diff options
Diffstat (limited to 'resources/libraries/python/PLRsearch/Integrator.py')
-rw-r--r-- | resources/libraries/python/PLRsearch/Integrator.py | 55 |
1 files changed, 43 insertions, 12 deletions
diff --git a/resources/libraries/python/PLRsearch/Integrator.py b/resources/libraries/python/PLRsearch/Integrator.py index 035afd848c..86181eaa56 100644 --- a/resources/libraries/python/PLRsearch/Integrator.py +++ b/resources/libraries/python/PLRsearch/Integrator.py @@ -28,13 +28,31 @@ from numpy import random # TODO: Teach FD.io CSIT to use multiple dirs in PYTHONPATH, # then switch to absolute imports within PLRsearch package. # Current usage of relative imports is just a short term workaround. -import stat_trackers # pylint: disable=relative-import +from . import stat_trackers def try_estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False): - """Call estimate_nd but catch any exception and send traceback.""" + """Call estimate_nd but catch any exception and send traceback. + + This function does not return anything, computation result + is sent via the communication pipe instead. + + TODO: Move scale_coeff to a field of data class + with constructor/factory hiding the default value, + and receive its instance via pipe, instead of argument. + + :param communication_pipe: Endpoint for communication with parent process. + :param scale_coeff: Float number to tweak convergence speed with. + :param trace_enabled: Whether to emit trace level debugs. + Keeping trace disabled improves speed and saves memory. + Enable trace only when debugging the computation itself. + :type communication_pipe: multiprocessing.Connection + :type scale_coeff: float + :type trace_enabled: bool + :raises BaseException: Anything raised by interpreter or estimate_nd. + """ try: - return estimate_nd(communication_pipe, scale_coeff, trace_enabled) + estimate_nd(communication_pipe, scale_coeff, trace_enabled) except BaseException: # Any subclass could have caused estimate_nd to stop before sending, # so we have to catch them all. @@ -46,7 +64,22 @@ def try_estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False): def generate_sample(averages, covariance_matrix, dimension, scale_coeff): - """Generate next sample for estimate_nd""" + """Generate next sample for estimate_nd. + + Arguments control the multivariate normal "focus". + Keep generating until the sample point fits into unit area. + + :param averages: Coordinates of the focus center. + :param covariance_matrix: Matrix controlling the spread around the average. + :param dimension: If N is dimension, average is N vector and matrix is NxN. + :param scale_coeff: Coefficient to conformally multiply the spread. + :type averages: Indexable of N floats + :type covariance_matrix: Indexable of N indexables of N floats + :type dimension: int + :type scale_coeff: float + :returns: The generated sample point. + :rtype: N-tuple of float + """ covariance_matrix = copy.deepcopy(covariance_matrix) for first in range(dimension): for second in range(dimension): @@ -142,13 +175,12 @@ def estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False): In they are not enabled, trace_list will be empty. It is recommended to edit some lines manually to debug_list if needed. - :param communication_pipe: Pipe to comunicate with boss process. + :param communication_pipe: Endpoint for communication with parent process. :param scale_coeff: Float number to tweak convergence speed with. :param trace_enabled: Whether trace list should be populated at all. - Default: False - :type communication_pipe: multiprocessing.Connection (or compatible) + :type communication_pipe: multiprocessing.Connection :type scale_coeff: float - :type trace_enabled: boolean + :type trace_enabled: bool :raises OverflowError: If one sample dominates the rest too much. Or if value_logweight_function does not handle some part of parameter space carefully enough. @@ -201,10 +233,9 @@ def estimate_nd(communication_pipe, scale_coeff=8.0, trace_enabled=False): while not communication_pipe.poll(): if max_samples and samples >= max_samples: break - sample_point = generate_sample(param_focus_tracker.averages, - param_focus_tracker.covariance_matrix, - dimension, - scale_coeff) + sample_point = generate_sample( + param_focus_tracker.averages, param_focus_tracker.covariance_matrix, + dimension, scale_coeff) trace("sample_point", sample_point) samples += 1 trace("samples", samples) |