Snowball implementation (#1)

* Initial test of Snowball implementation

* Add functional plot

* Fix plot

* Remove older duplicate .py file

* Rename glacier-demo.py to snowball-demo.py

* untrack .idea directory

* Add .gitignore file to untrack .idea directory

.gitignore

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+.idea

snowball-demo.py

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+from random import sample
+from random import choices
+from random import shuffle
+import matplotlib.pyplot as plt
+import seaborn as sbn
+from collections import Counter
+
+# snowball consensus demo - no byzantine
+
+### define parameters
+
+# n: number of participants
+n = 400
+
+# k (sample size): between 1 and n | bigger the k the faster the conversion
+k = 10
+
+# alpha (quorum size): between 1 and k
+alpha = 9
+
+# beta (decision threshold): >= 1
+beta = 20
+
+
+# preference := pizza
+# n size list w/ each term n having it's own preference
+node_preference = [choices([True, False], weights=[0.55, 0.45])[0] for i in range(n)]
+print(Counter(node_preference))
+# success counter for each node
+node_counter = [0 for i in range(n)]
+
+# node decision
+node_decision = [None for i in range(n)]
+x_axis = []
+
+while not all(x is not None for x in node_decision): # returns false if any None exist - truthy, any is falsy
+    indices = [i for i, d in enumerate(node_decision) if d is None]
+    shuffle(indices)
+    x_axis.append(Counter(node_preference.copy()))  # read up on append command
+    for node_index in indices:
+        sample_response = sample(node_preference, k)
+        print(sample_response)
+        previous_preference = node_preference[node_index]
+        # count how many truth
+        sample_response_count = sample_response.count(previous_preference)
+        print(sample_response_count)
+        not_preference_count = len(sample_response)-sample_response_count
+        # change node decision to align with majority opinion from sampled size
+        # compare previous node opinion with majority opinion to increment counter if opinion is unchanged
+        if sample_response_count >= alpha:
+            node_counter[node_index] += 1
+        elif not_preference_count >= alpha:
+            node_counter[node_index] = 1
+            node_preference[node_index] = not previous_preference
+        else:
+            node_counter[node_index] = 0
+        if node_counter[node_index] > beta:
+            node_decision[node_index] = node_preference[node_index]
+
+
+#plot two lines, one w/ yes and one w/ no
+
+yes, no = zip(*((x[True], x[False]) for x in x_axis))
+sbn.lineplot(data={"yes": yes, "no": no})
+plt.show()
+# consecutiveSuccesses := 0
+# while not decided:
+#   ask k random people their preference
+#   if >= α give the same response:
+#     preference := response with >= α
+#     if preference == old preference:
+#       consecutiveSuccesses++
+#     else:
+#       consecutiveSuccesses = 1
+#   else:
+#     consecutiveSuccesses = 0
+#   if consecutiveSuccesses > β:
+#     decide(preference)