Map columns in datasets ↗

    from weave.scorers import EmbeddingSimilarityScorer

    similarity_scorer = EmbeddingSimilarityScorer()

    similarity_scorer.column_map = {
        "output": "model_output",  # The model's generated text
        "target": "answer"         # The expected or reference response
    }
    ```

For more details on scorer column mapping, see [Mapping Column Names with `column_map`](../evaluation/scorers#mapping-column-names-with-column_map).
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In the Weave TypeScript SDK, column mapping is configured on the `Evaluation` object using the `columnMapping` option, not on individual scorers. The mapping format is `{scorer_key: dataset_column}`.

The following example maps `expectedOutputTimesTwo` (used by the scorer) to the `expected` column in the dataset:

```typescript
    import * as weave from 'weave';

    const myScorer = weave.op(
      ({modelOutput, datasetRow}) => {
        return modelOutput * 2 === datasetRow.expectedOutputTimesTwo;
      },
      {name: 'myScorer'}
    );

    const myEval = new weave.Evaluation({
      id: 'my-evaluation',
      dataset: [{expected: 2}],
      scorers: [myScorer],
      columnMapping: {expectedOutputTimesTwo: 'expected'},
    });
    ```

For more details on TypeScript scorer arguments, see [Scorer Keyword Arguments](../evaluation/scorers#scorer-keyword-arguments).
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