latqcdtools.base.speedify

compile(func)

numbaList(inList)

Turn a list into List that numba can parse. 

numbaOFF()

Turn off numba compilation for small functions. 

numbaON()

Use numba wherever possible. By default it is turned off, since compilation takes some time,
and hence you will only see a performance boost for particularly long-running functions. Must be
called at the beginning of your code. 

parallel_function_eval(function, input_array, args=(), nproc=6, parallelizer='pathos.pools')

Parallelize a function over an input_array. Effectively this can replace a loop over an array and should
lead to a performance boost.

Args:
    function (func): to-be-parallelized function 
    input_array (array-like): array over which it should run 
    nproc (int): number of processes 

Returns:
    array-like: func(input_array)

parallel_reduce(function, input_array, args=(), nproc=6, parallelizer='pathos.pools') -> float

Parallelize a function over an input_array, then sum over the input_array elements. 

Args:
    function (func): to-be-parallelized function 
    input_array (array-like): array over which it should run 
    nproc (int): number of processes 

Returns:
    float

ComputationClass(function, input_array, args, nproc, parallelizer)