class Expression(Block):
args = List(Input)
input = Input()
def init(self, func, *args):
# HACK: should not directly reference lupa here
import lupa
if lupa.lua_type(args) == 'table':
args = args.values()
print ('Expression: ', func, args)
self.func = func
self.args = list(args)
self.output = Signal()
# Workaround for list event bug
self.input = self.args[0]
def _input_changed(self):
self.output.copy_traits(self.input, ['label', 'color'])
def process(self):
args = [chan.last for chan in self.args]
self.output.append([self.func(*args)])
self.output.process()
class PulseAnalyzer(Block):
input = Input()
def init(self, input):
self.input = input
self.output = Signal()
self.bpm = Signal()
self.gradient = Signal()
self.pulse = Signal()
self.last_beat = -1
self.timestamp = 0
def _input_changed(self):
self.output.copy_traits(self.input, ['label', 'color'])
def process(self):
avg = np.average(self.output.buffer)
max = np.max(self.output.buffer)
self.timestamp += 1
self.gradient.append([self.input.buffer[-1] - self.input.buffer[-2]])
buf = np.power(self.gradient.buffer[-50:], 2)
s = np.sum(np.hanning(50)[:50] * buf)
self.output.append([s])
for i, sample in enumerate(self.output.new):
new = 1.0 if sample > max * 0.7 else 0.0
self.pulse.append([new])
if new > self.pulse.buffer[-2]:
diff = self.timestamp - self.last_beat
bpm = 1.0 / (diff / 250.) * 60
self.bpm.append([bpm])
self.bpm.process()
print('beat event', diff, bpm, self.timestamp, self.last_beat)
self.last_beat = self.timestamp
self.output.process()
self.gradient.process()
class PulseAnalyzer(Block):
input = Input()
def init(self, input):
self.input = input
self.output = Signal()
self.bpm = Signal()
self.gradient = Signal()
self.pulse = Signal()
self.last_beat = -1
self.timestamp = 0
def _input_changed(self):
self.output.copy_traits(self.input, ["label", "color"])
def process(self):
avg = np.average(self.output.buffer)
max = np.max(self.output.buffer)
self.timestamp += 1
self.gradient.append([self.input.buffer[-1] - self.input.buffer[-2]])
buf = np.power(self.gradient.buffer[-50:], 2)
s = np.sum(np.hanning(50)[:50] * buf)
self.output.append([s])
for i, sample in enumerate(self.output.new):
new = 1.0 if sample > max * 0.7 else 0.0
self.pulse.append([new])
if new > self.pulse.buffer[-2]:
diff = self.timestamp - self.last_beat
bpm = 1.0 / (diff / 250.0) * 60
self.bpm.append([bpm])
self.bpm.process()
print("beat event", diff, bpm, self.timestamp, self.last_beat)
self.last_beat = self.timestamp
self.output.process()
self.gradient.process()
class RMS(Block): input = Input() avg_size = Int(42) def init(self, input): self.output = Signal() self.input = input def _input_changed(self): self.output.copy_traits(self.input, ['label', 'color']) def process(self): buf = np.array(self.input.buffer[-self.avg_size:]) rms = sum(buf ** 2) / len(buf) avg = np.sqrt(rms) self.output.append([avg]) self.output.process()
