use distribution for viral loads
This commit is contained in:
parent
f4b0dd084c
commit
55c1a2124a
1 changed files with 11 additions and 2 deletions
|
|
@ -1,6 +1,7 @@
|
|||
import numpy as np
|
||||
import scipy.stats as sct
|
||||
from typing import Optional
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
|
||||
# The (k, lambda) parameters for the weibull-distributions corresponding to each quantity
|
||||
|
|
@ -41,12 +42,20 @@ def generate_qr_values(samples: int, expiratory_activity: int, masked: bool, qid
|
|||
(e_k, e_lambda), (d_k, d_lambda) = weibull_parameters[expiratory_activity]
|
||||
emissions = sct.weibull_min.isf(sct.norm.sf(np.random.normal(size=samples)), e_k, loc=0, scale=e_lambda)
|
||||
diameters = sct.weibull_min.isf(sct.norm.sf(np.random.normal(size=samples)), d_k, loc=0, scale=d_lambda)
|
||||
viral_loads = np.random.normal(size=samples, loc=7.8, scale=1.7)
|
||||
|
||||
mask_efficiency = [0.75, 0.81, 0.81][expiratory_activity]
|
||||
qr_func = np.vectorize(calculate_qr)
|
||||
|
||||
# TODO: Add distributions for parameters
|
||||
viral_load = 7.8
|
||||
breathing_rate = 1
|
||||
|
||||
return qr_func(viral_load, emissions, diameters, mask_efficiency, qid)
|
||||
return qr_func(viral_loads, emissions, diameters, mask_efficiency, qid)
|
||||
|
||||
|
||||
def logscale_hist(x, bins):
|
||||
hist, bins = np.histogram(x, bins=bins)
|
||||
logscale_bins = np.logspace(np.log10(bins[0]), np.log10(bins[-1]), len(bins))
|
||||
plt.hist(x, bins=logscale_bins)
|
||||
plt.xscale('log')
|
||||
plt.show()
|
||||
|
|
|
|||
Loading…
Reference in a new issue