Fast histogramming in python built on pybind11
Project description
pygram11
Simple and fast histogramming in python via pybind11 and (optionally) OpenMP
pygram11 provides fast functions for generating histograms (and
their sums-of-weights squared). The API is very simple, check out the
documentation (you'll also find some benchmarks there) and my blog
post.
Installing
pygram11 requires only NumPy and pybind11 (and therefore a C++
compiler with C++11 support). Note: pybind11 must be installed
explicitly before pygram11 (because setup.py uses pybind11 to
determine include directories).
From PyPI
$ pip install pybind11 ## or `conda install pybind11`
$ pip install pygram11
From Source
$ git clone https://github.com/drdavis/pygram11.git
$ pip install pybind11
$ cd pygram11
$ pip install .
In Action
A fixed bin width histogram of weighted data in one dimension, accelerated with OpenMP:
>>> x = np.random.randn(10000)
>>> w = np.random.uniform(0.8, 1.2, 10000)
>>> h, sw2 = pygram11.histogram(x, bins=40, range=(-4, 4), weights=w, omp=True)
>>> stat_err = np.sqrt(sw2)
A variable bin width histogram in two dimensions:
>>> x = np.random.randn(10000)
>>> y = np.random.randn(10000)
>>> xbins = [-2.0, -1.0, -0.5, 1.5, 2.0]
>>> ybins = [-3.0, -1.5, -0.1, 0.8, 2.0]
>>> h = pygram11.histogram2d(x, y, bins=[xbins, ybins])
If there is something you'd like to see in pygram11, please open an issue or pull request.
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