universal¶

data_base.analyze.temporal_binning.universal(*args, **kwargs)¶

Bin spike times for dask or pandas dataframes.

Infers the dataframe type and calls the appropriate binning function.

Parameters:¶

ddf : df |

DataFrame with containing time values in columns whose name are integer-convertible.

bin_size : float, optional

Size of the bins. If not specified, bin_borders have to be specified.

min_time : float, optional

Minimum time to consider. If not specified, the minimum value in the DataFrame is used.

max_time : float, optional

Maximum time to consider. If not specified, the maximum value in the DataFrame is used.

normalize : bool, optional

If True, normalize the output to the total number of elements in the DataFrame.

rate : bool, optional

If True, normalize the output to the bin size. Only valid if df is a pandas DataFrame.

client : dask.distributed.Client

Dask client to use for parallel computation. Only valid if ddf is a dask DataFrame.

See also

temporal_binning_pd() and temporal_binning_dask()

Returns:¶

Bin borders and bin frequencies.

Return type:¶

tuple