Merge branch 'master' of github.com:adbrebs/taxi

1 files changed, 17 insertions, 6 deletions

diff --git a/data_analysis/cluster_arrival.py b/data_analysis/cluster_arrival.py
index fd4ea04..5e990cd 100644..100755
--- a/data_analysis/cluster_arrival.py
+++ b/data_analysis/cluster_arrival.py
@@ -1,20 +1,31 @@
-import matplotlib.pyplot as plt
+#!/usr/bin/env python
 import numpy
 import cPickle
 import scipy.misc
+import os
 
 from sklearn.cluster import MeanShift, estimate_bandwidth
 from sklearn.datasets.samples_generator import make_blobs
 from itertools import cycle
 
-print "Reading arrival point list"
-with open("arrivals.pkl") as f:
-    pts = cPickle.load(f)
+import data
+from data.hdf5 import taxi_it
+from data.transformers import add_destination
+
+print "Generating arrival point list"
+dests = []
+for v in taxi_it("train"):
+    if len(v['latitude']) == 0: continue
+    dests.append([v['latitude'][-1], v['longitude'][-1]])
+pts = numpy.array(dests)
+
+with open(os.path.join(data.path, "arrivals.pkl"), "w") as f:
+    cPickle.dump(pts, f, protocol=cPickle.HIGHEST_PROTOCOL)
 
 print "Doing clustering"
 bw = estimate_bandwidth(pts, quantile=.1, n_samples=1000)
 print bw
-bw = 0.001
+bw = 0.001 # (
 
 ms = MeanShift(bandwidth=bw, bin_seeding=True, min_bin_freq=5)
 ms.fit(pts)
@@ -22,6 +33,6 @@ cluster_centers = ms.cluster_centers_
 
 print "Clusters shape: ", cluster_centers.shape
 
-with open("arrival-cluters.pkl", "w") as f:
+with open(os.path.join(data.path, "arrival-clusters.pkl"), "w") as f:
     cPickle.dump(cluster_centers, f, protocol=cPickle.HIGHEST_PROTOCOL)