=================================================================================== 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
- Go to the Build directory.
- 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:
- Go to the Testing directory
- Run the following command: python3 demo.py
Sample input file: 2 # Number of dimensions 0.0 0.0 # initial values
1.0 - x[0] - x[1] >= 0.0
The following standard python libraries must be installed (if not already exist):
- pathlib
- numdifftools
- scipy
- numpy
To compile the code: Linux
- cd Build
- python3 run.py <input_file> <output_file> <N_results> Example: python3 run.py input.txt output.txt 100
Windows
- Go to the Build directory.
- Open run.py with Eclipse, Visual Studio or other compatible environment
- Go to Run, the Run configurations from the menu-bar (for Eclipse)
- Go to the Arguments tab and paste the following:
-
<input_file> <output_file> <N_results>
Example: python3 run.py input.txt output.txt 100 6. Click to Run the testcase
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.