pg_utils.pg_model.expansion.RadialExpansions

class pg_utils.pg_model.expansion.RadialExpansions(fields: LabeledCollection, bases: LabeledCollection, coeffs: LabeledCollection, **relations: Expr)

Bases: SpectralExpansion

Radial expansions, a collection of radial expansions for each field in the collection of dynamical variables.

In many (even most) spectral expansions, each field, or each component of the tensor are expanded using the same bases, only with different coefficients.

For PG applications, two complications arise:

• As we expand the elements of tensors, it would be desirable to implement different forms of bases for each individual field, so that the regularity constraints are fulfilled;

• we potentially have a mixture of quantities expressed in cylindrical and spherical coordinates.

The first point is tackled by using different bases and different relations, hence this class assumes a collection of basis.

__init__(fields: LabeledCollection, bases: LabeledCollection, coeffs: LabeledCollection, **relations: Expr) → None

Methods

__init__(fields, bases, coeffs, **relations)
apply(fun[, inplace, metadata])	Apply a function iteratively to all collection items
as_empty()	Return an object with the same configuration of attributes but with fields initiated as None.
copy()	Returns a deep copy of itself
deserialize(obj[, parser])	Deserialize an object
generate_collection(index_array)	Generate a new collection based on indices
load_json(fp[, parser])	Load LabeledCollection object from json
save_json(fp[, serializer])	Serialize the object in string format and save to json file
serialize([serializer])	Serialize the object
subs(sub_map[, inplace])	Substitute variables iteratively in all fields.

Attributes

iter_filter	iter_filter: bool determines whether None fields are skipped.
iter_name	iter_name: bool determines whether the string of the field is also returned.

apply(fun: Callable[[...], Any], inplace: bool = False, metadata: bool = False) → LabeledCollection

Apply a function iteratively to all collection items

Parameters:

• fun (Callable) – determines how the collection entries are processed. The signature of the function should take the form fun(type(self[i])) when metadata is False, and the form fun(str, type(self[i])) when metadata is True

• inplace (bool) – whether to write changes in situ.

• metadata (bool) – whether to pass field name to the function

Returns:

Updated object. If inplace, then the current object itself is returned.

Return type:

LabeledCollection

as_empty() → LabeledCollection

Return an object with the same configuration of attributes but with fields initiated as None. May be slightly faster than copy?

copy() → LabeledCollection

Returns a deep copy of itself

static deserialize(obj: ~typing.List[tuple], parser: ~typing.Callable[[str], ~typing.Any] = <function LabeledCollection.<lambda>>) → LabeledCollection

Deserialize an object

Parameters:

• obj (List[tuple]) – a serialized object of LabeledCollection

• parser (Callable[[str], Any]) – a parser that defines how each string can be parsed into meaningful objects

Returns:

LabeledCollection, that is deserialized from the input object

Warning

Sanitized input needed. Unexpected behaviour if input is not a legitimate serialized object

generate_collection(index_array: List[bool]) → LabeledCollection

Generate a new collection based on indices

Parameters:

index_array (List[bool]) – array of booleans indicating whether a field is to be included in the new collection

Returns:

new collection with elements specified by index_array

property iter_filter

iter_filter: bool determines whether None fields are skipped.

property iter_name

iter_name: bool determines whether the string of the field is also returned.

static load_json(fp: ~typing.TextIO, parser: ~typing.Callable[[str], ~typing.Any] = <function LabeledCollection.<lambda>>) → LabeledCollection

Load LabeledCollection object from json

convenient wrapper for deserialize

save_json(fp: ~typing.TextIO, serializer: ~typing.Callable[[~typing.Any], str] = <class 'str'>) → None

Serialize the object in string format and save to json file

Parameters:

• fp (TextIO) – file handle of the output file

• serializer (Callable[[Any], str]) – a callable that maps an element to a string. Default is the str method.

serialize(serializer: ~typing.Callable[[~typing.Any], str] = <class 'str'>) → List[tuple]

Serialize the object

Parameters:

serializer (Callable[[Any],str]) – a callable that maps an element to a string. Default is the str method.

Returns:

a list of serialized objects, in the format [(fname_1, serialized_element_1), (fname_2, serialized_element_2), …]

subs(sub_map: dict, inplace: bool = False)

Substitute variables iteratively in all fields. This utility is for collections with sympy.Expr elements. See warning below.

Parameters:

• sub_map (dict) – a substitution map

• inplace (bool) – whether the change is made in place; default is False

Warning

To use this method, all elements in the collection need to have implemented the subs method. This is intended for a collection of which all elements are sympy.Expr type. Then, this method calls apply internally to substitute all the variables.