def QuerySchema(self, descriptors):
(aggregatorScript, sourceIds) = self._AggregatorScriptFor(descriptors)
aggregator = Aggregator(cStringIO.StringIO(aggregatorScript))
result = Schema()
aggregator.run(
result,
[self.sources[sourceId].QuerySchema() for sourceId in sourceIds])
return result
def test_aggregate(self):
outFileName = "/Users/Tushar/Documents/Research/PuppetQuality/Puppet-lint_aggregator/testOut.csv"
outFile = open(outFileName, 'w')
outFile.write(CONSTS.HEADER)
Aggregator.aggregate("/Users/Tushar/Documents/Research/PuppetQuality/Puppet-lint_aggregator/test1/", "test1", outFile)
Aggregator.aggregate("/Users/Tushar/Documents/Research/PuppetQuality/Puppet-lint_aggregator/test2/", "test2", outFile)
outFile.close()
outReadFile = open(outFileName, 'r')
self.assertGreater(len(outReadFile.read()), 0)
def test_aggregate(self):
outFileName = "/Users/Tushar/Documents/Research/PuppetQuality/Puppet-lint_aggregator/testOut.csv"
outFile = open(outFileName, 'w')
outFile.write(CONSTS.HEADER)
Aggregator.aggregate(
"/Users/Tushar/Documents/Research/PuppetQuality/Puppet-lint_aggregator/test1/",
"test1", outFile)
Aggregator.aggregate(
"/Users/Tushar/Documents/Research/PuppetQuality/Puppet-lint_aggregator/test2/",
"test2", outFile)
outFile.close()
outReadFile = open(outFileName, 'r')
self.assertGreater(len(outReadFile.read()), 0)
def UpdateDescriptors(self, id, pool, descriptors=None):
if descriptors == None:
descriptors = pool.PresentAttributes()
scripts = self._DisgregatorScripts(descriptors)
for source, script in scripts.items():
if script == "": continue
disgregator = Aggregator(cStringIO.StringIO(script))
try:
result = self.sources[source].QueryDescriptors(id)
except:
result = Pool()
disgregator.run(result, [pool])
self.sources[source].UpdateDescriptors(id, result)
def QueryDescriptors(self, id, descriptors):
if self.verbose: print "++ Building aggregation script..."
(aggregatorScript, sourceIds) = self._AggregatorScriptFor(descriptors)
aggregator = Aggregator(cStringIO.StringIO(aggregatorScript))
result = Pool()
sourcesPools = []
for sourceId in sourceIds:
if self.verbose:
print "++ Querying descriptors from %s..." % sourceId
sourcePool = self.sources[sourceId].QueryDescriptors(id)
sourcesPools.append(sourcePool)
if self.verbose: print "++ Aggregating..."
aggregator.run(result, sourcesPools)
return result
def load():
global Ci_Database
global C_Ci_Database
global P_list
global Ci_Accumulated_Weights
global Ci_Accumulated_Distance
global C_token_Database
global token_Database
global token_Accumulated_Weights
global token_Accumulated_Distance
global target_context
results = Aggregator.load()
Ci_Database, C_Ci_Database, P_list, Ci_Accumulated_Weights, Ci_Accumulated_Distance, C_token_Database, token_Database, token_Accumulated_Weights, token_Accumulated_Distance, target_context = results
P_list = set(P_list)
target_context = filterContext(target_context)
import os
import Aggregator
from SmellDetector import Constants as CONSTS, Analyzer
root = CONSTS.REPO_ROOT
print("Initiating Analyzer...")
totalRepos = len(os.listdir(root))
currentItem = 0
for item in os.listdir(root):
currentFolder = os.path.join(root, item)
#print("Anlyzing: " + currentFolder)
if not os.path.isfile(currentFolder):
Analyzer.analyze(currentFolder, item)
currentItem += 1
print (str("{:.2f}".format(float(currentItem * 100)/float(totalRepos))) + "% analysis done.")
print("Analyzer - Done.")
print("Initiating metrics and smells aggregator...")
aggregatedFile = open(root + "/" + CONSTS.AGGREGATOR_FILE, 'wt')
aggregatedFile.write(CONSTS.CSV_HEADER)
for item in os.listdir(root):
currentFolder = os.path.join(root, item)
if not os.path.isfile(currentFolder):
Aggregator.aggregate(currentFolder, item, aggregatedFile)
aggregatedFile.close()
print("Metrics and smells aggregator - Done.")
