def __init__(self, pitch):
self.ji_intervals = np.array([
-2400, -2289, -2197, -2085, -2014, -1902, -1791, -1699, -1587,
-1516, -1404, -1312, -1200, -1089, -997, -885, -814, -702, -591,
-499, -387, -316, -204, -112, 0, 111, 203, 315, 386, 498, 609, 701,
813, 884, 996, 1088, 1200, 1311, 1403, 1515, 1586, 1698, 1809,
1901, 2013, 2084, 2196, 2288, 2400, 2511, 2603, 2715, 2786, 2898,
3009, 3101, 3213, 3284, 3396, 3488, 3600, 3711, 3803, 3915, 3986,
4098, 4209, 4301, 4413, 4484, 4596, 4688, 4800
])
self.pitch_obj = intonation.Pitch(pitch[:, 0], pitch[:, 1])
self.rec = intonation.Recording(self.pitch_obj)
self.intonation_profile = None
def hz2centsRafa(timeVec,
pitchInHz,
tonic=261.626,
plotHisto=False,
saveHisto=False,
title=None):
# with open(document, 'r') as f:
# data = f.readlines()
#
# data2 = []
# for i in range(len(data)):
# x = []
# time = float(data[i].split('\t')[0])
# x.append(time)
# value = float(data[i].split('\t')[1].rstrip('\r\n'))
# x.append(value)
# data2.append(x)
cents = [-10000] * len(pitchInHz)
for i in xrange(len(pitchInHz)):
if pitchInHz[i] > 0:
cents[i] = 1200 * np.log2(1.0 * pitchInHz[i] / tonic)
data = zip(timeVec, cents)
data_hist = np.array(data)
pitch_obj = intonation.Pitch(data_hist[:, 0], data_hist[:, 1])
#print data_hist[:,0], data_hist[:,1]
rec_obj = intonation.Recording(pitch_obj)
rec_obj.compute_hist()
# draw this histogram
rec_obj.histogram.plot()
if not isinstance(title, unicode):
title = title.decode('utf8') # decode the ascii to utf8
if plotHisto == True:
drawTitle(title, fontproperties=droidTitle)
show()
if saveHisto == True:
drawTitle(title, fontproperties=droidTitle)
savefig(title[:-4] + '-singingHisto.png', dpi=150, bbox_inches='tight')
rec_obj.histogram.get_peaks()
peaks = rec_obj.histogram.peaks
return peaks['peaks']
# ##Have a look at the data, it always does good! # <codecell> plot(data[52000:53000, 0], data[52000:53000, 1]) ylim(200, 1000) # <markdowncell> # ##Load the data into a pitch object # You can avail a number of different method on pitch object to study different aspects of intervals. Let's also look at what methods are # available and what they do. # <codecell> pitch_obj = intonation.Pitch(data[:, 0], data[:, 1]) help(pitch_obj) # <markdowncell> # ##Load the recording object # Recording object takes the pitch object, and defines methods that access pitch data and functions defined over it, to create # histogram and intonation profile of the corresponding recording. Load it and check the methods available on it. # <codecell> rec_obj = intonation.Recording(pitch_obj) help(rec_obj) # <markdowncell>