Data analysis updated for the new Dataset class. Coordinates are saved in a light numpy array for fast/light retrieval.

1 files changed, 0 insertions, 29 deletions

diff --git a/alex/plots.py b/alex/plots.py
deleted file mode 100644
index e405480..0000000
--- a/alex/plots.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import matplotlib.pyplot as plt
-import numpy
-import cPickle
-import scipy
-
-print "Loading data..."
-with open("train_normal.pkl") as f: normal = cPickle.load(f)
-
-print "Extracting x and y"
-xes = [c[0] for l in normal for c in l[-1]]
-yes = [c[1] for l in normal for c in l[-1]]
-
-xrg = [-8.75, -8.55]
-yrg = [41.05, 41.25]
-
-print "Doing 1d histogram"
-#plt.clf(); plt.hist(xes, bins=1000, range=xrg); plt.savefig("xhist.pdf")
-#plt.clf(); plt.hist(yes, bins=1000, range=yrg); plt.savefig("yhist.pdf")
-
-print "Doing 2d histogram"
-#plt.clf(); plt.hist2d(xes, yes, bins=500, range=[xrg, yrg]); plt.savefig("xymap.pdf")
-
-hist, xx, yy = numpy.histogram2d(xes, yes, bins=2000, range=[xrg, yrg])
-
-import ipdb; ipdb.set_trace()
-
-plt.clf(); plt.imshow(numpy.log(hist)); plt.savefig("xyhmap.pdf")
-
-scipy.misc.imsave("xymap.png", numpy.log(hist))