def test_110_run_dpmean_calculation(self):
"""(110) Run another DP mean calculation"""
msgt(self.test_110_run_dpmean_calculation.__doc__)
spec_props = self.spec_props_income
dp_mean = DPMeanSpec(spec_props)
print('Is this spec valid?', dp_mean.is_chain_valid())
if dp_mean.has_error():
print(dp_mean.get_error_messages())
print(dp_mean.get_error_msg_dict())
return
self.assertTrue(dp_mean.is_chain_valid())
# ------------------------------------------------------
# Run the actual mean
# ------------------------------------------------------
# Column indexes - We know this data has 11 columns
col_indexes = [idx for idx in range(0, 11)]
# File object
#
pums_filepath = join(TEST_DATA_DIR, 'PUMS5extract10000.csv')
self.assertTrue(isfile(pums_filepath))
file_like_obj = open(pums_filepath, 'r')
# Call run_chain
#
dp_mean.run_chain(col_indexes, file_like_obj)
if dp_mean.has_error():
print(dp_mean.get_error_messages())
return
final_dict = dp_mean.get_release_dict()
json_str = json.dumps(final_dict, indent=4)
print(json_str)
print('-- actual vals --')
print(('mean: 30,943.4566' '\nmin: -10,000.0' '\nmax: 713,000.0'))
self.assertIn('description', final_dict)
self.assertIn('text', final_dict['description'])
self.assertIn('html', final_dict['description'])
def test_100_run_dpmean_calculation(self):
"""(100) Run DP mean calculation"""
msgt(self.test_100_run_dpmean_calculation.__doc__)
spec_props = self.spec_props
dp_mean = DPMeanSpec(spec_props)
self.assertTrue(dp_mean.is_chain_valid())
if dp_mean.has_error():
print(dp_mean.get_error_messages())
return
#print('\nUI info:', json.dumps(dp_mean.get_success_msg_dict()))
# ------------------------------------------------------
# Run the actual mean
# ------------------------------------------------------
# Column indexes - We know this data has 20 columns
col_indexes = [idx for idx in range(0, 20)]
# File object
#
eye_fatigue_filepath = join(TEST_DATA_DIR, 'Fatigue_data.tab')
#print('eye_fatigue_filepath', eye_fatigue_filepath)
self.assertTrue(isfile(eye_fatigue_filepath))
file_obj = open(eye_fatigue_filepath, 'r')
# Call run_chain
#
dp_mean.run_chain(col_indexes, file_obj, sep_char="\t")
final_dict = dp_mean.get_release_dict()
self.assertIn('description', final_dict)
self.assertIn('text', final_dict['description'])
self.assertIn('html', final_dict['description'])
print('Actual mean: -0.9503854412185792')