def test2(self):
R = {
'aggregate':
'ci',
'clevels': [1],
'fname':
r'output/interaction_plot(SUPPRESSION~CYCLE_X_AGE_X_PHASE,yerr=95% ci).png',
'maintitle':
'SUPPRESSION by CYCLE * AGE * PHASE',
'numcols':
1,
'numrows':
2,
'rlevels': ['I', 'II'],
'subplot_titles': ['I', 'II'],
'xmaxs': [4.1749999999999998, 4.1749999999999998],
'xmins': [0.32499999999999996, 0.32499999999999996],
'y': [[[17.33333333, 22.41666667, 22.29166667, 20.75],
[7.34166667, 9.65, 9.70833333, 9.10833333]],
[[26.625, 38.70833333, 39.08333333, 40.83333333],
[10.24166667, 12.575, 13.19166667, 12.79166667]]],
'yerr': [[1.81325589, 1.44901936, 1.60883063, 1.57118871],
[2.49411239, 1.34873573, 1.95209851, 1.35412572]],
'ymax':
64.8719707118471,
'ymin':
0.0
}
# generate yerr
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/suppression~subjectXgroupXageXcycleXphase.csv')
D = df.interaction_plot('SUPPRESSION',
'CYCLE',
seplines='AGE',
sepyplots='PHASE',
yerr='ci',
output_dir='output')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
for d, r in zip(np.array(D['yerr']).flat, np.array(R['yerr']).flat):
self.assertAlmostEqual(d, r)
def test1(self):
R = {
'aggregate':
None,
'clevels': ['M1', 'M2', 'M3'],
'fname':
r'output/interaction_plot(ERROR~TIMEOFDAY_X_COURSE_X_MODEL,yerr=1.0).png',
'maintitle':
'ERROR by TIMEOFDAY * COURSE * MODEL',
'numcols':
3,
'numrows':
1,
'rlevels': [1],
'subplot_titles': ['M1', 'M2', 'M3'],
'xmaxs': [1.5, 1.5, 1.5],
'xmins': [-0.5, -0.5, -0.5],
'y': [[[9., 4.33333333], [8.66666667, 3.66666667],
[4.66666667, 1.66666667]],
[[7.5, 2.66666667], [6., 2.66666667], [5., 1.66666667]],
[[5., 2.66666667], [3.5, 2.33333333],
[2.33333333, 1.33333333]]],
'yerr': [[1.0, 1.0], [1.0, 1.0], [1.0, 1.0]],
'ymax':
11.119188627248182,
'ymin':
0.0
}
# specify yerr
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/error~subjectXtimeofdayXcourseXmodel_MISSING.csv')
D = df.interaction_plot('ERROR',
'TIMEOFDAY',
seplines='COURSE',
sepxplots='MODEL',
yerr=1.,
output_dir='output')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
for d, r in zip(np.array(D['yerr']).flat, np.array(R['yerr']).flat):
self.assertAlmostEqual(d, r)
def test01(self):
"""confidence interval error bars specified"""
R = {
'aggregate':
'ci',
'clevels': [1],
'fname':
r'output/interaction_plot(WORDS~AGE_X_CONDITION,yerr=95% ci).png',
'maintitle':
'WORDS by AGE * CONDITION',
'numcols':
1,
'numrows':
1,
'rlevels': [1],
'subplot_titles': [''],
'xmaxs': [1.5],
'xmins': [-0.5],
'y': [[[11.0, 14.8], [7.0, 6.5], [13.4, 17.6], [12.0, 19.3],
[6.9, 7.6]]],
'yerr': [[]],
'ymin':
0.0,
'ymax':
27.183257964740832
}
# a simple plot
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/words~ageXcondition.csv')
D = df.interaction_plot('WORDS',
'AGE',
seplines='CONDITION',
output_dir='output',
yerr='ci')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
for d, r in zip(np.array(D['yerr']).flat, np.array(R['yerr']).flat):
self.assertAlmostEqual(d, r)
def test6(self):
R = {
'aggregate':
'ci',
'clevels': [1],
'fname':
r'output/interaction_plot(SUPPRESSION~CYCLE_X_PHASE,yerr=95% ci).png',
'maintitle':
'SUPPRESSION by CYCLE * PHASE',
'numcols':
1,
'numrows':
2,
'rlevels': ['I', 'II'],
'subplot_titles': ['I', 'II'],
'xmaxs': [4.1749999999999998, 4.1749999999999998],
'xmins': [0.82499999999999996, 0.82499999999999996],
'y': [[12.3375, 16.03333333, 16., 14.92916667],
[18.43333333, 25.64166667, 26.1375, 26.8125]],
'yerr': [[3.18994762, 3.20528834, 3.26882751, 3.53477953],
[3.98429064, 4.5950803, 4.9514978, 4.97429769]],
'ymax':
64.8719707118471,
'ymin':
0.0
}
# generate yerr
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/suppression~subjectXgroupXageXcycleXphase.csv')
D = df.interaction_plot('SUPPRESSION',
'CYCLE',
sepyplots='PHASE',
yerr='ci',
output_dir='output')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
for d, r in zip(np.array(D['yerr']).flat, np.array(R['yerr']).flat):
self.assertAlmostEqual(d, r)
def test4(self):
R = {
'aggregate':
None,
'clevels':
['adjective', 'counting', 'imagery', 'intention', 'rhyming'],
'fname':
r'output/interaction_plot(WORDS~AGE_X_CONDITION).png',
'maintitle':
'WORDS by AGE * CONDITION',
