Demonstrating “Bring Your Own Beamline” simulation with XRT#

In this tutorial we’ll show a simulation optimization workflow by loading arbitrary XRT setups using xml/json. By the end, you should be able to go to XRT qook/glow and build your beamline from there to export and drop in to blop. Or if you are lucky enough for an XRT model to be already built for you, export to xml and load in blop.

Some Environment Setup#

note, like all other demos you need the blop_sim subpackage to run

import logging
import warnings

import matplotlib.pyplot as plt
import numpy as np
from bluesky.callbacks.best_effort import BestEffortCallback

# Import simulation devices (requires: pip install -e sim/)
from bluesky.run_engine import RunEngine
from bluesky.utils import ProgressBarManager
from bluesky_tiled_plugins import TiledWriter
from tiled.client import from_uri  # type: ignore[import-untyped]
from tiled.client.container import Container
from tiled.server import SimpleTiledServer

from blop.ax import Agent, Objective, RangeDOF
from blop.protocols import EvaluationFunction
from blop_sim.backends import XRTBackend
from blop_sim.devices.xrt import infer_detectors, infer_variables

# Suppress noisy logs from httpx and dependency deprecation warnings
logging.getLogger("httpx").setLevel(logging.WARNING)
warnings.filterwarnings("ignore", category=FutureWarning)

# Enable interactive plotting
plt.ion()

DETECTOR_STORAGE = "/tmp/blop/sim"

[INFO 07-28 17:28:44] ax.storage.sqa_store.with_db_settings_base: Ax SQL storage initialized with SQLAlchemy 2.0.51
/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/xrt/backends/raycing/sources/sybase.py:78: SyntaxWarning: invalid escape sequence '\s'
  :math:`\beta_i = \frac{\sigma_i^{2}}{\epsilon_i}`, with

fileName = r"toroid_focus.xml"
beam = XRTBackend(file=fileName)
dets = infer_detectors(beam)
motors = infer_variables(beam, filter_for=None)

created inferred variable toroid_focus:screen01:center:z of float type as value is None or auto.
                Be careful when setting this variable as the type is guessed as float by default.

A small view of the inferred motors#

for name, element in motors.items():
    print(name)
    for nm, motor in element.items():
        print(f"{nm} : {motor}")

bendingMagnet01
B0 : <InferredVariable::toroid_focus:bendingMagnet01:B0=<class 'float'>:1.0>
rho : <InferredVariable::toroid_focus:bendingMagnet01:rho=<class 'float'>:10.00692285594456>
toroidMirror01
R : <InferredVariable::toroid_focus:toroidMirror01:R=<class 'float'>:152982.84327559808>
r : <InferredVariable::toroid_focus:toroidMirror01:r=<class 'float'>:1162.0765699687756>
screen01
center:x : <InferredVariable::toroid_focus:screen01:center:x=<class 'int'>:0>
center:y : <InferredVariable::toroid_focus:screen01:center:y=<class 'int'>:30000>
center:z : <InferredVariable::toroid_focus:screen01:center:z=<class 'float'>:auto>
x:x : <InferredVariable::toroid_focus:screen01:x:x=<class 'float'>:1.0>
x:y : <InferredVariable::toroid_focus:screen01:x:y=<class 'float'>:-0.0>
x:z : <InferredVariable::toroid_focus:screen01:x:z=<class 'float'>:0.0>
z:x : <InferredVariable::toroid_focus:screen01:z:x=<class 'float'>:0.0>
z:y : <InferredVariable::toroid_focus:screen01:z:y=<class 'float'>:0.0>
z:z : <InferredVariable::toroid_focus:screen01:z:z=<class 'float'>:1.0>

Another glimpse into the inferred detectors#

for name, det in dets.items():
    print(f"{name} : {det}")

bendingMagnet01 : <blop_sim.devices.xrt.auto_element.InferredDetector object at 0x7fa944c4dd30>
toroidMirror01 : <blop_sim.devices.xrt.auto_element.InferredDetector object at 0x7fa944bd39d0>
screen01 : <blop_sim.devices.xrt.auto_element.InferredDetector object at 0x7fa944bd3b10>

Setting up an optimization#

toro_R = motors["toroidMirror01"]["R"]
toro_R.alias = "big_r"
toro_r = motors["toroidMirror01"]["r"]

screen = dets["screen01"]
screen.set_primary()


VERTICAL_BOUNDS = (toro_R.val - 15000, toro_R.val + 15000)
HORIZONTAL_BOUNDS = (toro_r.val - 500, toro_r.val + 500)
# Define DOFs using mirror radius signals
dofs = [
    RangeDOF(actuator=toro_R, bounds=VERTICAL_BOUNDS, parameter_type="float"),
    RangeDOF(actuator=toro_r, bounds=HORIZONTAL_BOUNDS, parameter_type="float"),
]

tiled_server = SimpleTiledServer()
tiled_client = from_uri(tiled_server.uri)
tiled_writer = TiledWriter(tiled_client)

RE = RunEngine({})
bec = BestEffortCallback()

# Send all metadata/data captured to the BestEffortCallback.
# RE.subscribe(bec)
RE.waiting_hook = ProgressBarManager()

tiled_client = from_uri(tiled_server.uri)
tiled_writer = TiledWriter(tiled_client)
RE.subscribe(tiled_writer)

Tiled version 0.2.14

0

# Single objective: minimize the geometric-mean FWHM
objectives = [
    Objective(name="fwhm", minimize=True),
]

class DetectorEvaluation(EvaluationFunction):
    def __init__(self, tiled_client: Container):
        self.tiled_client = tiled_client

    def _fwhm_from_profile(self, profile: np.ndarray) -> float:
        """Compute FWHM from a 1D marginal profile.

