def main():
"""
This file is the main method call. Execution starts from here.
It accepts input data either correct or incorrect data.
:return: Output of the data provided.
:param: It accepts file directory,which contains input_data.txt file.
"""
simulation = RobotSimulation()
execute_directory = sys.argv[1]
if len(execute_directory) == len("input_data"):
correct_files = fm.load("input_data", "r")
for correct_file in correct_files:
print("\n")
print("FIle executed from Input Directory - ", correct_file)
for values in fm.read(correct_file):
for line in values.split("\n"):
if len(line):
simulation.run(line)
elif len(execute_directory) == len("incorrect_data"):
incorrect_files = fm.load("incorrect_data")
for incorrect_file in incorrect_files:
print("\n")
print("FIle executed from Incorrect Directory - ", incorrect_file)
for values in fm.read(incorrect_file):
for line in values.split("\n"):
if len(line):
simulation.run(line)
else:
print("Please provide the exact directory")
def test_setup():
print(fm.create('resources'))
print(fm.load('resources'))
for i in fm.read('adverbs.dat'):
print(i)
print(fm.close('nouns.dat'))
print(fm.close())
def learnFromFiles():
path = fm.load('resources')
for f in path:
isFirst = True
lettercount = 0
for i in fm.read(f):
if isFirst:
for x in langs:
if i.replace("\n", "") == x.get("language"):
currentdict = x
break
else:
langs.append({"language": i.replace("\n", "")})
currentdict = langs[len(langs) - 1]
isFirst = False
else:
for singleletter in i:
if (ord(singleletter) >= 97 and ord(singleletter) <= 122
) or (ord(singleletter) >= 65
and ord(singleletter) <= 90):
lettercount = lettercount + 1
if singleletter.lower() in currentdict:
currentdict[singleletter.lower(
)] = currentdict[singleletter.lower()] + 1
else:
currentdict[singleletter.lower()] = 1
if "letternumber" in currentdict:
currentdict["letternumber"] = currentdict["letternumber"] + float(
lettercount)
else:
currentdict["letternumber"] = float(lettercount)
for i in langs:
handleFile(i)
def test_setup():
print(fm.create('resources'))
print(fm.load('resources'))
for i in fm.read('adverbs.dat'):
print(i)
print(fm.close('nouns.dat'))
print(fm.close())
def get_query_index(requete):
"""
fonction qui prend une requête écrite en entrée et donne son indice parmi les 64 requêtes proposées.
"""
index = 0
queries = fm.load("Requetes")
for query in queries:
for line in fm.read(query):
if line == requete:
index = query.split()[1]
return index
def convent(files):
all_words = []
for file in files:
for line in fm.read(file):
if '-' in line:
index = line.index('-')
english = line[:index:]
russian = line[index + 1::]
a = {english: russian.replace('\n', '')}
all_words.append(a)
return all_words
def main():
#opens all the files in the folder
all_files = fm.load('test')
docs = []
#instantiating Porter Stemming
stemmer = PorterStemmer()
for f in all_files:
docStr = ""
for i in fm.read(f):
docStr += i
# docStr.replace('\n', ' ')
# docStr.replace('\\', ' ')
# docStr.replace('.', ' ')
# docStr.replace(',', ' ')
docStr = remove_all("\n", docStr)
docStr = remove_all("\\", docStr)
docStr = remove_all('"', docStr)
docStr = remove_all(':', docStr)
docStr = remove_all(".", docStr)
docStr = remove_all(",", docStr)
#unicode encoding for stemming
p = docStr.decode('cp850').replace(u"\u2019", u"\x27")
res = " ".join([stemmer.stem(kw) for kw in p.split(" ")])
k = unicodedata.normalize('NFKD', res).encode('ascii', 'ignore')
docs.append(k)
docOfInterest = docs[5]
