updated docs example for analyzer

crema/analyze.py

@@ -37,20 +37,20 @@ def analyze(filename=None, y=None, sr=None):
     --------
     >>> from crema.analyze import analyze
     >>> import librosa
-    >>> jam = analyze(filename=librosa.util.example_audio_file())
+    >>> jam = analyze(filename=librosa.ex('brahms'))
     >>> jam
     <JAMS(file_metadata=<FileMetadata(...)>,
           annotations=[1 annotation],
           sandbox=<Sandbox(...)>)>
     >>> # Get the chord estimates
     >>> chords = jam.annotations['chord', 0]
     >>> chords.to_dataframe().head(5)
-           time  duration  value  confidence
-    0  0.000000  0.092880  E:maj    0.336977
-    1  0.092880  0.464399    E:7    0.324255
-    2  0.557279  1.021678  E:min    0.448759
-    3  1.578957  2.693515  E:maj    0.501462
-    4  4.272472  1.486077  E:min    0.287264
+            time  duration    value  confidence
+    0   0.000000  3.622313    G:min    0.767835
+    1   3.622313  1.207438  C:min/5    0.652179
+    2   4.829751  1.207438    D:maj    0.277913
+    3   6.037188  4.086712    G:min    0.878656
+    4  10.123900  1.486077   D#:maj    0.608746
     '''
 
     _load_models()

docs/index.rst

@@ -49,7 +49,7 @@ The simplest way to apply `crema` is via the command line:
     python -m crema.analyze -o my_song.jams /path/to/my_song.ogg
 
 .. note:: 
-    Any audio format supported by `librosa <https://librosa.github.io/>`_ will work here.
+    Any audio format supported by `librosa <https://librosa.org/>`_ will work here.
 
 This command will apply all analyzers to `mysong.ogg` and store the outputs as
 `my_song.jams`.