        Finds the half-maximum crossing points with sub-pixel interpolation.
        Returns a large value if the beam is too dim or fills the entire detector.
        """
        peak = profile.max()
        if peak == 0:
            return float(len(profile))  # No signal — return detector width as penalty

        half_max = peak / 2.0
        above = profile >= half_max
        if not above.any():
            return float(len(profile))

        indices = np.where(above)[0]
        left_idx = indices[0]
        right_idx = indices[-1]

        # Sub-pixel interpolation at left crossing
        if left_idx > 0:
            left = left_idx - 1 + (half_max - profile[left_idx - 1]) / (profile[left_idx] - profile[left_idx - 1])
        else:
            left = 0.0

        # Sub-pixel interpolation at right crossing
        if right_idx < len(profile) - 1:
            right = right_idx + (half_max - profile[right_idx]) / (profile[right_idx + 1] - profile[right_idx])
        else:
            right = float(len(profile) - 1)

        return right - left

    def _compute_stats(self, image: np.ndarray) -> tuple[float, float]:
        """Compute FWHM and integrated intensity from a beam image.

        Returns
        -------
        fwhm : float
            Geometric mean of the horizontal and vertical FWHM (in pixels).
        intensity : float
            Total integrated intensity (sum of all pixel values).
        """
        gray = image.squeeze().astype(np.float64)
        if gray.ndim == 3:
            gray = gray.mean(axis=-1)

        # Integrated intensity (total flux on detector)
        intensity = gray.sum()

        if intensity == 0:
            return 400.0, 0.0  # No beam — return max FWHM penalty

        # Marginal profiles: project onto each axis
        x_profile = gray.sum(axis=0)  # sum along Y rows -> X profile
        y_profile = gray.sum(axis=1)  # sum along X cols -> Y profile

        fwhm_x = self._fwhm_from_profile(x_profile)
        fwhm_y = self._fwhm_from_profile(y_profile)

        # Geometric mean FWHM — targets a small, round spot
        fwhm = np.sqrt(fwhm_x * fwhm_y)

        return float(fwhm), float(intensity)

    def __call__(self, uid: str, suggestions: list[dict]) -> list[dict]:
        outcomes = []
        run = self.tiled_client[uid]

        # Read beam images from detector
        images = run[f"primary/{screen.name}"].read()

        # Suggestion IDs stored in start document metadata
        suggestion_ids = [suggestion["_id"] for suggestion in run.metadata["start"]["blop_suggestions"]]

        # Compute statistics from each image
        for idx, sid in enumerate(suggestion_ids):
            image = images[idx]
            fwhm, intensity = self._compute_stats(image)

            outcome = {
                "_id": sid,
                "fwhm": fwhm,
                # "intensity": intensity,
            }
            outcomes.append(outcome)
        return outcomes

agent = Agent(
    sensors=[screen],
    dofs=dofs,
    objectives=objectives,
    evaluation_function=DetectorEvaluation(tiled_client),
    name="xrt-blop-demo",
    description="A demo of the Blop agent with XRT simulated beamline",
    experiment_type="demo",
)

# Run 1 iteration with a batch of 10 points for initial exploration
RE(agent.optimize(1, n_points=10))



╭───────────────────────────────────────────────── Optimization ──────────────────────────────────────────────────╮
│ Optimizer  AxOptimizer                                                                                          │
│ Actuators  big_r, toroid_focus:toroidMirror01:r                                                                 │
│ Sensors    screen01                                                                                             │
│ Iterations 1  Points/iter 10                                                                                    │
│ Run UID    0c48bbc6-7c3d-45d2-9ede-ed2cb892fd70                                                                 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯



125591 rays of 500000
250715 rays of 500000
375837 rays of 500000
501565 rays of 500000
screen01
center:
[0.0, 30000.0, 1763.2705775903494]





[INFO 07-28 17:28:50] ax.api.client: GenerationStrategy(name='Center+Sobol+MBM:fast', nodes=[CenterGenerationNode(next_node_name='Sobol', use_existing_trials_for_initialization=True), GenerationNode(name='Sobol', generator_specs=[GeneratorSpec(generator_enum=Sobol, generator_key_override=None)], transition_criteria=[MinTrials(transition_to='MBM'), MinTrials(transition_to='MBM')], suggested_experiment_status=ExperimentStatus.INITIALIZATION, pausing_criteria=[MaxTrialsAwaitingData(threshold=5)]), GenerationNode(name='MBM', generator_specs=[GeneratorSpec(generator_enum=BoTorch, generator_key_override=None)], transition_criteria=None, suggested_experiment_status=ExperimentStatus.OPTIMIZATION, pausing_criteria=None)]) chosen based on user input and problem structure.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 0 with parameters {'big_r': 152982.843276, 'toroid_focus:toroidMirror01:r': 1162.07657} using GenerationNode CenterOfSearchSpace.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 1 with parameters {'big_r': 145398.236121, 'toroid_focus:toroidMirror01:r': 1309.918679} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 2 with parameters {'big_r': 160157.286524, 'toroid_focus:toroidMirror01:r': 1041.052447} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 3 with parameters {'big_r': 165845.632869, 'toroid_focus:toroidMirror01:r': 1443.179306} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 4 with parameters {'big_r': 151077.091554, 'toroid_focus:toroidMirror01:r': 674.439288} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 5 with parameters {'big_r': 146024.532346, 'toroid_focus:toroidMirror01:r': 1581.85832} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 6 with parameters {'big_r': 161288.831494, 'toroid_focus:toroidMirror01:r': 848.275501} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 7 with parameters {'big_r': 155573.462676, 'toroid_focus:toroidMirror01:r': 1198.582433} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 8 with parameters {'big_r': 140372.670637, 'toroid_focus:toroidMirror01:r': 964.873435} using GenerationNode Sobol.
[INFO 07-28 17:28:50] ax.api.client: Generated new trial 9 with parameters {'big_r': 138226.612601, 'toroid_focus:toroidMirror01:r': 1474.784081} using GenerationNode Sobol.
[INFO 07-28 17:29:19] ax.api.client: Trial 9 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 8 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 1 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 5 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 4 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 0 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 2 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 6 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 3 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 7 marked COMPLETED.
[INFO 07-28 17:29:19] ax.api.client: Trial 0 marked COMPLETED.





