IRIS-HEP: Boost-histogram and Hist
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The document discusses the current state of histograms in Python and the need for a new library. It introduces boost-histogram, a C++ histogram library, and its new Python bindings. The bindings aim to provide a fast, flexible, and easily distributable histogram object for Python with support for multiple axis types and storage options. It also discusses plans for an additional wrapper library called hist for easy plotting and interfacing with other tools.
![Flexibility: Axis boost-histogram (Python)
• bh.axis.regular
▶ bh.axis.regular_uoflow
▶ bh.axis.regular_noflow
▶ bh.axis.regular_growth
• bh.axis.circular
• bh.axis.regular_log
• bh.axis.regular_sqrt
• bh.axis.regular_pow
• bh.axis.integer
• bh.axis.integer_noflow
• bh.axis.integer_growth
• bh.axis.variable
• bh.axis.category_int
• bh.axis.category_int_growth
0 0.5 1
bh.axis.regular(10,0,1)
𝜋/2
0, 2𝜋
𝜋
3𝜋/3
bh.axis.circular(8,0,2*np.pi)
0 0.3 0.5 1
bh.axis.variable([0,.3,.5,1])
0 1 2 3 4
bh.axis.integer(0,5)
2 5 8 3 7
bh.axis.category_int([2,5,8,3,7])
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IRIS-HEP: Boost-histogram and Hist
- 1. boost-histogram and hist Henry Schreiner April 15, 2019
- 2. Histograms in Python 1/27Henry Schreiner boost-histogram and hist April 15, 2019
- 3. Current state of histograms in Python Histograms in Python Core library: numpy • Historically slow • No histogram object • Plotting is separate Other libraries • Narrow focus: speed, plotting, or language • Many are abandoned • Poor design, backends, distribution HistBook Histogrammar pygram11 rootplotlib PyROOT YODA physt fast-histogramqhist Vaex hdrhistogram multihist matplotlib-hep pyhistogram histogram SimpleHist paida theodoregoetz numpy 2/27Henry Schreiner boost-histogram and hist April 15, 2019
- 4. What is needed? Histograms in Python Design • A histogram should be an object • Manipulation and plotting should be easy Performance • Fast single threaded filling • Multithreaded filling (since it’s 2019) Flexibility • Axes options: sparse, growing, labels • Storage: integers, weights, errors… Distribution • Easy to use anywhere, pip or conda • Should have wheels, be easy to build, etc. 3/27Henry Schreiner boost-histogram and hist April 15, 2019
- 5. Future of histograms in Python Histograms in Python Core histogramming libraries boost-histogram ROOT Universal adaptor Aghast Front ends (plotting, etc) hist mpl-hep physt others 4/27Henry Schreiner boost-histogram and hist April 15, 2019
- 6. Boost::Histogram (C++14) 5/27Henry Schreiner boost-histogram and hist April 15, 2019
- 7. Intro to Boost::Histogram Boost::Histogram (C++14) • Multidimensional templated header-only histogram library: /boostorg/histogram • Designed by Hans Dembinski, inspired by ROOT, GSL, and histbook Histogram • Axes • Storages • Accumulators Axes types • Regular, Circular • Variable • Integer • Category Storage ( Static Dynamic )Regular axis Regular axis with log transformaxes Optional overflowOptional underflow Accumulator int, double, unlimited, ... 6/27Henry Schreiner boost-histogram and hist April 15, 2019
- 8. Intro to Boost::Histogram Boost::Histogram (C++14) • Multidimensional templated header-only histogram library: /boostorg/histogram • Designed by Hans Dembinski, inspired by ROOT, GSL, and histbook Histogram • Axes • Storages • Accumulators Axes types • Regular, Circular • Variable • Integer • Category Storage ( Static Dynamic )Regular axis Regular axis with log transformaxes Optional overflowOptional underflow Accumulator int, double, unlimited, ... Boost 1.70 now released with Boost::Histogram! 6/27Henry Schreiner boost-histogram and hist April 15, 2019
- 9. boost-histogram (Python) 7/27Henry Schreiner boost-histogram and hist April 15, 2019
- 10. Intro to the Python bindings boost-histogram (Python) • Boost::Histogram developed with Python in mind • Original bindings based on Boost::Python ▶ Hard to build and distribute ▶ Somewhat limited • New bindings: /scikit-hep/boost-histogram ▶ 0-dependency build (C++14 only) ▶ State-of-the-art PyBind11 Design Flexibility Speed Distribution 8/27Henry Schreiner boost-histogram and hist April 15, 2019
