def createSnareFft():
# read in the snare drum sample
files = glob.glob('./snare_samples/*.wav')
matrix = numpy.array([])
for filename in files:
print filename
rate, data = wave_reader.readWav(filename)
data = wave_reader.stereoToMono(data)
features = analyzer.getFrequencies(data)
matrix = build_data.addToFeatureMatrix(matrix, features[0:2000])
build_data.saveFile('snaredata.csv', matrix)
def readSong(filename, segTime = 0.05): # read in the input song rate, data = wave_reader.readWav(filename) data = wave_reader.stereoToMono(data) # sample every 0.1 seconds by default segSize = segTime * rate matrix = numpy.array([]) print 'reading in song...' start = 0 end = segSize for i in range(0, int(math.floor(len(data)/segSize))): data_seg = data[start:end] start += segSize end += segSize features = analyzer.getFrequencies(data_seg) matrix = build_data.addToFeatureMatrix(matrix, features[0:2000]) outfile = os.path.splitext(filename)[0] + '.csv' build_data.saveFile(outfile, matrix) return matrix
if note_amp[note_freq_sort[j]] < max_amp * 0.3:
break
if note == None or note_name.index(note) > note_freq_sort[j]:
if last_note == None or abs(note_name.index(last_note) - note_freq_sort[j]) <= 7:
note = note_name[note_freq_sort[j]]
f.write("%.4f\n"%np.sum(note_amp))
if note != last_note:
if last_note != None:
toRtn.append((last_note, start_time, time))
last_note = note
start_time = time"""
f.close()
# if last_note != None:
# toRtn.append((last_note, start_time, t[1]*len(t)))
#print toRtn
#print len(toRtn)
return toRtn
if __name__ == "__main__":
# f = open("note_freq.txt", 'w')
# for i in range(len(note_name)):
# f.write("%s: %.4f\n" % (note_name[i], note_freq[i]))
_, _, fr, data = readWav("rec")
# qualify(data, fr)
# print("hello")
recognize(data, fr, 195)
# print(freqToNote(500))
def wav2mid(wav_file_name, tempo=120):
_, _, fr, data = readWav(wav_file_name)
note_time_list = recognize(data, fr, tempo)
outMidPath = writeMid(note_time_list, tempo)
print outMidPath
