def plot_district_age_distribution(percentiles,
ylabel,
fmt,
phi=50,
vax_policy="random",
N_jk=None,
n=5,
district_spacing=1.5,
age_spacing=0.1,
rotation=0):
fig = plt.figure()
district_ordering = list(districts_to_run.index)[:n]
for (i, district) in enumerate(district_ordering):
ylls = percentiles[district, phi, vax_policy]
for j in range(7):
plt.errorbar(x=[district_spacing * i + age_spacing * (j - 3)],
y=ylls[1, 6 - j] * USD /
(N_jk[f"N_{6-j}"][district] if N_jk else 1),
yerr=[[(ylls[1, 6 - j] - ylls[0, 6 - j]) * USD /
(N_jk[f"N_{6-j}"][district] if N_jk else 1)],
[(ylls[2, 6 - j] - ylls[1, 6 - j]) * USD /
(N_jk[f"N_{6-j}"][district] if N_jk else 1)]],
fmt=fmt,
color=age_group_colors[6 - j],
figure=fig,
label=None if i > 0 else age_bin_labels[6 - j],
ms=12,
elinewidth=5)
plt.xticks([1.5 * _ for _ in range(n)],
district_ordering,
rotation=rotation,
fontsize="20")
plt.yticks(fontsize="20")
plt.legend(title="age bin",
title_fontsize="20",
fontsize="20",
ncol=7,
loc="lower center",
bbox_to_anchor=(0.5, 1))
ymin, ymax = plt.ylim()
plt.vlines(x=[0.75 + 1.5 * _ for _ in range(n - 1)],
ymin=ymin,
ymax=ymax,
color="gray",
alpha=0.5,
linewidths=2)
plt.ylim(ymin, ymax)
plt.gca().grid(False, axis="x")
plt.PlotDevice().title(f"\n{vax_policy} demand curves").ylabel(
f"{ylabel}\n")
def plot_state_age_distribution(percentiles,
ylabel,
fmt,
district_spacing=1.5,
n=5,
age_spacing=0.1,
rotation=0,
ymin=0,
ymax=1000):
fig = plt.figure()
state_ordering = list(
sorted(percentiles.keys(),
key=lambda k: percentiles[k][0].max(),
reverse=True))
for (i, state) in enumerate(state_ordering[:n]):
ylls = percentiles[state]
for j in range(7):
plt.errorbar(x=[district_spacing * i + age_spacing * (j - 3)],
y=ylls[0, 6 - j],
yerr=[[(ylls[0, 6 - j] - ylls[1, 6 - j])],
[(ylls[2, 6 - j] - ylls[0, 6 - j])]],
fmt=fmt,
color=agebin_colors[6 - j],
figure=fig,
label=None if i > 0 else agebin_labels[6 - j],
ms=12,
elinewidth=5)
plt.xticks([1.5 * _ for _ in range(n)],
state_ordering,
rotation=rotation,
fontsize="20")
plt.yticks(fontsize="20")
# plt.legend(title = "age bin", title_fontsize = "20", fontsize = "20", ncol = 7,
plt.legend(fontsize="20",
ncol=7,
loc="lower center",
bbox_to_anchor=(0.5, 1))
plt.vlines(x=[0.75 + 1.5 * _ for _ in range(n - 1)],
ymin=ymin,
ymax=ymax,
color="gray",
alpha=0.5,
linewidths=4)
plt.ylim(ymin, ymax)
plt.gca().grid(False, axis="x")
plt.PlotDevice().ylabel(f"{ylabel}\n")
def outcomes_per_policy(percentiles,
metric_label,
fmt,
phis=[25, 50, 100, 200],
reference=(25, "no_vax"),
reference_color=no_vax_color,
vax_policies=["contact", "random", "mortality"],
policy_colors=[
contactrate_vax_color, random_vax_color,
mortality_vax_color
],
policy_labels=[
"contact rate priority", "random assignment",
"mortality priority"
],
spacing=0.2):
fig = plt.figure()
md, lo, hi = percentiles[reference]
*_, bars = plt.errorbar(x=[0],
y=[md],
yerr=[[md - lo], [hi - md]],
figure=fig,
fmt=fmt,
color=reference_color,
label="no vaccination",
ms=12,
elinewidth=5)
[_.set_alpha(0.5) for _ in bars]
plt.hlines(md,
xmin=-1,
xmax=5,
linestyles="dotted",
colors=reference_color)
for (i, phi) in enumerate(phis, start=1):
for (j, (vax_policy, color, label)) in enumerate(
zip(vax_policies, policy_colors, policy_labels)):
