diff options
Diffstat (limited to 'numpy/ma/extras.py')
| -rw-r--r-- | numpy/ma/extras.py | 19 |
1 files changed, 11 insertions, 8 deletions
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py index a05ea476b..0d5c73e7e 100644 --- a/numpy/ma/extras.py +++ b/numpy/ma/extras.py @@ -708,34 +708,37 @@ def _median(a, axis=None, out=None, overwrite_input=False): asorted = a else: asorted = sort(a, axis=axis) + if axis is None: axis = 0 elif axis < 0: - axis += a.ndim + axis += asorted.ndim if asorted.ndim == 1: idx, odd = divmod(count(asorted), 2) - return asorted[idx - (not odd) : idx + 1].mean() + return asorted[idx + odd - 1 : idx + 1].mean(out=out) - counts = asorted.shape[axis] - (asorted.mask).sum(axis=axis) + counts = count(asorted, axis=axis) h = counts // 2 + # create indexing mesh grid for all but reduced axis axes_grid = [np.arange(x) for i, x in enumerate(asorted.shape) if i != axis] ind = np.meshgrid(*axes_grid, sparse=True, indexing='ij') + # insert indices of low and high median ind.insert(axis, h - 1) low = asorted[tuple(ind)] low._sharedmask = False ind[axis] = h high = asorted[tuple(ind)] + # duplicate high if odd number of elements so mean does nothing odd = counts % 2 == 1 - if asorted.ndim == 1: - if odd: - low = high - else: - low[odd] = high[odd] + if asorted.ndim > 1: + np.copyto(low, high, where=odd) + elif odd: + low = high if np.issubdtype(asorted.dtype, np.inexact): # avoid inf / x = masked |