Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.
I didn't realize until #1110 that p is defined twice in the parameters object, first as a preprocess value and second as a temporal value (it takes the same default in each case). This is not the intended use of CNMFParams. Every parameter is meant to have a unique name, otherwise param.change_params() becomes ill defined.
I'm not sure what the best resolution is: either remove one of the p params, or split them into two p parameters for the two parameter dictionaries (e.g., the preprocess one is used more in the online algorithms). I haven't looked deeply enough here to have a good feel for the differences, to have an opinion of the best road forward.
As an aside, we should probably better explain the flow of p in demo_pipeline.py. There, it says we are turning off deconvolution by setting p to 0, but that line of code is actually commented out.
I didn't realize until #1110 that
pis defined twice in the parameters object, first as apreprocessvalue and second as atemporalvalue (it takes the same default in each case). This is not the intended use ofCNMFParams. Every parameter is meant to have a unique name, otherwiseparam.change_params()becomes ill defined.I'm not sure what the best resolution is: either remove one of the
pparams, or split them into twopparameters for the two parameter dictionaries (e.g., the preprocess one is used more in the online algorithms). I haven't looked deeply enough here to have a good feel for the differences, to have an opinion of the best road forward.As an aside, we should probably better explain the flow of
pindemo_pipeline.py. There, it says we are turning off deconvolution by settingpto 0, but that line of code is actually commented out.