Exemplo n.º 1
0
    def __init__(self, settings_file):

        self.settings_file = settings_file
        self.json_file = read_json(settings_file)
        self.todo_size, self.history_size, self.delta_size = -1, -1, -1
        self.todo_list, self.history_list, self.delta_list = [], [], []
        self.get_queue_size()
Exemplo n.º 2
0
    def __init__(self, name, settings_file, parent=None):

        self.name = name
        self.media_type = ""
        self.settings = read_json(settings_file)
        self.parent = parent

        self.get_suggested_metadata()
Exemplo n.º 3
0
reply_kb_university = ReplyKeyboardMarkup(
    [["City University of Hong Kong"], ["Hong Kong Baptist University"],
     ["Lingnan University"], ["The Chinese University of Hong Kong"],
     ["The Education University of Hong Kong"],
     ["The Hong Kong Polytechnic University"],
     ["The Hong Kong University of Science and Technology"],
     ["The University of Hong Kong"], ["Hang Seng University of Hong Kong"],
     ["Hong Kong Shue Yan University"], ["The Open University of Hong Kong"],
     ["Others"]],
    one_time_keyboard=True)

# reply_kb_example = ReplyKeyboardMarkup([['Where is the library?'],['Tell me the contact of KEC']], one_time_keyboard=True)

# initial the nltk parts
default_tagger = nltk.tag.DefaultTagger('NN')
model = read_json('json/models.json')
tl_MWs = read_multiwords_json('json/multiwords.json')

tags_dict = {}

tagger = nltk.tag.UnigramTagger(model=model, backoff=default_tagger)
tknzr = TweetTokenizer(strip_handles=True, reduce_len=True)
mwtknzr = MWETokenizer(tl_MWs)
stop_words = set(stopwords.words('english'))

# initialize the list of information for class schedule
clList = readClSchedule('schedule/MTT_2021S2_Custom.xls')


def createKeyBoardLayout(btnStringList: list) -> ReplyKeyboardMarkup:
    for btsString in btnStringList:
Exemplo n.º 4
0
    pl.clf()
    pl.plot(x, y, label='Raw Data')
    for i in range(len(smoothy)):
        pl.plot(x, smoothy[i], label='Smooth('+str(f[i])+')')
    pl.legend()
    pl.savefig('./imgs/lowess')
    print "Successfully created picture file lowess.png"




if __name__ == '__main__':
    #pdb.set_trace()
    import numpy as np
    from readjson import read_json
    cpu, cpu_time, mem, mem_time, load, load_time = read_json("./host2.json")


    #x = np.asarray(cpu_time)
    y=[]
    for i in xrange(30):
        y = y+cpu
    x = np.arange(0.0, len(y))

    print "----------------- LOWESS ---------------------"

    def chunks(l, n):
        for i in xrange(0, len(l), n):
            yield l[i:i+n]

    chunk_size = 1000
Exemplo n.º 5
0
    from ewma import ewma_with_window

    ave_y = ewma_with_window(y, 0.8, 50)
    pl.clf()
    pl.plot(x, y, label="raw data")
    pl.plot(x, ave_y, label="EWMAverage")
    pl.legend()
    pl.savefig("./imgs/emwa_window")
    print "Successfully created picture file emwa_window.png"


if __name__ == '__main__':
    #pdb.set_trace()
    import numpy as np
    from readjson import read_json
    cpu, cpu_time, mem, mem_time, load, load_time = read_json("./host2.json")

    x = np.asarray(cpu_time)
    y = cpu
    #x = np.array([[1,2,3,4,5,6],[1,232,3,41,5,6]]).reshape(2,6)
    #y = np.array([[1,2,2,3,4,5]])
    print(x.shape)
    print(y.shape)

    print "----------------- LOWESS ---------------------"
    testLowess(x, y)

    print "------------ Liner Regression ----------------"
    testLinerRegression(x, y)

    print "------------- Poly Regression ----------------"