────────────────────────────────────────── Iteration 1 / 1  (10 points) ───────────────────────────────────────────



  Acquire UID  a2d344d5-2f9f-47b4-b273-544f4f9b7439



┏━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Event ┃ Suggestion ID ┃  big_r ┃ toroid_focus:toroidMirror01:r ┃    fwhm ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│     0 │             0 │ 152983 │                       1162.08 │ 38.3015 │
│     1 │             1 │ 145398 │                       1309.92 │ 16.2013 │
│     2 │             2 │ 160157 │                       1041.05 │ 17.4272 │
│     3 │             3 │ 165846 │                       1443.18 │ 60.7359 │
│     4 │             4 │ 151077 │                       674.439 │ 26.6438 │
│     5 │             5 │ 146025 │                       1581.86 │ 19.1713 │
│     6 │             6 │ 161289 │                       848.276 │ 15.8496 │
│     7 │             7 │ 155573 │                       1198.58 │ 77.0534 │
│     8 │             8 │ 140373 │                       964.873 │ 12.6198 │
│     9 │             9 │ 138227 │                       1474.78 │ 15.9499 │
└───────┴───────────────┴────────┴───────────────────────────────┴─────────┘



  fwhm  min: 12.6198  max: 77.0534  mean: 29.9954
  (10 pts sampled)





                                    Summary Statistics                                     
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━┓
┃ Name                          ┃ Type    ┃     Min ┃     Max ┃    Mean ┃     Std ┃ Count ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━┩
│ big_r                         │ param   │  138227 │  165846 │  151695 │ 9203.69 │    10 │
│ toroid_focus:toroidMirror01:r │ param   │ 674.439 │ 1581.86 │  1169.9 │ 291.623 │    10 │
│ fwhm                          │ outcome │ 12.6198 │ 77.0534 │ 29.9954 │ 22.1217 │    10 │
└───────────────────────────────┴─────────┴─────────┴─────────┴─────────┴─────────┴───────┘



────────────────────────────────────────────── Optimization Complete ──────────────────────────────────────────────





('0c48bbc6-7c3d-45d2-9ede-ed2cb892fd70',
 'a2d344d5-2f9f-47b4-b273-544f4f9b7439')













# Run more iterations
RE(agent.optimize(5, n_points=5))











╭───────────────────────────────────────────────── Optimization ──────────────────────────────────────────────────╮
│ Optimizer  AxOptimizer                                                                                          │
│ Actuators  big_r, toroid_focus:toroidMirror01:r                                                                 │
│ Sensors    screen01                                                                                             │
│ Iterations 5 more (1 completed, 6 total)  Points/iter 5                                                         │
│ Run UID    0a07e5e9-57c6-4d40-8ee2-ba6f731f5228                                                                 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯



[INFO 07-28 17:29:21] ax.api.client: Generated new trial 10 with parameters {'big_r': 142552.529623, 'toroid_focus:toroidMirror01:r': 1662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:21] ax.api.client: Generated new trial 11 with parameters {'big_r': 138912.300526, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:21] ax.api.client: Generated new trial 12 with parameters {'big_r': 142901.500396, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:21] ax.api.client: Generated new trial 13 with parameters {'big_r': 140113.143129, 'toroid_focus:toroidMirror01:r': 1662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:21] ax.api.client: Generated new trial 14 with parameters {'big_r': 146846.087723, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:33] ax.api.client: Trial 10 marked COMPLETED.
[INFO 07-28 17:29:33] ax.api.client: Trial 13 marked COMPLETED.
[INFO 07-28 17:29:33] ax.api.client: Trial 11 marked COMPLETED.
[INFO 07-28 17:29:33] ax.api.client: Trial 12 marked COMPLETED.
[INFO 07-28 17:29:33] ax.api.client: Trial 14 marked COMPLETED.
[INFO 07-28 17:29:38] ax.api.client: Generated new trial 15 with parameters {'big_r': 142176.329772, 'toroid_focus:toroidMirror01:r': 1308.949748} using GenerationNode MBM.
[INFO 07-28 17:29:38] ax.api.client: Generated new trial 16 with parameters {'big_r': 142559.88062, 'toroid_focus:toroidMirror01:r': 1311.335974} using GenerationNode MBM.
[INFO 07-28 17:29:38] ax.api.client: Generated new trial 17 with parameters {'big_r': 141775.81881, 'toroid_focus:toroidMirror01:r': 1331.37397} using GenerationNode MBM.
[INFO 07-28 17:29:38] ax.api.client: Generated new trial 18 with parameters {'big_r': 161162.570712, 'toroid_focus:toroidMirror01:r': 1662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:38] ax.api.client: Generated new trial 19 with parameters {'big_r': 142556.439659, 'toroid_focus:toroidMirror01:r': 1430.043773} using GenerationNode MBM.
[INFO 07-28 17:29:50] ax.api.client: Trial 18 marked COMPLETED.
[INFO 07-28 17:29:50] ax.api.client: Trial 19 marked COMPLETED.
[INFO 07-28 17:29:50] ax.api.client: Trial 17 marked COMPLETED.
[INFO 07-28 17:29:50] ax.api.client: Trial 15 marked COMPLETED.
[INFO 07-28 17:29:50] ax.api.client: Trial 16 marked COMPLETED.
[INFO 07-28 17:29:54] ax.api.client: Generated new trial 20 with parameters {'big_r': 159870.192969, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:54] ax.api.client: Generated new trial 21 with parameters {'big_r': 159436.628663, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:54] ax.api.client: Generated new trial 22 with parameters {'big_r': 150002.566849, 'toroid_focus:toroidMirror01:r': 1662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:54] ax.api.client: Generated new trial 23 with parameters {'big_r': 160262.239497, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:29:54] ax.api.client: Generated new trial 24 with parameters {'big_r': 167982.843276, 'toroid_focus:toroidMirror01:r': 662.07657} using GenerationNode MBM.
[INFO 07-28 17:30:07] ax.api.client: Trial 21 marked COMPLETED.
[INFO 07-28 17:30:07] ax.api.client: Trial 20 marked COMPLETED.
[INFO 07-28 17:30:07] ax.api.client: Trial 23 marked COMPLETED.
[INFO 07-28 17:30:07] ax.api.client: Trial 24 marked COMPLETED.
[INFO 07-28 17:30:07] ax.api.client: Trial 22 marked COMPLETED.
[INFO 07-28 17:30:12] ax.api.client: Generated new trial 25 with parameters {'big_r': 143287.336686, 'toroid_focus:toroidMirror01:r': 986.585398} using GenerationNode MBM.
[INFO 07-28 17:30:12] ax.api.client: Generated new trial 26 with parameters {'big_r': 137982.843276, 'toroid_focus:toroidMirror01:r': 1118.146096} using GenerationNode MBM.
[INFO 07-28 17:30:12] ax.api.client: Generated new trial 27 with parameters {'big_r': 148904.012598, 'toroid_focus:toroidMirror01:r': 1078.240649} using GenerationNode MBM.
[INFO 07-28 17:30:12] ax.api.client: Generated new trial 28 with parameters {'big_r': 140073.859933, 'toroid_focus:toroidMirror01:r': 1294.887357} using GenerationNode MBM.
[INFO 07-28 17:30:12] ax.api.client: Generated new trial 29 with parameters {'big_r': 140902.378246, 'toroid_focus:toroidMirror01:r': 1485.310689} using GenerationNode MBM.
[INFO 07-28 17:30:24] ax.api.client: Trial 29 marked COMPLETED.
[INFO 07-28 17:30:24] ax.api.client: Trial 28 marked COMPLETED.
[INFO 07-28 17:30:24] ax.api.client: Trial 26 marked COMPLETED.
[INFO 07-28 17:30:24] ax.api.client: Trial 25 marked COMPLETED.
[INFO 07-28 17:30:24] ax.api.client: Trial 27 marked COMPLETED.
[INFO 07-28 17:30:30] ax.api.client: Generated new trial 30 with parameters {'big_r': 143106.209136, 'toroid_focus:toroidMirror01:r': 1145.395445} using GenerationNode MBM.
[INFO 07-28 17:30:30] ax.api.client: Generated new trial 31 with parameters {'big_r': 137982.843276, 'toroid_focus:toroidMirror01:r': 1662.07657} using GenerationNode MBM.
[INFO 07-28 17:30:30] ax.api.client: Generated new trial 32 with parameters {'big_r': 141700.622181, 'toroid_focus:toroidMirror01:r': 1155.676177} using GenerationNode MBM.
[INFO 07-28 17:30:30] ax.api.client: Generated new trial 33 with parameters {'big_r': 143978.719797, 'toroid_focus:toroidMirror01:r': 1215.47124} using GenerationNode MBM.
[INFO 07-28 17:30:30] ax.api.client: Generated new trial 34 with parameters {'big_r': 144829.635065, 'toroid_focus:toroidMirror01:r': 1013.18701} using GenerationNode MBM.
[INFO 07-28 17:30:43] ax.api.client: Trial 33 marked COMPLETED.
[INFO 07-28 17:30:43] ax.api.client: Trial 31 marked COMPLETED.
[INFO 07-28 17:30:43] ax.api.client: Trial 32 marked COMPLETED.
[INFO 07-28 17:30:43] ax.api.client: Trial 30 marked COMPLETED.
[INFO 07-28 17:30:43] ax.api.client: Trial 34 marked COMPLETED.





