Merge pull request #749 from neuropsychology/dev

0.2.3

.github/workflows/checks.yml

@@ -12,7 +12,7 @@ jobs:
             - name: Set up Python ${{ matrix.python-version }}
               uses: actions/setup-python@v4
               with:
-                  python-version: "3.8"
+                  python-version: "3.10"
 
             - name: Install dependencies
               run: |

.github/workflows/style.yml

@@ -12,18 +12,16 @@ jobs:
         runs-on: ubuntu-latest
 
         steps:
-            - uses: actions/checkout@master
+            - uses: actions/checkout@v3
 
             - name: Set up Python
               uses: actions/setup-python@v4
               with:
-                  python-version: "3.x"
+                  python-version: "3.10"
 
             - name: Install dependencies
               run: |
                   python -m pip install --upgrade setuptools pip wheel
-                  python -m pip install tox-gh-actions
-                  tox
 
             - name: Fix code style with isort (import calls)
               run: |
@@ -36,17 +34,17 @@ jobs:
                   # The GitHub editor is 127 chars wide. See https://black.readthedocs.io/en/stable/installation_and_usage.html
                   black neurokit2 --line-length 120 .
 
-            - name: Fix code style with docformatter (docstrings)
-              run: |
-                  pip install docformatter
-                  # See https://github.com/myint/docformatter
-                  docformatter neurokit2 --wrap-summaries 120 --wrap-descriptions 113 --blank --make-summary-multi-line --recursive
+            # - name: Fix code style with docformatter (docstrings)
+            #   run: |
+            #       pip install docformatter
+            #       # See https://github.com/myint/docformatter
+            #       docformatter neurokit2 --wrap-summaries 120 --wrap-descriptions 113 --blank --make-summary-multi-line --recursive
 
             - name: Detect remaining style errors with flake8
               run: |
                   pip install flake8
                   # The GitHub editor is 127 chars wide. See https://flake8.pycqa.org/en/latest/user/configuration.html
-                  flake8 neurokit2 --exclude neurokit2/__init__.py --max-line-length=127 --max-complexity=10 --ignore E303,C901,E203,W503
+                  flake8 neurokit2 --exclude neurokit2/__init__.py --max-line-length=127 --max-complexity=10 --ignore E303,C901,E203,W503,E712
 
             - name: Detect remaining style errors with Pylint (fail under)
               run: |

docs/conf.py

@@ -35,7 +35,7 @@ def find_author():
 
 project = "NeuroKit2"
 copyright = f"2020–{datetime.datetime.now().year}"
-author = '<a href="https://dominiquemakowski.github.io/">Dominique Makowski</a> and the <a href="https://github.com/neuropsychology/NeuroKit/blob/master/AUTHORS.rst">Team</a>'
+author = '<a href="https://dominiquemakowski.github.io/">Dominique Makowski</a> and the <a href="https://github.com/neuropsychology/NeuroKit/blob/master/AUTHORS.rst">Team</a>. This documentation is licensed under a <a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a> license.'
 
 # The short X.Y version.
 def find_version():

docs/examples/eeg_power/eeg_power.ipynb

@@ -49,7 +49,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# EEG Frequency Bands\n",
+    "## EEG Frequency Bands\n",
     "\n",
     "From fastest to slowest:\n",
     "\n",
@@ -71,7 +71,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Preprocessing"
+    "## Preprocessing"
    ]
   },
   {
@@ -160,7 +160,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Frontal Alpha Asymmetry (FAA)"
+    "## Frontal Alpha Asymmetry (FAA)"
    ]
   },
   {
@@ -454,7 +454,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Frontal Midline Theta (FMT)\n",
+    "## Frontal Midline Theta (FMT)\n",
     "\n",
     "\n",
     "\n"

docs/examples/index.rst

@@ -20,6 +20,7 @@ Physiological
    rsp_rrv/rsp_rrv
    eog_analyze/eog_analyze
    signal_simulation/signal_simulation
+   ppg_report/ppg_report
 
 EEG
 =============

docs/examples/ppg_report/ppg_report.ipynb

@@ -0,0 +1,130 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Save Preprocessing Reports"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This example can be referenced by [citing the package](https://neuropsychology.github.io/NeuroKit/cite_us.html).\n",
+    "\n",
+    "Reports are currently a **beta** feature (help us improve it!) only available for PPG signals. \n",
+    "\n",
+    "You can generate a report via the `report` argument in the processing function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "remove-input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# Note: this cell is hidden using the \"remove-input\" tag\n",
+    "import matplotlib.pyplot as plt\n",
+    "# Make bigger images\n",
+    "plt.rcParams['figure.figsize'] = [15, 5]  \n",
+    "plt.rcParams['font.size']= 14"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "skip-execution"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# import neurokit2 as nk\n",
+    "\n",
+    "# Simulate PPG signal\n",
+    "# signal = nk.ppg_simulate(duration=30, sampling_rate=200, heart_rate=60)\n",
+    "\n",
+    "# Process signal and save report\n",
+    "# df, info = nk.ppg_process(ppg_signal = signal, report = \"ppg_report.html\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": [
+     "remove-input"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The raw signal, sampled at 1000 Hz, was preprocessed using a bandpass filter ([0.5 - 8 Hz], Butterworth 3rd order; following Elgendi et al., 2013).\n",
+      "\n",
+      "The peak detection was carried out using the method described in Elgendi et al. (2013).\n",
+      "\n",
+      "|   PPG_Rate_Mean |   PPG_Rate_SD |\n",
+      "|----------------:|--------------:|\n",
+      "|         93.7041 |       23.5124 |\n",
+      "\n",
+      "References\n",
+      "- Elgendi M, Norton I, Brearley M, Abbott D, Schuurmans D (2013) Systolic Peak Detection in Acceleration Photoplethysmograms Measured from Emergency Responders in Tropical Conditions. PLoS ONE 8(10): e76585. doi:10.1371/journal.pone.0076585.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Note: this cell is hidden using the \"remove-input\" tag\n",
+    "# import neurokit2 as nk\n",
+    "\n",
+    "# Simulate PPG signal\n",
+    "# signal = nk.ppg_simulate(duration=30, sampling_rate=200, heart_rate=60)\n",
+    "\n",
+    "# Process signal and save report\n",
+    "# df, info = nk.ppg_process(ppg_signal = signal, report = \"text\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It also saves a `html` file (see example here) with interactive plots.\n",
+    "\n",
+    "![](ppg_report.png)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.7 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "11938c6bc6919ae2720b4d5011047913343b08a43b18698fd82dedb0d4417594"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

