DendrogramExplorer
Hierarchical dendrogram for Agglomerative clustering.
Reconstructs the merge history stored in the Clustering converter
report when run with the agglomerative algorithm and the
Compute distances option enabled.
The dendrogram shows the full cluster hierarchy: leaves represent individual samples, internal nodes represent merges, and the height of each merge reflects the linkage distance at which two sub-trees were joined. Reading the dendrogram reveals:
- The natural number of clusters (large gaps between consecutive merge heights suggest a good cut point).
- Relative similarity between groups.
- Potential outliers that merge last at very large distances.
This explorer raises an informative error if the last Clustering
converter was not run with the Agglomerative algorithm and
Compute distances enabled. No column selection is required.
Methods
get_results(self, exploration_path: str, options: Dict[str, Any]) -> Dict[str, Any]
DendrogramExplorerLoad the saved dendrogram and return it for the frontend.
Parameters
- exploration_path : str
- Path to the JSON file saved by
save_notebook. - options : Dict[str, Any]
- Rendering options from the frontend (unused).
Returns
- Dict[str, Any]
- Dictionary with keys
"data"(JSON-serialised Plotly figure),"type"("plotly_json"), and"config"(empty dict).
launch_exploration(self, _dataset: 'DashAIDataset', explorer_info: DashAI.back.dependencies.database.models.Explorer) -> Any
DendrogramExplorerBuild a Plotly dendrogram from the Agglomerative linkage data.
Parameters
- _dataset : DashAIDataset
- Not used. All data is read from the converter report.
- explorer_info : Explorer
- Explorer record, used for the optional custom title.
Returns
- plotly.graph_objects.Figure
- An interactive dendrogram figure.
prepare_dataset(self, loaded_dataset: 'DashAIDataset', _columns: List[Dict[str, Any]]) -> 'DashAIDataset'
DendrogramExplorerReturn the dataset unchanged.
Parameters
- loaded_dataset : DashAIDataset
- The full dataset.
- _columns : List[Dict[str, Any]]
- Ignored. Present for API compatibility.
Returns
- DashAIDataset
- The dataset as received, unmodified.
save_notebook(self, notebook_info: DashAI.back.dependencies.database.models.Notebook, explorer_info: DashAI.back.dependencies.database.models.Explorer, save_path: 'Path', result: Any) -> str
DendrogramExplorerSave the dendrogram figure to disk as a JSON file.
Parameters
- notebook_info : Notebook
- The notebook database record (unused).
- explorer_info : Explorer
- The explorer record used for filename generation.
- save_path : Path
- Directory where the file will be saved.
- result : Any
- The Plotly figure returned by
launch_exploration.
Returns
- str
- The path of the saved JSON file as a POSIX string.
get_credential(self, name: str)
ConfigObjectResolve a registered credential component by name.
Parameters
- name : str
- Credential component class name (e.g. "HuggingFaceCredential").
Returns
- BaseCredential
- An instance of the requested credential component.
get_metadata(cls) -> Dict[str, Any]
BaseExplorerGet metadata for the explorer, used by the DashAI frontend.
Returns
- Dict[str, Any]
- Dictionary containing display name, description, image preview path, category, icon, color, allowed semantic types, allowed dtypes, input cardinality constraints, and any optional capability flags declared by the explorer.
get_schema(cls) -> dict
ConfigObjectGenerates the component related Json Schema.
Returns
- dict
- Dictionary representing the Json Schema of the component.
set_context(self, context: Dict[str, Any]) -> None
BaseExplorerSet optional runtime context for explorers that need extra inputs.
validate_and_transform(self, raw_data: dict) -> dict
ConfigObjectIt takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Parameters
- raw_data : dict
- A dictionary with the data provided by the user to initialize the model.
Returns
- dict
- A validated dictionary with the necessary objects.
validate_columns(cls, explorer_info: DashAI.back.dependencies.database.models.Explorer, column_spec: Dict[str, Dict[str, str]]) -> bool
BaseExplorerValidate that the selected columns satisfy the explorer's constraints.
Parameters
- explorer_info : Explorer
- The database record for the explorer instance, including the selected columns.
- column_spec : Dict[str, Dict[str, str]]
- A mapping from column name to a dict with at least
"type"(semantic type name) and"dtype"(dtype string).
Returns
- bool
- True if all column constraints are satisfied, False otherwise.
validate_parameters(cls, params: Dict[str, Any]) -> bool
BaseExplorerValidate explorer parameters against the explorer's schema.
Parameters
- params : Dict[str, Any]
- The configuration parameters to validate.
Returns
- BaseExplorerSchema
- The validated and parsed schema instance. Subclasses that override this method may return a bool to indicate pass/fail without returning the model instance.