_Strategy

class simrun.modular_reduced_model_inference.strategy._Strategy(name)

Strategy base class.

This class is used to define a strategy for the optimizer. Each strategy sets up all necessary components to define a single cost function get_score(). This cost function is used by a simrun.modular_reduced_model_inference.solver to optimize the parameters of the strategy.

Each child class must implement a _get_score class method. These are used here to construct get_score(). It is this get_score method that is optimized during optimization.

As a function of the parameters, compute a value for each trial. The optimizer will optimize for this value (highest AUROC score)

Needs some repr for input data.

E.G. A strategy that needs to optimize for AP refractory, then the Strategy needs to incorporate this data

Parameters:
name : str

The name of the strategy.

Methods:

_get_score(x)

Compute the score for the given parameters x.

setup(data, DataSplitEvaluation)

Setup the strategy with the given data.

_setup()

Strategy-specific setup.

_get_x0()

Get an initial guess for the learnable weights of the basis functions \(\mathbf{x}\).

set_split(split, setup)

Set the split for this strategy.

get_score_static(_get_score, x, cupy_split)

static Convert the strategy-specific _get_score method to a static method.

get_y_static(y, numpy_split)

static Fetch the labels for the given split.

_objective_function_static(get_score, get_y, x)

static Compute the objective value for the given parameters x.

add_solver(solver, setup)

Add a solver to the strategy.