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#!/usr/bin/env python3
from __future__ import annotations
import boost_histogram as bh
# make 1-d histogram with 5 logarithmic bins from 1e0 to 1e5
h = bh.Histogram(
bh.axis.Regular(5, 1e0, 1e5, metadata="x", transform=bh.axis.transform.log),
storage=bh.storage.Weight(),
)
# fill histogram with numbers
x = (2e0, 2e1, 2e2, 2e3, 2e4)
h.fill(x, weight=4) # increment bin counter by 4
# iterate over bins and access bin counter
for idx, (lower, upper) in enumerate(h.axes[0]):
val = h[idx]
print(f"bin {idx} [{lower:g}, {upper:g}): {val.value} +/- {val.variance**0.5}")
# under- and overflow bin
lo, up = h.axes[0][bh.underflow]
print(
f"underflow [{lo:g}, {up:g}): {h[bh.underflow].value} +/- {h[bh.underflow].variance ** 0.5}"
)
lo, up = h.axes[0][bh.overflow]
print(
f"overflow [{lo:g}, {up:g}): {h[bh.overflow].value} +/- {h[bh.overflow].variance ** 0.5}"
)
# prints:
# bin 0 x in [1.0, 10.0): 4.0 +/- 4.0
# bin 1 x in [10.0, 100.0): 4.0 +/- 4.0
# bin 2 x in [100.0, 1000.0): 4.0 +/- 4.0
# bin 3 x in [1000.0, 10000.0): 4.0 +/- 4.0
# bin 4 x in [10000.0, 100000.0): 4.0 +/- 4.0
# underflow [0.0, 1.0): 0.0 +/- 0.0
# overflow [100000.0, inf): 0.0 +/- 0.0
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