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.
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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
-
build_model()[source]
Build model with original sizes for input and output variables.
-
compute_bounds()[source]
Compute lower and upper bounds of both input and output variables.
- Returns
lower bounds, upper bounds.
- Return type
dict, dict
-
normalize_data()[source]
Normalize dataset from lower and upper bounds.
-
scalable_derivatives(input_value=None)[source]
Evaluate the scalable derivatives.
- Parameters
input_value (dict) –
input values.
If None, use default inputs. Default: None
By default it is set to None.
- Returns
evaluation of the scalable derivatives.
- Return type
dict
-
scalable_function(input_value=None)[source]
Evaluate the scalable function.
- Parameters
input_value (dict) –
input values.
If None, use default inputs. Default: None.
By default it is set to None.
- Returns
evaluation of the scalable function.
- Return type
dict
-
ABBR = 'sm'
-
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)
