tabular_model#

astropy.modeling.tabular.tabular_model(dim, name=None)[source]#

Make a Tabular model where n_inputs is based on the dimension of the lookup_table.

This model has to be further initialized and when evaluated returns the interpolated values.

Parameters:

dimint: Dimensions of the lookup table.
namestr: Name for the class.

Examples

>>> table = np.array([[3., 0., 0.],
...                   [0., 2., 0.],
...                   [0., 0., 0.]])

>>> tab = tabular_model(2, name='Tabular2D')
>>> print(tab)
<class 'astropy.modeling.tabular.Tabular2D'>
Name: Tabular2D
N_inputs: 2
N_outputs: 1

>>> points = ([1, 2, 3], [1, 2, 3])

Setting fill_value to None, allows extrapolation. >>> m = tab(points, lookup_table=table, name=’my_table’, … bounds_error=False, fill_value=None, method=’nearest’)

>>> xinterp = [0, 1, 1.5, 2.72, 3.14]
>>> m(xinterp, xinterp)  
array([3., 3., 3., 0., 0.])