def adder(rate=11025, duration=1, sources=[], amplitude=1):
samples = int(duration*rate)
data = np.zeros(samples)
d_amplitude = get_buffer(samples, amplitude)
signals = [get_buffer(samples, source) for source in sources]
for i in range(samples):
val = 0
for signal in signals:
val += signal[i]
data[i] = val*d_amplitude[i]
return data
def sample_and_hold(rate=11025, duration=1, source=1, trigger=1):
samples = int(duration * rate)
data = np.zeros(samples)
d_source = get_buffer(samples, source)
d_trigger = get_buffer(samples, trigger)
data[0] = d_source[0]
for i in range(1, samples):
if d_trigger[i - 1] > 0 and d_trigger[i] <= 0:
data[i] = d_source[i]
else:
data[i] = data[i - 1]
return data
def sine_wave(rate=11025, duration=1, frequency=400, amplitude=1, ratio=0.5, offset=0):
samples = int(duration*rate)
data = np.zeros(samples)
t = 0
d_frequency = get_buffer(samples, frequency)
d_amplitude = get_buffer(samples, amplitude)
d_offset = get_buffer(samples, offset)
for i in range(samples):
t += d_frequency[i]/rate
t %= 1
data[i] = d_offset[i] + d_amplitude[i]*math.sin(t*2*math.pi)
return data
def square_wave(rate=11025, duration=1, frequency=400, amplitude=1, ratio=0.5, offset=0):
samples = int(duration*rate)
data = np.zeros(samples)
t = 0
d_frequency = get_buffer(samples, frequency)
d_amplitude = get_buffer(samples, amplitude)
d_ratio = get_buffer(samples, ratio)
d_offset = get_buffer(samples, offset)
for i in range(samples):
t += d_frequency[i]/rate
t %= 1
data[i] = d_offset[i] + d_amplitude[i]*(1 if t < d_ratio[i] else -1)
return data
def ramp(rate=11025, duration=1, source=1, start=0, end=1):
samples = int(duration*rate)
data = np.zeros(samples)
d_source = get_buffer(samples, source)
for i in range(samples):
t = i/samples
data[i] = d_source[i]*(start + (end-start)*t)
return data
def saw_wave(rate=11025, duration=1, frequency=400, amplitude=1, ratio=0.5, offset=0):
samples = int(duration*rate)
data = np.zeros(samples)
t = 0
d_frequency = get_buffer(samples, frequency)
d_amplitude = get_buffer(samples, amplitude)
d_ratio = get_buffer(samples, ratio)
d_offset = get_buffer(samples, offset)
for i in range(samples):
t += d_frequency[i]/rate
t %= 1
if t < d_ratio[i]:
v = -1 + 2*t/d_ratio[i]
else:
v = 1 - 2*(t-d_ratio[i])/(1-d_ratio[i])
data[i] = d_offset[i] + d_amplitude[i]*v
return data
def modulator(rate=11025, duration=1, sources=[]):
samples = int(duration*rate)
data = np.zeros(samples)
signals = [get_buffer(samples, source) for source in sources]
for i in range(samples):
val = 1
for signal in signals:
val *= signal[i]
data[i] = val
return data
def attack_decay(rate=11025, duration=1, source=1, attack_time=1):
samples = int(duration*rate)
data = np.zeros(samples)
d_source = get_buffer(samples, source)
for i in range(samples):
t = i/rate
if t < attack_time:
data[i] = d_source[i]*t / attack_time
else:
data[i] = d_source[i]*(duration-t)/(duration - attack_time)
return data
def sequencer(rate=11025, duration=1, inputs=[]):
# Calculate the total number of output samples. This will be *at least* duration*rate,
# but may be more if any input signals extend beyond that.
samples = int(duration * rate)
for source, start in inputs:
if is_buffer_signal(source):
end = int(start * rate) + get_signal_length(source)
if end > samples:
samples = end;
else:
raise TypeError('sequencer sources cannot be constants')
data = np.zeros(samples)
for source, start in inputs:
start_sample = int(start * rate)
transfer_samples = get_signal_length(source)
signal = get_buffer(transfer_samples, source)
for i in range(transfer_samples):
data[i + start_sample] += signal[i]
return data
