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159 lines
4.7 KiB
Plaintext
159 lines
4.7 KiB
Plaintext
[section Tutorial]
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[section Example 1: 1d-histogram in C++]
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How to make a 1d-histogram in C++ and to fill it:
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[c++]
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```
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#include <boost/histogram/static_histogram.hpp> // proposed for inclusion in Boost
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#include <boost/histogram/axis.hpp> // proposed for inclusion in Boost
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#include <boost/histogram/utility.hpp> // proposed for inclusion in Boost
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#include <iostream>
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#include <cmath>
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int main(int, char**) {
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namespace bh = boost::histogram;
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// create 1d-histogram with 10 equidistant bins from -1.0 to 2.0,
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// with axis of histogram labeled as "x"
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auto h = bh::make_static_histogram(bh::regular_axis(10, -1.0, 2.0, "x"));
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// fill histogram with data
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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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h.wfill(0.1, 5.0); // fill with a weighted entry, weight is 5.0
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// access histogram counts, loop includes under- and overflow bin
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const auto& a = h.axis<0>();
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for (int i = -1, n = bh::bins(a) + 1; i < n; ++i) {
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std::cout << "bin " << i
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<< " x in [" << bh::left(a, i) << ", " << bh::right(a, i) << "): "
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<< h.value(i) << " +/- " << std::sqrt(h.variance(i))
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<< std::endl;
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}
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/* program output:
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bin -1 x in [-inf, -1): 1 +/- 1
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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): 5 +/- 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): 0 +/- 0
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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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bin 10 x in [2, inf): 2 +/- 1.41421
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*/
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}
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```
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Example 2: Fill a 2d-histogram in Python with data in Numpy arrays
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[python]
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```
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import histogram as bh
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import numpy as np
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# create 2d-histogram over polar coordinates, with
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# 10 equidistant bins in radius from 0 to 5 and
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# 4 equidistant bins in polar angle
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h = bh.histogram(bh.regular_axis(10, 0.0, 5.0, "radius",
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uoflow=False),
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bh.polar_axis(4, 0.0, "phi"))
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# generate some numpy arrays with data to fill into histogram,
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# in this case normal distributed random numbers in x and y,
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# converted into polar coordinates
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x = np.random.randn(1000) # generate x
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y = np.random.randn(1000) # generate y
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rphi = np.empty((1000, 2))
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rphi[:, 0] = (x ** 2 + y ** 2) ** 0.5 # compute radius
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rphi[:, 1] = np.arctan2(y, x) # compute phi
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# fill histogram with numpy array
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h.fill(rphi)
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# access histogram counts (no copy)
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count_matrix = np.asarray(h)
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print count_matrix
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# program output:
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#
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# [[37 26 33 37]
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# [60 69 76 62]
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# [48 80 80 77]
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# [38 49 45 49]
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# [22 24 20 23]
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# [ 7 9 9 8]
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# [ 3 2 3 3]
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# [ 0 0 0 0]
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# [ 0 1 0 0]
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# [ 0 0 0 0]]
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```
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[endsect]
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[section Example 2: 2d-histogram in Python]
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How to make a 2d-histogram in Python and to fill it using a Numpy array:
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[python]
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``
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import histogram as bh
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import numpy as np
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# create a 2d-histogram without underflow and overflow bins
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# for polar coordinates, using a specialized polar_axis for
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# the binning of the angle 'phi'
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#
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# radial axis with label 'radius' has 10 bins from 0.0 to 5.0
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# polar axis with label 'phi' has 4 bins and a phase of 0.0
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h = bh.histogram(bh.regular_axis(10, 0.0, 5.0, "radius",
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uoflow=False),
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bh.polar_axis(4, 0.0, "phi"))
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# fill histogram with random values, using numpy to make
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# a two-dimensional normal distribution in cartesian coordinates
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x = np.random.randn(1000) # generate x
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y = np.random.randn(1000) # generate y
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rphi = np.empty((1000, 2))
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rphi[:, 0] = (x ** 2 + y ** 2) ** 0.5 # compute radius
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rphi[:, 1] = np.arctan2(y, x) # compute phi
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h.fill(rphi)
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# access counts as a numpy array (no data is copied)
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count_matrix = np.asarray(h)
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print count_matrix
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``
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The program output are the counts per bin as a 2d-array:
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[python]
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``
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[[37 26 33 37]
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[60 69 76 62]
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[48 80 80 77]
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[38 49 45 49]
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[22 24 20 23]
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[ 7 9 9 8]
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[ 3 2 3 3]
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[ 0 0 0 0]
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[ 0 1 0 0]
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[ 0 0 0 0]]
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``
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[endsect]
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[endsect] |