metawards.mixers.InteractionMatrix

class metawards.mixers.InteractionMatrix(n: int, value: float = 0.0)

This is an interaction matrix, which is used to control how the FOIs of different demographics are merged together.

An interaction matrix is just a square matrix, with a list[][] being perfectly acceptable. This is really a convenience class that makes it easier to create more complex interaction matrixes

__init__(n: int, value: float = 0.0)

Construct an interaction matrix that is n x n in size, where all values equal ‘value’

Methods

__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__(i)	Return the ith row of the matrix
__gt__(value, /)	Return self>value.
__init__(n[, value])	Construct an interaction matrix that is n x n in size, where all values equal 'value'
__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)
__reduce__()	Helper for pickle.
__reduce_ex__(protocol, /)	Helper for pickle.
__repr__()	Return repr(self).
__setattr__(name, value, /)	Implement setattr(self, name, value).
__setitem__(i, row)	"Set the ith row of the matrix equal to 'row'
__sizeof__()	Size of object in memory, in bytes.
__str__()	Return str(self).
__subclasshook__	Abstract classes can override this to customize issubclass().
detach(n)	Detach the 'nth' demographic from interacting with any other demographics.
diagonal(n[, value, off_diagonal])	Return a n x n matrix where each diagonal element equals 'value' and each off-diagonal element equals 'off_diagonal'
identity(n[, value, off_diagonal])	Return a n x n matrix where each diagonal element equals 'value' and each off-diagonal element equals 'off_diagonal'
ones(n[, value])	Return a n x n matrix where each element equals 'value'
resize(n[, value])	Resize this matrix to 'n x n', adding in extra values equal to 'value' if needed
zeroes(n[, value])	Return a n x n matrix where each element equals 'value'

Attributes

__dict__
__doc__
__hash__
__module__
__weakref__	list of weak references to the object (if defined)

__eq__(other)

Return self==value.

__getitem__(i: int)

Return the ith row of the matrix

__hash__ = None

__init__(n: int, value: float = 0.0)

Construct an interaction matrix that is n x n in size, where all values equal ‘value’

__setitem__(i: int, row: List[int])

“Set the ith row of the matrix equal to ‘row’

__str__()

Return str(self).

detach(n: int)

Detach the ‘nth’ demographic from interacting with any other demographics. This sets the ith row and ith column equal to zero (which not changing m[n][n])

static diagonal(n: int, value: float = 1.0, off_diagonal: float = 0.0)

Return a n x n matrix where each diagonal element equals ‘value’ and each off-diagonal element equals ‘off_diagonal’

static identity(n: int, value: float = 1.0, off_diagonal: float = 0.0)

Return a n x n matrix where each diagonal element equals ‘value’ and each off-diagonal element equals ‘off_diagonal’

static ones(n: int, value: float = 1.0)

Return a n x n matrix where each element equals ‘value’

resize(n: int, value: float = 0.0)

Resize this matrix to ‘n x n’, adding in extra values equal to ‘value’ if needed

static zeroes(n: int, value: float = 0.0)

Return a n x n matrix where each element equals ‘value’