def _test_cached_dframe(self, name, original_formula, dynamic):
formula = not dynamic and self.column_labels_to_slugs[original_formula]
for idx, row in self.dframe.iterrows():
try:
result = np.float64(row[name])
places = self.places
if dynamic:
# downsample and set low precision for time comparison
stored = (parse_date_to_unix_time(self.now) -
parse_date_to_unix_time(row['submit_date'])
) / 100
result = int(result / 100)
places = 0
else:
stored = np.float64(row[formula])
# one np.nan != np.nan, continue if we have two nan values
if np.isnan(result) and np.isnan(stored):
continue
msg = self._equal_msg(result, stored, original_formula)
self.assertAlmostEqual(result, stored, places, msg)
except ValueError:
msg = self._equal_msg(row[name], row[formula], formula)
self.assertEqual(row[name], row[formula], msg)
def eval(self, row, dataset):
return parse_date_to_unix_time(now())
def eval(self, row, dataset):
return parse_date_to_unix_time(now())