─────────────────────────────────────────── Iteration 2 / 6  (5 points) ───────────────────────────────────────────



  Acquire UID  1cf0057b-cab9-4c9c-be8e-85961a845d2f



┏━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Event ┃ Suggestion ID ┃  big_r ┃ toroid_focus:toroidMirror01:r ┃    fwhm ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│     0 │            10 │ 142553 │                       1662.08 │ 10.5673 │
│     1 │            11 │ 138912 │                       662.077 │ 20.7404 │
│     2 │            12 │ 142902 │                       662.077 │ 15.6037 │
│     3 │            13 │ 140113 │                       1662.08 │ 13.4675 │
│     4 │            14 │ 146846 │                       662.077 │ 24.5438 │
└───────┴───────────────┴────────┴───────────────────────────────┴─────────┘



  fwhm  min: 10.5673  max: 77.0534  mean: 25.6584
  (15 pts sampled)



─────────────────────────────────────────── Iteration 3 / 6  (5 points) ───────────────────────────────────────────



  Acquire UID  32f78c2e-2850-4a2d-b911-544976f40bac



┏━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Event ┃ Suggestion ID ┃  big_r ┃ toroid_focus:toroidMirror01:r ┃    fwhm ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│     0 │            15 │ 142176 │                       1308.95 │  9.6592 │
│     1 │            16 │ 142560 │                       1311.34 │ 10.0167 │
│     2 │            17 │ 141776 │                       1331.37 │ 10.6624 │
│     3 │            18 │ 161163 │                       1662.08 │ 63.3133 │
│     4 │            19 │ 142556 │                       1430.04 │ 9.80408 │
└───────┴───────────────┴────────┴───────────────────────────────┴─────────┘



  fwhm  min: 9.6592  max: 77.0534  mean: 24.4166
  (20 pts sampled)



─────────────────────────────────────────── Iteration 4 / 6  (5 points) ───────────────────────────────────────────



  Acquire UID  835c82f3-2c9a-43f6-80eb-6c493693f001



┏━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Event ┃ Suggestion ID ┃  big_r ┃ toroid_focus:toroidMirror01:r ┃    fwhm ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│     0 │            20 │ 159870 │                       662.077 │  18.289 │
│     1 │            21 │ 159437 │                       662.077 │ 20.2275 │
│     2 │            22 │ 150003 │                       1662.08 │ 41.7434 │
│     3 │            23 │ 160262 │                       662.077 │ 48.3928 │
│     4 │            24 │ 167983 │                       662.077 │ 54.7266 │
└───────┴───────────────┴────────┴───────────────────────────────┴─────────┘



  fwhm  min: 9.6592  max: 77.0534  mean: 26.8685
  (25 pts sampled)



─────────────────────────────────────────── Iteration 5 / 6  (5 points) ───────────────────────────────────────────



