MRG: #227 from vocalpy/fix-vignettes-pyos-review

Fix vignettes for PyOpenSci review, fix #220

doc/howto/convert-generic-seq.md

@@ -65,7 +65,7 @@ An example of such a format is the Audacity
 exported to .txt files, that you would get if you were to annotate with  
 [region labels](https://manual.audacityteam.org/man/label_tracks.html#type).
 This format is represented by the 
-{class}`crowsetta.formats.seq.AudTxt <crowsetta.formats.seq.audtxt.AudTxt>` 
+{class}`crowsetta.formats.seq.AudSeq <crowsetta.formats.seq.audseq.AudSeq>` 
 class in crowsetta.
 
 As described above,
@@ -115,12 +115,12 @@ Now we load the annotation files.
 import pathlib
 import crowsetta
 
-audtxt_paths = sorted(pathlib.Path('./data/giraudon-et-al-2021/audacity-annotations').glob('*.txt'))
+audseq_paths = sorted(pathlib.Path('./data/giraudon-et-al-2021/audacity-annotations').glob('*.txt'))
 # we make the list of ``Annotation``s "by hand" instead of getting it from a `to_annot` call
 annots = []
-for audtxt_path in audtxt_paths:
+for audseq_path in audseq_paths:
     annots.append(
-        crowsetta.formats.seq.AudTxt.from_file(audtxt_path).to_annot()
+        crowsetta.formats.seq.AudSeq.from_file(audseq_path).to_annot()
     )
 
 print(

doc/howto/remove-silent-labels-textgrid.md

@@ -4,13 +4,11 @@ jupytext:
     extension: .md
     format_name: myst
     format_version: 0.13
-    jupytext_version: 1.14.4
+    jupytext_version: 1.14.5
 kernelspec:
   display_name: Python 3 (ipykernel)
   language: python
   name: python3
-execution:
-  timeout: 120
 ---
 
 (howto-remove-silent-labels-textgrid)=
@@ -57,6 +55,21 @@ because we are only interested in transitions between syllables.
 So, to compute our transition matrix, 
 we need to remove all these intervals with `None` labels.
 
++++
+
+```{admonition} Download this page as a Jupyter notebook!
+To work with this tutorial interactively, 
+we suggest downloading this notebook!
+Click on the download icon in the upper right 
+to download a Markdown file (with '.md' extension) 
+that you can run as a Jupyter notebook 
+after installing Jupyter lab and jupytext.
+```
+
++++
+
+
+
 
 ## Workflow
 
@@ -299,7 +312,13 @@ def transmat_from_labels(labels: list[np.ndarray],
 +++
 
 The annotations we want to use are in a public project on the [Open Science Framework](osf.io).
-To download the files, we use the Python package [`osfclient`](https://github.com/osfclient/osfclient).
+To download the files, we use the Python package [`osfclient`](https://github.com/osfclient/osfclient). First we make sure it is installed.
+
+```{code-cell} ipython3
+!pip install osfclient
+```
+
+Then we import the package.
 
 ```{code-cell} ipython3
 import osfclient

doc/tutorial.md

@@ -61,10 +61,10 @@ get a list of those files.
 
 ```{code-cell} ipython3
 import pathlib
-audtxt_paths = sorted(pathlib.Path('./data/giraudon-et-al-2021/audacity-annotations').glob('*.txt'))
+audseq_paths = sorted(pathlib.Path('./data/giraudon-et-al-2021/audacity-annotations').glob('*.txt'))
 
-print(f'There are {len(audtxt_paths)} Audacity LabelTrack .txt files')
-first_five = "\n".join([str(path) for path in audtxt_paths[:5]])
+print(f'There are {len(audseq_paths)} Audacity LabelTrack .txt files')
+first_five = "\n".join([str(path) for path in audseq_paths[:5]])
 print(f'The first five are:\n{first_five}')
 ```
 
@@ -92,14 +92,14 @@ annotation files (methods are functions that “belong” to a class).
 We use the `from_file` method of the `Transcriber` to load the annotations.
 
 ```{code-cell} ipython3
-audtxts = []
+audseqs = []
 
-for audtxt_path in audtxt_paths:
-    audtxts.append(scribe.from_file(audtxt_path))
+for audseq_path in audseq_paths:
+    audseqs.append(scribe.from_file(audseq_path))
 
 
-print(f'There are {len(audtxts)} Audacity LabelTrack annotations')
-print(f'The first one looks like:\n{audtxts[0]}')
+print(f'There are {len(audseqs)} Audacity LabelTrack annotations')
+print(f'The first one looks like:\n{audseqs[0]}')
 ```
 
 ## Using the `to_annot` method to convert annotations into data types we can work with in Python
@@ -118,8 +118,8 @@ for multiple annotated audio files or spectrograms).
 
 ```{code-cell} ipython3
 annots = []
-for audtxt in audtxts:
-    annots.append(scribe.from_file(audtxt_path).to_annot())
+for audseq in audseqs:
+    annots.append(scribe.from_file(audseq_path).to_annot())
 print(f'The first Annotation: {annots[0]}')
 ```
 
@@ -160,8 +160,8 @@ to generic `crowsetta.Annotation`s into a one-liner:
 
 ```{code-cell} ipython3
 annots = []
-for audtxt_path in audtxt_paths:
-    annots.append(scribe.from_file(audtxt_path).to_annot())
+for audseq_path in audseq_paths:
+    annots.append(scribe.from_file(audseq_path).to_annot())
 ```
 
 We didn't do this above, just because we wanted to introduce the methods one-by-one.
@@ -206,8 +206,8 @@ using the `to_seq` method to load each file into a `Sequence`.
 
 ```{code-cell} ipython3
 seqs = []
-for audtxt_path in audtxt_paths:
-    seqs.append(scribe.from_file(audtxt_path).to_seq())
+for audseq_path in audseq_paths:
+    seqs.append(scribe.from_file(audseq_path).to_seq())
 ```
 
 Each sequence-like format has a `to_seq` method, 
@@ -221,9 +221,9 @@ you can get them directly by calling the method yourselves.
 For each annotation file, we should now have a `Sequence`.
 
 ```{code-cell} ipython3
-print("Number of annotation files: ", len(audtxt_paths))
+print("Number of annotation files: ", len(audseq_paths))
 print("Number of Sequences: ", len(seqs))
-if len(audtxt_paths) == len(seqs):
+if len(audseq_paths) == len(seqs):
     print("The number of annotation files is equal to number of sequences.")
 ```