armi.reactor.parameters.parameterDefinitions module

This module contains the code necessary to represent parameter definitions.

ParameterDefinitions are the metadata that describe specific parameters, and aid in enforcing certain rules upon the parameters themselves and the parameter collections that contain them.

This module also describes the ParameterDefinitionCollection class, which serves as a specialized container to manage related parameter definitions.

class armi.reactor.parameters.parameterDefinitions.Category[source]

Bases: object

A “namespace” for storing parameter categories.

Notes

  • cumulative parameters are accumulated over many time steps

  • pinQuantities parameters are defined on the pin level within a block

  • multiGroupQuantities parameters have group dependence (often a 1D numpy array)

  • fluxQuantities parameters are related to neutron or gamma flux

  • neutronics parameters are calculated in a neutronics global flux solve

  • gamma parameters are calculated in a fixed-source gamma solve

  • detailedAxialExpansion parameters are marked as such so that they are mapped from the

    uniform mesh back to the non-uniform mesh

  • reactivity coefficients parameters are related to reactivity coefficient or kinetics

    parameters for kinetics solutions

  • thermal hydraulics parameters come from a thermal hydraulics physics plugin (e.g., flow

    rates, temperatures, etc.)

depletion = 'depletion'
cumulative = 'cumulative'
cumulativeOverCycle = 'cumulative over cycle'
assignInBlueprints = 'assign in blueprints'
retainOnReplacement = 'retain on replacement'
pinQuantities = 'pinQuantities'
fluxQuantities = 'fluxQuantities'
multiGroupQuantities = 'multi-group quantities'
neutronics = 'neutronics'
gamma = 'gamma'
detailedAxialExpansion = 'detailedAxialExpansion'
reactivityCoefficients = 'reactivity coefficients'
thermalHydraulics = 'thermal hydraulics'
class armi.reactor.parameters.parameterDefinitions.ParamLocation(value)[source]

Bases: Flag

Represents the point on which a parameter is physically meaningful.

TOP = 1
CENTROID = 2
BOTTOM = 4
AVERAGE = 10
MAX = 16
CORNERS = 32
EDGES = 64
VOLUME_INTEGRATED = 128
CHILDREN = 256
class armi.reactor.parameters.parameterDefinitions.NoDefault[source]

Bases: object

Class used to allow distinction between not setting a default and setting a default of None.

class armi.reactor.parameters.parameterDefinitions.Serializer[source]

Bases: object

Abstract class describing serialize/deserialize operations for Parameter data.

Parameters need to be stored to and read from database files. This currently requires that the Parameter data be converted to a numpy array of a datatype supported by the h5py package. Some parameters may contain data that are not trivially representable in numpy/HDF5, and need special treatment. Subclassing Serializer and setting it as a Parameters serializer allows for special operations to be performed on the parameter values as they are stored to the database or read back in.

The Database already knows how to handle certain cases where the data are not straightforward to get into a numpy array, such as when:

  • There are Nones.

  • The dimensions of the values stored on each object are inconsistent (e.g., “jagged” arrays)

So, in these cases, a Serializer is not needed. Serializers are necessary for when the actual data need to be converted to a native data type (e.g., int, float, etc). For example, we use a Serializer to handle writing Flags to the Database, as they tend to be too big to fit into a system-native integer.

Important

Defining a Serializer for a Parameter in part defines the underlying representation of the data within a database file; the data stored in a database are sensitive to the code that wrote them. Changing the method that a Serializer uses to pack or unpack data may break compatibility with old database files. Therefore, Serializers should be diligent about signaling changes by updating their version. It is also good practice, whenever possible, to support reading old versions so that database files written by old versions can still be read.

version: Optional[str] = None
static pack(data: Sequence[any]) Tuple[ndarray, Dict[str, any]][source]

Given unpacked data, return packed data and a dictionary of attributes needed to unpack it.

This should perform the fundamental packing operation, returning the packed data and any metadata (“attributes”) that would be necessary to unpack the data. The class’s version is always stored, so no need to provide it as an attribute.

See also

armi.reactor.flags.FlagSerializer.pack

classmethod unpack(data: ndarray, version: Any, attrs: Dict[str, any]) Sequence[any][source]

Given packed data and attributes, return the unpacked data.

armi.reactor.parameters.parameterDefinitions.isNumpyArray(paramStr)[source]

Helper meta-function to create a method that sets a Parameter value to a NumPy array.

Parameters:

paramStr (str) – Name of the Parameter we want to set.

Returns:

A setter method on the Parameter class to force the value to be a NumPy array.

Return type:

function

class armi.reactor.parameters.parameterDefinitions.Parameter(name, units, description, location, saveToDB, default, setter, categories, serializer: Optional[Type[Serializer]] = None)[source]

Bases: object

Metadata about a specific parameter.

collectionType
name
fieldName
location
saveToDB
serializer
description
units
default
categories
assigned
setter(setter)[source]

Decorator method for assigning setter.

Notes

Unlike the traditional Python property class, this does not return a new instance of a Parameter; therefore it cannot be reassigned in the same way that a Python property can be.

