def test_simple_axis1(self):
a = np.arange(12).reshape(3, 4)
r = iintrp.Linear1dExtrapolator(interp1d(np.arange(4), a, axis=1))
# check non-extrapolation given the Extrapolator object
np.testing.assert_array_equal(r(0), np.array([0., 4., 8.]))
# check the result's shape in a 1d array (of len 0 & 1)
np.testing.assert_array_equal(r(np.array(0)), np.array([0., 4., 8.]))
np.testing.assert_array_equal(r(np.array([0])),
np.array([[0.], [4.], [8.]]))
# check extrapolation below the minimum value (and check the equivalent 0d & 1d arrays)
np.testing.assert_array_equal(r(-1), np.array([-1., 3., 7.]))
np.testing.assert_array_equal(r(np.array(-1)), np.array([-1., 3., 7.]))
np.testing.assert_array_equal(r(np.array([-1])),
np.array([[-1.], [3.], [7.]]))
# check extrapolation above the maximum value
np.testing.assert_array_equal(r(3), np.array([3., 7., 11.]))
np.testing.assert_array_equal(r(2.5), np.array([2.5, 6.5, 10.5]))
# 2 Non-extrapolation point
np.testing.assert_array_equal(
r(np.array([1.5, 2])), np.array([[1.5, 2.], [5.5, 6.], [9.5,
10.]]))
# 1 Non-extrapolation point & 1 upper value extrapolation
np.testing.assert_array_equal(
r(np.array([1.5, 5])), np.array([[1.5, 5.], [5.5, 9.], [9.5,
13.]]))
# 2 upper value extrapolation
np.testing.assert_array_equal(
r(np.array([4.5, 5])), np.array([[4.5, 5.], [8.5, 9.], [12.5,
13.]]))
# 1 lower value extrapolation & 1 Non-extrapolation point
np.testing.assert_array_equal(
r(np.array([-0.5, 1.5])),
np.array([[-0.5, 1.5], [3.5, 5.5], [7.5, 9.5]]))
# 2 lower value extrapolation
np.testing.assert_array_equal(
r(np.array([-1.5, -1])),
np.array([[-1.5, -1.], [2.5, 3.], [6.5, 7.]]))
# 2 lower value extrapolation, 2 Non-extrapolation point & 2 upper value extrapolation
np.testing.assert_array_equal(
r(np.array([-1.5, -1, 1.5, 2, 4.5, 5])),
np.array([[-1.5, -1., 1.5, 2., 4.5, 5.],
[2.5, 3., 5.5, 6., 8.5, 9.],
[6.5, 7., 9.5, 10., 12.5, 13.]]))
def test_variable_gradient(self):
a = np.array([[2, 4, 8], [0, 5, 11]])
r = iintrp.Linear1dExtrapolator(interp1d(np.arange(2), a, axis=0))
np.testing.assert_array_equal(r(0), np.array([ 2., 4., 8.]))
np.testing.assert_array_equal(r(-1), np.array([ 4., 3., 5.]))
np.testing.assert_array_equal(r(3), np.array([ -4., 7., 17.]))
np.testing.assert_array_equal(r(2.5), np.array([ -3., 6.5, 15.5]))
np.testing.assert_array_equal(r(np.array([1.5, 2])), np.array([[ -1., 5.5, 12.5],
[ -2., 6., 14. ]]))
np.testing.assert_array_equal(r(np.array([-1.5, 3.5])), np.array([[ 5., 2.5, 3.5],
[ -5., 7.5, 18.5]]))
def test_simple_axis0(self):
a = np.arange(12.).reshape(3, 4)
r = iintrp.Linear1dExtrapolator(interp1d(np.arange(3), a, axis=0))
np.testing.assert_array_equal(r(0), np.array([0., 1., 2., 3.]))
np.testing.assert_array_equal(r(-1), np.array([-4., -3., -2., -1.]))
np.testing.assert_array_equal(r(3), np.array([12., 13., 14., 15.]))
np.testing.assert_array_equal(r(2.5), np.array([10., 11., 12., 13.]))
# 2 Non-extrapolation point
np.testing.assert_array_equal(
r(np.array([1.5, 2])),
np.array([[6., 7., 8., 9.], [8., 9., 10., 11.]]))
