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)