From 228c18da9f717bef7d42538f6a64933755d9d54b Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Thu, 19 Mar 2026 10:24:33 +0000 Subject: [PATCH 01/46] HDF5/SQLite test data generator --- tests/generate_test_hdf5.py | 303 ++++++++++++++++++++++++++++++++++++ 1 file changed, 303 insertions(+) create mode 100644 tests/generate_test_hdf5.py diff --git a/tests/generate_test_hdf5.py b/tests/generate_test_hdf5.py new file mode 100644 index 00000000..d5eadfc2 --- /dev/null +++ b/tests/generate_test_hdf5.py @@ -0,0 +1,303 @@ +"""Generate synthetic HDF5 files visible to the running ICON server. + +Creates HDF5 files in the configured results directory and inserts the +matching SQLite records (experiment_source, job, scan_parameter, job_run) +so the server can find the data by job ID. + +Usage:: + + uv run python tests/generate_test_hdf5.py + +The script prints the job ID for each created entry so you can navigate to +it in the UI at http://localhost:8004. + +Requirements: +- The ICON database must already exist (run the server at least once so + Alembic has applied all migrations). +- The results directory must be writable. +""" + +from __future__ import annotations + +import json +from datetime import datetime, timedelta + +import h5py # type: ignore +import numpy as np +import sqlalchemy +import sqlalchemy.orm + +from icon.config.config import get_config +from icon.server.data_access.db_context.sqlite import engine +from icon.server.data_access.models.enums import JobRunStatus, JobStatus +from icon.server.data_access.models.sqlite.experiment_source import ExperimentSource +from icon.server.data_access.models.sqlite.job import Job +from icon.server.data_access.models.sqlite.job_run import JobRun +from icon.server.data_access.models.sqlite.scan_parameter import ScanParameter + +# --------------------------------------------------------------------------- +# Shared experiment source — reused across all generated jobs +# --------------------------------------------------------------------------- + +_EXPERIMENT_ID = "test.SyntheticExperiment (SyntheticExperiment)" + + +def _get_or_create_experiment_source(session: sqlalchemy.orm.Session) -> ExperimentSource: + existing = session.execute( + sqlalchemy.select(ExperimentSource).where( + ExperimentSource.experiment_id == _EXPERIMENT_ID + ) + ).scalar_one_or_none() + if existing: + return existing + source = ExperimentSource(experiment_id=_EXPERIMENT_ID) + session.add(source) + session.flush() # populate source.id without committing + return source + + +def _insert_job_and_run( + session: sqlalchemy.orm.Session, + source: ExperimentSource, + scan_values: list[float], + variable_id: str, + scheduled_time: datetime, +) -> tuple[Job, JobRun]: + """Insert a Job, ScanParameter, and JobRun; return both ORM objects.""" + job = Job( + experiment_source_id=source.id, + status=JobStatus.PROCESSED, + repetitions=1, + number_of_shots=1, + ) + session.add(job) + session.flush() # populate job.id + + scan_param = ScanParameter( + job_id=job.id, + variable_id=variable_id, + scan_values=scan_values, + ) + session.add(scan_param) + + run = JobRun( + job_id=job.id, + scheduled_time=scheduled_time, + status=JobRunStatus.DONE, + ) + session.add(run) + session.flush() + + return job, run + + +def _hdf5_path(scheduled_time: datetime) -> str: + """Return the HDF5 file path for a given scheduled time. + + Must match exactly how ``get_filename_by_job_id`` builds the name: + ``f"{scheduled_time}.h5"`` + """ + results_dir = get_config().data.results_dir + return f"{results_dir}/{scheduled_time}.h5" + + +def _write_hdf5( + filepath: str, + job_id: int, + x: np.ndarray, + y: np.ndarray, + variable_id: str, + result_channel: str, +) -> None: + """Write a minimal ICON-compatible HDF5 file.""" + n = len(x) + with h5py.File(filepath, "w") as h5: + h5.attrs["number_of_data_points"] = n + h5.attrs["number_of_shots"] = 1 + h5.attrs["experiment_id"] = _EXPERIMENT_ID + h5.attrs["job_id"] = job_id + h5.attrs["repetitions"] = 1 + h5.attrs["realtime_scan"] = False + + scan_dtype = [("timestamp", "S26"), (variable_id, np.float64)] + scan_ds = h5.create_dataset( + "scan_parameters", + shape=(n, 1), + dtype=scan_dtype, + compression="gzip", + ) + for i in range(n): + scan_ds[i] = (b"2025-01-01T00:00:00.000000", x[i]) + + result_dtype = [(result_channel, np.float64)] + result_ds = h5.create_dataset( + "result_channels", + shape=(n,), + dtype=result_dtype, + compression="gzip", + ) + result_ds[result_channel] = y + result_ds.attrs["Plot window metadata"] = json.dumps([ + {"name": "Results", "index": 0, "type": "readout", + "channel_names": [result_channel]}, + ]) + + shot_group = h5.create_group("shot_channels") + shot_group.attrs["Plot window metadata"] = json.dumps([]) + vector_group = h5.create_group("vector_channels") + vector_group.attrs["Plot window metadata"] = json.dumps([]) + h5.create_group("parameters") + + +def _create_job( + x: np.ndarray, + y: np.ndarray, + variable_id: str, + result_channel: str, + scheduled_time: datetime, + label: str, +) -> int: + """Create SQLite records + HDF5 file; return the job ID.""" + with sqlalchemy.orm.Session(engine) as session: + source = _get_or_create_experiment_source(session) + job, run = _insert_job_and_run( + session, + source, + scan_values=x.tolist(), + variable_id=variable_id, + scheduled_time=scheduled_time, + ) + session.commit() + job_id = job.id + + filepath = _hdf5_path(scheduled_time) + _write_hdf5(filepath, job_id, x, y, variable_id, result_channel) + print(f"[{label}] job_id={job_id} file={filepath}") + return job_id + + +# --------------------------------------------------------------------------- +# Curve generators — one per scenario +# --------------------------------------------------------------------------- + +# Use a fixed base time and offset each scenario by a minute so filenames +# don't collide even if the script is re-run on the same second. +_BASE_TIME = datetime(2025, 6, 1, 12, 0, 0) + + +def generate_clean_lorentzian() -> int: + """Clean Lorentzian peak (y0=1, A=5, x0=150 MHz, gamma=5 MHz).""" + x = np.linspace(100, 200, 100) + y = 1.0 + 5.0 / (1 + ((x - 150.0) / 5.0) ** 2) + y += np.random.default_rng(42).normal(0, 0.05, len(x)) + return _create_job( + x, y, + variable_id="frequency", + result_channel="counts", + scheduled_time=_BASE_TIME, + label="lorentzian_clean", + ) + + +def generate_noisy_lorentzian() -> int: + """Noisy Lorentzian peak (same params, noise=1.0).""" + x = np.linspace(100, 200, 100) + y = 1.0 + 5.0 / (1 + ((x - 150.0) / 5.0) ** 2) + y += np.random.default_rng(42).normal(0, 1.0, len(x)) + return _create_job( + x, y, + variable_id="frequency", + result_channel="counts", + scheduled_time=_BASE_TIME + timedelta(minutes=1), + label="lorentzian_noisy", + ) + + +def generate_w_shape() -> int: + """W-shaped curve: two Lorentzian dips at 130 and 170 MHz.""" + x = np.linspace(100, 200, 200) + y = ( + 10.0 + - 5.0 / (1 + ((x - 130.0) / 3.0) ** 2) + - 5.0 / (1 + ((x - 170.0) / 3.0) ** 2) + ) + y += np.random.default_rng(42).normal(0, 0.1, len(x)) + return _create_job( + x, y, + variable_id="frequency", + result_channel="counts", + scheduled_time=_BASE_TIME + timedelta(minutes=2), + label="w_shape", + ) + + +def generate_gaussian() -> int: + """Gaussian peak (y0=2, A=3, x0=5, sigma=0.8).""" + x = np.linspace(0, 10, 100) + y = 2.0 + 3.0 * np.exp(-((x - 5.0) ** 2) / (2 * 0.8**2)) + y += np.random.default_rng(42).normal(0, 0.05, len(x)) + return _create_job( + x, y, + variable_id="detuning", + result_channel="fluorescence", + scheduled_time=_BASE_TIME + timedelta(minutes=3), + label="gaussian", + ) + + +def generate_poly2() -> int: + """Quadratic curve (a=2, b=-3, c=1).""" + x = np.linspace(-5, 5, 50) + y = 2.0 * x**2 - 3.0 * x + 1.0 + y += np.random.default_rng(42).normal(0, 0.5, len(x)) + return _create_job( + x, y, + variable_id="voltage", + result_channel="counts", + scheduled_time=_BASE_TIME + timedelta(minutes=4), + label="poly2", + ) + + +def generate_harmonic() -> int: + """Harmonic oscillation (y0=1, A=2, omega=4, phi=0.5).""" + x = np.linspace(0, 10, 200) + y = 1.0 + 2.0 * np.cos(4.0 * x + 0.5) + y += np.random.default_rng(42).normal(0, 0.1, len(x)) + return _create_job( + x, y, + variable_id="time", + result_channel="population", + scheduled_time=_BASE_TIME + timedelta(minutes=5), + label="harmonic", + ) + + +def generate_damped_harmonic() -> int: + """Damped harmonic (y0=1, A=2, k=-0.3, omega=4, phi=0.5).""" + x = np.linspace(0, 10, 200) + y = 1.0 + np.exp(-0.3 * x) * 2.0 * np.cos(4.0 * x + 0.5) + y += np.random.default_rng(42).normal(0, 0.05, len(x)) + return _create_job( + x, y, + variable_id="time", + result_channel="population", + scheduled_time=_BASE_TIME + timedelta(minutes=6), + label="damped_harmonic", + ) + + +if __name__ == "__main__": + print(f"Results dir : {get_config().data.results_dir}") + print(f"Database : {get_config().databases.sqlite.file}") + print() + + generate_clean_lorentzian() + generate_noisy_lorentzian() + generate_w_shape() + generate_gaussian() + generate_poly2() + generate_harmonic() + generate_damped_harmonic() + + print("\nDone. Open http://localhost:8004 and go to the Data page to see the jobs.") From 4cf61fb63b4627004ab20b40e37a56bb184ad3ce Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Thu, 19 Mar 2026 14:47:12 +0000 Subject: [PATCH 02/46] Curve fitting engine --- pyproject.toml | 1 + src/icon/server/fitting/__init__.py | 10 ++ src/icon/server/fitting/fit_runner.py | 150 +++++++++++++++++++ src/icon/server/fitting/models.py | 203 ++++++++++++++++++++++++++ 4 files changed, 364 insertions(+) create mode 100644 src/icon/server/fitting/__init__.py create mode 100644 src/icon/server/fitting/fit_runner.py create mode 100644 src/icon/server/fitting/models.py diff --git a/pyproject.toml b/pyproject.toml index e7d147d8..acccbc4e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,6 +17,7 @@ server = [ "alembic>=1.14.0", "filelock>=3.16.1", "influxdb>=5.3.2", + "scipy>=1.14.0", "sqlalchemy>=2.0.36", "tables>=3.10.1", "h5py>=3.12.1", diff --git a/src/icon/server/fitting/__init__.py b/src/icon/server/fitting/__init__.py new file mode 100644 index 00000000..14a4531a --- /dev/null +++ b/src/icon/server/fitting/__init__.py @@ -0,0 +1,10 @@ +from icon.server.fitting.fit_runner import FitResult, run_curve_fit +from icon.server.fitting.models import FIT_MODELS, FitFunctionType, FitModel + +__all__ = [ + "FIT_MODELS", + "FitFunctionType", + "FitModel", + "FitResult", + "run_curve_fit", +] diff --git a/src/icon/server/fitting/fit_runner.py b/src/icon/server/fitting/fit_runner.py new file mode 100644 index 00000000..d50b3eb0 --- /dev/null +++ b/src/icon/server/fitting/fit_runner.py @@ -0,0 +1,150 @@ +from __future__ import annotations + +import logging +from dataclasses import dataclass + +import numpy as np +import numpy.typing as npt +from scipy.optimize import curve_fit # type: ignore[import-untyped] + +from icon.server.fitting.models import FIT_MODELS, FitFunctionType + +logger = logging.getLogger(__name__) + +_EXPECTED_RANGE_LEN = 2 +_MAX_FIT_EVALS = 10000 + + +@dataclass +class FitResult: + """Result of a curve fit operation.""" + + result_channel: str + func_type: str + x_range: list[float] | None + init: dict[str, float] + result: dict[str, float] + goodness: dict[str, float] + success: bool + message: str + + +def _filter_valid( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], +) -> tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]: + mask = np.isfinite(x) & np.isfinite(y) + return x[mask], y[mask] + + +def _compute_goodness( + y: npt.NDArray[np.float64], + y_fit: npt.NDArray[np.float64], + n_params: int, +) -> dict[str, float]: + n = len(y) + ss_res = float(np.sum((y - y_fit) ** 2)) + ss_tot = float(np.sum((y - np.mean(y)) ** 2)) + + r2 = 1.0 - ss_res / ss_tot if ss_tot > 0 else 0.0 + + dof = n - n_params + chi2_red = ss_res / dof if dof > 0 else float("inf") + + log_term = float(n * np.log(ss_res / n)) if ss_res > 0 and n > 0 else 0.0 + aic = log_term + 2.0 * n_params + bic = log_term + n_params * float(np.log(n)) if n > 0 else 0.0 + + return {"r2": r2, "chi2_red": chi2_red, "aic": aic, "bic": bic} + + +def _make_error( + result_channel: str, + func_type: str, + x_range: list[float] | None, + init: dict[str, float], + message: str, +) -> FitResult: + return FitResult( + result_channel=result_channel, + func_type=func_type, + x_range=x_range, + init=init, + result={}, + goodness={}, + success=False, + message=message, + ) + + +def _apply_range( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], + x_range: list[float] | None, +) -> tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]: + if x_range is not None and len(x_range) == _EXPECTED_RANGE_LEN: + mask = (x >= x_range[0]) & (x <= x_range[1]) + return x[mask], y[mask] + return x, y + + +def run_curve_fit( # noqa: PLR0913, C901 + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], + result_channel: str, + func_type: FitFunctionType, + x_range: list[float] | None = None, + init: dict[str, float] | None = None, +) -> FitResult: + """Run a curve fit on the given data.""" + if func_type not in FIT_MODELS: + return _make_error( + result_channel, func_type, x_range, init or {}, + f"Unknown fit function: {func_type}", + ) + + model = FIT_MODELS[func_type] + x, y = _apply_range(x, y, x_range) + x, y = _filter_valid(x, y) + + min_points = len(model.param_names) + 1 + if len(x) < min_points: + return _make_error( + result_channel, func_type, x_range, init or {}, + f"Insufficient data points: {len(x)} (need at least {min_points})", + ) + + # Build initial guess: merge user overrides on top of auto-guess + p0 = list(model.guess(x, y)) + if init: + for i, name in enumerate(model.param_names): + if name in init: + p0[i] = init[name] + + init_dict = dict(zip(model.param_names, p0)) + + try: + popt, _ = curve_fit(model.func, x, y, p0=p0, maxfev=_MAX_FIT_EVALS) + except (RuntimeError, ValueError) as exc: + return _make_error( + result_channel, func_type, x_range, init_dict, str(exc), + ) + + result_dict = dict(zip(model.param_names, (float(v) for v in popt))) + + if func_type == "poly2" and result_dict.get("a", 0) != 0: + result_dict["vertex"] = -result_dict["b"] / (2.0 * result_dict["a"]) + + y_fit = model.func(x, *popt) + goodness = _compute_goodness(y, y_fit, len(model.param_names)) + + return FitResult( + result_channel=result_channel, + func_type=func_type, + x_range=x_range, + init=init_dict, + result=result_dict, + goodness=goodness, + success=True, + message="Fit converged", + ) diff --git a/src/icon/server/fitting/models.py b/src/icon/server/fitting/models.py new file mode 100644 index 00000000..0a035d0d --- /dev/null +++ b/src/icon/server/fitting/models.py @@ -0,0 +1,203 @@ +from __future__ import annotations + +from dataclasses import dataclass +from typing import TYPE_CHECKING, Literal + +import numpy as np +import numpy.typing as npt + +if TYPE_CHECKING: + from collections.abc import Callable + +FitFunctionType = Literal[ + "gaussian", + "lorentzian", + "poly2", + "harmonic", + "damped_harmonic", +] + +_MIN_FWHM_POINTS = 2 + + +@dataclass(frozen=True) +class FitModel: + """Definition of a curve-fitting model.""" + + func: Callable[..., npt.NDArray[np.float64]] + param_names: list[str] + default_update_param: str + guess: Callable[[npt.NDArray[np.float64], npt.NDArray[np.float64]], list[float]] + + +def _lorentzian( + x: npt.NDArray[np.float64], + y0: float, + a: float, + x0: float, + gamma: float, +) -> npt.NDArray[np.float64]: + return np.asarray(y0 + a / (1.0 + ((x - x0) / gamma) ** 2)) + + +def _lorentzian_guess( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], +) -> list[float]: + n = len(y) + n10 = max(1, n // 10) + sorted_y = np.sort(y) + baseline = float(np.median(np.concatenate([sorted_y[:n10], sorted_y[-n10:]]))) + + peak_idx = int(np.argmax(np.abs(y - baseline))) + a = float(y[peak_idx] - baseline) + x0 = float(x[peak_idx]) + + above = np.where(np.abs(y - baseline) >= np.abs(a) / 2.0)[0] + if len(above) >= _MIN_FWHM_POINTS: + gamma = float(abs(x[above[-1]] - x[above[0]])) / 2.0 + else: + gamma = float(abs(x[-1] - x[0])) / 4.0 + + gamma = max(gamma, 1e-12) + return [baseline, a, x0, gamma] + + +def _gaussian( + x: npt.NDArray[np.float64], + y0: float, + a: float, + x0: float, + sigma: float, +) -> npt.NDArray[np.float64]: + return np.asarray(y0 + a * np.exp(-((x - x0) ** 2) / (2.0 * sigma**2))) + + +def _gaussian_guess( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], +) -> list[float]: + n = len(y) + n20 = max(1, n // 5) + baseline = float(np.mean(np.sort(y)[:n20])) + + peak_idx = int(np.argmax(np.abs(y - baseline))) + a = float(y[peak_idx] - baseline) + x0 = float(x[peak_idx]) + + half_max = np.abs(a) / 2.0 + above = np.where(np.abs(y - baseline) >= half_max)[0] + if len(above) >= _MIN_FWHM_POINTS: + fwhm = float(abs(x[above[-1]] - x[above[0]])) + sigma = fwhm / (2.0 * np.sqrt(2.0 * np.log(2.0))) + else: + sigma = float(abs(x[-1] - x[0])) / 10.0 + + sigma = max(sigma, 1e-12) + return [baseline, a, x0, sigma] + + +def _poly2( + x: npt.NDArray[np.float64], + a: float, + b: float, + c: float, +) -> npt.NDArray[np.float64]: + return np.asarray(a * x**2 + b * x + c) + + +def _poly2_guess( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], +) -> list[float]: + coeffs = np.polyfit(x, y, 2) + return coeffs.tolist() + + +def _harmonic( + x: npt.NDArray[np.float64], + y0: float, + a: float, + omega: float, + phi: float, +) -> npt.NDArray[np.float64]: + return np.asarray(y0 + a * np.cos(omega * x + phi)) + + +_MIN_FFT_POINTS = 3 + + +def _harmonic_guess( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], +) -> list[float]: + y0 = float(np.mean(y)) + a = float(np.max(y) - np.min(y)) / 2.0 + n = len(y) + if n >= _MIN_FFT_POINTS: + dx = float(np.mean(np.diff(x))) + fft_vals = np.abs(np.fft.rfft(y - y0)) + fft_vals[0] = 0 + if len(fft_vals) > 1: + peak_freq_idx = int(np.argmax(fft_vals)) + freq = peak_freq_idx / (n * dx) if dx > 0 else 1.0 + omega = 2.0 * np.pi * freq + else: + omega = 1.0 + else: + omega = 1.0 + phi = 0.0 + return [y0, a, omega, phi] + + +def _damped_harmonic( # noqa: PLR0913 + x: npt.NDArray[np.float64], + y0: float, + a: float, + k: float, + omega: float, + phi: float, +) -> npt.NDArray[np.float64]: + return np.asarray(y0 + np.exp(k * x) * a * np.cos(omega * x + phi)) + + +def _damped_harmonic_guess( + x: npt.NDArray[np.float64], + y: npt.NDArray[np.float64], +) -> list[float]: + hg = _harmonic_guess(x, y) + return [hg[0], hg[1], 0.0, hg[2], hg[3]] + + +FIT_MODELS: dict[str, FitModel] = { + "lorentzian": FitModel( + func=_lorentzian, + param_names=["y0", "a", "x0", "gamma"], + default_update_param="x0", + guess=_lorentzian_guess, + ), + "gaussian": FitModel( + func=_gaussian, + param_names=["y0", "a", "x0", "sigma"], + default_update_param="x0", + guess=_gaussian_guess, + ), + "poly2": FitModel( + func=_poly2, + param_names=["a", "b", "c"], + default_update_param="vertex", + guess=_poly2_guess, + ), + "harmonic": FitModel( + func=_harmonic, + param_names=["y0", "a", "omega", "phi"], + default_update_param="omega", + guess=_harmonic_guess, + ), + "damped_harmonic": FitModel( + func=_damped_harmonic, + param_names=["y0", "a", "k", "omega", "phi"], + default_update_param="omega", + guess=_damped_harmonic_guess, + ), +} From 6311196d0fe716be9219cdc24bdd6b66119d6359 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Fri, 20 Mar 2026 09:15:41 +0000 Subject: [PATCH 03/46] Persist fit results in HDF5 and expose run_fit/delete_fit API --- .../server/api/experiment_data_controller.py | 95 +++++++++++++++++++ .../experiment_data_repository.py | 89 +++++++++++++++++ 2 files changed, 184 insertions(+) diff --git a/src/icon/server/api/experiment_data_controller.py