for i in range(num_songs):
analysis_sample_rate = GETTERS.get_analysis_sample_rate(h5, i)
artist_7digitalid = GETTERS.get_artist_7digitalid(h5, i)
artist_familiarity = GETTERS.get_artist_familiarity(h5, i)
artist_hotttnesss = GETTERS.get_artist_hotttnesss(h5, i)
artist_id = GETTERS.get_artist_id(h5, i)
artist_latitude = GETTERS.get_artist_latitude(h5, i)
artist_location = GETTERS.get_artist_location(h5, i)
artist_longitude = GETTERS.get_artist_longitude(h5, i)
artist_mbid = GETTERS.get_artist_mbid(h5, i)
artist_mbtags = ','.join(
str(e) for e in GETTERS.get_artist_mbtags(h5, i)) # array
artist_mbtags_count = ','.join(
str(e)
for e in GETTERS.get_artist_mbtags_count(h5, i)) # array
artist_name = GETTERS.get_artist_name(h5, i)
artist_playmeid = GETTERS.get_artist_playmeid(h5, i)
artist_terms = ','.join(
str(e) for e in GETTERS.get_artist_terms(h5, i)) # array
#artist_terms_freq = ','.join(str(e) for e in GETTERS.get_artist_terms_freq(h5, i)) # array
#artist_terms_weight = ','.join(str(e) for e in GETTERS.get_artist_terms_weight(h5, i)) # array
#audio_md5 = GETTERS.get_audio_md5(h5, i)
#bars_confidence = ','.join(str(e) for e in GETTERS.get_bars_confidence(h5, i)) # array
#bars_start = ','.join(str(e) for e in GETTERS.get_bars_start(h5, i)) # array
#beats_confidence = ','.join(str(e) for e in GETTERS.get_beats_confidence(h5, i)) # array
#beats_start = ','.join(str(e) for e in GETTERS.get_beats_start(h5, i)) # array
danceability = GETTERS.get_danceability(h5, i)
duration = GETTERS.get_duration(h5, i)
end_of_fade_in = GETTERS.get_end_of_fade_in(h5, i)
energy = GETTERS.get_energy(h5, i)
def func_to_extract_features(filename):
"""
This function does 3 simple things:
- open the song file
- get artist ID and put it
- close the file
"""
global cntnan
global cntdanceability
global listfeatures
global listhotness
global listyear
global listloudness
global listkey
global listmode
global listduration
cf = []
h5 = GETTERS.open_h5_file_read(filename)
nanfound = 0
#Get target feature: song hotness
#FEATURE 0
song_hotness = GETTERS.get_song_hotttnesss(h5)
if math.isnan(song_hotness):
nanfound = 1
cntnan = cntnan + 1
else:
cf.append(song_hotness)
#FEATURE 1
#Get song loudness
song_loudness = GETTERS.get_loudness(h5)
if math.isnan(song_loudness):
nanfound = 1
cntnan = cntnan + 1
else:
cf.append(song_loudness)
#FEATURE 2
#Get key of the song
song_key = GETTERS.get_key(h5)
if math.isnan(song_key):
nanfound = 1
cntnan = cntnan + 1
else:
cf.append(song_key)
#FEATURE 3
#Get duration of the song
song_duration = GETTERS.get_duration(h5)
if math.isnan(song_duration):
nanfound = 1
cntnan = cntnan + 1
else:
cf.append(song_duration)
#FEATURE 4-15
#Get Average Pitch Class across all segments
#Get the pitches (12 pitches histogram for each segment)
pitches = GETTERS.get_segments_pitches(h5)
M = np.mat(pitches)
meanpitches = M.mean(axis=0)
pitches_arr = np.asarray(meanpitches)
pitches_list = []
for i in range(0,12):
pitches_list.append(pitches_arr[0][i])
cf.append(pitches_list)
#FEATURE 16, 27
#Get Average Timbre Class across all segments
timbres = GETTERS.get_segments_timbre(h5)
