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modifications to qR subplot style

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Andrejh 2021-02-07 10:27:39 +01:00 committed by markus
parent 8ec19f8e85
commit a25e6f33e3
1 changed files with 23 additions and 16 deletions
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39
cara/montecarlo.py
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@ -56,6 +56,7 @@ lognormal_parameters = ((0.10498338229297108, -0.6872121723362303), # BR, se
(0.1894616357138137, 0.551771330362601), # BR, moderate exercise
(0.21744554768657565, 1.1644665696723049)) # BR, heavy exercise
# NOT USED (directly in calculated in concentration_vs_diameter )
emission_concentrations = (1.38924e-6, 1.07098e-4, 5.29935e-4)
concentration_vs_diameter = (
@ -393,14 +394,16 @@ def print_qr_info(qr_values: np.ndarray) -> None:
def present_model(model: MCConcentrationModel, bins: int = 200) -> None:
global data
fig, axs = plt.subplots(2, 2, sharex=False, sharey=False)
fig.set_figheight(8)
fig.set_figwidth(10)
fig.suptitle('Summary of model parameters')
plt.tight_layout()
plt.subplots_adjust(hspace=0.2)
plt.subplots_adjust(hspace=0.4)
plt.subplots_adjust(wspace=0.2)
plt.subplots_adjust(top=0.88)
plt.subplots_adjust(bottom=0.1)
fig.set_figheight(10)
for x, y in ((0, 0), (1, 0), (1, 1)):
@ -415,41 +418,45 @@ def present_model(model: MCConcentrationModel, bins: int = 200) -> None:
top = axs[x, y].get_ylim()[1]
mean, median, std = np.mean(data), np.median(data), np.std(data)
axs[x, y].vlines(x=(mean, median, mean - std, mean + std), ymin=0, ymax=top,
colors=('red', 'green', 'pink', 'pink'))
colors=('grey', 'black', 'lightgrey', 'lightgrey'),
linestyles=('solid', 'solid', 'dashed', 'dashed'))
axs[0, 0].set_title('Viral load')
axs[0, 0].set_xlabel('Viral load [log10(RNA copies / mL)]')
axs[0, 0].set_xlabel('Viral load [$log10(RNA\,copies\;mL^{-1}$)]')
ds = np.linspace(0.1, 15, 2000)
unmasked = [model.infected._concentration_distribution_without_mask()(d) for d in ds]
masked = [model.infected._concentration_distribution_with_mask()(d) for d in ds]
if model.infected.masked:
axs[0, 1].plot(ds, masked, 'g', label="With mask")
axs[0, 1].plot(ds, unmasked, 'r--', label="Without mask")
axs[0, 1].plot(ds, masked, 'b', label="With mask")
axs[0, 1].plot(ds, unmasked, 'k--', label="Without mask")
axs[0, 1].legend(loc="upper right")
else:
axs[0, 1].plot(ds, masked, 'g--', label="With mask")
axs[0, 1].plot(ds, unmasked, 'r', label="Without mask")
axs[0, 1].plot(ds, masked, 'b--', label="With mask")
axs[0, 1].plot(ds, unmasked, 'k', label="Without mask")
axs[0, 1].legend(loc="upper right")
axs[0, 1].set_title(r'Particle emission concentration vs diameter')
axs[0, 1].set_ylabel('Particle emission concentration [cm^-3]')
# add the label automatically to the title of the plot ??
# categories_particles = ("Breathing", "Speaking", "Shouting") ??
axs[0, 1].set_title(r'Particle emissions')
axs[0, 1].set_ylabel('Particle emission concentration [$cm^{-3}$]')
axs[0, 1].set_xlabel(r'Diameter [$\mu$m]')
categories = ("seated", "standing", "light exercise", "moderate exercise", "heavy exercise")
axs[1, 0].set_title(f'Breathing rate - '
f'{categories[model.infected.breathing_category - 1]}')
axs[1, 0].set_xlabel('Breathing rate [m^3 / h]')
axs[1, 0].set_xlabel('Breathing rate [$m^3\;h^{-1}$]')
axs[1, 1].set_title('qR')
axs[1, 1].set_xlabel('qR [log10(q / h)]')
axs[1, 1].set_title('Quantum generation rate')
axs[1, 1].set_xlabel('qR [log10($q\;h^{-1}$)]')
mean_patch = patches.Patch(color='red', label='Mean')
median_patch = patches.Patch(color='green', label='Median')
std_patch = patches.Patch(color='pink', label='Standard deviations')
fig.legend(handles=(mean_patch, median_patch, std_patch))
mean_patch = patches.Patch(color='grey',label='Mean')
median_patch = patches.Patch(color='black', label='Median')
std_patch = patches.Patch(color='lightgrey', linestyle='dashed', label='Standard deviations')
fig.legend(handles=(mean_patch, std_patch, median_patch))
plt.show()
print(10**np.median(data))
def buaonanno_exposure_model():