def animate_event_annotation(self):
"""Save H: ill, and E: test positive to the upper right
"""
if (self.is_show_only):
self.mtex_event_h.scale(1.0 / self.scale_eq_f)
self.txt_event_h.scale(0.8 / self.scale_txt_f)
self.mtex_event_e.scale(1.0 / self.scale_eq_f)
self.txt_event_e.scale(0.8 / self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_h, LEFT + DOWN,
ORIGIN + 0.0 * RIGHT + 3.0 * UP)
print(self.mtex_event_h.get_center())
self.txt_event_h.next_to(self.mtex_event_h)
print(self.txt_event_h.get_center())
myutil.critical_point_move_to(self.mtex_event_e, LEFT + DOWN,
ORIGIN + 2.5 * RIGHT + 3.0 * UP)
print(self.mtex_event_e.get_center())
self.txt_event_e.next_to(self.mtex_event_e)
print(self.txt_event_e.get_center())
return
self.play(ApplyMethod(self.txt_event_h.scale, 1.0 / self.scale_eq_f),
ApplyMethod(self.txt_event_h.scale, 0.8 / self.scale_txt_f),
ApplyMethod(self.txt_event_e.scale, 1.0 / self.scale_eq_f),
ApplyMethod(self.txt_event_e.scale, 0.8 / self.scale_txt_f))
self.play(
ApplyMethod(self.mtex_event_h.move_to,
ORIGIN + 0.2 * RIGHT + 3.2 * UP),
ApplyMethod(self.txt_event_h.move_to,
ORIGIN + 1.3 * RIGHT + 3.2 * UP),
ApplyMethod(self.mtex_event_e.move_to,
ORIGIN + 2.7 * RIGHT + 3.17 * UP),
ApplyMethod(self.txt_event_e.move_to,
ORIGIN + 4.0 * RIGHT + 3.17 * UP))
self.wait(self.time_wait)
def show_bayes(self):
"""ベイズの定理
"""
# E: 検査+， H: 病気
self.mtex_event_h.scale(1.0 / self.scale_eq_f)
self.txt_event_h.scale(0.8 / self.scale_txt_f)
self.mtex_event_e.scale(1.0 / self.scale_eq_f)
self.txt_event_e.scale(0.8 / self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_h, LEFT + DOWN,
ORIGIN + 0.0 * RIGHT + 3.0 * UP)
self.txt_event_h.next_to(self.mtex_event_h)
myutil.critical_point_move_to(self.mtex_event_e, LEFT + DOWN,
ORIGIN + 2.5 * RIGHT + 3.0 * UP)
self.txt_event_e.next_to(self.mtex_event_e)
if (self.is_show_only):
self.add(self.mtex_bayes_full)
self.add(self.mtex_event_e, self.txt_event_e)
self.add(self.mtex_event_h, self.txt_event_h)
return
self.play(FadeIn(self.mtex_bayes_full), FadeIn(self.mtex_event_e),
FadeIn(self.txt_event_e), FadeIn(self.mtex_event_h),
FadeIn(self.txt_event_h))
self.wait(self.time_wait)
def create_title(self):
"""
"""
self.txt_assumption = Text(r"前提:" ).scale(self.scale_title_f)
self.txt_no_perfect = Text(r"完璧な検査はない").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_assumption, LEFT + DOWN, ORIGIN + -6 * RIGHT + 2.8 * UP)
self.txt_no_perfect.next_to(self.txt_assumption)
self.txt_handle_non_perfect = Text(r"不確実を扱う道具の話").scale(self.scale_txt_f)
myutil.critical_point_move_to(self.txt_handle_non_perfect, LEFT + DOWN, ORIGIN + -5.5 * RIGHT + 2.0 * UP)
self.txt_not_pre = Text(r"記号" ). scale(self.scale_txt_f)
self.mtex_not_1 = MathTex(r"\lnot"). scale(1.0).set_color(self.col_n)
self.txt_not_ja = Text(r": 〜ではない").scale(self.scale_txt_f)
# It seems Text and MathTex don't share the positioning. Use other Text
myutil.critical_point_move_to(self.txt_not_pre, LEFT + DOWN, ORIGIN + +0.2 * RIGHT + 3.0 * UP)
self.mtex_not_1.next_to(self.txt_not_pre)
self.txt_not_ja.next_to(self.mtex_not_1)
self.mtex_not_2 = MathTex(r"\lnot"). scale(self.scale_eq_f).set_color(self.col_n)
self.txt_ill = Text(r"病気"). scale(self.scale_txt_f)
self.txt_not_ill = Text(r": 病気ではない").scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_not_2, LEFT + DOWN, ORIGIN + + 0.24 * RIGHT + 2.5 * UP)
self.txt_ill.next_to(self.mtex_not_2)
self.txt_not_ill.next_to(self.txt_ill)
def animate_probablity(self):
"""part 3
animate P()'s meaning
"""
# probability notation: reposition
myutil.critical_point_move_to(self.tex_prob_eq[1], LEFT + DOWN, ORIGIN + -6.0 * RIGHT + -2.0 * UP)
myutil.critical_point_move_to(self.tex_prob_eq[2], LEFT + DOWN, ORIGIN + -6.0 * RIGHT + -2.0 * UP)
for i in range(0, len(self.txt_prob_exp)):
self.txt_prob_exp[i].next_to(self.tex_prob_eq[i], buff=0.2)
# working memory (Transform(a, b): a = b, a is written
eq_work = copy.deepcopy(self.tex_prob_eq[0])
# P()
self.play(FadeIn(eq_work))
self.wait(self.time_wait)
# P() : 〜の確率
self.play(FadeIn(self.txt_prob_exp[0]))
self.wait(self.time_wait)
# P(A)
self.play(Transform(eq_work, self.tex_prob_eq[1]),
FadeOut(self.txt_prob_exp[0]))
self.wait(self.time_wait)
# P(A): A の確率
self.play(FadeIn(self.txt_prob_exp[1]))
self.wait(self.time_wait)
# P(H|E)
self.play(Transform(eq_work, self.tex_prob_eq[2]),
FadeOut(self.txt_prob_exp[1]))
self.wait(self.time_wait)
# P(H|E): E の時，H となる確率
self.play(FadeIn(self.txt_prob_exp[2]))
self.wait(self.time_wait)
def animate_bayes_simple_to_full(self):
"""Transit Bayes simple forma to full form
"""
if (self.is_show_only):
self.remove(self.mtex_bayes_simple)
self.add(self.mtex_bayes_full)
self.wait(1)
return
# replace with working copy. move P(E) to down
# Note: self.remove(self.mtex_bayes_simple) does not work, seems objects are implicitly copied.
# self.remove(self.mtex_bayes_simple[0],
# self.mtex_bayes_simple[1],
# self.mtex_bayes_simple[2],
# self.mtex_bayes_simple[3],
# self.mtex_bayes_simple[4],
# self.mtex_bayes_simple[5],
# )
eq_simple_dest = copy.deepcopy(self.mtex_bayes_simple)
# self.add(eq_simple_dest)
# destination: P(E) = P(H)P(E|H) + P(\lnot H)P(E|\lnot H)
tex_e_full = MathTex(
r"P(E)", # [0] e [0,2]
r"=", # [1]
r"P(H)", # [2] h [2,2]
r"P(E|H)", # [3] e [3,2] h [3,4]
r"+", # [4]
r"P(\lnot H)", # [5] h [5,3] n [5, 2]
r"P(E|\lnot H)" # [6] e [6,2] h [6,5] n [6, 4]
).scale(self.scale_eq_f)
h_indices = [[2, 2], [3, 4], [5, 3], [6, 5]]
for [i, j] in h_indices:
tex_e_full[i][j].set_color(self.col_h)
e_indices = [[0, 2], [3, 2], [6, 2]]
for [i, j] in e_indices:
tex_e_full[i][j].set_color(self.col_e)
n_indices = [[5, 2], [6, 4]]
for [i, j] in n_indices:
tex_e_full[i][j].set_color(self.col_n)
# push original position
pushd_src_pos = eq_simple_dest[5].get_center()
# get the dest position (based on critical point)
# Note 1: 'RIGHT + DOWN' of the 0-th element! not 'LEFT + DOWN'
# Thus re-adjuetment whole by LEFT + DOWN
# Note 2: myutil.critical_point_move_to(tex[0], ...) creates
# object copy of tex[0], derefernce by tex failed.
car_tex_e_full = copy.deepcopy(tex_e_full[0])
myutil.critical_point_move_to(car_tex_e_full, RIGHT + DOWN,
self.pos_line_3)
pos_ld_car_tex_e_full = car_tex_e_full.get_critical_point(LEFT + DOWN)
myutil.critical_point_move_to(tex_e_full, LEFT + DOWN,
pos_ld_car_tex_e_full)
pushd_dst_pos = tex_e_full[0].get_center()
# move to the src
tex_e_full[0].move_to(pushd_src_pos)
# denominator P(E) moves to explanation
self.play(ApplyMethod(tex_e_full[0].move_to, pushd_dst_pos))
self.wait(self.time_wait)
# Explain P(E) '= '
self.play(FadeIn(tex_e_full[1]))
self.wait(self.time_wait)
# Explain P(E) = 'P(H)'
self.play(FadeIn(tex_e_full[2]))
self.wait(self.time_wait)
# Explain P(E) = P(H) 'P(\lnot H)'
self.play(FadeIn(tex_e_full[5]))
self.wait(self.time_wait)
# Explain P(E) = P(H)'P(E|H)' P(\lnot H)
self.play(FadeIn(tex_e_full[3]))
self.wait(self.time_wait)
# Explain P(E) = P(H)P(E|H) P(\lnot H)'P(E|\lnot H)'
self.play(FadeIn(tex_e_full[6]))
self.wait(self.time_wait)
# Explain P(E) = P(H)P(E|H) '+' P(\lnot H)P(E|\lnot H)
self.play(FadeIn(tex_e_full[4]))
self.wait(self.time_wait)
# update to eq to full, keep denominator empty
self.add(self.mtex_bayes_full[0], self.mtex_bayes_full[1])
self.remove(eq_simple_dest[0], eq_simple_dest[1], eq_simple_dest[2],
eq_simple_dest[3])
# these seems implicitly copied
self.remove(self.mtex_bayes_simple[0], self.mtex_bayes_simple[1],
self.mtex_bayes_simple[2], self.mtex_bayes_simple[3],
self.mtex_bayes_simple[4])
# P(H)P(E|H) in eq to move, transform the fraction bar
pos_src_p_h = self.mtex_bayes_simple[2].get_center()
pos_src_p_e_b_h = self.mtex_bayes_simple[3].get_center()
pos_dst_p_h = self.mtex_bayes_full[2].get_center()
pos_dst_p_e_b_h = self.mtex_bayes_full[3].get_center()
self.mtex_bayes_full[2].move_to(pos_src_p_h)
self.mtex_bayes_full[3].move_to(pos_src_p_e_b_h)
self.play(
ApplyMethod(self.mtex_bayes_full[2].move_to, pos_dst_p_h),
ApplyMethod(self.mtex_bayes_full[3].move_to, pos_dst_p_e_b_h),
Transform(eq_simple_dest[4], self.mtex_bayes_full[4]))
self.wait(self.time_wait)
# move the right hand side of P(E) = P(H)P{E|H) + P(\lnot H)P{E|\lnot H)
# self.play(FadeOut(self.mtex_bayes_simple[5]))
self.remove(self.mtex_bayes_simple[5]) # This seems implicitly copied
self.play(FadeOut(eq_simple_dest[5]))
self.wait(self.time_wait)
# partal zip?
self.play(
FadeOut(tex_e_full[0]), FadeOut(tex_e_full[1]),
ApplyMethod(tex_e_full[2].move_to,
self.mtex_bayes_full[5].get_center()),
ApplyMethod(tex_e_full[3].move_to,
self.mtex_bayes_full[6].get_center()),
ApplyMethod(tex_e_full[4].move_to,
self.mtex_bayes_full[7].get_center()),
ApplyMethod(tex_e_full[5].move_to,
self.mtex_bayes_full[8].get_center()),
ApplyMethod(tex_e_full[6].move_to,
self.mtex_bayes_full[9].get_center()))
self.wait(self.time_wait)
# replace work equation to shared full beyes equation
self.remove(tex_e_full)
self.add(self.mtex_bayes_full)
self.wait(self.time_wait)
def create_bayes_eq(self):
"""
"""
self.txt_title_bayes = Text(r"ベイズの定理").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN,
ORIGIN + -6.3 * RIGHT + 3.0 * UP)
# simple Bayes form (3b1b form, cond later) # indices for h,e color
self.mtex_bayes_simple = MathTex(
r"P(H|E)", # [0] e [0,4] h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(E)}", # [5] e [5,2]
r"}", # [6]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_simple, LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4]]
for [i, j] in self.h_indices:
self.mtex_bayes_simple[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [5, 2]]
for [i, j] in self.e_indices:
self.mtex_bayes_simple[i][j].set_color(self.col_e)
# full Bayes form # indices for h,e color (MathTex removes white space))
self.mtex_bayes_full = MathTex(
r"P(H|E)", # [0] e [0,4], h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(H)", # [5] h [5,2]
r"P(E|H)}", # [6] e [6,2], h [6,4]
r"+", # [7]
r"{P(\lnot H)", # [8] h [8,3], n [8,2]
r"P(E |\lnot H)}}", # [9] e [9,2], h [9,5], n [9,4]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_full, LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4], [5, 2], [6, 4], [8, 3],
[9, 5]]
for [i, j] in self.h_indices:
self.mtex_bayes_full[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [6, 2], [9, 2]]
for [i, j] in self.e_indices:
self.mtex_bayes_full[i][j].set_color(self.col_e)
self.n_indices = [[8, 2], [9, 4]]
for [i, j] in self.n_indices:
self.mtex_bayes_full[i][j].set_color(self.col_n)
# --- Event examples
# event example H
var_buff = 0.2
self.mtex_event_h = MathTex(r"H").scale(self.scale_eq_f).set_color(
self.col_h)
self.txt_event_h = Text(r": 病気").scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_h, RIGHT + DOWN,
ORIGIN + -4.0 * RIGHT + 0.2 * UP)
self.txt_event_h.next_to(self.mtex_event_h, buff=var_buff)
# event example E
self.mtex_event_e = MathTex(r"E").scale(self.scale_eq_f).set_color(
self.col_e)
self.txt_event_e = Text(r": 検査＋", t2c={
r"[3:4]": self.col_positive
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_e, RIGHT + DOWN,
ORIGIN + -4.0 * RIGHT + -0.6 * UP)
self.txt_event_e.next_to(self.mtex_event_e, buff=var_buff)
# event example H|E
self.pos_line_3 = ORIGIN + -4.0 * RIGHT + -1.5 * UP
self.pos_line_4 = ORIGIN + -4.0 * RIGHT + -2.3 * UP
self.mtex_event_h_b_e = MathTex(r"H", r"|",
r"E").scale(self.scale_eq_f)
self.mtex_event_h_b_e[0].set_color(self.col_h)
self.mtex_event_h_b_e[2].set_color(self.col_e)
self.txt_event_h_b_e = Text(r": E (検査＋) の時に H (病気)",
t2c={
r"[1:2]": self.col_e,
r"[5:6]": self.col_positive,
r"[10:11]": self.col_h,
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_h_b_e, RIGHT + DOWN,
self.pos_line_3)
self.txt_event_h_b_e.next_to(self.mtex_event_h_b_e, buff=var_buff)
# event example P(H|E)
self.mtex_event_prob_h_b_e = MathTex(r"P(", r"H", r"|", r"E",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_h_b_e[1].set_color(self.col_h)
self.mtex_event_prob_h_b_e[3].set_color(self.col_e)
self.txt_event_prob_h_b_e = Text(r": E (検査＋) の時に H (病気) の確率",
t2c={
r"[1:2]": self.col_e,
r"[5:6]": self.col_positive,
r"[10:11]": self.col_h
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_prob_h_b_e, RIGHT + DOWN,
self.pos_line_4)
self.txt_event_prob_h_b_e.next_to(self.mtex_event_prob_h_b_e,
buff=var_buff)
# event example 5 P(H)
self.mtex_event_prob_h = MathTex(r"P(", r"H",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_h[1].set_color(self.col_h)
self.txt_event_prob_h = Text(r": H (病気) の確率",
t2c={
r"[1:2]": self.col_h
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_prob_h, RIGHT + DOWN,
self.pos_line_3)
self.txt_event_prob_h.next_to(self.mtex_event_prob_h, buff=var_buff)
