codespell: action, config + some typos fixed

.codespellrc

@@ -0,0 +1,4 @@
+[codespell]
+skip = .git,*.pdf,*.svg
+ignore-regex = ^\s*"image/\S+": ".*
+ignore-words-list = adn

.github/workflows/codespell.yml

@@ -0,0 +1,22 @@
+---
+name: Codespell
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+permissions:
+  contents: read
+
+jobs:
+  codespell:
+    name: Check for spelling errors
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Codespell
+        uses: codespell-project/actions-codespell@v2

pynacollada/Pynapple Paper Figures/Siegle 2021/Siegle_dataset.ipynb

@@ -41,7 +41,7 @@
    "source": [
     "The __EcephysProjectCache__ object of the AllenSDK delivers the data to you as ready-to-analyze Python objects. It automatically keeps track of which files are stored locally, and will download additional files as needed.\n",
     "\n",
-    "The next bit involves dowloading the data onto your local machine. This section is adapted from <a href=\"https://allensdk.readthedocs.io/en/2.16.0/_static/examples/nb/ecephys_data_access.html\" target=\"_blank\">here</a>, where you can find a more detailed account of how to use data from the Allen Institute.\n",
+    "The next bit involves downloading the data onto your local machine. This section is adapted from <a href=\"https://allensdk.readthedocs.io/en/2.16.0/_static/examples/nb/ecephys_data_access.html\" target=\"_blank\">here</a>, where you can find a more detailed account of how to use data from the Allen Institute.\n",
     "\n",
     "Before downloading the data, you must decide where the manifest.json file lives. This file serves as the map that guides the EcephysProjectCache object to the file locations.\n",
     "\n",

pynacollada/eeg_processing/Tutorial_ripple_detection.ipynb

@@ -176,7 +176,7 @@
    "id": "82b21ea7",
    "metadata": {},
    "source": [
-    "Second step is to look at the enveloppe of the filtered signal."
+    "Second step is to look at the envelope of the filtered signal."
    ]
   },
   {

pynacollada/eeg_processing/eeg_processing.py

@@ -64,7 +64,7 @@ def bandpass_filter(data, lowcut, highcut, fs, order=4):
             time_units='s')
 
     else:
-        raise RuntimeError("Unknow format. Should be Tsd/TsdFrame")
+        raise RuntimeError("Unknown format. Should be Tsd/TsdFrame")
 
 def detect_oscillatory_events(lfp, epoch, freq_band, thres_band, duration_band, min_inter_duration, wsize=51):
     """
@@ -85,7 +85,7 @@ def detect_oscillatory_events(lfp, epoch, freq_band, thres_band, duration_band,
     min_inter_duration : float
         The minimum duration between two events otherwise they are merged (in seconds)
     wsize : int, optional
-        The size of the window for digitial filtering
+        The size of the window for digital filtering
 
     Returns
     -------
@@ -145,7 +145,7 @@ def detect_oscillatory_events(lfp, epoch, freq_band, thres_band, duration_band,
 
 # def getPeaksandTroughs(lfp, min_points):
 #   """  
-#       At 250Hz (1250/5), 2 troughs cannont be closer than 20 (min_points) points (if theta reaches 12Hz);     
+#       At 250Hz (1250/5), 2 troughs cannot be closer than 20 (min_points) points (if theta reaches 12Hz);     
 #   """
 #   import scipy.signal
 #   if isinstance(lfp, nap.time_series.Tsd):

pynacollada/neural_tuning/neural_tuning.py

@@ -183,7 +183,7 @@ def centerTuningCurves(tcurve):
 # copied to neural_tuning
 def offsetTuningCurves(tcurve, diffs):
 	"""
-	offseting tuning curves synced by diff
+	offsetting tuning curves synced by diff
 	"""	
 	new_tcurve 		= []
 	for p in tcurve.columns: