Skip to content

Latest commit

 

History

History
59 lines (48 loc) · 1.33 KB

README.md

File metadata and controls

59 lines (48 loc) · 1.33 KB
Raw

MMI estimation

MI

Dependencies

  • pytorch
  • joblib
  • sklearn
  • numpy
  • scipy
  • matplotlib
  • tqdm

Dependencies for if-estimators

  • oct2py

Dependencies for AIC (better install following packages with brew if your machine is Mac)

  • cmake
  • boost
  • python3
  • boost-python3

build AIC module

cd MMI/IC
cmake src/
# set paths of python3, boost and boost-python3 in CMakeCache.txt
# and then cmake again
# until you see "-- Generating done"
make
# if successful, you will see
# Scanning dependencies of target AIC
# [ 50%] Building CXX object CMakeFiles/AIC.dir/pylib.cpp.o
# [100%] Linking CXX shared library AIC.so
# [100%] Built target AIC
# now AIC is built

How to run

cd ..
# check the configuration in settings.py
python -m MMI.main

How to add new mi estimators

  • go to model/
  • create a new class (see mine.py/linear_regression.py for example)
  • must contain the predict function (given a N by 2 matrix, return the MI estimator (float))
  • go to settings.py, add the corresponding configuration in the variable model

How to add new synthetic data

  • go to data/
  • create a new class (see bimodal.py for example)
  • must contain the two property: data and ground_truth (see bimodal.py for example)
  • go to settings.py, add the corresponding configuration in the variable data