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Cleaning up docstrings for new tally arithmetic routines in tallies.py
This commit is contained in:
Will Boyd
parent
7bc104b21b
commit
9c9eb446a1
6 changed files with 252 additions and 193 deletions
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@ -369,7 +369,7 @@
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"text/plain": [
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"<IPython.core.display.Image object>"
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]
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@ -580,7 +580,7 @@
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" License: http://mit-crpg.github.io/openmc/license.html\n",
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" Version: 0.7.0\n",
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" Git SHA1: e0c2aace2e73367536fa03e153b67a2d038cd2b3\n",
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" Date/Time: 2015-10-02 23:48:55\n",
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" Date/Time: 2015-10-03 00:24:54\n",
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" MPI Processes: 1\n",
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"\n",
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" ===========================================================================\n",
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@ -636,20 +636,20 @@
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"\n",
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" =======================> TIMING STATISTICS <=======================\n",
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"\n",
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" Total time for initialization = 5.7300E-01 seconds\n",
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" Reading cross sections = 1.2700E-01 seconds\n",
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" Total time in simulation = 2.1409E+01 seconds\n",
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" Time in transport only = 2.1383E+01 seconds\n",
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" Time in inactive batches = 2.7630E+00 seconds\n",
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" Time in active batches = 1.8646E+01 seconds\n",
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" Time synchronizing fission bank = 2.0000E-03 seconds\n",
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" Sampling source sites = 2.0000E-03 seconds\n",
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" SEND/RECV source sites = 0.0000E+00 seconds\n",
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" Total time for initialization = 7.0100E-01 seconds\n",
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" Reading cross sections = 1.5800E-01 seconds\n",
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" Total time in simulation = 2.0485E+01 seconds\n",
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" Time in transport only = 2.0465E+01 seconds\n",
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" Time in inactive batches = 3.0920E+00 seconds\n",
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" Time in active batches = 1.7393E+01 seconds\n",
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" Time synchronizing fission bank = 5.0000E-03 seconds\n",
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" Sampling source sites = 4.0000E-03 seconds\n",
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" SEND/RECV source sites = 1.0000E-03 seconds\n",
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" Time accumulating tallies = 0.0000E+00 seconds\n",
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" Total time for finalization = 1.0000E-03 seconds\n",
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" Total time elapsed = 2.1994E+01 seconds\n",
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" Calculation Rate (inactive) = 4524.07 neutrons/second\n",
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" Calculation Rate (active) = 2011.16 neutrons/second\n",
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" Total time elapsed = 2.1200E+01 seconds\n",
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" Calculation Rate (inactive) = 4042.69 neutrons/second\n",
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" Calculation Rate (active) = 2156.04 neutrons/second\n",
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"\n",
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" ============================> RESULTS <============================\n",
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"\n",
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@ -33,42 +33,42 @@ class StatePoint(object):
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each batch
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cmfd_src : ndarray
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CMFD fission source distribution over all mesh cells and energy groups.
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current_batch : int
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current_batch : Integral
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Number of batches simulated
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date_and_time : str
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Date and time when simulation began
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entropy : ndarray
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Shannon entropy of fission source at each batch
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gen_per_batch : int
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gen_per_batch : Integral
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Number of fission generations per batch
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global_tallies : ndarray of compound datatype
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Global tallies for k-effective estimates and leakage. The compound
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datatype has fields 'name', 'sum', 'sum_sq', 'mean', and 'std_dev'.
