Change n_iter to max_iter in TSNE parameters

[miltoncamacho]

Updates the argument for sklearn.manifold.TSNE from n_iter to max_iter.

Closes #1275

[codecov[bot]]

Codecov Report

:x: Patch coverage is 71.42857% with 2 lines in your changes missing coverage. Please review. :white_check_mark: Project coverage is 89.83%. Comparing base (ac50072) to head (e75d656). :warning: Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
tedana/decomposition/ica.py	71.42%	1 Missing and 1 partial :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1276      +/-   ##
==========================================
- Coverage   89.86%   89.83%   -0.04%     
==========================================
  Files          29       29              
  Lines        4383     4389       +6     
  Branches      725      726       +1     
==========================================
+ Hits         3939     3943       +4     
- Misses        295      296       +1     
- Partials      149      150       +1     

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[eurunuela]

What is the new minimum version after this change? What version of sklearn made the change? We have to make sure that's reflected in pyproject.toml.

[miltoncamacho]

The version of sklearn is 1.8.0, but the test fails because scikit-learn 1.8.0 requires python version >=3.11 and tedana only need >=3.9. Is this something we feel is doable?

  × No solution found when resolving dependencies for split (markers:
  │ python_full_version == '3.10.*'):
  ╰─▶ Because the requested Python version (>=3.9) does not satisfy
      Python>=3.11 and scikit-learn==1.8.0 depends on Python>=3.11, we can
      conclude that scikit-learn==1.8.0 cannot be used.
      And because only scikit-learn<=1.8.0 is available, we can conclude that
      scikit-learn>=1.8.0 cannot be used.
      And because your project depends on scikit-learn>=1.8.0 and your project
      requires tedana[all], we can conclude that your project's requirements

[tsalo]

fMRIPrep builds on 3.10 so we won't want to increase our minimum Python version above that. I don't know what the situation is with AFNI.

[tsalo]

For now, I recommend checking the sklearn version and modifying the parameter name based on that.

[tsalo]

The changes look good to me. I just made a couple of suggestions to hopefully address the linter errors.