#testing on article
a = ArticleScorer(docOfInterest, docs)
print(a.represent())
docs_and_similarities = []
for docOfInterest in docs:
# print docOfInterest
a = ArticleScorer(docOfInterest, docs)
# print(a.represent())
docs_and_similarities.append((docOfInterest, a.represent()))
print docs_and_similarities
best_matches = queue.PriorityQueue()
article = docs_and_similarities[0]
for other in docs_and_similarities[1:]:
print "score", cosine(article, other)
best_matches.put((-1 * cosine(article, other), other[0]))
for i in xrange(5):
print extract_title(best_matches.get()[1])
def main(argv):
print "\n"
sequence = []
all_files = fm.load('Edge1_')
for f in all_files:
Sort_file(f)
all_files = fm.load('Edge1_')
for f in all_files:
sampling_time = 5 # in mins
file_ = open("Edge1_/" + f, 'r')
line = file_.readline()
data = line.split(' ')
prev_time = data[1] + ' ' + data[2]
date_format = "%Y-%m-%d %H:%M:%S"
prev_time_ = datetime.strptime(prev_time, date_format)
#print prev_time_
no_cars = 0
avg_velocity = 0
for line in fm.read(f):
line = line.replace('\n', '')
data = line.split(' ')
current_time = data[1] + ' ' + data[2]
current_time_ = datetime.strptime(current_time, date_format)
time_interval = current_time_ - prev_time_
print time_interval
if time_interval.seconds < sampling_time * 60:
no_cars = no_cars + 1
avg_velocity = avg_velocity + float(data[9])
#print no_cars
else:
dd = str(data[5]) + ' ' + str(
data[6]) + ' ' + str(no_cars) + ' ' + str(
avg_velocity / no_cars) + '\n'
print dd
prev_time_ = current_time_
avg_velocity = float(data[9])
no_cars = 1
with open('feature_extracted.txt', 'a') as outfile:
outfile.write(dd)
return 0
def test_setup():
print("begin test_setup")
print(fm.create('resources'))
if 'words.dat' and 'nouns.dat' in fm.create('resources'):
print('Files Missing')
print(fm.load('resources'))
for i in fm.read('adverbs.dat'):
print(i)
print(fm.close('words.dat'))
print(fm.close())
try:
print(fm.close('words.dat'))
raise ValueError("test_setup failed") # pragma: no cover
except IOError:
print("test_setup passed")
def test_setup():
print("begin test_setup")
print(fm.create('resources'))
if 'words.dat' and 'nouns.dat' in fm.create('resources'):
print('Files Missing')
print(fm.load('resources'))
for i in fm.read('adverbs.dat'):
print(i)
print(fm.close('words.dat'))
print(fm.close())
try:
print(fm.close('words.dat'))
raise ValueError("test_setup failed") # pragma: no cover
except IOError:
print("test_setup passed")
def create_terms_pairs(folder_name):
"""
cree un dictionnaire de paires de term: term_id a partir de la collection
"""
documents = fm.load(folder_name)
terms_pairs = {}
id = 1
for document in documents:
for line in fm.read(document):
for word in line.split():
try:
terms_pairs[word]
except KeyError:
terms_pairs[word] = id
id += 1
return terms_pairs
def create_terms_doc_pairs(folder_name):
"""
cree une liste de paires de (terme_id, doc_id)
"""
documents_pairs = create_document_pairs(folder_name)
terms_pairs = create_terms_pairs(folder_name)
documents = fm.load(folder_name)
terms_doc_pairs_list = []
for document in documents:
for line in fm.read(document):
for word in line.split():
term_id = terms_pairs[word]
document_id = documents_pairs[document]
pair = (term_id, document_id)
terms_doc_pairs_list.append(pair)
return terms_doc_pairs_list
def moyenne_precisions():
"""
fonction qui ne prend rien en entrée
et qui fait la moyenne des précisions pour les 64 requêtes de query.text
