def calculate_column(dataset, dframe, formula, name):
"""
For calculating new columns.
Get necessary data given a calculation ID, execute calculation formula,
store results in dataset the calculation refers to.
"""
# parse formula into function and variables
parser = Parser()
func = parser.parse_formula(formula)
new_column = dframe.apply(func, axis=1, args=(parser, ))
new_column.name = name
return Observation.update(dframe.join(new_column), dataset)
class TestParser(TestBase):
def setUp(self):
self.parser = Parser()
self.row = {'VAR': 1}
TestBase.setUp(self)
def _check_func(self, parse_result):
func = parse_result
self.assertEqual(func.func_name, '_eval')
return parse_result
def test_parse_formula(self):
func = self._check_func(
self.parser.parse_formula('VAR'))
self.assertEqual(func(self.row, self.parser), 1)
def test_bnf(self):
result = self.parser.BNF()
print type(self.parser.bnf)
self.assertNotEqual(self.parser.bnf, None)
def test_parse_formula_with_var(self):
func = self._check_func(
self.parser.parse_formula('VAR + 1'))
self.assertEqual(func(self.row, self.parser), 2)
def test_parse_formula_bad_formula(self):
bad_formulas = [
'=BAD +++ FOR',
#'2 +>+ 1',
#'1 ** 2',
]
for bad_formula in bad_formulas:
self.assertRaises(ParseError, self.parser.parse_formula,
bad_formula)
