pygram11
Simple and fast histogramming in Python accelerated with OpenMP with help from pybind11.
pygram11 provides functions for very fast histogram calculations
(and the variance in each bin) in one and two dimensions. The API is
very simple; documentation can be found
here (you'll also find some
benchmarks
there).
Installing
From PyPI
Binary wheels are provided for Linux, macOS, and Windows. They can be installed from PyPI:
pip install pygram11 # or uv pip install
From conda-forge
For installation via the conda package manager pygram11 is part of
conda-forge.
conda install pygram11 -c conda-forge
From Source
You need a C++17 compiler and OpenMP. If you are using a relatively
modern GCC release on Linux then you probably don't have to worry
about the OpenMP dependency. If you are on macOS, you can install
libomp from Homebrew.
git clone https://github.com/douglasdavis/pygram11.git --recurse-submodules
cd pygram11
pip install .
Or let pip handle the cloning procedure:
pip install git+https://github.com/douglasdavis/pygram11.git@main
Tests are run on Python versions >= 3.11 and binary wheels are
provided for those versions.
In Action
A histogram (with fixed bin width) of weighted data in one dimension:
>>> rng = np.random.default_rng(123)
>>> x = rng.standard_normal(10000)
>>> w = rng.uniform(0.8, 1.2, x.shape[0])
>>> h, err = pygram11.histogram(x, bins=40, range=(-4, 4), weights=w)
A histogram with fixed bin width which saves the under and overflow in the first and last bins:
>>> x = rng.standard_normal(1000000)
>>> h, __ = pygram11.histogram(x, bins=20, range=(-3, 3), flow=True)
where we've used __ to catch the None returned when weights are
absent. A histogram in two dimensions with variable width bins:
>>> x = rng.standard_normal(1000)
>>> y = rng.standard_normal(1000)
>>> xbins = [-2.0, -1.0, -0.5, 1.5, 2.0, 3.1]
>>> ybins = [-3.0, -1.5, -0.1, 0.8, 2.0, 2.8]
>>> h, err = pygram11.histogram2d(x, y, bins=[xbins, ybins])
Manually controlling OpenMP acceleration with context managers:
>>> with pygram11.omp_disabled(): # disable all thresholds.
... result, _ = pygram11.histogram(x, bins=10, range=(-3, 3))
...
>>> with pygram11.omp_forced(key="thresholds.var1d"): # force a single threshold.
... result, _ = pygram11.histogram(x, bins=[-3, -2, 0, 2, 3])
...
Histogramming multiple weight variations for the same data, then putting the result in a DataFrame (the input pandas DataFrame will be interpreted as a NumPy array):
>>> N = 10000
>>> weights = pd.DataFrame({"weight_a": np.abs(rng.standard_normal(N)),
... "weight_b": rng.uniform(0.5, 0.8, N),
... "weight_c": rng.uniform(0.0, 1.0, N)})
>>> data = rng.standard_normal(N)
>>> count, err = pygram11.histogram(data, bins=20, range=(-3, 3), weights=weights, flow=True)
>>> count_df = pd.DataFrame(count, columns=weights.columns)
>>> err_df = pd.DataFrame(err, columns=weights.columns)
I also wrote a blog post with some simple examples.
Other Libraries
- boost-histogram provides Pythonic object oriented histograms.
- Simple and fast histogramming in Python using the NumPy C API: fast-histogram (no variance or overflow support).
- To calculate histograms in Python on a GPU, see cupy.histogram.
If there is something you'd like to see in pygram11, please open an issue or pull request.
1 maintainer
Metadata
1 maintainer
Release files for pygram11 0.15.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pygram11-0.15.0.tar.gz | 1.4 MB | Details |
Built distributions (wheels)
Total release size: 26.0 MB
Release files / pygram11-0.15.0.tar.gz
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Release files / pygram11-0.15.0-cp312-cp312-musllinux_1_2_x86_64.whl
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| Size | 1.6 MB |
| Tags | CPython 3.12 Linux musl 1.2+ x86-64 |
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No |
| Uploaded via |
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Release files / pygram11-0.15.0-cp312-cp312-musllinux_1_2_aarch64.whl
| Download URL | pygram11-0.15.0-cp312-cp312-musllinux_1_2_aarch64.whl |
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| Size | 1.5 MB |
| Tags | CPython 3.12 Linux musl 1.2+ ARM64 |
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No |
| Uploaded via |
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Release files / pygram11-0.15.0-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
| Download URL | pygram11-0.15.0-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 416.1 kB |
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BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
| Download URL | pygram11-0.15.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl |
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| Size | 428.3 kB |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp312-cp312-macosx_14_0_arm64.whl
| Download URL | pygram11-0.15.0-cp312-cp312-macosx_14_0_arm64.whl |
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| Size | 592.0 kB |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
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Release files / pygram11-0.15.0-cp311-cp311-win_amd64.whl
| Download URL | pygram11-0.15.0-cp311-cp311-win_amd64.whl |
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| Size | 227.7 kB |
| Tags | CPython 3.11 Windows x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp311-cp311-win32.whl
| Download URL | pygram11-0.15.0-cp311-cp311-win32.whl |
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| Size | 197.1 kB |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Release files / pygram11-0.15.0-cp311-cp311-musllinux_1_2_x86_64.whl
| Download URL | pygram11-0.15.0-cp311-cp311-musllinux_1_2_x86_64.whl |
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| Size | 1.6 MB |
| Tags | CPython 3.11 Linux musl 1.2+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp311-cp311-musllinux_1_2_aarch64.whl
| Download URL | pygram11-0.15.0-cp311-cp311-musllinux_1_2_aarch64.whl |
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| Size | 1.5 MB |
| Tags | CPython 3.11 Linux musl 1.2+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
| Download URL | pygram11-0.15.0-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 418.0 kB |
| Tags | CPython 3.11 Linux glibc 2.24+ ARM64 Linux glibc 2.28+ ARM64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
| Download URL | pygram11-0.15.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl |
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| Size | 428.0 kB |
| Tags | CPython 3.11 Linux glibc 2.17+ x86-64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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Release files / pygram11-0.15.0-cp311-cp311-macosx_14_0_arm64.whl
| Download URL | pygram11-0.15.0-cp311-cp311-macosx_14_0_arm64.whl |
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| Size | 588.7 kB |
| Tags | CPython 3.11 macOS 14.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.0
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