def test_transform_data(self):
"""
Tests that the transform_data method gives the correct 10 by 10 matrix.
"""
data = self.close['spx'][3:103]
flags = MatrixFlagLabels(data, window=30)
test1 = flags._transform_data(row_num=32, window=30)
test2 = flags._transform_data(row_num=100, window=90)
test1_actual = pd.DataFrame(
[[0, 1. / 3, 0, 0, 1. / 3, 1. / 3, 0, 0, 0, 0],
[0, 2. / 3, 0, 0, 1. / 3, 0, 0, 0, 0, 0],
[0, 0, 1. / 3, 2. / 3, 0, 0, 0, 0, 0, 0],
[1. / 3, 0, 0, 0, 0, 1. / 3, 0, 0, 0, 0],
[1. / 3, 0, 1. / 3, 1. / 3, 1. / 3, 0, 0, 0, 0, 0],
[1. / 3, 0, 1. / 3, 0, 0, 0, 0, 0, 1. / 3, 0],
[0, 0, 0, 0, 0, 0, 0, 1. / 3, 1. / 3, 1. / 3],
[0, 0, 0, 0, 0, 0, 0, 1. / 3, 1. / 3, 1. / 3],
[0, 0, 0, 0, 0, 0, 2. / 3, 0, 0, 1. / 3],
[0, 0, 0, 0, 0, 1. / 3, 1. / 3, 1. / 3, 0, 0]])
test2_column_actual = pd.Series(
[0, 0, 0, 0, 0, 0, 0, 1. / 3, 1. / 9, 5. / 9])
pd.testing.assert_frame_equal(test1, test1_actual)
pd.testing.assert_series_equal(test2[1],
test2_column_actual,
check_names=False) # Check 1 column
# Assert that all columns sum to 1.
self.assertTrue(
test2.sum(axis=0).values.all() == np.array([1.] * 10).all())
def test_threshold(self):
"""
Tests for when threshold is desired.
"""
data = self.close['spx'][425:500]
idx = data[60:].index
flags = MatrixFlagLabels(prices=data,
window=60,
template_name='leigh_bull')
test5 = flags.apply_labeling_matrix(threshold=4)
test6 = flags.apply_labeling_matrix(threshold=-1.5)
test5_actual = pd.Series(
[-1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], index=idx)
test6_actual = pd.Series([1] * 15, index=idx)
pd.testing.assert_series_equal(test5, test5_actual)
pd.testing.assert_series_equal(test6, test6_actual)
def test_init(self):
"""
Tests that exceptions are raised correctly during initialization of the class if inputs are wrong.
"""
# Length of data less than 10.
close = self.close['spx']
with self.assertRaises(Exception):
MatrixFlagLabels(close[0:7], window=30)
# Window less than 10.
with self.assertRaises(Exception):
MatrixFlagLabels(close[0:30], window=5)
# Window greater than len(data).
with self.assertRaises(Exception):
MatrixFlagLabels(close[0:30], window=50)
# Data is a DataFrame, not Series.
with self.assertRaises(Exception):
MatrixFlagLabels(self.close, window=60)
def test_apply_labeling(self):
"""
Test for the function the users would actually use, for creating full labels from matrix.
"""
data = self.close['spx'][0:100]
flags = MatrixFlagLabels(prices=data,
window=60,
template_name='leigh_bull')
test5 = flags.apply_labeling_matrix()
# Verify that the output has 40 (100 - 60) rows.
self.assertTrue(len(test5) == 40)
# Check values.
test5_subset = test5[10:20]
test5_subset_actual = pd.Series([
-0.91666667, -1.25, -1.75, -2.16666667, -2.66666667, -2.66666667,
-2.75, -2.5, -2.58333333, -2.66666667
],
index=test5_subset.index)
pd.testing.assert_series_equal(test5_subset, test5_subset_actual)
def test_set_template(self):
"""
Tests for user setting a new template. Also verifies that exception is raised for invalid template formats.
"""
new_template = pd.DataFrame(np.random.randint(-3, 3, size=(10, 10)))
flags = MatrixFlagLabels(self.close['spx'], window=100)
flags.set_template(new_template) # Correct template
bad_shape = pd.DataFrame(np.random.randint(-3, 3,
size=(9,
10))) # Not 10 by 10
with self.assertRaises(Exception):
flags.set_template(bad_shape)
nan_template = new_template.copy()
nan_template.iloc[2, 3] = np.nan # Has NaN
with self.assertRaises(Exception):
flags.set_template(nan_template)
def test_template_init(self):
"""
Checks that other templates are given correctly.
