WISE: Wavelet Image Segmentation and Evaluation¶
The WISE package has been developed to address the issue of detecting significant features in radio interferometric images and obtaining reliable velocity field from cross-correlation of these regions in multi-epoch observations.
It comprises three main constituents:
- Detection of structural information is performed using the segmented wavelet decomposition (SWD) method. The SWD algorithm provides a structural representation of astronomical images with exceptional sensitivity for identifying compact and marginally resolved features as well as large scale structural patterns. It delivers a set of two-dimensional significant structural patterns (SSP), which are identified at each scale of the wavelet decomposition.
- Tracking of these SSP detected in multiple-epoch images is performed with a multiscale cross-correlation (MCC) algorithm. It combines structural information on different scales of the wavelet decomposition and provides a robust and reliable cross-identification of related SSP.
- A stacked cross correlation (SCC) is introduced to recover multiple velocity components from partially overlapping emitting regions.
This software is based on a method introduced and described in:
Installation¶
The WISE package can be installed using the conda package management system. You can install conda easily by downloading the installer corresponding to your OS and for Python 2.7 at:
http://conda.pydata.org/miniconda.html
and following the installation instruction at:
http://conda.pydata.org/docs/install/quick.html
Once done, you can install WISE in just one command line:
conda install -c flomertens -c conda-forge wise cython dask
It is also possible to install WISE using pip:
pip install wisetool
Alternative manual installation:¶
Latest version of WISE and libwise package can be download at:
https://github.com/flomertens/libwise/releases/
https://github.com/flomertens/wise/releases/
Each package can be installed with the command line:
python setup.py install
Requirements:
- numpy (>= 1.5)
- scipy (>= 0.10)
- skimage (>= 0.5)
- astropy (>= 0.4)
- matplotlib (>= 1.0)
- pyqt (>= 4.8)
- pandas
- pyregion (https://pypi.python.org/pypi/pyregion)
- uncertainties (https://pypi.python.org/pypi/uncertainties)
- pymorph (https://pypi.python.org/pypi/pymorph)
Using WISE¶
WISE can be used either from the command line or from an ipython notebook. Check the tutorials below to see how to use it.