merge with new style
This commit is contained in:
Luis Aleixo
parent
e8f4db16fa
commit
c81e9b1c14
1 changed files with 24 additions and 29 deletions
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@ -38,8 +38,7 @@ def exposure_model_from_vl_breathing():
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exposure_mc = breathing_exposure_vl(vl)
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exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
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# divide by 2 to have in 30min (half an hour)
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(
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cn_B=0.06, cn_L=0.2) / 2
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2) / 2
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er_means.append(np.mean(emission_rate))
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er_medians.append(np.median(emission_rate))
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lower_percentiles.append(np.quantile(emission_rate, 0.01))
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@ -69,7 +68,7 @@ def exposure_model_from_vl_breathing():
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build_breathing_legend(fig)
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############ Plot ############
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plt.title('Exhaled virions while breathing for 30 min',
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plt.title('',
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fontsize=16, fontweight="bold")
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plt.ylabel(
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'Aerosol viral load, $\mathrm{vl_{out}}$\n(RNA copies)', fontsize=14)
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@ -87,7 +86,7 @@ def exposure_model_from_vl_breathing_cn():
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fig = plt.figure()
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ax = fig.add_subplot(1, 1, 1)
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n_lines = 1
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n_lines = 30
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cns = np.linspace(0.01, 0.5, n_lines)
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cmap = define_colormap(cns)
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@ -124,8 +123,7 @@ def exposure_model_from_vl_breathing_cn():
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r"$\mathbf{c_{n,B}=0.06}$", color=cmap.to_rgba(cn), fontsize=12)
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cmap = fig.colorbar(cmap, ticks=[0.01, 0.1, 0.25, 0.5])
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cmap.set_label(
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label='Particle emission concentration, ${c_{n,B}}$', fontsize=12)
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cmap.set_label(label='Particle emission concentration, ${c_{n,B}}$', fontsize=12)
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ax.set_yscale('log')
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############# Coleman #############
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@ -142,7 +140,7 @@ def exposure_model_from_vl_breathing_cn():
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build_breathing_legend(fig)
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############ Plot ############
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plt.title('Exhaled virions while breathing for 30 min',
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plt.title('',
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fontsize=16, fontweight="bold")
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plt.ylabel(
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'Aerosol viral load, $\mathrm{vl_{out}}$\n(RNA copies)', fontsize=14)
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@ -167,8 +165,7 @@ def exposure_model_from_vl_talking():
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exposure_mc = talking_exposure_vl(vl)
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exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
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# divide by 4 to have in 15min (quarter of an hour)
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(
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cn_B=0.06, cn_L=0.2)/4
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2)/4
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er_means.append(np.mean(emission_rate))
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er_medians.append(np.median(emission_rate))
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lower_percentiles.append(np.quantile(emission_rate, 0.01))
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@ -189,7 +186,7 @@ def exposure_model_from_vl_talking():
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build_talking_legend(fig)
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############ Plot ############
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plt.title('Exhaled virions while speaking (vocalization) for 15min',
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plt.title('',
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fontsize=16, fontweight="bold")
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plt.ylabel(
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'Aerosol viral load, $\mathrm{vl_{out}}$\n(RNA copies)', fontsize=14)
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@ -199,12 +196,11 @@ def exposure_model_from_vl_talking():
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plt.show()
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def exposure_model_from_vl_talking_cn():
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fig = plt.figure()
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ax = fig.add_subplot(1, 1, 1)
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n_lines = 1
