Also bump Bliss version
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56108cea38
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152
mpd/client.py
152
mpd/client.py
@ -103,60 +103,63 @@ if "XDG_DATA_HOME" in os.environ:
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else:
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_BLISSIFY_DATA_HOME = os.path.expanduser("~/.local/share/blissify")
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# Distance between two songs
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def distance(x, y):
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distance = math.sqrt(
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"""
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Compute the distance between two songs.
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Params:
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- x: First song dict
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- y: Second song dict
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Returns: The cartesian distance between the two songs.
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"""
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return math.sqrt(
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(x["tempo"] - y["tempo"])**2 +
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(x["amplitude"] - y["amplitude"])**2 +
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(x["frequency"] - y["frequency"])**2 +
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(x["attack"] - y["attack"])**2)
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return distance
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(x["attack"] - y["attack"])**2
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)
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# Distance between a set and a point
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def distance_set(X, y):
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temp_distance = distance(X[0], y);
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for song in X:
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a = distance(song, y);
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temp_distance = a if a < temp_distance else temp_distance;
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return temp_distance;
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# Hausdorff distance between two sets
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def hauff_distance_sets(X, Y):
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temp_distance = distance_set(X, Y[0]);
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for song in X:
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a = distance_set(Y, song);
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temp_distance = a if a > temp_distance else temp_distance;
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for song in Y:
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a = distance_set(X, song);
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temp_distance = a if a > temp_distance else temp_distance;
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return temp_distance
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def mean_song(X):
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count = 0;
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"""
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Compute a "mean" song for a given iterable of song dicts.
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Params:
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- X: An iterable of song dicts.
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Returns: A "mean" song, whose features are the mean features of the songs
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in the iterable.
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"""
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count = 0
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result = {'tempo': 0, 'amplitude': 0, 'frequency': 0, 'attack': 0}
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for song in X:
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result["tempo"] += song["tempo"];
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result["amplitude"] += song["amplitude"];
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result["frequency"] += song["frequency"];
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result["attack"] += song["attack"];
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count = count + 1;
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result["tempo"] /= count;
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result["amplitude"] /= count;
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result["frequency"] /= count;
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result["attack"] /= count;
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return result;
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result["tempo"] += song["tempo"]
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result["amplitude"] += song["amplitude"]
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result["frequency"] += song["frequency"]
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result["attack"] += song["attack"]
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count = count + 1
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result["tempo"] /= count
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result["amplitude"] /= count
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result["frequency"] /= count
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result["attack"] /= count
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return result
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# Custom distance between two sets
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def distance_sets(X, Y):
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a = mean_song(X);
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b = mean_song(Y);
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"""
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Compute the distance between two iterables of song dicts, defined as the
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distance between the two mean songs of the iterables.
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return distance(a, b);
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Params:
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- X: First iterable of song dicts.
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- Y: First iterable of song dicts.
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Returns: The distance between the two iterables.
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"""
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return distance(mean_song(X), mean_song(Y))
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def main_album(queue_length):
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def _init():
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# Get MPD connection settings
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try:
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mpd_host = os.environ["MPD_HOST"]
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@ -199,6 +202,7 @@ def main_album(queue_length):
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all_songs = [x["file"] for x in client.listall() if "file" in x]
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current_song = random.choice(all_songs)
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client.add(current_song)
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logging.info("Currently played song is %s." % (current_song,))
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# Get current song coordinates
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@ -211,12 +215,18 @@ def main_album(queue_length):
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client.disconnect()
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sys.exit(1)
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return client, conn, cur, current_song_coords
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def main_album(queue_length):
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client, conn, cur, current_song_coords = _init()
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for i in range(queue_length):
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# No cache management
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# Get all songs from the current album
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album = current_song_coords["album"];
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album = current_song_coords["album"]
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cur.execute("SELECT id, tempo, amplitude, frequency, attack, filename, album FROM songs WHERE album=?", (album,))
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target_album_set = cur.fetchall();
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target_album_set = cur.fetchall()
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# Get all other songs
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cur.execute("SELECT id, tempo, amplitude, frequency, attack, filename, album FROM songs ORDER BY album")
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@ -233,9 +243,9 @@ def main_album(queue_length):
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# Get all songs from the current temporary album
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while tmp_song_data:
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if (current_album_set[i]["album"] == tmp_song_data["album"]):
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current_album_set.append(tmp_song_data);
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current_album_set.append(tmp_song_data)
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else:
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break;
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break
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tmp_song_data = cur.fetchone()
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i = i + 1
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# Skip current album and already processed albums
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@ -244,7 +254,7 @@ def main_album(queue_length):
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tmp_distance = distance_sets(current_album_set, target_album_set)
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if tmp_distance < shortest_distance or shortest_distance == -1:
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shortest_distance = tmp_distance
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closest_album = current_album_set;
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closest_album = current_album_set
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logging.info("Closest album found is \"%s\". Distance is %f." % (closest_album[0]["album"], shortest_distance))
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for song in closest_album:
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@ -255,59 +265,9 @@ def main_album(queue_length):
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client.close()
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client.disconnect()
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def main_single(queue_length):
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# Get MPD connection settings
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try:
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mpd_host = os.environ["MPD_HOST"]
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try:
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mpd_password, mpd_host = mpd_host.split("@")
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except ValueError:
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mpd_password = None
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except KeyError:
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mpd_host = "localhost"
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mpd_password = None
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try:
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mpd_port = os.environ["MPD_PORT"]
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except KeyError:
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mpd_port = 6600
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# Connect to MPD
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client = PersistentMPDClient(host=mpd_host, port=mpd_port)
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if mpd_password is not None:
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client.password(mpd_password)
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# Connect to db
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db_path = os.path.join(_BLISSIFY_DATA_HOME, "db.sqlite3")
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logging.debug("Using DB path: %s." % (db_path,))
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conn = sqlite3.connect(db_path)
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conn.row_factory = sqlite3.Row
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conn.execute('pragma foreign_keys=ON')
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cur = conn.cursor()
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# Ensure random is not enabled
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status = client.status()
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if int(status["random"]) != 0:
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logging.warning("Random mode is enabled. Are you sure you want it?")
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# Take the last song from current playlist and iterate from it
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playlist = client.playlist()
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if len(playlist) > 0:
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current_song = playlist[-1].replace("file: ", "").rstrip()
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# If current playlist is empty
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else:
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# Add a random song to start with
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all_songs = [x["file"] for x in client.listall() if "file" in x]
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current_song = random.choice(all_songs)
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client.add(current_song)
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logging.info("Currently played song is %s." % (current_song,))
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# Get current song coordinates
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cur.execute("SELECT id, tempo, amplitude, frequency, attack, filename FROM songs WHERE filename=?", (current_song,))
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current_song_coords = cur.fetchone()
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if current_song_coords is None:
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logging.error("Current song %s is not in db. You should update the db." %
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(current_song,))
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client.close()
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client.disconnect()
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sys.exit(1)
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client, conn, cur, current_song_coords = _init()
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for i in range(queue_length):
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# Get cached distances from db
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