second policy "check_progress"implemented; moved and renamed most policy/state variable functions over to network_helpers

network_helpers.py

@@ -65,6 +65,21 @@ def add_proposals_and_relationships_to_network(n: nx.DiGraph, proposals: int, fu
         n = initial_conflict_network(n, rate = .25)
         n = initial_social_network(n, scale = 1)
     return n
+
+def update_collateral_pool(params, step, sL, s, _input):
+    commons = s["commons"]
+    s["collateral_pool"] = commons._collateral_pool
+    return "collateral_pool", commons._collateral_pool
+
+def update_token_supply(params, step, sL, s, _input):
+    commons = s["commons"]
+    s["token_supply"] = commons._token_supply
+    return "token_supply", commons._token_supply
+
+def update_funding_pool(params, step, sL, s, _input):
+    commons = s["commons"]
+    s["funding_pool"] = commons._funding_pool
+    return "funding_pool", commons._funding_pool
 # =========================================================================================================
 def gen_new_participant(network, new_participant_tokens):
     i = len([node for node in network.nodes])
@@ -135,7 +150,7 @@ def calc_median_affinity(network):
     median_affinity = np.median(affinities)
     return median_affinity
 
-def driving_process(params, step, sL, s):
+def gen_new_participants_proposals_funding_random(params, step, sL, s):
     network = s['network']
     commons = s['commons']
     funds = s['funding_pool']
@@ -223,3 +238,99 @@ def add_participants_proposals_to_network(params, step, sL, s, _input):
     value = network
 
     return (key, value)
+
+def new_participants_and_new_funds_commons(params, step, sL, s, _input):
+    commons = s["commons"]
+    if _input['new_participant']:
+        tokens, realized_price = commons.deposit(_input['new_participant_investment'])
+        # print(tokens, realized_price, _input['new_participant_tokens'])
+    if _input['funds_arrival']:
+        commons._funding_pool += _input['funds_arrival']
+    return "commons", commons
+# =========================================================================================================
+def make_proposals_pass_or_fail_random(params, step, sL, s):
+    network = s['network']
+    proposals = get_proposals(network)
+
+    completed = []
+    failed = []
+    for j in proposals:
+        if network.nodes[j]['status'] == 'active':
+            grant_size = network.nodes[j]['funds_requested']
+            base_completion_rate=params[0]['base_completion_rate']
+            likelihood = 1.0/(base_completion_rate+np.log(grant_size))
+
+            base_failure_rate = params[0]['base_failure_rate']
+            failure_rate = 1.0/(base_failure_rate+np.log(grant_size))
+            if np.random.rand() < likelihood:
+                completed.append(j)
+            elif np.random.rand() < failure_rate:
+                failed.append(j)
+    return({'completed':completed, 'failed':failed})
+
+def get_sentimental(sentiment, force, decay=0):
+    mu = decay
+    sentiment = sentiment*(1-mu) + force
+    if sentiment > 1:
+        sentiment = 1
+    return sentiment
+
+def sentiment_decays_wo_completed_proposals(params, step, sL, s, _input):
+    network = s['network']
+    proposals = get_proposals(network)
+    completed = _input['completed']
+    failed = _input['failed']
+
+    grants_outstanding = np.sum([network.nodes[j]['funds_requested'] for j in proposals if network.nodes[j]['status']=='active'])
+    grants_completed = np.sum([network.nodes[j]['funds_requested'] for j in completed])
+    grants_failed = np.sum([network.nodes[j]['funds_requested'] for j in failed])
+
+    sentiment = s['sentiment']
+
+    if grants_outstanding>0:
+        force = (grants_completed-grants_failed)/grants_outstanding
+    else:
+        force=1
+
+    mu = params[0]['sentiment_decay']
+    if (force >=0) and (force <=1):
+        sentiment = get_sentimental(sentiment, force, mu)
+    else:
+        sentiment = get_sentimental(sentiment, 0, mu)
+
+    key = 'sentiment'
+    value = sentiment
+
+    return (key, value)
+
+def complete_proposal(params, step, sL, s, _input):
+    network = s['network']
+    participants = get_participants(network)
+    proposals = get_proposals(network)
+    competitors = get_edges_by_type(network, 'conflict')
+    completed = _input['completed']
+    for j in completed:
+        network.nodes[j]['status']='completed'
+
+        for c in proposals:
+             if (j,c) in competitors:
+                 conflict = network.edges[(j,c)]['conflict']
+                 for i in participants:
+                     network.edges[(i,c)]['affinity'] = network.edges[(i,c)]['affinity'] *(1-conflict)
+
+        for i in participants:
+            force = network.edges[(i,j)]['affinity']
+            sentiment = network.nodes[i]['sentiment']
+            network.nodes[i]['sentiment'] = get_sentimental(sentiment, force, decay=0)
+
+    failed = _input['failed']
+    for j in failed:
+        network.nodes[j]['status']='failed'
+        for i in participants:
+            force = -network.edges[(i,j)]['affinity']
+            sentiment = network.nodes[i]['sentiment']
+            network.nodes[i]['sentiment'] = get_sentimental(sentiment, force, decay=0)
+
+    key = 'network'
+    value = network
+    return (key, value)