b/src/icon/server/api/experiment_data_controller.py index 86abf682..95637ef1 100644 --- a/src/icon/server/api/experiment_data_controller.py +++ b/src/icon/server/api/experiment_data_controller.py @@ -2,11 +2,16 @@ from dataclasses import asdict from typing import Any +import numpy as np import pydase from icon.server.data_access.repositories.experiment_data_repository import ( ExperimentDataRepository, + delete_fit_result_by_job_id, + write_fit_result_by_job_id, ) +from icon.server.fitting import run_curve_fit +from icon.server.web_server.socketio_emit_queue import emit_queue __all__ = ["ExperimentDataController"] @@ -42,3 +47,93 @@ async def get_experiment_data_by_job_id( max_transfer_bytes=max_transfer_bytes, ) return asdict(result) + + async def run_fit( + self, + job_id: int, + result_channel: str, + func_type: str, + x_range: list[float] | None = None, + init: dict[str, float] | None = None, + ) -> dict[str, Any]: + """Run a curve fit on a result channel of a finished job. + + Args: + job_id: Job identifier. + result_channel: Name of the result channel to fit. + func_type: Fit model name (e.g. "lorentzian"). + x_range: Optional [min, max] to restrict fit domain. + init: Optional initial parameter overrides. + + Returns: + Serialised FitResult dict. + """ + data = await asyncio.to_thread( + ExperimentDataRepository.get_experiment_data_by_job_id, + job_id=job_id, + ) + + # Find the first non-timestamp scan parameter for x-values + scan_param_name = next( + (p for p in data.scan_parameters if p != "timestamp"), None + ) + if scan_param_name is None: + return asdict(run_curve_fit( + x=np.array([]), + y=np.array([]), + result_channel=result_channel, + func_type=func_type, # type: ignore[arg-type] + )) + + scan_values = data.scan_parameters[scan_param_name] + channel_values = data.result_channels.get(result_channel, {}) + + # Build aligned x, y arrays sorted by index + indices = sorted(set(scan_values.keys()) & set(channel_values.keys())) + x = np.array([float(scan_values[i]) for i in indices]) + y = np.array([float(channel_values[i]) for i in indices]) + + fit_result = await asyncio.to_thread( + run_curve_fit, + x=x, + y=y, + result_channel=result_channel, + func_type=func_type, # type: ignore[arg-type] + x_range=x_range, + init=init, + ) + + if fit_result.success: + await asyncio.to_thread( + write_fit_result_by_job_id, + job_id=job_id, + fit_result=fit_result, + ) + + result_dict = asdict(fit_result) + emit_queue.put({ + "event": f"experiment_fit_{job_id}", + "data": result_dict, + }) + return result_dict + + async def delete_fit( + self, + job_id: int, + result_channel: str, + ) -> None: + """Delete a fit result for a result channel. + + Args: + job_id: Job identifier. + result_channel: Name of the result channel whose fit to remove. + """ + await asyncio.to_thread( + delete_fit_result_by_job_id, + job_id=job_id, + result_channel=result_channel, + ) + emit_queue.put({ + "event": f"experiment_fit_{job_id}", + "data": {"result_channel": result_channel, "deleted": True}, + }) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index a1418e4a..8e4ba4a4 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -18,6 +18,7 @@ ) from icon.server.data_access.repositories.job_repository import JobRepository from icon.server.data_access.repositories.job_run_repository import JobRunRepository +from icon.server.fitting.fit_runner import FitResult from icon.server.utils.h5py import get_hdf5_dtype, get_result_channels_dataset from icon.server.web_server.socketio_emit_queue import emit_queue @@ -125,6 +126,8 @@ class ExperimentData: """Mapping of parameter id to time series (tuple of timestamp str and value).""" total_data_points: int """Total number of data points in the HDF5 file (before truncation).""" + fits: dict[str, dict[str, object]] + """Fit results keyed by result channel name.""" def get_filename_by_job_id(job_id: int) -> str: @@ -630,6 +633,7 @@ def get_experiment_data_by_job_id( realtime_scan=False, parameters={}, total_data_points=0, + fits={}, ) filename = get_filename_by_job_id(job_id) @@ -752,6 +756,7 @@ def get_experiment_data_by_job_id( for entry in sequence_json_dataset ] data.parameters = extract_parameter_values(h5file) + data.fits = _read_fits_from_hdf5(h5file) return data @@ -763,3 +768,87 @@ def last_value(d: h5py.Dataset) -> ParameterValue: return ParameterValue(timestamp=ts.decode(), value=val) return {key: last_value(dataset) for key, dataset in h5file["parameters"].items()} + + +def _read_fits_from_hdf5( + h5file: h5py.File, +) -> dict[str, dict[str, object]]: + """Read all fit results from an HDF5 file.""" + if "fits" not in h5file: + return {} + + fits: dict[str, dict[str, object]] = {} + fits_group = cast("h5py.Group", h5file["fits"]) + for channel_name in fits_group: + channel_group = cast("h5py.Group", fits_group[channel_name]) + fit_data = json.loads(cast("str", channel_group.attrs["fit_result"])) + fits[channel_name] = fit_data + return fits + + +def write_fit_result_by_job_id( + *, + job_id: int, + fit_result: FitResult, +) -> None: + """Write a fit result into the HDF5 file for a job. + + Creates or overwrites the ``fits/`` group. + + Args: + job_id: Job identifier. + fit_result: The fit result to persist. + """ + filename = get_filename_by_job_id(job_id) + file = f"{get_config().data.results_dir}/{filename}" + lock_path = ( + f"{get_config().data.results_dir}/.{filename}" + f"{ExperimentDataRepository.LOCK_EXTENSION}" + ) + with FileLock(lock_path), h5py.File(file, "a") as h5file: + fits_group = h5file.require_group("fits") + channel = fit_result.result_channel + if channel in fits_group: + del fits_group[channel] + grp = fits_group.create_group(channel) + grp.attrs["fit_result"] = json.dumps(asdict(fit_result)) + + +def get_fit_results_by_job_id(*, job_id: int) -> dict[str, dict[str, object]]: + """Read all fit results for a job from its HDF5 file. + + Args: + job_id: Job identifier. + + Returns: + Dict mapping result channel names to their fit result dicts. + """ + filename = get_filename_by_job_id(job_id) + file = f"{get_config().data.results_dir}/{filename}" + if not os.path.exists(file): + return {} + + lock_path = ( + f"{get_config().data.results_dir}/.{filename}" + f"{ExperimentDataRepository.LOCK_EXTENSION}" + ) + with FileLock(lock_path), h5py.File(file, "r") as h5file: + return _read_fits_from_hdf5(h5file) + + +def delete_fit_result_by_job_id(*, job_id: int, result_channel: str) -> None: + """Delete a fit result for a specific channel from the HDF5 file. + + Args: + job_id: Job identifier. + result_channel: Name of the result channel whose fit to delete. + """ + filename = get_filename_by_job_id(job_id) + file = f"{get_config().data.results_dir}/{filename}" + lock_path = ( + f"{get_config().data.results_dir}/.{filename}" + f"{ExperimentDataRepository.LOCK_EXTENSION}" + ) + with FileLock(lock_path), h5py.File(file, "a") as h5file: + if "fits" in h5file and result_channel in h5file["fits"]: + del h5file["fits"][result_channel] From 5228c8093f083c1cf28d7bde6859fd79d16553b7 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Fri, 20 Mar 2026 16:32:08 +0000 Subject: [PATCH 04/46] Fit panel UI with plot overlay and click-to-guide --- frontend/src/components/JobView.tsx | 26 +- frontend/src/components/ResultChannelPlot.tsx | 49 ++- frontend/src/components/jobView/FitPanel.tsx | 315 ++++++++++++++++++ frontend/src/hooks/useExperimentData.tsx | 19 ++ frontend/src/types/ExperimentData.ts | 12 + frontend/src/utils/fitFunctions.ts | 61 ++++ 6 files changed, 476 insertions(+), 6 deletions(-) create mode 100644 frontend/src/components/jobView/FitPanel.tsx create mode 100644 frontend/src/utils/fitFunctions.ts diff --git a/frontend/src/components/JobView.tsx b/frontend/src/components/JobView.tsx index 12b3f57c..9f9df5e4 100644 --- a/frontend/src/components/JobView.tsx +++ b/frontend/src/components/JobView.tsx @@ -1,4 +1,4 @@ -import { useEffect, useMemo, useState } from "react"; +import { useCallback, useEffect, useMemo, useState } from "react"; import { Alert, Button, @@ -27,6 +27,7 @@ import { deserialize } from "../utils/deserializer"; import { updateJobParams } from "../utils/updateJobParams"; import { cancelJob } from "../utils/cancelJob"; import HistogramPlot from "./jobView/HistogramPlot"; +import FitPanel from "./jobView/FitPanel"; function getPlotTitle(scheduledTime?: string, experimentName?: string): string { if (!scheduledTime) return experimentName || ""; @@ -90,6 +91,9 @@ export const JobView = ({ experimentData.total_data_points > 0 && loadedDataPoints < experimentData.total_data_points; + const [clickedX, setClickedX] = useState(null); + const handleChartClick = useCallback((x: number) => setClickedX(x), []); + const [showRepetitions, setShowRepetitions] = useState(() => { const v = localStorage.getItem("showRepetitions"); return v ? JSON.parse(v) : false; @@ -206,10 +210,10 @@ export const JobView = ({ {jobId} - {experimentMetadata?.constructor_kwargs.name && ( + {experimentMetadata?.constructor_kwargs?.name && ( <> {" "} - - {experimentMetadata?.constructor_kwargs.name} ( + - {experimentMetadata?.constructor_kwargs?.name} ( {experimentMetadata?.class_name}) )} @@ -396,7 +400,7 @@ export const JobView = ({ title={win.name} subtitle={getPlotTitle( jobRunInfo?.scheduled_time, - experimentMetadata?.constructor_kwargs.name, + experimentMetadata?.constructor_kwargs?.name, )} /> )} @@ -435,19 +439,31 @@ export const JobView = ({ title={win.name} subtitle={getPlotTitle( jobRunInfo?.scheduled_time, - experimentMetadata?.constructor_kwargs.name, + experimentMetadata?.constructor_kwargs?.name, )} repetitions={jobInfo?.repetitions} showRepetitions={showRepetitions} scanParameters={jobInfo?.scan_parameters} windowSize={windowSize} yRange={{ min: yMin, max: yMax }} + fits={is1D ? experimentData.fits : undefined} + onChartClick={is1D ? handleChartClick : undefined} /> )} ))} + {is1D && jobId && ( + + + + )} + diff --git a/frontend/src/components/ResultChannelPlot.tsx b/frontend/src/components/ResultChannelPlot.tsx index cbf5cd49..43274f69 100644 --- a/frontend/src/components/ResultChannelPlot.tsx +++ b/frontend/src/components/ResultChannelPlot.tsx @@ -1,5 +1,5 @@ import React, { useCallback, useEffect, useMemo, useState } from "react"; -import { ExperimentData } from "../types/ExperimentData"; +import { ExperimentData, FitResult } from "../types/ExperimentData"; import { ReactECharts, ReactEChartsProps } from "./ReactEcharts"; import { EChartsOption } from "echarts"; import type { ECharts } from "echarts/core"; @@ -7,6 +7,7 @@ import { useNotifications } from "@toolpad/core"; import { copyEChartsToClipboard } from "../utils/copyEChartsToClipboard"; import { ScanParameter } from "../types/ScanParameter"; import { buildResultChannelChartSeries } from "../utils/buildResultChannelChartSeries"; +import { evaluateFit } from "../utils/fitFunctions"; interface ResultChannelPlotProps { experimentData: ExperimentData; @@ -19,6 +20,8 @@ interface ResultChannelPlotProps { scanParameters: ScanParameter[] | undefined; windowSize?: number | null; yRange?: { min: number | null; max: number | null }; + fits?: Record; + onChartClick?: (xValue: number) => void; } const formatAxisLabel = (value: string): string => { @@ -100,6 +103,8 @@ const ResultChannelPlot = ({ scanParameters = [], windowSize = null, yRange, + fits = {}, + onChartClick, }: ResultChannelPlotProps) => { const [chart, setChart] = useState(null); const notifications = useNotifications(); @@ -340,6 +345,33 @@ const ResultChannelPlot = ({ }; } + // Add fit curve overlays for 1D scans + if (scanParameters.length === 1 && fits) { + const ordinaryEntry = scanInfo.find((p) => p.name !== "timestamp"); + const fitXArr = (ordinaryEntry?.scanValues ?? []) as number[]; + + for (const [channelName, fitResult] of Object.entries(fits)) { + if (!fitResult.success || !channelNames.includes(channelName)) continue; + + const xMinVal = fitResult.x_range ? fitResult.x_range[0] : Math.min(...fitXArr); + const xMaxVal = fitResult.x_range ? fitResult.x_range[1] : Math.max(...fitXArr); + const nPoints = 200; + const step = (xMaxVal - xMinVal) / (nPoints - 1); + const fitX = Array.from({ length: nPoints }, (_, i) => xMinVal + i * step); + const fitY = evaluateFit(fitResult.func_type, fitResult.result, fitX); + const fitData = fitX.map((x, i) => [x, fitY[i]]); + + (chartSeries as unknown[]).push({ + name: `${channelName} fit`, + type: "line", + data: fitData, + showSymbol: false, + lineStyle: { type: "dashed", width: 2 }, + tooltip: { show: false }, + }); + } + } + return { title, textStyle: { fontFamily: "sans-serif", fontSize: 12 }, @@ -381,6 +413,8 @@ const ResultChannelPlot = ({ showRepetitions, windowSize, yRange, + fits, + channelNames, ]); const updateChart = useCallback( @@ -390,6 +424,19 @@ const ResultChannelPlot = ({ [setChart], ); + useEffect(() => { + if (!chart || !onChartClick) return; + const handler = (params: { data?: unknown[] | unknown }) => { + if (Array.isArray(params.data) && typeof params.data[0] === "number") { + onChartClick(params.data[0]); + } + }; + chart.on("click", handler); + return () => { + chart.off("click", handler); + }; + }, [chart, onChartClick]); + useEffect(() => { if (!is2D || !chart) return; diff --git a/frontend/src/components/jobView/FitPanel.tsx b/frontend/src/components/jobView/FitPanel.tsx new file mode 100644 index 00000000..90520780 --- /dev/null +++ b/frontend/src/components/jobView/FitPanel.tsx @@ -0,0 +1,315 @@ +import { useState } from "react"; +import { + Button, + Card, + CardContent, + FormControl, + Grid, + InputLabel, + MenuItem, + Select, + Table, + TableBody, + TableCell, + TableHead, + TableRow, + TextField, + Typography, + Accordion, + AccordionSummary, + AccordionDetails, + Alert, +} from "@mui/material"; +import { ExpandMore } from "@mui/icons-material"; +import { ExperimentData, FitResult } from "../../types/ExperimentData"; +import { runMethod } from "../../socket"; +import { FIT_PARAM_NAMES, FIT_TYPES } from "../../utils/fitFunctions"; + +interface FitPanelProps { + jobId: string; + experimentData: ExperimentData; + clickedX: number | null; +} + +export default function FitPanel({ jobId, experimentData, clickedX }: FitPanelProps) { + const channelNames = Object.keys(experimentData.result_channels); + const [selectedChannel, setSelectedChannel] = useState(channelNames[0] ?? ""); + const [funcType, setFuncType] = useState("lorentzian"); + const [xMin, setXMin] = useState(""); + const [xMax, setXMax] = useState(""); + const [initOverrides, setInitOverrides] = useState>({}); + const [fitting, setFitting] = useState(false); + + const [updateParamId, setUpdateParamId] = useState(""); + const [updateValue, setUpdateValue] = useState(""); + + const fit: FitResult | undefined = experimentData.fits[selectedChannel]; + const paramNames = FIT_PARAM_NAMES[funcType] ?? []; + + // Pre-fill x0 from click + const effectiveInit = { ...initOverrides }; + if (clickedX !== null && paramNames.includes("x0") && !effectiveInit["x0"]) { + effectiveInit["x0"] = String(clickedX); + } + + const handleFit = () => { + setFitting(true); + const xRange = + xMin !== "" && xMax !== "" ? [parseFloat(xMin), parseFloat(xMax)] : null; + + const init: Record = {}; + for (const [key, val] of Object.entries(effectiveInit)) { + if (val !== "") init[key] = parseFloat(val); + } + + runMethod( + "data.run_fit", + [], + { + job_id: Number(jobId), + result_channel: selectedChannel, + func_type: funcType, + x_range: xRange, + init: Object.keys(init).length > 0 ? init : null, + }, + () => setFitting(false), + ); + }; + + const handleDelete = () => { + runMethod("data.delete_fit", [], { + job_id: Number(jobId), + result_channel: selectedChannel, + }); + }; + + const handleUpdateParameter = () => { + if (!updateParamId || updateValue === "") return; + runMethod("parameters.update_parameter_by_id", [ + updateParamId, + parseFloat(updateValue), + ]); + }; + + // Get scan parameter names for "update parameter" dropdown + const scanParamKeys = Object.keys(experimentData.scan_parameters).filter( + (k) => k !== "timestamp", + ); + const allParamIds = Object.keys(experimentData.parameters); + + return ( + + + + Curve Fitting + + + + + + Channel + + + + + + + Model + + + + + + setXMin(e.target.value)} + /> + + + setXMax(e.target.value)} + /> + + + + + }> + Initial parameter overrides + + + + {paramNames.map((name) => ( + + + setInitOverrides((prev) => ({ + ...prev, + [name]: e.target.value, + })) + } + /> + + ))} + + {clickedX !== null && ( + + Clicked x = {clickedX.toFixed(4)} (used as x0 hint if not overridden) + + )} + + + +
+ + {fit && ( + + )} +
+ + {fit && ( +
+ {!fit.success && ( + + {fit.message} + + )} + {fit.success && ( + <> + + Fit Results ({fit.func_type}) + + + + + Parameter + Value + + + + {Object.entries(fit.result).map(([key, val]) => ( + + {key} + {val.toFixed(6)} + + ))} + +
+ + + Goodness of Fit + + + + {Object.entries(fit.goodness).map(([key, val]) => ( + + {key} + {val.toFixed(6)} + + ))} + +
+ + + Update Parameter + + + + + Parameter + + + + + setUpdateValue(e.target.value)} + /> + + + + + + + )} +
+ )} +
+