###############################################################################
else:
status = MPI.Status()
while True:
# receive message
work = comm.recv(source=0, tag = MPI.ANY_TAG,status=status)
# check tag of received message
if status.Get_tag() == DIETAG: break
# do the work
resultz = np.array(work)
cosa = max(resultz.shape) #resultz[0,:].shape
print('cosa', cosa)
if cosa==5: # cosa[0]
resultpp = resultz[np.ix_([0],[1,2,3])]
state_agg = resultz[np.ix_([0],[4])]
resultp = Aggregator.mapping_inverse(resultpp,state_agg) #np.ones(3)
elif cosa==8: #cosa[0]
resultpp = resultz[np.ix_([0],[1,2,3])]
state_agg = resultz[np.ix_([0],[4])]
pred = resultz[np.ix_([0],[5,6,7])]
(resultp,actives) = Aggregator.mapping(resultpp,state_agg,pred)
#print(actives)
else:
resultpp = resultz[np.ix_([0],[1,2,3])]
state_agg = resultz[np.ix_([0],[4])]
pred = resultz[np.ix_([0],[5,6,7])]
(resultp,actives) = Aggregator.mapping(resultpp,state_agg,pred)
mm = 1.0 - actives
#resultp = np.c_[mm,[valls]]
resulto = np.array(resultz[0][0])
if sanity_check_counter == int(sanity_interval / interval):
content = previous_content
sanity_check_counter = 0
if len(content) != 0:
socketio.emit('newdata', content, namespace='/api')
socketio.sleep(interval)
@app.route('/')
def hello_world():
return render_template('index.html')
@socketio.on('slider', namespace='/api')
def slider(data):
print('slider value updated: %s' % data.get('value'))
@socketio.on('connect', namespace='/api')
def connect():
socketio.emit('newdata', aggregator.get_content(), namespace='/api')
if __name__ == '__main__':
aggregator = Aggregator.Aggregator()
command = sys.argv[1] if len(sys.argv) > 1 else "python3 ./test.py"
aggregator.register_component(command)
aggregator.start_gathering()
socketio.start_background_task(target=update)
socketio.run(app, host='0.0.0.0', port=8080)
# (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA from Aggregator import * from Schema import * import sys if sys.argv[1] == "-" : script = sys.stdin else : script = file(sys.argv[1]) sources = sys.argv[2:] target = Schema() aggregator = Aggregator(script) aggregator.run(target, [ Schema(file(source)) for source in sources ] ) target.Dump(sys.stdout)
def test(self):
t = tableau_test()
a = Aggregator()
a.init(self.f.compute)
print a.result(t)
import os
import Aggregator
from SmellDetector import Constants as CONSTS, Analyzer
root = CONSTS.REPO_ROOT
print("Initiating Analyzer...")
totalRepos = len(os.listdir(root))
currentItem = 0
for item in os.listdir(root):
currentFolder = os.path.join(root, item)
#print("Anlyzing: " + currentFolder)
if not os.path.isfile(currentFolder):
Analyzer.analyze(currentFolder, item)
currentItem += 1
print(
str("{:.2f}".format(float(currentItem * 100) / float(totalRepos))) +
"% analysis done.")
print("Analyzer - Done.")
print("Initiating metrics and smells aggregator...")
aggregatedFile = open(root + "/" + CONSTS.AGGREGATOR_FILE, 'wt')
aggregatedFile.write(CONSTS.CSV_HEADER)
for item in os.listdir(root):
currentFolder = os.path.join(root, item)
if not os.path.isfile(currentFolder):
Aggregator.aggregate(currentFolder, item, aggregatedFile)
aggregatedFile.close()
print("Metrics and smells aggregator - Done.")
