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display histogram of given model

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markus 2021-02-22 15:56:49 +01:00
parent 386b089273
commit dea98d3c6f
1 changed files with 14 additions and 12 deletions
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26
cara/montecarlo.py
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@ -591,18 +591,20 @@ def plot_pi_vs_viral_load(baselines: typing.Union[MCExposureModel, typing.List[M
plt.legend(labels)
# this is an inset plot inside the main plot
a = plt.axes([.2, .25, .3, .2], facecolor='lightgrey')
#TODO - Markus can you plot the hist using the chosen model instead of hardcoding
# in the 'exposure_model' str?
plt.title('Histogram',fontsize=10)
#choose between hist or violin plot
plt.hist(shared_office_model[1].infection_probability()/100, bins=50)
plt.xticks([0,0.5,1])
plt.yticks([])
#parts = plt.violinplot((shared_office_worst_model[1].infection_probability()/100, shared_office_model[1].infection_probability()/100, shared_office_better_model[1].infection_probability()/100), positions = (1, 2, 3), showmeans=True, showmedians=True)
#for pc in parts['bodies']:
# pc.set_facecolor('#D43F3A')
#plt.xticks([])
#plt.yticks([0,0.5,1], fontsize=8)
plt.title('Histogram', fontsize=10)
# choose between hist or violin plot
if len(baselines) == 1:
plt.hist(baselines[0].infection_probability()/100, bins=50)
plt.xticks([0, 0.5, 1])
plt.yticks([])
# parts = plt.violinplot((shared_office_worst_model[1].infection_probability()/100, shared_office_model[1].infection_probability()/100, shared_office_better_model[1].infection_probability()/100), positions = (1, 2, 3), showmeans=True, showmedians=True)
# for pc in parts['bodies']:
# pc.set_facecolor('#D43F3A')
# plt.xticks([])
# plt.yticks([0,0.5,1], fontsize=8)
plt.show()