Project cleanup before handing it to Ben

1 files changed, 11 insertions, 37 deletions

diff --git a/experiments/process.py b/experiments/process.py
index b5b70ca..5fc55ba 100644
--- a/experiments/process.py
+++ b/experiments/process.py
@@ -1,51 +1,25 @@
-from csv import DictReader
 import sys
 from ml import ml
 import numpy as np
-from cPickle import dump, load
+from cPickle import load
 from itertools import product
+from math import exp
 
 
-def build_network(filename):
-    victims = {}
-    non_victims = {}
-    with open(filename) as fh:
-        reader = DictReader(fh)
-        for row in reader:
-            from_, to = int(float(row["from"])), int(float(row["to"]))
-            if row["t2"] != "NA":
-                dt = int(row["t2"]) - int(row["t1"])
-                parent = (int(row["dist"]), dt)
-                if to not in victims:
-                    victims[to] = []
-                victims[to].append(parent)
-                if from_ not in victims:
-                    victims[from_] = []
-            else:
-                from_, to = int(float(row["from"])), int(float(row["to"]))
-                parent = (int(row["dist"]), 3012 - int(row["t1"]))
-                if to not in victims:
-                    non_victims[to] = []
-                non_victims[to].append(parent)
-                if from_ not in victims:
-                    victims[from_] = []
-    root_victims = {}
-    for victim in victims.keys():
-        if not victims[victim]:
-            del victims[victim]
-            root_victims[victim] = []
-    return root_victims, victims, non_victims
+def print_ll(alpha, delta):
+    beta, roots, ll = ml(root_victims, victims, non_victims, alpha, delta)
+    print "\t".join(map(str, [alpha, delta, beta, roots, ll, exp(ll)])) + "\n"
 
 
 if __name__ == "__main__":
-    #root_victims, victims, non_victims = build_network(sys.argv[1])
-    #dump((root_victims, victims, non_victims), open("network.pickle", "w"))
-    root_victims, victims, non_victims = load(open("network.pickle"))
+    if len(sys.argv) < 2:
+        sys.exit("usage: {0} <file>".format(sys.argv[0]))
 
-    alpha = np.arange(0.0000005, 0.00000051, 0.000001)
-    delta = np.arange(1., 1.000001, 0.001)
+    root_victims, victims, non_victims, age = load(open(sys.argv[1]))
+    alpha = 1. / np.arange(1., 1000., 10.)  # parameter of the time component
+    delta = np.arange(0.01, 0.9, 0.03)  # parameter of the structural component
     with open("out.log", "a") as fh:
         for a, d in product(alpha, delta):
-            beta, roots, ll = ml(root_victims, victims, non_victims, a, d)
+            beta, roots, ll = ml(root_victims, victims, non_victims, age, a, d)
             fh.write("\t".join(map(str, [a, d, beta, roots, ll])) + "\n")
             fh.flush()