# event example 6 P(E|H)
self.mtex_event_prob_e_b_h = MathTex(r"P(", r"E", r"|", r"H",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_e_b_h[1].set_color(self.col_e)
self.mtex_event_prob_e_b_h[3].set_color(self.col_h)
self.txt_event_prob_e_b_h = Text(r": H (病気) の時に，E (検査＋) の確率",
t2c={
r"[1:2]": self.col_h,
r"[10:11]": self.col_e,
r"[14:15]": self.col_positive,
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_prob_e_b_h, RIGHT + DOWN,
self.pos_line_3)
self.txt_event_prob_e_b_h.next_to(self.mtex_event_prob_e_b_h,
buff=var_buff)
# event example 7 P(E)
self.mtex_event_prob_e = MathTex(r"P(", r"E",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_e[1].set_color(self.col_e)
self.txt_event_prob_e = Text(r": E (検査＋) の確率",
t2c={
r"[1:2]": self.col_e,
r"[5:6]": self.col_positive,
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_prob_e, RIGHT + DOWN,
self.pos_line_3)
self.txt_event_prob_e.next_to(self.mtex_event_prob_e, buff=var_buff)
def create_bayes_eq(self):
"""create all mobjects
"""
self.txt_title_bayes = Text(r"具体例 2").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN, ORIGIN + -6.3 * RIGHT + 3.0 * UP)
# full Bayes form # indices for h,e color (MathTex removes white space))
self.mtex_bayes_full = MathTex(r"P(H|E)", # [0] e [0,4], h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(H)", # [5] h [5,2]
r"P(E|H)}", # [6] e [6,2], h [6,4]
r"+", # [7]
r"{P(\lnot H)", # [8] h [8,3], n [8,2]
r"P(E |\lnot H)}}", # [9] e [9,2], h [9,5], n [9,4]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_full, LEFT + DOWN, ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4], [5, 2], [6, 4], [8, 3], [9, 5]]
for [i,j] in self.h_indices:
self.mtex_bayes_full[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [6, 2], [9, 2]]
for [i,j] in self.e_indices:
self.mtex_bayes_full[i][j].set_color(self.col_e)
self.n_indices = [[8, 2], [9, 4]]
for [i,j] in self.n_indices:
self.mtex_bayes_full[i][j].set_color(self.col_n)
# --- Event examples
# event example H
self.mtex_event_h = MathTex(r"H"). scale(self.scale_event_eq_f).set_color(
self.col_h).move_to(0.2 * RIGHT + 3.4 * UP)
self.txt_event_h = Text(r": 病気").scale(self.scale_event_txt_f).move_to(1.3 * RIGHT + 3.4 * UP)
# event example E
self.mtex_event_e = MathTex(r"E").scale(self.scale_event_eq_f).set_color(
self.col_e).move_to(2.7 * RIGHT + 3.37 * UP)
self.txt_event_e = Text(r": 検査＋", t2c={r"[3:4]": self.col_positive}).scale(
self.scale_event_txt_f).move_to(4.0 * RIGHT + 3.37 * UP)
# --- another example (counter intuitive, but more realistic
# 病気の確率 0.1%: P(H) = 0.001
self.text_p_h = [Text(r"病気の確率").scale(self.scale_txt_f),
MathTex(r"0.1 \%"). scale(self.scale_eq_f),]
self.mtex_p_h = MathTex(r"P(H)", r"=", r"0.001").scale(self.scale_eq_f)
self.mtex_p_h[0][2].set_color(self.col_h)
# ¬病気の可能性 0.1%: P(¬H) = 0.999
self.text_p_not_h = [Text(r"¬病気の確率", t2c={"[0:1]": self.col_n}).scale(self.scale_txt_f),
MathTex(r"99.9 \%"). scale(self.scale_eq_f),]
self.mtex_p_not_h = MathTex(r"P(\lnot H)", r"=", r"0.999").scale(self.scale_eq_f)
self.mtex_p_not_h[0][2].set_color(self.col_n)
self.mtex_p_not_h[0][3].set_color(self.col_h)
# 病気の時に検査+ 100%: P(E|H) = 1.0
self.text_p_e_h = [Text(r"病気の時，検査＋", t2c={"[7:8]": self.col_positive}).scale(self.scale_txt_f),
MathTex(r"100 \%"). scale(self.scale_eq_f),]
self.mtex_p_e_h = MathTex(r"P(E|H)", r"=", r"1.0"). scale(self.scale_eq_f)
self.mtex_p_e_h[0][2].set_color(self.col_e)
self.mtex_p_e_h[0][4].set_color(self.col_h)
# ¬病気の時に検査+ 1%: P(E|¬H) = 0.01
self.text_p_e_not_h = [Text(r"¬病気の時，検査＋",
t2c={"[0:1]": self.col_n, "[8:9]": self.col_positive}).scale(self.scale_txt_f),
MathTex(r" 1 \%"). scale(self.scale_eq_f)]
self.mtex_p_e_not_h = MathTex(r"P(E|\lnot H)", r"=", r"0.01").scale(self.scale_eq_f)
self.mtex_p_e_not_h[0][2].set_color(self.col_e)
self.mtex_p_e_not_h[0][4].set_color(self.col_n)
self.mtex_p_e_not_h[0][5].set_color(self.col_h)
# text up shift and text right shift
text_up = [ 0.0, -0.8, -1.6, -2.4]
text_ri = [-5.5, +0.3]
text_align = [LEFT, RIGHT]
for i in range(0, 2):
myutil.critical_point_move_to(self.text_p_h[i], text_align[i], text_ri[i] * RIGHT + text_up[0] * UP)
myutil.critical_point_move_to(self.text_p_not_h[i], text_align[i], text_ri[i] * RIGHT + text_up[1] * UP)
myutil.critical_point_move_to(self.text_p_e_h[i], text_align[i], text_ri[i] * RIGHT + text_up[2] * UP)
myutil.critical_point_move_to(self.text_p_e_not_h[i], text_align[i], text_ri[i] * RIGHT + text_up[3] * UP)
mtex_ri = [+3.0, +3.4, +4.2]
text_align = [RIGHT, LEFT, LEFT]
for i in range(0, 3):
myutil.critical_point_move_to(self.mtex_p_h[i], text_align[i], ORIGIN + mtex_ri[i] * RIGHT + text_up[0] * UP)
myutil.critical_point_move_to(self.mtex_p_not_h[i], text_align[i], ORIGIN + mtex_ri[i] * RIGHT + text_up[1] * UP)
myutil.critical_point_move_to(self.mtex_p_e_h[i], text_align[i], ORIGIN + mtex_ri[i] * RIGHT + text_up[2] * UP)
myutil.critical_point_move_to(self.mtex_p_e_not_h[i], text_align[i], ORIGIN + mtex_ri[i] * RIGHT + text_up[3] * UP)
def create_table(self):
# horizontal lines
tab_width = self.get_tab_width()
self.line_tab_hline = []
for hidx in range(0, len(self.height_tcol)):
anchor_pos = self.get_tab_cell_anchor_pos(0, hidx)
self.line_tab_hline.append(
Line(anchor_pos, anchor_pos + tab_width * RIGHT,
color=self.color_tab_line, stroke_width=self.stroke_width_tab_line))
# append the last hline
hsize = len(self.height_tcol)
print("hsize: {0}".format(hsize))
last_h_anchor_pos = self.get_tab_cell_anchor_pos(0, hsize - 1) + self.height_tcol[hsize - 1] * DOWN
self.line_tab_hline.append(
Line(last_h_anchor_pos, last_h_anchor_pos + tab_width * RIGHT,
color=self.color_tab_line, stroke_width=self.stroke_width_tab_line))
# (0,2) vline is one level shorter
tab_height = self.get_tab_height()
self.line_tab_vline = []
self.line_tab_vline.append(
Line(self.get_tab_cell_anchor_pos(0, 0), self.get_tab_cell_anchor_pos(0, 0) + tab_height * DOWN,
color=self.color_tab_line, stroke_width=self.stroke_width_tab_line))
self.line_tab_vline.append(
Line(self.get_tab_cell_anchor_pos(1, 0), self.get_tab_cell_anchor_pos(1, 0) + tab_height * DOWN,
color=self.color_tab_line, stroke_width=self.stroke_width_tab_line))
# [2] vline is one level (self.height_tcol[0]) shorter
self.line_tab_vline.append(
Line(self.get_tab_cell_anchor_pos(2, 1),
self.get_tab_cell_anchor_pos(2, 1) + (tab_height - self.height_tcol[0]) * DOWN,
color=self.color_tab_line, stroke_width=self.stroke_width_tab_line))
# append the last vline
vsize = len(self.width_trow)
last_v_anchor_pos = self.get_tab_cell_anchor_pos(vsize - 1, 0) + self.width_trow[vsize - 1] * RIGHT
self.line_tab_vline.append(
Line(last_v_anchor_pos, last_v_anchor_pos + tab_height * DOWN,
color=self.color_tab_line, stroke_width=self.stroke_width_tab_line))
debug_show_all_cell_position = False
if (debug_show_all_cell_position):
