Private function for rank 1 arrays. Compute quantile ignoring NaNs. See nanpercentile for parameter usage
(
arr1d, q, overwrite_input=False, method="linear", weights=None,
weak_q=False,
)
| 1660 | |
| 1661 | |
| 1662 | def _nanquantile_1d( |
| 1663 | arr1d, q, overwrite_input=False, method="linear", weights=None, |
| 1664 | weak_q=False, |
| 1665 | ): |
| 1666 | """ |
| 1667 | Private function for rank 1 arrays. Compute quantile ignoring NaNs. |
| 1668 | See nanpercentile for parameter usage |
| 1669 | """ |
| 1670 | # TODO: What to do when arr1d = [1, np.nan] and weights = [0, 1]? |
| 1671 | arr1d, weights, overwrite_input = _remove_nan_1d(arr1d, |
| 1672 | second_arr1d=weights, overwrite_input=overwrite_input) |
| 1673 | if arr1d.size == 0: |
| 1674 | # convert to scalar |
| 1675 | return np.full(q.shape, np.nan, dtype=arr1d.dtype)[()] |
| 1676 | |
| 1677 | return fnb._quantile_unchecked( |
| 1678 | arr1d, |
| 1679 | q, |
| 1680 | overwrite_input=overwrite_input, |
| 1681 | method=method, |
| 1682 | weights=weights, |
| 1683 | weak_q=weak_q, |
| 1684 | ) |
| 1685 | |
| 1686 | |
| 1687 | def _nanvar_dispatcher(a, axis=None, dtype=None, out=None, ddof=None, |
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