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  • Customize your Processing Pipeline
  • Heart Rate Varability (HRV)
  • Extract and Visualize Individual Heartbeats
  • Locate P, Q, S and T waves in ECG
  • ECG-Derived Respiration (EDR)
  • Generating Abnormal 12-leads ECG
  • Analyze Electrodermal Activity (EDA)
  • Respiratory Rate Variability (RRV)
  • Analyze Electrooculography (EOG)
  • Simulate Artificial Physiological Signals
  • Save Preprocessing Reports
  • EEG Power in Frequency Bands
  • EEG Complexity Analysis
  • EEG Microstates
  • Fit a function to a non-linear pattern
  • Create epochs
  • Functions
    • Video Analysis
    • Microstates
    • Signal
    • Events
    • Epochs
    • Complexity
    • Markov Chains
    • Stats
    • Benchmarking
    • Resources
      • Learn Python in 10 minutes
      • Contributing guide
      • Recording good quality signals
      • Additional Resources
      • Studies
        • HRV Review
        • HRV Indices
        • HRV Tutorial
        • Complexity Review
        • Complexity Indices
        • EEG Complexity: Parameters Selection
        • EEG Analysis with GAMs
        • ECG Benchmark
        • EOG blink template
        • Repository
        • You don’t have Python #

          You are new to all this, and you’re not even sure if you have Python installed? Don’t worry, we’ll walk you through all of it.

          Python + VS code #

          You will need two things to program in Python, Python itself and an IDE software to edit and work with the Python scripts.

        • You can download Python from https://www.python.org/downloads/

        • For the IDE, we will go with VS Code

        • Once VS Code is launched, the next step is to add functionalities to support your development workflow. In particular, it is critical to get the Python Interactive extension

        • To start running some code, click New File and Ctrl+S to save the file into whichever directory in your computer you want, naming the file with a .py extension. Press Shift+Enter to send each line of code to an interactive window

        • Winpython #

          Another, perhaps easier option is to download a full distribution. The advantage of Winpython is its portability (i.e., works out of a folder) and default setup (convenient for science). However, it only exists for Windows .

        • Download a non-zero version of Winpython

        • Install it somewhere (the desktop is a good place). It creates a folder called WPyXX-xxxx

        • In the WPyXX-xxxx folder, open WinPython Command Prompt.exe

        • Now you can proceed to running the PIP command mentioned at the top

        • Miniconda or Anaconda #

          The difference between the two is straightforward, miniconda is recommended if you don’t have much storage space and you know what you want to install. Similar to Winpython, Anaconda comes with a base environment, meaning you have basic packages pre-installed. Here is some more information to help you choose between miniconda and Anaconda .

        • Download and install Miniconda or Anaconda (make sure the Anaconda3 directory is similar to this: C:\Users\<username>\anaconda3\ )

        • Open the Anaconda Prompt (search for it on your computer; see here for Mac users)

        • Run conda help to see your options

        • There should be a name in parentheses before your user’s directory, e.g. (base) C:\Users\<yourusername> . That is the name of your computing environment. By default, you have a base environment . We don’t want that, so create an environment.

        • Run conda env create <yourenvname> ; activate it every time you open conda by running conda activate <yourenvname>

        • Now you can proceed to the next step.

        • From conda #

          If you have Python installed as part of Miniconda or Anaconda , please follow these steps:

        • As described in above, open the Anaconda Prompt and activate your conda environment

        • You can now install NeuroKit2 from conda-forge by typing

        • conda config --add channels conda-forge
          conda install neurokit2
          

          conda or pip are the preferred methods to install NeuroKit2, as they will install the most up-to-date stable release.

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