- 11. Design boost-histogram (Python) • Supports Python 2.7 and 3.4+ • 260+ unit tests run on Azure on Linux, macOS, and Windows • Up to 16 axes supported (may go up or down) • 1D, 2D, and ND histograms all have the same interface Tries to stay close to the original Boost::Histogram where possible. C++ #include <boost/histogram.hpp> namespace bh = boost::histogram; auto hist = bh::make_histogram( bh::axis::regular<>{2, 0, 1, "x"}, bh::axis::regular<>{4, 0, 1, "y"}); hist(.2, .3); Python import boost.histogram as bh hist = bh.make_histogram( bh.axis.regular(2, 0, 1, metadata="x"), bh.axis.regular(4, 0, 1, metadata="y")) hist(.2, .3) 9/27Henry Schreiner boost-histogram and hist April 15, 2019
- 12. Design: Manipulations boost-histogram (Python) Combine two histograms hist1 + hist2 Scale a histogram hist * 2.0 Project a 3D histogram to 2D hist.project(0,1) # select axis Sum a histogram contents hist.sum() Access an axis axis0 = hist.axis(0) axis0.edges() # The edges array axis0.bin(1) # The bin accessors Fill 2D histogram with values or arrays hist(x, y) Fill copies in 4 threads, then merge hist.fill_threaded(4, x, y) Fill in 4 threads (atomic storage only) hist.fill_atomic(4, x, y) Convert to Numpy, 0-copy hist.view() # Or np.asarray(hist) 10/27Henry Schreiner boost-histogram and hist April 15, 2019
- 13. Flexibility: Axis boost-histogram (Python) • bh.axis.regular ▶ bh.axis.regular_uoflow ▶ bh.axis.regular_noflow ▶ bh.axis.regular_growth • bh.axis.circular • bh.axis.regular_log • bh.axis.regular_sqrt • bh.axis.regular_pow • bh.axis.integer • bh.axis.integer_noflow • bh.axis.integer_growth • bh.axis.variable • bh.axis.category_int • bh.axis.category_int_growth 0 0.5 1 bh.axis.regular(10,0,1) 𝜋/2 0, 2𝜋 𝜋 3𝜋/3 bh.axis.circular(8,0,2*np.pi) 0 0.3 0.5 1 bh.axis.variable([0,.3,.5,1]) 0 1 2 3 4 bh.axis.integer(0,5) 2 5 8 3 7 bh.axis.category_int([2,5,8,3,7]) 11/27Henry Schreiner boost-histogram and hist April 15, 2019
- 14. Flexibility: Storage types boost-histogram (Python) • bh.storage.int • bh.storage.double • bh.storage.unlimited (WIP) • bh.storage.atomic_int • bh.storage.weight (WIP) • bh.storage.profile (WIP, needs sampled fill) • bh.storage.weighted_profile (WIP, needs sampled fill) 12/27Henry Schreiner boost-histogram and hist April 15, 2019
- 15. Performance boost-histogram (Python) The following measurements are with: 1D • 100 regular bins • 10,000,000 entries 2D • 100x100 regular bins • 1,000,000 entries See my histogram performance post for measurements of other libraries. 13/27Henry Schreiner boost-histogram and hist April 15, 2019
- 16. Performance: macOS, dual core, 1D boost-histogram (Python) Type Storage Fill Time Speedup Numpy uint64 149.4 ms 1x Any int 236 ms 0.63x Regular int 86.23 ms 1.7x Regular aint 1 132 ms 1.1x Regular aint 2 168.2 ms 0.89x Regular aint 4 143.6 ms 1x Regular int 1 84.75 ms 1.8x Regular int 2 51.6 ms 2.9x Regular int 4 42.39 ms 3.5x 14/27Henry Schreiner boost-histogram and hist April 15, 2019
- 17. Performance: CentOS7, 24 core, 1D (anaconda) boost-histogram (Python) Type Storage Fill Time Speedup Numpy uint64 121 ms 1x Any int 261.5 ms 0.46x Regular int 142.2 ms 0.85x Regular aint 1 319.1 ms 0.38x Regular aint 48 272.9 ms 0.44x Regular int 1 243.4 ms 0.5x Regular int 6 94.76 ms 1.3x Regular int 12 71.38 ms 1.7x Regular int 24 52.26 ms 2.3x Regular int 48 43.01 ms 2.8x 15/27Henry Schreiner boost-histogram and hist April 15, 2019
- 18. Performance: KNL, 64 core, 1D (anaconda) boost-histogram (Python) Type Storage Fill Time Speedup Numpy uint64 716.9 ms 1x Any int 1418 ms 0.51x Regular int 824 ms 0.87x Regular aint 1 871.7 ms 0.82x Regular aint 4 437.1 ms 1.6x Regular aint 64 198.8 ms 3.6x Regular aint 128 186.8 ms 3.8x Regular aint 256 195.2 ms 3.7x Regular int 1 796.9 ms 0.9x Regular int 2 430.6 ms 1.7x Regular int 4 247.6 ms 2.9x Regular int 64 88.77 ms 8.1x Regular int 128 98.08 ms 7.3x Regular int 256 112.2 ms 6.4x 16/27Henry Schreiner boost-histogram and hist April 15, 2019
- 19. Performance: macOS, dual core, 2D boost-histogram (Python) Type Storage Fill Time Speedup Numpy uint64 121.1 ms 1x Any int 37.12 ms 3.3x Regular int 18.5 ms 6.5x Regular aint 1 20.21 ms 6x Regular aint 2 14.17 ms 8.5x Regular aint 4 10.23 ms 12x Regular int 1 17.86 ms 6.8x Regular int 2 9.41 ms 13x Regular int 4 6.854 ms 18x 17/27Henry Schreiner boost-histogram and hist April 15, 2019
