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Updated compare_viruses_vr graph

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This commit is contained in:
Luis Aleixo 2021-09-21 17:10:22 +02:00
parent ca1db4ef59
commit f67f3d3ba9
1 changed files with 44 additions and 43 deletions
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87
cara/results_paper.py
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@ -488,84 +488,89 @@ def compare_concentration_curves():
def compare_viruses_vr():
# Represented as tuples of three numbers on the interval [0, 1] (e.g. (1, 0, 0)) (R, G, B)
colors = [(0., 0.5, 0.5), (0, 0, 0.5), (0.5, 0, 0)]
colors_violin = ['lightsteelblue', 'wheat', 'darkseagreen']
colors = [(0., 0.5, 0.5), (0, 0, 0.5), (0.5, 0, 0), (0., 0.78, 0.)]
colors_violin=['lightsteelblue', 'wheat', 'darkseagreen']
colors_violin_lines = ['royalblue', 'orange', 'forestgreen']
# The colors of the borders surrounding the violin plots
border_colors = [(0, 0, 0), (0, 0, 0), (0, 0, 0)]
whisker_width = 0.8
positions = [1, 2, 3, 12]
exposure_models = [exposure_module('Light activity', expiration, 'No mask').build_model(
size=SAMPLE_SIZE) for expiration in ('Breathing', 'Talking', 'Shouting')]
vrs = [np.log10(emission_rate_when_present(pop))
for pop in exposure_models]
exposure_modules = [exposure_module('Light activity', expiration, 'No mask').build_model(size=SAMPLE_SIZE) for expiration in ('Breathing', 'Talking', 'Shouting')]
vrs = [np.log10(emission_rate_when_present(module)) for module in exposure_modules]
fig, ax = plt.subplots()
ax.set_xlim((0, 11))
parts = ax.violinplot(
vrs, quantiles=[(0.05, 0.95) for _ in vrs], showextrema=False)
parts = ax.violinplot(vrs, quantiles=[(0.05, 0.95) for _ in vrs], showextrema=False)
means = [np.log10(np.mean(10 ** vr)) for vr in vrs]
ax.hlines(y=means,
xmin=[pos - whisker_width / 2 for pos in positions[:3]],
xmax=[pos + whisker_width / 2 for pos in positions[:3]],
colors=colors_violin_lines,
alpha=0.8)
xmin=[pos - whisker_width / 2 for pos in positions[:3]],
xmax=[pos + whisker_width / 2 for pos in positions[:3]],
colors=colors_violin_lines,
alpha=0.8)
for pc, color, bc in zip(parts['bodies'], colors_violin, border_colors):
pc.set_facecolor(color)
pc.set_edgecolor(bc)
pc.set_alpha(0.5)
parts['cquantiles'].set_color(
[c for c in colors_violin_lines[:3] for _ in range(2)])
parts['cquantiles'].set_color([c for c in colors_violin_lines[:3] for _ in range(2)])
parts['cquantiles'].set_alpha(1)
positions = np.linspace(4.5, 11.5, 20)
positions=np.linspace(4.5, 11.5, 20)
######### SARS-CoV-2 #########
lower_bound = [418, 216, 216, 518, 648, 878, 893, 1670,
1872, 1915, 2002, 2002, 2189, 3341, 9835, 13968, 60667]
higher_bound = [4176, 2160, 2160, 5184, 6480, 8784, 8928, 16704,
18720, 19152, 20016, 20016, 21888, 33408, 98352, 139680, 606672]
######### SARS-CoV #########
lower_bound = [418]
higher_bound = [4176]
for i in range(len(lower_bound)):
data = np.random.uniform(lower_bound[i], higher_bound[i], size=200000)
ax.boxplot(np.log10(data), positions=[positions[i]], medianprops=dict(
color=colors[0] + (0.5,)), whiskerprops=dict(color=colors[0] + (0.5,)), boxprops=dict(color=colors[0] + (0.5,)))
ax.boxplot(np.log10(data), positions=[positions[i]], medianprops=dict(color=colors[3] + (0.5,)),
whiskerprops=dict(color=colors[3] + (0.5,)), boxprops=dict(color=colors[3] + (0.5,)))
######### SARS-CoV-2 #########
lower_bound = [216, 216, 518, 648, 878, 893, 1670, 1872, 1915, 2002, 2002, 2189, 3341, 9835, 13968, 60667]
higher_bound = [2160, 2160, 5184, 6480, 8784, 8928, 16704, 18720, 19152, 20016, 20016, 21888, 33408, 98352, 139680, 606672]
for i in range(len(lower_bound)):
data = np.random.uniform(lower_bound[i], higher_bound[i], size=200000)
