### Running Sample Problems

Source: https://github.com/theclimatecorporation/dfo-algorithm/blob/master/README.md

This module allows users to run a set of sample problems to test the DFO algorithm and other integrated optimization methods.

```python
import run_test_func

# To run a set of sample problems, the user can call the
# “run_test_func.py” module.
```

--------------------------------

### Solving a User-Defined Problem

Source: https://github.com/theclimatecorporation/dfo-algorithm/blob/master/README.md

This section outlines the steps to solve a user-defined blackbox optimization problem. It involves creating a Python module for the optimization function and a run file to configure and execute the chosen algorithms.

```python
# 1. Write your blackbox optimization function in a new Python module.
#    For examples of such functions see blackbox_opt/test_funcs/funcs_def.py

# 2. Write a run file with the module you wrote in the previous step imported.
#    You can modify the run_test_func.py module and use it as your run file.
#    Note that you should specify the algorithms(s) that you wish to solve
#    your problems with, a starting point and suitable options.
```

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