Instructions

Install code

Install with

git clone https://git0.fmf.uni-lj.si/studen/PBPK_public.git

Use GIT for Windows. More instructions on the web page.

On top of python, you'll need numpy and scipy. Install using pip

pip3 install numpy,scipy

Use windows terminal (ie. cmd.exe)

Follow cDiazepam.json. Basic instructions:

runSolver.main(setup,model,parameters,jobDir,srcDir) This constructs a model from the model file, sets it up with parameters from parameters file, uses the setup to drive calculation which it stores in jobDir. If srcDir is not a string NONE, it takes the solution from srcDir and continues it until tmax in setup is reached. setup['mode'] will select computation method. Typical value is 'IVP', which will use LSODA or a similar method, set through setup['method'] to perofrm adaptable step solution of an inital value problem. Selecting 'solveMatrix' as mode and 'solveSequential' as method will calculate solution using matrix equation, which should be faster.
runSolver.loadSolutionFromDir(jobDir,True) Read solution from dir jobDir. Returns a dict with fields t,sol,se,qt,sOut,lut,lutSE,setup,model,parameters,qt,sOut where:
- t is the sequence of time points
- sol is the list of solutions for each compartment at each time point
- se is the error
- lut is the look up table of named containers / indices pairs where index points to a list in solution, ie ['sol'][lut[containerName],j] is the concentration of containerName at time point j
- lutSE is the lookup table of parameters
- setup is the parsed setup file
- parameters are the parsed parameters
- model is the model parse model