def merge_dicts(self, l, name, transition_file):
DEVELOP = False
if DEVELOP:
result = []
for item in l:
for i in range(len(item.between)):
if i >= len(result):
result.append({})
val = item.between[i][0]
if val not in result[i]:
result[i][val] = 1
else:
result[i][val] += 1
for item in result:
sorted_result = sorted(item.iteritems(), key=operator.itemgetter(1), reverse=True)
for k, v in sorted_result:
print k + ":", v,
print
time_to_reach_first = self.__create_dict(True)
duplicates_first = self.__create_dict(True)
attributes_first = self.__create_dict(False, d=True)
time_to_reach_last= self.__create_dict(True)
duplicates_last = self.__create_dict(True)
attributes_last = self.__create_dict(False, d=True)
inter_time = []
for item in l:
for k, v in item.time_to_reach_first.iteritems():
time_to_reach_first[k].append(v)
for k, v in item.duplicates_first.iteritems():
duplicates_first[k].append(v)
for k, v in item.time_to_reach_last.iteritems():
time_to_reach_last[k].append(v)
for k, v in item.duplicates_last.iteritems():
duplicates_last[k].append(v)
for k, v in item.attributes_first.iteritems():
self.__merge_attributes(v, attributes_first, k)
for k, v in item.attributes_last.iteritems():
self.__merge_attributes(v, attributes_last, k)
if item.end_time != 0:
inter_time.append(item.end_time - item.begin_time)
print >>transition_file, name
print >>transition_file, robustnetLib.listToStr(inter_time, DEL = "\n")
print name
print "average:", robustnetLib.meanValue(inter_time), "stdev:", robustnetLib.stdevValue(inter_time)
print "min-ish:", robustnetLib.quartileResult(inter_time)[0]
print "min:", min(inter_time)
for k in time_to_reach_first.keys():
if max(duplicates_first[k]) == 0 and max(duplicates_last[k]) == 0:
continue
print "\t", k, robustnetLib.meanValue(time_to_reach_first[k]), robustnetLib.meanValue(duplicates_first[k]), min(duplicates_first[k]), len(duplicates_first[k])
self.__print_attributes(attributes_first, k)
print "\t\t", robustnetLib.meanValue(time_to_reach_last[k]), robustnetLib.meanValue(duplicates_last[k]), min(duplicates_last[k])
self.__print_attributes(attributes_last, k)
def __print_attributes(self, attribute_dict, event):
for k, v in attribute_dict[event].iteritems():
print "\t\t\t", k, "|",
if len(v) > 0 and isinstance(v[0], int):
try:
avg = float(sum(v)) / len(v)
stdev = robustnetLib.stdevValue(v, avg)
print "average:", avg, "stdev:", stdev
continue
except:
pass
counter = Counter(v).most_common(3)
for items in counter:
print items[0], ":", items[1], "|",
print
def __print_attributes(self, attribute_dict, event): for k, v in attribute_dict[event].iteritems(): print "\t\t\t", k, "|", if len(v) > 0 and isinstance(v[0], int): try: avg = float(sum(v))/len(v) stdev = robustnetLib.stdevValue(v, avg) print "average:", avg, "stdev:", stdev continue except: pass counter = Counter(v).most_common(3) for items in counter: print items[0], ":", items[1], "|", print
def merge_dicts(self, l, name, transition_file):
DEVELOP = False
if DEVELOP:
result = []
for item in l:
for i in range(len(item.between)):
if i >= len(result):
result.append({})
val = item.between[i][0]
if val not in result[i]:
result[i][val] = 1
else:
result[i][val] += 1
for item in result:
sorted_result = sorted(item.iteritems(),
key=operator.itemgetter(1),
reverse=True)
for k, v in sorted_result:
print k + ":", v,
print
time_to_reach_first = self.__create_dict(True)
duplicates_first = self.__create_dict(True)
attributes_first = self.__create_dict(False, d=True)
time_to_reach_last = self.__create_dict(True)
duplicates_last = self.__create_dict(True)
attributes_last = self.__create_dict(False, d=True)
inter_time = []
for item in l:
for k, v in item.time_to_reach_first.iteritems():
time_to_reach_first[k].append(v)
for k, v in item.duplicates_first.iteritems():
duplicates_first[k].append(v)
for k, v in item.time_to_reach_last.iteritems():
time_to_reach_last[k].append(v)
for k, v in item.duplicates_last.iteritems():
duplicates_last[k].append(v)
for k, v in item.attributes_first.iteritems():
self.__merge_attributes(v, attributes_first, k)
