TDT offers cross-platform data import tools to help customers with data analysis and collection using Matlab or Python.
As you navigate through the Matlab/Python data import tools, check out some of the examples we have posted. These examples include short and instructive workbooks that contain complete analysis code and associated plots generated from example data.
Read previously recorded data directly into Matlab or Python.
Importing data is easy, just follow these three steps to get started. Extract the zip files into the same folder on your machine.
1. Download the Matlab Tools
2. Add the path to the unzipped tools
>> SDKPATH = ‘path/to/sdk’;
>> addpath(genpath(SDKPATH));
3. Importing data is easy
>> data = TDTbin2mat(‘path/to/block’);
1. Install the TDT Python package from pypi. From the command line, type pip install tdt
2. In Python, you can download the example data with this:
>> import tdt
>> tdt.download_demo_data()
3. Importing data is easy:
>> data = tdt.read_block(‘path/to/block’)
Check out these live interactive notebooks:
00. Introduction to the TDT Python Package
01. Stream Plot example
02. Averaging Example
03. Raster PSTH Example
Or run them on your machine from the Jupyter notebook source code from GitHub.
Interact with Synapse and TDT hardware during a recording with the cross-platform API.
1. Download the Matlab Tools
2. Add the path to the unzipped tools
>> SDKPATH = ‘path/to/sdk’;
>> addpath(genpath(SDKPATH));
3. Connecting to Synapse is easy
>> syn = SynapseAPI();
1. Install the TDT Python package from pypi. From the command line, type
pip install tdt
2. In Python, connect to Synapse with this:
>> import tdt
>> syn = tdt.SynapseAPI()
The Matlab SDK includes the SynapseLive class for reading data as it is acquired. This is a Windows-only solution.