Substrate

Substrate is a class that implements chemical cues at different locations. It is the only class in NeuroDevSim that can be directly initiated with syntax Substrate(name,location,creation_cycle,amount). For example:

sub = Substrate("attractor",Point(10.,10.,10.),0,1)

creates a substrate named attractor at coordinate (10.,10.,10.) which will exist from the beginning of the simulation (cycle 0) and consists of a single molecule. Such a simple substrate is sufficient for a deterministic Chemical cue using Substrate.

However, before it can be used it should be added to the simulation. This can be done in two different ways: in the main code or by a Front during its manage_front call. The first case uses Admin_agent.add_substrate as shown in the Environment notebook:

if __name__ == '__main__':
    ...
    # add substrate information, in this case a single random point
    x = 20 + 60 * np.random.random()
    y = 20 + 60 * np.random.random()
    # instantiate a substrate
    sub = Substrate("attractor",Point(x,y,99.),...)
    # add it to the simulation volume
    admin.add_substrate(sub)

Alternatively, it can be produced by a Front that uses constellation.add_substrate:

def manage_front(self,constellation):
    ...
    sub = Substrate("attractor",self.mid(),0,1)
    constellation.add_substrate(sub)

though this is not enforced, the assumption is that the substrate is produced close to the front, in this case at its center.

Either add_substrate can be called with a single Substrate or a list of Susbstrate as parameter. Multiple instantiations of Substrate with the same name at different locations can be created and added. Once registered by add_substrate, all substrate of a given name can be found with the get_substrates as described in the Chemical cue using Substrate.

In addition to the simple definitions used till now, additional parameters can be supplied which allow for stochastic use of Substrate with the diff_gradient_to method described in Chemical cue using Substrate and illustrated in Environment notebook. For this stochastic approach a diffusion constant diff_c in µm^2/cycle needs to provided:

sub = Substrate("attractor",Point(10.,10.,10.),constellation.cycle,1000000000,diff_c=30.)

This will place a point source of 1,000,000,000 molecules of attractor at the given location on the given cycle, which will then start to diffuse away. The computed gradient will evolve as the cycle parameter passed to diff_gradient_to increases.

An alternative is to use a continuously producing point source. In that case the amount is ignored and, instead, an optional rate parameter is provided:

sub = Substrate("attractor",Point(10.,10.,10.),constellation.cycle,0,rate=1000.,diff_c=30.)

For the continuously producing point source, stochastic concentratons can be queried by diff_gradient_to either some cycles after the start or using a steady state gradient, see Chemical cue using Substrate.