def test_interpolateArray():
data = np.array([[1., 2., 4.], [10., 20., 40.], [100., 200., 400.]])
x = np.array([[0.3, 0.6], [1., 1.], [0.5, 1.], [0.5, 2.5], [10., 10.]])
result = pg.interpolateArray(data, x)
#import scipy.ndimage
#spresult = scipy.ndimage.map_coordinates(data, x.T, order=1)
spresult = np.array([5.92, 20., 11., 0.,
0.]) # generated with the above line
assert_array_almost_equal(result, spresult)
# test mapping when x.shape[-1] < data.ndim
x = np.array([[0.3, 0], [0.3, 1], [0.3, 2]])
r1 = pg.interpolateArray(data, x)
r2 = pg.interpolateArray(data, x[0, :1])
assert_array_almost_equal(r1, r2)
# test mapping 2D array of locations
x = np.array([[[0.5, 0.5], [0.5, 1.0], [0.5, 1.5]],
[[1.5, 0.5], [1.5, 1.0], [1.5, 1.5]]])
r1 = pg.interpolateArray(data, x)
#r2 = scipy.ndimage.map_coordinates(data, x.transpose(2,0,1), order=1)
r2 = np.array([
[8.25, 11., 16.5], # generated with the above line
[82.5, 110., 165.]
])
assert_array_almost_equal(r1, r2)
def test_interpolateArray():
data = np.array([[ 1., 2., 4. ],
[ 10., 20., 40. ],
[ 100., 200., 400.]])
x = np.array([[ 0.3, 0.6],
[ 1. , 1. ],
[ 0.5, 1. ],
[ 0.5, 2.5],
[ 10. , 10. ]])
result = pg.interpolateArray(data, x)
#import scipy.ndimage
#spresult = scipy.ndimage.map_coordinates(data, x.T, order=1)
spresult = np.array([ 5.92, 20. , 11. , 0. , 0. ]) # generated with the above line
assert_array_almost_equal(result, spresult)
# test mapping when x.shape[-1] < data.ndim
x = np.array([[ 0.3, 0],
[ 0.3, 1],
[ 0.3, 2]])
r1 = pg.interpolateArray(data, x)
r2 = pg.interpolateArray(data, x[0,:1])
assert_array_almost_equal(r1, r2)
# test mapping 2D array of locations
x = np.array([[[0.5, 0.5], [0.5, 1.0], [0.5, 1.5]],
[[1.5, 0.5], [1.5, 1.0], [1.5, 1.5]]])
r1 = pg.interpolateArray(data, x)
#r2 = scipy.ndimage.map_coordinates(data, x.transpose(2,0,1), order=1)
r2 = np.array([[ 8.25, 11. , 16.5 ], # generated with the above line
[ 82.5 , 110. , 165. ]])
assert_array_almost_equal(r1, r2)
def interpolateArray(data, x):
result = pg.interpolateArray(data, x, order=order)
assert result.shape == x.shape[:-1] + data.shape[x.shape[-1]:]
return result
def interpolateArray(data, x):
result = pg.interpolateArray(data, x, order=order)
assert result.shape == x.shape[:-1] + data.shape[x.shape[-1]:]
return result
