def distance(items, album_info, mapping):
"""Determines how "significant" an album metadata change would be.
Returns a float in [0.0,1.0]. `album_info` is an AlbumInfo object
reflecting the album to be compared. `items` is a sequence of all
Item objects that will be matched (order is not important).
`mapping` is a dictionary mapping Items to TrackInfo objects; the
keys are a subset of `items` and the values are a subset of
`album_info.tracks`.
"""
cur_artist, cur_album, _ = current_metadata(items)
cur_artist = cur_artist or ''
cur_album = cur_album or ''
# These accumulate the possible distance components. The final
# distance will be dist/dist_max.
dist = 0.0
dist_max = 0.0
# Artist/album metadata.
if not album_info.va:
dist += string_dist(cur_artist, album_info.artist) * ARTIST_WEIGHT
dist_max += ARTIST_WEIGHT
dist += string_dist(cur_album, album_info.album) * ALBUM_WEIGHT
dist_max += ALBUM_WEIGHT
# Matched track distances.
for item, track in mapping.iteritems():
dist += track_distance(item, track, album_info.va) * TRACK_WEIGHT
dist_max += TRACK_WEIGHT
# Extra and unmatched tracks.
for track in set(album_info.tracks) - set(mapping.values()):
dist += MISSING_WEIGHT
dist_max += MISSING_WEIGHT
for item in set(items) - set(mapping.keys()):
dist += UNMATCHED_WEIGHT
dist_max += UNMATCHED_WEIGHT
# Plugin distances.
plugin_d, plugin_dm = plugins.album_distance(items, album_info)
dist += plugin_d
dist_max += plugin_dm
# Normalize distance, avoiding divide-by-zero.
if dist_max == 0.0:
return 0.0
else:
return dist / dist_max
def distance(items, album_info, mapping):
"""Determines how "significant" an album metadata change would be.
Returns a float in [0.0,1.0]. `album_info` is an AlbumInfo object
reflecting the album to be compared. `items` is a sequence of all
Item objects that will be matched (order is not important).
`mapping` is a dictionary mapping Items to TrackInfo objects; the
keys are a subset of `items` and the values are a subset of
`album_info.tracks`.
"""
cur_artist, cur_album, _ = current_metadata(items)
cur_artist = cur_artist or ''
cur_album = cur_album or ''
# These accumulate the possible distance components. The final
# distance will be dist/dist_max.
dist = 0.0
dist_max = 0.0
# Artist/album metadata.
if not album_info.va:
dist += string_dist(cur_artist, album_info.artist) * ARTIST_WEIGHT
dist_max += ARTIST_WEIGHT
dist += string_dist(cur_album, album_info.album) * ALBUM_WEIGHT
dist_max += ALBUM_WEIGHT
# Matched track distances.
for item, track in mapping.iteritems():
dist += track_distance(item, track, album_info.va) * TRACK_WEIGHT
dist_max += TRACK_WEIGHT
# Extra and unmatched tracks.
for track in set(album_info.tracks) - set(mapping.values()):
dist += MISSING_WEIGHT
dist_max += MISSING_WEIGHT
for item in set(items) - set(mapping.keys()):
dist += UNMATCHED_WEIGHT
dist_max += UNMATCHED_WEIGHT
# Plugin distances.
plugin_d, plugin_dm = plugins.album_distance(items, album_info)
dist += plugin_d
dist_max += plugin_dm
# Normalize distance, avoiding divide-by-zero.
if dist_max == 0.0:
return 0.0
else:
return dist / dist_max
def distance(items, album_info):
"""Determines how "significant" an album metadata change would be.
Returns a float in [0.0,1.0]. The list of items must be ordered.
"""
cur_artist, cur_album, _ = current_metadata(items)
cur_artist = cur_artist or ''
cur_album = cur_album or ''
# These accumulate the possible distance components. The final
# distance will be dist/dist_max.
dist = 0.0
dist_max = 0.0
# Artist/album metadata.
if not album_info.va:
dist += string_dist(cur_artist, album_info.artist) * ARTIST_WEIGHT
dist_max += ARTIST_WEIGHT
dist += string_dist(cur_album, album_info.album) * ALBUM_WEIGHT
dist_max += ALBUM_WEIGHT
# Track distances.
for i, (item, track_info) in enumerate(zip(items, album_info.tracks)):
if item:
dist += track_distance(item, track_info, i+1, album_info.va) * \
TRACK_WEIGHT
dist_max += TRACK_WEIGHT
else:
dist += MISSING_WEIGHT
dist_max += MISSING_WEIGHT
# Plugin distances.
plugin_d, plugin_dm = plugins.album_distance(items, album_info)
dist += plugin_d
dist_max += plugin_dm
# Normalize distance, avoiding divide-by-zero.
if dist_max == 0.0:
return 0.0
else:
return dist/dist_max