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k_combined : list
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Combined estimator for k-effective and its uncertainty
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k_col_abs : float
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k_col_abs : Real
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Cross-product of collision and absorption estimates of k-effective
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k_col_tra : float
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k_col_tra : Real
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Cross-product of collision and tracklength estimates of k-effective
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k_abs_tra : float
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k_abs_tra : Real
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Cross-product of absorption and tracklength estimates of k-effective
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k_generation : ndarray
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Estimate of k-effective for each batch/generation
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meshes : dict
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Dictionary whose keys are mesh IDs and whose values are Mesh objects
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n_batches : int
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n_batches : Integral
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Number of batches
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n_inactive : int
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n_inactive : Integral
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Number of inactive batches
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n_particles : int
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n_particles : Integral
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Number of particles per generation
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n_realizations : int
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n_realizations : Integral
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Number of tally realizations
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path : str
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Working directory for simulation
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run_mode : str
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Simulation run mode, e.g. 'k-eigenvalue'
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seed : int
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seed : Integral
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Pseudorandom number generator seed
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source : ndarray of compound datatype
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Array of source sites. The compound datatype has fields 'wgt', 'xyz',
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@ -80,7 +80,7 @@ class StatePoint(object):
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Dictionary whose keys are tally IDs and whose values are Tally objects
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tallies_present : bool
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Indicate whether user-defined tallies are present
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version: tuple of int
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version: tuple of Integral
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Version of OpenMC
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summary : None or openmc.summary.Summary
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A summary object if the statepoint has been linked with a summary file
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@ -487,7 +487,7 @@ class StatePoint(object):
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A list of Nuclide objects (default is []).
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name : str, optional
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The name specified for the Tally (default is None).
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id : int, optional
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id : Integral, optional
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The id specified for the Tally (default is None).
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estimator: str, optional
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The type of estimator ('tracklength', 'analog'; default is None).
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@ -543,6 +543,8 @@ class StatePoint(object):
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for filter in filters:
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contains_filters = False
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# Test if requested filter is a subset of any of the test
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# tally's filters and if so continue to next filter
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for test_filter in test_tally.filters:
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if test_filter.is_subset(filter):
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contains_filters = True
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@ -82,7 +82,7 @@ class Summary(object):
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# Create the Material
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material = openmc.Material(material_id=material_id, name=name)
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# Set the Material's density to g/cm3 - this is what is used in OpenMC
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# Set the Material's density to atom/b-cm as used by OpenMC
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material.set_density(density=density, units='atom/b-cm')
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# Add all nuclides to the Material
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@ -34,7 +34,7 @@ class Tally(object):
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Parameters
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----------
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tally_id : int, optional
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tally_id : Integral, optional
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Unique identifier for the tally. If none is specified, an identifier
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will automatically be assigned
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name : str, optional
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@ -42,7 +42,7 @@ class Tally(object):
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Attributes
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----------
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id : int
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id : Integral
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Unique identifier for the tally
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name : str
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Name of the tally
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@ -56,17 +56,17 @@ class Tally(object):
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Type of estimator for the tally
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triggers : list of openmc.trigger.Trigger
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List of tally triggers
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num_score_bins : int
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num_score_bins : Integral
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Total number of scores, accounting for the fact that a single
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user-specified score, e.g. scatter-P3 or flux-Y2,2, might have multiple
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bins
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num_scores : int
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num_scores : Integral
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Total number of user-specified scores
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num_filter_bins : int
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num_filter_bins : Integral
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Total number of filter bins accounting for all filters
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num_bins : int
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num_bins : Integral
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Total number of bins for the tally
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num_realizations : int
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num_realizations : Integral
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Total number of realizations
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with_summary : bool
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Whether or not a Summary has been linked
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@ -743,7 +743,7 @@ class Tally(object):
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filter_type : str
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The type of Filter (e.g., 'cell', 'energy', etc.)
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filter_bin : int, tuple
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filter_bin : Integral or tuple
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The bin is an integer ID for 'material', 'surface', 'cell',
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'cellborn', and 'universe' Filters. The bin is an integer for the
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cell instance ID for 'distribcell' Filters. The bin is a 2-tuple of
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@ -842,11 +842,36 @@ class Tally(object):
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return score_index
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def get_filter_indices(self, filters=[], filter_bins=[]):
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"""
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"""Get indices into the filter axis of this tally's data arrays.
