r"""Computes CombMAX as proposed by [Fox et al.](https://trec.nist.gov/pubs/trec2/papers/txt/23.txt). ```bibtex @inproceedings{DBLP:conf/

r"""Computes CombMED as proposed by [Fox et al.](https://trec.nist.gov/pubs/trec2/papers/txt/23.txt). ```bibtex @inproceedings{DBLP:conf/

r"""Computes CombMIN as proposed by [Fox et al.](https://trec.nist.gov/pubs/trec2/papers/txt/23.txt). ```bibtex @inproceedings{DBLP:conf/

Used internally.

Execute the correct download operation. Depending on the size of the file online and offline, resume the download if the file offline is small

Performs (approximated) Fisher's Randomization Test. Null hypothesis: system A (control) and system B (treatment) are identical (i.e., syste

Convert a Pandas DataFrame to ranx.Qrels. Args: df (pandas.DataFrame): Qrels as Pandas DataFrame. q_id_col (str, opti

Returns query ids.

r"""Compute Interpolated Precision at Recall. Args: qrels (Union[np.ndarray, numba.typed.List]): IDs and relevance scores of _relevant_ d

r"""Computes ISR as proposed by [Mourão et al.](https://www.sciencedirect.com/science/article/abs/pii/S0895611114000664). ```bibtex @art

r"""Computes Log_ISR as proposed by [Mourão et al.](https://www.sciencedirect.com/science/article/abs/pii/S0895611114000664). ```bibtex

r"""Computes MAPFuse as proposed by [Lillis et al.](https://dl.acm.org/doi/10.1145/1835449.1835508). ```bibtex @inproceedings{DBLP:conf/sigir

Apply `max norm` to a run.

Two-sided Paired Student's t-Test. Null hypothesis: system A (control) and system B (treatment) are identical (i.e., system A has no effect

r"""Computes PosFuse as proposed by [Lillis et al.](https://dl.acm.org/doi/10.1145/1835449.1835508). ```bibtex @inproceedings{DBLP:conf/sigir

Apply `rank norm` to a run.

r"""Computes SegFuse as proposed by [Shokouhi](https://link.springer.com/chapter/10.1007/978-3-540-78646-7_33). ```bibtex @inproceedings{

Sets relevance level.

Apply `sum norm` to a run.

Convert Qrels to Pandas DataFrame with the following columns: `q_id`, `doc_id`, and `score`. Returns: pandas.DataFrame: Qrels as

Convert Qrels to Numba Typed List. Used internally.

Performs Tukey's Honestly Significant Difference (HSD) Test.

Apply `zmuv norm` to a run.

Add a query and its relevant documents with the associated relevance score. Args: q_id (str): Query ID doc_ids (List[

Add a query and its relevant documents with the associated relevance score judgment. Args: q_id (str): Query ID doc_i

r"""Compute Average Precision. Average Precision is the average of the Precision scores computed after each relevant document is retrieved.<br />

r"""Compute Discounted Cumulative Gain (DCG) as proposed by [Järvelin et al.](http://doi.acm.org/10.1145/582415.582418).<br /> If k > 0, only the

r"""Compute Discounted Cumulative Gain (DCG) at k as proposed by [Burges et al.](https://doi.org/10.1145/1102351.1102363).<br /> If k > 0, only th

Extract the scores from a given results dictionary.

Parse a qrels file into ranx.Qrels. Supported formats are JSON, TREC qrels, and gzipped TREC qrels. Correct import behavior is inferred from the file

Convert `ir-datasets` qrels into ranx.Qrels. It automatically downloads data if missing. Args: dataset_id (str): ID of the detaset

Convert a Parquet file to ranx.Qrels. Args: path (str): File path. q_id_col (str, optional): Query IDs column. Defaul

Download and load a ranx.Run from ranxhub. Args: path (str): Run ID. Returns: Run: ranx.Run

Returns doc ids and relevance scores.

Returns doc ids and relevance judgments.