python bindings for c++ reflection library (xo-distribution)

Getting Started

build + install dependencies

build + install

$ cd xo-pydistribution
$ mkdir build
$ cd build
$ INSTALL_PREFIX=/usr/local  # or wherever you prefer, e.g. ~/local
$ cmake \
    -DCMAKE_MODULE_PATH=${INSTALL_PREFIX}/share/cmake \
    -DCMAKE_PREFIX_PATH=${INSTALL_PREFIX} \
    -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} ..
$ make
$ make install

(also see .github/workflows/main.yml)

build for unit test coverage

$ cd xo-pydistribution
$ mkdir build-ccov
$ cd build-ccov
$ cmake \
    -DCMAKE_MODULE_PATH=${INSTALL_PREFIX}/share/cmake \
    -DCMAKE_PREFIX_PATH=${INSTALL_PREFIX} \
    -DCODE_COVERAGE=ON \
    -DCMAKE_BUILD_TYPE=Debug ..

LSP (language server) support

LSP looks for compile commands in the root of the source tree; while Cmake creates them in the root of its build directory.

$ cd xo-pydistribution
$ ln -s build/compile_commands.json  # supply compile commands to LSP

Examples

Assumes xo-pydistribution installed to ~/local2/lib

PYTHONPATH=~/local2/lib python
>>> import xo_pydistribution
>>> dir(xo_pydistribution)
['Distribution', 'ExplicitDist', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'normalcdf']
>>> from xo_pydistribution import *

normal distribution

>>> normalcdf(0.0)
0.5
>>> normalcdf(3.0)
0.9986501019683699

explicit distribution (online implementation). intended to model empirically a Bayesian prior.

>>> d=ExplicitDist.make(bucket_dx=0.01, ref_value=1e-6)
>>> d
<ExplicitDist :cdf_valid_flag 1 :bucket_dx 0.01 :ref_value 0 :lz 0 :hz 1 :lo_v [] :hi_v "[<ProbabilityBucket :wt 1 :cdf 1>]">
>>> d.cdf(0.0)
0.0
>>> d.cdf(0.01)
1.0

Rconybea / xo-pydistribution