# 1 Non-extrapolation point & 1 upper value extrapolation
np.testing.assert_array_equal(
r(np.array([1.5, 3])),
np.array([[6., 7., 8., 9.], [12., 13., 14., 15.]]))
# 2 upper value extrapolation
np.testing.assert_array_equal(
r(np.array([2.5, 3])),
np.array([[10., 11., 12., 13.], [12., 13., 14., 15.]]))
# 1 lower value extrapolation & 1 Non-extrapolation point
np.testing.assert_array_equal(
r(np.array([-1, 1.5])),
np.array([[-4., -3., -2., -1.], [6., 7., 8., 9.]]))
# 2 lower value extrapolation
np.testing.assert_array_equal(
r(np.array([-1.5, -1])),
np.array([[-6., -5., -4., -3.], [-4., -3., -2., -1.]]))
# 2 lower value extrapolation, 2 Non-extrapolation point & 2 upper value extrapolation
np.testing.assert_array_equal(
r(np.array([-1.5, -1, 1, 1.5, 2.5, 3])),
np.array([[-6., -5., -4., -3.], [-4., -3., -2., -1.],
[4., 5., 6., 7.], [6., 7., 8., 9.], [10., 11., 12., 13.],
[12., 13., 14., 15.]]))
def test_simple_3d_axis1(self):
a = np.arange(24.).reshape(3, 4, 2)
r = iintrp.Linear1dExtrapolator(interp1d(np.arange(4.), a, axis=1))
# a:
# [[[ 0 1]
# [ 2 3]
# [ 4 5]
# [ 6 7]]
#
# [[ 8 9]
# [10 11]
# [12 13]
# [14 15]]
#
# [[16 17]
# [18 19]
# [20 21]
# [22 23]]
# ]
np.testing.assert_array_equal(r(0), np.array([[ 0., 1.],
[ 8., 9.],
[ 16., 17.]]))
np.testing.assert_array_equal(r(1), np.array([[ 2., 3.],
[ 10., 11.],
[ 18., 19.]]))
np.testing.assert_array_equal(r(-1), np.array([[ -2., -1.],
[ 6., 7.],
[ 14., 15.]]))
np.testing.assert_array_equal(r(4), np.array([[ 8., 9.],
[ 16., 17.],
[ 24., 25.]]))
np.testing.assert_array_equal(r(0.25), np.array([[ 0.5, 1.5],
[ 8.5, 9.5],
[ 16.5, 17.5]]))
np.testing.assert_array_equal(r(-0.25), np.array([[ -0.5, 0.5],
[ 7.5, 8.5],
[ 15.5, 16.5]]))
np.testing.assert_array_equal(r(4.25), np.array([[ 8.5, 9.5],
[ 16.5, 17.5],
[ 24.5, 25.5]]))
np.testing.assert_array_equal(r(np.array([0.5, 1])), np.array([[[ 1., 2.], [ 2., 3.]],
[[ 9., 10.], [ 10., 11.]],
[[ 17., 18.], [ 18., 19.]]]))
np.testing.assert_array_equal(r(np.array([0.5, 4])), np.array([[[ 1., 2.], [ 8., 9.]],
[[ 9., 10.], [ 16., 17.]],
[[ 17., 18.], [ 24., 25.]]]))
np.testing.assert_array_equal(r(np.array([-0.5, 0.5])), np.array([[[ -1., 0.], [ 1., 2.]],
[[ 7., 8.], [ 9., 10.]],
[[ 15., 16.], [ 17., 18.]]]))
np.testing.assert_array_equal(r(np.array([-1.5, -1, 0.5, 1, 4.5, 5])),
np.array([[[ -3., -2.], [ -2., -1.], [ 1., 2.], [ 2., 3.], [ 9., 10.], [ 10., 11.]],
[[ 5., 6.], [ 6., 7.], [ 9., 10.], [ 10., 11.], [ 17., 18.], [ 18., 19.]],
[[ 13., 14.], [ 14., 15.], [ 17., 18.], [ 18., 19.], [ 25., 26.], [ 26., 27.]]]))