def test3(self):
df=DataFrame()
with self.assertRaises(Exception) as cm:
df.box_plot('a', output_dir='output')
self.assertEqual(str(cm.exception),
'Table must have data to print data')
def test3(self):
df = DataFrame()
with self.assertRaises(Exception) as cm:
df.box_plot('a', output_dir='output')
self.assertEqual(str(cm.exception),
'Table must have data to print data')
def test6(self):
df = DataFrame()
df['a'] = [2, 5]
df['b'] = [2, 3]
with self.assertRaises(KeyError) as cm:
df.box_plot('c', output_dir='output')
self.assertEqual(str(cm.exception), "'c'")
def test5(self):
df = DataFrame()
df['a'] = [2, 5]
df['b'] = [2, 3]
with self.assertRaises(Exception) as cm:
df.box_plot('a', 42, output_dir='output')
self.assertEqual(str(cm.exception), "'int' object is not iterable")
def test4(self):
df = DataFrame()
df['a'] = [2]
df['b'] = [2, 3]
with self.assertRaises(Exception) as cm:
df.box_plot('a', output_dir='output')
self.assertEqual(str(cm.exception), 'columns have unequal lengths')
def test6(self):
df=DataFrame()
df['a']=[2,5]
df['b']=[2,3]
with self.assertRaises(KeyError) as cm:
df.box_plot('c', output_dir='output')
self.assertEqual(str(cm.exception),"'c'")
def test5(self):
df=DataFrame()
df['a']=[2,5]
df['b']=[2,3]
with self.assertRaises(Exception) as cm:
df.box_plot('a',42, output_dir='output')
self.assertEqual(str(cm.exception),
"'int' object is not iterable")
def test4(self):
df=DataFrame()
df['a']=[2]
df['b']=[2,3]
with self.assertRaises(Exception) as cm:
df.box_plot('a', output_dir='output')
self.assertEqual(str(cm.exception),
'columns have unequal lengths')
def test1(self):
R = {
'd': [
np.array([
9, 8, 6, 8, 10, 4, 6, 5, 7, 7, 7, 9, 6, 6, 6, 11, 6, 3, 8,
7, 11, 13, 8, 6, 14, 11, 13, 13, 10, 11, 12, 11, 16, 11, 9,
23, 12, 10, 19, 11, 10, 19, 14, 5, 10, 11, 14, 15, 11, 11
]),
np.array([
8, 6, 4, 6, 7, 6, 5, 7, 9, 7, 10, 7, 8, 10, 4, 7, 10, 6, 7,
7, 14, 11, 18, 14, 13, 22, 17, 16, 12, 11, 20, 16, 16, 15,
18, 16, 20, 22, 14, 19, 21, 19, 17, 15, 22, 16, 22, 22, 18,
21
])
],
'fname':
'output\\box(WORDS~AGE).png',
'maintitle':
'WORDS by AGE',
'xlabels': ['AGE = old', 'AGE = young']
}
df = DataFrame()
df.TESTMODE = True
df.read_tbl('data/words~ageXcondition.csv')
D = df.box_plot('WORDS', ['AGE'], output_dir='output')
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['xlabels'], R['xlabels'])
for d, r in zip(np.array(D['d']).flat, np.array(R['d']).flat):
self.assertAlmostEqual(d, r)
def test0(self):
R = {
'd': [
9.0, 8.0, 6.0, 8.0, 10.0, 4.0, 6.0, 5.0, 7.0, 7.0, 7.0, 9.0,
6.0, 6.0, 6.0, 11.0, 6.0, 3.0, 8.0, 7.0, 11.0, 13.0, 8.0, 6.0,
14.0, 11.0, 13.0, 13.0, 10.0, 11.0, 12.0, 11.0, 16.0, 11.0,
9.0, 23.0, 12.0, 10.0, 19.0, 11.0, 10.0, 19.0, 14.0, 5.0, 10.0,
11.0, 14.0, 15.0, 11.0, 11.0, 8.0, 6.0, 4.0, 6.0, 7.0, 6.0,
5.0, 7.0, 9.0, 7.0, 10.0, 7.0, 8.0, 10.0, 4.0, 7.0, 10.0, 6.0,
