hyperspy.utils.parallel_pool module¶

class hyperspy.utils.parallel_pool.ParallelPool(num_workers=None, ipython_kwargs=None, ipyparallel=None)¶

Creates a ParallelPool by either looking for a ipyparallel client and then creating a load_balanced_view, or by creating a multiprocessing pool

has_pool¶

Boolean if the pool is available and active.

pool¶

The pool object.

ipython_kwargs¶

The dictionary with Ipyparallel connection arguments.

timeout¶

Timeout for either pool when waiting for results.

num_workers¶

The number of workers actually created (may be less than requested, but can’t be more).

timestep¶

Can be used as “ticks” to adjust CPU load when building upon this class.

is_ipyparallel¶

If the pool is ipyparallel-based

is_multiprocessing¶

If the pool is multiprocessing-based

Creates the ParallelPool and sets it up.

Parameters

num_workers ({None, int}) – the (max) number of workers to create. If less are available, smaller number is actually created.
ipyparallel ({None, bool}) – which pool to set up. True - ipyparallel. False - multiprocessing. None - try ipyparallel, then multiprocessing if failed.
ipython_kwargs ({None, dict}) – arguments that will be passed to the ipyparallel.Client when creating. Not None implies ipyparallel=True.

property is_multiprocessing: Returns bool if the pool is multiprocessing-based

setup(ipyparallel=None)

Sets up the pool.

Parameters: ipyparallel ({None, bool}) – if True, only tries to set up the ipyparallel pool. If False - only the multiprocessing. If None, first tries ipyparallel, and it does not succeed, then multiprocessing.

sleep(howlong=None)

Sleeps for the required number of seconds.

Parameters: howlong ({None, float}) – How long the pool should sleep for in seconds. If None (default), sleeps for “timestep”