M = np.mat(timbres)
meantimbres = M.mean(axis=0)
timbre_arr = np.asarray(meantimbres)
timbre_list = []
for i in range(0,12):
timbre_list.append(timbre_arr[0][i])
cf.append(timbre_list)
#FEATURE 28
#Get song year
song_year = GETTERS.get_year(h5)
if song_year == 0:
nanfound = 1
cntnan = cntnan + 1
else:
cf.append(song_year)
#FEATURE 29
#Get song tempo
song_tempo = GETTERS.get_tempo(h5)
cf.append(song_tempo)
#Feature 30
#Get max loudness for each segment
max_loudness_arr = GETTERS.get_segments_loudness_max(h5)
start_loudness_arr = GETTERS.get_segments_loudness_start(h5)
if nanfound == 0:
cf.append(max(max_loudness_arr)-min(start_loudness_arr))
#Feature 31
artist_familiarity = GETTERS.get_artist_familiarity(h5)
cf.append(artist_familiarity)
#Feature 32
song_title = GETTERS.get_title(h5)
cf.append(song_title)
#Featture 33
artist_name = GETTERS.get_artist_name(h5)
cf.append(artist_name)
#Feature 34
#location = GETTERS.get_artist_location(h5)
#cf.append(location)
#Tags
artist_mbtags = GETTERS.get_artist_mbtags(h5)
if not artist_mbtags.size:
genre = "Unknown"
else:
artist_mbcount = np.array(GETTERS.get_artist_mbtags_count(h5))
index_max = artist_mbcount.argmax(axis=0)
genre = artist_mbtags[index_max]
if genre == 'espa\xc3\xb1ol':
genre = "Unknown"
cf.append(genre)
if nanfound == 0:
strlist = list_to_csv(cf)
listfeatures.append(strlist)
mydict.setdefault(artist_name,[]).append(song_hotness)
h5.close()
hdf)
sections_start = hdf5_getters.get_sections_start(hdf)
sections_confidence = hdf5_getters.get_sections_confidence(hdf)
beats_start = hdf5_getters.get_beats_start(hdf)
beats_confidence = hdf5_getters.get_beats_confidence(hdf)
bars_start = hdf5_getters.get_bars_start(hdf)
bars_confidence = hdf5_getters.get_bars_confidence(hdf)
tatums_start = hdf5_getters.get_tatums_start(hdf)
tatums_confidence = hdf5_getters.get_tatums_confidence(hdf)
artist_mbtags = hdf5_getters.get_artist_mbtags(hdf)
artist_mbtags_count = hdf5_getters.get_artist_mbtags_count(hdf)
trList = [
artist_id.decode(),
artists_mb_id.decode(), artist_playmeid, artist_7digitalid,
artist_familarity,
artist_name.decode(), artist_hotttnesss,
artist_location.decode(),
release.decode(), release_7digitalid,
song_id.decode(),
title.decode(), song_hotttnesss, track_7digitalid,
analysis_sample_rate,
audio_md5.decode(), duration, end_of_fade_in, energy, key,
key_confidence, loudness, mode, mode_confidence,
start_of_fade_out, tempo, time_signature,
time_signature_confidence,
def fill_attributes(song, songH5File):
#----------------------------non array attributes-------------------------------
song.analysisSampleRate = str(
hdf5_getters.get_analysis_sample_rate(songH5File))
song.artistDigitalID = str(hdf5_getters.get_artist_7digitalid(songH5File))
song.artistFamiliarity = str(
hdf5_getters.get_artist_familiarity(songH5File))
song.artistHotness = str(hdf5_getters.get_artist_hottness(songH5File))
song.artistID = str(hdf5_getters.get_artist_id(songH5File))
song.artistLatitude = str(hdf5_getters.get_artist_latitude(songH5File))
song.artistLocation = str(hdf5_getters.get_artist_location(songH5File))
