def __init__(self, lens_data, tracer_normal, tracer_sensitive):
AbstractSensitivityFit.__init__(self=self, tracer_normal=tracer_normal, tracer_sensitive=tracer_sensitive)<EOL>self.fit_normal = lens_fit.LensProfileFit(lens_data=lens_data, tracer=tracer_normal)<EOL>self.fit_sensitive = lens_fit.LensProfileFit(lens_data=lens_data, tracer=tracer_sensitive)<EOL>
Evaluate the sensitivity of a profile fit to a specific component of a lens model and tracer. This is \
        performed by evaluating the likelihood of a fit to an image using two tracers:

        1) A 'normal tracer', which uses the same lens model as a the simulated lens data. This gives a baseline \
           value of the likelihood we can expect when we fit the model to itself.

        2) A 'sensitive tracer', which uses the same lens model as the simulated lens data, but also includes the \
           additional model components (e.g. a mass clump 'subhalo') which we are testing our sensitivity to.

        The difference in likelihood of these two fits informs us of how sensitive we are to the component in the \
        second tracer. For example, if the difference in likelihood is neglible, it means the model component had no \
        impact on our fit, meaning we are not sensitive to its properties.

        Parameters
        ----------
        lens_data: lens_data.LensData
            A simulated lens data which is used to determine our sensitiivity to specific model components.
        tracer_normal : ray_tracing.AbstractTracer
            A tracer whose galaxies have the same model components (e.g. light profiles, mass profiles) as the \
            lens data that we are fitting.
       tracer_sensitive : ray_tracing.AbstractTracerNonStack
            A tracer whose galaxies have the same model components (e.g. light profiles, mass profiles) as the \
            lens data that we are fitting, but also addition components (e.g. mass clumps) which we measure \
            how sensitive we are too.