# Show cell positions
anchor_txt = []
for x in range(0, len(self.width_trow)):
for y in range(0, len(self.height_tcol)):
anchor_txt.append(Text("({0},{1})".format(x, y)).move_to(
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
x, y, ORIGIN, show=True)))
self.add(*anchor_txt)
# text column title
scale_col_title_txt = 1.0
self.txt_tab_column_title = [
Text(r"検査結果").scale(scale_col_title_txt),
Text(r"実際" ).scale(scale_col_title_txt)
]
myutil.critical_point_move_to(self.txt_tab_column_title[0], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
0, 0, ORIGIN, show=False))
table_row_2_adjust = (self.width_trow[2] / 2)
myutil.critical_point_move_to(self.txt_tab_column_title[1], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
1, 0, ORIGIN, show=False)
+ table_row_2_adjust * RIGHT)
# test row title (+,-)
scale_row_title_txt = 1.2
self.txt_tab_test_title = [
Text(r"＋", font="sans-serif", color=self.color_positive).scale(scale_row_title_txt),
Text(r"−", font="sans-serif", color=self.color_negative).scale(scale_row_title_txt)
]
# '+' is localted at (0,2)
myutil.critical_point_move_to(self.txt_tab_test_title[0], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
0, 2, ORIGIN, show=False))
# '-' is localted at (0,3)
myutil.critical_point_move_to(self.txt_tab_test_title[1], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
0, 3, ORIGIN, show=False))
# ill, not ill title
scale_row_title_txt = 1.0
not_ill = VGroup()
tex_not = MathTex(r"\lnot").scale(scale_row_title_txt).set_color(self.col_n)
txt_ill = Text(r"病気" ). scale(scale_row_title_txt).next_to(tex_not)
not_ill.add(tex_not, txt_ill)
self.txt_tab_ill_title = [
Text(r"病気"). scale(scale_col_title_txt),
not_ill,
]
myutil.critical_point_move_to(self.txt_tab_ill_title[0], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
1, 1, ORIGIN, show=False))
myutil.critical_point_move_to(self.txt_tab_ill_title[1], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
2, 1, ORIGIN, show=False))
# table contents
self.txt_tab_true_pn = [
Text(r"真＋", font="sans-serif",
t2c = {"＋": self.color_positive}), # t2w = {"＋": BOLD} doesn't work
Text(r"真−", font="sans-serif",
t2c = {"−": self.color_negative}), # t2w = {"−": ULTRABOLD} doesn't work
]
myutil.critical_point_move_to(self.txt_tab_true_pn[0], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
1, 2, ORIGIN, show=False))
myutil.critical_point_move_to(self.txt_tab_true_pn[1], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
2, 3, ORIGIN, show=False))
self.txt_tab_false_pn = [
Text(r"偽＋", font="sans-serif", t2c = {"＋": self.color_positive}),
Text(r"偽−", font="sans-serif", t2c = {"−": self.color_negative}),
]
myutil.critical_point_move_to(self.txt_tab_false_pn[0], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
2, 2, ORIGIN, show=False))
myutil.critical_point_move_to(self.txt_tab_false_pn[1], ORIGIN,
myutil.get_tab_cell_critical_pos(self.pos_tab_origin,
self.width_trow, self.height_tcol,
1, 3, ORIGIN, show=False))
def create_bayes_eq(self):
"""
"""
self.txt_title_bayes = Text(r"何故ベイズの定理?").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN,
ORIGIN + -6.3 * RIGHT + 3.0 * UP)
# full Bayes form # indices for h,e color (MathTex removes white space))
self.mtex_bayes_full = MathTex(
r"P(H|E)", # [0] e [0,4], h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(H)", # [5] h [5,2]
r"P(E|H)}", # [6] e [6,2], h [6,4]
r"+", # [7]
r"{P(\lnot H)", # [8] h [8,3] n [8,2]
r"P(E |\lnot H)}}", # [9] e [9,2], h [9,5] n [9,4]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_full, LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4], [5, 2], [6, 4], [8, 3],
[9, 5]]
for [i, j] in self.h_indices:
self.mtex_bayes_full[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [6, 2], [9, 2]]
for [i, j] in self.e_indices:
self.mtex_bayes_full[i][j].set_color(self.col_e)
self.n_indices = [[8, 2], [9, 4]]
for [i, j] in self.n_indices:
self.mtex_bayes_full[i][j].set_color(self.col_n)
# --- Event examples
# event example H
var_buff = 0.2
self.mtex_event_h = MathTex(r"H").scale(self.scale_eq_f).set_color(
self.col_h)
self.txt_event_h = Text(r": 病気").scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_h, RIGHT + DOWN,
ORIGIN + -4.0 * RIGHT + 0.2 * UP)
self.txt_event_h.next_to(self.mtex_event_h, buff=var_buff)
# event example E
self.mtex_event_e = MathTex(r"E").scale(self.scale_eq_f).set_color(
self.col_e)
self.txt_event_e = Text(r": 検査＋", t2c={
r"[3:4]": self.col_positive
}).scale(self.scale_txt_f)
myutil.critical_point_move_to(self.mtex_event_e, RIGHT + DOWN,
ORIGIN + -4.0 * RIGHT + -0.6 * UP)
self.txt_event_e.next_to(self.mtex_event_e, buff=var_buff)
# P(H|E): 検査+ の時に実際に病気である確率。(不明，知りたいこと)
self.mtex_event_prob_h_b_e = MathTex(r"P(", r"H", r"|", r"E",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_h_b_e[1].set_color(self.col_h)
self.mtex_event_prob_h_b_e[3].set_color(self.col_e)
self.txt_event_prob_h_b_e = [
Text(r": 検査＋の時に実際に病気の確率", t2c={
r"[3:4]": self.col_positive,
}).scale(self.scale_txt_f),
Text(r": 「知りたいこと」", ).scale(self.scale_txt_f),
Text(r"(未知)", ).scale(self.scale_txt_f).set_color(RED),
]
myutil.critical_point_move_to(self.mtex_event_prob_h_b_e, RIGHT + DOWN,
-3.0 * RIGHT + 0.5 * UP)
self.txt_event_prob_h_b_e[0].next_to(self.mtex_event_prob_h_b_e,
buff=var_buff)
self.txt_event_prob_h_b_e[1].next_to(self.mtex_event_prob_h_b_e,
buff=var_buff)
myutil.critical_point_move_to(self.txt_event_prob_h_b_e[2],
LEFT + DOWN, 3.5 * RIGHT + 0.5 * UP)
# P(H): 実際に病気である確率。(難しい。推定可能，検査で改善可能)
self.mtex_event_prob_h = MathTex(r"P(", r"H",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_h[1].set_color(self.col_h)
self.txt_event_prob_h = [
Text(r": 実際に病気の確率", ).scale(self.scale_txt_f),
Text(r": 推定，改善可能", ).scale(self.scale_txt_f),
Text(r"(既知)", ).scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.mtex_event_prob_h, RIGHT + DOWN,
-3.0 * RIGHT + -0.4 * UP)
self.txt_event_prob_h[0].next_to(self.mtex_event_prob_h, buff=var_buff)
self.txt_event_prob_h[1].next_to(self.mtex_event_prob_h, buff=var_buff)
myutil.critical_point_move_to(self.txt_event_prob_h[2], LEFT + DOWN,
3.5 * RIGHT + -0.4 * UP)
# P(\lnot H): 実際に病気でない確率。H の補集合，P(H) がわかればわかる
self.mtex_event_prob_not_h = MathTex(r"P(", r"\lnot", r"H",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_not_h[1].set_color(self.col_n)
self.mtex_event_prob_not_h[2].set_color(self.col_h)
self.txt_event_prob_not_h = [
Text(r": 実際に病気でない確率", ).scale(self.scale_txt_f),
Text(r": H の補集合", ).scale(self.scale_txt_f),
Text(r"(既知)", ).scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.mtex_event_prob_not_h, RIGHT + DOWN,
-3.0 * RIGHT + -1.3 * UP)
self.txt_event_prob_not_h[0].next_to(self.mtex_event_prob_not_h,
buff=var_buff)
self.txt_event_prob_not_h[1].next_to(self.mtex_event_prob_not_h,
buff=var_buff)
myutil.critical_point_move_to(self.txt_event_prob_not_h[2],