song.artistLongitude = str(hdf5_getters.get_artist_longitude(songH5File))
song.artistmbID = str(hdf5_getters.get_artist_mbid(songH5File))
song.artistName = str(hdf5_getters.get_artist_name(songH5File))
song.artistPlayMeID = str(hdf5_getters.get_artist_playmeid(songH5File))
song.audioMD5 = str(hdf5_getters.get_audio_md5(songH5File))
song.danceability = str(hdf5_getters.get_danceability(songH5File))
song.duration = str(hdf5_getters.get_duration(songH5File))
song.endOfFadeIn = str(hdf5_getters.get_end_of_fade_in(songH5File))
song.energy = str(hdf5_getters.get_energy(songH5File))
song.key = str(hdf5_getters.get_key(songH5File))
song.keyConfidence = str(hdf5_getters.get_key_confidence(songH5File))
song.segementsConfidence = str(
hdf5_getters.get_segments_confidence(songH5File))
song.segementsConfidence = str(
hdf5_getters.get_sections_confidence(songH5File))
song.loudness = str(hdf5_getters.get_loudness(songH5File))
song.mode = str(hdf5_getters.get_mode(songH5File))
song.modeConfidence = str(hdf5_getters.get_mode_confidence(songH5File))
song.release = str(hdf5_getters.get_release(songH5File))
song.releaseDigitalID = str(
hdf5_getters.get_release_7digitalid(songH5File))
song.songHotttnesss = str(hdf5_getters.get_song_hotttnesss(songH5File))
song.startOfFadeOut = str(hdf5_getters.get_start_of_fade_out(songH5File))
song.tempo = str(hdf5_getters.get_tempo(songH5File))
song.timeSignature = str(hdf5_getters.get_time_signature(songH5File))
song.timeSignatureConfidence = str(
hdf5_getters.get_time_signature_confidence(songH5File))
song.title = str(hdf5_getters.get_title(songH5File))
song.trackID = str(hdf5_getters.get_track_id(songH5File))
song.trackDigitalID = str(hdf5_getters.get_track_7digitalid(songH5File))
song.year = str(hdf5_getters.get_year(songH5File))
#-------------------------------array attributes--------------------------------------
#array float
song.beatsStart_mean, song.beatsStart_var = convert_array_to_meanvar(
hdf5_getters.get_beats_start(songH5File))
#array float
song.artistTermsFreq_mean, song.artistTermsFreq_var = convert_array_to_meanvar(
hdf5_getters.get_artist_terms_freq(songH5File))
#array float
song.artistTermsWeight_mean, song.artistTermsWeight_var = convert_array_to_meanvar(
hdf5_getters.get_artist_terms_weight(songH5File))
#array int
song.artistmbTagsCount_mean, song.artistmbTagsCount_var = convert_array_to_meanvar(
hdf5_getters.get_artist_mbtags_count(songH5File))
#array float
song.barsConfidence_mean, song.barsConfidence_var = convert_array_to_meanvar(
hdf5_getters.get_bars_confidence(songH5File))
#array float
song.barsStart_mean, song.barsStart_var = convert_array_to_meanvar(
hdf5_getters.get_bars_start(songH5File))
#array float
song.beatsConfidence_mean, song.beatsConfidence_var = convert_array_to_meanvar(
hdf5_getters.get_beats_confidence(songH5File))
#array float
song.sectionsConfidence_mean, song.sectionsConfidence_var = convert_array_to_meanvar(
hdf5_getters.get_sections_confidence(songH5File))
#array float
song.sectionsStart_mean, song.sectionsStart_var = convert_array_to_meanvar(
hdf5_getters.get_sections_start(songH5File))
#array float
