Command Line Interface (CLI)

General structure

The models are objects, each with a set of properties and generic functions. Before interacting with a model, it must first be instantiated, e.g.

model=charmed

General commands

• qMRInfo(model) : Print the help for the ‘model’ object
• qMRusage(model) : Print the methods of ‘model’ and examples of how to interact with them
• qMRgenBatch(model) : Generate a batch example script for ‘model’ (will automatically download test data)

Model structure

All models have the following properties:

• MRIinputs : Names of input data
• voxelwise : Whether the fit is voxelwise [1] or a matrix operation [0]
• xnames : Names of output data
• Prot : structure containing the protocol parameters
• buttons :
• Options : options specific to the model (e.g. linear or non-linear fir for VFA-T1)

And functions:

• equation:

  Compute MR signal
  USAGE:
    Smodel = Model.equation(x)
  INPUT:
    x: [struct] OR [vector] containing Model output parameters
  

• fit:

  Fit experimental data
  USAGE:
    FitResults = Model.fit(data)
  INPUT:
    data: [struct] containing input data IN ORDER as in MRinuts
  NOTE: data are 1D. For 4D datasets use FitData(data,Model)
  

• plotModel:

  Plot model equation (and fitting)
  USAGE:
         Model.plotModel(obj, x)
         Model.plotModel(obj, x, data)
  INPUT:
    x: [struct] OR [vector] containing Model output parameters
    data: [struct] containing input data in ORDER as in MRinuts
  

Most models have these additional functions:

• Sim_Sensitivity_Analysis:

  Simulates sensitivity to fitted parameters:
     (1) vary fitting parameters from lower (lb) to upper (ub) bound in 10 steps
     (2) run Sim_Single_Voxel_Curve Nofruns times
     (3) Compute mean and std across runs
  USAGE:
    SimVaryResults = Model.Sim_Sensitivity_Analysis(OptTable, Opt);
  INPUT:
    OptTable: [struct] nominal value and range for each parameter.
       st: [vector] nominal values for output parameters
       fx: [binary vector] do not vary this parameter?
       lb: [vector] vary from lb...
       ub: [vector] up to ub
    Opt: [struct] Options of the simulation
  

• Sim_Single_Voxel_Curve:

  Simulates Single Voxel curves:
     (1) use equation to generate synthetic MRI data
     (2) add rician noise
     (3) fit and plot curve
  USAGE:
    FitResults = Model.Sim_Single_Voxel_Curve(x)
    FitResults = Model.Sim_Single_Voxel_Curve(x, Opt,display)
  INPUT:
    x: [struct] OR [vector] containing fit results
    display: [binary] 1=display, 0=nodisplay
  

Please type the following to see the specific usage of the model you are interested in

qMRusage(model)

Or the batch example associated with your model located here Methods available