From 230bdfa395ec9e58442614dc245d3ac806aece3e Mon Sep 17 00:00:00 2001 From: rhiag Date: Thu, 27 May 2021 17:32:39 -0700 Subject: [PATCH] Attempt to generate graph dynamically --- pages/predictions.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/pages/predictions.py b/pages/predictions.py index 59abfb2..acf3496 100644 --- a/pages/predictions.py +++ b/pages/predictions.py @@ -35,7 +35,6 @@ def recommend(index: int, n: int=5) -> 'tuple[np.ndarray]': ### Parameters index: index of song n: number of recommendations to pull - returns: (dist, ind), array of distances, array of indeces for recommended songs. Includes original song. ''' @@ -76,7 +75,6 @@ def get_songs_via_features(features: list, n_songs: int=5) -> 'list[int]': Converts input into the model's encoding, then runs it through the K-NearestNeighbors models Returns: - ### Parameters features: A list of all features required to run the model. The model encoder expects these inputs in this order: @@ -95,7 +93,6 @@ def get_songs_via_features(features: list, n_songs: int=5) -> 'list[int]': tempo, time_signature, popularity - n_songs: number of songs to return. ''' vec = model.encoder(np.array(features).reshape(1, -1)) @@ -197,7 +194,6 @@ def get_songs_via_features(features: list, n_songs: int=5) -> 'list[int]': [ dcc.Markdown( """ - **Instructions**: Adjust the attribute sliders. Your prediction outcome will update dynamically. Attribute Definitions: * **Duration** - Length of the song in ms