.. _auto_dataset_design_space_filler:

*DATASET DESIGN SPACE FILLER*
=============================

Identifies sparse regions in an existing design dataset and fills them with new candidate points to improve design-space coverage. Given a set of input columns, it generates a specified number of new input combinations using space-filling sampling, with optional normalization. Use this worker to augment a DOE dataset before surrogate model training or further exploration.

When to use
-----------

Classification: **process**.

Tagged: ``design_space_filler``, ``doe_augmentation``, ``minmax``, ``normalization``, ``sampling``, ``space_filling``, ``sparse_region``, ``znorm``.

Inputs
------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20 20 20

   * - Label
     - ID
     - Type
     - Default
     - Required
     - Description
   * - Dataset
     - dataset_1
     - dataset
     - —
     - 
     - Input dataset (tabular) to be checked for sparseness; must contain the columns nominated as design inputs — leave unconnected only if inputs are supplied programmatically.
   * - Inputs
     - inputs
     - scalar
     - —
     - 
     - Column names from dataset_1 that define the design-space axes to be analysed and filled; select one or more columns from the dataset picker.
   * - Sampling Size
     - sampling_size
     - text
     - 1000
     - 
     - Number of candidate points generated internally during the space-filling search; default 1000 — increase for higher-dimensional or denser coverage requirements.
   * - Number of New Inputs
     - num_new_inputs
     - text
     - 11
     - 
     - Number of new design points to return in the filled dataset; default 11 — set higher when a larger augmentation of the original dataset is needed.
   * - Normalize Data
     - normalize
     - string
     - no
     - 
     - Whether to normalise the input columns before computing distances for sparseness detection; options are 'yes' or 'no' (default) — enable when input columns have very different value ranges.
   * - Normalization Type
     - norm_type
     - string
     - znorm
     - 
     - Normalisation method applied when normalize='yes'; 'znorm' (default) performs z-score standardisation, 'minmax' scales each column to [0, 1].

Outputs
-------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20

   * - Label
     - ID
     - Type
     - Description
   * - Filled Design Space
     - dataset_filled_design_space
     - dataset
     - Tabular dataset containing the newly generated design points (num_new_inputs rows, same input columns as selected) that fill the sparse regions of the original design space.

Disciplines
-----------

- ai_ml.preprocessing
- data.dataset.transform
- design_exploration.doe

Runnable example
----------------

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: `/api/workflow/example?id=dataset_design_space_filler <https://www.d3view.com/api/workflow/example?id=dataset_design_space_filler>`_

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   Auto-generated from <code>transformation</code> schema. Worker id: <code>dataset_design_space_filler</code>. Schema hash: <code>22cc6b9a25f3</code>. Hand-curated docs in <code>workerexamples/</code> override this page when present.
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