neurokit2/__init__.py

@@ -32,7 +32,7 @@
 from .video import *
 
 # Info
-__version__ = "0.2.2"
+__version__ = "0.2.3"
 
 
 # Maintainer info

neurokit2/complexity/entropy_fuzzy.py

@@ -28,6 +28,8 @@ def entropy_fuzzy(signal, delay=1, dimension=2, tolerance="sd", approximate=Fals
         Tolerance (often denoted as *r*), distance to consider two data points as similar. If
         ``"sd"`` (default), will be set to :math:`0.2 * SD_{signal}`. See
         :func:`complexity_tolerance` to estimate the optimal value for this parameter.
+    approximate : bool
+        If ``True``, will compute the fuzzy approximate entropy (FuzzyApEn).
     **kwargs
         Other arguments.
 
@@ -38,8 +40,6 @@ def entropy_fuzzy(signal, delay=1, dimension=2, tolerance="sd", approximate=Fals
     info : dict
         A dictionary containing additional information regarding the parameters used
         to compute fuzzy entropy.
-    approximate : bool
-        If ``True``, will compute the fuzzy approximate entropy (FuzzyApEn).
 
     See Also
     --------
@@ -62,6 +62,7 @@ def entropy_fuzzy(signal, delay=1, dimension=2, tolerance="sd", approximate=Fals
       fuzzycapen, parameters = nk.entropy_fuzzy(signal, approximate=True, corrected=True)
       fuzzycapen
 
+
     References
     ----------
     * Ishikawa, A., & Mieno, H. (1979). The fuzzy entropy concept and its application. Fuzzy Sets

neurokit2/complexity/entropy_multiscale.py

@@ -242,7 +242,9 @@ def entropy_multiscale(
     """
     # Sanity checks
     if isinstance(signal, (np.ndarray, pd.DataFrame)) and signal.ndim > 1:
-        raise ValueError("Multidimensional inputs (e.g., matrices or multichannel data) are not supported yet.")
+        raise ValueError(
+            "Multidimensional inputs (e.g., matrices or multichannel data) are not supported yet."
+        )
     # Prevent multiple arguments error in case 'delay' is passed in kwargs
     if "delay" in kwargs:
         kwargs.pop("delay")

neurokit2/complexity/fractal_tmf.py

@@ -2,6 +2,7 @@
 import numpy as np
 import pandas as pd
 import scipy.stats
+from packaging import version
 
 from ..signal import signal_surrogate
 from .fractal_dfa import fractal_dfa
@@ -11,8 +12,8 @@ def fractal_tmf(signal, n=40, show=False, **kwargs):
     """**Multifractal Nonlinearity (tMF)**
 
     The Multifractal Nonlinearity index (*t*\\MF) is the *t*\\-value resulting from the comparison
-    between the multifractality of the signal (measured by the spectrum width, see
-    :func:`.fractal_dfa`) and the multifractality of linearized
+    of the multifractality of the signal (measured by the spectrum width, see
+    :func:`.fractal_dfa`) with the multifractality of linearized
     :func:`surrogates <.signal_surrogate>` obtained by the IAAFT method (i.e., reshuffled series
     with comparable linear structure).
 
@@ -111,9 +112,14 @@ def fractal_tmf(signal, n=40, show=False, **kwargs):
         w[i] = fractal_dfa(surro, multifractal=True, show=False)[0]["Width"]
 
     # Run t-test
-    t, p = scipy.stats.ttest_1samp(w, w0)
-    t = t[0]
-    info["p"] = p[0]
+    # TODO: adjust in the future
+    if version.parse(scipy.__version__) < version.parse("1.10.0"):
+        t, p = scipy.stats.ttest_1samp(w, w0)
+        t = t[0]
+        t = t.item()
+        info["p"] = p[0]
+    else:
+        t, info["p"] = scipy.stats.ttest_1samp(w, w0)
 
     if show is True:
         pd.Series(w).plot(kind="density", label="Width of surrogates")

neurokit2/complexity/utils_complexity_coarsegraining.py

@@ -115,7 +115,7 @@ def complexity_coarsegraining(signal, scale=2, method="nonoverlapping", show=Fal
       signal = nk.signal_simulate(duration=0.5, frequency=[5, 20])
 
       @savefig p_complexity_coarsegraining4.png scale=100%
-      coarsegrained = nk.complexity_coarsegraining(signal, scale=40, method="timeshift", show=True)
+      coarsegrained = nk.complexity_coarsegraining(signal, scale=30, method="timeshift", show=True)
       @suppress
       plt.close()