+ ); +} diff --git a/frontend/src/hooks/useExperimentData.tsx b/frontend/src/hooks/useExperimentData.tsx index 1d3b1c63..c7354a01 100644 --- a/frontend/src/hooks/useExperimentData.tsx +++ b/frontend/src/hooks/useExperimentData.tsx @@ -3,6 +3,7 @@ import { runMethod, socket } from "../socket"; import { ExperimentData, ExperimentDataPoint, + FitResult, ParameterValue, } from "../types/ExperimentData"; import { SerializedObject } from "../types/SerializedObject"; @@ -21,6 +22,7 @@ const emptyExperimentData: ExperimentData = { json_sequences: [], parameters: {}, total_data_points: 0, + fits: {}, }; /** @@ -109,9 +111,25 @@ export function useExperimentData(jobId: string | undefined) { }); }; + const fitEvent = `experiment_fit_${jobId}`; + const handleFitEvent = (data: FitResult & { deleted?: boolean }) => { + setExperimentData((prev) => { + if (data.deleted) { + const { [data.result_channel]: _removed, ...rest } = prev.fits; + void _removed; + return { ...prev, fits: rest }; + } + return { + ...prev, + fits: { ...prev.fits, [data.result_channel]: data }, + }; + }); + }; + socket.on(dataPointEvent, handleNewDataPoint); socket.on(metadataEvent, handleMetadata); socket.on(parameterValueEvent, handleValueEvent); + socket.on(fitEvent, handleFitEvent); runMethod("data.get_experiment_data_by_job_id", [], { job_id: jobId }, (ack) => { const deserialized = deserialize(ack as SerializedObject) as @@ -131,6 +149,7 @@ export function useExperimentData(jobId: string | undefined) { socket.off(dataPointEvent, handleNewDataPoint); socket.off(metadataEvent, handleMetadata); socket.off(parameterValueEvent, handleValueEvent); + socket.off(fitEvent, handleFitEvent); }; }, [jobId]); diff --git a/frontend/src/types/ExperimentData.ts b/frontend/src/types/ExperimentData.ts index cad018f4..005fecca 100644 --- a/frontend/src/types/ExperimentData.ts +++ b/frontend/src/types/ExperimentData.ts @@ -28,6 +28,17 @@ export interface ParameterValue { value: string | number | boolean; } +export interface FitResult { + result_channel: string; + func_type: string; + x_range: [number, number] | null; + init: Record; + result: Record; + goodness: Record; + success: boolean; + message: string; +} + export interface ExperimentData { plot_windows: PlotWindows; shot_channels: Record>; @@ -37,4 +48,5 @@ export interface ExperimentData { json_sequences: [number, string][]; parameters: Record; total_data_points: number; + fits: Record; } diff --git a/frontend/src/utils/fitFunctions.ts b/frontend/src/utils/fitFunctions.ts new file mode 100644 index 00000000..2a151772 --- /dev/null +++ b/frontend/src/utils/fitFunctions.ts @@ -0,0 +1,61 @@ +/** + * Evaluate a fit function at the given x-values using fitted parameters. + */ +export function evaluateFit( + funcType: string, + params: Record, + xValues: number[], +): number[] { + switch (funcType) { + case "lorentzian": + return xValues.map((x) => { + const { y0, a, x0, gamma } = params; + return y0 + a / (1 + ((x - x0) / gamma) ** 2); + }); + + case "gaussian": + return xValues.map((x) => { + const { y0, a, x0, sigma } = params; + return y0 + a * Math.exp(-((x - x0) ** 2) / (2 * sigma ** 2)); + }); + + case "poly2": + return xValues.map((x) => { + const { a, b, c } = params; + return a * x ** 2 + b * x + c; + }); + + case "harmonic": + return xValues.map((x) => { + const { y0, a, omega, phi } = params; + return y0 + a * Math.cos(omega * x + phi); + }); + + case "damped_harmonic": + return xValues.map((x) => { + const { y0, a, k, omega, phi } = params; + return y0 + Math.exp(k * x) * a * Math.cos(omega * x + phi); + }); + + default: + return xValues.map(() => NaN); + } +} + +/** Names of the fit parameters for each model type. */ +export const FIT_PARAM_NAMES: Record = { + lorentzian: ["y0", "a", "x0", "gamma"], + gaussian: ["y0", "a", "x0", "sigma"], + poly2: ["a", "b", "c"], + harmonic: ["y0", "a", "omega", "phi"], + damped_harmonic: ["y0", "a", "k", "omega", "phi"], +}; + +/** Available fit model types. */ +export const FIT_TYPES = [ + "lorentzian", + "gaussian", + "poly2", + "harmonic", + "damped_harmonic", +] as const; From bda5d4e2aad674c8ae6e6e6c5979e39285d26036 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Mon, 23 Mar 2026 10:21:16 +0000 Subject: [PATCH 05/46] Tests for curve fitting --- frontend/jest.config.js | 7 ++ .../src/utils/__tests__/fitFunctions.test.ts | 72 ++++++++++++ tests/server/fitting/__init__.py | 0 tests/server/fitting/test_fit_runner.py | 109 ++++++++++++++++++ tests/server/fitting/test_models.py | 83 +++++++++++++ 5 files changed, 271 insertions(+) create mode 100644 frontend/jest.config.js create mode 100644 frontend/src/utils/__tests__/fitFunctions.test.ts create mode 100644 tests/server/fitting/__init__.py create mode 100644 tests/server/fitting/test_fit_runner.py create mode 100644 tests/server/fitting/test_models.py diff --git a/frontend/jest.config.js b/frontend/jest.config.js new file mode 100644 index 00000000..c44ef36e --- /dev/null +++ b/frontend/jest.config.js @@ -0,0 +1,7 @@ +/** @type {import('ts-jest').JestConfigWithTsJest} **/ +export default { + testEnvironment: "node", + transform: { + "^.+.tsx?$": ["ts-jest", {}], + }, +}; diff --git a/frontend/src/utils/__tests__/fitFunctions.test.ts b/frontend/src/utils/__tests__/fitFunctions.test.ts new file mode 100644 index 00000000..92679d90 --- /dev/null +++ b/frontend/src/utils/__tests__/fitFunctions.test.ts @@ -0,0 +1,72 @@ +import { evaluateFit } from "../fitFunctions"; + +describe("evaluateFit", () => { + describe("lorentzian", () => { + it("should return peak value at x0", () => { + const params = { y0: 0, a: 10, x0: 5, gamma: 1 }; + const result = evaluateFit("lorentzian", params, [5]); + expect(result[0]).toBeCloseTo(10, 5); + }); + + it("should return baseline far from peak", () => { + const params = { y0: 3, a: 10, x0: 0, gamma: 1 }; + const result = evaluateFit("lorentzian", params, [1e6]); + expect(result[0]).toBeCloseTo(3, 1); + }); + + it("should be symmetric around x0", () => { + const params = { y0: 0, a: 1, x0: 5, gamma: 1 }; + const [left] = evaluateFit("lorentzian", params, [3]); + const [right] = evaluateFit("lorentzian", params, [7]); + expect(left).toBeCloseTo(right, 10); + }); + }); + + describe("gaussian", () => { + it("should return peak value at x0", () => { + const params = { y0: 0, a: 5, x0: 3, sigma: 1 }; + const result = evaluateFit("gaussian", params, [3]); + expect(result[0]).toBeCloseTo(5, 5); + }); + }); + + describe("poly2", () => { + it("should compute quadratic correctly", () => { + const params = { a: 1, b: 2, c: 3 }; + const result = evaluateFit("poly2", params, [0, 1, 2]); + expect(result[0]).toBeCloseTo(3); + expect(result[1]).toBeCloseTo(6); + expect(result[2]).toBeCloseTo(11); + }); + }); + + describe("harmonic", () => { + it("should return y0 + A at phase 0", () => { + const params = { y0: 1, a: 2, omega: Math.PI, phi: 0 }; + const result = evaluateFit("harmonic", params, [0]); + expect(result[0]).toBeCloseTo(3); + }); + }); + + describe("damped_harmonic", () => { + it("should match harmonic with k=0", () => { + const x = [0, 1, 2, 3, 4, 5]; + const harmonicParams = { y0: 1, a: 2, omega: 3, phi: 0.5 }; + const dampedParams = { y0: 1, a: 2, k: 0, omega: 3, phi: 0.5 }; + + const harmonic = evaluateFit("harmonic", harmonicParams, x); + const damped = evaluateFit("damped_harmonic", dampedParams, x); + + for (let i = 0; i < x.length; i++) { + expect(damped[i]).toBeCloseTo(harmonic[i], 10); + } + }); + }); + + describe("unknown function", () => { + it("should return NaN for unknown types", () => { + const result = evaluateFit("unknown", {}, [1, 2, 3]); + expect(result.every((v) => isNaN(v))).toBe(true); + }); + }); +}); diff --git a/tests/server/fitting/__init__.py b/tests/server/fitting/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/server/fitting/test_fit_runner.py b/tests/server/fitting/test_fit_runner.py new file mode 100644 index 00000000..0db625b4 --- /dev/null +++ b/tests/server/fitting/test_fit_runner.py @@ -0,0 +1,109 @@ +import numpy as np +import pytest + +from icon.server.fitting.fit_runner import FitResult, run_curve_fit + + +def _synthetic_lorentzian( + n: int = 100, + noise: float = 0.0, +) -> tuple[np.ndarray, np.ndarray, dict[str, float]]: + """Generate synthetic Lorentzian data.""" + true_params = {"y0": 1.0, "a": 5.0, "x0": 5.0, "gamma": 0.5} + x = np.linspace(0, 10, n) + y = true_params["y0"] + true_params["a"] / ( + 1.0 + ((x - true_params["x0"]) / true_params["gamma"]) ** 2 + ) + if noise > 0: + rng = np.random.default_rng(42) + y = y + rng.normal(0, noise, n) + return x, y, true_params + + +class TestRunCurveFit: + def test_lorentzian_clean(self) -> None: + x, y, true = _synthetic_lorentzian(noise=0.01) + result = run_curve_fit(x, y, "ch1", "lorentzian") + assert result.success + assert result.result["x0"] == pytest.approx(true["x0"], abs=0.1) + assert result.result["a"] == pytest.approx(true["a"], abs=0.5) + assert result.goodness["r2"] > 0.99 + + def test_lorentzian_noisy(self) -> None: + x, y, true = _synthetic_lorentzian(noise=0.5) + result = run_curve_fit(x, y, "ch1", "lorentzian") + assert result.success + assert result.result["x0"] == pytest.approx(true["x0"], abs=1.0) + + def test_unknown_func_type(self) -> None: + x = np.linspace(0, 10, 50) + y = np.ones(50) + result = run_curve_fit(x, y, "ch1", "nonexistent") # type: ignore[arg-type] + assert not result.success + assert "Unknown" in result.message + + def test_insufficient_points(self) -> None: + x = np.array([1.0, 2.0]) + y = np.array([1.0, 2.0]) + result = run_curve_fit(x, y, "ch1", "lorentzian") + assert not result.success + assert "Insufficient" in result.message + + def test_nan_data_filtered(self) -> None: + x, y, _ = _synthetic_lorentzian(n=100, noise=0.01) + y[10] = np.nan + y[20] = np.inf + x[30] = np.nan + result = run_curve_fit(x, y, "ch1", "lorentzian") + assert result.success + + def test_x_range_filter(self) -> None: + x, y, true = _synthetic_lorentzian(n=200, noise=0.01) + result = run_curve_fit(x, y, "ch1", "lorentzian", x_range=[3.0, 7.0]) + assert result.success + assert result.result["x0"] == pytest.approx(true["x0"], abs=0.2) + + def test_init_override(self) -> None: + x, y, true = _synthetic_lorentzian(noise=0.01) + result = run_curve_fit(x, y, "ch1", "lorentzian", init={"x0": 4.9}) + assert result.success + assert result.result["x0"] == pytest.approx(true["x0"], abs=0.2) + + def test_w_shape_with_init(self) -> None: + """Two Lorentzian dips; init selects correct peak.""" + x = np.linspace(0, 20, 200) + y = 10.0 - 5.0 / (1 + ((x - 5.0) / 0.5) ** 2) - 5.0 / ( + 1 + ((x - 15.0) / 0.5) ** 2 + ) + # Guide to the second peak + result = run_curve_fit(x, y, "ch1", "lorentzian", init={"x0": 15.0}) + assert result.success + assert result.result["x0"] == pytest.approx(15.0, abs=1.0) + + def test_gaussian_fit(self) -> None: + x = np.linspace(-5, 5, 100) + y = 2.0 + 3.0 * np.exp(-((x - 1.0) ** 2) / (2.0 * 0.5**2)) + rng = np.random.default_rng(42) + y += rng.normal(0, 0.05, len(y)) + result = run_curve_fit(x, y, "ch1", "gaussian") + assert result.success + assert result.result["x0"] == pytest.approx(1.0, abs=0.3) + + def test_poly2_fit(self) -> None: + x = np.linspace(-5, 5, 50) + y = 2.0 * x**2 - 3.0 * x + 1.0 + result = run_curve_fit(x, y, "ch1", "poly2") + assert result.success + assert result.result["a"] == pytest.approx(2.0, abs=0.1) + assert "vertex" in result.result + + def test_fit_result_fields(self) -> None: + x, y, _ = _synthetic_lorentzian(noise=0.01) + result = run_curve_fit(x, y, "ch1", "lorentzian") + assert isinstance(result, FitResult) + assert result.func_type == "lorentzian" + assert result.result_channel == "ch1" + assert "r2" in result.goodness + assert "chi2_red" in result.goodness + assert "aic" in result.goodness + assert "bic" in result.goodness diff --git a/tests/server/fitting/test_models.py b/tests/server/fitting/test_models.py new file mode 100644 index 00000000..feecc930 --- /dev/null +++ b/tests/server/fitting/test_models.py @@ -0,0 +1,83 @@ +import numpy as np +import pytest + +from icon.server.fitting.models import FIT_MODELS + + +class TestLorentzianFunction: + def test_peak_at_x0(self) -> None: + model = FIT_MODELS["lorentzian"] + x = np.array([5.0]) + result = model.func(x, 0.0, 10.0, 5.0, 1.0) + assert result[0] == pytest.approx(10.0) + + def test_baseline(self) -> None: + model = FIT_MODELS["lorentzian"] + x = np.array([1e6]) + result = model.func(x, 3.0, 10.0, 0.0, 1.0) + assert result[0] == pytest.approx(3.0, abs=0.01) + + def test_symmetry(self) -> None: + model = FIT_MODELS["lorentzian"] + x0 = 5.0 + left = model.func(np.array([x0 - 2.0]), 0.0, 1.0, x0, 1.0) + right = model.func(np.array([x0 + 2.0]), 0.0, 1.0, x0, 1.0) + assert left[0] == pytest.approx(right[0]) + + +class TestLorentzianGuess: + def test_reasonable_peak_guess(self) -> None: + model = FIT_MODELS["lorentzian"] + x = np.linspace(0, 10, 100) + y0, a, x0, gamma = 1.0, 5.0, 5.0, 0.5 + y = y0 + a / (1.0 + ((x - x0) / gamma) ** 2) + guess = model.guess(x, y) + # x0 guess should be near the peak + assert abs(guess[2] - x0) < 1.0 + + def test_dip_guess(self) -> None: + model = FIT_MODELS["lorentzian"] + x = np.linspace(0, 10, 100) + y = 10.0 - 5.0 / (1.0 + ((x - 5.0) / 0.5) ** 2) + guess = model.guess(x, y) + # A should be negative for a dip + assert guess[1] < 0 + + +class TestGaussianFunction: + def test_peak_at_x0(self) -> None: + model = FIT_MODELS["gaussian"] + x = np.array([3.0]) + result = model.func(x, 0.0, 5.0, 3.0, 1.0) + assert result[0] == pytest.approx(5.0) + + +class TestPoly2Function: + def test_known_values(self) -> None: + model = FIT_MODELS["poly2"] + x = np.array([0.0, 1.0, 2.0]) + result = model.func(x, 1.0, 2.0, 3.0) + np.testing.assert_array_almost_equal(result, [3.0, 6.0, 11.0]) + + def test_guess(self) -> None: + model = FIT_MODELS["poly2"] + x = np.linspace(-5, 5, 50) + y = 2.0 * x**2 - 3.0 * x + 1.0 + guess = model.guess(x, y) + assert guess[0] == pytest.approx(2.0, abs=0.1) + + +class TestHarmonicFunction: + def test_at_zero_phase(self) -> None: + model = FIT_MODELS["harmonic"] + x = np.array([0.0]) + result = model.func(x, 1.0, 2.0, np.pi, 0.0) + assert result[0] == pytest.approx(3.0) + + +class TestDampedHarmonicFunction: + def test_no_damping_matches_harmonic(self) -> None: + x = np.linspace(0, 10, 50) + harmonic = FIT_MODELS["harmonic"].func(x, 1.0, 2.0, 3.0, 0.5) + damped = FIT_MODELS["damped_harmonic"].func(x, 1.0, 2.0, 0.0, 3.0, 0.5) + np.testing.assert_array_almost_equal(harmonic, damped) From af221cf4f390b5d5c40b045ac562140ec003652a Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Mon, 23 Mar 2026 20:21:39 +0000 Subject: [PATCH 06/46] Improve fit panel --- frontend/src/components/JobView.tsx | 12 +- frontend/src/components/ResultChannelPlot.tsx | 15 +- frontend/src/components/jobView/FitPanel.tsx | 107 ++++++++---- frontend/src/pages/data.tsx | 2 +- frontend/src/utils/fitFunctions.ts | 9 ++ .../experiment_data_repository.py | 61 ++++--- src/icon/server/fitting/fit_runner.py | 3 + tests/generate_test_hdf5.py | 152 ++++++++++++++++++ 8 files changed, 303 insertions(+), 58 deletions(-) diff --git a/frontend/src/components/JobView.tsx b/frontend/src/components/JobView.tsx index 9f9df5e4..3b3eb7e1 100644 --- a/frontend/src/components/JobView.tsx +++ b/frontend/src/components/JobView.tsx @@ -38,9 +38,11 @@ function getPlotTitle(scheduledTime?: string, experimentName?: string): string { export const JobView = ({ jobId, onLoaded, + showFitPanel = false, }: { jobId: string | undefined; onLoaded?: () => void; + showFitPanel?: boolean; }) => { const [experimentMetadata, setExperimentMetadata] = useState(null); @@ -94,6 +96,9 @@ export const JobView = ({ const [clickedX, setClickedX] = useState(null); const handleChartClick = useCallback((x: number) => setClickedX(x), []); + // Reset clicked position when switching jobs + useEffect(() => setClickedX(null), [jobId]); + const [showRepetitions, setShowRepetitions] = useState(() => { const v = localStorage.getItem("showRepetitions"); return v ? JSON.parse(v) : false; @@ -446,20 +451,21 @@ export const JobView = ({ scanParameters={jobInfo?.scan_parameters} windowSize={windowSize} yRange={{ min: yMin, max: yMax }} - fits={is1D ? experimentData.fits : undefined} - onChartClick={is1D ? handleChartClick : undefined} + fits={showFitPanel && is1D ? experimentData.fits : undefined} + onChartClick={showFitPanel && is1D ? handleChartClick : undefined} /> )}
))} - {is1D && jobId && ( + {showFitPanel && is1D && jobId && jobInfo?.status === JobStatus.PROCESSED && ( )} diff --git a/frontend/src/components/ResultChannelPlot.tsx b/frontend/src/components/ResultChannelPlot.tsx index 43274f69..42b60d2e 100644 --- a/frontend/src/components/ResultChannelPlot.tsx +++ b/frontend/src/components/ResultChannelPlot.tsx @@ -426,14 +426,19 @@ const ResultChannelPlot = ({ useEffect(() => { if (!chart || !onChartClick) return; - const handler = (params: { data?: unknown[] | unknown }) => { - if (Array.isArray(params.data) && typeof params.data[0] === "number") { - onChartClick(params.data[0]); + const zr = chart.getZr(); + const handler = (params: { offsetX: number; offsetY: number }) => { + const point = [params.offsetX, params.offsetY]; + if (chart.containPixel("grid", point)) { + const dataPoint = chart.convertFromPixel("grid", point); + if (dataPoint && typeof dataPoint[0] === "number" && isFinite(dataPoint[0])) { + onChartClick(dataPoint[0]); + } } }; - chart.on("click", handler); + zr.on("click", handler); return () => { - chart.off("click", handler); + zr.off("click", handler); }; }, [chart, onChartClick]); diff --git a/frontend/src/components/jobView/FitPanel.tsx b/frontend/src/components/jobView/FitPanel.tsx index 90520780..d5c1960c 100644 --- a/frontend/src/components/jobView/FitPanel.tsx +++ b/frontend/src/components/jobView/FitPanel.tsx @@ -1,4 +1,4 @@ -import { useState } from "react"; +import { useEffect, useState } from "react"; import { Button, Card, @@ -21,17 +21,30 @@ import { Alert, } from "@mui/material"; import { ExpandMore } from "@mui/icons-material"; +import { useNotifications } from "@toolpad/core"; import { ExperimentData, FitResult } from "../../types/ExperimentData"; +import { ScanParameter } from "../../types/ScanParameter"; import { runMethod } from "../../socket"; -import { FIT_PARAM_NAMES, FIT_TYPES } from "../../utils/fitFunctions"; +import { + FIT_DEFAULT_UPDATE_PARAM, + FIT_PARAM_NAMES, + FIT_TYPES, +} from "../../utils/fitFunctions"; interface FitPanelProps { jobId: string; experimentData: ExperimentData; clickedX: number | null; + scanParameters?: ScanParameter[]; } -export default function FitPanel({ jobId, experimentData, clickedX }: FitPanelProps) { +export default function FitPanel({ + jobId, + experimentData, + clickedX, + scanParameters = [], +}: FitPanelProps) { + const notifications = useNotifications(); const channelNames = Object.keys(experimentData.result_channels); const [selectedChannel, setSelectedChannel] = useState(channelNames[0] ?? ""); const [funcType, setFuncType] = useState("lorentzian"); @@ -43,12 +56,53 @@ export default function FitPanel({ jobId, experimentData, clickedX }: FitPanelPr const [updateParamId, setUpdateParamId] = useState(""); const [updateValue, setUpdateValue] = useState(""); + const channelKey = channelNames.join(","); + useEffect(() => { + if ( + channelNames.length > 0 && + (!selectedChannel || !channelNames.includes(selectedChannel)) + ) { + setSelectedChannel(channelNames[0]); + } + }, [channelKey]); + + // Reset form state when switching jobs + useEffect(() => { + setInitOverrides({}); + setXMin(""); + setXMax(""); + setUpdateParamId(""); + setUpdateValue(""); + }, [jobId]); + const fit: FitResult | undefined = experimentData.fits[selectedChannel]; const paramNames = FIT_PARAM_NAMES[funcType] ?? []; - // Pre-fill x0 from click + // Non-realtime scan parameters (the ones relevant for fitting) + const ordinaryScanParams = scanParameters.filter((sp) => !sp.realtime); + + // Pre-fill update parameter and value when a new fit arrives + const defaultParam = fit?.success + ? FIT_DEFAULT_UPDATE_PARAM[fit.func_type] + : undefined; + const defaultValue = + defaultParam && fit?.result && defaultParam in fit.result + ? fit.result[defaultParam] + : undefined; + + useEffect(() => { + if (!fit?.success) return; + if (ordinaryScanParams.length > 0 && !updateParamId) { + setUpdateParamId(ordinaryScanParams[0].variable_id); + } + if (defaultValue !== undefined) { + setUpdateValue(String(defaultValue)); + } + }, [fit?.success, defaultValue]); + + // Pre-fill x0 from click (only if user hasn't touched x0 at all) const effectiveInit = { ...initOverrides }; - if (clickedX !== null && paramNames.includes("x0") && !effectiveInit["x0"]) { + if (clickedX !== null && paramNames.includes("x0") && !("x0" in initOverrides)) { effectiveInit["x0"] = String(clickedX); } @@ -85,18 +139,21 @@ export default function FitPanel({ jobId, experimentData, clickedX }: FitPanelPr const handleUpdateParameter = () => { if (!updateParamId || updateValue === "") return; - runMethod("parameters.update_parameter_by_id", [ - updateParamId, - parseFloat(updateValue), - ]); + const displayName = + ordinaryScanParams.find((sp) => sp.variable_id === updateParamId)?.name ?? + updateParamId; + runMethod( + "parameters.update_parameter_by_id", + [updateParamId, parseFloat(updateValue)], + {}, + () => + notifications.show(`Updated ${displayName} to ${updateValue}`, { + autoHideDuration: 3000, + severity: "success", + }), + ); }; - // Get scan parameter names for "update parameter" dropdown - const scanParamKeys = Object.keys(experimentData.scan_parameters).filter( - (k) => k !== "timestamp", - ); - const allParamIds = Object.keys(experimentData.parameters); - return ( @@ -188,7 +245,7 @@ export default function FitPanel({ jobId, experimentData, clickedX }: FitPanelPr ))} - {clickedX !== null && ( + {clickedX !== null && paramNames.includes("x0") && ( Clicked x = {clickedX.toFixed(4)} (used as x0 hint if not overridden) @@ -264,23 +321,13 @@ export default function FitPanel({ jobId, experimentData, clickedX }: FitPanelPr diff --git a/frontend/src/pages/data.tsx b/frontend/src/pages/data.tsx index e04b13ed..cbd71aca 100644 --- a/frontend/src/pages/data.tsx +++ b/frontend/src/pages/data.tsx @@ -107,7 +107,7 @@ export function DataPage() { {selectedJobId ? (
{layoutReady ? ( - + ) : (
Loading...
