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Script Mode

Script mode provides full automation and reproducibility.

Minimal Flow

  1. Parse netlist using XyceNetlistParser.
  2. Create COBRA with component mappings and optimizer/simulator.
  3. Define design goals.
  4. Define optimization properties.
  5. Call cobra.run(...).

Reference Example

Use examples/main.py as the canonical end-to-end script.

from cobra import (
    COBRA,
    DesignGoal,
    OptimizationProperty,
    OptimizationType,
    OptunaOptimizer,
    XyceSimulator,
)
from cobra.optimizers.design_goal_collection import find_parameter
from cobra.spice_sim.netlist_parsers.xyce_netlist_parser import XyceNetlistParser

Key Construction Pattern

parser = XyceNetlistParser().from_file("your_netlist.cir")

cobra = COBRA(
    netlist_parser=parser,
    component_onnx_mapping={
        "X1": "model.onnx",
        "X2": "fixed_component.s6p",
    },
    optimizer=OptunaOptimizer(multi_objective=False, sampler="tpe", pruner="median"),
    circuit_simulator=XyceSimulator(),
)

Defining Goals and Parameters

A goal binds one DesignParameter to min/max limits. Look parameters up by name with find_parameter(...), or list the ones valid for a netlist with get_available_parameters(num_ports).

goals = [
    DesignGoal(find_parameter("S11_dB"), max_value=-9, frequency_range="125-135ghz"),
    DesignGoal(find_parameter("S21_dB"), min_value=-3, max_value=0, frequency_range="125-135ghz"),
]

from cobra.optimizers.design_goal_collection import make_power_dbm

# Output power at one spectral line of an .HB run
goals.append(
    DesignGoal(make_power_dbm("Out"), min_value=10.0, frequency_range="35ghz")
)

Power and gain parameters depend on the nodes and ports of the circuit, so they are built per netlist instead of being looked up by name. See Advanced -> Harmonic Balance.

params = [
    OptimizationProperty(
        name="X1:bottom_winding_diameter",
        type=OptimizationType.MODEL_INPUT,
        min_value=20.0,
        max_value=100.0,
        step=0.1,
    ),
    OptimizationProperty(
        name="Cshunt_p",
        type=OptimizationType.NETLIST_VARIABLE,
        unit="F",
        min_value=0.0,
        max_value=20.0,
        step=1.0,
    ),
]

Running

context = cobra.run(
    netlist="your_netlist.cir",
    design_goals=goals,
    optimization_parameters=params,
    max_iterations=200,
    results_name="your_experiment_name",
)

Optional Fine-Tuning

You can configure optional EM fine-tuning by providing Palace command and ORCA geometry. See Advanced -> Fine-Tuning.