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88 lines
3.3 KiB
C++
88 lines
3.3 KiB
C++
#include <boost/histogram.hpp>
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#include <iostream>
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int main(int, char**) {
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namespace bh = boost::histogram;
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using namespace bh::literals; // enables _c suffix
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/*
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create a static 1d-histogram with an axis that has 10 equidistant
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bins on the real line from -1.0 to 2.0, and label it as "x"
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*/
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auto h = bh::make_static_histogram(
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bh::axis::regular<>(10, -1.0, 2.0, "x")
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);
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// fill histogram with data, typically this would happen in a loop
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h.fill(-1.5); // put in underflow bin
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h.fill(-1.0); // included in first bin, bin interval is semi-open
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h.fill(-0.5);
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h.fill(1.1);
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h.fill(0.3);
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h.fill(1.7);
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h.fill(2.0); // put in overflow bin, bin interval is semi-open
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h.fill(20.0); // put in overflow bin
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/*
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use bh::count(N) if you would otherwise call h.fill(...) with
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*same* argument N times, N is an integer argument
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*/
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h.fill(1.0, bh::count(4));
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/*
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do a weighted fill using bh::weight, which accepts a double
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- don't mix this with bh::count, both have a different effect on the
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variance (see Rationale for an explanation regarding weights)
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- if you don't know what this is good for, use bh::count instead,
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it is most likeliy what you want and it is more efficient
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*/
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h.fill(0.1, bh::weight(2.5));
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/*
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iterate over bins, loop excludes under- and overflow bins
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- index 0_c is a compile-time number, the only way in C++ to make
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axis(...) to return a different type for each index
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- for-loop yields instances of `std::pair<int, bin_type>`, where
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`bin_type` usually is a semi-open interval representing the bin,
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whose edges can be accessed with methods `lower()` and `upper()`,
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but the [bin type] depends on the axis, look it up in the reference
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- `value(index)` method returns the bin count at index
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- `variance(index)` method returns a variance estimate of the bin
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count at index (see Rationale section for what this means)
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*/
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for (const auto& bin : h.axis(0_c)) {
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std::cout << "bin " << bin.first << " x in ["
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<< bin.second.lower() << ", " << bin.second.upper() << "): "
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<< h.value(bin.first) << " +/- "
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<< std::sqrt(h.variance(bin.first))
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<< std::endl;
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}
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// accessing under- and overflow bins is easy, use indices -1 and 10
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std::cout << "underflow bin [" << h.axis(0_c)[-1].lower()
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<< ", " << h.axis(0_c)[-1].upper() << "): "
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<< h.value(-1) << " +/- " << std::sqrt(h.variance(-1))
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<< std::endl;
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std::cout << "overflow bin [" << h.axis(0_c)[10].lower()
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<< ", " << h.axis(0_c)[10].upper() << "): "
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<< h.value(10) << " +/- " << std::sqrt(h.variance(10))
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<< std::endl;
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/* program output:
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bin 0 x in [-1, -0.7): 1 +/- 1
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bin 1 x in [-0.7, -0.4): 1 +/- 1
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bin 2 x in [-0.4, -0.1): 0 +/- 0
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bin 3 x in [-0.1, 0.2): 2.5 +/- 2.5
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bin 4 x in [0.2, 0.5): 1 +/- 1
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bin 5 x in [0.5, 0.8): 0 +/- 0
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bin 6 x in [0.8, 1.1): 4 +/- 2
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bin 7 x in [1.1, 1.4): 1 +/- 1
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bin 8 x in [1.4, 1.7): 0 +/- 0
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bin 9 x in [1.7, 2): 1 +/- 1
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underflow bin [-inf, -1): 1 +/- 1
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overflow bin [2, inf): 2 +/- 1.41421
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*/
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}
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