data_base ❭ db_initializers ❭ synapse_activation_binning ❭ init

init¶

data_base.db_initializers.synapse_activation_binning.init(db, groupby='', scheduler=None, prefun=prefun, applyfun=applyfun, postfun=postfun, maxtime=400)¶

Main pipeline to bin synapse activations from a Synapse activation dataframe.

Parameters:¶

db (ISFDataBase) – The simrun-initialized database object. Must contain the key synapse\_activation.
groupby (str) – Aggregation key for the synapse activation bins. Available values include:
- celltype
- presynaptic\_column
- proximal (soma distance < 500 um)
- EI (Lumping the EXC / INH celltypes together)
- binned\_somadist: synapse counts for all 50 microns
- any column in the specified dataframe.
- Can be a list, if “sub-subgroups” should be calculated.
scheduler (dask scheduler) – A dask scheduler for the comptation (e.g. dask.distributed.Client.get())
prefun (callable) – A function to preprocess the synapse activation dataframe before binning. The function should take a pandas dataframe and return a pandas dataframe. Default: prefun()
applyfun (callable) – A function to bin the synapse activations. The function should take a pandas dataframe and return a numpy array. Default: applyfun()
postfun (callable) – A function to postprocess the binned synapse activations. The function should take a pandas series and return a numpy array. Default: postfun()

Returns:¶

None. The binned synapse activation data will be stored in db.