aggregate_numpy.py 文件源码

def _mean(group_idx, a, size, fill_value, dtype=np.dtype(np.float64)):
    if np.ndim(a) == 0:
        raise ValueError("cannot take mean with scalar a")
    counts = np.bincount(group_idx, minlength=size)
    if np.iscomplexobj(a):
        dtype = a.dtype  # TODO: this is a bit clumsy
        sums = np.empty(size, dtype=dtype)
        sums.real = np.bincount(group_idx, weights=a.real,
                                minlength=size)
        sums.imag = np.bincount(group_idx, weights=a.imag,
                                minlength=size)
    else:
        sums = np.bincount(group_idx, weights=a,
                           minlength=size).astype(dtype)

    with np.errstate(divide='ignore'):
        ret = sums.astype(dtype) / counts
    if not np.isnan(fill_value):
        ret[counts == 0] = fill_value
    return ret