本文整理汇总了Python中pyvttbl.DataFrame.interaction_plot方法的典型用法代码示例。如果您正苦于以下问题：Python DataFrame.interaction_plot方法的具体用法？Python DataFrame.interaction_plot怎么用？Python DataFrame.interaction_plot使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyvttbl.DataFrame的用法示例。
在下文中一共展示了DataFrame.interaction_plot方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test3
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test3(self):
R = {'aggregate': 'ci',
'clevels': ['I', 'II'],
'fname': '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('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)示例2: test4
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test4(self):
R = {'aggregate': None,
'clevels': ['adjective',
'counting',
'imagery',
'intention',
'rhyming'],
'fname': '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('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)示例3: test1
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test1(self):
R = {'aggregate': None,
'clevels': ['M1', 'M2', 'M3'],
'fname': '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('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)示例4: test31
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test31(self):
# separate y plots and separate x plots
df=DataFrame()
df.TESTMODE = True
df.read_tbl('data\suppression~subjectXgroupXageXcycleXphase.csv')
D = df.interaction_plot('SUPPRESSION','CYCLE',
seplines='AGE',
sepxplots='GROUP',
sepyplots='PHASE',
yerr='sem',
output_dir='output')示例5: test01
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test01(self):
"""confidence interval error bars specified"""
R = {'aggregate': 'ci',
'clevels': [1],
'fname': '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('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)示例6: test2
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test2(self):
R = {'aggregate': 'ci',
'clevels': [1],
'fname': '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('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)示例7: test6
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test6(self):
R = {'aggregate': 'ci',
'clevels': [1],
'fname': '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('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)示例8: test7
# 需要导入模块: from pyvttbl import DataFrame [as 别名]
# 或者: from pyvttbl.DataFrame import interaction_plot [as 别名]
def test7(self):
R = {'aggregate': 'ci',
'clevels': ['I', 'II'],
'fname': '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('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)