reno.components.Scalar

class reno.components.Scalar(value)

Bases: EquationPart

A static, single value equation part, representing some simple value that doesn’t need to be computed.

Parameters:

value (int | float | np.ndarray) – The scalar value to use.

Methods

__init__(value)
clip(min, max)
equal(obj)
eval([t, save, force])	No compute necessary, just get the previously specified value.
find_refs_of_type(search_type[, already_checked])	Actually recursive as opposed to seek_refs, returns a list of all equation parts matching passed type.
get_shape()	For now this is returning an integer because we only allow a single additional dimension.
get_type()	Similar to shape, this gets computed recursively, used to automatically determine if the value needs to be initialized with a certain numpy type.
is_static()	Convenience shortcut for reno.utils.is_static() - True if this equation doesn't rely on any dynamic values (thus constant), False if it does.
latex(**kwargs)	Construct a string representation of this portion of the equation for use in a latex display.
not_equal(obj)
pt(**refs)	Get a pytensor graph representing this piece of an equation.
pt_str(**refs)	Construct a string containing relevant pytensor code for this piece of the equation.
seek_refs()	Immediate refs only, depth=1.
series_max()
series_min()
sum([axis])

Attributes

dtype	The type of each underlying value.
shape	The size of the data dimension, 1 by default.
timeseries	Get a timeseries view of the data (includes all historical data across all timesteps.)

__annotations__ = {}

__module__ = 'reno.components'

__repr__()

Return repr(self).

eval(t=0, save=False, force=False, **kwargs)

No compute necessary, just get the previously specified value. (And likely use it in the rest of the equation.)

Parameters:

• t (int)

• save (bool)

• force (bool)

Return type:

int | float | ndarray

get_shape()

For now this is returning an integer because we only allow a single additional dimension. Note that this shape _does not_ incoporate time or batch dimensions, only the “data” dimension if applicable. This should be overridden by subclasses, e.g. operations which would change the shape.

Return type:

int

get_type()

Similar to shape, this gets computed recursively, used to automatically determine if the value needs to be initialized with a certain numpy type.

Return type:

type

pt(**refs)

Get a pytensor graph representing this piece of an equation.

Parameters:

refs (dict[str, TensorVariable])

Return type:

TensorVariable

pt_str(**refs)

Construct a string containing relevant pytensor code for this piece of the equation. This is useful for “compiling” into pymc code.

Parameters:

refs (dict[str, str])

Return type:

str