Merge pull request #9 from embodied-computation-group/dev

Push v0.1.3 from dev branch

.flake8

@@ -0,0 +1,5 @@
+[flake8]
+max-line-length = 88
+extend-ignore = E203, E722, E501
+exclude =
+    __init__.py

.gitignore

@@ -0,0 +1,3 @@
+*.pyc
+*-checkpoint.ipynb
+mypyreports/

.isort.cfg

@@ -0,0 +1,8 @@
+[settings]
+known_third_party = ecgdetectors,matplotlib,numpy,pandas,plotly,psychopy,pytest,requests,scipy,seaborn,serial,sphinx_bootstrap_theme,tqdm
+multi_line_output = 3
+include_trailing_comma = True
+force_grid_wrap = 0
+use_parentheses = True
+ensure_newline_before_comments = True
+line_length = 88

.pre-commit-config.yaml

@@ -0,0 +1,23 @@
+repos:
+-   repo: https://github.com/pre-commit/mirrors-isort
+    rev: v4.3.21
+    hooks:
+    - id: isort
+      files: ^systole/
+-   repo: https://github.com/ambv/black
+    rev: stable
+    hooks:
+    - id: black
+      language_version: python3
+      files: ^systole/
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v2.3.0
+    hooks:
+    - id: flake8
+      files: ^systole/
+-   repo: https://github.com/pre-commit/mirrors-mypy
+    rev: ''  # Use the sha / tag you want to point at
+    hooks:
+    - id: mypy 
+      files: ^systole/
+      args: [--ignore-missing-imports]

.travis.yml

@@ -4,14 +4,19 @@ python:
   - "3.6"
   - "3.7"
   - "3.8"
+  - "3.9"
 
 install:
   - pip install -r requirements-test.txt
   - pip install -r requirements.txt
-  - pip install coverage pytest
+  - pip install coverage pytest black mypy flake8 isort
 
 script:
   - coverage run -m pytest
+  - black --check ./systole/
+  - isort ./systole/
+  - mypy ./systole/ --ignore-missing-imports --follow-imports=skip
+  - flake8 ./systole/
 
 after_success:
   - bash <(curl -s https://codecov.io/bash)

MANIFEST.in

@@ -2,11 +2,3 @@
 include README.rst
 include LICENSE
 include requirements.txt
-
-# Add datasets files
-include systole/datasets/ppg.npy
-include systole/datasets/rr.txt
-include systole/datasets/Task1_ECG.npy
-include systole/datasets/Task1_EDA.npy
-include systole/datasets/Task1_Respiration.npy
-include systole/datasets/Task1_Stim.npy

README.rst

@@ -14,6 +14,18 @@
 .. image:: https://codecov.io/gh/embodied-computation-group/systole/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/embodied-computation-group/systole
 
+.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
+  :target: https://github.com/psf/black
+
+.. image:: https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336
+  :target: https://pycqa.github.io/isort/
+
+.. image:: http://www.mypy-lang.org/static/mypy_badge.svg
+  :target: http://mypy-lang.org/
+
+.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white
+  :target: https://github.com/pre-commit/pre-commit
+
 ================
 
 .. figure::  https://github.com/embodied-computation-group/systole/raw/master/source/images/banner.png
@@ -38,35 +50,44 @@ Systole can be installed using pip:
 
 The following packages are required to use Systole:
 
-* Numpy (>=1.15)
-* SciPy (>=1.3.0)
-* Pandas (>=0.24)
-* Matplotlib (>=3.0.2)
-* Seaborn (>=0.9.0)
-* py-ecg-detectors (>=1.0.2)
+* `Numpy <https://numpy.org/>`_ (>=1.15)
+* `SciPy <https://www.scipy.org/>`_ (>=1.3.0)
+* `Pandas <https://pandas.pydata.org/>`_ (>=0.24)
+* `Matplotlib <https://matplotlib.org/>`_ (>=3.0.2)
+* `Seaborn <https://seaborn.pydata.org/>`_ (>=0.9.0)
+* `py-ecg-detectors <https://github.com/berndporr/py-ecg-detectors>`_ (>=1.0.2)
 
 Interactive plotting functions and reports generation will also require the following packages to be installed:
 
-* plotly (>=4.8.0)
-* plotly_express (>=0.4.1)
+* `Plotly <https://plotly.com/>`_ (>=4.8.0)
 
-For an overview of all the recording functionalities, you can refer to the following tutorials:
+Tutorial
+========
+
+For an overview of all the recording functionalities, you can refer to the following examples:
 
 * Recording
 * Artefacts detection and artefacts correction
 * Heart rate variability
 
