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Double Gaussian Runner

Example runner that implements a simple synthetic function for testing and demonstration purposes.

SyntheticDoubleGaussianRunner 

SyntheticDoubleGaussianRunner(*args, **kwargs)

Bases: Runner

A simple Runner that implements a double Gaussian with a background slope.

kwargs

dimensions (int): Number of dimensions (1 or 2). model_parameters - vector of model parameters [a, g11, g12, g13, g21, g22, g23]: y = ax + g11np.exp(-(x - g13)2/g12) + g21*np.exp(-(x - g23)2/g22)

Returns a dictionary of containing the output and True for success. Future developments can include synthetic failure implementations.

Source code in src/enchanted_surrogates/runners/synthetic_double_gaussian_runner.py 
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def __init__(self, *args, **kwargs):
    self.dimensions = kwargs.get("dimensions", 1)

    if self.dimensions == 1:
        self.model_parameters = kwargs.get(
            "model_parameters",
            [0.2, 1.0, 0.001, 0.2, 0.6, 0.01, 0.7]
        )

    elif self.dimensions == 2:
        self.model_parameters = kwargs.get(
            "model_parameters",
            [0.2, 0.1,   # plane slopes ax, ay
             1.0, 0.02, 0.3, 0.3,   # hill 1 (centered near middle)
             0.8, 0.04, 0.75, 0.6]  # hill 2 (off-center)
        )
    else:
        raise ValueError("Only dimensions=1 or 2 supported.")

single_code_run 

single_code_run(run_dir, params=None)

Run the synthetic function with given parameters.

Parameters:

Name Type Description Default
run_dir str

Directory to save outputs.

 required
params dict

Dictionary of parameter values. For 1D: {'x': value} For 2D: {'x': value, 'y': value}

 None

Returns:

Name Type Description
dict dict

A dictionary containing the output and success status.
Source code in src/enchanted_surrogates/runners/synthetic_double_gaussian_runner.py 
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def single_code_run(self, run_dir: str, params: dict = None) -> dict:
    """
    Run the synthetic function with given parameters.

    Args:
        run_dir (str): Directory to save outputs.
        params (dict): Dictionary of parameter values.
                       For 1D: {'x': value}
                       For 2D: {'x': value, 'y': value}

    Returns:
        dict: A dictionary containing the output and success status.
    """
    if params is None:
        params = {}

    outfile = os.path.join(run_dir, "output.txt")

    if self.dimensions == 1:
        x = float(params["x"])
        a, g11, g12, g13, g21, g22, g23 = self.model_parameters

        z = a * x
        z += g11 * np.exp(-(x - g13)**2 / g12)
        z += g21 * np.exp(-(x - g23)**2 / g22)

    elif self.dimensions == 2:
        x = float(params["x"])
        y = float(params["y"])

        (ax, ay,
         g11, g12, g1x, g1y,
         g21, g22, g2x, g2y) = self.model_parameters

        # background plane
        z = ax * x + ay * y

        # Gaussian hills
        z += self.gaussian_2d(x, y, g11, g12, g1x, g1y)
        z += self.gaussian_2d(x, y, g21, g22, g2x, g2y)

    with open(outfile, "a") as f:
        f.write(str(z))

    return {"output": z, "success": True}