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n_lines = 30
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cns = np.linspace(0.01, 2, n_lines)
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cmap = define_colormap(cns)
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@ -237,8 +233,8 @@ def exposure_model_from_vl_talking_cn():
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plt.text(viral_loads[int(len(viral_loads)*0.93)], 10**5.5,
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r"$\mathbf{c_{n,L}=0.2}$", color=cmap.to_rgba(cn), fontsize=12)
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fig.colorbar(cmap, ticks=[0.01, 0.5, 1.0, 2.0],
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label="Particle emission concentration, ${c_{n,L}}$", fontsize=14)
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cmap = fig.colorbar(cmap, ticks=[0.01, 0.5, 1.0, 2.0])
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cmap.set_label(label='Particle emission concentration, ${c_{n,L}}$', fontsize=12)
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ax.set_yscale('log')
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############# Coleman #############
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@ -248,7 +244,7 @@ def exposure_model_from_vl_talking_cn():
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build_talking_legend(fig)
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############ Plot ############
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plt.title('Exhaled virions while speaking (vocalization)\nfor 15min',
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plt.title('',
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fontsize=16, fontweight="bold")
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plt.ylabel(
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'Aerosol viral load, $\mathrm{vl_{out}}$\n(RNA copies)', fontsize=14)
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@ -307,30 +303,29 @@ def present_vl_er_histograms():
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viral_loads = [np.log10(vl) for vl in viral_load_in_sputum]
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axs[0].hist(viral_loads, bins=300, color='lightgrey')
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axs[0].set_xlabel('vl (log$_{10}$(RNA copies mL$^{-1}$))')
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axs[0].hist(viral_loads, bins = 300, color='lightgrey')
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axs[0].set_xlabel('vl$_{\mathrm{in}}$ (log$_{10}$ RNA copies mL$^{-1}$)')
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mean = np.mean(viral_loads)
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axs[0].vlines(x=(mean), ymin=0, ymax=axs[0].get_ylim()[
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1], colors=('black'), linestyles=('dashed'))
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axs[0].vlines(x=(mean), ymin=0, ymax=axs[0].get_ylim()[1], colors=('grey'), linestyles=('dashed'))
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breathing_mean_er = np.mean(breathing_er)
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speaking_mean_er = np.mean(speaking_er)
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shouting_mean_er = np.mean(shouting_er)
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axs[1].hist(breathing_er, bins=300, color='lightsteelblue')
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axs[1].hist(speaking_er, bins=300, color='wheat')
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axs[1].hist(shouting_er, bins=300, color='darkseagreen')
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axs[1].set_xlabel('vR (log$_{10}$)')
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axs[1].hist(breathing_er, bins = 300, color='lightsteelblue')
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axs[1].hist(speaking_er, bins = 300, color='wheat')
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axs[1].hist(shouting_er, bins = 300, color='darkseagreen')
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axs[1].set_xlabel('vR (log$_{10}$ virions h$^{-1}$)')
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axs[1].vlines(x=(breathing_mean_er, speaking_mean_er, shouting_mean_er), ymin=0, ymax=axs[1].get_ylim()[1], colors=(
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'cornflowerblue', 'goldenrod', 'olivedrab'), alpha=(0.75, 0.75, 0.75), linestyles=('dashed', 'dashed', 'dashed'))
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axs[1].vlines(x=(breathing_mean_er, speaking_mean_er, shouting_mean_er), ymin=0, ymax=axs[1].get_ylim()[1], colors=('cornflowerblue', 'goldenrod', 'olivedrab'), alpha=(0.75, 0.75, 0.75), linestyles=('dashed', 'dashed', 'dashed'))
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labels = [Patch([], [], color=color, label=label)
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for color, label in zip(['lightsteelblue', 'wheat', 'darkseagreen', 'lightgrey'],
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['Breathing vR', 'Speaking vR', 'Shouting vR', 'Viral Load'])]
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labels.append(mlines.Line2D([], [], color='grey',
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marker='', linestyle='dashed', label='Mean'))
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for color, label in zip(['lightgrey', 'lightsteelblue', 'wheat', 'darkseagreen'],
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['Viral Load', 'Breathing', 'Speaking', 'Shouting'])]
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labels.append(mlines.Line2D([], [], color='black',
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marker='', linestyle='dashed', label='Mean'))
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for x in (0, 1):
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axs[x].set_yticklabels([])
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