song.segmentsConfidence_mean, song.segmentsConfidence_var = convert_array_to_meanvar(
hdf5_getters.get_segments_confidence(songH5File))
#array float
song.segmentsLoudness_mean, song.segmentsLoudness_var = convert_array_to_meanvar(
hdf5_getters.get_segments_loudness_max(songH5File))
#array float
song.segmentsLoudnessMaxTime_mean, song.segmentsLoudnessMaxTime_var = convert_array_to_meanvar(
hdf5_getters.get_segments_loudness_max_time(songH5File))
#array float
song.segmentsLoudnessMaxStart_mean, song.segmentsLoudnessMaxStart_var = convert_array_to_meanvar(
hdf5_getters.get_segments_loudness_start(songH5File))
#array float
song.segmentsStart_mean, song.segmentsStart_var = convert_array_to_meanvar(
hdf5_getters.get_segments_start(songH5File))
#array float
song.tatumsConfidence_mean, song.tatumsConfidence_var = convert_array_to_meanvar(
hdf5_getters.get_tatums_confidence(songH5File))
#array float
song.tatumsStart_mean, song.tatumsStart_var = convert_array_to_meanvar(
hdf5_getters.get_tatums_start(songH5File))
#array2d float
song.segmentsTimbre_mean, song.segmentsTimbre_var = covert_2darray_to_meanvar(
hdf5_getters.get_segments_timbre(songH5File))
#array2d float
song.segmentsPitches_mean, song.segmentsPitches_var = covert_2darray_to_meanvar(
hdf5_getters.get_segments_pitches(songH5File))
#------------------------array string attributes------------------------
song.similarArtists = convert_array_to_string(
hdf5_getters.get_similar_artists(songH5File)) #array string
song.artistTerms = convert_array_to_string(
hdf5_getters.get_artist_terms(songH5File)) #array string
song.artistmbTags = convert_array_to_string(
hdf5_getters.get_artist_mbtags(songH5File)) #array string
return song
process_completion += 1
else:
process_completion += 1
tempPath = os.path.abspath(os.path.join(root,name))
h5file = hdf5_getters.open_h5_file_read(tempPath)
#meta info
track_id_str = hdf5_getters.get_track_id(h5file)
song_id_str = hdf5_getters.get_song_id(h5file)
year = hdf5_getters.get_year(h5file)
#genre info
artist_terms = hdf5_getters.get_artist_terms(h5file)
artist_mbtags = hdf5_getters.get_artist_mbtags(h5file)
artist_mbtags_count = hdf5_getters.get_artist_mbtags_count(h5file)
artist_terms_freq = hdf5_getters.get_artist_terms_freq(h5file)
artist_terms_weight = hdf5_getters.get_artist_terms_weight(h5file)
#factoring in mbtags counts & thresholding artist_terms
idx = 0
for countVal in artist_mbtags_count:
for rep in range(0,countVal-1):
artist_mbtags = numpy.append(artist_mbtags,artist_mbtags[idx])
idx += 1
for i in range(0,len(artist_terms)):
if artist_terms_freq[i]*artist_terms_weight[i] < 0.16: #0.4*0.4 = 0.16
artist_terms[i]=""
# finding genre
song.artist7digitalid = remove_trap_characters(
str(hdf5_getters.get_artist_7digitalid(songH5File)))
temp = hdf5_getters.get_artist_terms(songH5File)
song.artistTerms = remove_trap_characters(str(list(temp)))
song.artistTermsCount = get_list_length(temp)
song.artistTermsFreq = remove_trap_characters(
str(list(hdf5_getters.get_artist_terms_freq(songH5File))))
song.artistTermsWeight = remove_trap_characters(
str(list(hdf5_getters.get_artist_terms_weight(songH5File))))