#Program Entry Point
from Generator import *
import tensorflow as tf
from Discriminator import *
from Aggregator import *
from DataPrep import *
#Add support for altering images. (ie flip image. etc..)
#All ops are for 3d tensors, so something like this has to be used..
#result = tf.map_fn(lambda img: tf.image.random_flip_left_right(img), images)
#Add leaky relu
with tf.Session() as sess:
batchSize = 64
numIters = 500
gen = Generator(batchSize)
discrim = Discriminator(batchSize, gen)
a = Aggregator(sess, discrim)
saver = tf.train.Saver()
try:
saver.restore(sess, "savedModel.ckpt")
print("Successfully Restored Model!!")
except:
sess.run(tf.global_variables_initializer())
print("No model available for restoration")
allData = loadAllData()
a.learn(allData, numIters, batchSize)
saver.save(sess, "savedModel.ckpt")
def helperTestParser(self, input):
aggregator = Aggregator(cStringIO.StringIO(input))
sink = cStringIO.StringIO()
aggregator.dump(sink)
return sink.getvalue()
def helperTestParser(self, input) : aggregator = Aggregator(cStringIO.StringIO(input)) sink = cStringIO.StringIO() aggregator.dump(sink) return sink.getvalue()
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
from Aggregator import *
from Pool import *
import sys
if sys.argv[1] == "-":
script = sys.stdin
else:
script = file(sys.argv[1])
sources = sys.argv[2:]
target = Pool()
aggregator = Aggregator(script)
aggregator.run(target, [Pool(file(source)) for source in sources])
target.Dump(sys.stdout)
7.You can freely analyze the code, and propose any changes
8.Parts of this code cannot be used to any other software creating without written permission of i2
July 2012, Krakow Poland
"""
import wx
import Aggregator as Agg_module
class Agg_GUI(Agg_module.MyDialog):
def __init__(self, V):
Agg_module.MyDialog.__init__(self, V)
stand_alone = True
try:
Visum
stand_alone = 0
except:
Visum = Agg_module.Visum_Init("D:/agr.ver")
if __name__ == "__main__":
if stand_alone:
app = wx.PySimpleApp(0)
wx.InitAllImageHandlers()
APNR = Agg_GUI(Visum)
app.SetTopWindow(APNR)
APNR.Show()
if stand_alone:
app.MainLoop()
# (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA from Aggregator import * from Pool import * import sys if sys.argv[1] == "-" : script = sys.stdin else : script = file(sys.argv[1]) sources = sys.argv[2:] target = Pool() aggregator = Aggregator(script) aggregator.run(target, [ Pool(file(source)) for source in sources ] ) target.Dump(sys.stdout)
###############################################################################
else:
status = MPI.Status()
while True:
# receive message
work = comm.recv(source=0, tag=MPI.ANY_TAG, status=status)
# check tag of received message
if status.Get_tag() == DIETAG: break
# do the work
resultz = np.array(work)
cosa = max(resultz.shape) #resultz[0,:].shape
#print('cosa', cosa)
if cosa == 5: # cosa[0]
resultpp = resultz[np.ix_([0], [1, 2, 3])]
state_agg = resultz[np.ix_([0], [4])]
resultp = Aggregator.mapping_inverse(resultpp,
state_agg) #np.ones(3)
elif cosa == 8: #cosa[0]
resultpp = resultz[np.ix_([0], [1, 2, 3])]
state_agg = resultz[np.ix_([0], [4])]
pred = resultz[np.ix_([0], [5, 6, 7])]
(resultp, actives, momentsmat, labdist,
polprime) = Aggregator.mapping(resultpp, state_agg, pred)
#print(actives)
else:
resultpp = resultz[np.ix_([0], [1, 2, 3])]
state_agg = resultz[np.ix_([0], [4])]
pred = resultz[np.ix_([0], [5, 6, 7])]
(resultp, actives, momentsmat, labdist,
polprime) = Aggregator.mapping(resultpp, state_agg, pred)
mm = 1.0 - actives
#resultp = np.c_[mm,[valls]]