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33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
#[ guide_python_histogram
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import histogram as hg
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# make 1-d histogram with 5 logarithmic bins from 1e0 to 1e5
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h = hg.histogram(hg.axis.regular_log(5, 1e0, 1e5, "x"))
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# fill histogram with numbers
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for x in (2e0, 2e1, 2e2, 2e3, 2e4):
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h(x, weight=4) # increment bin counter by 4
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# iterate over bins and access bin counter
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for idx, (lower, upper) in enumerate(h.axis(0)):
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print "bin {0} x in [{1}, {2}): {3} +/- {4}".format(
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idx, lower, upper, h.bin(idx).value, h.bin(idx).variance ** 0.5)
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# under- and overflow bins are accessed like in C++
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lo, up = h.axis(0)[-1]
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print "underflow [{0}, {1}): {2} +/- {3}".format(lo, up, h(-1).value, h(-1).variance)
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lo, up = h.axis(0)[5]
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print "overflow [{0}, {1}): {2} +/- {3}".format(lo, up, h(5).value, h(5).variance)
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# prints:
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# bin 0 x in [1.0, 10.0): 4.0 +/- 4.0
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# bin 1 x in [10.0, 100.0): 4.0 +/- 4.0
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# bin 2 x in [100.0, 1000.0): 4.0 +/- 4.0
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# bin 3 x in [1000.0, 10000.0): 4.0 +/- 4.0
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# bin 4 x in [10000.0, 100000.0): 4.0 +/- 4.0
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# underflow [0.0, 1.0): 0.0 +/- 0.0
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# overflow [100000.0, inf): 0.0 +/- 0.0
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#]
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