model module¶
Scalable model¶
This module implements the abstract concept of scalable model which is used by scalable disciplines. A scalable model is built from a input-output learning dataset associated with a function and generalizing its behavior to a new user-defined problem dimension, that is to say new user-defined input and output dimensions.
The concept of scalable model is implemented
through ScalableModel
, an abstract class which is instantiated from:
data provided as a
Dataset
variables sizes provided as a dictionary whose keys are the names of inputs and outputs and values are their new sizes. If a variable is missing, its original size is considered.
Scalable model parameters can also be filled in. Otherwise the model uses default values.
See also
The ScalableDiagonalModel
class overloads ScalableModel
.
Classes:
|
Scalable model. |
- class gemseo.problems.scalable.data_driven.model.ScalableModel(data, sizes=None, **parameters)[source]¶
Bases:
object
Scalable model.
Constructor.
- Parameters
data (Dataset) – learning dataset.
sizes (dict) –
sizes of input and output variables. If None, use the original sizes. Default: None.
By default it is set to None.
parameters – model parameters
Attributes:
Inputs names.
Original sizes of variables.
Outputs names.
Methods:
Build model with original sizes for input and output variables.
Compute lower and upper bounds of both input and output variables.
Normalize dataset from lower and upper bounds.
scalable_derivatives
([input_value])Evaluate the scalable derivatives.
scalable_function
([input_value])Evaluate the scalable function.
- ABBR = 'sm'¶
- compute_bounds()[source]¶
Compute lower and upper bounds of both input and output variables.
- Returns
lower bounds, upper bounds.
- Return type
dict, dict
- property inputs_names¶
Inputs names.
- Returns
names of the inputs.
- Return type
list(str)
- property original_sizes¶
Original sizes of variables.
- Returns
original sizes of variables.
- Return type
dict
- property outputs_names¶
Outputs names.
- Returns
names of the outputs.
- Return type
list(str)