  Acquire UID  99a7bbcf-8a73-49a7-a4ad-feb306cc1024



┏━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Event ┃ Suggestion ID ┃  big_r ┃ toroid_focus:toroidMirror01:r ┃    fwhm ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│     0 │            25 │ 143287 │                       986.585 │ 12.4555 │
│     1 │            26 │ 137983 │                       1118.15 │ 16.3164 │
│     2 │            27 │ 148904 │                       1078.24 │ 20.1454 │
│     3 │            28 │ 140074 │                       1294.89 │ 13.1625 │
│     4 │            29 │ 140902 │                       1485.31 │ 12.0901 │
└───────┴───────────────┴────────┴───────────────────────────────┴─────────┘



  fwhm  min: 9.6592  max: 77.0534  mean: 24.8627
  (30 pts sampled)



─────────────────────────────────────────── Iteration 6 / 6  (5 points) ───────────────────────────────────────────



  Acquire UID  8d246185-6c1b-49f9-93b0-2156a5cf05a6



┏━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Event ┃ Suggestion ID ┃  big_r ┃ toroid_focus:toroidMirror01:r ┃    fwhm ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│     0 │            30 │ 143106 │                        1145.4 │ 11.2553 │
│     1 │            31 │ 137983 │                       1662.08 │ 17.4012 │
│     2 │            32 │ 141701 │                       1155.68 │ 8.74728 │
│     3 │            33 │ 143979 │                       1215.47 │ 13.7494 │
│     4 │            34 │ 144830 │                       1013.19 │ 14.6752 │
└───────┴───────────────┴────────┴───────────────────────────────┴─────────┘



  fwhm  min: 8.74728  max: 77.0534  mean: 23.1917
  (35 pts sampled)





                                    Summary Statistics                                     
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━┓
┃ Name                          ┃ Type    ┃     Min ┃     Max ┃    Mean ┃     Std ┃ Count ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━┩
│ big_r                         │ param   │  137983 │  167983 │  147966 │ 8841.61 │    35 │
│ toroid_focus:toroidMirror01:r │ param   │ 662.077 │ 1662.08 │ 1157.67 │ 347.125 │    35 │
│ fwhm                          │ outcome │ 8.74728 │ 77.0534 │ 23.1917 │ 17.5212 │    35 │
└───────────────────────────────┴─────────┴─────────┴─────────┴─────────┴─────────┴───────┘



────────────────────────────────────────────── Optimization Complete ──────────────────────────────────────────────





('0a07e5e9-57c6-4d40-8ee2-ba6f731f5228',
 '1cf0057b-cab9-4c9c-be8e-85961a845d2f',
 '32f78c2e-2850-4a2d-b911-544976f40bac',
 '835c82f3-2c9a-43f6-80eb-6c493693f001',
 '99a7bbcf-8a73-49a7-a4ad-feb306cc1024',
 '8d246185-6c1b-49f9-93b0-2156a5cf05a6')













_ = agent.ax_client.compute_analyses()









[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.core.experiment: Encountered ValueError Data to attach is empty. while attaching results. Proceeding and returning results fetched without attaching.
[ERROR 07-28 17:30:45] ax.analysis.analysis: Failed to compute TransferLearningAnalysis
[ERROR 07-28 17:30:45] ax.analysis.analysis: Traceback (most recent call last):
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/analysis/analysis.py", line 115, in compute_result
    card = self.compute(
        experiment=experiment,
        generation_strategy=generation_strategy,
        adapter=adapter,
    )
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/analysis/healthcheck/transfer_learning_analysis.py", line 104, in compute
    transferable_experiments = identify_transferable_experiments(
        search_space=experiment.search_space,
    ...<4 lines>...
        experiment_name=experiment.name,
    )
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/load.py", line 839, in identify_transferable_experiments
    experiments_search_spaces = _query_historical_experiments_given_parameters(
        parameter_names=list(search_space.parameters.keys()),
        experiment_types=experiment_types,
        config=config,
    )
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/load.py", line 759, in _query_historical_experiments_given_parameters
    with session_scope() as session:
         ~~~~~~~~~~~~~^^
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/contextlib.py", line 141, in __enter__
    return next(self.gen)
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/db.py", line 287, in session_scope
    session = get_session()
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/db.py", line 263, in get_session
    init_engine_and_session_factory()
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/db.py", line 191, in init_engine_and_session_factory
    raise ValueError("Must specify either `url` or `creator`.")
ValueError: Must specify either `url` or `creator`.









    

        
        Overview of the Entire Optimization Process 
        
        

        This analysis provides an overview of the entire optimization process. It includes visualizations of the results obtained so far, insights into the parameter and metric relationships learned by the Ax model, diagnostics such as model fit, and health checks to assess the overall health of the experiment.
        

    

    

        



    

        
        Results Analysis
        
        

        Result Analyses provide a high-level overview of the results of the optimization process so far with respect to the metrics specified in experiment design.
        

    

    

        



    

        
        Metric Effects: Predicted and observed effects for all arms in the experiment
        
        

        These pair of plots visualize the metric effects for each arm, with the Ax model predictions on the left and the raw observed data on the right. The predicted effects apply shrinkage for noise and adjust for non-stationarity in the data, so they are more representative of the reproducible effects that will manifest in a long-term validation experiment. 
        

    

    

        



    

        
        Metric Effects Pair for fwhm
        
        

        
        

    

    

        



    



    

        Modeled Arm Effects on fwhm
        
Modeled effects on fwhm. This plot visualizes predictions of the true metric changes for each arm based on Ax's model. This is the expected delta you would expect if you (re-)ran that arm. This plot helps in anticipating the outcomes and performance of arms based on the model's predictions. Note, flat predictions across arms indicate that the model predicts that there is no effect, meaning if you were to re-run the experiment, the delta you would see would be small and fall within the confidence interval indicated in the plot.

        
    

    

        




    
                            
                    




    








    

        Observed Arm Effects on fwhm
        
Observed effects on fwhm. This plot visualizes the effects from previously-run arms on a specific metric, providing insights into their performance. This plot allows one to compare and contrast the effectiveness of different arms, highlighting which configurations have yielded the most favorable outcomes. 

