def init_colors(self):
SelfSimilarFractal.init_colors(self)
internal_pis = [
pi for pi in self.get_family() if isinstance(pi, PiCreature)
]
colors = color_gradient(self.colors, len(internal_pis))
for pi, color in zip(internal_pis, colors):
pi.init_colors()
pi.body.set_stroke(color, width=0.5)
pi.set_color(color)
def set_submobject_colors_by_gradient(self, *colors):
if len(colors) == 0:
raise Exception("Need at least one color")
elif len(colors) == 1:
return self.set_color(*colors)
mobs = self.family_members_with_points()
new_colors = color_gradient(colors, len(mobs))
for mob, color in zip(mobs, new_colors):
mob.set_color(color, family=False)
return self
def set_submobject_colors_by_gradient(self, *colors):
if len(colors) == 0:
raise Exception("Need at least one color")
elif len(colors) == 1:
return self.set_color(*colors)
mobs = self.family_members_with_points()
new_colors = color_gradient(colors, len(mobs))
for mob, color in zip(mobs, new_colors):
mob.set_color(color, family=False)
return self
def init_colors(self):
SelfSimilarFractal.init_colors(self)
internal_pis = [
pi
for pi in self.submobject_family()
if isinstance(pi, PiCreature)
]
colors = color_gradient(self.colors, len(internal_pis))
for pi, color in zip(internal_pis, colors):
pi.init_colors()
pi.body.set_stroke(color, width=0.5)
pi.set_color(color)
def set_color_by_gradient(self, *colors):
self.rgbas = np.array(
map(color_to_rgba, color_gradient(colors, len(self.points))))
return self
start_rgba, end_rgba = map(color_to_rgba, [start_color, end_color])
for mob in self.family_members_with_points():
num_points = mob.get_num_points()
mob.rgbas = np.array([
interpolate(start_rgba, end_rgba, alpha)
for alpha in np.arange(num_points) / float(num_points)
])
return self
def get_riemann_rectangles(
self,
graph,
x_min=None,
x_max=None,
dx=0.1,
input_sample_type="left",
stroke_width=1,
stroke_color=BLACK,
fill_opacity=1,
start_color=None,
end_color=None,
show_signed_area=True,
width_scale_factor=1.001
):
x_min = x_min if x_min is not None else self.x_min
x_max = x_max if x_max is not None else self.x_max
if start_color is None:
start_color = self.default_riemann_start_color
if end_color is None:
end_color = self.default_riemann_end_color
rectangles = VGroup()
x_range = np.arange(x_min, x_max, dx)
colors = color_gradient([start_color, end_color], len(x_range))
for x, color in zip(x_range, colors):
if input_sample_type == "left":
sample_input = x
elif input_sample_type == "right":
sample_input = x + dx
elif input_sample_type == "center":
sample_input = x + 0.5 * dx
else:
raise Exception("Invalid input sample type")
graph_point = self.input_to_graph_point(sample_input, graph)
points = VGroup(*list(map(VectorizedPoint, [
self.coords_to_point(x, 0),
self.coords_to_point(x + width_scale_factor * dx, 0),
graph_point
])))
rect = Rectangle()
rect.replace(points, stretch=True)
if graph_point[1] < self.graph_origin[1] and show_signed_area:
fill_color = invert_color(color)
else:
fill_color = color
rect.set_fill(fill_color, opacity=fill_opacity)
rect.set_stroke(stroke_color, width=stroke_width)
rectangles.add(rect)
return rectangles
def get_division_along_dimension(self, p_list, dim, colors, vect):
p_list = self.complete_p_list(p_list)
colors = color_gradient(colors, len(p_list))
last_point = self.get_edge_center(-vect)
parts = VGroup()
for factor, color in zip(p_list, colors):
part = SampleSpace()
part.set_fill(color, 1)
part.replace(self, stretch=True)
part.stretch(factor, dim)
part.move_to(last_point, -vect)
last_point = part.get_edge_center(vect)
parts.add(part)
return parts
def get_division_along_dimension(self, p_list, dim, colors, vect):
p_list = self.complete_p_list(p_list)
colors = color_gradient(colors, len(p_list))
last_point = self.get_edge_center(-vect)
parts = VGroup()
for factor, color in zip(p_list, colors):
part = SampleSpace()
part.set_fill(color, 1)
part.replace(self, stretch=True)
part.stretch(factor, dim)
part.move_to(last_point, -vect)
last_point = part.get_edge_center(vect)
parts.add(part)
return parts
def set_color_by_gradient(self, *colors):
self.rgbas = np.array(map(
color_to_rgba,
color_gradient(colors, len(self.points))
))
return self
start_rgba, end_rgba = map(color_to_rgba, [start_color, end_color])
for mob in self.family_members_with_points():
num_points = mob.get_num_points()
mob.rgbas = np.array([
interpolate(start_rgba, end_rgba, alpha)
for alpha in np.arange(num_points) / float(num_points)
])
return self
