def audio_data_updated(self, data):
# Calculate the low, mids, and high indexes scaling based on the pixel count
intensities = np.array([
np.mean(data.melbank_lows()),
np.mean(data.melbank_mids()),
np.mean(data.melbank_highs())
])
self.update_drop_frames()
if intensities[0] - self.filtered_intensities[0] > self._config[
"lows_sensitivity"]:
self.new_drop(randint(0, self.pixel_count - 1),
COLORS.get(self._config['lows_colour']))
if intensities[1] - self.filtered_intensities[1] > self._config[
"mids_sensitivity"]:
self.new_drop(randint(0, self.pixel_count - 1),
COLORS.get(self._config['mids_colour']))
if intensities[2] - self.filtered_intensities[2] > self._config[
"high_sensitivity"]:
self.new_drop(randint(0, self.pixel_count - 1),
COLORS.get(self._config['high_colour']))
self.filtered_intensities = self.intensity_filter.update(intensities)
self.pixels = self.get_drops()
def _generate_bezier_curve(self, gradient_colors, gradient_length):
# Check to see if we have a custom gradient, or a predefined one and
# load the colors accordingly
if isinstance(gradient_colors, str):
gradient_name = gradient_colors.lower()
gradient_colors = []
if GRADIENTS.get(gradient_name):
gradient_colors = GRADIENTS.get(gradient_name)
elif COLORS.get(gradient_name):
gradient_colors = [gradient_name]
if not gradient_colors:
gradient_colors = GRADIENTS.get('spectral')
rgb_list = np.array(
[COLORS[color.lower()] for color in gradient_colors]).T
n_colors = len(rgb_list[0])
t = np.linspace(0.0, 1.0, gradient_length)
polynomial_array = np.array([
self._bernstein_poly(i, n_colors - 1, t)
for i in range(0, n_colors)
])
gradient = np.array([
np.dot(rgb_list[0], polynomial_array),
np.dot(rgb_list[1], polynomial_array),
np.dot(rgb_list[2], polynomial_array)
])
_LOGGER.info(
('Generating new gradient curve for {}'.format(gradient_colors)))
self._gradient_curve = gradient
def _generate_gradient_curve(self, gradient_colors, gradient_length,
repeat):
# Check to see if we have a custom gradient, or a predefined one and
# load the colors accordingly
if isinstance(gradient_colors, str):
gradient_name = gradient_colors
gradient_colors = []
if GRADIENTS.get(gradient_name):
gradient_colors = GRADIENTS.get(gradient_name).get("colors")
#gradient_method = GRADIENTS.get(gradient_name).get("method", gradient_method)
elif COLORS.get(gradient_name):
gradient_colors = [gradient_name]
if not gradient_colors:
gradient_colors = GRADIENTS.get('spectral')
self.rgb_list = np.array(
[COLORS[color.lower()] for color in gradient_colors]).T
n_colors = len(self.rgb_list[0])
# if gradient_method == "bezier":
# t = np.linspace(0.0, 1.0, gradient_length)
# polynomial_array = np.array([self._bernstein_poly(i, n_colors-1, t) for i in range(0, n_colors)])
# polynomial_array = np.fliplr(polynomial_array)
# gradient = np.array([np.dot(self.rgb_list[0], polynomial_array),
# np.dot(self.rgb_list[1], polynomial_array),
# np.dot(self.rgb_list[2], polynomial_array)])
# _LOGGER.info(('Generating new gradient curve for {}'.format(gradient_colors)))
# self._gradient_curve = gradient
# elif gradient_method == "cubic_ease":
gradient = np.zeros((3, gradient_length))
gradient_split = np.array_split(gradient, repeat, axis=1)
for i in range(len(gradient_split)):
segment_length = len(gradient_split[i][0])
t = np.zeros(segment_length)
ease_chunks = np.array_split(t, n_colors - 1)
color_pairs = np.array([(self.rgb_list.T[i],
self.rgb_list.T[i + 1])
for i in range(n_colors - 1)])
gradient_split[i] = np.hstack(
self._color_ease(len(ease_chunks[i]), *color_pairs[i])
for i in range(n_colors - 1))
_LOGGER.info(
('Generating new gradient curve for {}'.format(gradient_colors)))
self._gradient_curve = np.hstack(gradient_split)
def _generate_bezier_curve(self, gradient_colors, gradient_length):
gradient_method = "bezier"
# Check to see if we have a custom gradient, or a predefined one and
# load the colors accordingly
if isinstance(gradient_colors, str):
gradient_name = gradient_colors
gradient_colors = []
if GRADIENTS.get(gradient_name):
gradient_colors = GRADIENTS.get(gradient_name).get("colors")
gradient_method = GRADIENTS.get(gradient_name).get("method", "bezier")
elif COLORS.get(gradient_name):
gradient_colors = [gradient_name]
if not gradient_colors:
gradient_colors = GRADIENTS.get('spectral')
self.rgb_list = np.array([COLORS[color.lower()] for color in gradient_colors]).T
n_colors = len(self.rgb_list[0])
if gradient_method == "bezier":
t = np.linspace(0.0, 1.0, gradient_length)
polynomial_array = np.array([self._bernstein_poly(i, n_colors-1, t) for i in range(0, n_colors)])
gradient = np.array([np.dot(self.rgb_list[0], polynomial_array),
np.dot(self.rgb_list[1], polynomial_array),
np.dot(self.rgb_list[2], polynomial_array)])
_LOGGER.info(('Generating new gradient curve for {}'.format(gradient_colors)))
self._gradient_curve = gradient
else:
gradient = np.zeros((gradient_length, 3))
for i in range(gradient_length):
rgb_i = i % n_colors
gradient[i] = (self.rgb_list[0][rgb_i], self.rgb_list[1][rgb_i], self.rgb_list[2][rgb_i])
self._gradient_curve = gradient.T
