# IBM Visualization Data Explorer Programmer's Reference

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# Chapter 14. Data Processing

Partial Table-of-Contents

- 14.1 Data Partitioning
- 14.2 Interpolation and Mapping
- 14.3 Invalid Data
- Examples
- 14.4 Growing and Shrinking Partitioned Data
- 14.5 Hashing
- Examples
- 14.6 Pick-Assistance Routines
- Example

  The higher-level processing functions available in Data Explorer include: data partitioning, interpolation and mapping, invalid-data handling, growing and shrinking partitioned data, hashing, and picking.

  ## 14.1 Data Partitioning

  Partitioning is the process of dividing a Field into spatially disjoint subsets called "partitions." The result is a Composite Field, whose members are partitions. Partitioning is particularly useful for parallel processing.

  Since each interpolation element of an input Field is assigned to one and only one partition, the resulting partitions cover precisely the same region of space as the original input Field did without overlap. However, because the input elements cover the same region of space, the bounding boxes of the resulting partitions may overlap.

  `Group DXPartition()` | Divides a Field into partitions. See DXPartition.

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