LEFT + DOWN, 3.5 * RIGHT + -1.3 * UP)
# P(E|H): 実際に病気の時に検査+ の確率: 検査キットの性能, (測定可能，既知)
self.mtex_event_prob_e_b_h = MathTex(r"P(", r"E", r"|", r"H",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_e_b_h[1].set_color(self.col_e)
self.mtex_event_prob_e_b_h[3].set_color(self.col_h)
self.txt_event_prob_e_b_h = [
Text(r": 実際に病気の時に，検査＋の確率", t2c={
r"[12:13]": self.col_positive,
}).scale(self.scale_txt_f),
Text(r": 検査の性能: 感度", ).scale(self.scale_txt_f),
Text(r"(既知)", ).scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.mtex_event_prob_e_b_h, RIGHT + DOWN,
-3.0 * RIGHT + -2.2 * UP)
self.txt_event_prob_e_b_h[0].next_to(self.mtex_event_prob_e_b_h,
buff=var_buff)
self.txt_event_prob_e_b_h[1].next_to(self.mtex_event_prob_e_b_h,
buff=var_buff)
myutil.critical_point_move_to(self.txt_event_prob_e_b_h[2],
LEFT + DOWN, 3.5 * RIGHT + -2.2 * UP)
# P(E|\lnot H): 実際に病気でない時に検査+ の確率: 検査キットの性能 (測定可能，既知)
self.mtex_event_prob_e_b_not_h = MathTex(r"P(", r"E", r"|", r"\lnot",
r"H",
r")").scale(self.scale_eq_f)
self.mtex_event_prob_e_b_not_h[1].set_color(self.col_e)
self.mtex_event_prob_e_b_not_h[3].set_color(self.col_n)
self.mtex_event_prob_e_b_not_h[4].set_color(self.col_h)
self.txt_event_prob_e_b_not_h = [
Text(r": 実際に病気でない時に，検査＋の確率", t2c={
r"[14:15]": self.col_positive,
}).scale(self.scale_txt_f),
Text(r": 検査の性能: 1 - 特異度", ).scale(self.scale_txt_f),
Text(r"(既知)", ).scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.mtex_event_prob_e_b_not_h,
RIGHT + DOWN, -3.0 * RIGHT + -3.1 * UP)
self.txt_event_prob_e_b_not_h[0].next_to(
self.mtex_event_prob_e_b_not_h, buff=var_buff)
self.txt_event_prob_e_b_not_h[1].next_to(
self.mtex_event_prob_e_b_not_h, buff=var_buff)
myutil.critical_point_move_to(self.txt_event_prob_e_b_not_h[2],
LEFT + DOWN, 3.5 * RIGHT + -3.1 * UP)
def create_bayes_eq(self):
"""create all mobjects
"""
self.txt_title_bayes = Text(r"再検査の効果").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN,
ORIGIN + -6.3 * RIGHT + 3.0 * UP)
# full Bayes form # indices for h,e color (MathTex removes white space))
self.mtex_bayes_full = MathTex(
r"P(H|E)", # [0] e [0,4], h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(H)", # [5] h [5,2]
r"P(E|H)}", # [6] e [6,2], h [6,4]
r"+", # [7]
r"{P(\lnot H)", # [8] h [8,3], n [8,2]
r"P(E |\lnot H)}}", # [9] e [9,2], h [9,5], n [9,4]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_full, LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4], [5, 2], [6, 4], [8, 3],
[9, 5]]
for [i, j] in self.h_indices:
self.mtex_bayes_full[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [6, 2], [9, 2]]
for [i, j] in self.e_indices:
self.mtex_bayes_full[i][j].set_color(self.col_e)
self.n_indices = [[8, 2], [9, 4]]
for [i, j] in self.n_indices:
self.mtex_bayes_full[i][j].set_color(self.col_n)
# 11 people example values
self.p_h_nom = MathTex(r"P(H)", r"=", r"0.09").scale(
self.scale_eq_f).move_to(-2.0 * RIGHT + +0.5 * UP)
self.p_h_nom[0][2].set_color(self.col_h)
self.p_h_den = copy.deepcopy(self.p_h_nom)
# P(E|H) nominator term, denominator
self.p_e_h_nom = MathTex(r"P(E|H)", r"=", r"1.0").scale(
self.scale_eq_f).move_to(+2.5 * RIGHT + +0.5 * UP)
self.p_e_h_nom[0][2].set_color(self.col_e)
self.p_e_h_nom[0][4].set_color(self.col_h)
self.p_e_h_den = copy.deepcopy(self.p_e_h_nom)
# P(\lnot H)
self.p_not_h_den = MathTex(r"P(\lnot H)", r"=", r"0.91").scale(
self.scale_eq_f).move_to(-2.2 * RIGHT + -0.5 * UP)
self.p_not_h_den[0][2].set_color(self.col_n)
self.p_not_h_den[0][3].set_color(self.col_h)
# P(E|\lnot H)
self.p_e_not_h_den = MathTex(r"P(E|\lnot H)", r"=", r"0.01").scale(
self.scale_eq_f).move_to(+2.5 * RIGHT + -0.5 * UP)
self.p_e_not_h_den[0][2].set_color(self.col_e)
self.p_e_not_h_den[0][4].set_color(self.col_n)
self.p_e_not_h_den[0][5].set_color(self.col_h)
# # simple from the figure
# self.p_h_e_simple = MathTex(r"P(H|E)", r"=", r"{1", r"\over", r"11}", r"\approx", r"0.09").\
# scale(self.scale_eq_f).move_to(0.0 * RIGHT + +2.0 * UP)
# self.p_h_e_simple[0][2].set_color(self.col_h)
# self.p_h_e_simple[0][4].set_color(self.col_e)
# --- Event examples
# event example H
self.mtex_event_h = MathTex(r"H").scale(
self.scale_event_eq_f).set_color(self.col_h).move_to(0.2 * RIGHT +
3.2 * UP)
self.txt_event_h = Text(r": 病気").scale(
self.scale_event_txt_f).move_to(1.3 * RIGHT + 3.2 * UP)
# event example E
self.mtex_event_e = MathTex(r"E").scale(
self.scale_event_eq_f).set_color(self.col_e).move_to(2.7 * RIGHT +
3.17 * UP)
self.txt_event_e = Text(r": 検査＋", t2c={
r"[3:4]": self.col_positive
}).scale(self.scale_event_txt_f).move_to(4.0 * RIGHT + 3.17 * UP)
# 11 people position
self.nb_people = self.nb_true_positive + self.nb_false_positive
# create 11 people
self.svg_people = []
for i in range(0, self.nb_people):
pos = self.people_pos_left + i * self.people_delta_dist
person = SVGMobject("svg/person_silhouette", fill_opacity=1.0).scale(self.person_size).\
move_to(pos).set_color(self.col_false_positive)
self.svg_people.append(person)
# true positive color
self.svg_people[0].set_color(self.col_positive)
# move true positive label
self.label_true_positive = myutil.LabeledRectangle(Text(
r"真＋", t2c={
"[0:1]": WHITE,
"[1:2]": WHITE
}).scale(self.scale_label_txt),
tip_direction=DOWN,
color=RED,
fill_color=RED,
fill_opacity=1.0)
myutil.critical_point_move_to(self.label_true_positive, DOWN, self.people_pos_left).\
shift(self.person_size * self.label_shift_up * UP)
self.label_false_positives = []
for i in range(0, self.nb_false_positive):
fpos_dst = self.people_pos_left + (
i + self.nb_true_positive) * self.people_delta_dist
label_fpos = myutil.LabeledRectangle(
Text(
r"偽＋".format(i), # i is for debug
t2c={
"[0:1]": BLACK,
"[1:2]": RED,
"[2:]": BLACK
}).scale(self.scale_label_txt),
tip_direction=DOWN,
color=WHITE,
fill_color=WHITE,
fill_opacity=1.0)
self.label_false_positives.append(label_fpos)
# move false positive label
myutil.critical_point_move_to(self.label_false_positives[i], DOWN, fpos_dst).\
shift(self.person_size * self.label_shift_up * UP)
if (i % 2 == 0):
self.label_false_positives[i].shift(self.label_shift_up * UP)
self.rhs = MathTex(r"\approx", r"0.91").scale(
self.scale_eq_f).move_to(-2.4 * RIGHT + 2.0 * UP)
self.text_repeat = Text(r"独立した再検査によって精度向上").scale(
self.scale_txt_f).move_to(-1.0 * RIGHT + 1.0 * UP)
def create_title(self):
"""
"""
scale_f = 0.7
self.txt_title_ja = Text(r"病気の検査とベイズの定理").scale(self.scale_title_f)
self.txt_title_en = Text(
r"Medical Diagnosis and Bayes' Theorem").scale(self.scale_txt_f)
self.txt_ref_video = [
Text(r"参考ビデオ(英語)").scale(self.scale_txt_f),
Text(r"* 3Blue1Brown: Bayes theorem").scale(self.scale_txt_f),
Text(r"* Numberphile: Are you REALLY sick?").scale(
self.scale_txt_f),
Text(r"* Veritasium: The Bayesian Trap").scale(self.scale_txt_f)
]
self.txt_footnote_en = Text(
r"The video narration is in Japanese with English subtitles."