)} diff --git a/frontend/src/utils/fitFunctions.ts b/frontend/src/utils/fitFunctions.ts index 2a151772..3bd11403 100644 --- a/frontend/src/utils/fitFunctions.ts +++ b/frontend/src/utils/fitFunctions.ts @@ -51,6 +51,15 @@ export const FIT_PARAM_NAMES: Record = { damped_harmonic: ["y0", "a", "k", "omega", "phi"], }; +/** Default result parameter to use for "Update Parameter" per model. */ +export const FIT_DEFAULT_UPDATE_PARAM: Record = { + lorentzian: "x0", + gaussian: "x0", + poly2: "vertex", + harmonic: "f", + damped_harmonic: "f", +}; + /** Available fit model types. */ export const FIT_TYPES = [ "lorentzian", diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index 8e4ba4a4..807d0828 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -655,9 +655,12 @@ def get_experiment_data_by_job_id( # Estimate bytes per data point from HDF5 metadata bytes_per_point = 0 - shot_group = cast("h5py.Group", h5file["shot_channels"]) - for ds in shot_group.values(): - bytes_per_point += ds.shape[1] * ds.dtype.itemsize + if "shot_channels" in h5file: + shot_group = cast( + "h5py.Group", h5file["shot_channels"] + ) + for ds in shot_group.values(): + bytes_per_point += ds.shape[1] * ds.dtype.itemsize bytes_per_point += cast( "h5py.Dataset", h5file["result_channels"] ).dtype.itemsize @@ -665,13 +668,14 @@ def get_experiment_data_by_job_id( "h5py.Dataset", h5file["scan_parameters"] ).dtype.itemsize # Add vector channel size (average across all data points) - vector_group = cast("h5py.Group", h5file["vector_channels"]) - total_vector_bytes = 0 - for channel_group in vector_group.values(): - for dataset in cast("h5py.Group", channel_group).values(): - total_vector_bytes += dataset.shape[0] * dataset.dtype.itemsize - if total > 0: - bytes_per_point += total_vector_bytes // total + if "vector_channels" in h5file: + vector_group = cast("h5py.Group", h5file["vector_channels"]) + total_vector_bytes = 0 + for channel_group in vector_group.values(): + for dataset in cast("h5py.Group", channel_group).values(): + total_vector_bytes += dataset.shape[0] * dataset.dtype.itemsize + if total > 0: + bytes_per_point += total_vector_bytes // total # JSON serialisation roughly doubles the raw size bytes_per_point = max(bytes_per_point * 2, 1) @@ -716,31 +720,50 @@ def get_experiment_data_by_job_id( # Convert shot channels into dicts with index as key if "shot_channels" in h5file: - shot_channels_group = cast("h5py.Group", h5file["shot_channels"]) - data.plot_windows["shot_channels"] = json.loads( - cast("str", shot_channels_group.attrs["Plot window metadata"]) + shot_channels_group = cast( + "h5py.Group", h5file["shot_channels"] ) + if "Plot window metadata" in shot_channels_group.attrs: + data.plot_windows["shot_channels"] = json.loads( + cast( + "str", + shot_channels_group.attrs[ + "Plot window metadata" + ], + ) + ) data.shot_channels = { key: dict(enumerate(value[start_index:].tolist(), start=start_index)) # type: ignore for key, value in cast( - "Sequence[tuple[str, h5py.Dataset]]", shot_channels_group.items() + "Sequence[tuple[str, h5py.Dataset]]", + shot_channels_group.items(), ) } if "vector_channels" in h5file: - vector_channels_group = cast("h5py.Group", h5file["vector_channels"]) - data.plot_windows["vector_channels"] = json.loads( - cast("str", vector_channels_group.attrs["Plot window metadata"]) + vector_channels_group = cast( + "h5py.Group", h5file["vector_channels"] ) + if "Plot window metadata" in vector_channels_group.attrs: + data.plot_windows["vector_channels"] = json.loads( + cast( + "str", + vector_channels_group.attrs[ + "Plot window metadata" + ], + ) + ) data.vector_channels = { channel_name: { int(data_point): vector_dataset[:].tolist() for data_point, vector_dataset in cast( - "Sequence[tuple[str, h5py.Dataset]]", vector_group.items() + "Sequence[tuple[str, h5py.Dataset]]", + vector_group.items(), ) } for channel_name, vector_group in cast( - "Sequence[tuple[str, h5py.Group]]", vector_channels_group.items() + "Sequence[tuple[str, h5py.Group]]", + vector_channels_group.items(), ) } diff --git a/src/icon/server/fitting/fit_runner.py b/src/icon/server/fitting/fit_runner.py index d50b3eb0..3fd182fc 100644 --- a/src/icon/server/fitting/fit_runner.py +++ b/src/icon/server/fitting/fit_runner.py @@ -135,6 +135,9 @@ def run_curve_fit( # noqa: PLR0913, C901 if func_type == "poly2" and result_dict.get("a", 0) != 0: result_dict["vertex"] = -result_dict["b"] / (2.0 * result_dict["a"]) + if func_type in ("harmonic", "damped_harmonic") and "omega" in result_dict: + result_dict["f"] = result_dict["omega"] / (2.0 * np.pi) + y_fit = model.func(x, *popt) goodness = _compute_goodness(y, y_fit, len(model.param_names)) diff --git a/tests/generate_test_hdf5.py b/tests/generate_test_hdf5.py index d5eadfc2..a017f29c 100644 --- a/tests/generate_test_hdf5.py +++ b/tests/generate_test_hdf5.py @@ -75,6 +75,7 @@ def _insert_job_and_run( scan_param = ScanParameter( job_id=job.id, + name=variable_id, variable_id=variable_id, scan_values=scan_values, ) @@ -287,6 +288,156 @@ def generate_damped_harmonic() -> int: ) +def _insert_job_and_run_2d( # noqa: PLR0913 + session: sqlalchemy.orm.Session, + source: ExperimentSource, + scan_values_x: list[float], + variable_id_x: str, + scan_values_y: list[float], + variable_id_y: str, + scheduled_time: datetime, +) -> tuple[Job, JobRun]: + """Insert a Job with two ScanParameters and a JobRun; return both ORM objects.""" + job = Job( + experiment_source_id=source.id, + status=JobStatus.PROCESSED, + repetitions=1, + number_of_shots=1, + ) + session.add(job) + session.flush() + + scan_param_x = ScanParameter( + job_id=job.id, + name=variable_id_x, + variable_id=variable_id_x, + scan_values=scan_values_x, + ) + scan_param_y = ScanParameter( + job_id=job.id, + name=variable_id_y, + variable_id=variable_id_y, + scan_values=scan_values_y, + ) + session.add(scan_param_x) + session.add(scan_param_y) + + run = JobRun( + job_id=job.id, + scheduled_time=scheduled_time, + status=JobRunStatus.DONE, + ) + session.add(run) + session.flush() + + return job, run + + +def _write_hdf5_2d( # noqa: PLR0913 + filepath: str, + job_id: int, + x_flat: np.ndarray, + y_flat: np.ndarray, + z: np.ndarray, + variable_id_x: str, + variable_id_y: str, + result_channel: str, +) -> None: + """Write a minimal ICON-compatible HDF5 file for a 2D scan.""" + n = len(z) + with h5py.File(filepath, "w") as h5: + h5.attrs["number_of_data_points"] = n + h5.attrs["number_of_shots"] = 1 + h5.attrs["experiment_id"] = _EXPERIMENT_ID + h5.attrs["job_id"] = job_id + h5.attrs["repetitions"] = 1 + h5.attrs["realtime_scan"] = False + + scan_dtype = [ + ("timestamp", "S26"), + (variable_id_x, np.float64), + (variable_id_y, np.float64), + ] + scan_ds = h5.create_dataset( + "scan_parameters", + shape=(n, 1), + dtype=scan_dtype, + compression="gzip", + ) + for i in range(n): + scan_ds[i] = (b"2025-01-01T00:00:00.000000", x_flat[i], y_flat[i]) + + result_dtype = [(result_channel, np.float64)] + result_ds = h5.create_dataset( + "result_channels", + shape=(n,), + dtype=result_dtype, + compression="gzip", + ) + result_ds[result_channel] = z + result_ds.attrs["Plot window metadata"] = json.dumps([ + {"name": "Results", "index": 0, "type": "readout", + "channel_names": [result_channel]}, + ]) + + shot_group = h5.create_group("shot_channels") + shot_group.attrs["Plot window metadata"] = json.dumps([]) + vector_group = h5.create_group("vector_channels") + vector_group.attrs["Plot window metadata"] = json.dumps([]) + h5.create_group("parameters") + + +def generate_2d_gaussian() -> int: + """2D Gaussian peak over frequency x amplitude grid. + + z = A * exp(-((x-x0)^2/(2*sx^2) + (y-y0)^2/(2*sy^2))) + offset + with A=5, x0=150, y0=5, sx=15, sy=2, offset=1. + """ + variable_id_x = "frequency" + variable_id_y = "amplitude" + result_channel = "counts" + scheduled_time = _BASE_TIME + timedelta(minutes=7) + + nx, ny = 20, 15 + x_vals = np.linspace(100, 200, nx) + y_vals = np.linspace(0, 10, ny) + + # Outer loop over x, inner loop over y + x_grid, y_grid = np.meshgrid(x_vals, y_vals, indexing="ij") + x_flat = x_grid.ravel() + y_flat = y_grid.ravel() + + # 2D Gaussian + amp, x0, y0, sx, sy, offset = 5.0, 150.0, 5.0, 15.0, 2.0, 1.0 + z = amp * np.exp(-( + (x_flat - x0) ** 2 / (2 * sx**2) + + (y_flat - y0) ** 2 / (2 * sy**2) + )) + offset + z += np.random.default_rng(42).normal(0, 0.1, len(z)) + + with sqlalchemy.orm.Session(engine) as session: + source = _get_or_create_experiment_source(session) + job, run = _insert_job_and_run_2d( + session, + source, + scan_values_x=x_vals.tolist(), + variable_id_x=variable_id_x, + scan_values_y=y_vals.tolist(), + variable_id_y=variable_id_y, + scheduled_time=scheduled_time, + ) + session.commit() + job_id = job.id + + filepath = _hdf5_path(scheduled_time) + _write_hdf5_2d( + filepath, job_id, x_flat, y_flat, z, + variable_id_x, variable_id_y, result_channel, + ) + print(f"[2d_gaussian] job_id={job_id} file={filepath}") + return job_id + + if __name__ == "__main__": print(f"Results dir : {get_config().data.results_dir}") print(f"Database : {get_config().databases.sqlite.file}") @@ -299,5 +450,6 @@ def generate_damped_harmonic() -> int: generate_poly2() generate_harmonic() generate_damped_harmonic() + generate_2d_gaussian() print("\nDone. Open http://localhost:8004 and go to the Data page to see the jobs.") From b4702e9460e2de10e8f911f1ed70322a7147a0f2 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Tue, 14 Apr 2026 06:10:04 +0000 Subject: [PATCH 07/46] Move fit curve generation to backend, remove frontend model evaluation --- frontend/src/components/ResultChannelPlot.tsx | 20 ++--- frontend/src/types/ExperimentData.ts | 1 + .../src/utils/__tests__/fitFunctions.test.ts | 84 ++++--------------- frontend/src/utils/fitFunctions.ts | 44 ---------- src/icon/server/fitting/fit_runner.py | 19 +++-- src/icon/server/fitting/models.py | 36 +++++++- 6 files changed, 74 insertions(+), 130 deletions(-) diff --git a/frontend/src/components/ResultChannelPlot.tsx b/frontend/src/components/ResultChannelPlot.tsx index 42b60d2e..7b2e783c 100644 --- a/frontend/src/components/ResultChannelPlot.tsx +++ b/frontend/src/components/ResultChannelPlot.tsx @@ -7,7 +7,6 @@ import { useNotifications } from "@toolpad/core"; import { copyEChartsToClipboard } from "../utils/copyEChartsToClipboard"; import { ScanParameter } from "../types/ScanParameter"; import { buildResultChannelChartSeries } from "../utils/buildResultChannelChartSeries"; -import { evaluateFit } from "../utils/fitFunctions"; interface ResultChannelPlotProps { experimentData: ExperimentData; @@ -347,19 +346,14 @@ const ResultChannelPlot = ({ // Add fit curve overlays for 1D scans if (scanParameters.length === 1 && fits) { - const ordinaryEntry = scanInfo.find((p) => p.name !== "timestamp"); - const fitXArr = (ordinaryEntry?.scanValues ?? []) as number[]; - for (const [channelName, fitResult] of Object.entries(fits)) { - if (!fitResult.success || !channelNames.includes(channelName)) continue; - - const xMinVal = fitResult.x_range ? fitResult.x_range[0] : Math.min(...fitXArr); - const xMaxVal = fitResult.x_range ? fitResult.x_range[1] : Math.max(...fitXArr); - const nPoints = 200; - const step = (xMaxVal - xMinVal) / (nPoints - 1); - const fitX = Array.from({ length: nPoints }, (_, i) => xMinVal + i * step); - const fitY = evaluateFit(fitResult.func_type, fitResult.result, fitX); - const fitData = fitX.map((x, i) => [x, fitY[i]]); + if (!fitResult.success || !fitResult.fit_curve) continue; + if (!channelNames.includes(channelName)) continue; + + const fitData = fitResult.fit_curve.x.map((x, i) => [ + x, + fitResult.fit_curve!.y[i], + ]); (chartSeries as unknown[]).push({ name: `${channelName} fit`, diff --git a/frontend/src/types/ExperimentData.ts b/frontend/src/types/ExperimentData.ts index 005fecca..a699d623 100644 --- a/frontend/src/types/ExperimentData.ts +++ b/frontend/src/types/ExperimentData.ts @@ -37,6 +37,7 @@ export interface FitResult { goodness: Record; success: boolean; message: string; + fit_curve?: { x: number[]; y: number[] }; } export interface ExperimentData { diff --git a/frontend/src/utils/__tests__/fitFunctions.test.ts b/frontend/src/utils/__tests__/fitFunctions.test.ts index 92679d90..24577d52 100644 --- a/frontend/src/utils/__tests__/fitFunctions.test.ts +++ b/frontend/src/utils/__tests__/fitFunctions.test.ts @@ -1,72 +1,24 @@ -import { evaluateFit } from "../fitFunctions"; - -describe("evaluateFit", () => { - describe("lorentzian", () => { - it("should return peak value at x0", () => { - const params = { y0: 0, a: 10, x0: 5, gamma: 1 }; - const result = evaluateFit("lorentzian", params, [5]); - expect(result[0]).toBeCloseTo(10, 5); - }); - - it("should return baseline far from peak", () => { - const params = { y0: 3, a: 10, x0: 0, gamma: 1 }; - const result = evaluateFit("lorentzian", params, [1e6]); - expect(result[0]).toBeCloseTo(3, 1); - }); - - it("should be symmetric around x0", () => { - const params = { y0: 0, a: 1, x0: 5, gamma: 1 }; - const [left] = evaluateFit("lorentzian", params, [3]); - const [right] = evaluateFit("lorentzian", params, [7]); - expect(left).toBeCloseTo(right, 10); - }); +import { FIT_DEFAULT_UPDATE_PARAM, FIT_PARAM_NAMES, FIT_TYPES } from "../fitFunctions"; + +describe("fit model metadata", () => { + it("every FIT_TYPE has param names defined", () => { + for (const ft of FIT_TYPES) { + expect(FIT_PARAM_NAMES[ft]).toBeDefined(); + expect(FIT_PARAM_NAMES[ft].length).toBeGreaterThan(0); + } }); - describe("gaussian", () => { - it("should return peak value at x0", () => { - const params = { y0: 0, a: 5, x0: 3, sigma: 1 }; - const result = evaluateFit("gaussian", params, [3]); - expect(result[0]).toBeCloseTo(5, 5); - }); - }); - - describe("poly2", () => { - it("should compute quadratic correctly", () => { - const params = { a: 1, b: 2, c: 3 }; - const result = evaluateFit("poly2", params, [0, 1, 2]); - expect(result[0]).toBeCloseTo(3); - expect(result[1]).toBeCloseTo(6); - expect(result[2]).toBeCloseTo(11); - }); - }); - - describe("harmonic", () => { - it("should return y0 + A at phase 0", () => { - const params = { y0: 1, a: 2, omega: Math.PI, phi: 0 }; - const result = evaluateFit("harmonic", params, [0]); - expect(result[0]).toBeCloseTo(3); - }); - }); - - describe("damped_harmonic", () => { - it("should match harmonic with k=0", () => { - const x = [0, 1, 2, 3, 4, 5]; - const harmonicParams = { y0: 1, a: 2, omega: 3, phi: 0.5 }; - const dampedParams = { y0: 1, a: 2, k: 0, omega: 3, phi: 0.5 }; - - const harmonic = evaluateFit("harmonic", harmonicParams, x); - const damped = evaluateFit("damped_harmonic", dampedParams, x); - - for (let i = 0; i < x.length; i++) { - expect(damped[i]).toBeCloseTo(harmonic[i], 10); - } - }); + it("every FIT_TYPE has a default update param", () => { + for (const ft of FIT_TYPES) { + expect(FIT_DEFAULT_UPDATE_PARAM[ft]).toBeDefined(); + } }); - describe("unknown function", () => { - it("should return NaN for unknown types", () => { - const result = evaluateFit("unknown", {}, [1, 2, 3]); - expect(result.every((v) => isNaN(v))).toBe(true); - }); + it("FIT_TYPES contains expected models", () => { + expect(FIT_TYPES).toContain("lorentzian"); + expect(FIT_TYPES).toContain("gaussian"); + expect(FIT_TYPES).toContain("poly2"); + expect(FIT_TYPES).toContain("harmonic"); + expect(FIT_TYPES).toContain("damped_harmonic"); }); }); diff --git a/frontend/src/utils/fitFunctions.ts b/frontend/src/utils/fitFunctions.ts index 3bd11403..4cf4bca5 100644 --- a/frontend/src/utils/fitFunctions.ts +++ b/frontend/src/utils/fitFunctions.ts @@ -1,47 +1,3 @@ -/** - * Evaluate a fit function at the given x-values using fitted parameters. - */ -export function evaluateFit( - funcType: string, - params: Record, - xValues: number[], -): number[] { - switch (funcType) { - case "lorentzian": - return xValues.map((x) => { - const { y0, a, x0, gamma } = params; - return y0 + a / (1 + ((x - x0) / gamma) ** 2); - }); - - case "gaussian": - return xValues.map((x) => { - const { y0, a, x0, sigma } = params; - return y0 + a * Math.exp(-((x - x0) ** 2) / (2 * sigma ** 2)); - }); - - case "poly2": - return xValues.map((x) => { - const { a, b, c } = params; - return a * x ** 2 + b * x + c; - }); - - case "harmonic": - return xValues.map((x) => { - const { y0, a, omega, phi } = params; - return y0 + a * Math.cos(omega * x + phi); - }); - - case "damped_harmonic": - return xValues.map((x) => { - const { y0, a, k, omega, phi } = params; - return y0 + Math.exp(k * x) * a * Math.cos(omega * x + phi); - }); - - default: - return xValues.map(() => NaN); - } -} - /** Names of the fit parameters for each model type. */ export const FIT_PARAM_NAMES: Record = { lorentzian: ["y0", "a", "x0", "gamma"], diff --git a/src/icon/server/fitting/fit_runner.py b/src/icon/server/fitting/fit_runner.py index 3fd182fc..d8b7519d 100644 --- a/src/icon/server/fitting/fit_runner.py +++ b/src/icon/server/fitting/fit_runner.py @@ -15,6 +15,9 @@ _MAX_FIT_EVALS = 10000 +_FIT_CURVE_POINTS = 200 + + @dataclass class FitResult: """Result of a curve fit operation.""" @@ -27,6 +30,7 @@ class FitResult: goodness: dict[str, float] success: bool message: str + fit_curve: dict[str, list[float]] | None = None def _filter_valid( @@ -132,15 +136,19 @@ def run_curve_fit( # noqa: PLR0913, C901 result_dict = dict(zip(model.param_names, (float(v) for v in popt))) - if func_type == "poly2" and result_dict.get("a", 0) != 0: - result_dict["vertex"] = -result_dict["b"] / (2.0 * result_dict["a"]) - - if func_type in ("harmonic", "damped_harmonic") and "omega" in result_dict: - result_dict["f"] = result_dict["omega"] / (2.0 * np.pi) + if model.derived_params: + result_dict.update(model.derived_params(result_dict)) y_fit = model.func(x, *popt) goodness = _compute_goodness(y, y_fit, len(model.param_names)) + # Generate smooth fit curve for plotting + x_min, x_max = float(x.min()), float(x.max()) + step = (x_max - x_min) / (_FIT_CURVE_POINTS - 1) + curve_x = [x_min + i * step for i in range(_FIT_CURVE_POINTS)] + curve_y = model.func(np.array(curve_x), *popt).tolist() + fit_curve = {"x": curve_x, "y": curve_y} + return FitResult( result_channel=result_channel, func_type=func_type, @@ -150,4 +158,5 @@ def run_curve_fit( # noqa: PLR0913, C901 goodness=goodness, success=True, message="Fit converged", + fit_curve=fit_curve, ) diff --git a/src/icon/server/fitting/models.py b/src/icon/server/fitting/models.py index 0a035d0d..91c25851 100644 --- a/src/icon/server/fitting/models.py +++ b/src/icon/server/fitting/models.py @@ -28,6 +28,9 @@ class FitModel: param_names: list[str] default_update_param: str guess: Callable[[npt.NDArray[np.float64], npt.NDArray[np.float64]], list[float]] + derived_params: ( + Callable[[dict[str, float]], dict[str, float]] | None + ) = None def _lorentzian( @@ -169,6 +172,32 @@ def _damped_harmonic_guess( return [hg[0], hg[1], 0.0, hg[2], hg[3]] +def _poly2_derived(result: dict[str, float]) -> dict[str, float]: + a = result.get("a", 0) + if a != 0: + return {"vertex": -result["b"] / (2.0 * a)} + return {} + + +def _harmonic_derived(result: dict[str, float]) -> dict[str, float]: + if "omega" in result: + return {"f": result["omega"] / (2.0 * np.pi)} + return {} + + +# Adding a new fit model +# ---------------------- +# 1. Define _my_model(x, p1, p2, ...) -> NDArray (the model function). +# 2. Define _my_model_guess(x, y) -> list[float] (initial parameter estimator). +# 3. (Optional) Define _my_model_derived(result) -> dict if the model has +# useful derived quantities (e.g. vertex from quadratic coefficients). +# 4. Add an entry to FIT_MODELS below. The param_names order must match the +# function signature. default_update_param is the fitted value pre-filled +# in the "Update Parameter" UI (can be a derived param name). +# 5. Add the model name to FIT_TYPES, FIT_PARAM_NAMES, and +# FIT_DEFAULT_UPDATE_PARAM in