def test_bad_arguments(self):
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
plot_similarity(setup_pd(), setup_np(), setup_np(), test=True)
expected_error_msg = "Similarity matrix type is not np.ndarray."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
plot_similarity(setup_np(), setup_pd(), setup_np(), test=True)
expected_error_msg = "Novelty score array type is not np.ndarray."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
def test_calculate_similarity(self):
"""
Test calculate_similarity function. The test fails when:
- Given array is not a numpy array
- Given array is not 2 dimensional
Returns
-------
None.
"""
test_argument = setup_pd()
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
calculate_similarity(test_argument)
expected_error_msg = "Data format is not a numpy array."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
test_argument2 = setup_np()
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
calculate_similarity(test_argument2)
expected_error_msg = "Matrix is not 2 dimensional."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
def test_STL_decomposition(self):
""" Test STL_decomposition function. Test passes with proper arguments
and raises an AssertionError if the input time series is not numpy
array.
Returns
-------
None.
"""
res = STL_decomposition(setup_np(), 'Test title', test=True)
assert res is not None
assert res.observed.all() is not None
assert res.trend.all() is not None
assert res.seasonal.all() is not None
assert res.resid.all() is not None
test_argument = setup_pd()
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
STL_decomposition(test_argument, 'Test title', test=True)
expected_error_msg = "Series is not a numpy array."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
def test_setup_pd(self):
"""
Test that setup_pd function returns a pandas dataframe
Returns
-------
None.
"""
test_argument = setup_pd()
assert isinstance(test_argument, pd.DataFrame)
def test_rolling_statistics(self):
"""
Test with proper arguments.
Returns
-------
None.
"""
test_argument = setup_pd()
test_argument = test_argument['level'].to_frame()
res = rolling_statistics(test_argument, w = 7, savename = False, savepath = False, test = True)
print(type(res))
assert res is not None, 'Function returned a None object.'
def test_process_decorator(self):
@process_decorator
def summary(df,name):
ser = df[name]
_ = summary_statistics.summary_statistics(ser,
"{} summary".format(name),
window = 14,
savepath = False,
savename = False,
test = False)
df = setup_pd()
cols = ['level']
summary(df,cols)
def test_doi2int(self):
"""
Test with proper arguments.
Returns
-------
None.
"""
df = setup_pd()
test_argument = (2011, 3, 1), (2011, 6, 1)
a, b = doi2index(test_argument, df)
assert a == pytest.approx(4478.12331851853)
assert b == pytest.approx(4570.12331851853)
def test_rolling_statistics_long_window(self):
"""
Given too large window size, Rolling_statistics raises an error.
Returns
-------
None.
"""
test_argument = setup_pd()
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
rolling_statistics(test_argument,w=10000000)
expected_error_msg = "Window length is larger than the time series length."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
def test_rolling_statistics_w(self):
"""
Given window size as a string, Rolling_statistics raises an error.
Returns
-------
None.
"""
test_argument = setup_pd()
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
rolling_statistics(test_argument,w=str(7))
expected_error_msg = "Window size is not an integer."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
def test_plot_decorator(self):
df = setup_pd()
name = ['level']
_ = plot_timeseries(df,
name,
title = "test title",
roll = False,
xlab = "Time",
ylab = "Value",
ylim = False,
savename = False,
savepath = False,
highlight = False,
test=True
)
def test_summary_statistics(self):
"""
Test Summary_statistics function. Test that Pandas data frame as an
argument raises an error.
Returns
-------
None.
"""
# Store information about raised ValueError in exc_info
with pytest.raises(AssertionError) as exc_info:
summary_statistics(setup_pd(),
'Test title',
savepath=False,
savename=False,
test=True)
expected_error_msg = "Series is not a pandas Series."
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
