def test_reverse_inversion_not_applied(reparam):
"""Assert the reverse inversion works correctly"""
reparam.parameters = ['x']
reparam.prime_parameters = ['x_prime']
reparam.offsets = {'x': 1.0}
reparam._edges = {'x': False}
reparam.bounds = {'x': [0, 5]}
x_val = np.array([[1], [2]])
x = numpy_array_to_live_points(x_val, ['x'])
x_prime = numpy_array_to_live_points(np.array([3, 4]), ['x_prime'])
log_j = np.zeros(2)
with patch('nessai.reparameterisations.inverse_rescale_minus_one_to_one',
side_effect=lambda x, *args, **kwargs:
(x, np.array([5, 6]))) as f:
x_out, x_prime_out, log_j_out = RescaleToBounds._reverse_inversion(
reparam,
x,
x_prime,
log_j,
'x',
'x_prime',
)
assert f.call_args_list[0][1] == {'xmin': 0, 'xmax': 5}
# Should be output of rescaling minus offset
np.testing.assert_array_equal(x_out['x'], np.array([2, 3]))
# x_prime should be the same
assert x_prime_out is x_prime
# Jacobian should just include jacobian from rescaling
np.testing.assert_array_equal(log_j_out, np.array([5, 6]))
def test_reverse_inversion(reparam):
"""Assert the reverse inversion works correctly"""
reparam.parameters = ['x']
reparam.prime_parameters = ['x_prime']
reparam.offsets = {'x': 1.0}
reparam._edges = {'x': 'upper'}
reparam.bounds = {'x': [0, 5]}
x_val = np.array([[-0.7], [0.4]])
x = numpy_array_to_live_points(x_val, ['x'])
x_prime = numpy_array_to_live_points(np.array([3, 4]), ['x_prime'])
log_j = np.zeros(2)
# Return the same value to check that the negative values are handled
# correctly
with patch('nessai.reparameterisations.inverse_rescale_zero_to_one',
side_effect=lambda x, *args: (x, np.array([5, 6]))) as f:
x_out, x_prime_out, log_j_out = RescaleToBounds._reverse_inversion(
reparam,
x,
x_prime,
log_j,
'x',
'x_prime',
)
assert f.call_args_list[0][0][1] == 0.0
assert f.call_args_list[0][0][2] == 5.0
# Should be output of rescaling minus offset
np.testing.assert_array_equal(x_out['x'], np.array([1.3, 1.6]))
# x_prime should be the same
assert x_prime_out is x_prime
# Jacobian should just include jacobian from rescaling
np.testing.assert_array_equal(log_j_out, np.array([5, 6]))