temp = hdf5_getters.get_artist_mbtags(songH5File)
song.artistMBTags = remove_trap_characters(str(list(temp)))
song.artistMBTagsOuterCount = get_list_length(temp)
song.artistMBTagsCount = remove_trap_characters(
str(list(hdf5_getters.get_artist_mbtags_count(songH5File))))
song.analysisSampleRate = remove_trap_characters(
str(hdf5_getters.get_analysis_sample_rate(songH5File)))
song.audioMD5 = remove_trap_characters(
str(hdf5_getters.get_audio_md5(songH5File)))
song.endOfFadeIn = remove_trap_characters(
str(hdf5_getters.get_end_of_fade_in(songH5File)))
song.startOfFadeOut = remove_trap_characters(
str(hdf5_getters.get_start_of_fade_out(songH5File)))
song.energy = remove_trap_characters(
str(hdf5_getters.get_energy(songH5File)))
song.release = remove_trap_characters(
str(hdf5_getters.get_release(songH5File)))
song.release7digitalid = remove_trap_characters(
str(hdf5_getters.get_release_7digitalid(songH5File)))
song.songHotness = remove_trap_characters(
h5 = GETTERS.open_h5_file_read(f)
num_songs = GETTERS.get_num_songs(h5)
print f, num_songs
for i in range(num_songs):
analysis_sample_rate = GETTERS.get_analysis_sample_rate(h5, i)
artist_7digitalid = GETTERS.get_artist_7digitalid(h5, i)
artist_familiarity = GETTERS.get_artist_familiarity(h5, i)
artist_hotttnesss = GETTERS.get_artist_hotttnesss(h5, i)
artist_id = GETTERS.get_artist_id(h5, i)
artist_latitude = GETTERS.get_artist_latitude(h5, i)
artist_location = GETTERS.get_artist_location(h5, i)
artist_longitude = GETTERS.get_artist_longitude(h5, i)
artist_mbid = GETTERS.get_artist_mbid(h5, i)
artist_mbtags = ','.join(str(e) for e in GETTERS.get_artist_mbtags(h5, i)) # array
artist_mbtags_count = ','.join(str(e) for e in GETTERS.get_artist_mbtags_count(h5, i)) # array
artist_name = GETTERS.get_artist_name(h5, i)
artist_playmeid = GETTERS.get_artist_playmeid(h5, i)
artist_terms = ','.join(str(e) for e in GETTERS.get_artist_terms(h5, i)) # array
#artist_terms_freq = ','.join(str(e) for e in GETTERS.get_artist_terms_freq(h5, i)) # array
#artist_terms_weight = ','.join(str(e) for e in GETTERS.get_artist_terms_weight(h5, i)) # array
#audio_md5 = GETTERS.get_audio_md5(h5, i)
#bars_confidence = ','.join(str(e) for e in GETTERS.get_bars_confidence(h5, i)) # array
#bars_start = ','.join(str(e) for e in GETTERS.get_bars_start(h5, i)) # array
#beats_confidence = ','.join(str(e) for e in GETTERS.get_beats_confidence(h5, i)) # array
#beats_start = ','.join(str(e) for e in GETTERS.get_beats_start(h5, i)) # array
danceability = GETTERS.get_danceability(h5, i)
duration = GETTERS.get_duration(h5, i)
end_of_fade_in = GETTERS.get_end_of_fade_in(h5, i)
energy = GETTERS.get_energy(h5, i)
key = GETTERS.get_key(h5, i)
def hd5_single_random_file_parser():
# Open an h5 file in read mode
h5 = hdf5_getters.open_h5_file_read(
'/home/skalogerakis/Documents/MillionSong/MillionSongSubset/A/M/G/TRAMGDX12903CEF79F.h5'
)
function_tracker = filter(
lambda x: x.startswith('get'),
hdf5_getters.__dict__.keys()) # Detects all the getter functions
for f in function_tracker: # Print everything in function tracker
print(f)
