# Muhammad Hafiz Wan Rosli
# Media Arts & Technology
# Music Information Retrieval
# MAT240E: Homework05 - Audio Feature Extraction III

#Analysis of pitch and tempo detection using essentia's built in algorithms
#http://essentia.upf.edu/

#Experiments on different methods of segmenting signals based on sudden tempo changes for auto segmentation
#Using essentia's BeatTrackerMultiFeature(), RhythmExtractor2013() & OnsetRate()
#Plots of detected tatums and onsets
#More explorations with texture windows and euclidean distances are done in Homework06

from essentia import *
from essentia.standard import *
from scipy.signal import decimate
import os
%pylab inline

import matplotlib as mpl
mpl.rcParams['figure.figsize'] = (16,4)

loader = essentia.standard.MonoLoader(filename = './Music/iTunes/iTunes Media/Music/Ravi Shankar/Master Of Sitar/01 Raag Alahya Bilawal (Early Morning Raag).mp3')
audio = loader()

sampleRate = 44100
audioSnippet = audio[0*44100:60*44100]
sample_dur_secs = len(audioSnippet)/ float(sampleRate)
win_size=1024
hop = 512
window_start = arange(0, len(audioSnippet), hop)
w = Windowing(type = 'hann')

pitchconfs = []
f0= []

spectrum = Spectrum()
pitchyin = PitchYinFFT()

for frame in FrameGenerator(audioSnippet, frameSize = 1024, hopSize = 512):
    pitch, pconfidence = pitchyin(spectrum(w(frame)))
    f0.append(pitch)
    pitchconfs.append(pconfidence)

plot(linspace(0, sample_dur_secs, len(f0)), f0)

tonicICM = TonicIndianArtMusic()
tonic = tonicICM(audioSnippet)

tonic

beatTrack = BeatTrackerMultiFeature()
rhythmExtractor = RhythmExtractor2013()

#for frame in FrameGenerator(audio[0: 10*44100], frameSize = 1024, hopSize = 512):
bpm, ticks, confidence, estimates, bpmintervals = rhythmExtractor(audioSnippet)
#ticks, tConfidence = beatTrack(audioSnippet)
    #ticks.append(tick)
    #tickConfs.append(tConfidence)

plot(linspace(0, sample_dur_secs, len(estimates)), estimates)
twinx()
plot(linspace(0, sample_dur_secs, len(bpmintervals)), bpmintervals, color = 'r')

confidence

plot(linspace(0, sample_dur_secs, len(audioSnippet)), audioSnippet)
#plot(linspace(0, sample_dur_secs, len(audioSnippet)), audioSnippet)
for tick in ticks:
    axvline(tick, linewidth=1, color='r')

distanceBetweenTicks=[]
for i in ticks:
    distance = abs(ticks[i] - ticks[i-1])
    distanceBetweenTicks.append(distance)

plot(linspace(0, sample_dur_secs, len(audioSnippet)), audioSnippet)
#for tick in ticks:
#    axvline(tick, linewidth=1, color='r')
plot(linspace(0, sample_dur_secs, len(distanceBetweenTicks)),distanceBetweenTicks, color = 'g')
axvline((argmax(distanceBetweenTicks[:]) / float(len(distanceBetweenTicks))) * sample_dur_secs, linewidth=3, color='k', alpha = 0.5)
#xlim(10,30)

onsetDetector = OnsetRate()
onsets, onsetRate = onsetDetector(audioSnippet)

plot(linspace(0, sample_dur_secs, len(audioSnippet)), audioSnippet, color = 'b')
#plot(linspace(0, sample_dur_secs, len(audioSnippet)), audioSnippet)
for onset in onsets:
    axvline(onset, linewidth=1, color = 'g')
for tick in ticks:
    axvline(tick, linewidth=1, color = 'r')
#xlim(40,60)
#ylim(1,-1)

def onsetVStick(input_sig):
    sampleRate = 44100
    sample_dur_secs = len(input_sig)/ float(sampleRate)
    beatTrack = BeatTrackerMultiFeature()
    rhythmExtractor = RhythmExtractor2013()
    onsetDetector = OnsetRate()

    bpm, ticks, confidence, estimates, bpmintervals = rhythmExtractor(input_sig)
    onsets, onsetRate = onsetDetector(input_sig)

    plot(linspace(0, sample_dur_secs, len(input_sig)), input_sig, color = 'k')
    for onset in onsets:
        axvline(onset, linewidth=1, color='r', alpha = '0.7')
    for tick in ticks:
        axvline(tick, linewidth=1, color='w', alpha = '0.9')

rShankar = []
for root, dirs, files in os.walk('./Music/iTunes/iTunes Media/Music/Ravi Shankar/Master Of Sitar'):
    for name in files:
        loader = essentia.standard.MonoLoader(filename = os.path.join(root, name))
        rShankar.append(loader())

#detected onsets vs detected ticks

onsetVStick(rShankar[0][0: 30*sampleRate])

onsetVStick(rShankar[1][30*sampleRate: 60*sampleRate])

onsetVStick(rShankar[2][60*sampleRate: 90*sampleRate])

onsetVStick(rShankar[3][90*sampleRate: 120*sampleRate])