def __init__(self, contribution_factor=<NUM_LIT:0.0>, noise_factor=<NUM_LIT:0.0>, noise_power=<NUM_LIT:1.0>):
self.contribution_factor = contribution_factor<EOL>self.noise_factor = noise_factor<EOL>self.noise_power = noise_power<EOL>self.component_number = next(self._ids)<EOL>
If a *Galaxy* is given a *HyperGalaxy* as an attribute, the noise-map in the regions of the image that the \
        galaxy is located will be scaled, to prevent over-fitting of the galaxy. 

        This is performed by first computing the hyper-galaxy's 'contribution-map', which determines the fraction of \
        flux in every pixel of the image that can be associated with this particular hyper-galaxy. This is computed \
        using  hyper-hyper set (e.g. fitting.fit_data.FitDataHyper), which includes  best-fit unblurred_image_1d of \
        the galaxy's light from a previous analysis phase.

        The *HyperGalaxy* class contains the hyper-parameters which are associated with this galaxy for scaling the \
        noise-map.

        Parameters
        -----------
        contribution_factor : float
            Factor that adjusts how much of the galaxy's light is attributed to the contribution map.
        noise_factor : float
            Factor by which the noise-map is increased in the regions of the galaxy's contribution map.
        noise_power : float
            The power to which the contribution map is raised when scaling the noise-map.