Ejemplo n.º 1
0
def _sample(arr, level, axis, mode):
    arr = dtype.as_float32(arr.copy())
    dx, dy, dz = arr.shape
    # Determine the new size, dim, of the down-/up-sampled dimension
    if mode == 0:
        dim = int(arr.shape[axis] / np.power(2, level))
    if mode == 1:
        dim = int(arr.shape[axis] * np.power(2, level))

    out = _init_out(arr, axis, dim)
    return extern.c_sample(mode, arr, dx, dy, dz, level, axis, out)
Ejemplo n.º 2
0
def _sample(arr, level, axis, mode):
    arr = dtype.as_float32(arr)
    dx, dy, dz = arr.shape

    if mode == 0:
        dim = arr.shape[axis] / np.power(2, level)
    if mode == 1:
        dim = arr.shape[axis] * np.power(2, level)

    out = _init_out(arr, axis, dim)
    return extern.c_sample(mode, arr, dx, dy, dz, level, axis, out)
Ejemplo n.º 3
0
def _sample(arr, level, axis, mode):
    arr = dtype.as_float32(arr)
    dx, dy, dz = arr.shape

    if mode == 0:
        dim = arr.shape[axis] / np.power(2, level)
    if mode == 1:
        dim = arr.shape[axis] * np.power(2, level)

    out = _init_out(arr, axis, dim)
    return extern.c_sample(mode, arr, dx, dy, dz, level, axis, out)
Ejemplo n.º 4
0
def _sample(arr, level, axis, mode):
    arr = dtype.as_float32(arr.copy())
    dx, dy, dz = arr.shape
    # Determine the new size, dim, of the down-/up-sampled dimension
    if mode == 0:
        dim = int(arr.shape[axis] / np.power(2, level))
    if mode == 1:
        dim = int(arr.shape[axis] * np.power(2, level))

    out = _init_out(arr, axis, dim)
    return extern.c_sample(mode, arr, dx, dy, dz, level, axis, out)