Create functions.py

functions.py

@@ -0,0 +1,20 @@
+import numpy as np
+
+# Used to test if all the listed attributes of all team members and applicants are the same
+def all_equal(attribute_list):
+    return len(set(attribute_list)) == 1
+
+# I decided to treat all attributes as independent from eachother, since large negative covariances between attributes made the cdf go to 0 very quickly
+def make_independent(cov_matrix):
+    dim = len(cov_matrix)
+    for i in range(dim):
+        for j in range(dim):
+            if not i==j:
+                cov_matrix[i,j] = 0
+    return cov_matrix
+
+# Define compatibility as the geometric mean of the probabilities for each attribute that a person on the team will have a lower value
+def compatibility(model, attributes, candidate_dict):
+    num_attributes = len(attributes)
+    candidate_values = [candidate_dict[attribute] for attribute in attributes]
+    return model.cdf(np.array(candidate_values))**(1/num_attributes)