https://github.com/esheldon/weighting

Derive weights so that the distributions of two populations are proportional in N-dimensional space
https://github.com/esheldon/weighting

Last synced: 3 days ago
JSON representation

Derive weights so that the distributions of two populations are proportional in N-dimensional space

• Host: GitHub
• URL: https://github.com/esheldon/weighting
• Owner: esheldon
• Created: 2015-06-20T13:41:12.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2017-06-28T18:46:09.000Z (over 7 years ago)
• Last Synced: 2024-10-19T21:21:06.414Z (19 days ago)
• Language: C
• Homepage:
• Size: 201 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# weighting

Derive weights so that the distributions of two populations are proportional in N-dimensional space

This is a pure C code based on the original C++ code by Carlos Cunha;

significant parts of the code are essentially unchanged.  A python wrapper is

provided

# python code

Currently the python code just calls out to the C code.  I plan to make a proper

C extension in the future

For an example, see the test code weighting.test_gaussians()

## Installing python code

```bash

python setup.py install --prefix=/some/path

python setup.py install --prefix=~/local

# The python code calls out to the C code, so make

# sure the executable is in your path

```

# C code

## compilation

Currently codes for different number of dimensions are compiled separately. The following

make different executables 

```bash

# makes calcweights5

make ndim=5

# makes calcweights1.  Make sure to clean first

make clean

make ndim=1

# installation

make clean

make ndim=2 install

make clean

make ndim=5 install prefix=~/local

# uninstall

make ndim=5 uninstall prefix=~/local

```