def test_all_fit_attributes_dict(lengths, _):
"""
Test describe_powerlaw_fit.
"""
fit = length_distributions.determine_fit(lengths)
result = length_distributions.all_fit_attributes_dict(fit)
assert isinstance(result, dict)
def automatic_fit(self) -> powerlaw.Fit:
"""
Get automatic powerlaw Fit.
"""
if self._automatic_fit is None:
self._automatic_fit = length_distributions.determine_fit(
self.length_array)
return self._automatic_fit
def test_describe_powerlaw_fit(lengths, label):
"""
Test describe_powerlaw_fit.
"""
fit = length_distributions.determine_fit(lengths)
result = length_distributions.describe_powerlaw_fit(fit=fit,
label=label,
length_array=lengths)
assert isinstance(result, dict)
def determine_manual_fit(self, cut_off: float) -> powerlaw.Fit:
"""
Get manually determined Fit with set cut off.
"""
return length_distributions.determine_fit(self.length_array,
cut_off=cut_off)
def test_determine_fit(length_array: np.ndarray, cut_off: float):
"""
Test determine_fit.
"""
fit = length_distributions.determine_fit(length_array, cut_off)
assert isinstance(fit, powerlaw.Fit)
