Getting Started

Working with the grid

After successful creation of an HDF5 Grid (please see Input/Output Documentation for details) one can load the grid using:

>>> from starkit.gridkit import load_grid
>>> grid = load_grid('mygrid.h5')
>>> grid
<SpectralGrid(teff=6200.0, logg=4.0, mh=0.5)>

The values for teff, logg and mh are the defaults for the grid, but have no other special meaning and can be changed. StarKit heavily uses astropy.modeling please refer to its reference guide.

One can then just evaluate the grid at a certain parameter point:

>>> grid.teff = 5780.
>>> grid.logg = 4.4
>>> grid.mh = 0.0
>>> wave, flux = grid()
>>> plot(wave, flux)

To change the grid parameters interactively and plot the resulting spectrum, you can use the example notebook: Plotting the spectrum interactively.

StarKit works with a so called plugin-architecture that can modify the generated spectrum. For example, one can use the doppler shift plugin:

>>> from starkit.base.operations.stellar import DopplerShift, RotationalBroadening
>>> doppler = DopplerShift(vrad=0)
>>> doppler.vrad = 20
>>> new_wave, new_flux = doppler(wave, flux)

These plugins can then be concatenated (again see reference guide):

>>> my_model = grid | doppler
>>> my_model
<CompoundModel0(teff_0=5780.0, logg_0=4.4, mh_0=0.0, vrad_1=20.0)>

You can then add further plugins to the model:

>>> from starkit.base.operations.stellar import RotationalBroadening, CCM89Extinction
>>> rotation = RotationalBroadening.from_grid(grid, vrot=200) # it is imperative to load from_grid here as it needs to
>>> extinction = CCM89Extinction(a_v=1.0, r_v=3.1)
>>> my_model = grid | rotation | doppler | extinction
>>> my_model
<CompoundModel3(teff_0=2300.0, logg_0=0.0, mh_0=0.5, alpha_0=0.0, vrot_1=200.0, limb_darkening_1=0.6, vrad_2=200.0, a_v_3=1.0, r_v_3=3.1)>
>>> my_model.param_names
(u'teff_0',
 u'logg_0',
 u'mh_0',
 u'alpha_0',
 u'vrot_1',
 u'limb_darkening_1',
 u'vrad_2',
 u'a_v_3',
 u'r_v_3')
 >>> my_model.vrot_1 = 300

There is a convenience function to assemble models:

>>> from starkit import assemble_model
>>> my_model = assemble_model(grid, vrad=20, a_v=0.3, vrot=300)
>>> my_model.__class__
<class 'starkit.base.assemble_model.CompoundModel5'>
Name: CompoundModel5
Inputs: ()
Outputs: ('wavelength', 'flux')
Fittable parameters: (u'teff_0', u'logg_0', u'mh_0', u'alpha_0', u'vrot_1', u'limb_darkening_1', u'vrad_2', u'a_v_3', u'r_v_3')
Expression: [0] | [1] | [2] | [3]
Components:
    [0]: <SpectralGrid(teff=2300.0, logg=0.0, mh=0.5, alpha=0.0)>

    [1]: <RotationalBroadening(vrot=300.0, limb_darkening=0.6)>

    [2]: <DopplerShift(vrad=20.0)>

    [3]: <CCM89Extinction(a_v=0.3, r_v=3.1)>

Working with grid and spectra

The next step is to work with grid and spectra.