider parameter ranges when plotting ### Visual Clarity - Limit number of series to 5-7 for readability - Use contrasting colors for multiple lines - Enable grid for precise value reading ### Data Analysis ```python # Effective parameter combinations x_axis: "guidance" y_axis: "perceived_quality" # Step efficiency analysis x_axis: "steps" y_axis: "generation_time" # LoRA impact assessment x_axis: "lora_strength" y_axis: "style_adherence" ``` ## Integration Examples ### Complete Analysis Pipeline ``` 1. Generate with parameters 2. Plot results 3. Export data 4. Statistical analysis ``` ### Multi-Plot Workflow ``` Params → Plot1 (steps vs quality) ↘ Plot2 (guidance vs coherence) ↘ Plot3 (strength vs style) → Combined Analysis ``` ## Advanced Features ### Custom Metrics - Define custom Y-axis metrics - Import external quality scores - Calculate derived values ### Export Options - PNG/SVG image formats - CSV data export - JSON statistics export ### Styling Options ```python # Professional presentation color_scheme: "scientific" show_grid: True show_legend: True # Minimal style color_scheme: "minimal" show_grid: False show_legend: False ``` ## Statistical Analysis ### Available Metrics - Mean, Median, Mode - Standard Deviation - Correlation Coefficients - Trend Lines - R-squared Values ### Interpretation Guide - **Positive Correlation**: Parameters increase together - **Negative Correlation**: Inverse relationship - **No Correlation**: Independent parameters ## Tips and Tricks ### Optimal Visualization 1. Start with scatter plots for exploration 2. Use line plots for trends 3. Apply heatmaps for 2D parameter spaces 4. Bar charts for final comparisons ### Data Preparation - Normalize scales when comparing different metrics - Remove outliers for cleaner plots - Group similar parameters ### Performance Tips - Cache plot images for repeated viewing - Export data for external analysis - Use lower resolution for preview plots ## Troubleshooting ### Empty Plots - Verify sampler_params contains data - Check axis parameter selection - Ensure valid parameter ranges ### Scaling Issues - Use logarithmic scale for wide ranges - Normalize data if needed - Adjust plot dimensions ### Export Problems - Check file permissions - Verify export path exists - Ensure sufficient disk space ## Use Cases ### Hyperparameter Optimization Track and visualize the effect of different sampling parameters on output quality. ### LoRA Strength Analysis Plot the relationship between LoRA strength and style transfer effectiveness. ### Efficiency Studies Analyze generation time vs quality trade-offs across different settings. ### Batch Comparison Compare multiple generation runs to identify optimal parameters. ## Version History - **1.0.0**: Initial adaptation from comfyui-essentials-nodes - **1.0.1**: Added heatmap visualization - **1.0.2**: Enhanced statistical analysis - **1.0.3**: Improved export capabilities ## Credits Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.