semvec/pypi-packages huggingface dataset:
oxasl-multite 0.3.0.post7
Python library for modelling multi-TE ASL data
License: Apache-2.0

# OXASL_MULTITE

Plugin for the OXASL pipeline to support multi-TE ASL data.

The data is optionally initially fitted to the standard resting state
ASL model and then the fitted perfusion/arrival time data is used to initialize
the multi-TE model to fit the exchange time.

## Issues

## Citation
magneto-python 0.2.0
Magneto Python library
License: Apache-2.0
Requires Python: >=3.9
Keywords: bdf, data integration, nyu

# Magneto

Magneto is an innovative framework designed to enhance schema matching (SM) by intelligently combining small, pre-trained language models (SLMs) with large language models (LLMs). Our approach is structured to be both cost-effective and broadly applicable.

## Installation


You can install the latest stable version of Magneto from [PyPI](https://pypi.org/project/magneto-python/):

```
pip install magneto-python
```


## Usage
After the installation, you can use the stand-alone version of Magneto like this:

```Python
from magneto import Magneto
import pandas as pd

source = pd.DataFrame({"column_1": ["a1", "b1", "c1"], "col_2": ["a2", "b2", "c2"]})
target = pd.DataFrame({"column_1a": ["a1", "b1", "c1"], "col2": ["a2", "b2", "c2"]})

mode = "header_values_verbose"
mag = Magneto(encoding_mode=mode)
matches = mag.get_matches(source, target)

print(matches)
```

See our [GitHub repository](https://github.com/VIDA-NYU/data-integration-eval/tree/main/algorithms/magneto) for more examples.