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)