1/ CLA model is "the network", your description.py sets params for the model; 2/ OPF is framework, eg now for constructiong a model from the params and running swarming; network describes how regions are connected (CLAmodel is an example of a network) 3/ no, it says the other direction of implication: if maxSegments.. are not -1, global devay must be disabled. 4/ you'll find and issue for that: fixed 'mode': number of synapses per segment, segs per cell is given and fixed; "variable sized/growing" - these can change as needed. AFAIK not supported now.
Cheers, On Wed, May 4, 2016 at 9:27 AM, Weiru Zeng <[email protected]> wrote: > Hi everyone: > > Recently, I learned the model_params.py of the opf. The code below which > is in the TP.py confuses me: > > > # Fixed size CLA mode? > if maxSegmentsPerCell != -1 or maxSynapsesPerSegment != -1: > assert (maxSegmentsPerCell > 0 and maxSynapsesPerSegment > 0) > assert (globalDecay == 0.0) > assert (maxAge == 0) > > > The question is: > > 1. What's the CLA model? > 2. What's the relationship of the opf, clamodel and network? > 3. Dose the code above means that maxSegmentsPerCell and > maxSynapsesPerSegment must be set to -1 by default if golbalDecay is used? > On the contrary, if this two parameters great than 0, there will be no > decay to the segments of cells that did not become active. Is it right? > 4. What's the mean of the "fixed size CLA model"? > -- Marek Otahal :o)
