algorithm for calculating quantile (default: QuantileAlgo.type7)
controls whether the input is modified in place, default is false
The interquartile range of the input.
Simple example
import mir.math.common: approxEqual; import mir.ndslice.slice: sliced; auto x = [3.0, 1.0, 4.0, 2.0, 0.0].sliced; assert(x.interquartileRange.approxEqual(2.0)); assert(x.interquartileRange(0.25).approxEqual(2.0)); assert(x.interquartileRange(0.25, 0.75).approxEqual(2.0));
Interquartile Range of vector
import mir.math.common: approxEqual; import mir.ndslice.slice: sliced; auto x = [1.0, 9.8, 0.2, 8.5, 5.8, 3.5, 4.5, 8.2, 5.2, 5.2, 2.5, 1.8, 2.2, 3.8, 5.2, 9.2, 6.2, 9.2, 9.2, 8.5].sliced; assert(x.interquartileRange.approxEqual(5.25));
Interquartile Range of matrix
import mir.math.common: approxEqual; import mir.ndslice.fuse: fuse; import mir.ndslice.slice: sliced; auto x = [ [1.0, 9.8, 0.2, 8.5, 5.8, 3.5, 4.5, 8.2, 5.2, 5.2], [2.5, 1.8, 2.2, 3.8, 5.2, 9.2, 6.2, 9.2, 9.2, 8.5] ].fuse; assert(x.interquartileRange.approxEqual(5.25));
Allow modification of input
import mir.algorithm.iteration: all; import mir.math.common: approxEqual; import mir.ndslice.slice: sliced; auto x = [3.0, 1.0, 4.0, 2.0, 0.0].sliced; auto x_copy = x.dup; auto result = x.interquartileRange!(QuantileAlgo.type7, true); assert(!x.all!approxEqual(x_copy));
Can also set algorithm type
import mir.math.common: approxEqual; import mir.ndslice.slice: sliced; auto x = [1.0, 9.8, 0.2, 8.5, 5.8, 3.5, 4.5, 8.2, 5.2, 5.2, 2.5, 1.8, 2.2, 3.8, 5.2, 9.2, 6.2, 9.2, 9.2, 8.5].sliced; assert(x.interquartileRange!"type1".approxEqual(6.0)); assert(x.interquartileRange!"type2".approxEqual(5.5)); assert(x.interquartileRange!"type3".approxEqual(6.0)); assert(x.interquartileRange!"type4".approxEqual(6.0)); assert(x.interquartileRange!"type5".approxEqual(5.5)); assert(x.interquartileRange!"type6".approxEqual(5.75)); assert(x.interquartileRange!"type7".approxEqual(5.25)); assert(x.interquartileRange!"type8".approxEqual(5.583333)); assert(x.interquartileRange!"type9".approxEqual(5.5625));
Can also set algorithm or output type
import mir.math.common: approxEqual; import mir.ndslice.slice: sliced; auto a = [1, 1e34, 1, -1e34, 0].sliced; auto x = a * 10_000; auto result0 = x.interquartileRange!float; assert(result0.approxEqual(10_000)); static assert(is(typeof(result0) == float)); auto result1 = x.interquartileRange!(float, "type8"); assert(result1.approxEqual(6.666667e37)); static assert(is(typeof(result1) == float));
Support for array
import mir.math.common: approxEqual; double[] x = [3.0, 1.0, 4.0, 2.0, 0.0]; assert(x.interquartileRange.approxEqual(2.0));
Computes the interquartile range of the input.
By default, this function computes the result using quantile, i.e. result = quantile(x, 0.75) - quantile(x, 0.25). There are also overloads for providing a low value, as in result = quantile(x, 1 - low) - quantile(x, low) and both a low and high value, as in result = quantile(x, high) - quantile(x, low).
For all QuantileAlgo except QuantileAlgo.type1 and QuantileAlgo.type3, by default, if F is not floating point type or complex type, then the result will have a double type if F is implicitly convertible to a floating point type or a type for which isComplex!F is true.
For QuantileAlgo.type1 and QuantileAlgo.type3, the return type is the $(MATHREF sum, elementType) of the input.