Distribution of code implementing the Bayesian PSC detection algorithm described in Merel et al, J. Neuro. Meths., 2016.
To run an example of generating data and inference, run the script example.m.
- The input data should be saved in a .mat file. The variable should be named "traces" and stored as a K x T matrix where K is the number of traces and T is the number of samples in each trace. See example.mat.
- See the m-file get_params.m for detailed information on the parameters needed to run the algorithm.
- Unless provided, the code automatically generates a savefile name based on the values in get_params.m - namely the name of the file with the input data and a four-digit identifier. This four-digit identfier needs to be changed to run inference on the same data again. If the savefile name is already taken, the code will abort and not overwrite previous results.
- The user should always input values of time in the units of seconds. However, the code converts everything to the unit of samples before running inference. This is the most convenient arrangement because then users only need to change the value of params.dt when the data has different sampling rates.