numpy.net | A port of NumPy to .Net | Data Manipulation library

Unlike most NumPy implementations, our library does not require the GIL (Global Interpreter Lock). This allows us to offer a fully multi-threaded library. You are free to launch as many threads as you want to manipulate our ndarray objects. If your application can take advantage of that, you may be able to achieve much higher overall performance. Take note that if multiple threads are manipulating the same ndarray object, you may get unexpected results. For example, if one thread is adding numbers and another thread is dividing, you may get unexpected calculations. The original authors of NumPy did a fine job of isolating arrays from each other to make this feature possible. If you must manipulate the same ndarray from two different threads, it may be necessary to implement some sort of application layer locking on the ndarray object to get the expected results. We have ported the original "RandomState" random number generator and most of the distributions associated with that. Seed values produce the same exact output as python which should make porting applications easier. Our version is implemented as an instantiable class, each with independent random engines so it can be used in multi-threaded applications. NEW FEATURE! We now support user defined random number generators. Implement a interface class with your generator and pass that to the random constructor and use that to generate random numbers in all of the supported distributions. We have implemented the numpy histogram API. https://numpy.org/doc/stable/reference/routines.statistics.html. We have implemented the latest numpy financial API with full support of decimal data types. https://numpy.org/numpy-financial/latest/.