Metadata-Version: 2.1
Name: fitsdataset
Version: 0.0.3
Summary: A PyTorch Dataset for the FITS file format
Home-page: https://github.com/amritrau/fitsdataset
Author: Amrit Rau
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: torch
Requires-Dist: astropy

FITSDataset
===
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This package contains a custom PyTorch Dataset for quick and easy training on FITS files, commonly used in astronomical data analysis. In particular, the `FITSDataset` class caches FITS files as PyTorch tensors for the purpose of increasing training speed.

Contributions and feedback are welcome; please open a pull request or an issue.

## Quickstart
Using Python 3.6+, install from source with
```bash
pip install fitsdataset
```

Create a toy dataset with samples from the
[Hyper Suprime-Cam survey](https://www.naoj.org/Projects/HSC/) with:
```python
>>> from fitsdataset import FITSDataset
>>> dataset = FITSDataset("path/to/examples/hsc/", size=101, label_col="target")
```

Notice that the cached tensors appear in `path/to/examples/hsc/tensors`.

## Preparing a dataset
Prepare your own FITS dataset by creating the following directory structure:
```
path/to/data/
  info.csv
  cutouts/
    img1.fits
    img2.fits
    ...
```
where `info.csv` has a filename column (basename) and a prediction target column. See [here](https://github.com/amritrau/fitsdataset/blob/master/examples/hsc/info.csv) for an example.

## Documentation
```python
>>> from fitsdataset import FITSDataset
>>> help(FITSDataset)
```
