metawards.Demographics¶
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class
metawards.Demographics(demographics: List[metawards._demographic.Demographic] = <factory>, random_seed: Optional[int] = None, interaction_matrix: Optional[List[List[int]]] = None, _names: Dict[str, int] = <factory>, _name: Optional[str] = None, _version: Optional[str] = None, _authors: Optional[str] = None, _contacts: Optional[str] = None, _references: Optional[str] = None, _filename: Optional[str] = None, _repository: Optional[str] = None, _repository_version: Optional[str] = None, _repository_branch: Optional[str] = None)[source]¶ This class holds metadata about all of the demographics being modelled
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__init__(demographics: List[metawards._demographic.Demographic] = <factory>, random_seed: Optional[int] = None, interaction_matrix: Optional[List[List[int]]] = None, _names: Dict[str, int] = <factory>, _name: Optional[str] = None, _version: Optional[str] = None, _authors: Optional[str] = None, _contacts: Optional[str] = None, _references: Optional[str] = None, _filename: Optional[str] = None, _repository: Optional[str] = None, _repository_version: Optional[str] = None, _repository_branch: Optional[str] = None) → None¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__add__(other)__delattr__(name, /)Implement delattr(self, name).
__dir__()Default dir() implementation.
__eq__(other)Return self==value.
__format__(format_spec, /)Default object formatter.
__ge__(value, /)Return self>=value.
__getattribute__(name, /)Return getattr(self, name).
__getitem__(item)__gt__(value, /)Return self>value.
__init__([demographics, random_seed, …])Initialize self.
__init_subclass__This method is called when a class is subclassed.
__le__(value, /)Return self<=value.
__len__()__lt__(value, /)Return self<value.
__ne__(value, /)Return self!=value.
__new__(**kwargs)Create and return a new object.
__radd__(other)__reduce__()Helper for pickle.
__reduce_ex__(protocol, /)Helper for pickle.
__repr__()Return repr(self).
__setattr__(name, value, /)Implement setattr(self, name, value).
__sizeof__()Size of object in memory, in bytes.
__str__()Return str(self).
__subclasshook__Abstract classes can override this to customize issubclass().
add(demographic)Add a demographic to the set to be modelled
build(params[, population, max_nodes, …])Build the set of networks described by these demographics and the passed parameters
copy()Return a copy of this demographics object that should allow a safe reset between runs.
from_data(data[, json_dir])Construct and return a Demographics object constructed from a (json-deserialised) data dictionary
from_json(s)Construct and return Demographics loaded from the passed json file
get_index(item)Return the index of the passed item
get_name(item)Return the name of the demographic at ‘item’
Return whether or not these demographics need to use multiple custom networks (e.g.
load([name, repository, folder, filename])Load the parameters for the specified set of demographics.
specialise(network[, profiler, nthreads])Build the set of networks that will model this set of demographics applied to the passed Network.
to_data()Return a data dictionary for this object that can be serialised to json
to_json([filename, indent, auto_bzip])Serialise the Demographics to JSON.
Return whether or not at least one of these demographics specifies the use of a named network model
Attributes
__annotations____dataclass_fields____dataclass_params____dict____doc____hash____module____weakref__list of weak references to the object (if defined)
_authors_contacts_filename_name_references_repository_repository_branch_repository_version_versionThe interaction matrix between demographics.
The random seed to used when using any random number generator to resolve decisions needed when allocating individuals to demographics.
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add(demographic: metawards._demographic.Demographic)[source]¶ Add a demographic to the set to be modelled
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build(params: Parameters, population: Population = None, max_nodes: int = 16384, max_links: int = 4194304, nthreads: int = 1, profiler: Profiler = None) → _Union[Network, Networks][source]¶ Build the set of networks described by these demographics and the passed parameters
- Parameters
params (Parameters) – Parameters used to help build the model networks
max_nodes (int) – Initial guess for the maximum number of nodes(wards)
max_links (int) – Initial guess for the maximum number of links between wards
profiler (Profiler) – Profiler used to profile the specialisation
nthreads (int) – Number of threads over which to parallelise the work
- Returns
The set of Networks that represent the model run over the full set of different demographics(or Network if there is just a single demographic)
- Return type
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copy()[source]¶ Return a copy of this demographics object that should allow a safe reset between runs. This deepcopies things that may change, while shallow copying things that won’t
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demographics: List[metawards._demographic.Demographic]¶ The list of individual Demographic objects, one for each demographic being modelled
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static
from_data(data, json_dir=None) → metawards._demographics.Demographics[source]¶ Construct and return a Demographics object constructed from a (json-deserialised) data dictionary
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static
from_json(s: str)[source]¶ Construct and return Demographics loaded from the passed json file
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interaction_matrix: List[List[int]] = None¶ The interaction matrix between demographics. This should be a list of lists that shows how demographic ‘i’ affects demographic ‘j’
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is_multi_network()[source]¶ Return whether or not these demographics need to use multiple custom networks (e.g. refer to different network models)
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static
load(name: Optional[str] = None, repository: Optional[str] = None, folder: str = 'demographics', filename: Optional[str] = None)[source]¶ Load the parameters for the specified set of demographics. This will look for a file called f”{name}.json” in the directory f”{repository}/{folder}/{name}.json”
By default this will load nothing.
Alternatively you can provide the full path to the json file via the “filename” argument
- Parameters
name (str) – The name of the demographics to load. This is the name that will be searched for in the METAWARDSDATA diseases directory
repository (str) – The location of the cloned METAWARDSDATA repository
folder (str) – The name of the folder within the METAWARDSDATA repository that contains the diseases
filename (str) – The name of the file to load the disease from - this directly loads this file without searching through the METAWARDSDATA repository
- Returns
demographics – The constructed and validated demographics
- Return type
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random_seed: int = None¶ The random seed to used when using any random number generator to resolve decisions needed when allocating individuals to demographics. This is set here so that the Demographics are uniquely determined and reproducible across runs
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specialise(network: Network, profiler: Profiler = None, nthreads: int = 1)[source]¶ Build the set of networks that will model this set of demographics applied to the passed Network.
- Parameters
- Returns
networks – The set of Networks that represent the model run over the full set of different demographics
- Return type
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to_json(filename: Optional[str] = None, indent: Optional[int] = None, auto_bzip: bool = True) → str[source]¶ Serialise the Demographics to JSON. This will write to a file if filename is set, otherwise it will return a JSON string.
- Parameters
filename (str) – The name of the file to write the JSON to. The absolute path to the written file will be returned. If filename is None then this will serialise to a JSON string which will be returned.
indent (int) – The number of spaces of indent to use when writing the json
auto_bzip (bool) – Whether or not to automatically bzip2 the written json file
- Returns
Returns either the absolute path to the written file, or the json-serialised string
- Return type
str
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