"""
close = self.close['spx']
leigh_bull = pd.DataFrame(
[[.5, 0, -1, -1, -1, -1, -1, -1, -1, 0],
[1, 0.5, 0, -0.5, -1, -1, -1, -1, -0.5, 0],
[1, 1, 0.5, 0, -0.5, -0.5, -0.5, -0.5, 0, 0.5],
[0.5, 1, 1, 0.5, 0, -0.5, -0.5, -0.5, 0, 1],
[0, 0.5, 1, 1, 0.5, 0, 0, 0, 0.5, 1],
[0, 0, 0.5, 1, 1, 0.5, 0, 0, 1, 1],
[-0.5, 0, 0, 0.5, 1, 1, 0.5, 0.5, 1, 1],
[-0.5, -1, 0, 0, 0.5, 1, 1, 1, 1, 0],
[-1, -1, -1, -0.5, 0, 0.5, 1, 1, 0, -2],
[-1, -1, -1, -1, -1, 0, 0.5, 0.5, -2, -2.5]])
leigh_bear = pd.DataFrame(np.flip(np.array(leigh_bull), axis=0))
cervelloroyo_bull = pd.DataFrame(
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, -1, -1, -1, -1, -1, -1],
[0, 0, 0, -1, -2, -2, -2, -2, -2, -2],
[0, 0, -1, -3, -3, -3, -3, -3, -3, -3],
[0, -1, -3, -5, -5, -5, -5, -5, -5, -5],
[0, -1, -5, -5, -5, -5, -5, -5, -5, -5],
[0, -1, -5, -5, -5, -5, -5, -5, -5, -5],
[5, -1, -5, -5, -5, -5, -5, -5, -5, -5]])
cervelloroyo_bear = pd.DataFrame(
np.flip(np.array(cervelloroyo_bull), axis=0))
test7 = MatrixFlagLabels(close, 30, template_name='leigh_bear')
test8 = MatrixFlagLabels(close, 30, template_name='cervelloroyo_bear')
test9 = MatrixFlagLabels(close, 30, template_name='cervelloroyo_bull')
pd.testing.assert_frame_equal(test7.template, leigh_bear)
pd.testing.assert_frame_equal(test8.template, cervelloroyo_bear)
pd.testing.assert_frame_equal(test9.template, cervelloroyo_bull)
# Exception for invalid name.
with self.assertRaises(Exception):
MatrixFlagLabels(close[0:7], window=30, template_name='abcd')
with self.assertRaises(Exception):
test7._init_template('abcd')
def test_apply_template(self):
"""
Tests for the apply template to matrix. A matrix is used which satisfies the constraints of transform_data.
Then, the template is changed, and the applied to the same matrix.
"""
matrix = pd.DataFrame(
[[0, 1. / 3, 0, 0, 1. / 3, 1. / 3, 0, 0, 0, 0],
[0, 2. / 3, 0, 0, 1. / 3, 0, 0, 0, 0, 0],
[0, 0, 1. / 3, 2. / 3, 0, 0, 0, 0, 0, 0],
[1. / 3, 0, 0, 0, 0, 1. / 3, 0, 0, 0, 0],
[1. / 3, 0, 1. / 3, 1. / 3, 1. / 3, 0, 0, 0, 0, 0],
[1. / 3, 0, 1. / 3, 0, 0, 0, 0, 0, 1. / 3, 0],
[0, 0, 0, 0, 0, 0, 0, 1. / 3, 1. / 3, 1. / 3],
[0, 0, 0, 0, 0, 0, 0, 1. / 3, 1. / 3, 1. / 3],
[0, 0, 0, 0, 0, 0, 2. / 3, 0, 0, 1. / 3],
[0, 0, 0, 0, 0, 1. / 3, 1. / 3, 1. / 3, 0, 0]])
flags = MatrixFlagLabels(self.close['spx'],
window=100,
template_name='leigh_bull')
test3 = flags._apply_template_to_matrix(matrix, flags.template)
self.assertAlmostEqual(test3, 2.6666666667)
# Replace the template with another bull template proposed in Cervello-Royo's paper.
new_template = pd.DataFrame([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, -1, -1, -1, -1, -1, -1],
[0, 0, 0, -1, -2, -2, -2, -2, -2, -2],
[0, 0, -1, -3, -3, -3, -3, -3, -3, -3],
[0, -1, -3, -5, -5, -5, -5, -5, -5, -5],
[0, -1, -5, -5, -5, -5, -5, -5, -5, -5],
[0, -1, -5, -5, -5, -5, -5, -5, -5, -5],
[5, -1, -5, -5, -5, -5, -5, -5, -5, -5]])
flags.set_template(new_template)
test4 = flags._apply_template_to_matrix(matrix, flags.template)
self.assertAlmostEqual(test4, -22.666666667)