Handling Data in Syncopy

Syncopy utilizes a simple data format based on HDF5 and JSON (see Reading and Writing Data for details). These formats were chosen for their ubiquity as they can be handled well in virtually all popular programming languages, and for allowing streaming, parallel access enabling computing on parallel architectures.

Currently, data in other formats (e.g. from a recording system) have to be converted before use with Syncopy. For this purpose, later versions of Syncopy will include importing and exporting engines, for example based on Neo or NWB.

Loading and Saving Syncopy (*.spy) Data

Reading and writing data with Syncopy

syncopy.load(filename[, tag, dataclass, …])

Load Syncopy data object(s) from disk

syncopy.save(out[, container, tag, …])

Save Syncopy data object to disk

Functions for Editing Syncopy Data Objects

Defining trials, data selection and padding.

syncopy.definetrial(obj[, trialdefinition, …])

(Re-)define trials of a Syncopy data object

syncopy.selectdata(data[, trials, channels, …])

Create a new Syncopy object from a selection

syncopy.padding(data, padtype[, pad, …])

Perform data padding on Syncopy object or numpy.ndarray