        
    

    

        




    
                            
                    




    








    




    








    



    

        Utility Progression
        
Shows the best fwhm value achieved so far across completed trials (objective is to minimize). The x-axis shows trial index. Only completed or early-stopped trials with complete metric data are included, so there may be gaps if some trials failed, were abandoned, or have incomplete data. The y-axis shows cumulative best utility. Only improvements are plotted, so flat segments indicate trials that didn't surpass the previous best. Infeasible trials (violating outcome constraints) don't contribute to the improvements.

        
    

    

        




    
                            
                    




    








    

        Best Trial for Experiment
        
Displays the trial with the best objective value based on raw observations. This reflects actual measured performance during execution. This trial achieved the optimal objective value and represents the recommended configuration for your optimization goal. Only considering COMPLETED trials.

        
    

    

        

  
    

      
      trial_index
      arm_name
      trial_status
      generation_node
      fwhm
      big_r
      toroid_focus:toroidMirror01:r
    

  
  
    

      0
      32
      32_0
      COMPLETED
      MBM
      8.747275
      141700.622181
      1155.676177
    

  


    








    

        Summary for xrt-blop-demo
        
High-level summary of the `Trial`-s in this `Experiment`

        
    

    

        

  
    

      
      trial_index
      arm_name
      trial_status
      generation_node
      fwhm
      big_r
      toroid_focus:toroidMirror01:r
    

  
  
    

      0
      0
      0_0
      COMPLETED
      CenterOfSearchSpace
      38.301529
      152982.843276
      1162.076570
    

    

      1
      1
      1_0
      COMPLETED
      Sobol
      16.201340
      145398.236121
      1309.918679
    

    

      2
      2
      2_0
      COMPLETED
      Sobol
      17.427218
      160157.286524
      1041.052447
    

    

      3
      3
      3_0
      COMPLETED
      Sobol
      60.735904
      165845.632869
      1443.179306
    

    

      4
      4
      4_0
      COMPLETED
      Sobol
      26.643834
      151077.091554
      674.439288
    

    

      5
      5
      5_0
      COMPLETED
      Sobol
      19.171328
      146024.532346
      1581.858320
    

    

      6
      6
      6_0
      COMPLETED
      Sobol
      15.849621
      161288.831494
      848.275501
    

    

      7
      7
      7_0
      COMPLETED
      Sobol
      77.053370
      155573.462676
      1198.582433
    

    

      8
      8
      8_0
      COMPLETED
      Sobol
      12.619759
      140372.670637
      964.873435
    

    

      9
      9
      9_0
      COMPLETED
      Sobol
      15.949864
      138226.612601
      1474.784081
    

    

      10
      10
      10_0
      COMPLETED
      MBM
      10.567268
      142552.529623
      1662.076570
    

    

      11
      11
      11_0
      COMPLETED
      MBM
      20.740411
      138912.300526
      662.076570
    

    

      12
      12
      12_0
      COMPLETED
      MBM
      15.603704
      142901.500396
      662.076570
    

    

      13
      13
      13_0
      COMPLETED
      MBM
      13.467454
      140113.143129
      1662.076570
    

    

      14
      14
      14_0
      COMPLETED
      MBM
      24.543823
      146846.087723
      662.076570
    

    

      15
      15
      15_0
      COMPLETED
      MBM
      9.659196
      142176.329772
      1308.949748
    

    

      16
      16
      16_0
      COMPLETED
      MBM
      10.016747
      142559.880620
      1311.335974
    

    

      17
      17
      17_0
      COMPLETED
      MBM
      10.662418
      141775.818810
      1331.373970
    

    

      18
      18
      18_0
      COMPLETED
      MBM
      63.313327
      161162.570712
      1662.076570
    

    

      19
      19
      19_0
      COMPLETED
      MBM
      9.804084
      142556.439659
      1430.043773
    

    

      20
      20
      20_0
      COMPLETED
      MBM
      18.288981
      159870.192969
      662.076570
    

    

      21
      21
      21_0
      COMPLETED
      MBM
      20.227451
      159436.628663
      662.076570
    

    

      22
      22
      22_0
      COMPLETED
      MBM
      41.743425
      150002.566849
      1662.076570
    

    

      23
      23
      23_0
      COMPLETED
      MBM
      48.392807
      160262.239497
      662.076570
    

    

      24
      24
      24_0
      COMPLETED
      MBM
      54.726581
      167982.843276
      662.076570
    

    

      25
      25
      25_0
      COMPLETED
      MBM
      12.455523
      143287.336686
      986.585398
    

    

      26
      26
      26_0
      COMPLETED
      MBM
      16.316409
      137982.843276
      1118.146096
    

    

      27
      27
      27_0
      COMPLETED
      MBM
      20.145375
      148904.012598
      1078.240649
    

    

      28
      28
      28_0
      COMPLETED
      MBM
      13.162487
      140073.859933
      1294.887357
    

    

      29
      29
      29_0
      COMPLETED
      MBM
      12.090061
      140902.378246
      1485.310689
    

    

      30
      30
      30_0
      COMPLETED
      MBM
      11.255295
      143106.209136
      1145.395445
    

    

      31
      31
      31_0
      COMPLETED
      MBM
      17.401187
      137982.843276
      1662.076570
    

    

      32
      32
      32_0
      COMPLETED
      MBM
      8.747275
      141700.622181
      1155.676177
    

    

      33
      33
      33_0
      COMPLETED
      MBM
      13.749409
      143978.719797
      1215.471240
    

    

      34
      34
      34_0
      COMPLETED
      MBM
      14.675176
      144829.635065
      1013.187010
    

  


    








    








    

        
        Insights Analysis
        
        

        Insight Analyses display information to help understand the underlying experiment i.e parameter and metric relationships learned by the Ax model.Use this information to better understand your experiment space and users.
        

    

    

        



    

        
        Top Surfaces Analysis: Parameter sensitivity, slice, and contour plots
        
        

        The top surfaces analysis displays three analyses in one. First, it shows parameter sensitivities, which shows the sensitivity of the metrics in the experiment to the most important parameters. Subsetting to only the most important parameters, it then shows slice plots and contour plots for each metric in the experiment, displaying the relationship between the metric and the most important parameters. 
        

