def scroll_through_patrons(self):
logo_box = Square(side_length=2.5)
logo_box.to_corner(DOWN + LEFT, buff=MED_LARGE_BUFF)
total_width = SPACE_WIDTH - logo_box.get_right()[0]
black_rect = Rectangle(fill_color=BLACK,
fill_opacity=1,
stroke_width=0,
width=2 * SPACE_WIDTH,
height=1.1 * SPACE_HEIGHT)
black_rect.to_edge(UP, buff=0)
line = DashedLine(SPACE_WIDTH * LEFT, SPACE_WIDTH * RIGHT)
line.move_to(black_rect, DOWN)
line.shift(SMALL_BUFF * SMALL_BUFF * DOWN)
self.add(line)
patrons = VGroup(*map(TextMobject, self.specific_patrons))
patrons.scale(self.patron_scale_val)
for patron in patrons:
if patron.get_width() > self.max_patron_width:
patron.scale_to_fit_width(self.max_patron_width)
columns = VGroup(*[
VGroup(*patrons[i::self.n_patron_columns]).arrange_submobjects(
DOWN, buff=MED_SMALL_BUFF)
for i in range(self.n_patron_columns)
])
columns.arrange_submobjects(
RIGHT,
buff=LARGE_BUFF,
aligned_edge=UP,
)
columns.scale_to_fit_width(total_width - 1)
columns.next_to(black_rect, DOWN, 3 * LARGE_BUFF)
columns.to_edge(RIGHT)
self.play(
columns.next_to,
SPACE_HEIGHT * DOWN,
UP,
LARGE_BUFF,
columns.to_edge,
RIGHT,
Animation(black_rect),
rate_func=None,
run_time=self.run_time,
)
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.highlight(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.highlight(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
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.highlight(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.highlight(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
