def test_valuewithsamples_equality() -> None:
value = ValueWithSamples(1, np.array([1, 2, 3]))
isequal = ValueWithSamples(1, np.array([1, 2, 3]))
isnotequal_1 = ValueWithSamples(2, np.array([1, 2, 3]))
isnotequal_2 = ValueWithSamples(1, np.array([2, 2, 3]))
isnotequal_3 = ValueWithSamples(2, np.array([2, 2, 3]))
assert value == isequal
assert value != isnotequal_1
assert value != isnotequal_2
assert value != isnotequal_3
def std(self) -> ValueWithSamples[float]:
"""
Compute the standard deviation.
Returns
-------
ValueWithSamples
the (weighted) standard deviation of the (weighted) fill values and
bootstrap resamples.
"""
variance = self.variance()
return ValueWithSamples(np.sqrt(variance.nominal),
np.sqrt(variance.samples))
def mean(self) -> ValueWithSamples[float]:
"""
Compute the mean.
Returns
-------
ValueWithSamples
the (weighted) mean of the (weighted) fill values and bootstrap resamples.
"""
nominal = float(
_mean(sumwt=self._sum_wt.nominal.view(),
sumw=self._sum_w.nominal.view()))
samples = _mean(sumwt=self._sum_wt.samples.view(),
sumw=self._sum_w.samples.view())
return ValueWithSamples(nominal, samples.flatten())
def variance(self) -> ValueWithSamples[float]:
"""
Compute the variance.
Returns
-------
ValueWithSamples
the (weighted) variance of the (weighted) fill values and bootstrap
resamples.
"""
nominal = float(
_variance(
sumw=self._sum_w.nominal.view(),
sumwt=self._sum_wt.nominal.view(),
sumwt2=self._sum_wt2.nominal.view(),
))
samples = _variance(
sumw=self._sum_w.samples.view(),
sumwt=self._sum_wt.samples.view(),
sumwt2=self._sum_wt2.samples.view(),
)
return ValueWithSamples(nominal, samples.flatten())
def skewness(self) -> ValueWithSamples[float]:
"""
Compute the skewness.
Returns
-------
ValueWithSamples
the (weighted) skewness of the (weighted) fill values and bootstrap
resamples.
"""
nominal = float(
_skewness(
sumw=self._sum_w.nominal.view(),
sumwt=self._sum_wt.nominal.view(),
sumwt2=self._sum_wt2.nominal.view(),
sumwt3=self._sum_wt3.nominal.view(),
))
samples = _skewness(
sumw=self._sum_w.samples.view(),
sumwt=self._sum_wt.samples.view(),
sumwt2=self._sum_wt2.samples.view(),
sumwt3=self._sum_wt3.samples.view(),
)
return ValueWithSamples(nominal, samples.flatten())
def test_valuewithsamples_addition() -> None:
lhs = ValueWithSamples(1, np.array([1, 2, 3]))
rhs = ValueWithSamples(2, np.array([4, 5, 6]))
total = lhs + rhs
assert total.nominal == 3
assert np.array_equal(total.samples, [5, 7, 9])
def test_valuewithsamples_division() -> None:
lhs = ValueWithSamples(4, np.array([4, 9, 16]))
rhs = ValueWithSamples(2, np.array([2, 3, 4]))
total = lhs / rhs
assert total.nominal == 2
assert np.array_equal(total.samples, [2, 3, 4])
def test_valuewithsamples_multiplication() -> None:
lhs = ValueWithSamples(2, np.array([1, 2, 3]))
rhs = ValueWithSamples(3, np.array([4, 5, 6]))
total = lhs * rhs
assert total.nominal == 6
assert np.array_equal(total.samples, [4, 10, 18])
def test_valuewithsamples_subtraction() -> None:
lhs = ValueWithSamples(1, np.array([1, 2, 3]))
rhs = ValueWithSamples(2, np.array([4, 5, 6]))
total = lhs - rhs
assert total.nominal == -1
assert np.array_equal(total.samples, [-3, -3, -3])