, pc_coeff1, pc_coeff2, pc_coeff3, pc_coeff4, pc_coeff5, luminosity_distance, **kwargs)[source]

Signal model based on a five-component principal component decomposition of a model.

While this was initially intended for modelling supernova signal, it is applicable to any situation using such a principal component decomposition.

\[h_{A} = \frac{10^{-22}}{d_{L}} \sum_{i=1}^{5} c_{i} h_{i}\]
frequency_array: UNUSED
pc_coeff1: float

The first principal component coefficient.

pc_coeff2: float

The second principal component coefficient.

pc_coeff3: float

The third principal component coefficient.

pc_coeff4: float

The fourth principal component coefficient.

pc_coeff5: float

The fifth principal component coefficient.

luminosity_distance: float

The distance to the source, the amplitude is scaled such that the amplitude at 10 kpc is 1e-23.

kwargs: dict

Dictionary containing numpy arrays with the real and imaginary components of the principal component decomposition.


The plus and cross polarizations of the signal