我编写了一个 LINQ 函数来插值和规范化时间序列数据，以便可以聚合/合并它。
重采样功能如下。我已经在 Code Project 中写了一个 short article 关于这种技术的文章。
// The function is an extension method, so it must be defined in a static class.
public static class ResampleExt
{
// Resample an input time series and create a new time series between two
// particular dates sampled at a specified time interval.
public static IEnumerable<OutputDataT> Resample<InputValueT, OutputDataT>(
// Input time series to be resampled.
this IEnumerable<InputValueT> source,
// Start date of the new time series.
DateTime startDate,
// Date at which the new time series will have ended.
DateTime endDate,
// The time interval between samples.
TimeSpan resampleInterval,
// Function that selects a date/time value from an input data point.
Func<InputValueT, DateTime> dateSelector,
// Interpolation function that produces a new interpolated data point
// at a particular time between two input data points.
Func<DateTime, InputValueT, InputValueT, double, OutputDataT> interpolator
)
{
// ... argument checking omitted ...
//
// Manually enumerate the input time series...
// This is manual because the first data point must be treated specially.
//
var e = source.GetEnumerator();
if (e.MoveNext())
{
// Initialize working date to the start date, this variable will be used to
// walk forward in time towards the end date.
var workingDate = startDate;
// Extract the first data point from the input time series.
var firstDataPoint = e.Current;
// Extract the first data point's date using the date selector.
var firstDate = dateSelector(firstDataPoint);
// Loop forward in time until we reach either the date of the first
// data point or the end date, which ever comes first.
while (workingDate < endDate && workingDate <= firstDate)
{
// Until we reach the date of the first data point,
// use the interpolation function to generate an output
// data point from the first data point.
yield return interpolator(workingDate, firstDataPoint, firstDataPoint, 0);
// Walk forward in time by the specified time period.
workingDate += resampleInterval;
}
//
// Setup current data point... we will now loop over input data points and
// interpolate between the current and next data points.
//
var curDataPoint = firstDataPoint;
var curDate = firstDate;
//
// After we have reached the first data point, loop over remaining input data points until
// either the input data points have been exhausted or we have reached the end date.
//
while (workingDate < endDate && e.MoveNext())
{
// Extract the next data point from the input time series.
var nextDataPoint = e.Current;
// Extract the next data point's date using the data selector.
var nextDate = dateSelector(nextDataPoint);
// Calculate the time span between the dates of the current and next data points.
var timeSpan = nextDate - firstDate;
// Loop forward in time until wwe have moved beyond the date of the next data point.
while (workingDate <= endDate && workingDate < nextDate)
{
// The time span from the current date to the working date.
var curTimeSpan = workingDate - curDate;
// The time between the dates as a percentage (a 0-1 value).
var timePct = curTimeSpan.TotalSeconds / timeSpan.TotalSeconds;
// Interpolate an output data point at the particular time between
// the current and next data points.
yield return interpolator(workingDate, curDataPoint, nextDataPoint, timePct);
// Walk forward in time by the specified time period.
workingDate += resampleInterval;
}
// Swap the next data point into the current data point so we can move on and continue
// the interpolation with each subsqeuent data point assuming the role of
// 'next data point' in the next iteration of this loop.
curDataPoint = nextDataPoint;
curDate = nextDate;
}
// Finally loop forward in time until we reach the end date.
while (workingDate < endDate)
{
// Interpolate an output data point generated from the last data point.
yield return interpolator(workingDate, curDataPoint, curDataPoint, 1);
// Walk forward in time by the specified time period.
workingDate += resampleInterval;
}
}
}
}