def test_calc_total_error():
stat = numpy.array([1, 2])
sys = numpy.array([3, 4])
assert utils.calc_total_error(None, None) is None
assert (utils.calc_total_error(stat, None) == stat).all()
assert (utils.calc_total_error(None, sys) == sys).all()
# Unlike the above tests, only look for equivalence within
# a tolerance, since the numbers are manipulated rather than
# copied in this case (although the equation should be the same
# so the old approach of using equality should actually be okay
# here).
ans = numpy.sqrt(stat * stat + sys * sys)
assert utils.calc_total_error(stat, sys) == pytest.approx(ans)
def test_calc_total_error(self):
stat = numpy.array([1, 2])
sys = numpy.array([3, 4])
self.assertEqual(utils.calc_total_error(None, None), None)
assert_equal(utils.calc_total_error(stat, None), stat)
assert_equal(utils.calc_total_error(None, sys), sys)
# Unlike the above tests, only look for equivalence within
# a tolerance, since the numbers are manipulated rather than
# copied in this case (although the equation should be the same
# so the old approach of using equality should actually be okay
# here).
ans = numpy.sqrt(stat * stat + sys * sys)
assert_allclose(utils.calc_total_error(stat, sys), ans)
def get_error(self, filter=False, staterrfunc=None):
"""Return the total error on the dependent variable.
Parameters
----------
filter : bool, optional
Should the filter attached to the data set be applied to
the return value or not. The default is `False`.
staterrfunc : function
If no statistical error has been set, the errors will
be calculated by applying this function to the
dependent axis of the data set.
Returns
-------
axis : array or `None`
The error for each data point, formed by adding the
statistical and systematic errors in quadrature.
See Also
--------
get_dep : Return the independent axis of a data set.
get_staterror : Return the statistical errors on the dependent axis of a data set.
get_syserror : Return the systematic errors on the dependent axis of a data set.
"""
return calc_total_error(self.get_staterror(filter, staterrfunc),
self.get_syserror(filter))
def get_error(self, filter=False, staterrfunc=None):
"""Return the total error on the dependent variable.
Parameters
----------
filter : bool, optional
Should the filter attached to the data set be applied to
the return value or not. The default is `False`.
staterrfunc : function
If no statistical error has been set, the errors will
be calculated by applying this function to the
dependent axis of the data set.
Returns
-------
axis : array or `None`
The error for each data point, formed by adding the
statistical and systematic errors in quadrature.
See Also
--------
get_dep : Return the independent axis of a data set.
get_staterror : Return the statistical errors on the dependent axis of a data set.
get_syserror : Return the systematic errors on the dependent axis of a data set.
"""
return calc_total_error(self.get_staterror(filter, staterrfunc),
self.get_syserror(filter))
def get_error(self, filter=False, staterrfunc=None):
"Return total error in dependent variable"
return calc_total_error(self.get_staterror(filter, staterrfunc),
self.get_syserror(filter))
