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9abbe46e3d
* Travis uses b2 and codecov now * replacing boost::multiprecision with custom implementation to avoid the dependency * improved axis implementation: `update` is now a normal method * introduced use_default tag type to set defaults * whitespace fixes and doc update
54 lines
1.7 KiB
C++
54 lines
1.7 KiB
C++
// Copyright 2019 Hans Dembinski
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//
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt
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// or copy at http://www.boost.org/LICENSE_1_0.txt)
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//[ guide_fill_profile
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#include <boost/format.hpp>
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#include <boost/histogram.hpp>
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#include <cassert>
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#include <iostream>
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#include <sstream>
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#include <utility>
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int main() {
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using namespace boost::histogram;
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// make a profile, it computes the mean of the samples in each histogram cell
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auto h = make_profile(axis::regular<>(3, 0.0, 1.0));
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// mean is computed from the values marked with the sample() helper function
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h(0.10, sample(2.5)); // 2.5 goes to bin 0
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h(0.25, sample(3.5)); // 3.5 goes to bin 0
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h(0.45, sample(1.2)); // 1.2 goes to bin 1
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h(sample(3.4), 0.51); // 3.4 goes to bin 1, sample be at the front
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// fills from tuples are also supported, 1.3 and 1.9 go to bin 2
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auto xs1 = std::make_tuple(0.81, sample(1.3));
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auto xs2 = std::make_tuple(0.86, sample(1.9));
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h(xs1);
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h(xs2);
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// builtin accumulators have methods to access their state
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std::ostringstream os;
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for (auto x : indexed(h)) {
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// use `.` to access methods of accessor, like `index()`
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// use `->` to access methods of accumulator
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const auto i = x.index();
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const auto n = x->count(); // how many samples are in this bin
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const auto vl = x->value(); // mean value
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const auto vr = x->variance(); // estimated variance of the mean value
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os << boost::format("bin %i count %i value %.1f variance %.1f\n") % i % n % vl % vr;
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}
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std::cout << os.str() << std::flush;
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assert(os.str() == "bin 0 count 2 value 3.0 variance 0.5\n"
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"bin 1 count 2 value 2.3 variance 2.4\n"
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"bin 2 count 2 value 1.6 variance 0.2\n");
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}
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//]
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