'numcols':
5,
'numrows':
1,
'rlevels': [1],
'subplot_titles':
['adjective', 'counting', 'imagery', 'intention', 'rhyming'],
'xmaxs': [1.5, 1.5, 1.5, 1.5, 1.5],
'xmins': [-0.5, -0.5, -0.5, -0.5, -0.5],
'y': [[11., 14.8], [7., 6.5], [13.4, 17.6], [12., 19.3],
[6.9, 7.6]],
'yerr': [[], [], [], [], []],
'ymax':
27.183257964740832,
'ymin':
0.0
}
# a simple plot
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/words~ageXcondition.csv')
D = df.interaction_plot('WORDS',
'AGE',
sepxplots='CONDITION',
output_dir='output')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
for d, r in zip(np.array(D['yerr']).flat, np.array(R['yerr']).flat):
self.assertAlmostEqual(d, r)
def test31(self):
# separate y plots and separate x plots
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/suppression~subjectXgroupXageXcycleXphase.csv')
D = df.interaction_plot('SUPPRESSION',
'CYCLE',
seplines='AGE',
sepxplots='GROUP',
sepyplots='PHASE',
yerr='sem',
output_dir='output')
def test7(self):
R = {
'aggregate':
'ci',
'clevels': ['I', 'II'],
'fname':
r'output/interaction_plot(SUPPRESSION~CYCLE_X_PHASE_X_GROUP,yerr=95% ci).png',
'maintitle':
'SUPPRESSION by CYCLE * PHASE * GROUP',
'numcols':
2,
'numrows':
2,
'rlevels': ['AA', 'AB'],
'subplot_titles': [
'GROUP = AA, PHASE = AA', 'GROUP = AA, PHASE = AA',
'GROUP = AB, PHASE = AB', 'GROUP = AB, PHASE = AB'
],
'xmaxs': [
4.1500000000000004, 4.1500000000000004, 4.1500000000000004,
4.1500000000000004
],
'xmins': [
0.84999999999999998, 0.84999999999999998, 0.84999999999999998,
0.84999999999999998
],
'y': [[13.2125, 16.3, 16.8125, 15.0875],
[14.5875, 19.1875, 15.1375, 17.675],
[9.075, 16.1625, 14.5625, 11.6875],
[15.7125, 27.1125, 30.3, 32.3]],
'yerr': [[6.41377058, 4.90274323, 6.52638491, 4.723284],
[7.98351964, 7.01554694, 5.50066923, 4.7712851],
[4.06006718, 6.15225848, 4.21669129, 6.23708923],
[4.55687267, 7.52964629, 8.43210133, 10.3156968]],
'ymax':
64.8719707118471,
'ymin':
0.0
}
# separate y plots and separate x plots
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/suppression~subjectXgroupXageXcycleXphase.csv')
D = df.interaction_plot('SUPPRESSION',
'CYCLE',
sepxplots='PHASE',
sepyplots='GROUP',
yerr='ci',
where=[('GROUP', 'not in', ['LAB'])],
output_dir='output')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
for d, r in zip(np.array(D['yerr']).flat, np.array(R['yerr']).flat):
self.assertAlmostEqual(d, r)
def test3(self):
R = {
'aggregate':
'ci',
'clevels': ['I', 'II'],
'fname':
r'output/whereGROUPnotLAB.png',
'maintitle':
'SUPPRESSION by CYCLE * AGE * PHASE * GROUP',
'numcols':
2,
'numrows':
2,
'rlevels': ['AA', 'AB'],
'subplot_titles': [
'GROUP = AA, PHASE = AA', 'GROUP = AA, PHASE = AA',
'GROUP = AB, PHASE = AB', 'GROUP = AB, PHASE = AB'
],
'xmaxs': [
4.1500000000000004, 4.1500000000000004, 4.1500000000000004,
4.1500000000000004
],
'xmins': [
0.84999999999999998, 0.84999999999999998, 0.84999999999999998,
0.84999999999999998
],
'y':
[[[17.75, 22.375, 23.125, 20.25], [8.675, 10.225, 10.5, 9.925]],
[[20.875, 28.125, 20.75, 24.25], [8.3, 10.25, 9.525, 11.1]],
[[12.625, 23.5, 20., 15.625], [5.525, 8.825, 9.125, 7.75]],
[[22.75, 41.125, 46.125, 51.75], [8.675, 13.1, 14.475, 12.85]]],
'ymax':
64.8719707118471,
'ymin':
0.0
}
# separate y plots and separate x plots
df = DataFrame()
df.TESTMODE = True
df.read_tbl(r'data/suppression~subjectXgroupXageXcycleXphase.csv')
D = df.interaction_plot('SUPPRESSION',
'CYCLE',
seplines='AGE',
sepxplots='PHASE',
sepyplots='GROUP',
yerr='ci',
where=[('GROUP', 'not in', ['LAB'])],
fname='whereGROUPnotLAB.png',
output_dir='output')
self.assertEqual(D['aggregate'], R['aggregate'])
self.assertEqual(D['clevels'], R['clevels'])
self.assertEqual(D['rlevels'], R['rlevels'])
self.assertEqual(D['numcols'], R['numcols'])
self.assertEqual(D['numrows'], R['numrows'])
self.assertEqual(D['fname'], R['fname'])
self.assertEqual(D['maintitle'], R['maintitle'])
self.assertEqual(D['subplot_titles'], R['subplot_titles'])
self.assertAlmostEqual(D['ymin'], R['ymin'])
self.assertAlmostEqual(D['ymax'], R['ymax'])
for d, r in zip(np.array(D['y']).flat, np.array(R['y']).flat):
self.assertAlmostEqual(d, r)
