def parse(structSignature: str, bindingGrammar: Grammar) -> list:
contents = fileHandler.readFile(filename)
struct = fileHandler.findStructSignature(structSignature, contents)
parsed = bindingGrammar.parse(struct)
if parsed.is_valid:
parsed_list = TreeParser(parsed)
return parsed_list.getBindings()
print(parsed.as_str())
return []
def checkForTableID(moduleID):
#string = "@PersistenceCapable(detachable = \"true\", table = \"foo_account\")"
flag = True
task_dict = {}
table_dict = {}
for f in fileHandler.getAllFilesMatching('*.java'):
contents = fileHandler.readFile(f)
# Initial work on checking task/config names
# try:
# method = javaHandler.readMethod(contents, "public String getDisplayLabel()")
# print method
# except:
# False
try:
method = javaHandler.readMethod(contents, "public TaskConfigIf getTaskConfigImplementation")
if (method[0].split()[2] in task_dict.keys()):
log.critical("Task config re-used: " + method[0].split()[2] + " in files: " + f + " & " + task_dict[method[0].split()[2]])
flag = False
else:
task_dict[method[0].split()[2]] = f
except:
False
for line in contents:
if(("@PersistenceCapable" in line) and ("table" in line)):
inBrackets = gstring.getTargetBetweenBrackets(line)
attributes = inBrackets.split(",")
tableAttribute = [s for s in attributes if "table" in s]
a = re.findall('"([^"]*)"', tableAttribute[0])[0]
if (a in table_dict.keys()):
log.critical("\tTable already used: " + a + " (files: " + table_dict.get(str(a)) + " & " + f)
flag = False
else:
table_dict[str(a)] = f
if(not a.startswith((moduleID + "_"))):
log.critical("\tThe table ID in class " + f + " is not prefixed the moduleID and an underscore: " + moduleID + "_")
if (flag == False):
log.critical("Table checking failed")
exit(1)
'''
def getClassesListedForEnhancement():
files = fileHandler.getAllFilesMatching("jdo.files")
#Go through and get all of the files that are LISTED for enhancement
newList = []
for f in files:
if("src" in f):
newList.append(f)
files = newList
listOfClasses = []
for f in files:
fileContents = fileHandler.readFile(f)
classes = getJDOClassesInFile(fileContents)
for c in classes:
listOfClasses.append(c)
return listOfClasses
reminderList['items'] = []
writeFile("reminderlist.txt", reminderList)
def reminderQuit():
"""
This function has to be called when shutting down. It terminates all waiting threads.
"""
try:
for index, el in timerList.iteritems():
el.cancel()
except:
for index, el in timerList.items():
el.cancel()
timerList = {}
reminderList = readFile("reminderlist.txt", {'items': []})
reminderList['items'] = sort(reminderList['items'])
reminderList['items'] = [i for i in reminderList['items'] if not i['hidden']]
for e in reminderList['items']:
e['time'] = str2date(e['time'])
waitTime = e['time'] - dt.now()
n = Notify.Notification.new(e['name'])
n.set_urgency(Notify.Urgency.LOW)
timerList[e['uuid']] = Timer(waitTime.total_seconds(), showAlarm,
[n, e['name']])
timerList[e['uuid']].start()
Notify.init("Jarvis")
from fileHandler import readFile, separator
from Regressao_Logistica import constroi_modelo
import numpy as np
import matplotlib.pyplot as plt
matrix = readFile('tic-tac-toe.data')
X_treino, Y_treino, X_teste, Y_teste = separator(0.3, matrix)
X_treino = np.array(X_treino).T.astype(np.float)
Y_treino = np.array([Y_treino]).astype(np.float)
X_teste = np.array(X_teste).T.astype(np.float)
Y_teste = np.array([Y_teste]).astype(np.float)
print(X_treino.shape)
print(Y_treino.shape)
print(X_teste.shape)
print(Y_teste.shape)
def raioGraficalizador(dados, intervalo, numeroIteracoes, taxaAprendizado):
fig, ax = plt.subplots()
x = [None] * dados.__len__()
for i in range(dados.__len__()):
x[i] = i * intervalo
ax.plot(x, dados)
plt.scatter(x, dados) # scatter são os quadradinhos na linha
titulo = 'Taxa de aprendizado: {0} | Número de iterações: {1}'
def hasAnnotations(filePath): sub = "import javax.jdo.annotations" contents = fileHandler.readFile(filePath) return len([s for s in contents if sub in s]) != 0
# Select the best trigger match from the actions list
for key in actions:
foundMatch = False
for trigger in actions[key]['trigger']:
newScore, indexList = scoreSentence(data, trigger, distancePenalty = 0.5, additionalTargetPenalty = 0, wordMatchPenalty = 0.5)
if foundMatch and len(indexList) > len(indices):
# A match for this action was already found.
# But this trigger matches more words.
indices = indexList
if newScore < score:
if not foundMatch:
indices = indexList
minArgs = actions[key]['minArgs']
foundMatch = True
score = newScore
action = key
if not action:
return
data = data.split();
for i in sorted(indices, reverse=True):
del data[i]
if len(data) < minArgs:
warning("Not enough arguments for specified command {0}".format(action))
return
data = " ".join(data)
globals()[action](data)
todoList = readFile("todolist.txt", {'items':[]})
todoList['items'] = fixTypes(sort(todoList['items']))