Merge pull request #896 from danibene/docs/hrv_feature_names

[Docs] typos
neuropsychology · Sep 7, 2023 · d867214 · d867214
2 parents 4fdc9df + 619c8d6
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diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
@@ -15,6 +15,6 @@ I changed the `foo()` function so that ...
 Here are some things to check before creating the PR. If you encounter any issues, do let us know :)
 
 - [ ] I have read the [CONTRIBUTING](https://github.com/neuropsychology/NeuroKit/blob/master/.github/CONTRIBUTING.rst#structure-and-code) file.
-- [ ] My PR is targetted at the **dev branch** (and not towards the master branch).
+- [ ] My PR is targeted at the **dev branch** (and not towards the master branch).
 - [ ] I ran the [CODE CHECKS](https://github.com/neuropsychology/NeuroKit/blob/master/.github/CONTRIBUTING.rst#run-code-checks) on the files I added or modified and fixed the errors.
-- [ ] I have added the newly added features to **News.rst** (if applicable)
+- [ ] I have added the newly added features to **News.rst** (if applicable)
diff --git a/neurokit2/complexity/entropy_shannon.py b/neurokit2/complexity/entropy_shannon.py
@@ -10,7 +10,7 @@ def entropy_shannon(signal=None, base=2, symbolize=None, show=False, freq=None,
 
     Compute Shannon entropy (SE). Entropy is a measure of unpredictability of the
     state, or equivalently, of its average information content. Shannon entropy (SE) is one of the
-    first and most basic measure of entropy and a foundational concept of information theory,
+    first and most basic measures of entropy and a foundational concept of information theory,
     introduced by Shannon (1948) to quantify the amount of information in a variable.
 
     .. math::

diff --git a/neurokit2/hrv/hrv_nonlinear.py b/neurokit2/hrv/hrv_nonlinear.py
@@ -101,9 +101,9 @@ def hrv_nonlinear(peaks, sampling_rate=1000, show=False, **kwargs):
     * **SampEn**: See :func:`.entropy_sample`.
     * **ShanEn**: See :func:`.entropy_shannon`.
     * **FuzzyEn**: See :func:`.entropy_fuzzy`.
-    * **MSE**: See :func:`.entropy_multiscale`.
-    * **CMSE**: See :func:`.entropy_multiscale`.
-    * **RCMSE**: See :func:`.entropy_multiscale`.
+    * **MSEn**: See :func:`.entropy_multiscale`.
+    * **CMSEn**: See :func:`.entropy_multiscale`.
+    * **RCMSEn**: See :func:`.entropy_multiscale`.
     * **CD**: See :func:`.fractal_correlation`.
     * **HFD**: See :func:`.fractal_higuchi` (with ``kmax`` set to ``"default"``).
     * **KFD**: See :func:`.fractal_katz`.