frontend/src/utils/fitFunctions.ts. +# 6. Add tests in tests/server/fitting/. + FIT_MODELS: dict[str, FitModel] = { "lorentzian": FitModel( func=_lorentzian, @@ -187,17 +216,20 @@ def _damped_harmonic_guess( param_names=["a", "b", "c"], default_update_param="vertex", guess=_poly2_guess, + derived_params=_poly2_derived, ), "harmonic": FitModel( func=_harmonic, param_names=["y0", "a", "omega", "phi"], - default_update_param="omega", + default_update_param="f", guess=_harmonic_guess, + derived_params=_harmonic_derived, ), "damped_harmonic": FitModel( func=_damped_harmonic, param_names=["y0", "a", "k", "omega", "phi"], - default_update_param="omega", + default_update_param="f", guess=_damped_harmonic_guess, + derived_params=_harmonic_derived, ), } From d5eef5dc0bf1c354352280e69a273ea3d0156178 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Tue, 14 Apr 2026 06:36:03 +0000 Subject: [PATCH 08/46] Auto-fit new jobs using the fit model from previous run of same experiment (if exists) --- src/icon/server/fitting/auto_fit.py | 144 +++++++++++++++++++++++ src/icon/server/pre_processing/worker.py | 6 + 2 files changed, 150 insertions(+) create mode 100644 src/icon/server/fitting/auto_fit.py diff --git a/src/icon/server/fitting/auto_fit.py b/src/icon/server/fitting/auto_fit.py new file mode 100644 index 00000000..760c9156 --- /dev/null +++ b/src/icon/server/fitting/auto_fit.py @@ -0,0 +1,144 @@ +"""Auto-fit: repeat the previous fit when a new job finishes.""" + +from __future__ import annotations + +import logging +from dataclasses import asdict +from typing import Any + +import numpy as np + +from icon.server.data_access.models.enums import JobStatus +from icon.server.data_access.repositories.experiment_data_repository import ( + ExperimentData, + ExperimentDataRepository, + get_fit_results_by_job_id, + write_fit_result_by_job_id, +) +from icon.server.data_access.repositories.job_repository import JobRepository +from icon.server.fitting.fit_runner import run_curve_fit +from icon.server.web_server.socketio_emit_queue import emit_queue + +logger = logging.getLogger(__name__) + + +def try_auto_fit(job_id: int, experiment_source_id: int) -> None: + """Auto-fit the new job using the fit config from the previous job. + + Looks up the most recent previous PROCESSED job for the same experiment + source that has a stored fit, then runs the same model on the new data + with fresh initial guesses. Failures are logged but never raised. + + Args: + job_id: The newly completed job. + experiment_source_id: The experiment source to find previous jobs. + """ + try: + _auto_fit(job_id, experiment_source_id) + except Exception: + logger.exception("Auto-fit failed for job %d", job_id) + + +def _auto_fit(job_id: int, experiment_source_id: int) -> None: + previous_job_id = _find_previous_job_with_fit( + experiment_source_id, exclude_job_id=job_id + ) + if previous_job_id is None: + return + + previous_fits = get_fit_results_by_job_id(job_id=previous_job_id) + if not previous_fits: + return + + data = ExperimentDataRepository.get_experiment_data_by_job_id( + job_id=job_id, + max_transfer_bytes=2**62, + ) + + scan_param_name = next( + (p for p in data.scan_parameters if p != "timestamp"), None + ) + if scan_param_name is None: + return + + for channel_name, fit_data in previous_fits.items(): + if fit_data.get("success") and fit_data.get("func_type"): + _fit_channel(job_id, data, scan_param_name, channel_name, fit_data) + + +def _fit_channel( + job_id: int, + data: ExperimentData, + scan_param_name: str, + channel_name: str, + fit_data: dict[str, Any], +) -> None: + """Run a single auto-fit for one channel and persist the result.""" + channel_values = data.result_channels.get(channel_name, {}) + if not channel_values: + return + + scan_values = data.scan_parameters[scan_param_name] + indices = sorted( + set(scan_values.keys()) & set(channel_values.keys()) + ) + x = np.array([float(scan_values[i]) for i in indices]) + y = np.array([float(channel_values[i]) for i in indices]) + + func_type = fit_data["func_type"] + fit_result = run_curve_fit( + x=x, + y=y, + result_channel=channel_name, + func_type=func_type, # type: ignore[arg-type] + ) + + if fit_result.success: + write_fit_result_by_job_id(job_id=job_id, fit_result=fit_result) + emit_queue.put({ + "event": f"experiment_fit_{job_id}", + "data": asdict(fit_result), + }) + logger.info( + "Auto-fit %s on job %d channel '%s' succeeded", + func_type, + job_id, + channel_name, + ) + else: + logger.warning( + "Auto-fit %s on job %d channel '%s' failed: %s", + func_type, + job_id, + channel_name, + fit_result.message, + ) + + +_MAX_PREVIOUS_JOBS_TO_CHECK = 10 + + +def _find_previous_job_with_fit( + experiment_source_id: int, + exclude_job_id: int, +) -> int | None: + """Find the most recent PROCESSED job with a stored fit. + + Only checks the last few jobs to avoid scanning the entire history. + """ + rows = JobRepository.get_job_by_experiment_source_and_status( + experiment_source_id=experiment_source_id, + status=JobStatus.PROCESSED, + ) + # Rows are ordered by (priority asc, created asc), so iterate in reverse + checked = 0 + for (job,) in reversed(rows): + if job.id == exclude_job_id: + continue + fits = get_fit_results_by_job_id(job_id=job.id) + if fits: + return job.id + checked += 1 + if checked >= _MAX_PREVIOUS_JOBS_TO_CHECK: + break + return None diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index a4cccc39..720a349c 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -38,6 +38,7 @@ from icon.server.data_access.repositories.pycrystal_library_repository import ( PycrystalLibraryRepository, ) +from icon.server.fitting.auto_fit import try_auto_fit from icon.server.hardware_processing.task import HardwareProcessingTask if TYPE_CHECKING: @@ -224,6 +225,11 @@ def run(self) -> None: run_id=pre_processing_task.job_run.id, status=JobRunStatus.DONE, ) + + try_auto_fit( + job_id=pre_processing_task.job.id, + experiment_source_id=pre_processing_task.job.experiment_source_id, + ) except Exception as e: logger.exception( "JobRun with id '%s' failed with error: %s", From ea2c5358aa5e1921795a23dd62b6a6c3672749af Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Tue, 14 Apr 2026 06:44:16 +0000 Subject: [PATCH 09/46] npm run build --- .../server/frontend/assets/index-4aMgS08R.js | 45 ------------------- .../server/frontend/assets/index-CwRx0pcN.js | 45 +++++++++++++++++++ src/icon/server/frontend/index.html | 2 +- 3 files changed, 46 insertions(+), 46 deletions(-) delete mode 100644 src/icon/server/frontend/assets/index-4aMgS08R.js create mode 100644 src/icon/server/frontend/assets/index-CwRx0pcN.js diff --git a/src/icon/server/frontend/assets/index-4aMgS08R.js b/src/icon/server/frontend/assets/index-4aMgS08R.js deleted file mode 100644 index 7e63e3fc..00000000 --- a/src/icon/server/frontend/assets/index-4aMgS08R.js +++ /dev/null @@ -1,45 +0,0 @@ -import{r as fb,a as db,b as y,c as rt,j as d,u as Mr,S as hb,d as mb,B as pb,A as bv,e as vb,f as $t,I as St,g as yb,h as $c,T as xv,i as gb,C as Sv,k as Ev,l as il,m as bb,n as Kp,o as xt,s as Uf,p as be,q as gn,t as wv,v as Wn,P as xb,D as Or,w as vf,x as Sb,L as Eb,y as wb,z as wr,G as Cb,E as Cv,F as _b,H as Cr,J as _r,K as Tr,M as Jc,N as _v,O as Tv,Q as xo,R as rl,U 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ic(e,t){return(e.lanes&t)!==0?!0:(e=e.dependencies,!!(e!==null&&cs(e)))}function f1(e,t,n){switch(t.tag){case 3:hl(t,t.stateNode.containerInfo),sa(t,ht,e.memoizedState.cache),Di();break;case 27:case 5:st(t);break;case 4:hl(t,t.stateNode.containerInfo);break;case 10:sa(t,t.type,t.memoizedProps.value);break;case 13:var i=t.memoizedState;if(i!==null)return i.dehydrated!==null?(da(t),t.flags|=128,null):(n&t.child.childLanes)!==0?Cm(e,t,n):(da(t),e=Zn(e,t,n),e!==null?e.sibling:null);da(t);break;case 19:var o=(e.flags&128)!==0;if(i=(n&t.childLanes)!==0,i||(Ai(e,t,n,!1),i=(n&t.childLanes)!==0),o){if(i)return Tm(e,t,n);t.flags|=128}if(o=t.memoizedState,o!==null&&(o.rendering=null,o.tail=null,o.lastEffect=null),ce(mt,mt.current),i)break;return null;case 22:case 23:return t.lanes=0,bm(e,t,n);case 24:sa(t,ht,e.memoizedState.cache)}return Zn(e,t,n)}function jm(e,t,n){if(e!==null)if(e.memoizedProps!==t.pendingProps)vt=!0;else{if(!ic(e,n)&&(t.flags&128)===0)return vt=!1,f1(e,t,n);vt=(e.flags&131072)!==0}else vt=!1,He&&(t.flags&1048576)!==0&&ah(t,us,t.index);switch(t.lanes=0,t.tag){case 16:e:{e=t.pendingProps;var i=t.elementType,o=i._init;if(i=o(i._payload),t.type=i,typeof i=="function")mu(i)?(e=tl(i,e),t.tag=1,t=Em(null,t,i,e,n)):(t.tag=0,t=Iu(null,t,i,e,n));else{if(i!=null){if(o=i.$$typeof,o===K){t.tag=11,t=vm(null,t,i,e,n);break e}else if(o===I){t.tag=14,t=ym(null,t,i,e,n);break e}}throw t=$(i)||i,Error(s(306,t,""))}}return t;case 0:return Iu(e,t,t.type,t.pendingProps,n);case 1:return i=t.type,o=tl(i,t.pendingProps),Em(e,t,i,o,n);case 3:e:{if(hl(t,t.stateNode.containerInfo),e===null)throw Error(s(387));i=t.pendingProps;var c=t.memoizedState;o=c.element,Du(e,t),Bi(t,i,null,n);var v=t.memoizedState;if(i=v.cache,sa(t,ht,i),i!==c.cache&&Eu(t,[ht],n,!0),Ui(),i=v.element,c.isDehydrated)if(c={element:i,isDehydrated:!1,cache:v.cache},t.updateQueue.baseState=c,t.memoizedState=c,t.flags&256){t=wm(e,t,i,n);break e}else 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o=t.type._context,i=t.pendingProps.children,Ia(t),o=Tt(o),i=i(o),t.flags|=1,wt(e,t,i,n),t.child;case 14:return ym(e,t,t.type,t.pendingProps,n);case 15:return gm(e,t,t.type,t.pendingProps,n);case 19:return Tm(e,t,n);case 31:return i=t.pendingProps,n=t.mode,i={mode:i.mode,children:i.children},e===null?(n=As(i,n),n.ref=t.ref,t.child=n,n.return=t,t=n):(n=kn(e.child,i),n.ref=t.ref,t.child=n,n.return=t,t=n),t;case 22:return bm(e,t,n);case 24:return Ia(t),i=Tt(ht),e===null?(o=_u(),o===null&&(o=Pe,c=wu(),o.pooledCache=c,c.refCount++,c!==null&&(o.pooledCacheLanes|=n),o=c),t.memoizedState={parent:i,cache:o},ju(t),sa(t,ht,o)):((e.lanes&n)!==0&&(Du(e,t),Bi(t,null,null,n),Ui()),o=e.memoizedState,c=t.memoizedState,o.parent!==i?(o={parent:i,cache:i},t.memoizedState=o,t.lanes===0&&(t.memoizedState=t.updateQueue.baseState=o),sa(t,ht,i)):(i=c.cache,sa(t,ht,i),i!==o.cache&&Eu(t,[ht],n,!0))),wt(e,t,t.pendingProps.children,n),t.child;case 29:throw t.pendingProps}throw Error(s(156,t.tag))}function 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o=t.type;if(e!==null&&t.stateNode!=null)e.memoizedProps!==i&&Kn(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return Ie(t),null}e=Ue.current,ji(t)?lh(t):(e=Dp(o,i,n),t.stateNode=e,Kn(t))}return Ie(t),null;case 5:if(cn(t),n=t.type,e!==null&&t.stateNode!=null)e.memoizedProps!==i&&Kn(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return Ie(t),null}if(e=Ue.current,ji(t))lh(t);else{switch(o=Xs(Mt.current),e){case 1:e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case 2:e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;default:switch(n){case"svg":e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case"math":e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;case"script":e=o.createElement("div"),e.innerHTML=" + From 7ea6a524634bf36caabaf7d3deee6d122ce9f8ef Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Gerhard=20Br=C3=A4unlich?= Date: Fri, 8 May 2026 14:51:02 +0200 Subject: [PATCH 10/46] fix: make hdf5 file access more robust This replaces the filelock mechanism by the hdf5 builtin lock mechanism --- pyproject.toml | 1 - .../experiment_data_repository.py | 236 +++++++++++------- src/icon/server/utils/h5py.py | 36 --- 3 files changed, 144 insertions(+), 129 deletions(-) delete mode 100644 src/icon/server/utils/h5py.py diff --git a/pyproject.toml b/pyproject.toml index d8b6632c..cb31731f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -15,7 +15,6 @@ dependencies = [ [project.optional-dependencies] server = [ "alembic>=1.14.0", - "filelock>=3.16.1", "influxdb>=5.3.2", "sqlalchemy>=2.0.36", "tables>=3.10.1", diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index d45d93ea..1aa623c4 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -1,14 +1,17 @@ import json import logging import os +import time +from collections.abc import Iterator +from contextlib import contextmanager from dataclasses import asdict, dataclass from datetime import datetime -from typing import TYPE_CHECKING, Literal, TypedDict, cast +from pathlib import Path +from typing import TYPE_CHECKING, Any, Literal, TypedDict, cast import h5py # type: ignore import numpy as np import numpy.typing as npt -from filelock import FileLock from icon.config.config import get_config from icon.server.data_access.db_context.influxdb_v1 import DatabaseValueType @@ -18,7 +21,6 @@ ) from icon.server.data_access.repositories.job_repository import JobRepository from icon.server.data_access.repositories.job_run_repository import JobRunRepository -from icon.server.utils.h5py import get_hdf5_dtype, get_result_channels_dataset from icon.server.web_server.socketio_emit_queue import emit_queue if TYPE_CHECKING: @@ -338,11 +340,9 @@ class ExperimentDataRepository: """Repository for HDF5-based experiment data. Manages HDF5 file creation and updates (metadata, results, parameters), with - file-level locking to support concurrent writers. + hdf5-level locking to support concurrent writers. """ - LOCK_EXTENSION = ".lock" - @staticmethod def update_metadata_by_job_id( # noqa: PLR0913 *, @@ -368,15 +368,11 @@ def update_metadata_by_job_id( # noqa: PLR0913 """ filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" + h5_path = Path(get_config().data.results_dir) / filename job = JobRepository.get_job_by_id(job_id=job_id, load_experiment_source=True) - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) - with FileLock(lock_path), h5py.File(file, "a") as h5file: + with h5_open(h5_path, "a") as h5file: h5file.attrs["number_of_data_points"] = 0 h5file.attrs["number_of_shots"] = number_of_shots h5file.attrs["experiment_id"] = job.experiment_source.experiment_id @@ -414,7 +410,8 @@ def update_metadata_by_job_id( # noqa: PLR0913 if readout_metadata["readout_channel_names"]: result_dataset = get_result_channels_dataset( - h5file=h5file, result_channels=readout_metadata["readout_channel_names"] + h5file=h5file, + result_channels=readout_metadata["readout_channel_names"], ) result_dataset.attrs["Plot window metadata"] = json.dumps( readout_metadata["readout_channel_windows"] @@ -461,13 +458,9 @@ def write_experiment_data_by_job_id( """ filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" + h5_path = Path(get_config().data.results_dir) / filename - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) - with FileLock(lock_path), h5py.File(file, "a") as h5file: + with h5_open(h5_path, "a") as h5file: try: number_of_shots: int = h5file.attrs["number_of_shots"] number_of_data_points: int = h5file.attrs["number_of_data_points"] @@ -515,7 +508,7 @@ def write_experiment_data_by_job_id( if data_point["index"] >= number_of_data_points: h5file.attrs["number_of_data_points"] = data_point["index"] + 1 - logger.debug("Appended data to %s", file) + logger.debug("Appended data to %s", h5_path) emit_queue.put( { @@ -543,13 +536,9 @@ def write_parameter_update_by_job_id( """ filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) + h5_path = Path(get_config().data.results_dir) / filename parameter_updates = {} - with FileLock(lock_path), h5py.File(file, "a") as h5file: + with h5_open(h5_path, "a") as h5file: parameters_group = h5file.require_group("parameters") for param_id, value in parameter_values.items(): @@ -633,39 +622,41 @@ def get_experiment_data_by_job_id( ) filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" + h5_path = Path(get_config().data.results_dir) / filename - if not os.path.exists(file): - logger.warning("The file %s does not exist.", file) + if not os.path.exists(h5_path): + logger.warning("The file %s does not exist.", h5_path) return data - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) - with FileLock(lock_path), h5py.File(file, "r") as h5file: + with h5_open(h5_path, "r") as h5file: data.realtime_scan = bool(h5file.attrs.get("realtime_scan", False)) - total = int(h5file.attrs["number_of_data_points"]) + total = int(h5file.attrs.get("number_of_data_points", 0)) data.total_data_points = total # Estimate bytes per data point from HDF5 metadata - bytes_per_point = 0 - shot_group = cast("h5py.Group", h5file["shot_channels"]) - for ds in shot_group.values(): - bytes_per_point += ds.shape[1] * ds.dtype.itemsize - bytes_per_point += cast( - "h5py.Dataset", h5file["result_channels"] - ).dtype.itemsize - bytes_per_point += cast( - "h5py.Dataset", h5file["scan_parameters"] - ).dtype.itemsize + shot_channels_group = cast("h5py.Group | None", h5file.get("shot_channels")) + result_channel_dataset = h5file.get("result_channels") + scan_parameters = cast("h5py.Dataset | None", h5file.get("scan_parameters")) + + bytes_per_point = sum( + ds.shape[1] * ds.dtype.itemsize + for ds in (shot_channels_group or {}).values() + ) + sum( + ds.dtype.itemsize + for ds in (result_channel_dataset, scan_parameters) + if ds is not None + ) + # Add vector channel size (average across all data points) - vector_group = cast("h5py.Group", h5file["vector_channels"]) - total_vector_bytes = 0 - for channel_group in vector_group.values(): - for dataset in cast("h5py.Group", channel_group).values(): - total_vector_bytes += dataset.shape[0] * dataset.dtype.itemsize + vector_channels_group = cast( + "h5py.Group | None", h5file.get("vector_channels") + ) + total_vector_bytes = sum( + dataset.shape[0] * dataset.dtype.itemsize + for channel_group in (vector_channels_group or {}).values() + for dataset in cast("h5py.Group", channel_group).values() + ) if total > 0: bytes_per_point += total_vector_bytes // total # JSON serialisation roughly doubles the raw size @@ -675,31 +666,34 @@ def get_experiment_data_by_job_id( start_index = max(0, total - max_data_points) if start_index > 0: logger.info( - "Loading last %d of %d data points " - "(~%d bytes/point, %d MB budget)", + "Loading last %d of %d data points (~%d bytes/point, %d MB budget)", total - start_index, total, bytes_per_point, max_transfer_bytes // 1_000_000, ) - scan_parameters: npt.NDArray = h5file["scan_parameters"][start_index:] # type: ignore - data.scan_parameters = { - param: { - start_index + i: value[0].item().decode() - if isinstance(value[0], np.bytes_) - else value[0].item() - for i, value in enumerate(scan_parameters[param]) + if scan_parameters is not None: + scan_parameters: npt.NDArray = scan_parameters[start_index:] # type: ignore + data.scan_parameters = { + param: { + start_index + i: value[0].item().decode() + if isinstance(value[0], np.bytes_) + else value[0].item() + for i, value in enumerate(scan_parameters[param]) + } + for param in cast("tuple[str, ...]", scan_parameters.dtype.names) } - for param in cast("tuple[str, ...]", scan_parameters.dtype.names) - } - if "result_channels" in h5file: - result_channel_dataset = cast("h5py.Dataset", h5file["result_channels"]) - data.plot_windows["result_channels"] = json.loads( - cast("str", result_channel_dataset.attrs["Plot window metadata"]) - ) - result_channels = cast("npt.NDArray", result_channel_dataset[start_index:]) # type: ignore + if result_channel_dataset is not None: + plot_metadata = result_channel_dataset.attrs.get("Plot window metadata") + if plot_metadata: + data.plot_windows["result_channels"] = json.loads( + cast("str", plot_metadata) + ) + result_channels = cast( + "npt.NDArray[Any]", result_channel_dataset[start_index:] + ) # type: ignore data.result_channels = { channel_name: dict( enumerate( @@ -707,27 +701,34 @@ def get_experiment_data_by_job_id( start=start_index, ) ) - for channel_name in cast("tuple[str, ...]", result_channels.dtype.names) + for channel_name in cast( + "tuple[str, ...]", result_channels.dtype.names + ) } # Convert shot channels into dicts with index as key - if "shot_channels" in h5file: - shot_channels_group = cast("h5py.Group", h5file["shot_channels"]) - data.plot_windows["shot_channels"] = json.loads( - cast("str", shot_channels_group.attrs["Plot window metadata"]) - ) + if shot_channels_group is not None: + plot_metadata = shot_channels_group.attrs.get("Plot window metadata") + if plot_metadata: + data.plot_windows["shot_channels"] = json.loads( + cast("str", plot_metadata) + ) data.shot_channels = { - key: dict(enumerate(value[start_index:].tolist(), start=start_index)) # type: ignore + key: dict( + enumerate(value[start_index:].tolist(), start=start_index) + ) # type: ignore for key, value in cast( - "Sequence[tuple[str, h5py.Dataset]]", shot_channels_group.items() + "Sequence[tuple[str, h5py.Dataset]]", + shot_channels_group.items(), ) } - if "vector_channels" in h5file: - vector_channels_group = cast("h5py.Group", h5file["vector_channels"]) - data.plot_windows["vector_channels"] = json.loads( - cast("str", vector_channels_group.attrs["Plot window metadata"]) - ) + if vector_channels_group is not None: + plot_metadata = vector_channels_group.attrs.get("Plot window metadata") + if plot_metadata: + data.plot_windows["vector_channels"] = json.loads( + cast("str", plot_metadata) + ) data.vector_channels = { channel_name: { int(data_point): vector_dataset[:].tolist() @@ -736,21 +737,21 @@ def get_experiment_data_by_job_id( ) } for channel_name, vector_group in cast( - "Sequence[tuple[str, h5py.Group]]", vector_channels_group.items() + "Sequence[tuple[str, h5py.Group]]", + vector_channels_group.items(), ) } - if "sequence_json" in h5file: - sequence_json_dataset = cast( - "h5py.Dataset", h5file["sequence_json"] - ) - data.json_sequences = [ - [ - cast("np.int32", entry["index"]).item(), - entry["Sequence"].decode(), - ] - for entry in sequence_json_dataset + sequence_json_dataset = cast( + "h5py.Dataset | tuple[()]", h5file.get("sequence_json", ()) + ) + data.json_sequences = [ + [ + cast("np.int32", entry["index"]).item(), + entry["Sequence"].decode(), ] + for entry in sequence_json_dataset + ] data.parameters = extract_parameter_values(h5file) return data @@ -762,4 +763,55 @@ def last_value(d: h5py.Dataset) -> ParameterValue: ts, val = d[-1].tolist() return ParameterValue(timestamp=ts.decode(), value=val) - return {key: last_value(dataset) for key, dataset in h5file["parameters"].items()} + return { + key: last_value(dataset) + for key, dataset in h5file.get("parameters", {}).items() + } + + +def get_hdf5_dtype( + value: str | float | bool, +) -> type[np.float64 | np.bool | np.int64] | h5py.Datatype: + """Return the HDF5-compatible dtype.""" + + if isinstance(value, str): + return h5py.string_dtype() + if isinstance(value, bool): + return np.bool + if isinstance(value, int): + return np.int64 + if isinstance(value, float): + return np.float64 + + raise TypeError(f"Unsupported parameter type: {type(value)}") + + +def get_result_channels_dataset( + h5file: h5py.File, result_channels: list[str], number_of_data_points: int = 1 +) -> h5py.Dataset: + sorted_result_channels = sorted(result_channels) + result_dtype = np.dtype([(key, np.float64) for key in sorted_result_channels]) + + return h5file.require_dataset( + "result_channels", + shape=(number_of_data_points,), + maxshape=(None,), + chunks=True, + dtype=result_dtype, + compression="gzip", + compression_opts=9, + ) + + +POLL_INTERVAL = 0.05 + + +@contextmanager +def h5_open(path: Path, mode: str, **kwargs: Any) -> Iterator[h5py.File]: + while True: + try: + with h5py.File(str(path), mode, **kwargs) as h5file: + yield h5file + break + except (OSError, FileNotFoundError): + time.sleep(POLL_INTERVAL) diff --git a/src/icon/server/utils/h5py.py b/src/icon/server/utils/h5py.py deleted file mode 100644 index 30530f60..00000000 --- a/src/icon/server/utils/h5py.py +++ /dev/null @@ -1,36 +0,0 @@ -import h5py # type: ignore -import numpy as np - - -def get_hdf5_dtype( - value: str | float | bool, -) -> type[np.float64 | np.bool | np.int64] | h5py.Datatype: - """Return the HDF5-compatible dtype.""" - - if isinstance(value, str): - return h5py.string_dtype() - if isinstance(value, bool): - return np.bool - if isinstance(value, int): - return np.int64 - if isinstance(value, float): - return np.float64 - - raise TypeError(f"Unsupported parameter type: {type(value)}") - - -def get_result_channels_dataset( - h5file: h5py.File, result_channels: list[str], number_of_data_points: int = 1 -) -> h5py.Dataset: - sorted_result_channels = sorted(result_channels) - result_dtype = np.dtype([(key, np.float64) for key in sorted_result_channels]) - - return h5file.require_dataset( - "result_channels", - shape=(number_of_data_points,), - maxshape=(None,), - chunks=True, - dtype=result_dtype, - compression="gzip", - compression_opts=9, - ) From 878162c5fd41a66c66d55928669616c512a0d89b Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Sat, 2 May 2026 15:26:29 +0200 Subject: [PATCH 11/46] adding device parameter group to ExperimentMetadata to be able to connect to the client via a notebook --- src/icon/server/api/models/experiment_dict.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/icon/server/api/models/experiment_dict.py b/src/icon/server/api/models/experiment_dict.py index 41800903..6b2f765c 100644 --- a/src/icon/server/api/models/experiment_dict.py +++ b/src/icon/server/api/models/experiment_dict.py @@ -1,4 +1,4 @@ -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any from icon.server.api.models.parameter_metadata import ParameterMetadata @@ -14,6 +14,8 @@ class ExperimentMetadata: """Constructor keyword arguments used to instantiate the experiment.""" parameters: dict[str, dict[str, ParameterMetadata]] """Mapping of display groups to parameter metadata.""" + device_parameter_groups: list[Any] = field(default_factory=list) + """Device parameter groups associated with this experiment.""" ExperimentDict = dict[str, ExperimentMetadata] From 7c6f2811ee4320bde9154ce1c6f2ed027f5362c6 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Sun, 3 May 2026 18:25:34 +0200 Subject: [PATCH 12/46] changes to ExperimentJobProxy to be able to live plot the data in a notebook --- src/icon/client/api/experiments_controller.py | 188 +++++++++++++++++- src/icon/server/pre_processing/worker.py | 2 +- 2 files changed, 185 insertions(+), 5 deletions(-) diff --git a/src/icon/client/api/experiments_controller.py b/src/icon/client/api/experiments_controller.py index 15234549..ce7c0002 100644 --- a/src/icon/client/api/experiments_controller.py +++ b/src/icon/client/api/experiments_controller.py @@ -1,10 +1,17 @@ from __future__ import annotations +import asyncio import logging +import time from collections import Counter +from collections.abc import AsyncGenerator from datetime import datetime from typing import TYPE_CHECKING, Any, TypedDict +import matplotlib.pyplot as plt +import pandas as pd + +from icon.client.api.helpers.notebook import in_notebook from icon.server.api.models.experiment_dict import ExperimentMetadata if TYPE_CHECKING: @@ -163,6 +170,165 @@ def __init__(self, *, client: Client, job_id: int) -> None: self._client = client self._job_id = job_id self._getting_data = False + self._client._sio.on( + f"experiment_{self._job_id}", self._handle_live_data_point + ) + + @property + def job_id(self) -> int: + return self._job_id + + @property + def status(self) -> str: + """High-level job status: 'submitted', 'processing', or 'processed'.""" + job_dict: dict[str, Any] = self._client.trigger_method( + "scheduler.get_job_by_id", + kwargs={"job_id": self._job_id}, + ) + return str(job_dict["status"]) + + @property + def run_status(self) -> str | None: + """Run-level status: 'pending', 'processing', 'done', 'failed', or 'cancelled'. + + Returns None if no run record exists yet (job still queued). + """ + try: + run_dict: dict[str, Any] = self._client.trigger_method( + "scheduler.get_job_run_by_id", + kwargs={"job_id": self._job_id}, + ) + return str(run_dict["status"]) + except Exception: + return None + + @property + def run_log(self) -> str | None: + """Failure or cancellation message from the run, or None if no message.""" + try: + run_dict: dict[str, Any] = self._client.trigger_method( + "scheduler.get_job_run_by_id", + kwargs={"job_id": self._job_id}, + ) + return run_dict.get("log") or None + except Exception: + return None + + @property + def data(self) -> pd.DataFrame | None: + """Accumulated experiment data received so far, or None if no data yet.""" + return self._client._experiment_job_data.get(self._job_id) + + def wait(self, poll_interval: float = 2.0) -> None: + """Block until the job is done, then raise if it failed or was cancelled. + + Args: + poll_interval: Seconds between status polls. + + Raises: + RuntimeError: If the run finished with status 'failed' or 'cancelled'. + """ + while self.status != "processed": + time.sleep(poll_interval) + terminal_run_status = self.run_status + if terminal_run_status in ("failed", "cancelled"): + log = self.run_log or "(no log)" + raise RuntimeError( + f"Job {self._job_id} {terminal_run_status}:\n{log}" + ) + + def cancel(self) -> None: + """Cancel this job. No-op if already processed.""" + self._client.trigger_method( + "scheduler.cancel_job", + kwargs={"job_id": self._job_id}, + ) + + def toggle_plot(self) -> None: + """Start live plotting if idle, stop it if already running.""" + if not self._getting_data: + self._start_plot() + else: + self._stop_plot() + + def _start_plot(self) -> None: + self._getting_data = True + asyncio.run_coroutine_threadsafe( + self._subscribe_to_experiment_data_stream(), + self._client._loop, + ).result() + + def _stop_plot(self) -> None: + self._getting_data = False + asyncio.run_coroutine_threadsafe( + self._unsubscribe_from_experiment_data_stream(), + self._client._loop, + ).result() + + async def _subscribe_to_experiment_data_stream(self) -> None: + self._client._sio.on( + f"experiment_{self._job_id}", self._handle_live_data_point + ) + self._client._loop.create_task(self._run_plot()) + + async def _unsubscribe_from_experiment_data_stream(self) -> None: + self._client._sio.handlers.get("/", {}).pop( + f"experiment_{self._job_id}", None + ) + + async def _handle_live_data_point(self, data_point: dict[str, Any]) -> None: + row = {**data_point.get("scan_params", {}), **data_point.get("result_channels", {})} + df_new = pd.DataFrame([row], index=[data_point["index"]]) + existing = self._client._experiment_job_data.get(self._job_id) + if existing is None: + self._client._experiment_job_data[self._job_id] = df_new + else: + self._client._experiment_job_data[self._job_id] = pd.concat( + [existing, df_new] + ) + + async def _run_plot(self) -> None: + self._fig, self._ax = plt.subplots() + (self._line,) = self._ax.plot([], [], "r-") + self._ax.grid() + plt.ion() + plt.show() + + async for data_frame in self._get_frame(): + self._update_plot(data_frame) + if in_notebook(): + self._fig.canvas.draw_idle() + else: + self._fig.canvas.flush_events() + await asyncio.sleep(0.01) + + self._getting_data = False + await self._unsubscribe_from_experiment_data_stream() + + async def _get_frame(self) -> AsyncGenerator[pd.DataFrame | None, None]: + previous_length = 0 + while self._getting_data: + current_data = self._client._experiment_job_data.get(self._job_id) + current_length = len(current_data.index) if current_data is not None else 0 + if current_length > previous_length: + previous_length = current_length + yield current_data + else: + await asyncio.sleep(0.1) + + def _update_plot(self, data_frame: pd.DataFrame | None) -> None: + if data_frame is not None: + self._line.set_data(data_frame.iloc[:, 0], data_frame.iloc[:, 1]) + if not self._ax.get_xlabel(): + self._ax.set_xlabel(data_frame.columns[0]) + self._ax.set_ylabel(data_frame.columns[1]) + self._ax.relim() + self._ax.autoscale_view() + + def __repr__(self) -> str: + return f"" + + class ExperimentProxy: @@ -186,6 +352,14 @@ def __repr__(self) -> str: repr += f"\n - {display_group}" return repr + + def __iter__(self): + for name in self._experiment_metadata.parameters: + yield DisplayGroupProxy( + self._client, + name, + self._experiment_metadata.parameters[name], + ) def __getitem__(self, display_group_name: str) -> Any: return DisplayGroupProxy( @@ -196,10 +370,11 @@ def __getitem__(self, display_group_name: str) -> Any: def schedule( self, - scan_parameters: list[ScanParameter], + scan_parameters: list[ScanParameter] = [], priority: int = 20, repetitions: int = 1, - local_parameters_timestamp: datetime = datetime.now(), + number_of_shots: int = 50, + local_parameters_timestamp: datetime | None = None, git_commit_hash: str | None = None, auto_calibration: bool = False, ) -> ExperimentJobProxy: @@ -219,6 +394,8 @@ def schedule( Priority level of the experiment (default: 20). repetitions: Number of repetitions for the experiment to average over (default: 1). + number_of_shots: + Number of hardware shots per scan point (default: 50). local_parameters_timestamp: Timestamp of the local parameters to be used. Defaults to the current time. @@ -227,11 +404,13 @@ def schedule( take the latest commit on the main/master branch. Defaults to None. auto_calibration: Defines whether the parameter fits defined by the experiment should be - applied automatically . + applied automatically. Returns: ExperimentJobProxy: Proxy object for the scheduled experiment job. """ + if local_parameters_timestamp is None: + local_parameters_timestamp = datetime.now() job_id: int = self._client.trigger_method( "scheduler.submit_job", @@ -245,7 +424,7 @@ def schedule( "values": parameter["values"], **( {"device_name": parameter["device_name"]} - if "device_name" in parameter + if parameter.get("device_name") is not None else {} ), } @@ -254,6 +433,7 @@ def schedule( "priority": priority, "local_parameters_timestamp": local_parameters_timestamp, "repetitions": repetitions, + "number_of_shots": number_of_shots, "git_commit_hash": git_commit_hash, "auto_calibration": auto_calibration, }, diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index 05a44c18..9cfa3014 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -90,7 +90,7 @@ def get_scan_combinations(job: Job) -> list[dict[str, DatabaseValueType]]: } if not parameter_values: - return [] + return [{}] * job.repetitions # Generate combinations using itertools.product keys, values = zip(*parameter_values.items()) From 32ddd1000165f0e3e1a4d535351d0662fb865714 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Wed, 6 May 2026 10:50:46 +0200 Subject: [PATCH 13/46] fix error 'sqlalchemy.exc.MultipleResultsFound: Multiple rows were found when exactly one was required' --- .../data_access/repositories/job_run_repository.py | 14 ++++++++++++-- 1 file changed, 12 insertions(+), 2 deletions(-) diff --git a/src/icon/server/data_access/repositories/job_run_repository.py b/src/icon/server/data_access/repositories/job_run_repository.py index f9d40cf3..446c740a 100644 --- a/src/icon/server/data_access/repositories/job_run_repository.py +++ b/src/icon/server/data_access/repositories/job_run_repository.py @@ -159,7 +159,12 @@ def get_run_by_job_id(*, job_id: int, load_job: bool = False) -> JobRun: """ with sqlalchemy.orm.Session(engine) as session: - stmt = select(JobRun).where(JobRun.job_id == job_id) + stmt = ( + select(JobRun) + .where(JobRun.job_id == job_id) + .order_by(JobRun.scheduled_time.desc()) + .limit(1) + ) if load_job: stmt = stmt.options(sqlalchemy.orm.joinedload(JobRun.job)) @@ -180,7 +185,12 @@ def get_scheduled_time_by_job_id(*, job_id: int) -> datetime: """ with sqlalchemy.orm.Session(engine) as session: - stmt = select(JobRun.scheduled_time).where(JobRun.job_id == job_id) + stmt = ( + select(JobRun.scheduled_time) + .where(JobRun.job_id == job_id) + .order_by(JobRun.scheduled_time.desc()) + .limit(1) + ) scheduled_time = session.execute(stmt).scalar_one() logger.debug("Got scheduled time for job_id %s", job_id) From e7d2bf39666260b28e1c50ca80d2643caab61a64 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Mon, 27 Apr 2026 14:09:08 +0000 Subject: [PATCH 14/46] Always write plot window metadata for shot and vector channel groups --- .../experiment_data_repository.py | 23 ++++++++++--------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index d45d93ea..d39a8cf7 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -420,17 +420,15 @@ def update_metadata_by_job_id( # noqa: PLR0913 readout_metadata["readout_channel_windows"] ) - if readout_metadata["shot_channel_names"]: - shot_group = h5file.require_group("shot_channels") - shot_group.attrs["Plot window metadata"] = json.dumps( - readout_metadata["shot_channel_windows"] - ) + shot_group = h5file.require_group("shot_channels") + shot_group.attrs["Plot window metadata"] = json.dumps( + readout_metadata["shot_channel_windows"] + ) - if readout_metadata["vector_channel_names"]: - vector_group = h5file.require_group("vector_channels") - vector_group.attrs["Plot window metadata"] = json.dumps( - readout_metadata["vector_channel_windows"] - ) + vector_group = h5file.require_group("vector_channels") + vector_group.attrs["Plot window metadata"] = json.dumps( + readout_metadata["vector_channel_windows"] + ) emit_queue.put( { @@ -726,7 +724,10 @@ def get_experiment_data_by_job_id( if "vector_channels" in h5file: vector_channels_group = cast("h5py.Group", h5file["vector_channels"]) data.plot_windows["vector_channels"] = json.loads( - cast("str", vector_channels_group.attrs["Plot window metadata"]) + cast( + "str", + vector_channels_group.attrs.get("Plot window metadata", "[]"), + ) ) data.vector_channels = { channel_name: { From 067e16e5060cdeed3c2bfa9cfca51cc6ad2674d0 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Wed, 6 May 2026 12:18:42 +0200 Subject: [PATCH 15/46] adding get parameter by id to parameters controller --- src/icon/server/api/parameters_controller.py | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/src/icon/server/api/parameters_controller.py b/src/icon/server/api/parameters_controller.py index 19712339..9aeedcba 100644 --- a/src/icon/server/api/parameters_controller.py +++ b/src/icon/server/api/parameters_controller.py @@ -59,6 +59,19 @@ def __init__(self) -> None: self._all_parameter_metadata: dict[str, ParameterMetadata] = {} self._display_group_metadata: dict[str, dict[str, ParameterMetadata]] = {} + def get_parameter_by_id(self, parameter_id: str) -> DatabaseValueType: + """Return the current value of a single parameter. + + Args: + parameter_id: The unique identifier of the parameter. + + Returns: + The current value stored in the shared parameters dict. + """ + + return ParametersRepository.get_shared_parameters()[parameter_id] + + def update_parameter_by_id(self, parameter_id: str, value: Any) -> None: """Update a single parameter value in InfluxDB. From 4eac2f5a5d85166e95c90ae2d59dd5e36e1d42c0 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Fri, 8 May 2026 15:05:01 +0200 Subject: [PATCH 16/46] adding Antti's fix for experiments with different priorities --- src/icon/server/hardware_processing/task.