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Posted 3 Nov 2003

# Input and output iterators for sampling a data stream

, 3 Nov 2003
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These iterators provide a simple way to sample or stretch a fixed size data set to fit in a larger or smaller container

## Introduction

I was working on an application to show 3D paths using Direct3D and ran into a video card limit in the number of elements in the path. To solve the problem, I wrote some simple code to sample the data I was generating without just clipping the data off at a fixed point. While I needed it for this special case, the problem is a general one that arises in stretching or shrinking data such as images or changing the sample rate of audio files.

I searched for some code that would accomplish that and the closest I could come up with was writing a custom predicate for the boost filter iterator. While writing the predicate, I realized there was a more general solution that would support not just sampling the data set but stretching it as well.

In order to provide the most flexible and easy to use interface I provided 3 ways that the sample algorithm can be used. Through an input iterator, an output iterator or a predicate that can be used by the boost filter iterator or the STL `remove_if` algorithm.

## Using the code

Using the iterator is relatively simple. Per the STL convention, I've provided a pair of template functions that allow for easy creation of both input and output iterator forms. Here is a simple sample that shows the use of both forms input and output.

```std::vector<INT> list;
for(int i=0; i<7; ++i)
list.push_back(i);

std::cout << "Original sequence:" << std::endl;
std::copy(list.begin(), list.end(), std::ostream_iterator<INT>(std::cout, " "));
std::cout << std::endl;

std::cout << "Input sampled/stretched at various intervals:" << std::endl;
for(size_t dest_size = 1; dest_size<=list.size()*2; ++dest_size)
{
std::copy(sample::sample(list.begin(), dest_size, list.size()),
sample::sample(list.end(), dest_size, list.size()),
std::ostream_iterator<INT>(std::cout, " "));
std::cout << std::endl;
};

std::cout << "Output sampled/stretched at various intervals:" << std::endl;
for(size_t dest_size = 1; dest_size<=list.size()*2; ++dest_size)
{
std::copy(list.begin(), list.end(), sample::sample_output(
std::ostream_iterator<INT>(std::cout, " "), dest_size, list.size()));
std::cout << std::endl;
};
```

The biggest limitation of these objects is that you must know the size of both the input and output dataset. Also, a simple sampling method is used that only takes the location of the element in the data set into account. It doesn't look at the quality of the sample point to drop. For example an optimal solution for sampling a 3D curve would take the curvature at each point into account when deciding to drop a data point.

## Points of Interest

I suspected that moving the ownership of the actual base iterator object out of the functor object into the wrapping iterator objects would provide a greater flexibility and ease of use. I'm working on some more advanced sample functors right now that will use averaging/linear interpolation as well as spline interpolation, and I think these will be simplified by owning the iterator since they will make it easier for the algorithm to read/write the interpolated data without having excessive access to the iterator class internal objects. I hope to post the updated functors in the near future and will include any updates to these iterators that are required to make it work.

A list of licenses authors might use can be found here

## Share

 Software Developer (Senior) Standard Beagle Studios United States
I co-founded Standard Beagle Studio, a software development consulting service in Austin Texas with my wife Cindy Brummer. We focus mostly on web projects, but have built some react native mobile apps, and even a windows screen saver or two.

I started my career back when ASP pages were state of the art, and IE3 was considered a web browser. I've worked with Microsoft technologies for most of that time, and have recently branched out into node, wordpress, and react native applications.

I'm a web developer, math and physics enthusiast, father of 2, and all around great guy. I live in Austin TX and love using technology to change people's lives for the better. When I manage scrape together some spare time, I build generative art at curvature of the mind.

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 Could not get it to compile. WREY5-Nov-03 1:09 WREY 5-Nov-03 1:09
 Re: Could not get it to compile. andy brummer5-Nov-03 8:48 andy brummer 5-Nov-03 8:48
 Re: Could not get it to compile. WREY5-Nov-03 11:02 WREY 5-Nov-03 11:02
 Works for some apps KevinHall4-Nov-03 6:31 KevinHall 4-Nov-03 6:31
 This may work for some applications -- your's being one. However, this is not the best solution in all cases. Sometimes a different way of resampling (for creating smaller data sets) or interpolating (for larger data sets) is necessary. I'm sure anyone who needs something more sophisticated is alredy aware of good sources, but in case someone is not, I suggest browsing through "Numerical Recipes in C". This isn't to retract from the work you did though. For the set of applications where this would apply, this look good.
 Re: Works for some apps andy brummer4-Nov-03 14:10 andy brummer 4-Nov-03 14:10
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