Added uniform distribution for masks

cara/apps/calculator/model_generator.py

@@ -10,7 +10,7 @@ from cara import models
 from cara import data
 import cara.monte_carlo as mc
 from .. import calculator
-from cara.monte_carlo.data import activity_distributions, virus_distributions
+from cara.monte_carlo.data import activity_distributions, virus_distributions, mask_distributions
 
 
 LOG = logging.getLogger(__name__)
@@ -301,7 +301,10 @@ class FormData:
     def mask(self) -> models.Mask:
         # Initializes the mask type if mask wearing is "continuous", otherwise instantiates the mask attribute as
         # the "No mask"-mask
-        mask = models.Mask.types[self.mask_type if self.mask_wearing_option == "mask_on" else 'No mask']
+        if self.mask_wearing_option == 'mask_on':
+            mask = mask_distributions[self.mask_type]
+        else:
+            mask = models.Mask.types['No mask']
         return mask
 
     def infected_population(self) -> mc.InfectedPopulation:

cara/monte_carlo/data.py

@@ -1,7 +1,7 @@
 import numpy as np
 
 import cara.monte_carlo as mc
-from cara.monte_carlo.sampleable import Normal,LogNormal,LogCustomKernel
+from cara.monte_carlo.sampleable import Normal,LogNormal,LogCustomKernel, Uniform
 
 
 # From CERN-OPEN-2021-04 and refererences therein
@@ -58,3 +58,10 @@ virus_distributions = {
                 infectious_dose=60/1.6,
                 ),
 }
+
+
+# From CERN-OPEN-2021-04 and refererences therein
+mask_distributions = {
+    'Type I': mc.Mask(Uniform(0.25, 0.80)),
+    'FFP2': mc.Mask(Uniform(0.83, 0.91)),
+}

cara/monte_carlo/sampleable.py

@@ -28,6 +28,18 @@ class Normal(SampleableDistribution):
         return np.random.normal(self.mean, self.standard_deviation, size=size)
 
 
+class Uniform(SampleableDistribution):
+    """
+    Defines a continuous uniform distribution
+    """
+    def __init__(self, low: float, high: float):
+        self.low = low
+        self.high = high
+
+    def generate_samples(self, size: int) -> float_array_size_n:
+        return np.random.uniform(self.low, self.high, size=size)
+
+
 class LogNormal(SampleableDistribution):
     """
     Defines a lognormal distribution (i.e. Gaussian distribution vs. the