v0.0.2post1: Add support of selecting different from subsets proportionately (#270)

* Use numpy to count the unique number of labels for efficiency

* Add support of selection different cluster subsets proportionately

* Add tests for the proportional selection

* Fix the problem of when zero number of elements selected from the minority class

* Add tests for imbalance case of multiple classes

* Add testing data for imbalance cases

* Reformat with black

* Add data points to smallest cluster when not enough data points

* Add test for checking the number of labels match the number of total data points

* Ignore NotImplementedError in coverage report

* Add typing hints for returns

* Add typing hints