# ndslice
**Quick interactive visualization for N-dimensional NumPy arrays**
A python package for browsing slices, applying FFTs, and inspecting data.
Quickly checking multi-dimensional data usually means writing the same matplotlib boilerplate over and over. This tool lets you just call `ndslice(data)` and interactively explore what you've got.
## Usage
```python
from ndslice import ndslice
import numpy as np
# Create some data
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
z = np.linspace(-5, 5, 50)
X, Y, Z = np.meshgrid(x, y, z, indexing='ij')
mag = np.exp(-(X**2 + Y**2 + Z**2) / 10)
pha = np.pi/4 * (X + Y + Z)
complex_data = mag * np.exp(1j * pha)
ndslice(complex_data, title='3D Complex Gaussian')
```
## Features
Data slicing and dimension selection should be intuitive: click the two dimensions you want to show and slice using the spinboxes.
**Centered FFT** - Click dimension labels to apply centered 1D FFT transforms. Useful for checking k-space data in MRI reconstructions or analyzing frequency content.
**Line plot** - See 1D slices through your data. Shift+scroll for Y zoom, Ctrl+scroll for X zoom:
**Scaling**
Log scaling is often good for k-space visualization.
Symmetric log scaling is an extension of the log scale which supports negative values.
**Colormap**
Change colormap:
- `Ctrl+1` Grayscale
- `Ctrl+2` Viridis
- `Ctrl+3` Plasma
- `Ctrl+4` Rainbow
**Axis flipping**
Click arrow icons (⬇️/⬆️ and ⬅️/➡️) next to dimension labels to flip axes.
Default orientation is image-style (origin lower-left).
Flip the primary axis for matrix-style (origin upper-left).
**Non-blocking windows**
By default, windows open in separate processes, allowing multiple simultaneous views:
```python
ndslice(data1)
ndslice(data2) # Both windows appear
```
Use `block=True` to wait for the window to close before continuing:
```python
ndslice(data1, block=True) # Script pauses here
ndslice(data2) # Shown after first closes
```
### Command Line
```bash
ndslice data.npy # Numpy file
ndslice --help # Show all options
```
**File support**
ndslice has CLI support and can conveniently display:
- Numpy `.npy` / `.npz`
- MATLAB `.mat` (requires scipy)
- HDF5 `.h5` / `.hdf5`, (requires h5py)
- [BART](https://mrirecon.github.io/bart/) `.cfl` + `.hdr`
- Philips `.REC` + `.xml`
- NifTI `.nii` / `.nii.gz`
- Dicom pixel array `.dcm` (requires pydicom)
HDF5 files can be compound complex dtype, or real/imag fields.
If there are multiple datasets in the file, a selection GUI appears which highlights arrays supported by ndslice (essentially numeric).
Double click to open.
## Installation
### From PyPI
```bash
pip install ndslice
pip install h5py # Optional for HDF5 CLI support
```
### From source
```bash
git clone https://github.com/henricryden/ndslice.git
cd ndslice
# Use directly without installing
python -m ndslice data.npy
pip install -e .
```
## Requirements
- Python >= 3.8
- NumPy >= 1.20.0
- PyQtGraph >= 0.12.0
- PyQt5 >= 5.15.0
- h5py >= 3.0.0 (for HDF5 file support in CLI)
## License
MIT License - see LICENSE file for details.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## Acknowledgments
Built with [PyQtGraph](https://www.pyqtgraph.org/) for high-performance visualization.
---
Henric Rydén
Karolinska University Hospital
Stockholm, Sweden
Raw data
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"description": "# ndslice\n\n**Quick interactive visualization for N-dimensional NumPy arrays**\n\nA python package for browsing slices, applying FFTs, and inspecting data.\n\nQuickly checking multi-dimensional data usually means writing the same matplotlib boilerplate over and over. This tool lets you just call `ndslice(data)` and interactively explore what you've got.\n\n## Usage\n```python\nfrom ndslice import ndslice\nimport numpy as np\n\n# Create some data\nx = np.linspace(-5, 5, 100)\ny = np.linspace(-5, 5, 100)\nz = np.linspace(-5, 5, 50)\nX, Y, Z = np.meshgrid(x, y, z, indexing='ij')\nmag = np.exp(-(X**2 + Y**2 + Z**2) / 10)\npha = np.pi/4 * (X + Y + Z)\ncomplex_data = mag * np.exp(1j * pha)\n\nndslice(complex_data, title='3D Complex Gaussian')\n```\n\n\n\n## Features\n\nData slicing and dimension selection should be intuitive: click the two dimensions you want to show and slice using the spinboxes.\n\n**Centered FFT** - Click dimension labels to apply centered 1D FFT transforms. Useful for checking k-space data in MRI reconstructions or analyzing frequency content.\n\n\n**Line plot** - See 1D slices through your data. Shift+scroll for Y zoom, Ctrl+scroll for X zoom:\n\n\n\n**Scaling**\n\nLog scaling is often good for k-space visualization.\nSymmetric log scaling is an extension of the log scale which supports negative values.\n\n\n**Colormap**\nChange colormap:\n- `Ctrl+1` Grayscale\n- `Ctrl+2` Viridis\n- `Ctrl+3` Plasma\n- `Ctrl+4` Rainbow\n\n\n**Axis flipping**\nClick arrow icons (\u2b07\ufe0f/\u2b06\ufe0f and \u2b05\ufe0f/\u27a1\ufe0f) next to dimension labels to flip axes.\nDefault orientation is image-style (origin lower-left).\nFlip the primary axis for matrix-style (origin upper-left).\n\n**Non-blocking windows**\n\nBy default, windows open in separate processes, allowing multiple simultaneous views:\n```python\nndslice(data1)\nndslice(data2) # Both windows appear\n```\n\nUse `block=True` to wait for the window to close before continuing:\n```python\nndslice(data1, block=True) # Script pauses here\nndslice(data2) # Shown after first closes\n```\n\n\n### Command Line\n```bash\nndslice data.npy # Numpy file\nndslice --help # Show all options\n```\n\n**File support**\nndslice has CLI support and can conveniently display:\n\n- Numpy `.npy` / `.npz`\n- MATLAB `.mat` (requires scipy)\n- HDF5 `.h5` / `.hdf5`, (requires h5py)\n- [BART](https://mrirecon.github.io/bart/) `.cfl` + `.hdr`\n- Philips `.REC` + `.xml`\n- NifTI `.nii` / `.nii.gz`\n- Dicom pixel array `.dcm` (requires pydicom)\n\nHDF5 files can be compound complex dtype, or real/imag fields.\n\nIf there are multiple datasets in the file, a selection GUI appears which highlights arrays supported by ndslice (essentially numeric).\nDouble click to open.\n\n\n\n\n## Installation\n\n### From PyPI\n\n```bash\npip install ndslice\npip install h5py # Optional for HDF5 CLI support\n```\n\n### From source\n\n```bash\ngit clone https://github.com/henricryden/ndslice.git\ncd ndslice\n\n# Use directly without installing\npython -m ndslice data.npy\n\npip install -e .\n```\n\n\n## Requirements\n\n- Python >= 3.8\n- NumPy >= 1.20.0\n- PyQtGraph >= 0.12.0\n- PyQt5 >= 5.15.0\n- h5py >= 3.0.0 (for HDF5 file support in CLI)\n\n## License\n\nMIT License - see LICENSE file for details.\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## Acknowledgments\n\nBuilt with [PyQtGraph](https://www.pyqtgraph.org/) for high-performance visualization.\n\n\n---\nHenric Ryd\u00e9n\n\nKarolinska University Hospital\n\nStockholm, Sweden\n",
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