This header-only open-source library provides an easy-to-use state-of-the-art multi-dimensional histogram class for the professional statistician and everyone who needs to counts things. The histogram is easy to use for the casual user and yet very customizable. It does not restrict the power-user. The library offers a unique safety guarantee: cell counts cannot overflow or be capped in the standard configuration. And it can do more than counting. The histogram can be equipped with arbitrary accumulators to compute means, medians, and whatever you fancy in each cell. The library is very fast single-threaded (see benchmarks) and several parallelization options are provided for multi-threaded programming.

This project was developed for inclusion in Boost and passed Boost review in September 2018. The plan is to have a first official Boost-release in April 2019 with the upcoming version 1.70. Of course, you can use it already now (but pick the latest release!). The source code is licensed under the Boost Software License.

Check out the full documentation. Python bindings to this library are available elsewhere.

Features

Extremely customisable multi-dimensional histogram
Simple, convenient, STL and Boost-compatible interface
Counters with high dynamic range, cannot overflow or be capped (1)
Better performance than other libraries (see benchmarks for details)
Efficient use of memory (1)
Support for custom axis types: define how input values should map to indices
Support for under-/overflow bins (can be disabled individually to reduce memory consumption)
Support for axes that grow automatically with input values (2)
Support for weighted increments
Support for profiles and user-defined accumulators in histogram cells (3)
Support for completely stack-based histograms
Support for adding and scaling histograms
Support for custom allocators
Support for programming with units (4)
Optional serialization based on Boost.Serialization

In the standard configuration, if you don't use weighted increments. The counter capacity is increased dynamically as the cell counts grow. When even the largest plain integral type would overflow, the storage switches to a Boost.Multiprecision integer, which is only limited by available memory.
An axis can be configured to grow when a value is encountered that is outside of its range. It then grows new bins towards this value so that the value ends up in the new highest or lowest bin.
The histogram can be configured to hold an arbitrary accumulator in each cell instead of a simple counter. Extra values can be passed to the histogram, for example, to compute the mean and variance of values which fall into the same cell. This can be used to compute variance estimates for each cell. These are useful when histograms are to be compared quantitatively and if a statistical model is fitted to the cell values.
Builtin axis types can configured to only accept dimensional quantities, like those from Boost.Units. This means you get an error if you try to fill a length when the histogram axis expects a time, for example.

Dependencies

Boost >= 1.66 header-only installation is sufficient
Optional: CMake >= 3.5 Boost.Serialization Boost.Accumulators Boost.Range Boost.Units

Build instructions

If you don't want to run the tests, there is nothing to build. Just copy the content of the include folder to a place where your project can find it.

The tests can be build with b2 from the Boost project or cmake. If you are not a Boost developer, use cmake.

git clone https://github.com/boostorg/histogram.git
mkdir build && cd build
cmake ..
make

To run the tests, do make test or ctest -v for more output.

Code example

The following stripped-down example was taken from the Getting started section in the documentation. Have a look into the docs to see the full version with comments and more examples.

Example: Fill a 1d-histogram

#include <boost/histogram.hpp>
#include <boost/format.hpp> // used here for printing
#include <functional> // for std::ref

int main() {
    namespace bh = boost::histogram;

    auto h = bh::make_histogram(
      bh::axis::regular<>(6, -1.0, 2.0, "x")
    );

    // fill histogram
    auto data = { -0.4, 1.1, 0.3, 1.7 };
    std::for_each(data.begin(), data.end(), std::ref(h));

    // iterate over bins
    for (auto x : bh::indexed(h)) {
      std::cout << boost::format("bin %2i [%4.1f, %4.1f): %i\n")
        % x.index() % x.bin().lower() % x.bin().upper() % *x;
    }

    std::cout << std::flush;

    /* program output:

    bin -1 [-inf, -1.0): 1
    bin  0 [-1.0, -0.5): 1
    bin  1 [-0.5, -0.0): 1
    bin  2 [-0.0,  0.5): 2
    bin  3 [ 0.5,  1.0): 0
    bin  4 [ 1.0,  1.5): 1
    bin  5 [ 1.5,  2.0): 1
    bin  6 [ 2.0,  inf): 2
    */
}

Benchmarks

Boost.Histogram is more flexible and faster than other C/C++ libraries:

Details on the benchmark are given in the documentation.

What users say

John Buonagurio | Manager at E^xponent^®

"I just wanted to say 'thanks' for your awesome Histogram library. I'm working on a software package for processing meteorology data and I'm using it to generate wind roses with the help of Qt and QwtPolar. Looks like you thought of just about everything here – the circular axis type was practically designed for this application, everything 'just worked'."

State of project

Development is currently targets the 4.0 release, the first one to appear officially in Boost (Boost-1.70 is planned for April 2019). More than 500 individual tests make sure that the implementation works as expected. Full documentation is available. User feedback is appreciated!

The library was reviewed in September 2018 by the Boost Community under review manager Mateusz Loskot. It was conditionally accepted with requests to improve aspects of the interface and documentation. Current development is focusing on implementing these requests. Code-breaking changes of the interface are currently happening on the develop branch. If you want to use the library in production code, please use the latest release. After the library is released as part of Boost, the interface will be kept stable.

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Histogram