def get_circles_and_points(self, min_input, max_input):
input_left, input_right = [
self.interval.number_to_point(num)
for num in min_input, max_input
]
input_circle = Circle(
radius = np.linalg.norm(input_left-input_right)/2,
color = WHITE
)
input_circle.shift((input_left+input_right)/2)
input_points = Line(
input_left, input_right,
color = self.input_color
)
output_points = Mobject(color = self.output_color)
n = self.output.get_num_points()
output_points.add_points(
self.output.points[int(min_input*n):int(max_input*n)]
)
output_center = output_points.points[int(0.5*output_points.get_num_points())]
max_distance = np.linalg.norm(output_center-output_points.points[-1])
output_circle = Circle(
radius = max_distance,
color = WHITE
)
output_circle.shift(output_center)
return (
input_circle,
input_points,
output_circle,
output_points
)
class ThoughtBubble(Bubble):
DEFAULT_CONFIG = {
"num_bulges": 7,
"initial_inner_radius": 1.8,
"initial_width": 6,
}
def __init__(self, **kwargs):
Bubble.__init__(self, **kwargs)
def get_tip(self):
return self.small_circle.get_bottom()
def generate_points(self):
self.small_circle = Circle().scale(0.15)
self.small_circle.shift(2.5 * DOWN + 2 * LEFT)
self.add(self.small_circle)
self.add(Circle().scale(0.3).shift(2 * DOWN + 1.5 * LEFT))
for n in range(self.num_bulges):
theta = 2 * np.pi * n / self.num_bulges
self.add(Circle().shift((np.cos(theta), np.sin(theta), 0)))
self.filter_out(
lambda p: np.linalg.norm(p) < self.initial_inner_radius)
self.stretch_to_fit_width(self.initial_width)
self.highlight("white")
def get_circles_and_points(self, min_input, max_input):
input_left, input_right = [
self.interval.number_to_point(num)
for num in min_input, max_input
]
input_circle = Circle(
radius = np.linalg.norm(input_left-input_right)/2,
color = WHITE
)
input_circle.shift((input_left+input_right)/2)
input_points = Line(
input_left, input_right,
color = self.input_color
)
output_points = Mobject(color = self.output_color)
n = self.output.get_num_points()
output_points.add_points(
self.output.points[int(min_input*n):int(max_input*n)]
)
output_center = output_points.points[int(0.5*output_points.get_num_points())]
max_distance = np.linalg.norm(output_center-output_points.points[-1])
output_circle = Circle(
radius = max_distance,
color = WHITE
)
output_circle.shift(output_center)
return (
input_circle,
input_points,
output_circle,
output_points
)
class ThoughtBubble(Bubble):
DEFAULT_CONFIG = {
"num_bulges" : 7,
"initial_inner_radius" : 1.8,
"initial_width" : 6,
}
def __init__(self, **kwargs):
Bubble.__init__(self, **kwargs)
def get_tip(self):
return self.small_circle.get_bottom()
def generate_points(self):
self.small_circle = Circle().scale(0.15)
self.small_circle.shift(2.5*DOWN+2*LEFT)
self.add(self.small_circle)
self.add(Circle().scale(0.3).shift(2*DOWN+1.5*LEFT))
for n in range(self.num_bulges):
theta = 2*np.pi*n/self.num_bulges
self.add(Circle().shift((np.cos(theta), np.sin(theta), 0)))
self.filter_out(lambda p : np.linalg.norm(p) < self.initial_inner_radius)
self.stretch_to_fit_width(self.initial_width)
self.highlight("white")