7.0, 7.0, 14.0, 11.0, 18.0, 14.0, 13.0, 22.0, 17.0, 16.0, 12.0,
11.0, 20.0, 16.0, 16.0, 15.0, 18.0, 16.0, 20.0, 22.0, 14.0,
19.0, 21.0, 19.0, 17.0, 15.0, 22.0, 16.0, 22.0, 22.0, 18.0,
21.0
],
'fname':
'output\\box(WORDS).png',
'maintitle':
'WORDS',
'val':
'WORDS'
}
df = DataFrame()
df.TESTMODE = True
df.read_tbl('data/words~ageXcondition.csv')
D = df.box_plot('WORDS', output_dir='output')
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['val'], R['val'])
for d, r in zip(np.array(D['d']).flat, np.array(R['d']).flat):
self.assertAlmostEqual(d, r)
def test1(self):
R = {'d': [np.array([ 9, 8, 6, 8, 10, 4, 6, 5, 7, 7,
7, 9, 6, 6, 6, 11, 6, 3, 8, 7,
11, 13, 8, 6, 14, 11, 13, 13, 10, 11,
12, 11, 16, 11, 9, 23, 12, 10, 19, 11,
10, 19, 14, 5, 10, 11, 14, 15, 11, 11]),
np.array([ 8, 6, 4, 6, 7, 6, 5, 7, 9, 7,
10, 7, 8, 10, 4, 7, 10, 6, 7, 7,
14, 11, 18, 14, 13, 22, 17, 16, 12, 11,
20, 16, 16, 15, 18, 16, 20, 22, 14, 19,
21, 19, 17, 15, 22, 16, 22, 22, 18, 21])],
'fname': 'output\\box(WORDS~AGE).png',
'maintitle': 'WORDS by AGE',
'xlabels': [u'AGE = old', u'AGE = young']}
df=DataFrame()
df.TESTMODE=True
df.read_tbl('data/words~ageXcondition.csv')
D=df.box_plot('WORDS',['AGE'], output_dir='output')
self.assertEqual(D['fname'],R['fname'])
self.assertEqual(D['maintitle'],R['maintitle'])
self.assertEqual(D['xlabels'],R['xlabels'])
for d,r in zip(np.array(D['d']).flat,
np.array(R['d']).flat):
self.assertAlmostEqual(d,r)
def test0(self):
R = {'d': [9.0, 8.0, 6.0, 8.0, 10.0, 4.0, 6.0, 5.0, 7.0, 7.0,
7.0, 9.0, 6.0, 6.0, 6.0, 11.0, 6.0, 3.0, 8.0, 7.0,
11.0, 13.0, 8.0, 6.0, 14.0, 11.0, 13.0, 13.0, 10.0,
11.0, 12.0, 11.0, 16.0, 11.0, 9.0, 23.0, 12.0, 10.0,
19.0, 11.0, 10.0, 19.0, 14.0, 5.0, 10.0, 11.0, 14.0,
15.0, 11.0, 11.0, 8.0, 6.0, 4.0, 6.0, 7.0, 6.0, 5.0,
7.0, 9.0, 7.0, 10.0, 7.0, 8.0, 10.0, 4.0, 7.0, 10.0,
6.0, 7.0, 7.0, 14.0, 11.0, 18.0, 14.0, 13.0, 22.0, 17.0,
16.0, 12.0, 11.0, 20.0, 16.0, 16.0, 15.0, 18.0, 16.0,
20.0, 22.0, 14.0, 19.0, 21.0, 19.0, 17.0, 15.0, 22.0,
16.0, 22.0, 22.0, 18.0, 21.0],
'fname': 'output\\box(WORDS).png',
'maintitle': 'WORDS',
'val': 'WORDS'}
df=DataFrame()
df.TESTMODE=True
df.read_tbl('data/words~ageXcondition.csv')
D=df.box_plot('WORDS', output_dir='output')
self.assertEqual(D['fname'],R['fname'])
self.assertEqual(D['maintitle'],R['maintitle'])
self.assertEqual(D['val'],R['val'])
for d,r in zip(np.array(D['d']).flat,
np.array(R['d']).flat):
self.assertAlmostEqual(d,r)
def pivotTableBoxplot(filename,uid,factors):
df = DataFrame()
df.read_tbl(os.path.join(app.config['DATA_FOLDER'], filename))
df.box_plot('data',factors)
origoutputfn = "box(data~"+factors[0]
for i in range(1,len(factors)):
origoutputfn+=("_X_"+factors[i])
origoutputfn+=").png"
outputfn = 'box_plot'
for i in range(0,len(factors)):
outputfn+='_'+factors[i]
outputfn+='.png'
