Metadata-Version: 2.4
Name: pycubeview
Version: 0.1.3
Summary: A Flexible and Interactive Spectral (and more!) Image Viewer for Python
License: LICENSE
License-File: LICENSE
Author: Z.M. Vig
Author-email: zvig@umd.edu
Requires-Python: >=3.13,<4
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Dist: alphashape (>=1.3.1,<2.0.0)
Requires-Dist: arguably (>=1.3.0,<2.0.0)
Requires-Dist: cmap (>=0.6.2,<0.7.0)
Requires-Dist: pandas (>=2.3.3,<3.0.0)
Requires-Dist: pandas-stubs (>=2.3.3.251201,<3.0.0.0)
Requires-Dist: pyqt6 (>=6.10.0,<7.0.0)
Requires-Dist: pyqtgraph (>=0.14.0,<0.15.0)
Requires-Dist: shapely (>=2.1.2,<3.0.0)
Requires-Dist: spectralio (>=0.1.4,<0.2.0)
Requires-Dist: types-shapely (>=2.1.0.20250917,<3.0.0.0)
Description-Content-Type: text/markdown

# pycubeview 🔎

A Flexible and Interactive Spectral (and more!) Image Viewer for Python

---

## Motivation ✨

Whether it's an imaging spectrometer or an InSAR time-series, many remotely
sensed scientific data comes in the form of a cube, which is here defined as
any dataset that has spatial information in two dimensions and measured values
in a third dimension. Below are listed some examples of scientific data cubes:

- Hyperspectral Imagery
- Multispectral Imagery
- Spectral Maps from lab spectrometers
- InSAR Time Series
- Cloud Cover Evolution Map
- LiDAR return counts
- Scanning medical imagery
- RGB Images
- General Vector Fields
- And Many More!


## Installation ⬇️

`pycubeview` can be directly install from the Python Package Index using `pip`.

```bash
pip install pycubeview
```

## Usage ⚙️

The basic CubeView GUI can be opened directly from the command line by ensuring you are in a python environment that has `pycubeview` installed and running

```bash
cubeview.exe
```

The CubeView GUI can also be started from a python script.

```python
from pycubeview import open_cubeview
open_cubeview(image_data, cube_data, wvl_data)
```
Where the data can optionally provided as either a Numpy-Array or a filepath to one of the supported file types.

## Supported File Types 📂
### Image and Cube Data
#### `spectralio` files

  - .geospcub
  - .spcub

#### `rasterio`-compatible files
  - .img
  - .bsq
  - .tif

### Wavelength Data
  - .wvl
  - .hdr
  - .txt
  - .csv