# First effort to check what each field contains.
print() # 55 available fields (exluding number of songs fields)
print("Num of songs -- ",
hdf5_getters.get_num_songs(h5)) # One song per file
print("Title -- ",
hdf5_getters.get_title(h5)) # Print the title of a specific h5 file
print("Artist familiarity -- ", hdf5_getters.get_artist_familiarity(h5))
print("Artist hotness -- ", hdf5_getters.get_artist_hotttnesss(h5))
print("Artist ID -- ", hdf5_getters.get_artist_id(h5))
print("Artist mbID -- ", hdf5_getters.get_artist_mbid(h5))
print("Artist playmeid -- ", hdf5_getters.get_artist_playmeid(h5))
print("Artist 7DigitalID -- ", hdf5_getters.get_artist_7digitalid(h5))
print("Artist latitude -- ", hdf5_getters.get_artist_latitude(h5))
print("Artist longitude -- ", hdf5_getters.get_artist_longitude(h5))
print("Artist location -- ", hdf5_getters.get_artist_location(h5))
print("Artist Name -- ", hdf5_getters.get_artist_name(h5))
print("Release -- ", hdf5_getters.get_release(h5))
print("Release 7DigitalID -- ", hdf5_getters.get_release_7digitalid(h5))
print("Song ID -- ", hdf5_getters.get_song_id(h5))
print("Song Hotness -- ", hdf5_getters.get_song_hotttnesss(h5))
print("Track 7Digital -- ", hdf5_getters.get_track_7digitalid(h5))
print("Similar artists -- ", hdf5_getters.get_similar_artists(h5))
print("Artist terms -- ", hdf5_getters.get_artist_terms(h5))
print("Artist terms freq -- ", hdf5_getters.get_artist_terms_freq(h5))
print("Artist terms weight -- ", hdf5_getters.get_artist_terms_weight(h5))
print("Analysis sample rate -- ",
hdf5_getters.get_analysis_sample_rate(h5))
print("Audio md5 -- ", hdf5_getters.get_audio_md5(h5))
print("Danceability -- ", hdf5_getters.get_danceability(h5))
print("Duration -- ", hdf5_getters.get_duration(h5))
print("End of Fade -- ", hdf5_getters.get_end_of_fade_in(h5))
print("Energy -- ", hdf5_getters.get_energy(h5))
print("Key -- ", hdf5_getters.get_key(h5))
print("Key Confidence -- ", hdf5_getters.get_key_confidence(h5))
print("Loudness -- ", hdf5_getters.get_loudness(h5))
print("Mode -- ", hdf5_getters.get_mode(h5))
print("Mode Confidence -- ", hdf5_getters.get_mode_confidence(h5))
print("Start of fade out -- ", hdf5_getters.get_start_of_fade_out(h5))
print("Tempo -- ", hdf5_getters.get_tempo(h5))
print("Time signature -- ", hdf5_getters.get_time_signature(h5))
print("Time signature confidence -- ",
hdf5_getters.get_time_signature_confidence(h5))
print("Track ID -- ", hdf5_getters.get_track_id(h5))
print("Segments Start -- ", hdf5_getters.get_segments_start(h5))
print("Segments Confidence -- ", hdf5_getters.get_segments_confidence(h5))
print("Segments Pitches -- ", hdf5_getters.get_segments_pitches(h5))
print("Segments Timbre -- ", hdf5_getters.get_segments_timbre(h5))
print("Segments Loudness max -- ",
hdf5_getters.get_segments_loudness_max(h5))
print("Segments Loudness max time-- ",
hdf5_getters.get_segments_loudness_max_time(h5))
print("Segments Loudness start -- ",
hdf5_getters.get_segments_loudness_start(h5))
print("Sections start -- ", hdf5_getters.get_sections_start(h5))
print("Sections Confidence -- ", hdf5_getters.get_sections_confidence(h5))
print("Beats start -- ", hdf5_getters.get_beats_start(h5))
print("Beats confidence -- ", hdf5_getters.get_beats_confidence(h5))
print("Bars start -- ", hdf5_getters.get_bars_start(h5))
print("Bars confidence -- ", hdf5_getters.get_bars_confidence(h5))
print("Tatums start -- ", hdf5_getters.get_tatums_start(h5))
print("Tatums confidence -- ", hdf5_getters.get_tatums_confidence(h5))
print("Artist mbtags -- ", hdf5_getters.get_artist_mbtags(h5))
print("Artist mbtags count -- ", hdf5_getters.get_artist_mbtags_count(h5))
print("Year -- ", hdf5_getters.get_year(h5))
fields = ['Title', 'Artist ID']
with open('Tester2.csv', 'w', newline='') as csvfile:
csv_writer = csv.writer(csvfile, delimiter=';')
# writing the fields
csv_writer.writerow(fields)
