def test1(self):
df=DataFrame()
df.TESTMODE=True
df.read_tbl('data/words~ageXcondition.csv')
D=df.histogram_plot('WORDS', cumulative=True, output_dir='output')
self.assertEqual(D['fname'],'output\\hist(WORDS,cumulative=True).png')
def test1(self):
df = DataFrame()
df.TESTMODE = True
df.read_tbl('data/words~ageXcondition.csv')
D = df.histogram_plot('WORDS', cumulative=True, output_dir='output')
self.assertEqual(D['fname'], 'output\\hist(WORDS,cumulative=True).png')
def test0(self):
R = {'bins': np.array([ 4, 14, 17, 12, 15, 10, 9, 5, 6, 8]),
'counts': np.array([ 3., 5., 7., 9., 11., 13., 15., 17., 19., 21., 23.]),
'fname': 'output\\hist(WORDS).png'}
df=DataFrame()
df.TESTMODE=True
df.read_tbl('data/words~ageXcondition.csv')
D=df.histogram_plot('WORDS', output_dir='output')
self.assertEqual(D['fname'],R['fname'])
for d,r in zip(D['bins'].flat,R['bins'].flat):
self.assertAlmostEqual(d,r)
for d,r in zip(D['counts'].flat,R['counts'].flat):
self.assertAlmostEqual(d,r)
def test0(self):
R = {
'bins': np.array([4, 14, 17, 12, 15, 10, 9, 5, 6, 8]),
'counts':
np.array([3., 5., 7., 9., 11., 13., 15., 17., 19., 21., 23.]),
'fname': 'output\\hist(WORDS).png'
}
df = DataFrame()
df.TESTMODE = True
df.read_tbl('data/words~ageXcondition.csv')
D = df.histogram_plot('WORDS', output_dir='output')
self.assertEqual(D['fname'], R['fname'])
for d, r in zip(D['bins'].flat, R['bins'].flat):
self.assertAlmostEqual(d, r)
for d, r in zip(D['counts'].flat, R['counts'].flat):
self.assertAlmostEqual(d, r)
