Trait basic_dsp_vector::StatisticsSplitOps

pub trait StatisticsSplitOps<T> {
    type Result;

    fn statistics_split(&self, len: usize) -> ScalarResult<Self::Result>;
}

This trait offers operations to calculate statistics about the data in a type.

Required Associated Types

type Result

Required Methods

fn statistics_split(&self, len: usize) -> ScalarResult<Self::Result>

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true.

Example

use basic_dsp_vector::*;
let vector = vec!(Complex32::new(1.0, 2.0), Complex32::new(3.0, 4.0), Complex32::new(5.0, 6.0)).to_complex_time_vec();
let result = vector.statistics_split(2).expect("Ignoring error handling in examples");
assert_eq!(result[0].sum, Complex32::new(6.0, 8.0));
assert_eq!(result[1].sum, Complex32::new(3.0, 4.0));
}

Implementors

impl<S, T, N, D> StatisticsSplitOps<Complex<T>> for DspVec<S, T, N, D>where
    S: ToSlice<T>,
    T: RealNumber,
    N: ComplexNumberSpace,
    D: Domain,

type Result = ArrayVec<Statistics<Complex<T>>, STATS_VEC_CAPACTIY>

impl<S, T, N, D> StatisticsSplitOps<T> for DspVec<S, T, N, D>where
    S: ToSlice<T>,
    T: RealNumber,
    N: RealNumberSpace,
    D: Domain,

type Result = ArrayVec<Statistics<T>, STATS_VEC_CAPACTIY>