def test_regression_summary():
#little luck getting this test to pass (It should?), can be used for
#visual testing of the regression.summary table
#fixed, might fail at minute changes
from scikits.statsmodels.regression.tests.test_regression import TestOLS
#from test_regression import TestOLS
import time
from string import Template
t = time.localtime()
desired = Template(''' Summary of Regression Results
=======================================
| Dependent Variable: y|
| Model: OLS|
| Method: Least Squares|
| Date: $XXcurrentXdateXX|
| Time: $XXtimeXXX|
| # obs: 16.0|
| Df residuals: 9.0|
| Df model: 6.0|
==============================================================================
| coefficient std. error t-statistic prob. |
------------------------------------------------------------------------------
| x1 15.06 84.91 0.1774 0.8631 |
| x2 -0.03582 0.03349 -1.0695 0.3127 |
| x3 -2.020 0.4884 -4.1364 0.0025 |
| x4 -1.033 0.2143 -4.8220 0.0009 |
| x5 -0.05110 0.2261 -0.2261 0.8262 |
| x6 1829. 455.5 4.0159 0.0030 |
| const -3.482e+06 8.904e+05 -3.9108 0.0036 |
==============================================================================
| Models stats Residual stats |
------------------------------------------------------------------------------
| R-squared: 0.9955 Durbin-Watson: 2.559 |
| Adjusted R-squared: 0.9925 Omnibus: 0.7486 |
| F-statistic: 330.3 Prob(Omnibus): 0.6878 |
| Prob (F-statistic): 4.984e-10 JB: 0.6841 |
| Log likelihood: -109.6 Prob(JB): 0.7103 |
| AIC criterion: 233.2 Skew: 0.4200 |
| BIC criterion: 238.6 Kurtosis: 2.434 |
------------------------------------------------------------------------------'''
).substitute(XXcurrentXdateXX=str(
time.strftime("%a, %d %b %Y", t)),
XXtimeXXX=str(time.strftime("%H:%M:%S",
t)))
desired = str(desired)
aregression = TestOLS()
TestOLS.setupClass()
results = aregression.res1
r_summary = str(results.summary_old())
## print('###')
## print(r_summary)
## print('###')
## print(desired)
## print('###')
actual = r_summary
import numpy as np
actual = '\n'.join((line.rstrip() for line in actual.split('\n')))
# print len(actual), len(desired)
# print repr(actual)
# print repr(desired)
# counter = 0
# for c1,c2 in zip(actual, desired):
# if not c1==c2 and counter<20:
# print c1,c2
# counter += 1
np.testing.assert_(actual == desired)
'''examples to check summary, not converted to tests yet
'''
if __name__ == '__main__':
from scikits.statsmodels.regression.tests.test_regression import TestOLS
#def mytest():
aregression = TestOLS()
TestOLS.setupClass()
results = aregression.res1
r_summary = str(results.summary_old())
print r_summary
olsres = results
print '\n\n'
r_summary = str(results.summary())
print r_summary
print '\n\n'
from scikits.statsmodels.discrete.tests.test_discrete import TestProbitNewton
aregression = TestProbitNewton()
TestProbitNewton.setupClass()
results = aregression.res1
r_summary = str(results.summary())
print r_summary
print '\n\n'
'''examples to check summary, not converted to tests yet
'''
if __name__ == '__main__':
from scikits.statsmodels.regression.tests.test_regression import TestOLS
#def mytest():
aregression = TestOLS()
TestOLS.setupClass()
results = aregression.res1
r_summary = str(results.summary_old())
print r_summary
olsres = results
print '\n\n'
r_summary = str(results.summary())
print r_summary
print '\n\n'
from scikits.statsmodels.discrete.tests.test_discrete import TestProbitNewton
aregression = TestProbitNewton()
TestProbitNewton.setupClass()
results = aregression.res1
r_summary = str(results.summary())
print r_summary
def test_regression_summary():
#little luck getting this test to pass (It should?), can be used for
#visual testing of the regression.summary table
#fixed, might fail at minute changes
from scikits.statsmodels.regression.tests.test_regression import TestOLS
#from test_regression import TestOLS
import time
from string import Template
t = time.localtime()
desired = Template(
''' Summary of Regression Results
=======================================
| Dependent Variable: y|
| Model: OLS|
| Method: Least Squares|
| Date: $XXcurrentXdateXX|
| Time: $XXtimeXXX|
| # obs: 16.0|
| Df residuals: 9.0|
| Df model: 6.0|
==============================================================================
| coefficient std. error t-statistic prob. |
------------------------------------------------------------------------------
| x1 15.06 84.91 0.1774 0.8631 |
| x2 -0.03582 0.03349 -1.0695 0.3127 |
| x3 -2.020 0.4884 -4.1364 0.0025 |
| x4 -1.033 0.2143 -4.8220 0.0009 |
| x5 -0.05110 0.2261 -0.2261 0.8262 |
| x6 1829. 455.5 4.0159 0.0030 |
| const -3.482e+06 8.904e+05 -3.9108 0.0036 |
==============================================================================
| Models stats Residual stats |
------------------------------------------------------------------------------
| R-squared: 0.9955 Durbin-Watson: 2.559 |
| Adjusted R-squared: 0.9925 Omnibus: 0.7486 |
| F-statistic: 330.3 Prob(Omnibus): 0.6878 |
| Prob (F-statistic): 4.984e-10 JB: 0.6841 |
| Log likelihood: -109.6 Prob(JB): 0.7103 |
| AIC criterion: 233.2 Skew: 0.4200 |
| BIC criterion: 238.6 Kurtosis: 2.434 |
------------------------------------------------------------------------------'''
).substitute(XXcurrentXdateXX = str(time.strftime("%a, %d %b %Y",t)),
XXtimeXXX = str(time.strftime("%H:%M:%S",t)))
desired = str(desired)
aregression = TestOLS()
TestOLS.setupClass()
results = aregression.res1
r_summary = str(results.summary_old())
## print('###')
## print(r_summary)
## print('###')
## print(desired)
## print('###')
actual = r_summary
import numpy as np
actual = '\n'.join((line.rstrip() for line in actual.split('\n')))
# print len(actual), len(desired)
# print repr(actual)
# print repr(desired)
# counter = 0
# for c1,c2 in zip(actual, desired):
# if not c1==c2 and counter<20:
# print c1,c2
# counter += 1
np.testing.assert_(actual == desired)