Fix basic optimization example unknown arguments issues

[IanBoyanZhang]

Description

Remove verbose and print_step arguments when calling GlobalBestPSO optimizer in multiple examples and docs.

Related Issue

Fixing outdated examples and documents issues reported in issue 264 and in issue 317.

Motivation and Context

Thank you for providing great open source project.

Was trying to run inverse kinematics example and basic optimization example jupyter notebook. Original examples complain unexpected keyword argument errors for verbose and print_step.

I haven't gone through the solver source code, hopefully this is the right fix that is inline with author's intention.

How Has This Been Tested?

Ran basic_optimization jupyter notebook locally.

Screenshots (if appropriate):

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)

Checklist:

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.
• I have read the CONTRIBUTING document.
• I have added tests to cover my changes.
• All new and existing tests passed.

[ljvmiranda921]

LGTM! Thank you for your contribution @IanBoyanZhang !

[ljvmiranda921]

@allcontributors[bot] please add @IanBoyanZhang for docs and examples

[allcontributors]

@ljvmiranda921

I've put up a pull request to add @IanBoyanZhang! 🎉

[bhaskatripathi]

Your BinaryPSO with the objective function mentioned in the documentation doesn't works. It returns an n-dimensional array instead of [1 0 0 01 01...etc]
Please correct get that fixed too as it is better to not give examples of running code than giving incorrect/outdated ones

[ljvmiranda921]

HI @bhaskatripathi , can you point the specific part of the documentation where it does not work? I've already tested what's working on this link and it gives the correct output as expected.