def testCSVIntegrity(self):
print("** Test CSV Integrity **")
the_normalizer = Normalizer("datasets/test_normalization.csv")
data = the_normalizer.get_csv()
origin_data = [['0', '3', '0'], ['1', '33', '100'], ['0.5', '6', '90']]
length = 3
self.assertTrue(data == origin_data, "Data and CSV file doesn't match")
self.assertTrue(length == the_normalizer.getRowLength(),
"Line length doesn't match")
def __init__(self, k, n, columns, datafile):
"""Constructeur pour la classe KMeanClusterer"""
super(KMeanClusterer, self).__init__()
# Number of clusters wanted
self.k = k
self.n = n
self.is_over = False
# columns to work with
self.columns = sorted(columns)
# Get CSV data
norm = Normalizer(datafile)
self.data = norm.normalize()
self.row_length = norm.getRowLength()
self.clusters = []
def __init__(self, k, n, columns, datafile):
"""Constructeur pour la classe KMeanClusterer"""
super(KMeanClusterer, self).__init__()
# Number of clusters wanted
self.k = k
self.n = n
self.is_over = False
# columns to work with
self.columns = sorted(columns)
# Get CSV data
norm = Normalizer(datafile)
self.data = norm.normalize()
self.row_length = norm.getRowLength()
self.clusters = []