Metadata-Version: 2.1
Name: neurokit2
Version: 0.0.18
Summary: The Python Toolbox for Neurophysiological Signal Processing.
Home-page: https://github.com/neuropsychology/NeuroKit
Author: Dominique Makowski
Author-email: dom.makowski@gmail.com
License: MIT license
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        **The Python Toolbox for Neurophysiological Signal Processing (EDA, ECG, PPG, EMG, EEG...)**
        
        This package is the continuation of `NeuroKit1 <https://github.com/neuropsychology/NeuroKit.py>`_. It's a user-friendly package with which you can analyze your physiological data with only two lines of code.
        
        ..
            Quick Example
            =============
        
            .. code-block:: python
        
                # Load packages
                import neurokit2 as nk  
                import pandas as pd
                
                # Download an example dataset
                data = pd.read_csv("https://raw.githubusercontent.com/neuropsychology/NeuroKit/master/data/bio_resting_5min_100hz.csv")
                
                # Preprocess the data (clean signals, filter, etc.)
                processed_data, info = nk.bio_process(ecg=data["ECG"], rsp=data["RSP"], eda=data["EDA"], sampling_rate=100)
                
                # Compute relevant features
                results = nk.bio_analyze(processed_data, sampling_rate=100)  
        
        
        Installation
        ============
        
        To install NeuroKit2, run this command in your terminal:
        
        .. code-block::
        
            pip install https://github.com/neuropsychology/neurokit/zipball/master
        
        Contribution
        ============
        
        NeuroKit2 is a collaborative project with a community of contributors with all levels of development expertise. Thus, if you have some ideas for **improvement**, **new features**, or just want to **learn Python** and do something useful at the same time, do not hesitate and check out the `CONTRIBUTION <https://neurokit2.readthedocs.io/en/latest/contributing.html>`_ guide.
        
        
        Documentation
        =============
        
        .. image:: https://readthedocs.org/projects/neurokit2/badge/?version=latest
                :target: https://neurokit2.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
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                :alt: API
                
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                :target: https://neurokit2.readthedocs.io/en/latest/tutorials/index.html
                :alt: Tutorials
                
        .. image:: https://mybinder.org/badge_logo.svg
                :target: https://mybinder.org/v2/gh/sangfrois/NeuroKit/dev?urlpath=lab%2Ftree%2Fdocs%2Fexamples
                
                
        Click on the links above and check out our tutorials:
        
        Tutorials
        ---------
        
        -  `Install Python and NeuroKit <https://neurokit2.readthedocs.io/en/latest/installation.html>`_
        -  `How to contribute <https://neurokit2.readthedocs.io/en/latest/contributing.html>`_
        -  `Understanding NeuroKit <https://neurokit2.readthedocs.io/en/latest/tutorials/understanding.html>`_
        -  `Included datasets <https://neurokit2.readthedocs.io/en/latest/datasets.html>`_
        
        Examples
        --------
        
        -  `Simulate Artificial Physiological Signals <https://neurokit2.readthedocs.io/en/latest/examples/simulation.html>`_
        -  `Customize your Processing Pipeline <https://neurokit2.readthedocs.io/en/latest/examples/custom.html>`_
        -  `Event-related Analysis <https://neurokit2.readthedocs.io/en/latest/examples/eventrelated.html>`_
        -  `Analyze Electrodermal Activity (EDA) <https://neurokit2.readthedocs.io/en/latest/examples/eda.html>`_
        -  `Analyze Respiratory Rate Variability (RRV) <https://neurokit2.readthedocs.io/en/latest/examples/rrv.html>`_
        -  `Extract and Visualize Individual Heartbeats <https://neurokit2.readthedocs.io/en/latest/examples/heartbeats.html>`_
        -  `Delineate QRS peaks, onsets and offsets <https://neurokit2.readthedocs.io/en/latest/examples/ecg_delineation.html>`_
        
        
        *You can try out these examples directly in your browser by* `clicking here <https://github.com/neuropsychology/NeuroKit/tree/master/docs/examples#cloud-based-interactive-examples>`_.
        