    

    

        



    



    

        Sensitivity Analysis for fwhm
        
Understand how each parameter affects fwhm according to a second-order sensitivity analysis.

        
    

    

        




    
                            
                    




    












    

        
        Slice Plots: Metric effects by parameter value
        
        

        These plots show the relationship between a metric and a parameter. They show the predicted values of the metric on the y-axis as a function of the parameter on the x-axis while keeping all other parameters fixed at their status_quo value (if available), best trial value, or the center of the search space.
        

    

    

        



    



    

        fwhm vs. big_r
        
The slice plot provides a one-dimensional view of predicted outcomes for fwhm as a function of a single parameter, while keeping all other parameters fixed at their best trial value (Arm 15_0). This visualization helps in understanding the sensitivity and impact of changes in the selected parameter on the predicted metric outcomes.

        
    

    

        




    
                            
                    




    








    

        fwhm vs. toroid_focus:toroidMirror01:r
        
The slice plot provides a one-dimensional view of predicted outcomes for fwhm as a function of a single parameter, while keeping all other parameters fixed at their best trial value (Arm 15_0). This visualization helps in understanding the sensitivity and impact of changes in the selected parameter on the predicted metric outcomes.

        
    

    

        




    
                            
                    




    








    








    

        
        Contour Plots: Metric effects by parameter values
        
        

        These plots show the relationship between a metric and two parameters. They show the predicted values of the metric (indicated by color) as a function of the two parameters on the x- and y-axes while keeping all other parameters fixed at their status_quo value (if available), best trial value, or the center of the search space.
        

    

    

        



    



    

        fwhm (Mean) vs. big_r, toroid_focus:toroidMirror01:r
        
The contour plot visualizes the predicted outcomes for fwhm across a two-dimensional parameter space, with other parameters held fixed at their best trial value (Arm 15_0). This plot helps in identifying regions of optimal performance and understanding how changes in the selected parameters influence the predicted outcomes. Contour lines represent levels of constant predicted values, providing insights into the gradient and potential optima within the parameter space.

        
    

    

        




    
                            
                    




    








    




    




    








    

        
        Diagnostic Analysis
        
        

        Diagnostic Analyses provide information about the optimization process and the quality of the model fit. You can use this information to understand if the experimental design should be adjusted to improve optimization quality.
        

    

    

        



    

        
        Cross Validation: Assessing model fit
        
        

        Cross-validation plots display the model fit for each metric in the experiment. The model is trained on a subset of the data and then predicts the outcome for the remaining subset. The plots show the predicted outcome for the validation set on the y-axis against its actual value on the x-axis. Points that align closely with the dotted diagonal line indicate a strong model fit, signifying accurate predictions. Additionally, the plots include confidence intervals that provide insight into the noise in observations and the uncertainty in model predictions. 

NOTE: A horizontal, flat line of predictions indicates that the model has not picked up on sufficient signal in the data, and instead is just predicting the mean.
        

    

    

        



    



    

        Cross Validation for fwhm (R² = 0.58)
        
The cross-validation plot displays the model fit for each metric in the experiment. It employs a leave-one-out approach, where the model is trained on all data except one sample, which is used for validation. The plot shows the predicted outcome for the validation set on the y-axis against its actual value on the x-axis. Points that align closely with the dotted diagonal line indicate a strong model fit, signifying accurate predictions. Additionally, the plot includes 95% confidence intervals that provide insight into the noise in observations and the uncertainty in model predictions. A horizontal, flat line of predictions indicates that the model has not picked up on sufficient signal in the data, and instead is just predicting the mean.

        
    

    

        




    
                            
                    




    








    

        Summary of model fits
        
R² (coefficient of determination) measures how well the model predicts each metric. Higher values indicate better model fit. Metrics with R² >= 0.1 are highlighted in green.

        
    

    

        




    
                            
                    




    








    








    



    

        Generation Strategy Graph
        
GenerationStrategy: Center+Sobol+MBM:fast

Visualize the structure of a GenerationStrategy as a directed graph. Each node
represents a GenerationNode in the strategy, and edges represent transitions
between nodes based on TransitionCriterion. Edge labels show the criterion
class names that trigger the transition.


        
    

    

        
b'\n\n\n\n\n\nGenerationStrategy\n\n\n\nCenterOfSearchSpace\n\nCenterOfSearchSpace\n()\n\n\n\nSobol\n\nSobol\n\n\n\nCenterOfSearchSpace->Sobol\n\n\nAutoTransitionAfterGen\n\n\n\nMBM\n\nMBM\n(BoTorch)\n\n\n\nSobol->MBM\n\n\nMinTrials(5)\nMinTrials(2)\n\n\n\n'

    








    








    

        
        Health Checks
        
        

        Comprehensive health checks designed to identify potential issues in the Ax experiment. These checks cover areas such as metric fetching, search space configuration, and candidate generation, with the aim of flagging areas where user intervention may be necessary to ensure the experiment's robustness and success.
        

    

    

        



    



    

        Baseline Improvement Healthcheck
        
All 1 objective(s) improved over baseline.

**Metric `fwhm` improved 77.16%** from `38.30` in arm `'0_0'` to `8.75` in arm `'32_0'`.

**Note:** Using the first trial's first arm ('0_0') as the baseline since no explicit baseline was provided.

        
    

    

        

  
    

      
      Metric
      Status
      Details
    

  
  
    

      0
      fwhm
      Improved
      **Metric `fwhm` improved 77.16%** from `38.30` in arm `'0_0'` to `8.75` in arm `'32_0'`.
    

  


    








    

        TransferLearningAnalysis Error
        
ValueError: Must specify either `url` or `creator`.

