pwAddData

 Any valid Matlab command can be saved in the MCode section in the
 second column. For PottersWheel, two kind of commands are relevant:

 1. Specification of experimental settings

    Use "MCode  drivingFunctions(1).name = 'Epo';"
    to specify that the first driving function is named 'Epo'.
    Use "MCode  drivingFunctions(1).stimuli(1)=pwGetDrivingFunction('steps',[-1 0 5],  [0 6 0]);"
    to specify that Epo is a step function with values 0, 6, and 0
    at time points -1, 0, and 5.
    A second stimulus could be defined via
    "MCode  drivingFunctions(1).stimuli(2)=pwGetDrivingFunction('steps',[-1 0],  [0 6]);"
    Compare pwAddU.

    Since PW 2.0.55 an alternative approach to specify experimental settings
    can be applied, which avoids the MCode keyword and improves readibility
    by using several spreadsheet cells.
    The above example would be written as:

     Header  Name    StimulusNr  Type   Time points  Values
     Input   Epo     1           steps  -1;0;5       0;6;0
     Input   Epo     2           steps  -1;0         0;6


    Since PW 2.1.09 a name may be specified for each stimulus:

     Header    Number  Name
     Stimulus  1       Epo-Pulse
     Stimulus  2       Epo-Continuous

    If no stimulus name is specified, PottersWheel will assign an automatic
    stimulus names. A systematic stimulus name is important to select a subset
    of stimulations when working with PottersWheel database files (PWDB, see
    pwDbCreate, pwAddDataFromDB).

 2. Specification of experiment-depending initial values for
    dynamical variables x, for dynamic parameters k,
    and for scaling parameters s.

    Use the command "MCode  x0.('A') = 0.34;" to set the initial concentration
    of species A to a value of 0.34.
    Use the command "MCode  k.('production_rate') = 0.23;" to set the
    parameter production_rate to a value of 0.23.
    The same approach can be applied to scaling parameters using e.g.
    "MCode  s.('scalingParName') = 0.1".

    If the initial value or the parameter value is not experiment-dependent,
    it is recommended to specify its value directly in the model definition file.
    Compare pwAddX and pwAddK.

    Alternatively, see pwSetFittedK, pwSetFittedS, pwSetFittedX.