def evaluate(self, context, symbol, start=None, end=None):
df_split = context.dependencies(source_reference)
df_normalization = pandas.DataFrame(index=dateutils.range(start, end))
for column in ['open', 'high', 'low', 'close']:
df_normalization[column] = 1
for i in range(len(df_split)):
row = df_split.ix[i]
day = dateutils.relative_working_day(-1, row.name)
df_normalization.update(df_normalization[:day] * row['factor'])
df_normalization['volume'] = 1 / df_normalization['close']
return df_normalization
def test_return_should_be_instance_of_date(self):
assert isinstance(util.relative_working_day(0), date)
def test_should_consider_last_working_day_if_weekend_date_was_given2(self):
assert util.relative_working_day(2, date(2012, 12,
15)) == date(2012, 12, 18)
def test_should_return_friday_date_if_weekend_and_0_as_arg(self):
d = date(2012, 12, 16)
assert util.relative_working_day(0, d) == util.last_working_day(d)
def test_should_use_today_if_no_argument_is_given(self):
assert util.relative_working_day(0) == util.last_working_day(
date.today())
def test_should_return_date_1_working_day_ago(self):
dt_today = date.today()
assert util.relative_working_day(-1) == util.last_working_day(
util.last_working_day(dt_today) - timedelta(1))
def test_should_return_positive_relative_day(self):
assert util.relative_working_day(20, date(2012, 12,
17)) == date(2013, 1, 14)
def test_should_return_negative_relative_day(self):
assert util.relative_working_day(-20, date(2012, 12,
17)) == date(2012, 11, 19)
