How to get single median in numpy masked array with even number of entires

I have a numpy masked nd-array. I need to find the median along a specific axis. For some cases, I end up having even number of elements, in which case numpy.ma.median gives average of the middle two elements. However, I don't want the average. I want one of the median elements. Any one of the two is fine. How do I get this?

MWE:

>>> import numpy
>>> data=numpy.arange(-5,10).reshape(3,5)
>>> mdata=numpy.ma.masked_where(data<=0,data)
>>> numpy.ma.median(mdata, axis=0)
masked_array(data=[5.0, 3.5, 4.5, 5.5, 6.5],
             mask=[False, False, False, False, False],
       fill_value=1e+20)

As you can see, it is averaging (1 and 6) and providing fractional values (3.5). I want any one of 1 or 6.

Solution

numpy.percentile(array, 50) gives median value.
numpy.percentile has an option to specify interpolation to nearest.
However this function is not available in numpy.ma module.
The trick used in this answer can be used here.

The idea is to fill invalid values with nan and use numpy.nanpercentile() with nearest interpolation.

>>> mdata1 = numpy.ma.filled(mdata.astype('float'), numpy.nan)
>>> numpy.nanpercentile(mdata1, 50, axis=0, interpolation='nearest')
array([5., 1., 2., 3., 4.])