def test_x1_surrounds_x2_with_constant_distribution(self):
"""
x1 domain surrounds x2
"""
# old size
m = 20
# new size
n = 30
# bin edges
x_old = np.linspace(0., 1., m + 1)
x_new = np.linspace(0.05, 0.26, n + 1)
# constant spline
mms_spline = BoundedUnivariateSpline([0, .1, .2, 1],
[1, 1, 1, 1], s=0.)
y_old = np.array([mms_spline.integral(x_old[i],
x_old[i + 1])
for i in range(m)])
y_new_mms = np.array([mms_spline.integral(x_new[i],
x_new[i + 1])
for i in range(n)])
# rebin
y_new = rebin.rebin(x_old, y_old, x_new, interp_kind=3)
assert_allclose(y_new, y_new_mms)
def test_x2_right_overlap_x1_with_constant_distribution(self):
"""
x2 domain overlaps x1 domain from the right
"""
# old size
m = 20
# new size
n = 30
# bin edges
x_old = np.linspace(0., 1., m + 1)
x_new = np.linspace(0.95, 1.05, n + 1)
# constant spline
mms_spline = BoundedUnivariateSpline([0, .1, .2, 1],
[1, 1, 1, 1], s=0.)
y_old = np.array([mms_spline.integral(x_old[i],
x_old[i + 1])
for i in range(m)])
y_new_mms = np.array([mms_spline.integral(x_new[i],
x_new[i + 1])
for i in range(n)])
# rebin
y_new = rebin.rebin(x_old, y_old, x_new, interp_kind=3)
assert_allclose(y_new, y_new_mms, rtol=1e-6, atol=1e-4)