Examples

>>> class MyParameterCollection(parameters.ParameterCollection):
...     mass = parameters.Parameter(...)
...     @mass.setter
...     def mass(self, value):
...         if value < 0:
...             raise ValueError("Negative mass is not possible, consider a diet.")
...         self._p_speed = value
backUp()[source]

Back up the assigned state.

restoreBackup(paramsToApply)[source]

Restore the backed up state.

atLocation(loc)[source]

True if parameter is defined at location.

hasCategory(category: str) bool[source]

True if a parameter has a specific category.

class armi.reactor.parameters.parameterDefinitions.ParameterDefinitionCollection[source]

Bases: object

A very specialized container for managing parameter definitions.

Notes

_representedTypes is used to detect if this ParameterDefinitionCollection contains definitions for only one type. If the collection only exists for 1 type, the lookup (__getitem__) can short circuit O(n) logic for O(1) dictionary lookup.

add(paramDef)[source]

Add a Parameter to this collection.

items()[source]
extend(other)[source]

Grow a parameter definition collection by another parameter definition collection.

inCategory(categoryName)[source]

Create a ParameterDefinitionCollection that contains definitions that are in a specific category.

atLocation(paramLoc)[source]

Make a param definition collection with all defs defined at a specific location.

Parameters can be defined at various locations within their container based on ParamLocation. This allows selection by those values.

since(mask)[source]

Create a ParameterDefinitionCollection that contains definitions that have been modified since a specific set of actions.

unchanged_since(mask)[source]

Create a ParameterDefinitionCollection that contains definitions that have not been modified since a specific set of actions. This is the complementary set of the collection returned by since.

forType(compositeType)[source]

Create a ParameterDefinitionCollection that contains definitions for a specific composite type.

resetAssignmentFlag(mask)[source]

Clear the assigned flag for a certain operation on all parameters.

These flags will get set by the param definition setters if they get changed again.

Notes

See http://www.vipan.com/htdocs/bitwisehelp.html to understand the bitwise operations

setAssignmentFlag(mask)[source]
byNameAndType(name, compositeType)[source]

Get a Parameter by compositeType and name.

byNameAndCollectionType(name, collectionType)[source]

Get a Parameter by collectionType and name.

property categories

Get the categories of all the Parameter instances within this collection.

property names
lock()[source]
property locked
toWriteToDB(assignedMask: Optional[int] = None)[source]

Get a list of acceptable parameters to store to the database for a level of the data model.

Parameters:

assignedMask (int) – A bitmask to down-filter which params to use based on how “stale” they are.

createBuilder(*args, **kwargs)[source]

Create an associated object that can create definitions into this collection.

Using the returned ParameterBuilder will add all defined parameters to this ParameterDefinitionCollection, using the passed arguments as defaults. Arguments should be valid arguments to ParameterBuilder.__init__()

class armi.reactor.parameters.parameterDefinitions.ParameterBuilder(location=ParamLocation.AVERAGE, default=<class 'armi.reactor.parameters.parameterDefinitions.NoDefault'>, categories=None, saveToDB=True)[source]

Bases: object

Factory for creating Parameter and parameter properties.

Create a ParameterBuilder.

associateParameterDefinitionCollection(paramDefs)[source]

Associate this parameter factory with a specific ParameterDefinitionCollection.

Subsequent calls to defParam will automatically add the created ParameterDefinitions to this ParameterDefinitionCollection. This results in a cleaner syntax when defining many ParameterDefinitions.

defParam(name, units, description, location=None, saveToDB=<class 'armi.reactor.parameters.parameterDefinitions.NoDefault'>, default=<class 'armi.reactor.parameters.parameterDefinitions.NoDefault'>, setter=<class 'armi.reactor.parameters.parameterDefinitions.NoDefault'>, categories=None, serializer: ~typing.Optional[~typing.Type[~armi.reactor.parameters.parameterDefinitions.Serializer]] = None)[source]

Create a parameter as a property (with get/set) on a class.

Parameters:
  • name (str) – the official name of the parameter

  • units (str) – string representation of the units

  • description (str) – a brief, but precise-as-possible description of what the parameter is used for.

  • location (str) – string representation of the location the attribute is applicable to, such as average, max, etc.

  • saveToDB (bool) – indicator as to whether the parameter should be written to the database. The actual default is defined by the ParameterBuilder, and is True.

  • default (immutable type) – a default value for this parameter which must be an immutable type. If the type is mutable, e.g. a list, dict, an exception should be raised, or unknown behavior.

  • setter (None or callable) – If None, there is no direct way to set the parameter. If some other callable method, (which may have the same name as the property!) then the setter method is used instead.

  • categories (List of str) – A list of categories to which this Parameter should belong. Categories are typically used to engage special treatment for certain Parameters.

  • serializer (Optional subclass of Serializer) – A class describing how the parameter data should be stored to the database. This is usually only needed in exceptional cases where it is difficult to store a parameter in a numpy array.

Notes

It is not possible to initialize the parameter on the class this method would be used on, because there is no instance (i.e. self) when this method is run. However, this method could access a globally available set of definitions, if one existed.