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This is a helper routine for the Tally.get_values(...) routine to
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extract tally data. This routine returns the indices into the filter
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axis of the tally's data array (axis=0) for particular combinations
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of filters and their corresponding bins.
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Parameters
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----------
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filters : list of str
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A list of filter type strings
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(e.g., ['mesh', 'energy']; default is [])
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filter_bins : list of Iterables
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A list of the filter bins corresponding to the filter_types
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parameter (e.g., [(1,), (0., 0.625e-6)]; default is []). Each bin
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in the list is the integer ID for 'material', 'surface', 'cell',
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'cellborn', and 'universe' Filters. Each bin is an integer for the
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cell instance ID for 'distribcell' Filters. Each bin is a 2-tuple of
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floats for 'energy' and 'energyout' filters corresponding to the
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energy boundaries of the bin of interest. The bin is a (x,y,z)
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3-tuple for 'mesh' filters corresponding to the mesh cell of
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interest. The order of the bins in the list must correspond to the
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filter_types parameter.
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Returns
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-------
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ndarray
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A NumPy array of the filter indices
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:param filters:
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:param filter_bins:
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:return:
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"""
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cv.check_iterable_type('filters', filters, basestring)
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@ -882,10 +907,11 @@ class Tally(object):
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for k in range(filter.num_bins):
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bins.append((filter.bins[k], filter.bins[k+1]))
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# Create list of cell instance IDs for distribcell Filters
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elif filter.type == 'distribcell':
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bins = np.arange(filter.num_bins)
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# Create list of IDs for bins for all other Filter types
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# Create list of IDs for bins for all other filter types
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else:
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bins = filter.bins
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@ -911,10 +937,23 @@ class Tally(object):
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return filter_indices
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def get_nuclide_indices(self, nuclides):
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"""
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"""Get indices into the nuclide axis of this tally's data arrays.
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This is a helper routine for the Tally.get_values(...) routine to
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extract tally data. This routine returns the indices into the nuclide
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axis of the tally's data array (axis=1) for one or more nuclides.
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Parameters
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----------
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nuclides : list of str
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A list of nuclide name strings
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(e.g., ['U-235', 'U-238']; default is [])
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Returns
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-------
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ndarray
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A NumPy array of the nuclide indices
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:param nuclides:
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:return:
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"""
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cv.check_iterable_type('nuclides', nuclides, basestring)
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@ -932,10 +971,23 @@ class Tally(object):
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return nuclide_indices
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def get_score_indices(self, scores):
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"""
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"""Get indices into the score axis of this tally's data arrays.
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This is a helper routine for the Tally.get_values(...) routine to
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extract tally data. This routine returns the indices into the score
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axis of the tally's data array (axis=2) for one or more scores.
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Parameters
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----------
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scores : list of str
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A list of one or more score strings
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(e.g., ['absorption', 'nu-fission']; default is [])
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Returns
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-------
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ndarray
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A NumPy array of the score indices
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:param scores:
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:return:
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"""
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cv.check_iterable_type('scores', scores, basestring)
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@ -954,19 +1006,20 @@ class Tally(object):
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def get_values(self, scores=[], filters=[], filter_bins=[],
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nuclides=[], value='mean'):
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"""Returns a tally score value given a list of filters to satisfy.
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"""Returns one or more tallied values given a list of scores, filters,
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filter bins and nuclides.
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This method constructs a 3D NumPy array for the requested Tally data
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indexed by filter bin, nuclide bin, and score index. The method will
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order the data in the array as specified in the parameter lists
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order the data in the array as specified in the parameter lists.
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Parameters
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----------
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scores : list
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scores : list of str
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A list of one or more score strings
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(e.g., ['absorption', 'nu-fission']; default is [])
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filters : list
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filters : list of str
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A list of filter type strings
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(e.g., ['mesh', 'energy']; default is [])
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@ -982,7 +1035,7 @@ class Tally(object):
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interest. The order of the bins in the list must correspond to the
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filter_types parameter.
