def __init__(self, *args, **kwargs):
self.__class__ = type(str(self.__class__),
(self.__class__, IterativePE), {})
IterativePE.__init__(self, *args, **kwargs)
# name=self.name
ProvenancePE.__init__(self, self.name, *args, **kwargs)
def __init__(self, t_start, t_finish, channel):
IterativePE.__init__(self)
self.t_start=t_start
self.t_finish=t_finish
self.channel=channel
self.counter = 0
self.bulksize = 10
def __init__(self, t_start, t_finish, channel):
IterativePE.__init__(self)
self.t_start = t_start
self.t_finish = t_finish
self.channel = channel
self.counter = 0
self.bulksize = 10
def __init__(self, sentimentData):
IterativePE.__init__(self)
afinnfile = open(ROOT_DIR + sentimentData)
self.sentiment= {}
for line in afinnfile:
term, score = line.split("\t") # The file is tab-delimited. "\t" means "tab character"
self.sentiment[term] = float(score) # Convert the score to an integer.
self.method = 'AFINN'
def __init__(self, sentimentData):
IterativePE.__init__(self)
afinnfile = open(ROOT_DIR + sentimentData)
self.sentiment = {}
for line in afinnfile:
term, score = line.split(
"\t") # The file is tab-delimited. "\t" means "tab character"
self.sentiment[term] = float(
score) # Convert the score to an integer.
self.method = 'AFINN'
def __init__(self, index):
IterativePE.__init__(self)
self.index = index
def __init__(self): IterativePE.__init__(self) self.method = 'SWN3'
def __init__(self,rootpah):
IterativePE.__init__(self)
#self._add_input('input')
#self._add_output('output')
self.counter = 0
self.roothpath=rootpah
def __init__(self):
IterativePE.__init__(self)
self.count = defaultdict(int)
def __init__(self, tag):
IterativePE.__init__(self)
self.tag = tag
def __init__(self, label):
IterativePE.__init__(self)
self.label = label
def __init__(self):
IterativePE.__init__(self)
self.US_states={}
self.US_states=self.load_states("us-states.json")
def __init__(self, tag):
IterativePE.__init__(self)
self.tag = tag
def __init__(self):
IterativePE.__init__(self)
self.method = 'SWN3'
def __init__(self, sentimentData):
IterativePE.__init__(self)
self.filename = ROOT_DIR + sentimentData
self.db = {}
self.sentiment = self.parse_src_file()
self.threshold = 0.87
def __init__(self, compare):
IterativePE.__init__(self)
self.compare = compare
def __init__(self, divisor):
IterativePE.__init__(self)
self.divisor = divisor
def testIterative():
it = IterativePE()
tools.ok_(it._process(1) is None)
def __init__(self,index):
IterativePE.__init__(self)
#self._add_input('input')
#self._add_output('output')
self.index = index
def __init__(self):
IterativePE.__init__(self)
self.US_states = {}
self.US_states = self.load_states("us-states.json")
def __init__(self, rootpah):
IterativePE.__init__(self)
#self._add_input('input')
#self._add_output('output')
self.counter = 0
self.roothpath = rootpah
def __init__(self, compute_fn, params={}):
IterativePE.__init__(self)
self.compute_fn = compute_fn
self.params = params
def __init__(self, label):
IterativePE.__init__(self)
self.label = label
self.ext = 'data' if label == 'real' else label
self.pattern = re.compile('(\w*\.\w*)\.(\w*)\.{}'.format(self.ext))
def __init__(self, compute_fn, params={}):
IterativePE.__init__(self)
self.compute_fn = compute_fn
self.params = params
def __init__(self,ty,freq=(0.3, 1.0, 3.0),damp=0.1):
IterativePE.__init__(self)
self.ty=ty
self.frequencies = freq
self.damp = damp
def __init__(self, compute_fn=None, params={}):
IterativePE.__init__(self)
self._add_output('output',
tuple_type=['result', 'station', 'counter', 't_now'])
self.compute_fn = compute_fn
self.params = params
def __init__(self):
IterativePE.__init__(self)
def __init__(self, sentimentData):
IterativePE.__init__(self)
self.filename= ROOT_DIR + sentimentData
self.db = {}
self.sentiment=self.parse_src_file()
self.threshold = 0.87
def __init__(self, index):
IterativePE.__init__(self)
# self._add_input('input')
# self._add_output('output')
self.index = index
def __init__(self, compute_fn=None, params={}):
IterativePE.__init__(self)
self._add_output('output', tuple_type=['result', 'station', 'counter'])
self.compute_fn = compute_fn
self.params = params
