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This is a gaussian emulator and Baysiean analysis with PyMC

Installation with miniforge

  1. Install miniforge for python3 by following the instructions on https://github.com/conda-forge/miniforge.
  2. Update and activate the base environment:
    $> conda update --all
    $> conda activate
  1. Set the channel priority to flexible (required before using the environment yml files, otherwise the solver may fail or produce an unusable env):
    $> conda config --set channel_priority flexible
  1. Go to /path/to/Bayesian-package and create the virtual environment.

    On Linux/Windows:

    $> conda env create --name <env_name> --file=environmentCrossPlatform.yml

On Mac, environmentCrossPlatform.yml does NOT work — use environmentMac.yml instead, and prefix the command with CONDA_SUBDIR=osx-64 so the correct platform packages are selected (without it, packages will fail to install):

    $> CONDA_SUBDIR=osx-64 conda env create --name <env_name> --file=environmentMac.yml
  1. Activate the environment:
    $> conda activate <env_name>
  1. Start the program.

    On Linux/Windows:

   $> python -m GUI.GUIController.GUIControllerMP <number-of-cores>

On Mac, you must use pythonw instead of python (the regular python will not work for the GUI):

   $> pythonw -m GUI.GUIController.GUIControllerMP <number-of-cores>

IF the script refuses to use more than one core despite > 1, try to restart the terminal after step 4. Sometimes the installation of conda messes up the CPU affinity. Restarting after installation usually fixes it.

If not, use

    $> OPENBLAS_MAIN_FREE=1 python -m GUI.GUIController.GUIControllerMP <number-of-cores>

(or pythonw instead of python on Mac).

Using GUI

TBD

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Gaussian emulator and Bayesian analysis

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