).scale(self.scale_txt_f * 0.85)
myutil.critical_point_move_to(self.txt_title_ja, LEFT + DOWN,
ORIGIN + -6 * RIGHT + 2.8 * UP)
myutil.critical_point_move_to(self.txt_title_en, LEFT + DOWN,
ORIGIN + -6 * RIGHT + 1.8 * UP)
myutil.critical_point_move_to(self.txt_ref_video[0], LEFT + DOWN,
ORIGIN + -6 * RIGHT + 0.5 * UP)
myutil.critical_point_move_to(self.txt_ref_video[1], LEFT + DOWN,
ORIGIN + -5.5 * RIGHT + -0.5 * UP)
myutil.critical_point_move_to(self.txt_ref_video[2], LEFT + DOWN,
ORIGIN + -5.5 * RIGHT + -1.4 * UP)
myutil.critical_point_move_to(self.txt_ref_video[3], LEFT + DOWN,
ORIGIN + -5.5 * RIGHT + -2.3 * UP)
myutil.critical_point_move_to(self.txt_footnote_en, LEFT + DOWN,
ORIGIN + -6.5 * RIGHT + -3.2 * UP)
def create_bayes_eq(self):
"""
"""
self.txt_title_bayes = Text(r"ベイズの定理").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN, ORIGIN + -6.3 * RIGHT + 3.0 * UP)
self.txt_how_to_read = Text(r"式の「読み方」").scale(self.scale_txt_f)
myutil.critical_point_move_to(self.txt_how_to_read, LEFT + DOWN, ORIGIN + -1.0 * RIGHT + 3.0 * UP)
# simple Bayes form # indices for h,e color
self.mtex_bayes_simple = MathTex(r"P(H|E)", # e [0,4] h [0,2]
r"={", #
r"{P(H)", # h [2,2]
r"P(E|H)}", # e [3,2], h [3,4]
r"\over", #
r"{P(E)}", # e [5,2]
r"}", #
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_simple, LEFT + DOWN, ORIGIN + -5.0 * RIGHT + 1.1 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4]]
for [i,j] in self.h_indices:
self.mtex_bayes_simple[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [5, 2]]
for [i,j] in self.e_indices:
self.mtex_bayes_simple[i][j].set_color(self.col_e)
# events notation
self.tex_events_eq = MathTex(r"E", r",", r"H", r", A, B:").scale(self.scale_eq_f)
self.tex_events_eq[0].set_color(self.col_e)
self.tex_events_eq[2].set_color(self.col_h)
self.txt_events_exp = [
Text(r"事象 (Event): ").scale(self.scale_txt_f),
Text(r"病気, "). scale(self.scale_txt_f),
Text(r"検査＋", t2c={r"＋": self.col_positive},).scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.tex_events_eq, LEFT + DOWN, ORIGIN + -6.0 * RIGHT + 0.0 * UP)
myutil.critical_point_move_to(self.txt_events_exp[0], LEFT + DOWN, ORIGIN + -2.6 * RIGHT + 0.0 * UP)
for i in range(1, len(self.txt_events_exp)):
self.txt_events_exp[i].next_to(self.txt_events_exp[i-1], buff=0.2)
# conditional notation
self.tex_cond_eq = MathTex(r"H", r"|", r"E").scale(self.scale_eq_f)
self.tex_cond_eq[0].set_color(self.col_h)
self.tex_cond_eq[2].set_color(self.col_e)
myutil.critical_point_move_to(self.tex_cond_eq, LEFT + DOWN, ORIGIN + -6.0 * RIGHT + -1.0 * UP)
self.txt_cond_exp_1 = [
Text(r": Evidence (証拠)").scale(self.scale_txt_f).set_color(self.col_e),
Text(r"の時,"). scale(self.scale_txt_f),
Text(r"Hypothesis (仮説)").scale(self.scale_txt_f).set_color(self.col_h),
]
myutil.critical_point_move_to(self.txt_cond_exp_1[0], LEFT + DOWN, ORIGIN + -4.6 * RIGHT + -1.0 * UP)
for i in range(1, len(self.txt_cond_exp_1)):
self.txt_cond_exp_1[i].next_to(self.txt_cond_exp_1[i-1], buff=0.2)
# baseline adjustment of Evidence
self.txt_cond_exp_1[0].shift(0.05 * UP)
# Hypothesis given the Evidence
self.txt_cond_exp_2 = [
Text(r"Hypothesis"). scale(self.scale_txt_f).set_color(self.col_h),
Text(r"given"). scale(self.scale_txt_f),
Text(r"the Evidence").scale(self.scale_txt_f).set_color(self.col_e),
]
myutil.critical_point_move_to(self.txt_cond_exp_2[0], LEFT + DOWN, ORIGIN + -4.2 * RIGHT + -2.0 * UP)
for i in range(1, len(self.txt_cond_exp_2)):
self.txt_cond_exp_2[i].next_to(self.txt_cond_exp_2[i-1], buff=0.2)
# baseline adjustment of the Evidence
self.txt_cond_exp_2[2].shift(0.05 * UP)
# animation destination, destination of "Hypothesis of the Evidence"
self.tex_cond_eq_2 = MathTex(r"H", r"|", r"E").scale(self.scale_eq_f)
self.tex_cond_eq_2[0].set_color(self.col_h)
self.tex_cond_eq_2[2].set_color(self.col_e)
myutil.critical_point_move_to(self.tex_cond_eq_2, LEFT + DOWN, ORIGIN + -4.2 * RIGHT + -2.0 * UP)
# probability notation
self.tex_prob_eq = [
MathTex(r"P()"). scale(self.scale_eq_f),
MathTex(r"P(A)"). scale(self.scale_eq_f),
MathTex(r"P(", r"H", r"|", r"E", r")").scale(self.scale_eq_f),
]
self.tex_prob_eq[2][1].set_color(self.col_h)
self.tex_prob_eq[2][3].set_color(self.col_e)
self.txt_prob_exp = [
Text(r": 〜の確率 (Probability)").scale(self.scale_txt_f),
Text(r": A の確率"). scale(self.scale_txt_f),
Text(r": E の時に H になる確率",
t2c={"[1:2]": self.col_e, "[5:6]": self.col_h}
). scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.tex_prob_eq[0], LEFT + DOWN, ORIGIN + -6.0 * RIGHT + -2.0 * UP)
myutil.critical_point_move_to(self.tex_prob_eq[1], LEFT + DOWN, ORIGIN + 2.0 * RIGHT + -2.0 * UP)
myutil.critical_point_move_to(self.tex_prob_eq[2], LEFT + DOWN, ORIGIN + -6.0 * RIGHT + -3.0 * UP)
for i in range(0, len(self.txt_prob_exp)):
self.txt_prob_exp[i].next_to(self.tex_prob_eq[i])
def animate_positive_only(self):
"""Get positive only
"""
people_negative_xy_idx = []
for iy in range(0, self.nb_people_y):
for ix in range(0, self.nb_people_x):
if ([ix, iy] in self.true_positive_pcoords):
# skip true positive
continue
if ([ix, iy] in self.false_positive_pcoords):
# skip false positive
continue
people_negative_xy_idx.append([ix, iy])
people_negative = []
for pcoord in people_negative_xy_idx:
people_negative.append(
self.svg_people[self.get_person_1d_idx(pcoord)])
person_size = 0.9
nb_person = 11
nb_true_positive = 1
people_pos_left = -5.5 * RIGHT + -2.5 * UP
people_delta_dist = 1.1 * RIGHT
label_shift_up = 1.0
if (self.is_show_only):
# remove people negative
self.remove(*people_negative)
# move true positive
tpos_idx = self.get_person_1d_idx(self.true_positive_pcoords[0])
tpos_dst = people_pos_left
self.svg_people[tpos_idx].scale(
person_size * (1.0 / self.size_person_1000)).move_to(tpos_dst)
# move true positive label
myutil.critical_point_move_to(self.label_true_positive, DOWN, tpos_dst).\
shift(person_size * label_shift_up * UP)
for i in range(0, len(self.false_positive_pcoords)):
fpos_idx = self.get_person_1d_idx(
self.false_positive_pcoords[i])
# move false positive
fpos_dst = people_pos_left + (
i + nb_true_positive) * people_delta_dist
self.svg_people[fpos_idx].scale(
person_size *
(1.0 / self.size_person_1000)).move_to(fpos_dst)
# move false positive label
myutil.critical_point_move_to(self.label_false_positive[i], DOWN, fpos_dst).\
shift(person_size * label_shift_up * UP)
if (i % 2 == 0):
self.label_false_positive[i].shift(label_shift_up * UP)
return
# remove people negative
self.play(*[FadeOut(mobj) for mobj in people_negative])
# move true positive
tpos_idx = self.get_person_1d_idx(self.true_positive_pcoords[0])
tpos_dst = people_pos_left
# make true positive front
self.remove(self.svg_people[tpos_idx], self.label_true_positive)
self.add(self.svg_people[tpos_idx], self.label_true_positive)
# move true positive label (create a dummy and use for the destination position calculation)
tpos_label_dst_tmp = copy.deepcopy(self.label_true_positive)
myutil.critical_point_move_to(tpos_label_dst_tmp, DOWN,
tpos_dst).shift(person_size *
label_shift_up * UP)
# create a dummy dstination copy
tpos_person_dst_tmp = copy.deepcopy(self.svg_people[tpos_idx])
tpos_person_dst_tmp.scale(
person_size * (1.0 / self.size_person_1000)).move_to(tpos_dst)
self.play(
