def color_cycle():
led.pixels *= 0
#led.pixels = np.stack(np.tile(255, (1, config.N_PIXELS)), np.tile(0, (3, config.N_PIXELS)))
a = np.zeros(shape=(3, config.N_PIXELS))
led.pixels = np.append(a, np.tile(255, (1, config.N_PIXELS)), axis=0)
while True:
led.pixels = np.roll(led.pixels, 1, axis=0)
led.update()
time.sleep(1)
def microphone_update(audio_samples):
global y_roll, prev_rms, prev_exp, prev_fps_update
# Normalize samples between 0 and 1
y = audio_samples / 2.0**15
# Construct a rolling window of audio samples
y_roll[:-1] = y_roll[1:]
y_roll[-1, :] = np.copy(y)
y_data = np.concatenate(y_roll, axis=0).astype(np.float32)
vol = np.max(np.abs(y_data))
if vol < config.MIN_VOLUME_THRESHOLD:
#print('No audio input. Volume below threshold. Volume:', vol)
#led.pixels = np.tile(0, (4, config.N_PIXELS))
led.pixels *= 0
#led.pixels = np.zeros(shape=(4, config.N_PIXELS), dtype=np.int8)
led.update()
else:
# Transform audio input into the frequency domain
N = len(y_data)
N_zeros = 2**int(np.ceil(np.log2(N))) - N
# Pad with zeros until the next power of two
y_data *= fft_window
#detect_bpm(y_data)
y_padded = np.pad(y_data, (0, N_zeros), mode='constant')
YS = np.abs(np.fft.rfft(y_padded)[:N // 2])
# Construct a Mel filterbank from the FFT data
mel = np.atleast_2d(YS).T * dsp.mel_y.T
# Scale data to values more suitable for visualization
# mel = np.sum(mel, axis=0)
mel = np.sum(mel, axis=0)
mel = mel**2.0
# Gain normalization
mel_gain.update(np.max(gaussian_filter1d(mel, sigma=1.0)))
mel /= mel_gain.value
mel = mel_smoothing.update(mel)
# Map filterbank output onto LED strip
output = visualization_effect(mel)
led.pixels = output
led.update()
if config.USE_GUI:
# Plot filterbank output
x = np.linspace(config.MIN_FREQUENCY, config.MAX_FREQUENCY, len(mel))
mel_curve.setData(x=x, y=fft_plot_filter.update(mel))
# Plot the color channels
r_curve.setData(y=led.pixels[0])
g_curve.setData(y=led.pixels[1])
b_curve.setData(y=led.pixels[2])
if config.USE_GUI:
app.processEvents()
if config.DISPLAY_FPS:
fps = frames_per_second()
if time.time() - 0.5 > prev_fps_update:
prev_fps_update = time.time()
print('FPS {:.0f} / {:.0f}'.format(fps, config.FPS))
def single_color(color='white'):
rgb = askcolor(title="Tkinter Color Chooser")
a = np.empty((0, config.N_PIXELS), int)
a = np.append(a, np.tile(int(rgb[0][0]), (1, config.N_PIXELS)), axis=0)
a = np.append(a, np.tile(int(rgb[0][1]), (1, config.N_PIXELS)), axis=0)
a = np.append(a, np.tile(int(rgb[0][2]), (1, config.N_PIXELS)), axis=0)
a = np.append(a, np.tile(0, (1, config.N_PIXELS)), axis=0)
led.pixels = a
led.update()
time.sleep(1)
led.update()
def roll():
single_color_full_bri = np.zeros
# Turn all pixels off
led.pixels *= 0
led.pixels[0, 0] = 255 # Set 1st pixel red
led.pixels[1, 1] = 255 # Set 2nd pixel green
led.pixels[2, 2] = 255 # Set 3rd pixel blue
led.pixels[3, 3] = 255 # Set 3rd pixel white
print('Starting LED strand test')
while True:
led.pixels = np.roll(led.pixels, 1, axis=1)
led.update()
time.sleep(0.01)
energy_label.setText('Energy', color=inactive_color)
scroll_label.setText('Scroll', color=inactive_color)
spectrum_label.setText('Spectrum', color=inactive_color)
bpm_label.setText('BPM', color=active_color)
# Create effect "buttons" (labels with click event)
energy_label = pg.LabelItem('Energy')
scroll_label = pg.LabelItem('Scroll')
spectrum_label = pg.LabelItem('Spectrum')
bpm_label = pg.LabelItem('BPM')
energy_label.mousePressEvent = energy_click
scroll_label.mousePressEvent = scroll_click
spectrum_label.mousePressEvent = spectrum_click
bpm_label.mousePressEvent = bpm_click
energy_click(0)
# Layout
layout.nextRow()
layout.addItem(freq_label, colspan=4)
layout.nextRow()
layout.addItem(freq_slider, colspan=4)
layout.nextRow()
layout.addItem(energy_label)
layout.addItem(scroll_label)
layout.addItem(spectrum_label)
layout.addItem(bpm_label)
# Initialize LEDs
led.update()
# Start listening to live audio stream
microphone.start_stream(microphone_update)
def clear_all():
led.pixels *= 0
led.update()