update numbers and pipfile

Pipfile

@@ -0,0 +1,12 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+matplotlib = "*"
+
+[dev-packages]
+
+[requires]
+python_version = "3.9"

covidrisk.py

@@ -16,10 +16,10 @@ def p_meet_positive_bayes(groupsize:int):
     '''
         Bayesian approach
     '''
-    n_positive_tests = 1073.754     # number of positive tests in the last 14 days
-    n_tests = 6316.2                # total number of tests in the last 14 days
-    n_population = 100000           # sample size -> per 100k for switzerland
-    p_test_positive =  0.2          # probability of a positive person getting tested (0.5 is optimistic...)
+    n_positive_tests = 824.11 # number of positive tests in the last 14 days per 100k
+    n_tests = 6514.83         # number of tests in the last 14 days per 100k
+    n_population = 100000     # sample size (per 100k)
+    p_test_positive =  0.5    # probability of a positive person getting tested (0.5 is optimistic...)
 
     p_positive_test = n_positive_tests / n_tests
     p_test = n_tests / n_population
@@ -29,13 +29,14 @@ def p_meet_positive_bayes(groupsize:int):
 
 def plot_data(data):
     plt.plot(data)
-    plt.title("probability of meeting a covid positive in groupsize of n")
+    plt.title("probability of having a covid positive in groupsize of n")
     plt.xlabel("group size / n")
-    plt.ylabel("probability")
+    plt.ylabel("probability / %")
+    plt.grid(visible=True)
     plt.show()
 
 data = []
-for i in range(1, 300):
+for i in range(1, 325):
     data.append(p_meet_positive_bayes(i))
     print(f'The chance of meeting a positive in a group of {i} is: {p_meet_positive_bayes(i)}%')