reno.components.Metric

class reno.components.Metric(eq=None, label=None)

Bases: Reference

An equation for a measurement or observation on the overall simulation.

These run in a separate after-simulation analysis.

Generally intended to be a series aggregate type equation (e.g. using series_min/series_max/sum on slices of values across time from references computed during the simulation etc.

Methods

__init__([eq, label])	Create a metric equation node.
astype(dtype)	Returns a symbolic operation to convert the output of this equation to the specified type.
clip(min, max)	Returns a symbolic operation for enforcing the output is between the passed min and max.
debug_equation(t[, sample])	Get a latex string output with the debug version of this equation.
equal(obj)	Returns a symbolic operation for checking equality with passed object.
equation(**kwargs)	Get the representation of the full equation for the metric as a latex string.
eval([t, save, force])	Compute the equation for the given timestep.
find_parts_of_type(search_type[, ...])	Recursively search for all EquationParts in the tree of the specified type.
from_dict(data, refs)	Deserialize reference and parse data from dictionary previously saved from to_dict().
get_shape()	Get the size of the additional "data" dimension.
get_type()	Get the type of the target output of this equation expression.
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)	String representation suitable for a latex display.
mean([axis])	Returns a symbolic operation to find the series-wise mean of the array.
not_equal(obj)	Returns a symbolic operation for checking inequality with passed object.
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.
qual_name([dot])	Get a string with both the model and the reference name if this model is a submodel of something else.
seek_refs([include_ref_types])	Recursively find a list of all References immediately underneath this part.
series_max()	Returns a symbolic operation to find the series-wise maximum of the array.
series_min()	Returns a symbolic operation to find the series-wise minimum of the array.
sum([axis])	Returns a symbolic operation to find the series-wise sum of the array.
to_dict()	Serialize class into a dictionary for saving to file.

Attributes

dtype	The type of each underlying value.
shape	The size of the data dimension, 1 by default.
timeseries	Returns symbolic operation for getting a timeseries view of the data.
model	Keep a reference to container model, makes it easier to compare refs across multiple models.
label	Label is what's used in any visual representation (e.g. allows spaces where name does not.).
doc	A docstring to explain/describe the reference.

Parameters:

• eq (EquationPart)

• label (str)

__annotations__ = {}

__module__ = 'reno.components'

__repr__()

Return repr(self).

Return type:

str

__setattr__(name, value)

Implement setattr(self, name, value).

Parameters:

• name (str)

• value (Any)

debug_equation(t, sample=0, **kwargs)

Get a latex string output with the debug version of this equation.

Parameters:

• t (int)

• sample (int)

• kwargs (dict)

Return type:

str

equation(**kwargs)

Get the representation of the full equation for the metric as a latex string.

Parameters:

kwargs (dict)

Return type:

str

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

Compute the equation for the given timestep.

Parameters:

• t (int)

• save (bool)

• force (bool)

• kwargs (dict)

Return type:

int | float | ndarray

from_dict(data, refs)

Deserialize reference and parse data from dictionary previously saved from to_dict().

Parameters:

• data (dict)

• refs (dict[str, TrackedReference])

Return type:

None

model

Keep a reference to container model, makes it easier to compare refs across multiple models.

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

qual_name(dot=False)

Get a string with both the model and the reference name if this model is a submodel of something else.

This is primarily used for helping distinguish things in a multimodel setup.

Parameters:

dot (bool)

Return type:

str

to_dict()

Serialize class into a dictionary for saving to file.

Return type:

dict