Transform(self.svg_people[tpos_idx], tpos_person_dst_tmp),
ApplyMethod(self.label_true_positive.move_to,
tpos_label_dst_tmp.get_center()))
self.wait(self.time_wait)
# Same as the true positive people and labels
fpos_trans = []
label_move = []
for i in range(0, len(self.false_positive_pcoords)):
fpos_idx = self.get_person_1d_idx(self.false_positive_pcoords[i])
fpos_dst = people_pos_left + (i +
nb_true_positive) * people_delta_dist
ptmp = copy.deepcopy(self.svg_people[fpos_idx])
ptmp.scale(person_size *
(1.0 / self.size_person_1000)).move_to(fpos_dst)
fpos_trans.append(Transform(self.svg_people[fpos_idx], ptmp))
ltmp = copy.deepcopy(self.label_false_positive[i])
myutil.critical_point_move_to(ltmp, DOWN, fpos_dst).shift(
person_size * label_shift_up * UP)
if (i % 2 == 0):
ltmp.shift(label_shift_up * UP)
label_move.append(
ApplyMethod(self.label_false_positive[i].move_to,
ltmp.get_center()))
self.play(*fpos_trans, *label_move)
self.wait(self.time_wait)
def create_bayes_eq(self):
"""create all mobjects
"""
self.txt_title_bayes = Text(r"具体例 2").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN,
ORIGIN + -6.3 * RIGHT + 3.0 * UP)
# full Bayes form # indices for h,e color (MathTex removes white space))
self.mtex_bayes_full = MathTex(
r"P(H|E)", # [0] e [0,4], h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(H)", # [5] h [5,2]
r"P(E|H)}", # [6] e [6,2], h [6,4]
r"+", # [7]
r"{P(\lnot H)", # [8] h [8,3], n [8,2]
r"P(E |\lnot H)}}", # [9] e [9,2], h [9,5], n [9,4]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_full, LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4], [5, 2], [6, 4], [8, 3],
[9, 5]]
for [i, j] in self.h_indices:
self.mtex_bayes_full[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [6, 2], [9, 2]]
for [i, j] in self.e_indices:
self.mtex_bayes_full[i][j].set_color(self.col_e)
self.n_indices = [[8, 2], [9, 4]]
for [i, j] in self.n_indices:
self.mtex_bayes_full[i][j].set_color(self.col_n)
# 1000 people example values
self.p_h_nom = MathTex(r"0.001").scale(self.scale_eq_f).move_to(
self.mtex_bayes_full[2].get_center())
self.p_h_den = MathTex(r"0.001").scale(self.scale_eq_f).move_to(
self.mtex_bayes_full[5].get_center())
# P(E|H) nominator term, denominator
self.p_e_h_nom = MathTex(r"1.0").scale(self.scale_eq_f).move_to(
self.mtex_bayes_full[3].get_center())
self.p_e_h_den = MathTex(r"1.0").scale(self.scale_eq_f).move_to(
self.mtex_bayes_full[6].get_center())
# P(\lnot H)
self.p_not_h_den = MathTex(r"0.999").scale(self.scale_eq_f).move_to(
self.mtex_bayes_full[8].get_center())
# P(E|\lnot H)
self.p_e_not_h_den = MathTex(r"0.01").scale(self.scale_eq_f).move_to(
self.mtex_bayes_full[9].get_center())
# simple from the figure
self.p_h_e_simple = MathTex(r"P(H|E)", r"=", r"{1", r"\over", r"11}", r"\approx", r"0.09").\
scale(self.scale_eq_f).move_to(-3.0 * RIGHT + +2.0 * UP)
self.p_h_e_simple[0][2].set_color(self.col_h)
self.p_h_e_simple[0][4].set_color(self.col_e)
self.mtex_exp = MathTex(r"P(H)", r"\ll", r"P(E|\lnot H)").\
scale(self.scale_eq_f).move_to(2.0 * RIGHT + +2.0 * UP)
self.mtex_exp[0][2].set_color(self.col_h)
self.mtex_exp[2][2].set_color(self.col_e)
self.mtex_exp[2][4].set_color(self.col_n)
self.mtex_exp[2][5].set_color(self.col_h)
self.text_exp = Text(r"1% 間違える方法で 0.1% を見つける難しさ").scale(self.scale_txt_f).\
move_to(0.0 * RIGHT + +1.1 * UP)
# --- Event examples
# event example H
self.mtex_event_h = MathTex(r"H").scale(
self.scale_event_eq_f).set_color(self.col_h).move_to(0.2 * RIGHT +
3.2 * UP)
self.txt_event_h = Text(r": 病気").scale(
self.scale_event_txt_f).move_to(1.3 * RIGHT + 3.2 * UP)
# event example E
self.mtex_event_e = MathTex(r"E").scale(
self.scale_event_eq_f).set_color(self.col_e).move_to(2.7 * RIGHT +
3.17 * UP)
self.txt_event_e = Text(r": 検査＋", t2c={
r"[3:4]": self.col_positive
}).scale(self.scale_event_txt_f).move_to(4.0 * RIGHT + 3.17 * UP)
# show 1000 people
self.people_dx = (self.pos_people_max[0] -
self.pos_people_min[0]) / (self.nb_people_x - 1)
self.people_dy = (self.pos_people_max[1] -
self.pos_people_min[1]) / (self.nb_people_y - 1)
self.svg_people = []
for iy in range(0, self.nb_people_y):
for ix in range(0, self.nb_people_x):
pos = self.get_person_position([ix, iy])
person = SVGMobject("svg/person_silhouette", fill_opacity=1.0).scale(self.size_person_1000).\
move_to(pos).set_color(self.color_people)
self.svg_people.append(person)
# true positive label
pos = self.get_person_position(self.true_positive_pcoords[0])
self.label_true_positive = myutil.LabeledRectangle(Text(
r"真＋", t2c={
"[0:1]": WHITE,
"[1:2]": WHITE
}).scale(self.scale_label_txt),
tip_direction=DOWN,
color=RED,
fill_color=RED,
fill_opacity=1.0)
myutil.critical_point_move_to(self.label_true_positive, DOWN,
pos).shift(self.size_person_1000 * 0.8 *
UP)
# false positive label
idx = 0
self.label_false_positive = []
for pcoord in self.false_positive_pcoords:
lr = myutil.LabeledRectangle(Text(r"偽＋".format(idx),
t2c={
"[0:1]": BLACK,
"[1:2]": RED,
"[2:]": BLACK
}).scale(self.scale_label_txt),
tip_direction=DOWN,
color=WHITE,
fill_color=WHITE,
fill_opacity=1.0)
pos = self.get_person_position(pcoord)
myutil.critical_point_move_to(lr, DOWN, pos).shift(
self.size_person_1000 * 0.8 * UP)
self.label_false_positive.append(lr)
idx += 1
def create_text(self):
"""
"""
self.txt_want_to_know = Text(r"検査が不完全な時に知りたいこと").scale(
self.scale_title_f)
myutil.critical_point_move_to(self.txt_want_to_know, LEFT + DOWN,
ORIGIN + -6.0 * RIGHT + 2.5 * UP)
self.txt_test_positive = [
Text(r"1.検査結果").scale(self.scale_txt_f),
Text(r"＋", color=self.col_positive).scale(self.scale_txt_f),
Text(r"の時").scale(self.scale_txt_f),
Text(r"，実際に病気").scale(self.scale_txt_f),
Text(r"の可能性").scale(self.scale_txt_f),
]
self.txt_test_negative = [
Text(r"2.検査結果").scale(self.scale_txt_f),
Text(r"−", color=self.col_negative).scale(self.scale_txt_f),
Text(r"の時").scale(self.scale_txt_f),
Text(r"，実際に¬病気", t2c={
"[4:5]": self.col_n
}).scale(self.scale_txt_f),
Text(r"の可能性").scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.txt_test_positive[0], LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.5 * UP)
myutil.critical_point_move_to(self.txt_test_negative[0], LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 0.5 * UP)
for i in range(1, len(self.txt_test_positive)):
self.txt_test_positive[i].next_to(self.txt_test_positive[i - 1],
buff=0.1)
self.txt_test_negative[i].next_to(self.txt_test_negative[i - 1],
buff=0.1)
# Underlines
pos_when_beg = [
self.txt_test_positive[2].get_critical_point(LEFT + DOWN) +
self.line_down_offset * DOWN, # の時 0
self.txt_test_negative[2].get_critical_point(LEFT + DOWN) +
self.line_down_offset * DOWN, # の時 1
self.txt_test_positive[4].get_critical_point(LEFT + DOWN) +
self.line_down_offset * DOWN, # の可能性 0
self.txt_test_negative[4].get_critical_point(LEFT + DOWN) +
self.line_down_offset * DOWN, # の可能性 1
]
pos_when_end = [
self.txt_test_positive[2].get_critical_point(RIGHT + DOWN) +
self.line_down_offset * DOWN, # の時 0
self.txt_test_negative[2].get_critical_point(RIGHT + DOWN) +
self.line_down_offset * DOWN, # の時 1
self.txt_test_positive[4].get_critical_point(RIGHT + DOWN) +
self.line_down_offset * DOWN, # の可能性 0
self.txt_test_negative[4].get_critical_point(RIGHT + DOWN) +
self.line_down_offset * DOWN, # の可能性 1
