An Origin that obtains output from an underlying Probeable object.
As an example of use, suppose a Neuron has a SynapticIntegrator with a complex dendritic morphology, and that it is desired to model a gap junction between one of these dendrites and a dendrite on another Neuron. If the SynapticIntegrator can provide gap-junctional Origins, there is no problem. But it might not (for example the implementor of the SynapticIntegrator may not have anticipated this usage). However, if the SynapticIntegrator is Probeable and can be probed for the appropriate state variables, eg ion concentrations in the compartment of interest, then this class (ProbeableOrigin) provides a convenient way to model an Origin that outputs the probed information.
For a Neuron, if multi-dimensional state is to be output, it is generally better to create multiple one-dimensional Outputs than to creat one multi-dimensional Output. Reasons for this include the following:
For these reasons, this class supports only 1-dimensional Output, as a way to keep you out of trouble. This limits its usefulness with Probeables that are Ensembles, but such Probeables probably already provide the needed Outputs anyway.
If you really do want a Neuron to serve as a multi-dimensional Origin, you can do that, but not with this class.
@author Bryan Tripp
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