CHORDS = [ (A2, B3, G5),
(G2, B3, A5),
(F2, C, A5),
(F2, D, G5),
(E2, D, B5),
(F2, C, B5),
(F2, B3, A5),
(A2, B3, G5)
]
db = crashdb.load("data.json")
max_t = max(((max(db['heartbeats'][-1], db['pedals'][-1])), db['breaths'][-1]))
log.info("MAX TIME %s" % util.format_time(max_t))
notes = []
for heartbeat in db['heartbeats']:
pos = heartbeat / max_t
chord_pos = pos * (len(CHORDS) - 1)
p1, p2 = CHORDS[int(math.floor(chord_pos))][0], CHORDS[int(math.ceil(chord_pos))][0]
chord_pos -= int(chord_pos)
chord_pos = ease_in_out(chord_pos)
pitch = p1 if random.random() > chord_pos else p2
notes.append((heartbeat, [1, pitch, 127, util.format_time(heartbeat), chord_pos, p1, p2, get_note_name(pitch)]))
# notes.append((heartbeat + 0.1, [HEARTBEAT_CHANNEL, pitch, 110, util.format_time(heartbeat)]))
for pedal in db['pedals']:
pos = pedal / max_t
def process(t):
log.info("////////// process %s //////////" % t)
filename = "audio_tmp/%s.wav" % t
sample_rate, signal = wavfile.read(filename)
log.info("AUDIO SAMPLES %s" % len(signal))
log.info("SAMPLE RATE %s" % sample_rate)
duration = float(len(signal)) / sample_rate
log.info("AUDIO DURATION %ss" % util.format_time(duration))
signal = (np.array(signal).astype('float') / (2**16 * 0.5)) # assuming 16-bit PCM, -1 - 1
log.info("--> preprocessing")
magnitude = abs(signal)
thresholded_magnitude = (magnitude > THRESHOLD) * magnitude
# level = sp.smooth(thresholded_magnitude, size=10000) # shit -- smooth is too expensive for raspi
level = thresholded_magnitude
log.info("--> scanning")
TOLERANCE = sample_rate / 10 # within a tenth of a second, same sound (poor man's smoothing?)
indexes = []
maxes = []
durations = []
zeros = 0
on_chunk = False
for index, sample in enumerate(level):
if sample > 0.0:
if not on_chunk:
indexes.append(index)
durations.append(0)
maxes.append(0)
on_chunk = True
durations[-1] += 1
if sample > maxes[-1]:
maxes[-1] = sample
zeros = 0
if sample == 0.0:
if on_chunk:
zeros += 1
if zeros == TOLERANCE:
on_chunk = False
events = []
for i in xrange(len(indexes)):
value, t_, duration = maxes[i], t + int(float(indexes[i]) / sample_rate), float(durations[i]) / sample_rate
events.append((value, t_, duration))
for event in events:
log.debug(event)
if 'draw' in config and config['draw']:
from housepy import drawing
log.info("--> drawing")
ctx = drawing.Context(width=2000, height=500, background=(0., 0., 1.), hsv=True, flip=True, relative=True)
ctx.line([(float(i) / len(magnitude), sample) for (i, sample) in enumerate(magnitude)], thickness=1, stroke=(0., 0., 0.5))
ctx.line([(float(i) / len(thresholded_magnitude), sample) for (i, sample) in enumerate(thresholded_magnitude)], thickness=1, stroke=(0., 0., 0.))
ctx.line([(float(i) / len(level), sample) for (i, sample) in enumerate(level)], thickness=1, stroke=(0., 1., 1.))
level = sp.normalize(level)
ctx.line([(float(i) / len(level), sample) for (i, sample) in enumerate(level)], thickness=1, stroke=(0.15, 1., 1.))
ctx.line(0.0, THRESHOLD, 1.0, THRESHOLD, thickness=1, stroke=(0.55, 1., 1.))
ctx.show()
try:
data = []
for event in events:
value, t_, duration = event
data.append({'device': config['device'], 'kind': "sound", 'value': value, 't': t_, 'duration': duration})
response = net.read("http://%s:%s" % (config['server']['host'], config['server']['port']), json.dumps(data))
log.info(response)
except Exception as e:
log.error(log.exc(e))
if config['device'] != "Granu":
os.remove(filename)
ts.append(t)
try:
heartrate = float(trackpoint.findtext("%sHeartRateBpm/%sValue" % tuple([ns]*2)))
except Exception:
heartrate = heartrates[-1] if len(heartrates) else 0.0 # carry over, heartrate doesnt go to 0 (hopefully)
heartrates.append(heartrate)
try:
cadence = float(trackpoint.findtext("%sCadence" % tuple([ns])))
except Exception as e:
cadence = 0.0 # drop to 0, probably stopped
cadences.append(cadence * 2) # two feet!
log.info("DATA START TIME %s UTC" % datetime.datetime.utcfromtimestamp(start_t).strftime("%Y-%m-%d %H:%M:%S"))
num_samples = len(ts)
log.info("NUM DATA SAMPLES %s" % num_samples)
if len(ts) != int(ts[-1]):
log.warning("%s != %s" % (util.format_time(len(ts)), util.format_time(ts[-1])))
log.info("DURATION %s" % (util.format_time(ts[-1])))
log.info("CONVERTING AND SAMPLING")
# clean data
cadences = science.filter_deviations(cadences, positive_only=True)
# heartrates = science.filter_deviations(heartrates)
# normalize data
cadences_norm = science.normalize(cadences)
heartrates_norm = science.normalize(heartrates)
# show
ctx = drawing.Context(2000, 250, relative=True, flip=True)
ctx.line([(float(i) / num_samples, cadences_norm[i]) for i in range(num_samples)], stroke=(0, 0, 255), thickness=2)
log.info("GPX %s" % gpx_filename)
log.info("WAV %s" % wav_filename)
audio_start_dt = datetime.datetime.strptime(wav_filename.split('.')[0].split('/')[-1].replace('_smp', ''), "%Y%m%d %H%M%S")
audio_start_dt = util.to_utc(audio_start_dt)
# get video times
video_start_t, video_end_t = compile_gpx.get_video_times(gpx_filename)
log.info("AUDIO START %s" % audio_start_dt)
audio_start_t = float(calendar.timegm(audio_start_dt.timetuple()))
sample_rate, data = wavfile.read(wav_filename)
log.info("AUDIO SAMPLE RATE %s" % sample_rate)
log.info("AUDIO LENGTH (samples) %s" % len(data))
seconds = float(len(data)) / sample_rate
log.info("AUDIO DURATION %s" % util.format_time(seconds))
skip = video_start_t - audio_start_t
log.info("AUDIO SKIP %s%s" % ('-' if skip < 0 else '', util.format_time(abs(skip))))
# downsample to 60hz
target_sample_rate = 60.0
signal = science.downsample(data, int(sample_rate / target_sample_rate))
log.info("NEW LENGTH (samples) %s" % len(signal))
average = np.average(signal)
reduced = signal - average
reduced = [x if x >= 0 else 0 for x in reduced]
reduced = science.smooth(reduced, window_len=50)
reduced = science.normalize(reduced)
signal = science.normalize(signal)
log.info("DETECTING PEAKS")