From e93e744dec20049a6dff625984daf32ccd4829e0 Mon Sep 17 00:00:00 2001 From: Andrejh Date: Fri, 3 Sep 2021 12:08:40 +0200 Subject: [PATCH] legend updates --- cara/model_scenarios.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/cara/model_scenarios.py b/cara/model_scenarios.py index fdfd777f..df250ef9 100644 --- a/cara/model_scenarios.py +++ b/cara/model_scenarios.py @@ -449,7 +449,7 @@ def exposure_model_from_vl_breathing_cn(viral_loads): cmap = mpl.cm.ScalarMappable(norm=norm, cmap=mpl.colors.LinearSegmentedColormap.from_list("mycmap", colors)) cmap.set_array([]) - + for cn in tqdm(cns): er_means = [] for vl in viral_loads: @@ -520,12 +520,12 @@ def exposure_model_from_vl_breathing_cn(viral_loads): ) exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE) # divide by 2 to have in 30min (half an hour) - emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B = 0.1, cn_L = 1.0) / 2 + emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B = 0.06, cn_L = 1.0) / 2 er_means.append(np.mean(emission_rate)) ax.plot(viral_loads, er_means, color=cmap.to_rgba(cn, alpha=0.75), linewidth=1, ls='--') - plt.text(viral_loads[int(len(viral_loads)*0.95)], er_means[-1], "cn_B=0.1", color='black', size='small') - - fig.colorbar(cmap, ticks=[0.01, 0.25, 0.5], label="Particle emission concentration for breathing.") + plt.text(viral_loads[int(len(viral_loads)*0.94)], 10**4.5, r'$c_{n,B}=0.06$', color=cmap.to_rgba(cn), fontsize=10) + + fig.colorbar(cmap, ticks=[0.01, 0.25, 0.5], label="Particle emission concentration, $c_{n,B}$") ax.set_yscale('log') ############# Coleman #############