]
self.line_cond = [
Line(pos_when_beg[0],
pos_when_end[0],
color=self.line_color_when,
stroke_width=self.line_stroke_when),
Line(pos_when_beg[1],
pos_when_end[1],
color=self.line_color_when,
stroke_width=self.line_stroke_when)
]
self.line_possibility = [
Line(pos_when_beg[2],
pos_when_end[2],
color=self.line_color_cond,
stroke_width=self.line_stroke_when),
Line(pos_when_beg[3],
pos_when_end[3],
color=self.line_color_cond,
stroke_width=self.line_stroke_when)
]
# ベイズの定理 (Bayes theorem)
self.txt_bayes_1 = Text(r"ベイズの定理 (Bayes theorem)").scale(
self.scale_txt_f)
myutil.critical_point_move_to(self.txt_bayes_1, LEFT + DOWN,
ORIGIN + -6.0 * RIGHT + -1.0 * UP)
# E の時，H の可能性
self.txt_bayes_2 = [
Text(r"E ").scale(self.scale_txt_f),
Text(r"の時").scale(self.scale_txt_f),
Text(r"，H ").scale(self.scale_txt_f),
Text(r"の可能性").scale(self.scale_txt_f),
Text(r"→").scale(self.scale_txt_f),
Text(r"E ", color=YELLOW).scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.txt_bayes_2[0], LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + -2.0 * UP)
for i in range(1, len(self.txt_bayes_2)):
self.txt_bayes_2[i].next_to(self.txt_bayes_2[i - 1], buff=0.1)
# repeat E の時，H の可能性
self.txt_bayes_3 = [
Text(r"E ").scale(self.scale_txt_f),
Text(r"の時").scale(self.scale_txt_f),
Text(r"，H ").scale(self.scale_txt_f),
Text(r"の可能性").scale(self.scale_txt_f),
]
myutil.critical_point_move_to(self.txt_bayes_3[0], LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + -3.0 * UP)
for i in range(1, len(self.txt_bayes_3)):
self.txt_bayes_3[i].next_to(self.txt_bayes_3[i - 1], buff=0.1)
self.txt_e_changes_h = Text(r"証拠により可能性が変化")
def create_bayes_eq(self):
"""create all mobjects
"""
self.txt_title_bayes = Text(r"具体例 1").scale(self.scale_title_f)
myutil.critical_point_move_to(self.txt_title_bayes, LEFT + DOWN,
ORIGIN + -6.3 * RIGHT + 3.0 * UP)
# full Bayes form # indices for h,e color (MathTex removes white space))
self.mtex_bayes_full = MathTex(
r"P(H|E)", # [0] e [0,4], h [0,2]
r"={", # [1]
r"{P(H)", # [2] h [2,2]
r"P(E|H)}", # [3] e [3,2], h [3,4]
r"\over", # [4]
r"{P(H)", # [5] h [5,2]
r"P(E|H)}", # [6] e [6,2], h [6,4]
r"+", # [7]
r"{P(\lnot H)", # [8] h [8,3], n [8,2]
r"P(E |\lnot H)}}", # [9] e [9,2], h [9,5], n [9,4]
).scale(self.scale_eq_f)
myutil.critical_point_move_to(self.mtex_bayes_full, LEFT + DOWN,
ORIGIN + -5.0 * RIGHT + 1.4 * UP)
self.h_indices = [[0, 2], [2, 2], [3, 4], [5, 2], [6, 4], [8, 2],
[8, 3], [9, 4], [9, 5]]
for [i, j] in self.h_indices:
self.mtex_bayes_full[i][j].set_color(self.col_h)
self.e_indices = [[0, 4], [3, 2], [6, 2], [9, 2]]
for [i, j] in self.e_indices:
self.mtex_bayes_full[i][j].set_color(self.col_e)
self.n_indices = [[8, 2], [9, 4]]
for [i, j] in self.n_indices:
self.mtex_bayes_full[i][j].set_color(self.col_n)
# --- Event examples
# event example H
self.mtex_event_h = MathTex(r"H"). scale(self.scale_event_eq_f).set_color(self.col_h).\
move_to(0.2 * RIGHT + 3.4 * UP)
self.txt_event_h = Text(r": 病気").scale(self.scale_event_txt_f).\
move_to(1.3 * RIGHT + 3.4 * UP)
# event example E
self.mtex_event_e = MathTex(r"E").scale(self.scale_event_eq_f).set_color(self.col_e).\
move_to(2.7 * RIGHT + 3.37 * UP)
self.txt_event_e = Text(r": 検査＋", t2c={r"[3:4]": self.col_positive}).\
scale(self.scale_event_txt_f).move_to(4.0 * RIGHT + 3.37 * UP)
# show ten people
person_size = 0.9
nb_person = 10
nb_sick = 4
nb_false_positive = 2
nb_total_positive = nb_sick + nb_false_positive
people_pos_left = -4.5 * RIGHT + -2.5 * UP
people_delta_dist = 1.0 * RIGHT
self.svg_people = []
for i in range(0, nb_person):
pos = people_pos_left + i * people_delta_dist
person = SVGMobject("svg/person_silhouette").scale(
person_size).move_to(pos).set_color(self.color_people)
self.svg_people.append(person)
# 4 real sick people
sign_scale = 1.0
sick_sign = Text(r"病").scale(sign_scale).set_color(self.col_ill_sign)
self.sick_signs = []
for i in range(0, nb_sick):
self.sick_signs.append(copy.deepcopy(sick_sign))
for i in range(0, nb_sick):
pos = people_pos_left + (
i) * people_delta_dist + -0.3 * RIGHT + -0.15 * UP
myutil.critical_point_move_to(self.sick_signs[i], LEFT + DOWN, pos)
# 6 test positive
test_p_sign = Text(r"＋").scale(sign_scale).set_color(self.col_positive)
self.test_positive_signs = []
for i in range(0, nb_total_positive):
self.test_positive_signs.append(copy.deepcopy(test_p_sign))
for i in range(0, nb_total_positive):
pos = people_pos_left + (
i) * people_delta_dist + -0.25 * RIGHT + +1.0 * UP
myutil.critical_point_move_to(self.test_positive_signs[i],
LEFT + DOWN, pos)
# lines for brance anotation
br_up_off = 1.6 * UP
br_beg_off = 0.5 * LEFT
br_end_off = 0.5 * RIGHT
pos_sick_begin = self.svg_people[0].get_center(
) + br_up_off + br_beg_off
pos_sick_end = self.svg_people[nb_sick -
1].get_center() + br_up_off + br_end_off
pos_no_sick_begin = self.svg_people[nb_sick].get_center(
) + br_up_off + br_beg_off
pos_no_sick_end = self.svg_people[
nb_person - 1].get_center() + br_up_off + br_end_off
pos_false_pos_begin = self.svg_people[nb_sick].get_center(
) + br_up_off + br_beg_off
pos_false_pos_end = self.svg_people[
nb_total_positive - 1].get_center() + br_up_off + br_end_off
self.line_annot["sick"] = Line(pos_sick_begin, pos_sick_end)
self.line_annot["no_sick"] = Line(pos_no_sick_begin,
pos_no_sick_end).set_color(YELLOW)
self.line_annot["true_positive"] = Line(pos_sick_begin,
pos_sick_end).set_color(RED)
self.line_annot["false_positive"] = Line(
pos_false_pos_begin, pos_false_pos_end).set_color(BLUE)
self.line_annot["total_positive"] = Line(
pos_sick_begin, pos_false_pos_end).set_color(GREEN)
for key in self.line_annot:
self.brace_annot[key] = Brace(self.line_annot[key], UP)
self.mtex_annot["sick"] = self.brace_annot["sick"].get_tex(r"H")
self.mtex_annot["sick"].set_color(self.col_h)
self.mtex_annot["no_sick"] = self.brace_annot["no_sick"].get_tex(
r"\lnot", r"H")
self.mtex_annot["no_sick"][0].set_color(self.col_n)
self.mtex_annot["no_sick"][1].set_color(self.col_h)
self.mtex_annot["true_positive"] = self.brace_annot[
"true_positive"].get_tex(r"E", r"|", r"H")
self.mtex_annot["true_positive"][0].set_color(self.col_e)
self.mtex_annot["true_positive"][2].set_color(self.col_h)
self.mtex_annot["false_positive"] = self.brace_annot[
"false_positive"].get_tex(r"E", r"|", r"\lnot", r" H")
self.mtex_annot["false_positive"][0].set_color(self.col_e)
self.mtex_annot["false_positive"][2].set_color(self.col_n)
self.mtex_annot["false_positive"][3].set_color(self.col_h)
self.mtex_annot["total_positive"] = self.brace_annot[
"total_positive"].get_tex(r"E")
self.mtex_annot["total_positive"].set_color(self.col_e)
self.text_annot["sick"] = Text(r"病気").scale(self.scale_txt_f)
self.text_annot["no_sick"] = Text(r"¬病気", t2c={
"[0:1]": self.col_n
}).scale(self.scale_txt_f)
self.text_annot["true_positive"] = Text(r"病気の時，検査＋",
t2c={
"[7:8]": self.col_positive
}).scale(self.scale_txt_f)
self.text_annot["false_positive"] = Text(r"¬病気の時，検査＋",
t2c={
"[0:1]": self.col_n,
"[8:9]": self.col_positive
}).scale(self.scale_txt_f)
self.text_annot["total_positive"] = Text(r"検査＋",
t2c={
"[2:3]": self.col_positive
}).scale(self.scale_txt_f)
# copy the math tex position to text
for key in self.annot_key:
self.text_annot[key].move_to(self.mtex_annot[key].get_center())