ax.boxplot(np.log10(data), positions=[positions[i+1]], medianprops=dict(color=colors[0]+ (0.5,)),
whiskerprops=dict(color=colors[0]+ (0.5,)), boxprops=dict(color=colors[0]+ (0.5,)))
######### Measles #########
lower_bound = [259, 8640, 39816, 124416]
higher_bound = [2592, 86400, 398160, 1244160]
for i in range(len(lower_bound)):
data = np.random.uniform(lower_bound[i], higher_bound[i], size=200000)
ax.boxplot(np.log10(data), positions=[positions[i+5]], medianprops=dict(color=colors[1] + (
0.5,)), whiskerprops=dict(color=colors[1] + (0.5,)), boxprops=dict(color=colors[1] + (0.5,)))
ax.boxplot(np.log10(data), positions=[positions[i+5]], medianprops=dict(color=colors[1]+ (0.5,)),
whiskerprops=dict(color=colors[1]+ (0.5,)), boxprops=dict(color=colors[1]+ (0.5,)))
######### Influenza #########
lower_bound = [2, 114, 1138]
higher_bound = [16, 1145, 11376]
for i in range(len(lower_bound)):
data = np.random.uniform(lower_bound[i], higher_bound[i], size=200000)
ax.boxplot(np.log10(data), positions=[positions[i+12]], medianprops=dict(color=colors[2] + (
0.5,)), whiskerprops=dict(color=colors[2] + (0.5,)), boxprops=dict(color=colors[2] + (0.5,)))
ax.boxplot(np.log10(data), positions=[positions[i+12]], medianprops=dict(color=colors[2]+ (0.5,)),
whiskerprops=dict(color=colors[2]+ (0.5,)), boxprops=dict(color=colors[2]+ (0.5,)))
######### Rhinovirus #########
lower_bound = [45]
higher_bound = [446]
for i in range(len(lower_bound)):
data = np.random.uniform(lower_bound[i], higher_bound[i], size=200000)
ax.boxplot(np.log10(data), positions=[positions[i+8]], medianprops=dict(color=(0.5, 0.5, 0.5, 0.5, )),
whiskerprops=dict(color=(0.5, 0.5, 0.5, 0.5,)), boxprops=dict(color=(0.5, 0.5, 0.5, 0.5,)))
handles = [patches.Patch(edgecolor=c, facecolor='none', label=l) for c, l in zip(
[p + (0.5,) for p in [(0., 0.5, 0.5), (0, 0, 0.5), (0.5, 0, 0), (0.5, 0.5, 0.5)]], ('SARS-CoV-2', 'Measles', 'Influenza', 'Rhinovirus'))]
handles = [patches.Patch(edgecolor=c, facecolor='none', label=l)
for c, l in zip([p + (0.5,) for p in [(0., 0.78, 0.), (0., 0.5, 0.5), (0, 0, 0.5), (0.5, 0, 0), (0.5, 0.5, 0.5)]],
('SARS-CoV', 'SARS-CoV-2', 'Measles', 'Influenza', 'Rhinovirus'))]
boxplot_legend = plt.legend(handles=handles, loc='lower right')
ax.annotate("Bus ride", xy=(6, np.log10(5500)), color='k', fontsize=8,
@ -579,21 +584,17 @@ def compare_viruses_vr():
xytext=(-50, 40), textcoords='offset points',
arrowprops=dict(arrowstyle="->",
connectionstyle="arc3,rad=-0.2", color='lightgrey'))
handles = [patches.Patch(color=c, label=l) for c, l in zip(
[p for p in colors_violin], ('Breathing', 'Speaking', 'Shouting'))]
handles = [patches.Patch(color=c, label=l) for c, l in zip([p for p in colors_violin], ('Breathing', 'Speaking', 'Shouting'))]
plt.legend(handles=handles, loc='lower left', bbox_to_anchor=(0.12, 0.))
plt.gca().add_artist(boxplot_legend)
ax.hlines(y=[-2, 0, 2, 4, 6], xmin=ax.get_xlim()[0], xmax=ax.get_xlim()
[1], colors=(0.8, 0.8, 0.8), linestyles='--', alpha=0.3)
ax.vlines(x=4, ymin=ax.get_ylim()[0], ymax=ax.get_ylim()[
1], colors=(0.8, 0.8, 0.8))
ax.hlines(y=[-2, 0, 2, 4, 6], xmin=ax.get_xlim()[0], xmax=ax.get_xlim()[1], colors=(0.8, 0.8, 0.8), linestyles='--', alpha=0.3)
ax.vlines(x=4, ymin=ax.get_ylim()[0], ymax=ax.get_ylim()[1], colors=(0.8, 0.8, 0.8))
ax.set_yticks([i for i in range(-4, 7, 2)])
ax.set_yticklabels(['$10^{' + str(i) + '}$' for i in range(-4, 7, 2)])
ax.set_xticks([2, 7])
ax.set_xticklabels(
['SARS-CoV-2\n(model)', 'Literature Data\n(recorded outbreaks) '])
ax.set_xticklabels(['SARS-CoV-2\n(model)', 'Literature Data\n(recorded outbreaks) '])
ax.set_ylabel('Emission rate (virions h$^{-1}$)', fontsize=12)
plt.tight_layout()