# TODO: check if file exists
# Need to move/rename because output automatically goes to the base directory
os.rename(os.path.join(app.config['BASEDIR'], origoutputfn), os.path.join(app.config['DATA_FOLDER'], outputfn))
return outputfn
def test2(self):
R = {
'd': [
np.array([11, 13, 8, 6, 14, 11, 13, 13, 10, 11]),
np.array([9, 8, 6, 8, 10, 4, 6, 5, 7, 7]),
np.array([12, 11, 16, 11, 9, 23, 12, 10, 19, 11]),
np.array([10, 19, 14, 5, 10, 11, 14, 15, 11, 11]),
np.array([7, 9, 6, 6, 6, 11, 6, 3, 8, 7]),
np.array([14, 11, 18, 14, 13, 22, 17, 16, 12, 11]),
np.array([8, 6, 4, 6, 7, 6, 5, 7, 9, 7]),
np.array([20, 16, 16, 15, 18, 16, 20, 22, 14, 19]),
np.array([21, 19, 17, 15, 22, 16, 22, 22, 18, 21]),
np.array([10, 7, 8, 10, 4, 7, 10, 6, 7, 7])
],
'fname':
'output\\box(WORDS~AGE_X_CONDITION).png',
'maintitle':
'WORDS by AGE * CONDITION',
'xlabels': [
'AGE = old\nCONDITION = adjective',
'AGE = old\nCONDITION = counting',
'AGE = old\nCONDITION = imagery',
'AGE = old\nCONDITION = intention',
'AGE = old\nCONDITION = rhyming',
'AGE = young\nCONDITION = adjective',
'AGE = young\nCONDITION = counting',
'AGE = young\nCONDITION = imagery',
'AGE = young\nCONDITION = intention',
'AGE = young\nCONDITION = rhyming'
]
}
df = DataFrame()
df.TESTMODE = True
df.read_tbl('data/words~ageXcondition.csv')
D = df.box_plot('WORDS', ['AGE', 'CONDITION'], output_dir='output')
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['xlabels'], R['xlabels'])
for d, r in zip(np.array(D['d']).flat, np.array(R['d']).flat):
self.assertAlmostEqual(d, r)
def test2(self):
R = {'d': [np.array([11, 13, 8, 6, 14, 11, 13, 13, 10, 11]),
np.array([ 9, 8, 6, 8, 10, 4, 6, 5, 7, 7]),
np.array([12, 11, 16, 11, 9, 23, 12, 10, 19, 11]),
np.array([10, 19, 14, 5, 10, 11, 14, 15, 11, 11]),
np.array([ 7, 9, 6, 6, 6, 11, 6, 3, 8, 7]),
np.array([14, 11, 18, 14, 13, 22, 17, 16, 12, 11]),
np.array([8, 6, 4, 6, 7, 6, 5, 7, 9, 7]),
np.array([20, 16, 16, 15, 18, 16, 20, 22, 14, 19]),
np.array([21, 19, 17, 15, 22, 16, 22, 22, 18, 21]),
np.array([10, 7, 8, 10, 4, 7, 10, 6, 7, 7])],
'fname': 'output\\box(WORDS~AGE_X_CONDITION).png',
'maintitle': 'WORDS by AGE * CONDITION',
'xlabels': [u'AGE = old\nCONDITION = adjective',
u'AGE = old\nCONDITION = counting',
u'AGE = old\nCONDITION = imagery',
u'AGE = old\nCONDITION = intention',
u'AGE = old\nCONDITION = rhyming',
u'AGE = young\nCONDITION = adjective',
u'AGE = young\nCONDITION = counting',
u'AGE = young\nCONDITION = imagery',
u'AGE = young\nCONDITION = intention',
u'AGE = young\nCONDITION = rhyming']}
df=DataFrame()
df.TESTMODE=True
df.read_tbl('data/words~ageXcondition.csv')
D=df.box_plot('WORDS',['AGE','CONDITION'], output_dir='output')
self.assertEqual(D['fname'],R['fname'])
self.assertEqual(D['maintitle'],R['maintitle'])
self.assertEqual(D['xlabels'],R['xlabels'])
for d,r in zip(np.array(D['d']).flat,
np.array(R['d']).flat):
self.assertAlmostEqual(d,r)