        **Don't know which tutorial is suited for your case?** Follow this flowchart:
        
        
        .. image:: https://raw.github.com/neuropsychology/NeuroKit/master/docs/img/workflow.png
                :target: https://neurokit2.readthedocs.io/en/latest/?badge=latest
                
        Citation
        =========
        
        .. image:: https://zenodo.org/badge/218212111.svg
           :target: https://zenodo.org/badge/latestdoi/218212111
        
        .. image:: https://img.shields.io/badge/details-authors-purple.svg?colorB=9C27B0
           :target: https://neurokit2.readthedocs.io/en/latest/credits.html
           
        
        You can run:
        
        .. code-block:: python
        
            nk.cite()
        
        
        .. code-block:: tex
        
            You can cite NeuroKit2 as follows:
        
            - Makowski, D., Pham, T., Lau, Z. J., Brammer, J. C., Pham, H., Lesspinasse, F., 
              SchÃ¶lzel, C., & S H Chen, A. (2020). NeuroKit2: A Python Toolbox for Neurophysiological 
              Signal Processing. Retrieved March 28, 2020, from https://github.com/neuropsychology/NeuroKit
        
            Full bibtex reference:
        
            @misc{neurokit2,
              doi = {10.5281/ZENODO.3597887},
              url = {https://github.com/neuropsychology/NeuroKit},
              author = {Makowski, Dominique and Pham, Tam and Lau, Zen J. and Brammer, Jan C. and Pham, Hung and Lespinasse, Fran\c{c}ois and SchÃ¶lzel, Christopher and S H Chen, Annabel},
              title = {NeuroKit2: A Python Toolbox for Neurophysiological Signal Processing},
              publisher = {Zenodo},
              year = {2020},
            }
        
        ..
            Design
            =======
        
            *NeuroKit2* is designed to provide a **consistent**, **accessible** yet **powerful** and **flexible** API. 
        
            - **Consistency**: For each type of signals (ECG, RSP, EDA, EMG...), the same function names are called (in the form :code:`signaltype_functiongoal()`) to achieve equivalent goals, such as :code:`*_clean()`, :code:`*_findpeaks()`, :code:`*_process()`, :code:`*_plot()` (replace the star with the signal type, e.g., :code:`ecg_clean()`).
            - **Accessibility**: Using NeuroKit2 is made very easy for beginners through the existence of powerful high-level "master" functions, such as :code:`*_process()`, that performs cleaning, preprocessing and processing with sensible defaults.
            - **Flexibility**: However, advanced users can very easily build their own custom analysis pipeline by using the mid-level functions (such as :code:`*_clean()`, :code:`*_rate()`), offering more control and flexibility over their parameters.
        
        
        Overview
        ========
        
        Simulate physiological signals
        ------------------------------
        
        .. code-block:: python
        
            import numpy as np
            import pandas as pd
            import neurokit2 as nk
        
            # Generate synthetic signals
            ecg = nk.ecg_simulate(duration=10, heart_rate=70)
            ppg = nk.ppg_simulate(duration=10, heart_rate=70)
            rsp = nk.rsp_simulate(duration=10, respiratory_rate=15)
            eda = nk.eda_simulate(duration=10, scr_number=3)
            emg = nk.emg_simulate(duration=10, burst_number=2)
        
            # Visualise biosignals
            data = pd.DataFrame({"ECG": ecg,
                                 "PPG": ppg,
                                 "RSP": rsp,
                                 "EDA": eda,
                                 "EMG": emg})
            nk.signal_plot(data, subplots=True)
        
        
        .. image:: https://raw.github.com/neuropsychology/NeuroKit/master/docs/img/README_simulation.png
        
        
        Electrodermal Activity (EDA)
        -----------------------------
        
        .. code-block:: python
        
            # Generate 10 seconds of EDA signal (recorded at 250 samples / second) with 2 SCR peaks
            eda = nk.eda_simulate(duration=10, sampling_rate=250, scr_number=2 drift=0.01)
        
            # Process it
            signals, info = nk.eda_process(eda, sampling_rate=250)
        
            # Visualise the processing
            nk.eda_plot(signals, sampling_rate=250)
        
        .. image:: https://raw.github.com/neuropsychology/NeuroKit/master/docs/img/README_eda.png
        
        
        Cardiac activity (ECG)
        -----------------------
        
        .. code-block:: python
        
            # Generate 15 seconds of ECG signal (recorded at 250 samples / second)
            ecg = nk.ecg_simulate(duration=15, sampling_rate=250, heart_rate=70)
        