        
    

    

        
Traceback (most recent call last):
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/analysis/analysis.py", line 115, in compute_result
    card = self.compute(
        experiment=experiment,
        generation_strategy=generation_strategy,
        adapter=adapter,
    )
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/analysis/healthcheck/transfer_learning_analysis.py", line 104, in compute
    transferable_experiments = identify_transferable_experiments(
        search_space=experiment.search_space,
    ...<4 lines>...
        experiment_name=experiment.name,
    )
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/load.py", line 839, in identify_transferable_experiments
    experiments_search_spaces = _query_historical_experiments_given_parameters(
        parameter_names=list(search_space.parameters.keys()),
        experiment_types=experiment_types,
        config=config,
    )
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/load.py", line 759, in _query_historical_experiments_given_parameters
    with session_scope() as session:
         ~~~~~~~~~~~~~^^
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/contextlib.py", line 141, in __enter__
    return next(self.gen)
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/db.py", line 287, in session_scope
    session = get_session()
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/db.py", line 263, in get_session
    init_engine_and_session_factory()
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
  File "/home/runner/work/blop/blop/.pixi/envs/docs/lib/python3.13/site-packages/ax/storage/sqa_store/db.py", line 191, in init_engine_and_session_factory
    raise ValueError("Must specify either `url` or `creator`.")
ValueError: Must specify either `url` or `creator`.


    








    




    












agent.ax_client.summarize()













  
    

      
      trial_index
      arm_name
      trial_status
      generation_node
      fwhm
      big_r
      toroid_focus:toroidMirror01:r
    

  
  
    

      0
      0
      0_0
      COMPLETED
      CenterOfSearchSpace
      38.301529
      152982.843276
      1162.076570
    

    

      1
      1
      1_0
      COMPLETED
      Sobol
      16.201340
      145398.236121
      1309.918679
    

    

      2
      2
      2_0
      COMPLETED
      Sobol
      17.427218
      160157.286524
      1041.052447
    

    

      3
      3
      3_0
      COMPLETED
      Sobol
      60.735904
      165845.632869
      1443.179306
    

    

      4
      4
      4_0
      COMPLETED
      Sobol
      26.643834
      151077.091554
      674.439288
    

    

      5
      5
      5_0
      COMPLETED
      Sobol
      19.171328
      146024.532346
      1581.858320
    

    

      6
      6
      6_0
      COMPLETED
      Sobol
      15.849621
      161288.831494
      848.275501
    

    

      7
      7
      7_0
      COMPLETED
      Sobol
      77.053370
      155573.462676
      1198.582433
    

    

      8
      8
      8_0
      COMPLETED
      Sobol
      12.619759
      140372.670637
      964.873435
    

    

      9
      9
      9_0
      COMPLETED
      Sobol
      15.949864
      138226.612601
      1474.784081
    

    

      10
      10
      10_0
      COMPLETED
      MBM
      10.567268
      142552.529623
      1662.076570
    

    

      11
      11
      11_0
      COMPLETED
      MBM
      20.740411
      138912.300526
      662.076570
    

    

      12
      12
      12_0
      COMPLETED
      MBM
      15.603704
      142901.500396
      662.076570
    

    

      13
      13
      13_0
      COMPLETED
      MBM
      13.467454
      140113.143129
      1662.076570
    

    

      14
      14
      14_0
      COMPLETED
      MBM
      24.543823
      146846.087723
      662.076570
    

    

      15
      15
      15_0
      COMPLETED
      MBM
      9.659196
      142176.329772
      1308.949748
    

    

      16
      16
      16_0
      COMPLETED
      MBM
      10.016747
      142559.880620
      1311.335974
    

    

      17
      17
      17_0
      COMPLETED
      MBM
      10.662418
      141775.818810
      1331.373970
    

    

      18
      18
      18_0
      COMPLETED
      MBM
      63.313327
      161162.570712
      1662.076570
    

    

      19
      19
      19_0
      COMPLETED
      MBM
      9.804084
      142556.439659
      1430.043773
    

    

      20
      20
      20_0
      COMPLETED
      MBM
      18.288981
      159870.192969
      662.076570
    

    

      21
      21
      21_0
      COMPLETED
      MBM
      20.227451
      159436.628663
      662.076570
    

    

      22
      22
      22_0
      COMPLETED
      MBM
      41.743425
      150002.566849
      1662.076570
    

    

      23
      23
      23_0
      COMPLETED
      MBM
      48.392807
      160262.239497
      662.076570
    

    

      24
      24
      24_0
      COMPLETED
      MBM
      54.726581
      167982.843276
      662.076570
    

    

      25
      25
      25_0
      COMPLETED
      MBM
      12.455523
      143287.336686
      986.585398
    

    

      26
      26
      26_0
      COMPLETED
      MBM
      16.316409
      137982.843276
      1118.146096
    

    

      27
      27
      27_0
      COMPLETED
      MBM
      20.145375
      148904.012598
      1078.240649
    

    

      28
      28
      28_0
      COMPLETED
      MBM
      13.162487
      140073.859933
      1294.887357
    

    

      29
      29
      29_0
      COMPLETED
      MBM
      12.090061
      140902.378246
      1485.310689
    

    

      30
      30
      30_0
      COMPLETED
      MBM
      11.255295
      143106.209136
      1145.395445
    

    

      31
      31
      31_0
      COMPLETED
      MBM
      17.401187
      137982.843276
      1662.076570
    

    

      32
      32
      32_0
      COMPLETED
      MBM
      8.747275
      141700.622181
      1155.676177
    

    

      33
      33
      33_0
      COMPLETED
      MBM
      13.749409
      143978.719797
      1215.471240
    

    

      34
      34
      34_0
      COMPLETED
      MBM
      14.675176
      144829.635065
      1013.187010
    

  











optimal_parameters, metrics, _, _ = agent.ax_client.get_best_parameterization(use_model_predictions=False)
optimal_parameters









{'big_r': 141700.62218067932,
 'toroid_focus:toroidMirror01:r': 1155.676177494709}













from bluesky.plans import list_scan

uid = RE(
    list_scan(
        [screen],
        toro_r,
        [optimal_parameters[toro_r.name]],
        toro_R,
        [optimal_parameters[toro_R.name]],
    )
)













image = tiled_client[uid[0]][f"primary/{screen.name}"].read().squeeze()
plt.imshow(image)
plt.colorbar()
plt.title("Optimized toroid Mirror Beam")
plt.show()








../_images/42a6b58e81b845e1efde773c77cfa6d92ff57cdb31184ad2544f6e861c8d3801.png