DataHub

DataHub

Developer(s)	Christian Kothe; Chadwick Boulay.
Development status	-in development-
Written in	C, C++, Python, Java, C#, MATLAB
Operating system	Windows, Linux, MacOS, Android, iOS
Type	Data collection
License	Open source
Website	LSL webpage

Resources

DataHub

Downloads
viewer & streamer
Manuals
Documentation LSL Validation Supported Devices and Tools
Templates
example scripts (zip)

The DataHub Makes use of the lab streaming layer. The lab streaming layer (LSL) is a system for the unified collection of measurement time series in research experiments that handles both the networking, time-synchronization, (near-) real-time access as well as optionally the centralized collection, viewing and disk recording of the data.

Installation

Our support for LSL is mainly done in python. Download python here: Please choose a 64 bit version.. Run the installer and make sure to add Python to the file path (it's an option in the installer). Open a command prompt, start with upgrading the pip installer by typing:
c:>python -m pip install --upgrade pip
Then:
c:>pip install pylsl

more info: cross platform pylsl

Versions

The TSG uses the version 1.15.0. Open a command and type the following to find the version used:

c:>python
>>> import pylsl
>>> print(pylsl.__version__)

Usage

Python

Example demonstrating how to send LSL stream and marker data:

#!/usr/bin/env python3.10
# -*- coding: utf-8 -*-

import time
import numpy as np
import keyboard
import random
from pylsl import StreamInfo, StreamOutlet, local_clock
from LSLsettings import MarkerStreamSettings, DynamicMultiChannelStreamSettings

print(f"Setting up streams...")
marker_settings = MarkerStreamSettings()

# info marker StreamInfo, outlet
marker_info = StreamInfo(
    name=marker_settings.stream_name,
    type=marker_settings.stream_type,
    channel_count=marker_settings.channel_count,
    nominal_srate=marker_settings.sample_rate,
    channel_format=marker_settings.channel_format,
    source_id=marker_settings.source_id
)
marker_outlet = StreamOutlet(marker_info, chunk_size=marker_settings.push_chunk_size)

data_settings = DynamicMultiChannelStreamSettings(
    n_channels=4,
    stream_name="TestStream",
    stream_type="TestData",
    sample_rate=100,
    channel_names=["A", "B", "C", "D"]
)

# info data StreamInfo, outlet
data_info = StreamInfo(
    name=data_settings.stream_name,
    type=data_settings.stream_type,
    channel_count=data_settings.channel_count,
    nominal_srate=data_settings.sample_rate,
    channel_format=data_settings.channel_format,
    source_id=data_settings.source_id
)
data_outlet = StreamOutlet(data_info, chunk_size=data_settings.push_chunk_size)

running = True
marker_outlet.push_sample(["Start"])
buffer_dtype = object if data_settings.channel_format == "string" else float
buffer_in = np.array(data_settings.default_buffer, dtype=buffer_dtype)

print("Start streaming... Press 'q' to stop.")

while not(keyboard.is_pressed('q')):

    random_numbers = [random.randint(0, 1) for _ in range(4)]
    random_numbers = [num + 1 for num in random_numbers]
    data_outlet.push_sample(random_numbers)

    time.sleep(data_settings.push_interval)

marker_outlet.push_sample(["Stop"])

the settings.py file for LSL:

# settings.py

class BaseSettings:
    """Basisklasse met standaardinstellingen voor een LSL stream."""
    def __init__(self):
        self.stream_name = "BaseStream"
        self.stream_type = "Unknown"
        self.channel_count = 1
        self.sample_rate = 0
        self.channel_format = "float32"
        self.source_id = "BaseSource"

        self.channel_names = []
        self.push_chunk_size = 1
        self.push_interval = 0.001

        self.use_random_data = False
        self.dummy_string = "Test"
        self.random_string_options = ["A", "B", "C"]

        self.verbose = True
        self.quit_method = "psychopy"
        self.user_stop_message = "Press ENTER/RETURN to stop acquisition."

        self.default_buffer = ["Test"]

        # the scope is not implemented yet
        self.scope = "lan"

    def get_stream_options(self):
        if self.scope in ["local", "lan", "internet"]:
            return dict()
        else:
            raise ValueError(f"Unknown scope: {self.scope}")


class DynamicMultiChannelStreamSettings(BaseSettings):
    def __init__(
        self,
        n_channels=8,
        stream_name="DynamicStream",
        stream_type="EEG",
        sample_rate=256,
        channel_format="float32",
        channel_names=None
    ):
        super().__init__()
        self.stream_name = stream_name
        self.stream_type = stream_type
        self.channel_count = n_channels
        self.sample_rate = sample_rate
        self.channel_format = channel_format
        self.source_id = f"{stream_name}_Source"

        if channel_names is not None:
            if len(channel_names) != n_channels:
                raise ValueError(f"Number of channel names ({len(channel_names)}) does not match n_channels ({n_channels})")
            self.channel_names = channel_names
        else:
            self.channel_names = [f"Chan{i+1}" for i in range(n_channels)]

        self.default_buffer = [0.0 for _ in range(n_channels)]

class MarkerStreamSettings(BaseSettings):
    def __init__(self):
        super().__init__()
        self.stream_name = "MarkerStream"
        self.stream_type = "Markers"
        self.channel_count = 1
        self.sample_rate = 0  # 0 Hz = irregular sampling
        self.channel_format = "string"
        self.source_id = "MarkerSource"

        self.channel_names = []  # niet nodig voor markers
        self.default_buffer = ["TestMarker"]

Matlab

Please, read the instructions on the GitHub labstreaminglayer website (https://github.com/labstreaminglayer/liblsl-Matlab) on how to prepare Matlab to work with LSL. You can either use the latest release for your Matlab version, or if that doesn't workout well, build it from the source files. Make sure to add the liblsl-Matlab folder to your path recursively to make it available to your own scripts.

A short example for sending lsl streaming data:

%% instantiate the library
disp('Loading library...');
lib = lsl_loadlib();

% make a new stream outlet
disp('Creating a new streaminfo...');
info = lsl_streaminfo(lib,'BioSemi','EEG',8,100,'cf_float32','sdfwerr32432');

disp('Opening an outlet...');
outlet = lsl_outlet(info);

% send data into the outlet, sample by sample
disp('Now transmitting data...');
while true
    outlet.push_sample(randn(8,1));
    pause(0.01);
end

A short example for receiving lsl streaming data:

%% instantiate the library
disp('Loading the library...');
lib = lsl_loadlib();

% resolve a stream...
disp('Resolving an EEG stream...');
result = {};
while isempty(result)
    result = lsl_resolve_byprop(lib,'type','EEG'); end

% create a new inlet
disp('Opening an inlet...');
inlet = lsl_inlet(result{1});

disp('Now receiving data...');
while true
    % get data from the inlet
    [vec,ts] = inlet.pull_sample();
    % and display it
    fprintf('%.2f\t',vec);
    fprintf('%.5f\n',ts);
end