postprocessor.core.processes.dsignal.dsignalParameters

class dsignalParameters(**kwargs)[source]

Bases: ParametersABC

Window

Number of timepoints to consider for signal.

Methods

from_yaml(source)

Returns instance from a yaml filename or stdin

to_dict([iterable])

Recursive function to return a nested dictionary of the attributes of the class instance.

to_yaml([path])

Returns a yaml stream of the attributes of the class instance.

update(name, new_value)

Update values recursively if name is a dictionary, replace data where existing found or add if not.

default

from_dict

Defines parameters as attributes

Methods

from_yaml(source)

Returns instance from a yaml filename or stdin

to_dict([iterable])

Recursive function to return a nested dictionary of the attributes of the class instance.

to_yaml([path])

Returns a yaml stream of the attributes of the class instance.

update(name, new_value)

Update values recursively if name is a dictionary, replace data where existing found or add if not.

default

from_dict

__init__(**kwargs)

Defines parameters as attributes

Methods

__init__(**kwargs)

Defines parameters as attributes

default(**kwargs)

from_dict(d)

from_yaml(source)

Returns instance from a yaml filename or stdin

to_dict([iterable])

Recursive function to return a nested dictionary of the attributes of the class instance.

to_yaml([path])

Returns a yaml stream of the attributes of the class instance.

update(name, new_value)

Update values recursively if name is a dictionary, replace data where existing found or add if not.

classmethod from_yaml(source)

Returns instance from a yaml filename or stdin

to_dict(iterable='null')

Recursive function to return a nested dictionary of the attributes of the class instance.

Return type

Dict

to_yaml(path=None)

Returns a yaml stream of the attributes of the class instance. If path is provided, the yaml stream is saved there.

Parameters
pathUnion[Path, str]

Output path.

update(name, new_value)

Update values recursively if name is a dictionary, replace data where existing found or add if not. It warns against type changes.

If the existing structure under name is a dictionary, it looks for the first occurrence and modifies it accordingly.

If a leaf node that is to be changed is a collection, it adds the new elements.