1) The initialization now accepts "general" inputs that should apply to each gene. For example, rather than a gene input of [1,100] being interpreted to mean gene 1 hsould be 1 and gene 2 should be 100, it will apply a range of [1,100] to each gene.
2) The initialization now accepts "general" gene_input_types. For example, if the user had a set of index-dependent number values, they could just say ga.gene_input_type = "domain" and the package will propagate that across all genes in the chromosome. The user still has the option of defining the entire array or just defining a specific element if they so choose. For later commits, the general gene_input_type will have to be checked for validity; for example, a string can never be a range.
3) Fixed an issue in the ordering of the initialization function call.
4) Added comments surrounding the signfiicant changes to the initialization.
5) Added example tests to the testing file.
Random gene initialization now supports float ranges (assumed by default if gene input includes float). Backend was also optimized and cleaned up greatly.
Updated the check of incoming data to ensure validity - if the user enters a single digit, say "5", it will automatically be converted to a list like [5,5]. This already worked before with range, but it now works with domain as well.
In the initial commit, string inputs would implicitly be seen as domain, and all integer inputs would be seen as range. If the user wanted to assign any integer inputs as domain, they would have to call the entire gene_input_type, even if only to change a single element to domain. It has now been updated to where the user can specifically call the element they want to update. The testing file new_initialization_method_testing.py reflects this.
