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Some use-cases of function subtyping

Currently, numba functions display a lot of behaviours expected from true first-class functions. There are, however, 3 behaviours which we see as useful and are currently missing:

1. iterating over a sequence of functions
2. avoiding re-compilation of higher-order functions
3. ability to cache higher-order functions

iterating over a sequence of functions

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This line comes from the test code, right before the function is executed.

Type of tuple in test code Tuple(type(CPUDispatcher(<function TestBasicSubtyping.test_basic4.<locals>.foo1 at 0x7fdc32df7400>)), type(CPUDispatcher(<function TestBasicSubtyping.test_basic4.<locals>.foo2 at 0x7fdc32df7488>)))  code:  1566

This line comes from _intern. the tuple is created and assigned 1568 as typecode

Creating new tuple  
	 Type: Tuple(type(CPUDispatcher(<function TestBasicSubtyping.test_basic4.<locals>.foo1 at 0x7fdc32df7400>)), type(CPUDispatcher(<function TestBasicSubtyping.test_basic4.<locals>.foo2 at 0x7fdc32df7488>))) 
 id: 140583722982144 

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def gen_bw_bridge(steps, W, n):
    """
    Given a column vector of end values, it will create n brownian bridge
    simulations per value for the amount of steps as defined.
    Can be easily generalized to include random initial values
    and more general start and end times

    steps: integer, how many time intervals there will be 
            between 0 and 1
    W: (sims, 1) nump vector with end values of brownian motion