scipy.stats.mstats.trimr¶

scipy.stats.mstats.trimr(a, limits=None, inclusive=(True, True), axis=None)[source]¶

Trims an array by masking some proportion of the data on each end. Returns a masked version of the input array.

Parameters:

Parameters:	a : sequence Input array. limits : {None, tuple}, optional Tuple of the percentages to cut on each side of the array, with respect to the number of unmasked data, as floats between 0. and 1. Noting n the number of unmasked data before trimming, the (nlimits[0])th smallest data and the (nlimits[1])th largest data are masked, and the total number of unmasked data after trimming is n(1.-sum(limits)). The value of one limit can be set to None to indicate an open interval. inclusive* : {(True,True) tuple}, optional Tuple of flags indicating whether the number of data being masked on the left (right) end should be truncated (True) or rounded (False) to integers. axis : {None,int}, optional Axis along which to trim. If None, the whole array is trimmed, but its shape is maintained.

a : sequence: Input array.
limits : {None, tuple}, optional: Tuple of the percentages to cut on each side of the array, with respect to the number of unmasked data, as floats between 0. and 1. Noting n the number of unmasked data before trimming, the (n*limits[0])th smallest data and the (n*limits[1])th largest data are masked, and the total number of unmasked data after trimming is n*(1.-sum(limits)). The value of one limit can be set to None to indicate an open interval.
inclusive : {(True,True) tuple}, optional: Tuple of flags indicating whether the number of data being masked on the left (right) end should be truncated (True) or rounded (False) to integers.
axis : {None,int}, optional: Axis along which to trim. If None, the whole array is trimmed, but its shape is maintained.