type that satisfies isConvertibleToSlice!T && !isSlice!T
Median of vector
import mir.ndslice.slice: sliced; auto x0 = [9.0, 1, 0, 2, 3, 4, 6, 8, 7, 10, 5].sliced; assert(x0.median == 5); auto x1 = [9.0, 1, 0, 2, 3, 4, 6, 8, 7, 10].sliced; assert(x1.median == 5);
Median of dynamic array
auto x0 = [9.0, 1, 0, 2, 3, 4, 6, 8, 7, 10, 5]; assert(x0.median == 5); auto x1 = [9.0, 1, 0, 2, 3, 4, 6, 8, 7, 10]; assert(x1.median == 5);
Median of matrix
import mir.ndslice.fuse: fuse; auto x0 = [ [9.0, 1, 0, 2, 3], [4.0, 6, 8, 7, 10] ].fuse; assert(x0.median == 5);
Row median of matrix
import mir.algorithm.iteration: all; import mir.math.common: approxEqual; import mir.ndslice.fuse: fuse; import mir.ndslice.slice: sliced; import mir.ndslice.topology: alongDim, byDim, map; auto x = [ [0.0, 1.0, 1.5, 2.0, 3.5, 4.25], [2.0, 7.5, 5.0, 1.0, 1.5, 0.0] ].fuse; auto result = [1.75, 1.75].sliced; // Use byDim or alongDim with map to compute median of row/column. assert(x.byDim!0.map!median.all!approxEqual(result)); assert(x.alongDim!1.map!median.all!approxEqual(result));
Can allow original slice to be modified or set output type
import mir.ndslice.slice: sliced; auto x0 = [9.0, 1, 0, 2, 3, 4, 6, 8, 7, 10, 5].sliced; assert(x0.median!true == 5); auto x1 = [9, 1, 0, 2, 3, 4, 6, 8, 7, 10].sliced; assert(x1.median!(float, true) == 5);
Arbitrary median
assert(median(0, 1, 2, 3, 4) == 2);
For integral slices, can pass output type as template parameter to ensure output type is correct
import mir.ndslice.slice: sliced; auto x = [9, 1, 0, 2, 3, 4, 6, 8, 7, 10].sliced; assert(x.median!float == 5f); auto y = x.median; assert(y == 5.0); static assert(is(typeof(y) == double));