def get_vector(self, point, **kwargs):
output = np.array(self.func(point))
norm = get_norm(output)
if norm == 0:
output *= 0
else:
output *= self.length_func(norm) / norm
vector_config = dict(self.vector_config)
vector_config.update(kwargs)
vect = Vector(output, **vector_config)
vect.shift(point)
fill_color = rgb_to_color(
self.rgb_gradient_function(np.array([norm]))[0])
vect.set_color(fill_color)
return vect
def get_vector(self, point, **kwargs):
output = np.array(self.func(point))
norm = get_norm(output)
if norm == 0:
output *= 0
else:
output *= self.length_func(norm) / norm
vector_config = dict(self.vector_config)
vector_config.update(kwargs)
vect = Vector(output, **vector_config)
vect.shift(point)
fill_color = rgb_to_color(
self.rgb_gradient_function(np.array([norm]))[0]
)
vect.set_color(fill_color)
return vect
def __init__(self, func, **kwargs):
if not hasattr(self, "args"):
self.args = serialize_args([func])
if not hasattr(self, "config"):
self.config = serialize_config({
**kwargs,
})
VGroup.__init__(self, **kwargs)
self.func = func
dt = self.dt
start_points = self.get_start_points(
**self.start_points_generator_config)
for point in start_points:
points = [point]
for t in np.arange(0, self.virtual_time, dt):
last_point = points[-1]
points.append(last_point + dt * func(last_point))
if get_norm(last_point) > self.cutoff_norm:
break
line = VMobject()
step = max(1, int(len(points) / self.n_anchors_per_line))
line.set_points_smoothly(points[::step])
self.add(line)
self.set_stroke(self.stroke_color, self.stroke_width)
if self.color_by_arc_length:
len_to_rgb = get_rgb_gradient_function(
self.min_arc_length,
self.max_arc_length,
colors=self.colors,
)
for line in self:
arc_length = line.get_arc_length()
rgb = len_to_rgb([arc_length])[0]
color = rgb_to_color(rgb)
line.set_color(color)
elif self.color_by_magnitude:
image_file = get_color_field_image_file(
lambda p: get_norm(func(p)),
min_value=self.min_magnitude,
max_value=self.max_magnitude,
colors=self.colors,
)
self.color_using_background_image(image_file)
def __init__(self, func, **kwargs):
VGroup.__init__(self, **kwargs)
self.func = func
dt = self.dt
start_points = self.get_start_points(
**self.start_points_generator_config
)
for point in start_points:
points = [point]
for t in np.arange(0, self.virtual_time, dt):
last_point = points[-1]
points.append(last_point + dt * func(last_point))
if get_norm(last_point) > self.cutoff_norm:
break
line = VMobject()
step = max(1, int(len(points) / self.n_anchors_per_line))
line.set_points_smoothly(points[::step])
self.add(line)
self.set_stroke(self.stroke_color, self.stroke_width)
if self.color_by_arc_length:
len_to_rgb = get_rgb_gradient_function(
self.min_arc_length,
self.max_arc_length,
colors=self.colors,
)
for line in self:
arc_length = line.get_arc_length()
rgb = len_to_rgb([arc_length])[0]
color = rgb_to_color(rgb)
line.set_color(color)
elif self.color_by_magnitude:
image_file = get_color_field_image_file(
lambda p: get_norm(func(p)),
min_value=self.min_magnitude,
max_value=self.max_magnitude,
colors=self.colors,
)
self.color_using_background_image(image_file)
def get_value(self):
r = self.r_slider.get_value() / 255
g = self.g_slider.get_value() / 255
b = self.b_slider.get_value() / 255
alpha = self.a_slider.get_value()
return color_to_rgba(rgb_to_color((r, g, b)), alpha=alpha)
def tweak_color(color1, color2, weight=0.3):
"""Return a weighted-average of two colors."""
weight = np.clip(weight, 0, 1)
tweaked_rgb = weight * color_to_rgb(color2) + (
1 - weight) * color_to_rgb(color1)
return rgb_to_color(tweaked_rgb)