            # Process it
            signals, info = nk.ecg_process(ecg, sampling_rate=250)
        
            # Visualise the processing
            nk.ecg_plot(signals, sampling_rate=250)
        
        
        .. image:: https://raw.github.com/neuropsychology/NeuroKit/master/docs/img/README_ecg.png
        
        
        Respiration (RSP)
        ------------------
        
        .. code-block:: python
        
            # Generate one minute of respiratory (RSP) signal (recorded at 250 samples / second)
            rsp = nk.rsp_simulate(duration=60, sampling_rate=250, respiratory_rate=15)
        
            # Process it
            signals, info = nk.rsp_process(rsp, sampling_rate=250)
        
            # Visualise the processing
            nk.rsp_plot(signals, sampling_rate=250)
        
        
        .. image:: https://raw.github.com/neuropsychology/NeuroKit/master/docs/img/README_rsp.png
        
        
        Electromyography (EMG)
        -----------------------
        
        .. code-block:: python
        
            # Generate 10 seconds of EMG signal (recorded at 250 samples / second)
            emg = nk.emg_simulate(duration=10, sampling_rate=250, burst_number=3)
        
            # Process it
            signals = nk.emg_process(emg, sampling_rate=250)
        
            # Visualise the processing
            nk.emg_plot(signals, sampling_rate=250)
        
        
        .. image:: https://raw.github.com/neuropsychology/NeuroKit/master/docs/img/README_emg.png
        
        Photoplethysmography (PPG/BVP)
        -------------------------------
        
        .. code-block:: python
        
            # Generate 15 seconds of PPG signal (recorded at 250 samples / second)
            ppg = nk.ppg_simulate(duration=15, sampling_rate=250, heart_rate=70)
        
        
        
        Electrogastrography (EGG)
        --------------------------
        
        Consider `helping us develop it <https://neurokit2.readthedocs.io/en/latest/contributing.html>`_!
        
        
        
        Alternatives
        ============
        
        Here's a list of great alternative packages that you should check out:
        
        
        General
        --------
        
        - `BioSPPy <https://github.com/PIA-Group/BioSPPy>`_
        - `PySiology <https://github.com/Gabrock94/Pysiology>`_
        - `PsPM <https://github.com/bachlab/PsPM>`_
        - `pyphysio <https://github.com/MPBA/pyphysio>`_
        
        
        ECG
        ----
        
        - `biopeaks <https://github.com/JohnDoenut/biopeaks>`_
        - `hrv <https://github.com/rhenanbartels/hrv>`_
        - `hrv-analysis <https://github.com/Aura-healthcare/hrvanalysis>`_
        - `py-ecg-detectors <https://github.com/berndporr/py-ecg-detectors>`_
        - `HeartPy <https://github.com/paulvangentcom/heartrate_analysis_python>`_
        - `ECG_analysis <https://github.com/marianpetruk/ECG_analysis>`_
        - `pyedr <https://github.com/jusjusjus/pyedr>`_
        - `Systole <https://github.com/embodied-computation-group/systole>`_
        
        EDA
        ---
        
        - `eda-explorer <https://github.com/MITMediaLabAffectiveComputing/eda-explorer>`_
        - `cvxEDA <https://github.com/lciti/cvxEDA>`_
        - `Pypsy <https://github.com/brennon/Pypsy>`_
        - `BreatheEasyEDA <https://github.com/johnksander/BreatheEasyEDA>`_ *(matlab)*
        - `EDA <https://github.com/mateusjoffily/EDA>`_ *(matlab)*
        
        EEG
        ----
        
        - `MNE <https://github.com/mne-tools/mne-python>`_
        - `unfold <https://github.com/unfoldtoolbox/unfold>`_ *(matlab)*
          
          
        Eye-Tracking
        -------------
        
        - `PyGaze <https://github.com/esdalmaijer/PyGaze>`_
        - `PyTrack <https://github.com/titoghose/PyTrack>`_
        
        
        News
        =====
        
        
        0.0.1 (2019-10-29)
        -------------------
        
        * First release on PyPI.
        
Keywords: neurokit2
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/x-rst