+For an introduction to Systole and cardiac signal analysis, you can refer to the following tutorial:
+
+* Introduction to cardiac signal analysis - |Colab badge| - `Jupyter Book <https://legrandnico.github.io/Notebooks/IntroductionCardiacSignalAnalysis.html>`_ 
+
+.. |Colab badge| image:: https://colab.research.google.com/assets/colab-badge.svg
+  :target: https://colab.research.google.com/github/LegrandNico/Notebooks/blob/main/IntroductionCardiacSignalAnalysis.ipynb
+
 Recording
 =========
 
 Systole natively supports recording of physiological signals from the following setups:
 * `Nonin 3012LP Xpod USB pulse oximeter <https://www.nonin.com/products/xpod/>`_ together with the `Nonin 8000SM 'soft-clip' fingertip sensors <https://www.nonin.com/products/8000s/>`_ (USB).
-* Remote Data Access (RDA) via BrainVision Recorder together with Brain product ExG amplifier `<https://www.brainproducts.com/>`_ (Ethernet).
+* Remote Data Access (RDA) via BrainVision Recorder together with `Brain product ExG amplifier <https://www.brainproducts.com/>`_ (Ethernet).
 
 Artefact correction
 ===================
 
-Systole implements the artefact rejection method recently proposed by Lipponen & Tarvainen (2019) [#]_.
+Systole implements systolic peak detection inspired by van Gent et al. (2019) [#]_ and the artefact rejection method recently proposed by Lipponen & Tarvainen (2019) [#]_.
 
 .. code-block:: python
 
@@ -137,7 +158,7 @@ References
 
 **Peak detection (PPG signal)**
 
-.. [#] van Gent, P., Farah, H., van Nes, N., & van Arem, B. (2019). HeartPy: A novel heart rate algorithm for the analysis of noisy signals. Transportation Research Part F: Traffic Psychology and Behaviour, 66, 368–378. https://doi.org/10.1016/j.trf.2019.09.015
+.. [#] van Gent, P., Farah, H., van Nes, N., & van Arem, B. (2019). HeartPy: A novel heart rate algorithm for the analysis of noisy signals. *Transportation Research Part F: Traffic Psychology and Behaviour, 66, 368–378*. https://doi.org/10.1016/j.trf.2019.09.015
 
 **Artefact detection and correction:**
 

examples/Tutorial_recording.py

@@ -22,9 +22,13 @@
 # Recording and plotting your first time-series will only require 5 lines
 # of code:
 
+import time
+
 import serial
+
 from systole.recording import Oximeter
-ser = serial.Serial('COM4')  # Add your USB port here
+
+ser = serial.Serial("COM4")  # Add your USB port here
 
 # Open serial port, initialize and plot recording for Oximeter
 oxi = Oximeter(serial=ser).setup().read(duration=10)
@@ -56,7 +60,7 @@
 # seconds for a continuous recording). When inserted into a while loop, it can
 # record PPG signal in parallel with other commands.
 
-import time
+
 tstart = time.time()
 while time.time() - tstart < 10:
     oximeter.readInWaiting()
@@ -67,12 +71,9 @@
 # ----------------
 # Online heart beat detection, for cardiac-stimulus synchrony
 
-import serial
-import time
-from systole.recording import Oximeter
 
 # Open serial port
-ser = serial.Serial('COM4')  # Change this value according to your setup
+ser = serial.Serial("COM4")  # Change this value according to your setup
 
 # Create an Oxymeter instance and initialize recording
 oxi = Oximeter(serial=ser, sfreq=75, add_channels=4).setup()
@@ -84,4 +85,4 @@
         paquet = list(oxi.serial.read(5))
         oxi.add_paquet(paquet[2])  # Add new data point
         if oxi.peaks[-1] == 1:
-            print('Heartbeat detected')
+            print("Heartbeat detected")

examples/plot_ArtefactsCorrection.py

@@ -20,13 +20,13 @@
 # ectopic beats. This method is more relevant for HRV analyse of long recording
 # where the timing of experimental events is not important.
 
+import matplotlib.pyplot as plt
 #%%
 import numpy as np
-import matplotlib.pyplot as plt
+
 from systole import simulate_rr
-from systole.plotting import plot_subspaces
 from systole.correction import correct_peaks, correct_rr
-
+from systole.plotting import plot_subspaces
 
 #%% Method 1 - Peaks correction
 # #############################

examples/plot_ArtefactsDetection.py

@@ -12,8 +12,8 @@
 
 #%%
 from systole.detection import rr_artefacts
-from systole.utils import simulate_rr
 from systole.plotting import plot_subspaces
+from systole.utils import simulate_rr
 
 #%%
 # RR artefacts