def test_transformer_with_multiple_expression(self):
test_df = pd.DataFrame(
{
'code': [1, 2, 3, 4, 1, 2, 3],
'b': [4, 5, 6, 7, 6, 5, 4],
'c': [9, 8, 7, 6, 5, 4, 3]
},
index=[1, 1, 1, 1, 2, 2, 2],
dtype=float)
expression1 = SecurityMovingMax(20, 'b')
expression2 = SecurityMovingMin(20, 'c')
expression3 = SecurityMovingMax(20, 'b') + SecurityMovingMin(20, 'c')
calculated = transform(test_df,
[expression1, expression2, expression3],
cols=['factor1', 'factor2', 'factor3'],
category_field='code')
expected = [13., 13., 13., 13., 11., 9, 9.]
np.testing.assert_array_almost_equal(calculated['factor3'], expected)
np.testing.assert_array_almost_equal(
calculated['factor1'] + calculated['factor2'],
calculated['factor3'])
def test_transformer_without_category_name(self):
test_df = pd.DataFrame({'b': [4, 5, 6, 7, 6, 5, 4],
'c': [9, 8, 7, 6, 5, 4, 3]},
index=[1, 2, 3, 4, 5, 6, 7],
dtype=float)
expression = SecurityMovingMax(20, 'b') + SecurityMovingMinimum(20, 'c')
calculated = transform(test_df, [expression], cols=['user_factor'])
expected = [13., 13., 13., 13., 12., 11., 10.]
np.testing.assert_array_almost_equal(calculated['user_factor'], expected)
def test_transformer_with_category_group_totally_different(self):
test_df = pd.DataFrame({'code': [1, 2, 3, 4, 5, 6, 7],
'b': [4, 5, 6, 7, 6, 5, 4],
'c': [9, 8, 7, 6, 5, 4, 3]},
index=[1, 1, 1, 1, 2, 2, 2],
dtype=float)
expression = SecurityMovingAverage(2, 'b')
calculated = transform(test_df,
[expression],
cols=['ma'],
category_field='code')
expected = [4., 5., 6., 7., 6., 5., 4.]
np.testing.assert_array_almost_equal(calculated['ma'], expected)
def test_transformer_with_category_for_comparing():
test_df = pd.DataFrame(
{
'code': [1, 2, 3, 4, 1, 2, 3],
'b': [4, 5, 6, 7, 6, 5, 4],
'c': [9, 8, 7, 6, 5, 4, 3]
},
index=[1, 1, 1, 1, 2, 2, 2],
dtype=float)
value_holder = SecurityLatestValueHolder('b') > 4.
calculated = transform(test_df, [value_holder],
cols=['filter'],
category_field='code')
expected = [0., 1., 1., 1., 1., 1., 0.]
np.testing.assert_array_almost_equal(expected, calculated['filter'])
def test_transformer_with_category_value(self):
test_df = pd.DataFrame({'code': [1, 2, 3, 4, 1, 2, 3],
'b': [4, 5, 6, 7, 6, 5, 4],
'c': [9, 8, 7, 6, 5, 4, 3]},
index=[1, 1, 1, 1, 2, 2, 2],
dtype=float)
value_holder = SecurityLatestValueHolder('b')
filter = SecurityLatestValueHolder('b') >= 5
filtered_value_holder = value_holder[filter]
calculated = transform(test_df,
[filtered_value_holder],
cols=['filtered_b'],
category_field='code')
self.assertTrue(np.all(calculated['filtered_b'] >= 5))
expected = test_df[test_df.b >= 5]
np.testing.assert_array_almost_equal(expected.b, calculated['filtered_b'])
np.testing.assert_array_equal(expected.code, calculated['code'])