def main():
#
# initialize start by getting existing canopy centers and
# setting it to the intermediate results file
#
resultsPath = os.path.join(PROJECT_ROOT, 'intermediateResults.txt')
fileIn = open(resultsPath)
centroidsJson = fileIn.read()
fileIn.close()
# input file
filePath = os.path.join(PROJECT_ROOT, 'enron_corpus.txt')
#
# setup the delta that we consider threshhold for "close-enough"
#
delta = 10
#
# Begin iteration on change in centroids
#
#while delta > 0.01:
loop_count = 0
while loop_count < 20:
# parse old centroid values
# centersJson format: [ document1, document2,..., documentN ]
oldCentroids = json.loads(centroidsJson)
# run one iteration
mrJob2 = MRkMeansIter( args=[filePath] )
with mrJob2.make_runner() as runner:
runner.run()
# compare new centroids to old ones
# determine if we are close enough to a final clustering solution
fileIn = open(resultsPath)
centroidsJson = fileIn.read()
fileIn.close()
newCentroids = json.loads(centroidsJson)
delta = 0.0
for i in range(len(newCentroids)):
new_center_doc = newCentroids[i]
old_center_doc = oldCentroids[i]
dist = jaccard_dist(new_center_doc, old_center_doc)
delta += jaccard_dist(new_center_doc, old_center_doc)
delta = delta / len(newCentroids)
print delta
loop_count += 1
def main():
#first run the initializer to get starting centroids
filePath = '/Users/ashwin/repos/mlclass/kMeans3/input.txt'
centPath = "/Users/ashwin/repos/mlclass/kMeans3/"
kMeansStr = '3'
mrJob = MRkMeansInit([filePath] + ["--k" , kMeansStr , "--pathName", centPath])
#mrJob = MRkMeansInit(args=[filePath])
with mrJob.make_runner() as runner:
runner.run()
#pull out the centroid values to compare with values after one iteration
centPath = "/Users/ashwin/repos/mlclass/kMeans3/"
fileIn = open(centPath + "intermediateResults.txt")
centroidsJson = fileIn.read()
fileIn.close()
delta = 10
#Begin iteration on change in centroids
while delta > 0.01:
#parse old centroid values
oldCentroids = json.loads(centroidsJson)
#run one iteration
mrJob2 = MRkMeansIter(args=[filePath] + ["--k" , kMeansStr , "--pathName", centPath])
with mrJob2.make_runner() as runner:
runner.run()
#compare new centroids to old ones
fileIn = open(centPath + "intermediateResults.txt")
centroidsJson = fileIn.read()
fileIn.close()
newCentroids = json.loads(centroidsJson)
kMeans = len(newCentroids)
delta = 0.0
for i in range(kMeans):
delta += dist(newCentroids[i],oldCentroids[i])
print delta
def main():
#first run the initializer to get starting centroids
filePath = '/home/mike-bowles/pyWorkspace/mapReducers/src/kMeans3/input.txt'
#mrJob = MRkMeansInit(args=[filePath])
#mrJob = MRkMeansInit(args=['-r', 'emr', filePath])
#with mrJob.make_runner() as runner:
# runner.run()
#pull out the centroid values to compare with values after one iteration
centPath = "s3://mike-mrjob/kMeans/centroids/intermediateResults.txt"
key = EMRJobRunner().get_s3_key(centPath)
centroidsJson = key.get_contents_as_string()
delta = 10
#Begin iteration on change in centroids
while delta > 0.01:
#parse old centroid values
oldCentroids = json.loads(centroidsJson)
#run one iteration
mrJob2 = MRkMeansIter(args=['-r', 'emr', filePath])
with mrJob2.make_runner() as runner:
runner.run()
#compare new centroids to old ones
centroidsJson = key.get_contents_as_string()
newCentroids = json.loads(centroidsJson)
kMeans = len(newCentroids)
delta = 0.0
for i in range(kMeans):
delta += dist(newCentroids[i],oldCentroids[i])
print delta
def main():
#first run the initializer to get starting centroids
filePath = os.path.join(PROJECT_ROOT, 'input.txt')
mrJob = MRkMeansInit(args=[filePath])
with mrJob.make_runner() as runner:
runner.run()
#pull out the centroid values to compare with values after one iteration
centPath = os.path.join(PROJECT_ROOT, 'intermediateResults.txt')
fileIn = open(centPath)
centroidsJson = fileIn.read()
fileIn.close()
delta = 10
#Begin iteration on change in centroids
while delta > 0.001:
#parse old centroid values
oldCentroids = json.loads(centroidsJson)
#run one iteration
mrJob2 = MRkMeansIter(args=[filePath])
with mrJob2.make_runner() as runner:
runner.run()
#compare new centroids to old ones
fileIn = open(centPath)
centroidsJson = fileIn.read()
fileIn.close()
newCentroids = json.loads(centroidsJson)
kMeans = len(newCentroids)
delta = 0.0
for i in range(kMeans):
delta += dist(newCentroids[i], oldCentroids[i])
print "delta={0}, centers={1}".format(delta, str(newCentroids))
def main():
#first run the initializer to get starting centroids
filePath = os.path.join(PROJECT_ROOT, 'input.txt')
mrJob = MRkMeansInit(args=[filePath])
with mrJob.make_runner() as runner:
runner.run()
#pull out the centroid values to compare with values after one iteration
centPath = os.path.join(PROJECT_ROOT, 'intermediateResults.txt')
fileIn = open(centPath)
centroidsJson = fileIn.read()
fileIn.close()
delta = 10
#Begin iteration on change in centroids
while delta > 0.001:
#parse old centroid values
oldCentroids = json.loads(centroidsJson)
#run one iteration
mrJob2 = MRkMeansIter(args=[filePath])
with mrJob2.make_runner() as runner:
runner.run()
#compare new centroids to old ones
fileIn = open(centPath)
centroidsJson = fileIn.read()
fileIn.close()
newCentroids = json.loads(centroidsJson)
kMeans = len(newCentroids)
delta = 0.0
for i in range(kMeans):
delta += dist(newCentroids[i],oldCentroids[i])
print "delta={0}, centers={1}" .format(delta, str(newCentroids))