gemseo / caches

simple_cache module¶

Caching module to store only one entry.

class gemseo.caches.simple_cache.SimpleCache(tolerance=0.0, name=None)[source]¶

Bases: AbstractCache

Dictionary-based cache storing a unique entry.

Parameters:

tolerance (float) –
The tolerance below which two input arrays are considered equal: norm(new_array-cached_array)/(1+norm(cached_array)) <= tolerance. If this is the case for all the input names, then the cached output data shall be returned rather than re-evaluating the discipline. This tolerance could be useful to optimize CPU time. It could be something like 2 * numpy.finfo(float).eps.

By default it is set to 0.0.
name (str | None) – A name for the cache. If None, use the class name.

class Group(value)¶

Bases: StrEnum

A data group.

INPUTS = 'inputs'¶: The label for the input variables.

JACOBIAN = 'jacobian'¶: The label for the Jacobian.

OUTPUTS = 'outputs'¶: The label for the output variables.

cache_jacobian(input_data, jacobian_data)[source]¶

Cache the input and Jacobian data.

Parameters:

input_data (DataMapping) – The data containing the input data to cache.
jacobian_data (JacobianData) – The Jacobian data to cache.

Return type:

None

cache_outputs(input_data, output_data)[source]¶

Cache input and output data.

Parameters:

input_data (DataMapping) – The data containing the input data to cache.
output_data (DataMapping) – The data containing the output data to cache.

Return type:

None

clear()[source]¶

Clear the cache.

Return type:: None

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

get_all_entries()[source]¶

Return an iterator over all the entries.

The tolerance is ignored.

Yields:: The entries.
Return type:: Iterator[CacheEntry]

items() → a set-like object providing a view on D's items¶

keys() → a set-like object providing a view on D's keys¶

to_dataset(name='', categorize=True, input_names=(), output_names=())¶

Build a Dataset from the cache.

Parameters:

name (str) –
A name for the dataset. If empty, use the name of the cache.

By default it is set to “”.
categorize (bool) –
Whether to distinguish between the different groups of variables. Otherwise, group all the variables in Dataset.PARAMETER_GROUP`.

By default it is set to True.
input_names (Iterable[str]) –
The names of the inputs to be exported. If empty, use all the inputs.

By default it is set to ().
output_names (Iterable[str]) –
The names of the outputs to be exported. If empty, use all the outputs. If an output name is also an input name, the output name is suffixed with [out].

By default it is set to ().

Returns:

A dataset version of the cache.

Return type:

Dataset

values() → an object providing a view on D's values¶

property input_names: list[str]¶: The names of the inputs of the last entry.

property last_entry: CacheEntry¶: The last cache entry.

name: str¶: The name of the cache.

property names_to_sizes: dict[str, int]¶

The sizes of the variables of the last entry.

For a Numpy array, its size is used. For a container, its length is used. Otherwise, a size of 1 is used.

property output_names: list[str]¶: The names of the outputs of the last entry.

tolerance: float¶: The tolerance below which two input arrays are considered equal.

Examples using SimpleCache¶

Simple cache