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nuclides : list
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nuclides : list of str
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A list of nuclide name strings
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(e.g., ['U-235', 'U-238']; default is [])
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@ -1121,7 +1174,7 @@ class Tally(object):
|
|||
# Build DataFrame columns for filters if user requested them
|
||||
if filters:
|
||||
|
||||
# Append each Filter's DataFRame to the overall DataFrame
|
||||
# Append each Filter's DataFrame to the overall DataFrame
|
||||
for filter in self.filters:
|
||||
filter_df = filter.get_pandas_dataframe(data_size, summary)
|
||||
|
||||
|
|
@ -1192,7 +1245,7 @@ class Tally(object):
|
|||
suppose this tally has arrays of data with shape (8,5,5) corresponding
|
||||
to two filters (2 and 4 bins, respectively), five nuclides and five
|
||||
scores. This routine will return a version of the data array with the
|
||||
with a new shape of (2,4,5,5) such that the first two dimensions now
|
||||
with a new shape of (2,4,5,5) such that the first two dimensions
|
||||
correspond directly to the two filters with two and four bins.
|
||||
|
||||
Parameters
|
||||
|
|
@ -1203,9 +1256,8 @@ class Tally(object):
|
|||
|
||||
Returns
|
||||
-------
|
||||
float or ndarray
|
||||
A scalar or NumPy array of the Tally data indexed in the order
|
||||
each filter, nuclide and score is listed in the parameters.
|
||||
ndarray
|
||||
The tally data array indexed by filters, nuclides and scores.
|
||||
|
||||
"""
|
||||
|
||||
|
|
@ -1388,7 +1440,7 @@ class Tally(object):
|
|||
Returns
|
||||
-------
|
||||
Tally
|
||||
A new Tally outer that is the outer product with this one.
|
||||
A new Tally that is the outer product with this one.
|
||||
|
||||
Raises
|
||||
------
|
||||
|
|
@ -1408,15 +1460,17 @@ class Tally(object):
|
|||
new_tally.with_batch_statistics = True
|
||||
new_tally._derived = True
|
||||
|
||||
# Construct a combined derived name from the two tally operands
|
||||
if self.name != '' and other.name != '':
|
||||
new_name = '({0} {1} {2})'.format(self.name, binary_op, other.name)
|
||||
new_tally.name = new_name
|
||||
|
||||
# FIXME: Align filters
|
||||
# Find any shared filters between the two tallies
|
||||
self_filters = set(self.filters)
|
||||
other_filters = set(other.filters)
|
||||
filter_intersect = self_filters.intersection(other_filters)
|
||||
|
||||
# Align the shared filters to follow in each tally operand
|
||||
for i, filter in enumerate(filter_intersect):
|
||||
self_index = self.filters.index(filter)
|
||||
other_filter = other.filters[self_index]
|
||||
|
|
@ -1461,12 +1515,15 @@ class Tally(object):
|
|||
if self.num_realizations == other.num_realizations:
|
||||
new_tally.num_realizations = self.num_realizations
|
||||
|
||||
# Generate filter "outer products"
|
||||
# If filters are identical, simply reuse them in derived tally
|
||||
if self.filters == other.filters:
|
||||
for self_filter in self.filters:
|
||||
new_tally.add_filter(self_filter)
|
||||
|
||||
# Generate filter "outer products" for non-identical filters
|
||||
else:
|
||||
|
||||
# Find the common longest sequence of shared filters
|
||||
match = 0
|
||||
for self_filter, other_filter in zip(self.filters, other.filters):
|
||||
if self_filter == other_filter:
|
||||
|
|
@ -1477,11 +1534,11 @@ class Tally(object):
|
|||
match_filters = self.filters[:match]
