def test02(self):
df=DataFrame()
df.read_tbl('data/words~ageXcondition.csv')
D = repr(df.histogram('WORDS'))
R = "Histogram([('values', [4.0, 14.0, 17.0, 12.0, 15.0, 10.0, 9.0, 5.0, 6.0, 8.0]), \
('bin_edges', [3, 5.0, 7.0, 9.0, 11.0, 13.0, 15.0, 17.0, 19.0, 21.0, 23])], cname='WORDS')"
self.assertEqual(D, R)
def test02(self):
df = DataFrame()
df.read_tbl('data/words~ageXcondition.csv')
D = repr(df.histogram('WORDS'))
R = "Histogram([('values', [4.0, 14.0, 17.0, 12.0, 15.0, 10.0, 9.0, 5.0, 6.0, 8.0]), \
('bin_edges', [3, 5.0, 7.0, 9.0, 11.0, 13.0, 15.0, 17.0, 19.0, 21.0, 23])], cname='WORDS')"
self.assertEqual(D, R)
def test0(self):
R=[[4.0, 14.0, 17.0, 12.0, 15.0, 10.0, 9.0, 5.0, 6.0, 8.0],
[3.0, 5.0, 7.0, 9.0, 11.0, 13.0, 15.0, 17.0, 19.0, 21.0, 23.0]]
df=DataFrame()
df.read_tbl('data/words~ageXcondition.csv')
D=df.histogram('WORDS')
D=[D['values'],D['bin_edges']]
for (d,r) in zip(_flatten(D),_flatten(R)):
self.assertAlmostEqual(d,r)
def test0(self):
R = [[4.0, 14.0, 17.0, 12.0, 15.0, 10.0, 9.0, 5.0, 6.0, 8.0],
[3.0, 5.0, 7.0, 9.0, 11.0, 13.0, 15.0, 17.0, 19.0, 21.0, 23.0]]
df = DataFrame()
df.read_tbl('data/words~ageXcondition.csv')
D = df.histogram('WORDS')
D = [D['values'], D['bin_edges']]
for (d, r) in zip(_flatten(D), _flatten(R)):
self.assertAlmostEqual(d, r)
def test01(self):
df=DataFrame()
df.read_tbl('data/words~ageXcondition.csv')
D=str(df.histogram('WORDS',cumulative=True))
R = """\
Cumulative Histogram for WORDS
Bins Values
================
3.000 4.000
5.000 18.000
7.000 35.000
9.000 47.000
11.000 62.000
13.000 72.000
15.000 81.000
17.000 86.000
19.000 92.000
21.000 100.000
23.000 """
self.assertEqual(D, R)
def test01(self):
df = DataFrame()
df.read_tbl('data/words~ageXcondition.csv')
D = str(df.histogram('WORDS', cumulative=True))
R = """\
Cumulative Histogram for WORDS
Bins Values
================
3.000 4.000
5.000 18.000
7.000 35.000
9.000 47.000
11.000 62.000
13.000 72.000
15.000 81.000
17.000 86.000
19.000 92.000
21.000 100.000
23.000 """
self.assertEqual(D, R)
