From 12ed3200366cd570718dcddcc925fcc9dcfc2f39 Mon Sep 17 00:00:00 2001
From: Nicolas Barascud <10333715+nbara@users.noreply.github.com>
Date: Wed, 3 Jun 2020 13:48:44 +0200
Subject: [PATCH 1/4] Trigger github actions on PR

---
 .github/workflows/pythonpackage.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/pythonpackage.yml b/.github/workflows/pythonpackage.yml
index 28017583..b41f675d 100644
--- a/.github/workflows/pythonpackage.yml
+++ b/.github/workflows/pythonpackage.yml
@@ -4,7 +4,9 @@ on:
   push:
     branches-ignore:
       - 'gh-pages'
-
+  pull_request:
+    branches:
+      - master
 jobs:
   build:
 

From 483f44598794cbd8d8f907fed6bf35b456c76acd Mon Sep 17 00:00:00 2001
From: Nicolas Barascud <10333715+nbara@users.noreply.github.com>
Date: Wed, 3 Jun 2020 13:50:07 +0200
Subject: [PATCH 2/4] Update pythonpackage.yml

---
 .github/workflows/pythonpackage.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/pythonpackage.yml b/.github/workflows/pythonpackage.yml
index b41f675d..742f2b19 100644
--- a/.github/workflows/pythonpackage.yml
+++ b/.github/workflows/pythonpackage.yml
@@ -2,6 +2,8 @@ name: unit-tests
 
 on:
   push:
+    branches: 
+      - master
     branches-ignore:
       - 'gh-pages'
   pull_request:

From 54785c23bfe91b4fc6370afbaca48d04c0039648 Mon Sep 17 00:00:00 2001
From: Nicolas Barascud <10333715+nbara@users.noreply.github.com>
Date: Wed, 3 Jun 2020 14:03:02 +0200
Subject: [PATCH 3/4] Update pythonpackage.yml

---
 .github/workflows/pythonpackage.yml | 2 --
 1 file changed, 2 deletions(-)

diff --git a/.github/workflows/pythonpackage.yml b/.github/workflows/pythonpackage.yml
index 742f2b19..d4b6b34b 100644
--- a/.github/workflows/pythonpackage.yml
+++ b/.github/workflows/pythonpackage.yml
@@ -4,8 +4,6 @@ on:
   push:
     branches: 
       - master
-    branches-ignore:
-      - 'gh-pages'
   pull_request:
     branches:
       - master

From 8fb5fc9a85fac580f5f1e5b75886c70ee2e282e8 Mon Sep 17 00:00:00 2001
From: nbara <10333715+nbara@users.noreply.github.com>
Date: Wed, 3 Jun 2020 14:10:14 +0200
Subject: [PATCH 4/4] pep

---
 meegkit/star.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/meegkit/star.py b/meegkit/star.py
index 5a8b77a7..f4b178d4 100644
--- a/meegkit/star.py
+++ b/meegkit/star.py
@@ -74,7 +74,7 @@ def star(X, thresh=1, closest=[], depth=1, pca_thresh=1e-15, n_smooth=10,
 
     # Phase 1
     # -------------------------------------------------------------------------
-    # Find time intervals where at least one channel is excentric -> w == 0
+    # Find time intervals where at least one channel is eccentric -> w == 0
     # Compute covariance on artifact-free data.
 
     iter = n_iter
@@ -87,7 +87,7 @@ def star(X, thresh=1, closest=[], depth=1, pca_thresh=1e-15, n_smooth=10,
             # Compute channel data estimated from its neighbours
             z = _project_channel(X[:, neighbours], c0, ch, neighbours)
 
-            # Compute excentricity over time
+            # Compute eccentricity over time
             d[:, ch] = _eccentricity(X[:, ch][:, None], z, w, n_smooth).T
             d[:, ch] = d[:, ch] / thresh
 
@@ -122,7 +122,7 @@ def star(X, thresh=1, closest=[], depth=1, pca_thresh=1e-15, n_smooth=10,
     d = _eccentricity(X, None, w, n_smooth)
 
     rank = np.argsort(d, axis=1)[:, ::-1].astype(float)
-    rank[np.where(w)[0], :] = np.nan  # exclude parts that are not excentric
+    rank[np.where(w)[0], :] = np.nan  # exclude parts that are not eccentric
 
     depth = np.min((depth, n_chans - 1))
     ww = np.ones(X.shape)
@@ -134,7 +134,7 @@ def star(X, thresh=1, closest=[], depth=1, pca_thresh=1e-15, n_smooth=10,
         for ch in np.arange(n_chans):
             neighbours = _closest_neighbours(closest, ch, n_chans)
 
-            # find samples where channel `ch` is the most excentric
+            # find samples where channel `ch` is the most eccentric
             bad_samples = np.where(ch == rank[:, i_depth])[0]
             if i_depth != 0:  # exclude if not very bad
                 bad_samples = np.delete(