Activities

When dealing with complex biological systems, and biomedical research, it is common that you have complex inputs to the system. This might include e.g. stepwise increases of a dosing, or using multiple doses at multiple time points. Traditionally, you would have to run multiple short simulations, manually setting the values of these inputs at all of the timepoints where the inputs change. This is still possible with this toolbox, but a better way is to define these inputs using an activity object.

In short, the models can have predefined inputs by specifying this in the INPUTS header.

For example, if the model have two inputs ins and epi that vary over time, we can specify this in the INPUTS header:

########## INPUTS
ins = ins
epi = epi

It is also possible to rename the inputs, if the thing providing the input uses a different name:

########## INPUTS
ins = ins_plasma
epi = epi_plasma

Now, these inputs can come from the outputs of another model, or from an activity. The activity object can provide outputs using different types (such as piecewise constant, piecewise linear, cubic spline etc).

Lets assume that our system have two piecewise constant inputs, starting at 0, and switching to different values at given times. Also, lets assume that our activity is defined in minutes ('m'):

input_activity = sund.Activity(time_unit = 'm')
input_activity.add_output(sund.PIECEWISE_CONSTANT, 'epi', t=[10,15,70,75], f=[0,10,0,20,0])
input_activity.add_output(sund.PIECEWISE_CONSTANT, 'ins', t=[30], f=[0, 15])

Then it is possible to construct a simulation which uses this activity to provide inputs to the model:

model = sund.load_model('model_example')
simulation = sund.Simulation(time_unit='m', models=[model], activities=[input_activity])

Now, the simulation will automatically map the outputs from the activity object to the inputs that the model needs.