1 files changed, 0 insertions, 52 deletions
diff --git a/plip/basic/parallel.py b/plip/basic/parallel.py
deleted file mode 100644
index 1f71943..0000000
--- a/plip/basic/parallel.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import itertools
-import multiprocessing
-from builtins import zip
-from functools import partial
-
-from numpy import asarray
-
-
-class SubProcessError(Exception):
-    def __init__(self, e, exitcode=1):
-        self.exitcode = exitcode
-        super(SubProcessError, self).__init__(e)
-
-    pass
-
-
-def universal_worker(input_pair):
-    """This is a wrapper function expecting a tiplet of function, single
-       argument, dict of keyword arguments. The provided function is called
-       with the appropriate arguments."""
-    function, arg, kwargs = input_pair
-    return function(arg, **kwargs)
-
-
-def pool_args(function, sequence, kwargs):
-    """Return a single iterator of n elements of lists of length 3, given a sequence of len n."""
-    return zip(itertools.repeat(function), sequence, itertools.repeat(kwargs))
-
-
-def parallel_fn(f):
-    """Simple wrapper function, returning a parallel version of the given function f.
-       The function f must have one argument and may have an arbitray number of
-       keyword arguments. """
-
-    def simple_parallel(func, sequence, **args):
-        """ f takes an element of sequence as input and the keyword args in **args"""
-        if 'processes' in args:
-            processes = args.get('processes')
-            del args['processes']
-        else:
-            processes = multiprocessing.cpu_count()
-
-        pool = multiprocessing.Pool(processes)  # depends on available cores
-
-        result = pool.map_async(universal_worker, pool_args(func, sequence, args))
-        pool.close()
-        pool.join()
-        cleaned = [x for x in result.get() if x is not None]  # getting results
-        cleaned = asarray(cleaned)
-        return cleaned
-
-    return partial(simple_parallel, f)