Compute the median along the specified axis. Returns the median of the array elements. Parameters ---------- a : array_like Input array or object that can be converted to an array. axis : int, optional Axis along which the medians are computed. The default
(a, axis=None, out=None, overwrite_input=False, keepdims=False)
| 676 | |
| 677 | |
| 678 | def median(a, axis=None, out=None, overwrite_input=False, keepdims=False): |
| 679 | """ |
| 680 | Compute the median along the specified axis. |
| 681 | |
| 682 | Returns the median of the array elements. |
| 683 | |
| 684 | Parameters |
| 685 | ---------- |
| 686 | a : array_like |
| 687 | Input array or object that can be converted to an array. |
| 688 | axis : int, optional |
| 689 | Axis along which the medians are computed. The default (None) is |
| 690 | to compute the median along a flattened version of the array. |
| 691 | out : ndarray, optional |
| 692 | Alternative output array in which to place the result. It must |
| 693 | have the same shape and buffer length as the expected output |
| 694 | but the type will be cast if necessary. |
| 695 | overwrite_input : bool, optional |
| 696 | If True, then allow use of memory of input array (a) for |
| 697 | calculations. The input array will be modified by the call to |
| 698 | median. This will save memory when you do not need to preserve |
| 699 | the contents of the input array. Treat the input as undefined, |
| 700 | but it will probably be fully or partially sorted. Default is |
| 701 | False. Note that, if `overwrite_input` is True, and the input |
| 702 | is not already an `ndarray`, an error will be raised. |
| 703 | keepdims : bool, optional |
| 704 | If this is set to True, the axes which are reduced are left |
| 705 | in the result as dimensions with size one. With this option, |
| 706 | the result will broadcast correctly against the input array. |
| 707 | |
| 708 | Returns |
| 709 | ------- |
| 710 | median : ndarray |
| 711 | A new array holding the result is returned unless out is |
| 712 | specified, in which case a reference to out is returned. |
| 713 | Return data-type is `float64` for integers and floats smaller than |
| 714 | `float64`, or the input data-type, otherwise. |
| 715 | |
| 716 | See Also |
| 717 | -------- |
| 718 | mean |
| 719 | |
| 720 | Notes |
| 721 | ----- |
| 722 | Given a vector ``V`` with ``N`` non masked values, the median of ``V`` |
| 723 | is the middle value of a sorted copy of ``V`` (``Vs``) - i.e. |
| 724 | ``Vs[(N-1)/2]``, when ``N`` is odd, or ``{Vs[N/2 - 1] + Vs[N/2]}/2`` |
| 725 | when ``N`` is even. |
| 726 | |
| 727 | Examples |
| 728 | -------- |
| 729 | >>> import numpy as np |
| 730 | >>> x = np.ma.array(np.arange(8), mask=[0]*4 + [1]*4) |
| 731 | >>> np.ma.median(x) |
| 732 | 1.5 |
| 733 | |
| 734 | >>> x = np.ma.array(np.arange(10).reshape(2, 5), mask=[0]*6 + [1]*4) |
| 735 | >>> np.ma.median(x) |
searching dependent graphs…