|
||||
cross_filters = [self.filters[match:], other.filters[match:]]
|
||||
|
||||
# FIXME: This must be the common longest sequence of tallies at the beginning
|
||||
|
||||
# Simply reuse shared filters in derived tally
|
||||
for filter in match_filters:
|
||||
new_tally.add_filter(filter)
|
||||
|
||||
# Use cross filters to combine non-shared filters in derived tally
|
||||
if len(self.filters) != match and len(other.filters) == match:
|
||||
for filter in cross_filters[0]:
|
||||
new_tally.add_filter(filter)
|
||||
|
|
@ -1523,94 +1580,6 @@ class Tally(object):
|
|||
|
||||
return new_tally
|
||||
|
||||
def swap_filters(self, filter1, filter2):
|
||||
"""
|
||||
|
||||
:param filter1:
|
||||
:param filter2:
|
||||
:return:
|
||||
"""
|
||||
|
||||
# Check that results have been read
|
||||
if not self.derived and self.sum is None:
|
||||
msg = 'Unable to use tally arithmetic with Tally ID="{0}" ' \
|
||||
'since it does not contain any results.'.format(self.id)
|
||||
raise ValueError(msg)
|
||||
|
||||
cv.check_type('filter1', filter1, Filter)
|
||||
cv.check_type('filter2', filter2, Filter)
|
||||
|
||||
if filter1 == filter2:
|
||||
msg = 'Unable to swap a filter with itself'
|
||||
raise ValueError(msg)
|
||||
elif filter1 not in self.filters:
|
||||
msg = 'Unable to swap "{0}" filter1 in Tally ID="{1}" since it ' \
|
||||
'does not contain such a filter'.format(filter1.type, self.id)
|
||||
raise ValueError(msg)
|
||||
elif filter2 not in self.filters:
|
||||
msg = 'Unable to swap "{0}" filter2 in Tally ID="{1}" since it ' \
|
||||
'does not contain such a filter'.format(filter2.type, self.id)
|
||||
raise ValueError(msg)
|
||||
|
||||
swap_tally = copy.deepcopy(self)
|
||||
|
||||
# Swap the filters in the copied version of this Tally
|
||||
filter1_index = swap_tally.filters.index(filter1)
|
||||
filter2_index = swap_tally.filters.index(filter2)
|
||||
swap_tally.filters[filter1_index] = filter2
|
||||
swap_tally.filters[filter2_index] = filter1
|
||||
|
||||
# Update the strides for each of the filters
|
||||
stride = swap_tally.num_nuclides * swap_tally.num_score_bins
|
||||
for filter in reversed(swap_tally.filters):
|
||||
filter.stride = stride
|
||||
stride *= filter.num_bins
|
||||
|
||||
filters = [filter1.type, filter2.type]
|
||||
if filter1.type == 'distribcell':
|
||||
filter1_bins = np.arange(filter.num_bins)
|
||||
else:
|
||||
filter1_bins = [(filter1.get_bin(i)) for i in range(filter1.num_bins)]
|
||||
|
||||
if filter1.type == 'distribcell':
|
||||
filter2_bins = np.arange(filter2.num_bins)
|
||||
else:
|
||||
filter2_bins = [filter2.get_bin(i) for i in range(filter2.num_bins)]
|
||||
|
||||
if self.sum is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='sum')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally.sum[indices, :, :] = data
|
||||
|
||||
if self.sum_sq is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='sum_sq')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally.sum_sq[indices, :, :] = data
|
||||
|
||||
if self.sum is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='mean')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally._mean[indices, :, :] = data
|
||||
|
||||
if self.sum is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='std_dev')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally._std_dev[indices, :, :] = data
|
||||
|
||||
return swap_tally
|
||||
|
||||
def _align_tally_data(self, other):
|
||||
"""Aligns data from two tallies for tally arithmetic.
