Syncopy Data Basics

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.

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 Inspecting/Editing Syncopy Data Objects

Defining trials, data selection and NumPy ndarray interface

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

(Re-)define trials of a Syncopy data object

syncopy.selectdata(data[, trials, channel, ...])

Create a new Syncopy object from a selection

syncopy.show(data[, squeeze])

Show (partial) contents of Syncopy object

Plotting Functions

syncopy.singlepanelplot(data, **show_kwargs)

Plot Syncopy data in a single panel

syncopy.multipanelplot(data, **show_kwargs)

Plot Syncopy data in multiple panels

Importing Data into Syncopy

Currently, Syncopy supports importing data from FieldTrip raw data format and from NWB

syncopy.io.load_ft_raw(filename[, ...])

Imports raw time-series data from Field Trip into potentially multiple AnalogData objects, one for each structure found within the MAT-file.

syncopy.io.load_nwb(filename[, memuse])

Read contents of NWB files