for k, v in item.attributes_last.iteritems():
self.__merge_attributes(v, attributes_last, k)
if item.end_time != 0:
inter_time.append(item.end_time - item.begin_time)
print >> transition_file, name
print >> transition_file, robustnetLib.listToStr(inter_time, DEL="\n")
print name
print "average:", robustnetLib.meanValue(
inter_time), "stdev:", robustnetLib.stdevValue(inter_time)
print "min-ish:", robustnetLib.quartileResult(inter_time)[0]
print "min:", min(inter_time)
for k in time_to_reach_first.keys():
if max(duplicates_first[k]) == 0 and max(duplicates_last[k]) == 0:
continue
print "\t", k, robustnetLib.meanValue(
time_to_reach_first[k]), robustnetLib.meanValue(
duplicates_first[k]), min(duplicates_first[k]), len(
duplicates_first[k])
self.__print_attributes(attributes_first, k)
print "\t\t", robustnetLib.meanValue(
time_to_reach_last[k]), robustnetLib.meanValue(
duplicates_last[k]), min(duplicates_last[k])
self.__print_attributes(attributes_last, k)
def merge_dicts_and_print(self, l, name, transition_file):
DEVELOP = False
if DEVELOP:
result = []
for item in l:
for i in range(len(item.between)):
if i >= len(result):
result.append({})
val = item.between[i][0]
if val not in result[i]:
result[i][val] = 1
else:
result[i][val] += 1
for item in result:
sorted_result = sorted(item.iteritems(), key=operator.itemgetter(1), reverse=True)
# for k, v in sorted_result:
# print k + ":", v,
# print
time_to_reach_first = self.__create_dict(True, item=None)
duplicates_first = self.__create_dict(True)
attributes_first = self.__create_dict(False, d=True)
time_to_reach_last= self.__create_dict(True, item=None)
duplicates_last = self.__create_dict(True)
attributes_last = self.__create_dict(False, d=True)
duplicates_all = self.__create_dict(True)
attributes_all = self.__create_dict(False, d=True)
inter_time = []
for item in l:
for k, v in item.time_to_reach_first.iteritems():
time_to_reach_first[k].append(v)
for k, v in item.duplicates_first.iteritems():
duplicates_first[k].append(v)
for k, v in item.time_to_reach_last.iteritems():
time_to_reach_last[k].append(v)
for k, v in item.duplicates_last.iteritems():
duplicates_last[k].append(v)
for k, v in item.duplicates_all.iteritems():
duplicates_all[k].append(v)
for k, v in item.attributes_first.iteritems():
robustnetLib.mergeDict(v, attributes_first, k)
for k, v in item.attributes_last.iteritems():
robustnetLib.mergeDict(v, attributes_last, k)
for k, v in item.attributes_all.iteritems():
robustnetLib.mergeDict(v, attributes_all, k, True)
if item.end_time != 0:
inter_time.append(item.end_time - item.begin_time)
if transition_file:
print >>transition_file, name
print >>transition_file, robustnetLib.listToStr(inter_time, DEL = "\n")
print name
print "average:", robustnetLib.meanValue(inter_time), "stdev:", robustnetLib.stdevValue(inter_time)
print "min-ish:", robustnetLib.quartileResult(inter_time)[0]
print "min:", min(inter_time)
for k in time_to_reach_first.keys():
if max(duplicates_first[k]) == 0 and max(duplicates_last[k]) == 0:
continue
print "\t", k
print "\t\tBEGIN: ",
print "time from start:", robustnetLib.meanValue(time_to_reach_first[k]),
print "frequency appears: ", self.fraction_there(duplicates_first[k]),
print "duplicates:", robustnetLib.meanValue(duplicates_first[k]),
print "min appearances:", min(duplicates_first[k]),
print "number of tests:", len(duplicates_first[k])
self.__print_attributes(attributes_first, k)
print "\t\tALL: ",
print "frequency appears:", self.fraction_there(duplicates_all[k]),
print "duplicates:", robustnetLib.meanValue(duplicates_all[k]),
print "number of tests:", len(duplicates_all[k])
self.__print_attributes(attributes_all, k)
print "\t\tEND: ",
print "time from end:", robustnetLib.meanValue(time_to_reach_last[k]),
print "frequency appears:", self.fraction_there(duplicates_last[k]),
print "duplicates:", robustnetLib.meanValue(duplicates_last[k]),
print "min appearances:", min(duplicates_last[k])
print "RSSI and power ratio:", item.RSSI, item.power_ratio
self.__print_attributes(attributes_last, k)