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 : DataBase

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.

See also

prefun(), applyfun(), and postfun() for the default functions that bin the synapse activations.

See also

init() for how to simrun-initialize a database.