plot_edf
Generate an Empirical Distribution Function (EDF) plot to visualize the distribution of optimization objective values. Specify the target index and name for precise analysis of Optuna optimization results.
Instructions
Return the EDF plot as an image.
Args:
target:
An index to specify the value to display. To plot nth objective value, set this to n.
Note that this is 0-indexed, i.e., to plot the first objective value, set this to 0.
target_name:
Target’s name to display on the axis label.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| target | No | ||
| target_name | No | Objective Value |
Implementation Reference
- optuna_mcp/server.py:585-604 (handler)The `plot_edf` tool handler: generates an Empirical Distribution Function (EDF) plot of the study's objective values using `optuna.visualization.plot_edf`, converts it to PNG image using Plotly, and returns an MCP `Image` object.@mcp.tool() def plot_edf( target: int = 0, target_name: str = "Objective Value", ) -> Image: """Return the EDF plot as an image. Args: target: An index to specify the value to display. To plot nth objective value, set this to n. Note that this is 0-indexed, i.e., to plot the first objective value, set this to 0. target_name: Target’s name to display on the axis label. """ fig = optuna.visualization.plot_edf( mcp.study, target=lambda t: t.values[target], target_name=target_name, ) return Image(data=plotly.io.to_image(fig), format="png")