Use Simulated Models from the IPython Client¶

Prerequisites¶

• BEC is running with the simulated bpm4i device.
• The device exposes the simulation interface as dev.bpm4i.sim.

1. Inspect the available models¶

List the models exposed by the simulation interface:

dev.bpm4i.sim.get_models()

For a fuller overview of the active model, available methods, and current parameters, use:

dev.bpm4i.sim.show_all()

2. Select the simulation model¶

Set bpm4i to report values from a Gaussian simulation model:

dev.bpm4i.sim.select_model("GaussianModel")

The model names follow the LMFit built-in model class names. The same names are also shipped as the default BEC DAP model names.

See the LMFit built-in models for available model classes and parameters.

3. Set the model parameters¶

Set the Gaussian parameters and the motor used as the model input:

dev.bpm4i.sim.params = {
    "amplitude": 100,
    "center": 0,
    "sigma": 1,
    "ref_motor": "samx",
}

ref_motor tells the simulation which motor position to use as the model input. For bpm4i, samx is a good default for the examples in this documentation.

Make the simulation persistent¶

Prefer runtime setup from the IPython client while developing or onboarding users. Use device configuration only when the simulation should be the long-term default for a beamline or test configuration.

In that case, define sim_init inside the full device configuration:

bpm4i:
  deviceConfig:
    sim_init:
      model: GaussianModel
      params:
        amplitude: 100
        center: 0
        sigma: 1
        ref_motor: samx