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Efficient sampling of high dimensional spaces with complex, non-linear constraints

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Non-linear-Optimization

=================================================================================== Citrine Informatics Technical Challenge Scientific Software Engineer

Efficient sampling of high dimensional spaces with complex, non-linear constraints By Arash Nemati Hayati - 06/01/2018

To use this software:

  1. Go to the Build directory.
  2. Run the following command: python3 run.py <input_file> <output_file> <N_results>

Example: python3 run.py input.txt output.txt 100

A demo of the following testcase can be found inside the Testing directory:

  1. Go to the Testing directory
  2. Run the following command: python3 demo.py

Sample input file: 2 # Number of dimensions 0.0 0.0 # initial values

Simple 3-component mixture - constraint

1.0 - x[0] - x[1] >= 0.0

Installation

The following standard python libraries must be installed (if not already exist):

  1. pathlib
  2. numdifftools
  3. scipy
  4. numpy

To compile the code: Linux

  1. cd Build
  2. python3 run.py <input_file> <output_file> <N_results> Example: python3 run.py input.txt output.txt 100

Windows

  1. Go to the Build directory.
  2. Open run.py with Eclipse, Visual Studio or other compatible environment
  3. Go to Run, the Run configurations from the menu-bar (for Eclipse)
  4. Go to the Arguments tab and paste the following:
  5.  <input_file> <output_file> <N_results>
    

Example: python3 run.py input.txt output.txt 100 6. Click to Run the testcase

Bugs, issues, questions

All inquiries should be submitted on github https://github.com/arashnh11/Non-linear-Optimization or by email to a.nematihayati@gmail.com Comments are greatly appreciated.

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