def summary(self, output: str = 'summary', digits: int = 2) -> str:
"""
Builds and prints the summary report.
Args
----
output: str
Can be either "summary" or "report". The first is a simpler output just
informing general metrics such as expected absolute or relative effect.
digits: int
Defines the number of digits after the decimal point to round. For
`digits=2`, value 1.566 becomes 1.57.
Returns
-------
summary: str
Contains results of the causal impact analysis.
Raises
------
ValueError: If input `output` is not either 'summary' or 'report'.
If input `digits` is not of type integer.
"""
if not isinstance(digits, int):
raise ValueError(
f'Input value for digits must be integer. Received "{type(digits)}" '
'instead.')
result = summarizer.summary(self.summary_data, self.p_value,
self.alpha, output, digits)
return result
def test_output_summary_1(summary_data, fix_path):
alpha = 0.1
p_value = 0.459329
result = summarizer.summary(summary_data, p_value, alpha=alpha)
expected = open(os.path.join(fix_path,
'test_output_summary_1')).read().strip()
assert result == expected
def test_output_summary_single_digit(summary_data, fix_path):
summarizer.summary_data = summary_data
alpha = 0.1
p_value = 0.459329
result = summarizer.summary(summary_data, p_value, alpha, digits=1)
expected = open(os.path.join(
fix_path, 'test_output_summary_single_digit')).read().strip()
assert result == expected
def test_report_summary_1(summary_data, fix_path):
# detected positive signal but with no significance.
alpha = 0.1
p_value = 0.5
summary_data['average']['rel_effect'] = 0.41
summary_data['average']['rel_effect_lower'] = -0.30
summary_data['average']['rel_effect_upper'] = 0.30
result = summarizer.summary(summary_data,
p_value,
alpha=alpha,
output='report')
expected = open(os.path.join(fix_path,
'test_report_summary_1')).read().strip()
assert result == expected
def test_report_summary_4(summary_data, fix_path):
# detected negative signal with significance.
summary_data['average']['rel_effect'] = -0.343
summary_data['average']['rel_effect_lower'] = -0.434
summary_data['average']['rel_effect_upper'] = -0.234
alpha = 0.1
p_value = 0.05
result = summarizer.summary(summary_data,
p_value,
alpha=alpha,
output='report')
expected = open(os.path.join(fix_path,
'test_report_summary_4')).read().strip()
assert result == expected
def test_summary_raises(summary_data):
with pytest.raises(ValueError):
summarizer.summary(summary_data, 0.1, output='test')