# writing the data rows
csv_writer.writerow(
[hdf5_getters.get_title(h5),
hdf5_getters.get_artist_id(h5)])
h5.close() # close h5 when completed in the end
def getInfo(files):
data = []
build_str = ''
with open(sys.argv[1], 'r') as f:
contents = f.read()
c = contents.split()
f.close()
print("creating csv with following fields:" + contents)
for i in c:
build_str = build_str + i + ','
build_str = build_str[:-1]
build_str = build_str + '\n'
for fil in files:
curFile = getters.open_h5_file_read(fil)
d2 = {}
get_table = {'track_id': getters.get_track_id(curFile), 'segments_pitches': getters.get_segments_pitches(curFile), 'time_signature_confidence': getters.get_time_signature_confidence(curFile), 'song_hotttnesss': getters.get_song_hotttnesss(curFile), 'artist_longitude': getters.get_artist_longitude(curFile), 'tatums_confidence': getters.get_tatums_confidence(curFile), 'num_songs': getters.get_num_songs(curFile), 'duration': getters.get_duration(curFile), 'start_of_fade_out': getters.get_start_of_fade_out(curFile), 'artist_name': getters.get_artist_name(curFile), 'similar_artists': getters.get_similar_artists(curFile), 'artist_mbtags': getters.get_artist_mbtags(curFile), 'artist_terms_freq': getters.get_artist_terms_freq(curFile), 'release': getters.get_release(curFile), 'song_id': getters.get_song_id(curFile), 'track_7digitalid': getters.get_track_7digitalid(curFile), 'title': getters.get_title(curFile), 'artist_latitude': getters.get_artist_latitude(curFile), 'energy': getters.get_energy(curFile), 'key': getters.get_key(curFile), 'release_7digitalid': getters.get_release_7digitalid(curFile), 'artist_mbid': getters.get_artist_mbid(curFile), 'segments_confidence': getters.get_segments_confidence(curFile), 'artist_hotttnesss': getters.get_artist_hotttnesss(curFile), 'time_signature': getters.get_time_signature(curFile), 'segments_loudness_max_time': getters.get_segments_loudness_max_time(curFile), 'mode': getters.get_mode(curFile), 'segments_loudness_start': getters.get_segments_loudness_start(curFile), 'tempo': getters.get_tempo(curFile), 'key_confidence': getters.get_key_confidence(curFile), 'analysis_sample_rate': getters.get_analysis_sample_rate(curFile), 'bars_confidence': getters.get_bars_confidence(curFile), 'artist_playmeid': getters.get_artist_playmeid(curFile), 'artist_terms_weight': getters.get_artist_terms_weight(curFile), 'segments_start': getters.get_segments_start(curFile), 'artist_location': getters.get_artist_location(curFile), 'loudness': getters.get_loudness(curFile), 'year': getters.get_year(curFile), 'artist_7digitalid': getters.get_artist_7digitalid(curFile), 'audio_md5': getters.get_audio_md5(curFile), 'segments_timbre': getters.get_segments_timbre(curFile), 'mode_confidence': getters.get_mode_confidence(curFile), 'end_of_fade_in': getters.get_end_of_fade_in(curFile), 'danceability': getters.get_danceability(curFile), 'artist_familiarity': getters.get_artist_familiarity(curFile), 'artist_mbtags_count': getters.get_artist_mbtags_count(curFile), 'tatums_start': getters.get_tatums_start(curFile), 'artist_id': getters.get_artist_id(curFile), 'segments_loudness_max': getters.get_segments_loudness_max(curFile), 'bars_start': getters.get_bars_start(curFile), 'beats_start': getters.get_beats_start(curFile), 'artist_terms': getters.get_artist_terms(curFile), 'sections_start': getters.get_sections_start(curFile), 'beats_confidence': getters.get_beats_confidence(curFile), 'sections_confidence': getters.get_sections_confidence(curFile)}
tid = fil.split('/')[-1].split('.')[0]
# print(c)
for i in c:
if i in get_table:
d2[i] = get_table[i]
d2[i] = str(d2[i]).replace('\n','')
build_str = build_str + d2[i] + ','
else:
print('error: unspecified field')
exit(0)
build_str = build_str[:-1]
# print(build_str[:-1])
build_str = build_str + '\n'
curFile.close()
build_str = build_str.replace('b','').replace("'",'').replace('"','')
return (build_str)
