Specific instructions on exporting data from Jdaviz to your notebook vary slightly for each instance of Jdaviz, including for :ref:`Specviz <api-import>`, :ref:`Cubeviz <api-import-cubeviz>`, :ref:`Mosviz <mosviz-import-data>`, and :ref:`Imviz <imviz-import-data>`. These instructions all provide the ability to import data with the GUI or the API via the Jupyter notebook.
If using the Jupyter notebook, users can load data into the application through code using the load_data
method, which takes as input either the name of a local file or a
:class:`~spectral_cube.SpectralCube` or :class:`~specutils.Spectrum1D` object.
For Specviz:
from jdaviz import Specviz from specutils import Spectrum1D specviz = Specviz() specviz.app spec1d = Spectrum1D.read("/path/to/data/spectrum_file.fits") specviz.load_data(spec1d)
If you need to create your own ~specutils.Spectrum1D file:
from specutils import Spectrum1D flux = np.random.randn(200) * u.Jy wavelength = np.arange(5100, 5300) * u.AA spec1d = Spectrum1D(spectral_axis=wavelength, flux=flux)
For Cubeviz:
from jdaviz import Cubeviz cubeviz = Cubeviz() cubeviz.app cubeviz.load_data("/path/to/data/cube_file.fits")
For Mosviz:
from jdaviz import Mosviz mosviz = Mosviz() mosviz.app mosviz.load_data(directory="/path/to/data", instrument="nirspec") # Or "niriss"
For Imviz:
from jdaviz import Imviz imviz = Imviz() imviz.app imviz.load_data("/path/to/data/image.fits")
Jdaviz comes with curated line lists built by the scientific community. If you cannot find the lines you need, you can add your own by constructing an :ref:`astropy table <astropy:construct_table>`; For example:
from astropy.table import QTable from astropy import units as u my_line_list = QTable() my_line_list['linename'] = ['Hbeta','Halpha'] my_line_list['rest'] = [4851.3, 6563]*u.AA my_line_list['redshift'] = u.Quantity(0.046) # Optional viz.load_line_list(my_line_list) # Show all imported line lists viz.spectral_lines