|
||||
|
||||
|
|
@ -1727,6 +1696,94 @@ class Tally(object):
|
|||
data['other']['std. dev.'] = other_std_dev
|
||||
return data
|
||||
|
||||
def swap_filters(self, filter1, filter2):
|
||||
"""
|
||||
|
||||
:param filter1:
|
||||
:param filter2:
|
||||
:return:
|
||||
"""
|
||||
|
||||
# Check that results have been read
|
||||
if not self.derived and self.sum is None:
|
||||
msg = 'Unable to use tally arithmetic with Tally ID="{0}" ' \
|
||||
'since it does not contain any results.'.format(self.id)
|
||||
raise ValueError(msg)
|
||||
|
||||
cv.check_type('filter1', filter1, Filter)
|
||||
cv.check_type('filter2', filter2, Filter)
|
||||
|
||||
if filter1 == filter2:
|
||||
msg = 'Unable to swap a filter with itself'
|
||||
raise ValueError(msg)
|
||||
elif filter1 not in self.filters:
|
||||
msg = 'Unable to swap "{0}" filter1 in Tally ID="{1}" since it ' \
|
||||
'does not contain such a filter'.format(filter1.type, self.id)
|
||||
raise ValueError(msg)
|
||||
elif filter2 not in self.filters:
|
||||
msg = 'Unable to swap "{0}" filter2 in Tally ID="{1}" since it ' \
|
||||
'does not contain such a filter'.format(filter2.type, self.id)
|
||||
raise ValueError(msg)
|
||||
|
||||
swap_tally = copy.deepcopy(self)
|
||||
|
||||
# Swap the filters in the copied version of this Tally
|
||||
filter1_index = swap_tally.filters.index(filter1)
|
||||
filter2_index = swap_tally.filters.index(filter2)
|
||||
swap_tally.filters[filter1_index] = filter2
|
||||
swap_tally.filters[filter2_index] = filter1
|
||||
|
||||
# Update the strides for each of the filters
|
||||
stride = swap_tally.num_nuclides * swap_tally.num_score_bins
|
||||
for filter in reversed(swap_tally.filters):
|
||||
filter.stride = stride
|
||||
stride *= filter.num_bins
|
||||
|
||||
filters = [filter1.type, filter2.type]
|
||||
if filter1.type == 'distribcell':
|
||||
filter1_bins = np.arange(filter.num_bins)
|
||||
else:
|
||||
filter1_bins = [(filter1.get_bin(i)) for i in range(filter1.num_bins)]
|
||||
|
||||
if filter1.type == 'distribcell':
|
||||
filter2_bins = np.arange(filter2.num_bins)
|
||||
else:
|
||||
filter2_bins = [filter2.get_bin(i) for i in range(filter2.num_bins)]
|
||||
|
||||
if self.sum is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='sum')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally.sum[indices, :, :] = data
|
||||
|
||||
if self.sum_sq is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='sum_sq')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally.sum_sq[indices, :, :] = data
|
||||
|
||||
if self.sum is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='mean')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally._mean[indices, :, :] = data
|
||||
|
||||
if self.sum is not None:
|
||||
for bin1, bin2 in itertools.product(filter1_bins, filter2_bins):
|
||||
filter_bins = [(bin1,), (bin2,)]
|
||||
data = self.get_values(filters=filters,
|
||||
filter_bins=filter_bins, value='std_dev')
|
||||
indices = swap_tally.get_filter_indices(filters, filter_bins)
|
||||
swap_tally._std_dev[indices, :, :] = data
|
||||
|
||||
return swap_tally
|
||||
|
||||
def __add__(self, other):
|
||||
"""Adds this tally to another tally or scalar value.
|
||||
|
||||
|
|
@ -2422,7 +2479,7 @@ class Tally(object):
|
|||
Returns
|
||||
-------
|
||||
Tally
|
||||
A new Tally outer that is the outer product with this one.
|
||||
A new Tally that is the outer product with this one.
|
||||
|
||||
"""
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue