Metadata-Version: 2.1
Name: trecrun
Version: 0.1.0
Summary: Library for working with TREC run files
Home-page: https://github.com/capreolus-ir/trecrun
Author: Andrew Yates
Author-email: one-name-then-the-next@gmail.com
License: UNKNOWN
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        # TRECRun
        
        `TRECRun` is a library for working with TREC run files, with an API heavily inspired by PyTerrier's pipeline operators.
        
        | API | Operator | Description |
        | --- | --- | --- |
        | `TRECRun(results)` | | Create a `TRECRun` object from a dictionary of results or a path to a run file in TREC format. |
        | `add(self, other)`, `subtract`, `multiply`, `divide` | `+`, `-`, `*`, `/` | Perform the given operation between self's document scores and `other`, which can be a `TRECRun` or a scalar. |
        | `topk(self, k)` | `%` | Retain only the top-k documents for each qid after sorting by score. |
        | `intersect(self, other)` | `&` | Retain only the queries and documents that appear in both `self` and `other`. |
        | `concat(self, other)` | | Concat the documents in `other` and `self`, with those in `other` appearing at the end. Their scores will be modified to accomplish this.  |
        | `normalize(self, method='rr')` | | Normalize scores in self using RRF (`rr`), sklearn's min-max scaling (`minmax`), or sklearn's scaling (`standard`).|
        | `write_trec_run(self, outf)` | | Write `self` to `outfn` in TREC format.|
        | `evaluate(self, qrels, metrics, return_average=True)` | | Compute `metrics` for `self` using `qrels` and return either the average metric or a dict mapping metric names to their values for each QID. |
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