"""
queries = fm.load("Requetes")
written_queries = []
precisions = []
rappel = [0] * (101)
precision = [0] * (101)
for query in queries:
for line in fm.read(query):
written_queries.append(line)
for i in range(64):
precisions.append(data_courbe(written_queries[i])[1])
for i in range(101):
rappel[i] = i / 100
for j in range(64):
precision[i] += precisions[j][i] / 64
return rappel, precision
def calculateDistance(text, lang, i, max, isLearning, isWiki):
path = fm.load('constlearnt')
dicts = []
distances = {}
for f in path:
fromFileInfo = {}
isFirstLine = True
for y in fm.read(f):
if isFirstLine:
isFirstLine = False
else:
arr = y.split('/')
fromFileInfo[arr[0]] = arr[1].replace("\n", "")
dicts.append(fromFileInfo)
(dicts[len(dicts) - 1])["language"] = f.replace(".txt", "").replace(
"learned_", "")
newtextdict = getDictFromText(text, True)
for dic in dicts:
for ch in alphabet:
if not ch in dic:
dic[ch] = 0.0
if not ch in newtextdict:
newtextdict[ch] = 0.0
distances[dic["language"]] = euclideanDistance(newtextdict, dic)
print("Zgaduje, iz artykul jest w jezyku " +
min(distances, key=lambda k: distances[k]))
global tries
global correct
tries = tries + 1
if min(distances, key=lambda k: distances[k]) == lang:
correct = correct + 1
print("Jezyk sie zgadza")
else:
print("Jezyk sie nie zgadza")
print(("Skutecznosc zgadywania to w tym momencie " +
str(float(correct) / float(tries) * 100) + " proby: " + str(tries) +
" poprawne: " + str(correct)))
print("\n")
if isWiki:
testAlgorithm(i, max, isLearning, isWiki)
"""
import filemapper as fm
files=fm.load('Mom Proj')
fileslist=[]
for elem in files:
fileslist.append(elem.split('_'))
fileslistr=[]
for elem in fileslist:
elem[-1]=elem[-1].split('.')[0]
fileslistr.append(elem)
print(fileslistr)
loop=-1
final=[]
for f in files:
e=[]
loop=loop+1
for i in fm.read(f):
d=','.join(fileslistr[loop])
e.append(d+','+i)
final.append(e)
import csv
loop=-1
for elem in final:
loop=loop+1
name=str(''.join(fileslistr[loop]))+'1'+'.csv'
myfile = open(name, 'w')
wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
for ele in elem:
wr.writerow(ele.split(','))
for t in types:
results[t] = {}
for r in routers:
results[t][r] = {}
for bs in bufferSize:
results[t][r][bs] = {}
for n in nodes:
results[t][r][bs][n] = {}
# Read data
for t in types:
res = results[t]
files = fm.load(t)
for f in files:
r, bs, n, _ = f.split('_') # Getting the result's parameters
for line in fm.read(f):
try:
stat, value = line.split(':')
value = float(value)
res[r][bs][n][stat] = value
except ValueError:
pass
# Router Impact
for t in types:
for n in nodes:
delivery_probs = []
latency_avgs = []
overhead_ratio = []
hopcount_avg = []
for bs in bufferSize:
import filemapper as fm
all_files = fm.load('Pics')
for f in all_files:
for i in fm.read(f):
for f in all_files:
for i in fm.write
win_unicode_console.enable()
if len(sys.argv) > 1: # len小於2也就是不帶參數啦
sys.argv = [arg.decode(sys.stdout.encoding) for arg in sys.argv]
text = " ".join(sys.argv[1:])
# print(exec_segment(text))
text = str(text, 'utf-8')
print(text)
sys.exit()
for f in all_files:
if f == ".gitignore":
continue
elif f.endswith(".txt"):
content = ""
for i in filemapper.read(f):
content = content + i
# print(content)
result = exec_segment(content)
if isinstance(result, list):
result = ",".join(result)
# 加上欄位標題
line = []
if save_pos_tag_field == "true":
line.append("seg")
else:
line.append("seg_pos")
if save_pos_tag_field == "true" and enable_pos_tag == "true":