def get_order_n_self(self, order):
if order == 0:
result = self.get_seed_shape()
else:
lower_order = self.get_order_n_self(order - 1)
subparts = [lower_order.copy() for x in range(self.num_subparts)]
self.arrange_subparts(*subparts)
result = VGroup(*subparts)
result.scale_to_fit_height(self.height)
result.center()
return result
def get_dot_template(self, place):
# This should be replaced for non-base-10 counting scenes
dots = VGroup(*[
Dot(
point,
radius=0.25,
fill_opacity=0,
stroke_width=2,
stroke_color=WHITE,
) for point in self.get_template_configuration(place)
])
dots.scale_to_fit_height(self.dot_configuration_height)
return dots
def get_dot_template(self, place):
# This should be replaced for non-base-10 counting scenes
dots = VGroup(*[
Dot(
point,
radius=0.25,
fill_opacity=0,
stroke_width=2,
stroke_color=WHITE,
)
for point in self.get_template_configuration(place)
])
dots.scale_to_fit_height(self.dot_configuration_height)
return dots
def get_order_n_self(self, order):
if order == 0:
result = self.get_seed_shape()
else:
lower_order = self.get_order_n_self(order - 1)
subparts = [
lower_order.copy()
for x in range(self.num_subparts)
]
self.arrange_subparts(*subparts)
result = VGroup(*subparts)
result.scale_to_fit_height(self.height)
result.center()
return result
def get_secant_slope_group(
self,
x,
graph,
dx=None,
dx_line_color=None,
df_line_color=None,
dx_label=None,
df_label=None,
include_secant_line=True,
secant_line_color=None,
secant_line_length=10,
):
"""
Resulting group is of the form VGroup(
dx_line,
df_line,
dx_label, (if applicable)
df_label, (if applicable)
secant_line, (if applicable)
)
with attributes of those names.
"""
kwargs = locals()
kwargs.pop("self")
group = VGroup()
group.kwargs = kwargs
dx = dx or float(self.x_max - self.x_min) / 10
dx_line_color = dx_line_color or self.default_input_color
df_line_color = df_line_color or graph.get_color()
p1 = self.input_to_graph_point(x, graph)
p2 = self.input_to_graph_point(x + dx, graph)
interim_point = p2[0] * RIGHT + p1[1] * UP
group.dx_line = Line(p1, interim_point, color=dx_line_color)
group.df_line = Line(interim_point, p2, color=df_line_color)
group.add(group.dx_line, group.df_line)
labels = VGroup()
if dx_label is not None:
group.dx_label = TexMobject(dx_label)
labels.add(group.dx_label)
group.add(group.dx_label)
if df_label is not None:
group.df_label = TexMobject(df_label)
labels.add(group.df_label)
group.add(group.df_label)
if len(labels) > 0:
max_width = 0.8 * group.dx_line.get_width()
max_height = 0.8 * group.df_line.get_height()
if labels.get_width() > max_width:
labels.scale_to_fit_width(max_width)
if labels.get_height() > max_height:
labels.scale_to_fit_height(max_height)
if dx_label is not None:
group.dx_label.next_to(group.dx_line,
np.sign(dx) * DOWN,
buff=group.dx_label.get_height() / 2)
group.dx_label.set_color(group.dx_line.get_color())
if df_label is not None:
group.df_label.next_to(group.df_line,
np.sign(dx) * RIGHT,
buff=group.df_label.get_height() / 2)
group.df_label.set_color(group.df_line.get_color())
if include_secant_line:
secant_line_color = secant_line_color or self.default_derivative_color
group.secant_line = Line(p1, p2, color=secant_line_color)
group.secant_line.scale_in_place(secant_line_length /
group.secant_line.get_length())
group.add(group.secant_line)
return group
