问题描述
我有一连串的指标采样不均.我想对这些指标进行线性插值和上采样,以达到特定的采样频率.我曾尝试使用Accelerate Framework和SIMD框架,但我不确定该怎么做.
I have a stream of metrics that are unevenly sampled. I want to linearly interpolate and upsample these metrics to a specific sampling frequency. I have tried to use the Accelerate Framework and the SIMD framework but I am not really sure what to do.
问题本身如下:
let original_times:[Double] = [0.0, 2.0, 3.0, 6.0, 10.0]
let original_values: [Double] = [50.0, 20.0, 30.0, 40.0, 10.0]
let new_times:[Double] = [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
所以我正在寻找一种通过某种线性插值方法查找new_values的方法.
So I am looking for a way to find the new_values through some sort of linear interpolation method.
推荐答案
vDSP_vgenpD
将为您完成这项工作.将原始时间和值传递给它,它将使用插值填充一个数组.例如:
vDSP_vgenpD
will do the job for you. Pass it the original times and values, and it will populate an array with the interpolated values. For example:
import Accelerate
let original_times:[Double] = [0.0, 2.0, 3.0, 6.0, 10.0]
let original_values: [Double] = [50.0, 20.0, 30.0, 40.0, 10.0]
var new_values = [Double](repeating: 0,
count: 11)
let stride = vDSP_Stride(1)
vDSP_vgenpD(original_values, stride,
original_times, stride,
&new_values, stride,
vDSP_Length(new_values.count),
vDSP_Length(original_values.count))
您可以使用以下方法获取时间/值元组数组:
You can get an array of time / value tuples with:
let result = new_values.enumerated().map{ return $0 }
看起来像:
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