-Cleaned up and optimized the initializing process to work faster
-"ranged" has the default value of [0,1] now
-"ranged" parameter now also accepts dictionary as the argument where the keys are the feature names and the values are the ranges desired to get random numbers from
python
randomData = FMatrix([250000,4],
ranged={"feat1":[0,100],
"feat2":[50,75],
"feat3":[-100,100],
"feat4":[5,10]
})
Should take ~1500ms to create 250000x4 float valued matrix
-Square matrix creation optimized
python
randomData = FMatrix(1000) Should take ~150ms
randomData = Matrix(1000) Should take ~650ms
-CMatrix is added but not fully stable and doesn't support all the methods Matrix class has yet
python
randomData = CMatrix(1000) Should take ~1100ms
-Added more properties (Check [README.md](https://github.com/MathStuff/MatricesM/blob/master/README.md))
-Bug fixes
[PyPI page](https://pypi.org/project/MatricesM/)