md, lo, hi = death_percentiles[phi, vax_policy]
*_, bars = plt.errorbar(x=[i + spacing * (j - 1)],
y=[md],
yerr=[[md - lo], [hi - md]],
figure=fig,
fmt=fmt,
color=color,
label=label if i == 0 else None,
ms=12,
elinewidth=5)
[_.set_alpha(0.5) for _ in bars]
plt.legend(ncol=4,
fontsize="20",
loc="lower center",
bbox_to_anchor=(0.5, 1))
plt.xticks(range(len(phis) + 1),
[f"$\phi = {phi}$%" for phi in ([0] + phis)],
fontsize="20")
plt.yticks(fontsize="20")
plt.PlotDevice().ylabel(f"{metric_label}\n")
plt.gca().grid(False, axis="x")
ymin, ymax = plt.ylim()
plt.vlines(x=[0.5 + _ for _ in range(len(phis))],
ymin=ymin,
ymax=ymax,
color="gray",
alpha=0.5,
linewidths=2)
plt.ylim(ymin, ymax)
plt.xlim(-0.5, len(phis) + 1.5)
Rt_dist = {
k: v
for (k, v) in sorted(Rt_dist.items(), key=lambda e: e[1][0], reverse=True)
if v != [0, 0, 0]
}
md, hi, lo = map(np.array, list(zip(*Rt_dist.values())))
*_, bars = plt.errorbar(
# x = [-2] + list(range(len(md))),
x=list(range(len(md))),
# y = np.r_[Rt_TTn, md],
y=md,
# yerr = [
# np.r_[Rt_TTn - Rt_CI_lower_TTn, md - lo],
# np.r_[Rt_CI_upper_TTn - Rt_TTn, hi - md]
# ],
yerr=[md - lo, hi - md],
fmt="s",
color=plt.BLK,
ms=8,
elinewidth=10,
label="$R_t$ (95% CI)")
[_.set_alpha(0.3) for _ in bars]
# plt.hlines(Rt_TTn, xmin = -3, xmax = len(md) + 1, linestyles = "dotted", colors = plt.BLK)
# plt.vlines(-1, ymin = 0, ymax = 6, linewidth = 3, colors = "black")
plt.ylim(bottom=0, top=6)
# plt.xlim(left = -3, right = len(md))
plt.xlim(left=-1, right=len(md))
plt.PlotDevice().ylabel("reproductive rate ($R_t$)\n").xlabel("\nstate")
# plt.xticks(ticks = [-2] + list(range(len(md))), labels = ["India"] + [state_name_lookup[_][:2] for _ in Rt_dist.keys()], fontsize = "20")
zip(
[
contact_percentiles,
], # random_percentiles, mortality_percentiles],
[
contactrate_vax_color,
] # random_vax_color, mortality_vax_color]
)):
for (i, (key, (lo, md, hi))) in enumerate(metrics.items()):
*_, bars = plt.errorbar(
x=[i],
y=[md],
yerr=[[md - lo], [hi - md]],
figure=fig,
fmt="o",
color=clr,
label=None if i > 0 else [
"contact rate prioritized", "random assignment",
"mortality prioritized"
][dx],
ms=12,
elinewidth=5)
[_.set_alpha(0.5) for _ in bars]
plt.xticks(
range(len(metrics)),
[f"{phi}%" for phi in (100 * (10**np.linspace(-1, 1, 11))).round(0)],
fontsize="20")
plt.yticks(fontsize="20")
plt.PlotDevice().ylabel("deaths\n").xlabel(
"\npercentage of population vaccinated annually")
# plt.ylim(200, 450)
for (k, v) in evaluated_death_percentiles.items() if "mortality" in k
}
novax_percentiles = {
k: v
for (k, v) in evaluated_death_percentiles.items() if "novacc" in k
}
fig = plt.figure()
*_, bars = plt.errorbar(x=[-1],
y=novax_percentiles["novaccination"][1],
yerr=[
novax_percentiles["novaccination"][1] -
[novax_percentiles["novaccination"][0]],
[
novax_percentiles["novaccination"][2] -
novax_percentiles["novaccination"][1]
]
],
fmt="o",
color=no_vax_color,
label="no vaccination",
figure=fig,
ms=12,
elinewidth=5)
[_.set_alpha(0.5) for _ in bars]
for (dx, (metrics, clr)) in enumerate(
zip([contact_percentiles, random_percentiles, mortality_percentiles],
[contactrate_vax_color, random_vax_color, mortality_vax_color])):
for (i, (key, (lo, md, hi))) in enumerate(metrics.items()):
*_, bars = plt.errorbar(
x=[i + 0.2 * (dx - 1)],