- 20. Performance: CentOS7, 24 core, 2D (anaconda) boost-histogram (Python) Type Storage Fill Time Speedup Numpy uint64 87.27 ms 1x Any int 41.42 ms 2.1x Regular int 21.67 ms 4x Regular aint 1 38.61 ms 2.3x Regular aint 6 19.89 ms 4.4x Regular aint 24 9.556 ms 9.1x Regular aint 48 8.518 ms 10x Regular int 1 36.5 ms 2.4x Regular int 6 8.976 ms 9.7x Regular int 12 5.318 ms 16x Regular int 24 4.388 ms 20x Regular int 48 5.839 ms 15x 18/27Henry Schreiner boost-histogram and hist April 15, 2019
- 21. Performance: KNL, 64 core, 2D (anaconda) boost-histogram (Python) Type Storage Fill Time Speedup Numpy uint64 439.5 ms 1x Any int 250.6 ms 1.8x Regular int 135.6 ms 3.2x Regular aint 1 142.2 ms 3.1x Regular aint 4 52.71 ms 8.3x Regular aint 32 12.05 ms 36x Regular aint 64 16.5 ms 27x Regular aint 256 43.93 ms 10x Regular int 1 141.1 ms 3.1x Regular int 2 70.78 ms 6.2x Regular int 4 36.11 ms 12x Regular int 64 18.93 ms 23x Regular int 128 36.09 ms 12x Regular int 256 55.64 ms 7.9x 19/27Henry Schreiner boost-histogram and hist April 15, 2019
- 22. Performance: Summary boost-histogram (Python) System 1D max speedup 2D max speedup macOS 1 core 1.7 x 6.5 x macOS 2 core 3.5 x 18 x Linux 1 core 0.85 x 4 x Linux 24 core 2.8 x 20 x KNL 1 core 0.87 x 3.2 x KNL 64 core 8.1 x 36 x • Note that Numpy 1D is well optimized (last few versions) • Anaconda versions may provide a few more optimizations to Numpy • Mixing axes types in boost-histogram can reduce performance by 2-3x 20/27Henry Schreiner boost-histogram and hist April 15, 2019
- 23. Distribution boost-histogram (Python) • We must provide excellent distribution. ▶ If anyone writes pip install boost-histogram and it fails, we have failed. • Docker ManyLinux1 GCC 8.3: /scikit-hep/manylinuxgcc Wheels • manylinux1 32, 64 bit (ready) • manylinux2010 64 bit (planned) • macOS 10.9+ (wip) • Windows 32, 64 bit, Python 3.6+ (wip) ▶ Is Python 2.7 Windows needed? Source • SDist (ready) • Build directly from GitHub (done) Conda • conda package (planned, easy) python -m pip install git+https://github.com/scikit-hep/boost-histogram.git@develop 21/27Henry Schreiner boost-histogram and hist April 15, 2019
- 24. Plans boost-histogram (Python) • Add shortcuts for axis types, fill out axis types • Allow view access into unlimited storage histograms • Add from_numpy and numpy style shortcut(s) • Filling ▶ Samples ▶ Weights ▶ Non-numerical fill (if possible) • Add profile, weighted_profile histograms • Add reduce operations • Release to PyPI • Add some docs and read the docs support First alpha Release planned this week 22/27Henry Schreiner boost-histogram and hist April 15, 2019
- 25. Bikeshedding (API discussion) boost-histogram (Python) Let’s discuss API! (On GitHub issues or gitter) • Download: pip install boost-histogram (WIP) • Use: import boost.histogram as bh • Create: hist = bh.histogram(bh.axis.regular(12,0,1)) • Fill: hist(values) • Access values, convert to numpy, etc. AndGod III 1am a it a a EAB.zpkpt.LY eEFEEIE Documentation • The documentation will also need useful examples, feel free to contribute! 23/27Henry Schreiner boost-histogram and hist April 15, 2019
- 26. hist 24/27Henry Schreiner boost-histogram and hist April 15, 2019
- 27. A slide about hist hist hist is the ‘wrapper’ piece that does plotting and interacts with the rest of the ecosystem. Plans • Easy plotting adaptors (mpl-hep) • Serialization formats (ROOT, HDF5) • Auto-multithreading • Statistical functions (Like TEfficiency) • Multihistograms (HistBook) • Interaction with fitters (ZFit, GooFit, etc) • Bayesian Blocks algorithm from SciKit-HEP • Command line histograms for stream of numbers Call for contributions • What do you need? • What do you want? • What would you like? Join in the development! This should combine the best features of other packages. 25/27Henry Schreiner boost-histogram and hist April 15, 2019
- 28. Questions? 26/27Henry Schreiner boost-histogram and hist April 15, 2019
- 29. Backup Questions? • Supported by IRIS-HEP, NSF OAC-1836650 27/27Henry Schreiner boost-histogram and hist April 15, 2019