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/icon/server/hardware_processing/task.py b/src/icon/server/hardware_processing/task.py index 85a9c985..00428174 100644 --- a/src/icon/server/hardware_processing/task.py +++ b/src/icon/server/hardware_processing/task.py @@ -34,4 +34,4 @@ class HardwareProcessingTask(pydantic.BaseModel): outdated_tasks: Any def __lt__(self, other: HardwareProcessingTask) -> bool: - return self.priority < other.priority or self.created < other.created + return (self.priority, self.created) < (other.priority, other.created) \ No newline at end of file From 06e1ec3c31921a7c3b488e0d126b89a36a7b3fee Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Fri, 8 May 2026 15:52:32 +0200 Subject: [PATCH 17/46] fixing hdf5 group param access error --- .../repositories/experiment_data_repository.py | 18 ++++++++++++++---- 1 file changed, 14 insertions(+), 4 deletions(-) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index 690712b9..9d65f6c3 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -761,10 +761,20 @@ def last_value(d: h5py.Dataset) -> ParameterValue: ts, val = d[-1].tolist() return ParameterValue(timestamp=ts.decode(), value=val) - return { - key: last_value(dataset) - for key, dataset in h5file.get("parameters", {}).items() - } + parameters_group = h5file.get("parameters") + if parameters_group is None: + return {} + + # param_ids may contain '/' which h5py treats as path separators, creating + # nested groups instead of flat datasets — use visititems to collect all leaves + result: dict[str, ParameterValue] = {} + + def visitor(name: str, obj: h5py.HLObject) -> None: + if isinstance(obj, h5py.Dataset): + result[name] = last_value(obj) + + parameters_group.visititems(visitor) + return result def get_hdf5_dtype( From f9c5c20b920f3f02bfda26aa989772b4a80117ed Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 11:45:10 +0200 Subject: [PATCH 18/46] decoding data if recieved data is in bytes --- .../data_access/repositories/experiment_data_repository.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index 9d65f6c3..8c45fcaa 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -759,6 +759,8 @@ def extract_parameter_values( ) -> dict[str, ParameterValue]: def last_value(d: h5py.Dataset) -> ParameterValue: ts, val = d[-1].tolist() + if isinstance(val, bytes): + val = val.decode() return ParameterValue(timestamp=ts.decode(), value=val) parameters_group = h5file.get("parameters") From 923c6fc8acc35f7788b36de4697400544b228071 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 13:09:37 +0200 Subject: [PATCH 19/46] adding a parameter controller class for the client to have control over server parameters --- src/icon/client/api/parameters_controller.py | 42 ++++++++++++++++++++ src/icon/client/client.py | 2 + 2 files changed, 44 insertions(+) create mode 100644 src/icon/client/api/parameters_controller.py diff --git a/src/icon/client/api/parameters_controller.py b/src/icon/client/api/parameters_controller.py new file mode 100644 index 00000000..59c9add1 --- /dev/null +++ b/src/icon/client/api/parameters_controller.py @@ -0,0 +1,42 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING + +from icon.client.api.experiments_controller import DisplayGroupProxy + +if TYPE_CHECKING: + from icon.client.client import Client + + +class ParametersController: + """Client-side controller for global parameters. + + Wraps the server's ``parameters`` pydase service, providing access to all + display groups and their parameters without going through a specific experiment. + + Usage:: + + client = Client(url="ws://localhost:8001") + client.parameters["Global Parameters"]["Tickle time"].value = 2.5 + """ + + def __init__(self, client: Client) -> None: + self._client = client + self._display_groups: dict[str, dict] = client.trigger_method( + "parameters.get_display_groups" + ) + + def __getitem__(self, display_group_name: str) -> DisplayGroupProxy: + return DisplayGroupProxy( + self._client, + display_group_name, + self._display_groups[display_group_name], + ) + + def __repr__(self) -> str: + lines = [""] + for group_name, params in self._display_groups.items(): + lines.append(f" [{group_name}]") + for meta in params.values(): + lines.append(f" - {meta['display_name']}") + return "\n".join(lines) diff --git a/src/icon/client/client.py b/src/icon/client/client.py index 86830399..bd4580f4 100644 --- a/src/icon/client/client.py +++ b/src/icon/client/client.py @@ -8,6 +8,7 @@ import socketio # type: ignore[import-untyped] from icon.client.api.experiments_controller import ExperimentsController +from icon.client.api.parameters_controller import ParametersController from icon.serialization.deserializer import loads from icon.serialization.serializer import dump @@ -115,6 +116,7 @@ def __init__( self._experiment_job_data: dict[int, pd.DataFrame] = {} # self.scheduler = SchedulerController(self) self.experiments = ExperimentsController(self) + self.parameters = ParametersController(self) async def _handle_experiment_data(self, data: ExperimentData) -> None: logger.debug("Updating experiment data...") From 98a2e7c629fa8fcccf6f94e5a721dc98b9ac913e Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 14:04:37 +0200 Subject: [PATCH 20/46] map the display name of the parameters in icon client to shorter names --- src/icon/client/api/experiments_controller.py | 43 +++++++++++++++++++ src/icon/client/api/parameters_controller.py | 21 ++++++--- 2 files changed, 58 insertions(+), 6 deletions(-) diff --git a/src/icon/client/api/experiments_controller.py b/src/icon/client/api/experiments_controller.py index ce7c0002..db5056f2 100644 --- a/src/icon/client/api/experiments_controller.py +++ b/src/icon/client/api/experiments_controller.py @@ -77,6 +77,49 @@ def get_experiment_identifier_dict(experiments: list[str]) -> dict[str, str]: return identifier_dict +def get_display_group_identifier_dict(display_groups: list[str]) -> dict[str, str]: + """Map short display-name keys to full display-group keys. + + ``'experiment_library.globals.global_parameters (Doppler Cooling)'`` + becomes ``'Global Parameters (Doppler Cooling)'``. When the short class + name collides across namespaces, the parent module is prepended to keep + keys unique. + + Args: + display_groups: Full display-group key strings as returned by the server. + + Returns: + Dict mapping short identifiers to full keys. + """ + + def _parse(key: str) -> tuple[str, str]: + namespace, _, instance = key.rpartition(" (") + return namespace, instance.rstrip(")") + + def _short(namespace: str, instance: str) -> str: + class_part = namespace.split(".")[-1].replace("_", " ").title() + return f"{class_part} ({instance})" + + def _longer(namespace: str, instance: str) -> str: + parts = namespace.split(".") + if len(parts) >= 2: + prefix = parts[-2].replace("_", " ").title() + class_part = parts[-1].replace("_", " ").title() + return f"{prefix} {class_part} ({instance})" + return f"{namespace} ({instance})" + + short_names = [_short(*_parse(k)) for k in display_groups] + counts = Counter(short_names) + + result: dict[str, str] = {} + for key in display_groups: + namespace, instance = _parse(key) + short = _short(namespace, instance) + result[short if counts[short] == 1 else _longer(namespace, instance)] = key + + return result + + def get_parameter_identifier_mapping( display_group_metadata: dict[str, ParameterMetadata], ) -> dict[str, str]: diff --git a/src/icon/client/api/parameters_controller.py b/src/icon/client/api/parameters_controller.py index 59c9add1..d90b9113 100644 --- a/src/icon/client/api/parameters_controller.py +++ b/src/icon/client/api/parameters_controller.py @@ -2,7 +2,10 @@ from typing import TYPE_CHECKING -from icon.client.api.experiments_controller import DisplayGroupProxy +from icon.client.api.experiments_controller import ( + DisplayGroupProxy, + get_display_group_identifier_dict, +) if TYPE_CHECKING: from icon.client.client import Client @@ -25,18 +28,24 @@ def __init__(self, client: Client) -> None: self._display_groups: dict[str, dict] = client.trigger_method( "parameters.get_display_groups" ) + self._display_group_id_mapping = get_display_group_identifier_dict( + list(self._display_groups.keys()) + ) def __getitem__(self, display_group_name: str) -> DisplayGroupProxy: + full_key = self._display_group_id_mapping.get( + display_group_name, display_group_name + ) return DisplayGroupProxy( self._client, - display_group_name, - self._display_groups[display_group_name], + full_key, + self._display_groups[full_key], ) def __repr__(self) -> str: lines = [""] - for group_name, params in self._display_groups.items(): - lines.append(f" [{group_name}]") - for meta in params.values(): + for short_name, full_key in self._display_group_id_mapping.items(): + lines.append(f" [{short_name}]") + for meta in self._display_groups[full_key].values(): lines.append(f" - {meta['display_name']}") return "\n".join(lines) From bb02fc167ffc63530be49282f54bf36ed0f13dcf Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 22:49:00 +0200 Subject: [PATCH 21/46] tentative stalling fix, from _update_metadata_and_display_group being called over and over again --- src/icon/server/api/api_service.py | 6 ++- src/icon/server/api/parameters_controller.py | 39 ++++++++++++++++++-- src/icon/server/data_access/venv_exec.py | 9 ++++- 3 files changed, 48 insertions(+), 6 deletions(-) diff --git a/src/icon/server/api/api_service.py b/src/icon/server/api/api_service.py index 7cddc4ab..307ef2a0 100644 --- a/src/icon/server/api/api_service.py +++ b/src/icon/server/api/api_service.py @@ -87,8 +87,10 @@ def __init__( @task(autostart=True) async def _update_experiment_and_parameter_metadata_task(self) -> None: while True: - await self._update_experiment_and_parameter_metadata() - + try: + await self._update_experiment_and_parameter_metadata() + except Exception as e: + logger.exception(f"Failed to update experiment and parameter metadata: exception {e}") await asyncio.sleep(get_config().experiment_library.update_interval) async def _update_experiment_and_parameter_metadata(self) -> None: diff --git a/src/icon/server/api/parameters_controller.py b/src/icon/server/api/parameters_controller.py index 9aeedcba..8539e8d3 100644 --- a/src/icon/server/api/parameters_controller.py +++ b/src/icon/server/api/parameters_controller.py @@ -1,4 +1,7 @@ +import dataclasses +import json import logging +import math from typing import Any import pydase @@ -41,10 +44,39 @@ def get_added_removed_and_updated_keys( removed_keys = keys1 - keys2 intersect_keys = keys1 & keys2 - updated_keys = {key for key in intersect_keys if new_dict[key] != cached_dict[key]} - + updated_keys = { + key + for key in intersect_keys + if not _values_equal(new_dict[key], cached_dict[key]) + } + return list(added_keys), list(removed_keys), list(updated_keys) +def _values_equal(a: Any, b: Any) -> bool: + """NaN-safe deep equality for parameter/experiment metadata values. + + Plain ``==`` returns False for NaN even when both sides are NaN, causing + spurious "updated" detections every reload cycle. Dataclasses are converted + with ``dataclasses.asdict`` before comparison so their nested float fields + are also covered. + """ + if dataclasses.is_dataclass(a) and not isinstance(a, type): + a = dataclasses.asdict(a) + if dataclasses.is_dataclass(b) and not isinstance(b, type): + b = dataclasses.asdict(b) + try: + return json.dumps(a, default=_nan_safe) == json.dumps(b, default=_nan_safe) + except (TypeError, ValueError): + return a == b + + +def _nan_safe(obj: Any) -> Any: + if isinstance(obj, float) and math.isnan(obj): + return None + raise TypeError(type(obj)) + + + class ParametersController(pydase.DataService): """Controller for parameter metadata and shared parameter values. @@ -117,7 +149,8 @@ async def _update_parameter_metadata_and_display_groups( added_params, removed_params, updated_params = ( get_added_removed_and_updated_keys( - self._all_parameter_metadata, parameter_metadata["all parameters"] + new_dict=parameter_metadata["all parameters"], + cached_dict=self._all_parameter_metadata, ) ) self._all_parameter_metadata = parameter_metadata["all parameters"] diff --git a/src/icon/server/data_access/venv_exec.py b/src/icon/server/data_access/venv_exec.py index 63641aa1..278abad7 100644 --- a/src/icon/server/data_access/venv_exec.py +++ b/src/icon/server/data_access/venv_exec.py @@ -53,7 +53,14 @@ async def run( env={"PYTHONPATH": python_path} if python_path else {}, ) - stdout, stderr = await proc.communicate(payload) + try: + stdout, stderr = await asyncio.wait_for( + proc.communicate(payload), timeout=60.0 + ) + except asyncio.TimeoutError: + proc.kill() + await proc.communicate() + raise RuntimeError("Venv subprocess timed out after 60 s") if logger is not None: logger.warning(stdout.decode()) From 9a0694adb2b772f6e40737072b47e82757dce31c Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 22:49:37 +0200 Subject: [PATCH 22/46] tentative stalling fix, from updating experiment metadata being called over and over again --- src/icon/server/api/experiments_controller.py | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/src/icon/server/api/experiments_controller.py b/src/icon/server/api/experiments_controller.py index d3e92cb7..8b14c14d 100644 --- a/src/icon/server/api/experiments_controller.py +++ b/src/icon/server/api/experiments_controller.py @@ -51,14 +51,9 @@ def _update_experiment_metadata(self, new_experiments: ExperimentDict) -> None: logger.debug("Updating experiment metadata...") added_exps, removes_exps, updated_exps = get_added_removed_and_updated_keys( - self._experiments, new_experiments + new_dict=new_experiments, cached_dict=self._experiments ) self._experiments = new_experiments if added_exps or removes_exps or updated_exps: - emit_queue.put( - { - "event": "experiments.update", - "data": new_experiments, - } - ) + emit_queue.put({"event": "experiments.update", "data": None}) From 0704a00c2108bb5dc2ac31759adc63382769f145 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 22:50:08 +0200 Subject: [PATCH 23/46] tentative stalling fix, trying to make loop more robust to cancelled experiment --- src/icon/server/pre_processing/worker.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index 9cfa3014..b8f06e7d 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -414,6 +414,8 @@ def _handle_regular_scan( try: index, data_point = self._data_points_to_process.get(block=False) except queue.Empty: + if job_run_cancelled_or_failed(job_id=pre_processing_task.job.id): + break time.sleep(0.001) continue From 8616e2574b5f06c2f2a680c8b25771832c735712 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 23:11:25 +0200 Subject: [PATCH 24/46] tentative stalling fix, trying to make loop more robust to cancelled experiment --- src/icon/server/hardware_processing/worker.py | 1 + src/icon/server/pre_processing/worker.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/src/icon/server/hardware_processing/worker.py b/src/icon/server/hardware_processing/worker.py index 7509b36d..f4f4632a 100644 --- a/src/icon/server/hardware_processing/worker.py +++ b/src/icon/server/hardware_processing/worker.py @@ -159,6 +159,7 @@ def run(self) -> None: if job_run_cancelled_or_failed( job_id=task.pre_processing_task.job.id, ): + task.processed_data_points.put(task) continue parameter_update_timestamp = ( diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index b8f06e7d..5f0bdd89 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -414,9 +414,9 @@ def _handle_regular_scan( try: index, data_point = self._data_points_to_process.get(block=False) except queue.Empty: + time.sleep(1.0) if job_run_cancelled_or_failed(job_id=pre_processing_task.job.id): break - time.sleep(0.001) continue if job_run_cancelled_or_failed( From 8e179199251860ca9958fd076e0a7b55b2c7ab16 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 12 May 2026 23:43:32 +0200 Subject: [PATCH 25/46] adding exception handling for method run of class Scheduler --- src/icon/server/scheduler/scheduler.py | 68 +++++++++++++++++--------- 1 file changed, 45 insertions(+), 23 deletions(-) diff --git a/src/icon/server/scheduler/scheduler.py b/src/icon/server/scheduler/scheduler.py index e1b717ce..6b8b0b1a 100644 --- a/src/icon/server/scheduler/scheduler.py +++ b/src/icon/server/scheduler/scheduler.py @@ -1,3 +1,4 @@ +import logging import multiprocessing import queue import time @@ -15,6 +16,8 @@ ) from icon.server.pre_processing.task import PreProcessingTask +logger = logging.getLogger(__name__) + def initialise_job_tables() -> None: # update job_runs table @@ -51,29 +54,48 @@ def __init__( def run(self) -> None: initialise_job_tables() while not should_exit(): - jobs = JobRepository.get_jobs_by_status_and_timeframe( - status=JobStatus.SUBMITTED - ) - for job_ in jobs: - job = JobRepository.update_job_status( - job=job_, status=JobStatus.PROCESSING + try: + jobs = JobRepository.get_jobs_by_status_and_timeframe( + status=JobStatus.SUBMITTED ) - run = JobRun(job_id=job.id, scheduled_time=datetime.now(tz=timezone)) - run = JobRunRepository.insert_run(run=run) + for job_ in jobs: + try: + job = JobRepository.update_job_status( + job=job_, status=JobStatus.PROCESSING + ) + run = JobRun( + job_id=job.id, scheduled_time=datetime.now(tz=timezone) + ) + run = JobRunRepository.insert_run(run=run) - self._pre_processing_queue.put( - PreProcessingTask( - job=job, - job_run=run, - git_commit_hash=job.git_commit_hash, - scan_parameters=job.scan_parameters, - local_parameters_timestamp=job.local_parameters_timestamp.astimezone( - tz=timezone - ).isoformat(), - priority=job.priority, - auto_calibration=job.auto_calibration, - debug_mode=job.debug_mode, - repetitions=job.repetitions, - ) - ) + self._pre_processing_queue.put( + PreProcessingTask( + job=job, + job_run=run, + git_commit_hash=job.git_commit_hash, + scan_parameters=job.scan_parameters, + local_parameters_timestamp=job.local_parameters_timestamp.astimezone( + tz=timezone + ).isoformat(), + priority=job.priority, + auto_calibration=job.auto_calibration, + debug_mode=job.debug_mode, + repetitions=job.repetitions, + ) + ) + except Exception: + logger.exception( + "Failed to dispatch job %s, reverting to SUBMITTED", + job_.id, + ) + try: + JobRepository.update_job_status( + job=job_, status=JobStatus.SUBMITTED + ) + except Exception: + logger.exception( + "Failed to revert job %s back to SUBMITTED", job_.id + ) + except Exception: + logger.exception("Unexpected error in scheduler loop") time.sleep(0.1) From d9245631db50ae5cbab51f77844ca299771ec4cc Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Thu, 14 May 2026 21:31:00 +0200 Subject: [PATCH 26/46] fix ordering of the display groups --- src/icon/server/api/api_service.py | 41 +++++++++++++++++++++++- src/icon/server/pre_processing/worker.py | 1 + 2 files changed, 41 insertions(+), 1 deletion(-) diff --git a/src/icon/server/api/api_service.py b/src/icon/server/api/api_service.py index 307ef2a0..2b0a08bb 100644 --- a/src/icon/server/api/api_service.py +++ b/src/icon/server/api/api_service.py @@ -2,7 +2,7 @@ import asyncio import logging -from typing import TYPE_CHECKING +from typing import TYPE_CHECKING, Any import pydase import requests.exceptions @@ -33,6 +33,41 @@ logger = logging.getLogger(__name__) +def _build_canonical_group_order(display_groups: dict[str, Any]) -> dict[str, int]: + """Map display group names to their canonical position index. + + Keys in display_groups have the form "namespace (DisplayGroupName)". + Assigns indices in first-occurrence order, matching namespace_registry + insertion order (i.e., code definition order). + """ + order: dict[str, int] = {} + for key in display_groups: + _, _, rest = key.rpartition(" (") + name = rest.rstrip(")") + if name not in order: + order[name] = len(order) + return order + + +def _reorder_experiment_display_groups( + experiment_metadata: Any, canonical_order: dict[str, int] +) -> None: + """Sort each experiment's parameters dict by canonical_order in-place. + + Global display groups appear first in namespace_registry (code) order. + Experiment-local groups not present in canonical_order sort to the end, + preserving their relative registration order among themselves. + """ + n = len(canonical_order) + for exp_meta in experiment_metadata.values(): + exp_meta["parameters"] = dict( + sorted( + exp_meta["parameters"].items(), + key=lambda kv: canonical_order.get(kv[0], n), + ) + ) + + class APIService(pydase.DataService): """Aggregates ICON's API controllers and manages background tasks. @@ -102,6 +137,10 @@ async def _update_experiment_and_parameter_metadata(self) -> None: experiment_metadata, parameter_metadata, ) = await self._experiment_library_client.load_metadata() + canonical_order = _build_canonical_group_order( + parameter_metadata["display groups"] + ) + _reorder_experiment_display_groups(experiment_metadata, canonical_order) self.experiments._update_experiment_metadata( new_experiments=experiment_metadata ) diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index 5f0bdd89..75e7d026 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -473,6 +473,7 @@ def _regenerate_outdated_jobs( parameter_dict={**self._parameter_dict, **task.scanned_params}, namespace=namespace, ) + task.created = datetime.now(timezone) self._submit_task_to_hw_worker(task=task) def _handle_realtime_scan( From 353794f212dfd7da7133406119791de5b0d2df9f Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Thu, 14 May 2026 23:37:01 +0200 Subject: [PATCH 27/46] fix import errors from merge --- .../data_access/repositories/experiment_data_repository.py | 1 - src/icon/server/pre_processing/worker.py | 3 --- 2 files changed, 4 deletions(-) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index 32a31d74..c3aecb09 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -22,7 +22,6 @@ from icon.server.data_access.repositories.job_repository import JobRepository from icon.server.data_access.repositories.job_run_repository import JobRunRepository from icon.server.fitting.fit_runner import FitResult -from icon.server.utils.h5py import get_hdf5_dtype, get_result_channels_dataset from icon.server.web_server.socketio_emit_queue import emit_queue if TYPE_CHECKING: diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index 34597c62..e88f5e81 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -33,9 +33,6 @@ from icon.server.data_access.repositories.parameters_repository import ( ParametersRepository, ) -from icon.server.data_access.repositories.pycrystal_library_repository import ( - PycrystalLibraryRepository, -) from icon.server.fitting.auto_fit import try_auto_fit from icon.server.hardware_processing.task import HardwareProcessingTask From fe32889cd05c2cfdb60d10be2b4ae5ce7657480a Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Mon, 18 May 2026 14:24:53 +0200 Subject: [PATCH 28/46] chore: update uv.lock to require Python >=3.12 Co-Authored-By: Claude Sonnet 4.6 --- uv.lock | 1346 ++++++++++--------------------------------------------- 1 file changed, 249 insertions(+), 1097 deletions(-) diff --git a/uv.lock b/uv.lock index 36ff4142..3bffa061 100644 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Berterottiere Date: Mon, 18 May 2026 14:33:51 +0200 Subject: [PATCH 29/46] feat(server): add TTL channel control via pydase API Adds server-side control of the 32 Zedboard FPGA TTL output channels. Each channel can be set to OFF (forced LOW), ON (forced HIGH), or CONTROL (pulse-sequence driven) using the ttlMasks / setTTLMasks RPC calls. Mask state is persisted to SQLite so it survives hardware power cycles. Changes: - TTLController (pydase.DataService) registered on APIService as .ttl - TTLRepository + ttl_mask_states SQLite table (alembic migration) - HardwareController.get_ttl_masks() / set_ttl_masks() wrappers - HardwareConfig.n_ttl_channels config field (default 32) - 19 unit tests covering mask encode/decode and controller logic - docs/ttl_server_implementation.md design reference Co-Authored-By: Claude Sonnet 4.6 --- docs/ttl_control.md | 119 +++++++++++++++ docs/ttl_server_implementation.md | 128 ++++++++++++++++ src/icon/config/v1.py | 1 + src/icon/server/api/api_service.py | 3 + src/icon/server/api/ttl_controller.py | 143 ++++++++++++++++++ .../a1b2c3d4e5f6_add_ttl_mask_state_table.py | 33 ++++ .../data_access/models/sqlite/__init__.py | 2 + .../models/sqlite/ttl_mask_state.py | 42 +++++ .../repositories/ttl_repository.py | 41 +++++ .../hardware_controller.py | 26 ++++ tests/server/__init__.py | 0 tests/server/api/test_ttl_controller.py | 125 +++++++++++++++ 12 files changed, 663 insertions(+) create mode 100644 docs/ttl_control.md create mode 100644 docs/ttl_server_implementation.md create mode 100644 src/icon/server/api/ttl_controller.py create mode 100644 src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py create mode 100644 src/icon/server/data_access/models/sqlite/ttl_mask_state.py create mode 100644 src/icon/server/data_access/repositories/ttl_repository.py create mode 100644 tests/server/__init__.py create mode 100644 tests/server/api/test_ttl_controller.py diff --git a/docs/ttl_control.md b/docs/ttl_control.md new file mode 100644 index 00000000..a4c0255b --- /dev/null +++ b/docs/ttl_control.md @@ -0,0 +1,119 @@ +# TTL Control in ionpulse_sdk_core + +## Overview + +Each of the 32 (on the RFSoC it think it's 16?) TTL output channels can be in one of three states: + +| State | Name | Behavior | +|---|---|---| +| 0 | OFF | Ionizer forces the line **LOW** (static override) | +| 1 | ON | Ionizer forces the line **HIGH** (static override) | +| 2 | CONTROL | sdk_core pulse sequence controls the line dynamically | + +State 2 is what Ionizer shows in **blue** — it means the FPGA pulse sequence owns that channel. States 0 and 1 are static overrides that the pulse sequence cannot override. + +--- + +## Hardware Mechanism: The Two-Mask System + +The FPGA exposes two 32-bit registers via RPC: + +``` +setTTLMasks(uint32 high_mask, uint32 low_mask) +ttlMasks() → (uint32 high_mask, uint32 low_mask) +``` + +For each bit position `n` (TTL channel n): + +| `high_mask[n]` | `low_mask[n]` | Result | +|---|---|---| +| 0 | 1 | Line forced **LOW** (state 0) | +| 1 | 0 | Line forced **HIGH** (state 1) | +| 0 | 0 | Line under **pulse sequence control** (state 2) | +| 1 | 1 | Undefined — do not use | + +Setting a channel to state 2 means clearing **both** its bits in both masks. The FPGA pulse sequence then drives that line as programmed in the waveform. + +### Per-channel helper logic + +To set channel `n` to a given state, read the current masks, modify the two bits, then write back: + +```python +def set_ttl_state(n, state, high_mask, low_mask): + bit = 1 << n + if state == 0: # forced LOW + high_mask &= ~bit + low_mask |= bit + elif state == 1: # forced HIGH + high_mask |= bit + low_mask &= ~bit + elif state == 2: # pulse-sequence control + high_mask &= ~bit + low_mask &= ~bit + return high_mask, low_mask +``` + +Reading the current state back: + +```python +def get_ttl_state(n, high_mask, low_mask): + bit = 1 << n + if low_mask & bit: return 0 # forced LOW + if high_mask & bit: return 1 # forced HIGH + return 2 # pulse-sequence control +``` + +--- + +## RPC API Reference + +These are msgpack-RPC calls on the sdk_core server: + +``` +# Read current override masks +(high_mask, low_mask) = rpc.call("ttlMasks") + +# Write override masks (affects all 32 channels at once) +rpc.call("setTTLMasks", high_mask, low_mask) +``` + +Both masks must be sent together. Always do a read-modify-write when changing individual channels to avoid clobbering others. + +--- + +## Pulse-Level Control (sdk_core side) + +When a TTL channel is in state 2 (CONTROL), the pulse sequence drives it. Each pulse step in the waveform carries two TTL fields: + +- **`ttl_pattern`** (uint32): The desired output state — which channels should be HIGH during this step. +- **`ttl_line_mask`** (uint32): Which channels are actually updated by this step. Channels not in the mask keep their previous value. + +Only channels in state 2 (both override bits clear) respond to these pulse-sequence commands. Channels held in state 0 or 1 are statically overridden at the hardware level and will not follow the pulse sequence regardless of `ttl_pattern`. + +--- + +## What to Implement in Your Server + +1. **On startup / connect**: call `ttlMasks()` to read the current hardware state. +2. **Per-channel state control**: implement read-modify-write using `setTTLMasks` to set individual channels to state 0, 1, or 2. +3. **Expose three operations per channel**: + - Force LOW (state 0) + - Force HIGH (state 1) + - Release to pulse sequence (state 2 — the "blue" / CONTROL mode) +4. **Pulse sequence**: when building waveforms, pass `ttl_pattern` and `ttl_line_mask` per step. Only channels in state 2 will respond. +5. **Persistence**: save the mask state so it can be restored on reconnect (the hardware forgets on power cycle). + +--- + +## Ionizer UI Mapping (for reference) + +| Ionizer element | Meaning | +|---|---| +| StateButton **red** | Channel in state 0 (forced LOW) | +| StateButton **green** | Channel in state 1 (forced HIGH) | +| ControlButton **blue** (PI / "397 0th") | Channel in state 2 (pulse-sequence control) | +| ControlButton **black** | Ionizer is in manual override mode (state 0 or 1) | + +The ControlButton is what switches between static override and pulse-sequence control. The StateButton only has effect when the ControlButton is not active. + +Key source files: `FPGAConnection.cpp:96–120` (mask logic), `ExperimentsSheet.cpp:747–786` (UI handlers), `api.h:141–147` (RPC method names), `bp_dds.h:112–165` (pulse-level TTL fields). diff --git a/docs/ttl_server_implementation.md b/docs/ttl_server_implementation.md new file mode 100644 index 00000000..930ac6af --- /dev/null +++ b/docs/ttl_server_implementation.md @@ -0,0 +1,128 @@ +# TTL Channel Control — Server Implementation + +## Background + +Each Zedboard FPGA TTL output channel can be in one of three states: + +| State | Name | Behavior | +|-------|------|----------| +| 0 | OFF | Channel forced LOW (static override) | +| 1 | ON | Channel forced HIGH (static override) | +| 2 | CONTROL | Pulse sequence owns the channel | + +The hardware exposes two RPC calls: `ttlMasks()` (read) and `setTTLMasks(high_mask, low_mask)` (write). Ionizer's C++ client implemented per-channel control via `FPGAConnection::setTTLlogicState()` / `getTTLlogicState()`. This document describes how ICON implements equivalent server-side control. + +--- + +## Why not use `tiqi_zedboard.TTLs`? + +The `TTLs` class (v1.3.0, available via the `zedboard` optional extra) exposes only binary ON/OFF control. Its `_set_channel_zedboard()` always writes a 1 into either `high_mask` or `low_mask`, making it impossible to express state 2 (CONTROL — both bits clear). The underlying RPC supports all three states, so `TTLController` works directly with the raw masks via `HardwareController.get_ttl_masks()` / `set_ttl_masks()`. No changes to tiqi-zedboard are required. + +--- + +## Architecture + +``` +APIService +└── ttl: TTLController (pydase.DataService) + ├── HardwareController → Zedboard RPC (ttlMasks / setTTLMasks) + └── TTLRepository → SQLite ttl_mask_states table (single row) +``` + +`TTLController` is added to `APIService` alongside the existing `StatusController`, `DevicesController`, etc. It owns a dedicated `HardwareController` connection (same pattern as `StatusController`, i.e. `connect=False` initially) and persists masks through `TTLRepository` backed by a single-row SQLite table. + +--- + +## Mask Encoding + +For channel `n`: + +| `high_mask[n]` | `low_mask[n]` | State | +|---|---|---| +| 0 | 1 | 0 — forced LOW | +| 1 | 0 | 1 — forced HIGH | +| 0 | 0 | 2 — CONTROL (pulse sequence) | + +Helper functions `_decode_state()` and `_encode_state()` in `ttl_controller.py` implement this logic. + +--- + +## Files Changed + +| File | Change | +|------|--------| +| `src/icon/config/v1.py` | Added `n_ttl_channels: int = 32` to `HardwareConfig` | +| `src/icon/server/hardware_processing/hardware_controller.py` | Added `get_ttl_masks()` and `set_ttl_masks()` | +| `src/icon/server/data_access/models/sqlite/ttl_mask_state.py` | New — SQLAlchemy model | +| `src/icon/server/data_access/models/sqlite/__init__.py` | Added `TTLMaskState` to `__all__` | +| `src/icon/server/data_access/repositories/ttl_repository.py` | New — upsert/read masks | +| `src/icon/server/api/ttl_controller.py` | New — pydase DataService | +| `src/icon/server/api/api_service.py` | Registered `self.ttl = TTLController()` | +| `src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py` | New — migration | +| `tests/server/__init__.py` | New — missing package marker | +| `tests/server/api/test_ttl_controller.py` | New — unit tests | + +--- + +## API + +### `ttl.get_states() -> list[int]` +Returns a list of 32 integers (0/1/2), one per channel, read live from hardware. +Falls back to the last persisted masks if the hardware is unreachable. + +### `ttl.set_state(channel: int, state: int) -> None` +Sets one channel to state 0, 1, or 2. Writes to hardware, then persists the +resulting masks to SQLite. Emits a `ttl.update` Socket.IO event. + +### `ttl.get_masks() -> dict[str, int]` +Returns `{"high_mask": ..., "low_mask": ...}` from hardware (or DB fallback). + +### `ttl.restore_masks() -> None` +Re-applies the last persisted masks to the hardware — useful after a power cycle. + +--- + +## Persistence + +The `ttl_mask_states` table holds at most one row (`id=1`): + +```sql +CREATE TABLE ttl_mask_states ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + high_mask INTEGER NOT NULL, + low_mask INTEGER NOT NULL, + updated_at TIMESTAMP WITH TIME ZONE NOT NULL +); +``` + +Migration: `a1b2c3d4e5f6_add_ttl_mask_state_table.py` (down_revision: `fc9af856df20`). + +--- + +## Configuration + +`hardware.n_ttl_channels` in the YAML config (default 32). Set to 16 for RFSoC hardware. + +```yaml +hardware: + host: zedboard.lab + port: 6007 + n_ttl_channels: 32 +``` + +--- + +## Manual Verification (with hardware) + +```python +# Start ICON server, then from a pydase client: +client.proxy.ttl.get_states() # read all 32 channel states +client.proxy.ttl.set_state(0, 1) # force channel 0 HIGH +client.proxy.ttl.set_state(0, 2) # release channel 0 to pulse sequence +client.proxy.ttl.get_masks() # inspect raw masks +client.proxy.ttl.restore_masks() # re-apply persisted masks after power cycle +``` + +After `set_state()`, confirm the hardware line changes state. After restarting the +server, the masks should be readable from the DB via `get_masks()` (hardware path) +or restored via `restore_masks()`. diff --git a/src/icon/config/v1.py b/src/icon/config/v1.py index ca47ce27..4aff09ab 100644 --- a/src/icon/config/v1.py +++ b/src/icon/config/v1.py @@ -58,6 +58,7 @@ class ServerConfig(BaseModel): class HardwareConfig(BaseModel): host: str = "localhost" port: int = 6007 + n_ttl_channels: int = 32 class ServiceConfigV1(BaseConfig): # type: ignore[misc] diff --git a/src/icon/server/api/api_service.py b/src/icon/server/api/api_service.py index 2b0a08bb..6f609bbc 100644 --- a/src/icon/server/api/api_service.py +++ b/src/icon/server/api/api_service.py @@ -18,6 +18,7 @@ from icon.server.api.scans_controller import ScansController from icon.server.api.scheduler_controller import SchedulerController from icon.server.api.status_controller import StatusController +from icon.server.api.ttl_controller import TTLController from icon.server.data_access.repositories.parameters_repository import ( ParametersRepository, ) @@ -117,6 +118,8 @@ def __init__( processes.""" self.status = StatusController() """Controller for system status monitoring.""" + self.ttl = TTLController() + """Controller for hardware TTL channel state.""" self._experiment_library_client = experiment_library_client @task(autostart=True) diff --git a/src/icon/server/api/ttl_controller.py b/src/icon/server/api/ttl_controller.py new file mode 100644 index 00000000..bf3f6c96 --- /dev/null +++ b/src/icon/server/api/ttl_controller.py @@ -0,0 +1,143 @@ +import asyncio +import logging + +import pydase + +from icon.config.config import get_config +from icon.server.data_access.repositories.ttl_repository import TTLRepository +from icon.server.hardware_processing.hardware_controller import HardwareController +from icon.server.web_server.socketio_emit_queue import emit_queue + +logger = logging.getLogger(__name__) + +_OFF = 0 +_ON = 1 +_CONTROL = 2 + + +def _decode_state(channel: int, high_mask: int, low_mask: int) -> int: + """Return the state (0=OFF, 1=ON, 2=CONTROL) of a single TTL channel.""" + bit = 1 << channel + if low_mask & bit: + return _OFF + if high_mask & bit: + return _ON + return _CONTROL + + +def _encode_state( + channel: int, state: int, high_mask: int, low_mask: int +) -> tuple[int, int]: + """Return updated (high_mask, low_mask) after setting channel to state.""" + bit = 1 << channel + if state == _OFF: + high_mask &= ~bit + low_mask |= bit + elif state == _ON: + high_mask |= bit + low_mask &= ~bit + elif state == _CONTROL: + high_mask &= ~bit + low_mask &= ~bit + else: + raise ValueError(f"Invalid TTL state {state!r}; must be 0 (OFF), 1 (ON), or 2 (CONTROL)") + return high_mask, low_mask + + +class TTLController(pydase.DataService): + """Per-channel TTL state control for the Zedboard FPGA. + + Each of the n_ttl_channels output channels can be set to one of three states: + + - 0 (OFF): channel forced LOW + - 1 (ON): channel forced HIGH + - 2 (CONTROL): channel driven by the pulse sequence + + Mask state is persisted to SQLite so it survives hardware power cycles. + """ + + def __init__(self) -> None: + super().__init__() + self._n_channels: int = get_config().hardware.n_ttl_channels + self._hw = HardwareController(connect=False) + self._repo = TTLRepository() + + def get_states(self) -> list[int]: + """Return the current state (0/1/2) for all channels. + + Reads live from the hardware when connected; falls back to the last + persisted masks if the hardware is unreachable. + """ + try: + high_mask, low_mask = self._hw.get_ttl_masks() + except RuntimeError: + logger.warning( + "Hardware unreachable; returning persisted TTL mask state" + ) + high_mask, low_mask = self._repo.get_masks() + return [ + _decode_state(ch, high_mask, low_mask) + for ch in range(self._n_channels) + ] + + def set_state(self, channel: int, state: int) -> None: + """Set a single TTL channel to state 0 (OFF), 1 (ON), or 2 (CONTROL). + + Persists the resulting masks to SQLite and emits a ``ttl.update`` event. + + Args: + channel: Channel index (0 to n_ttl_channels - 1). + state: 0 = forced LOW, 1 = forced HIGH, 2 = pulse-sequence control. + + Raises: + ValueError: If channel or state is out of range. + RuntimeError: If the hardware is unreachable. + """ + if not (0 <= channel < self._n_channels): + raise ValueError( + f"Channel {channel} out of range [0, {self._n_channels - 1}]" + ) + high_mask, low_mask = self._hw.get_ttl_masks() + high_mask, low_mask = _encode_state(channel, state, high_mask, low_mask) + self._hw.set_ttl_masks(high_mask, low_mask) + self._repo.save_masks(high_mask, low_mask) + emit_queue.put( + { + "event": "ttl.update", + "data": { + "channel": channel, + "state": state, + "high_mask": high_mask, + "low_mask": low_mask, + }, + } + ) + logger.info("TTL channel %d set to state %d", channel, state) + + def get_masks(self) -> dict[str, int]: + """Return the raw ``{'high_mask': ..., 'low_mask': ...}`` from hardware. + + Falls back to persisted masks if the hardware is unreachable. + """ + try: + high_mask, low_mask = self._hw.get_ttl_masks() + except RuntimeError: + logger.warning( + "Hardware unreachable; returning persisted TTL masks" + ) + high_mask, low_mask = self._repo.get_masks() + return {"high_mask": high_mask, "low_mask": low_mask} + + async def restore_masks(self) -> None: + """Write the last persisted masks back to the hardware. + + Useful after a hardware power cycle. Runs the RPC call in a thread to + avoid blocking the event loop. + """ + high_mask, low_mask = self._repo.get_masks() + await asyncio.to_thread(self._hw.set_ttl_masks, high_mask, low_mask) + logger.info( + "Restored TTL masks to hardware: high=0x%08x low=0x%08x", + high_mask, + low_mask, + ) diff --git a/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py b/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py new file mode 100644 index 00000000..d6836995 --- /dev/null +++ b/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py @@ -0,0 +1,33 @@ +"""Add ttl_mask_states table. + +Revision ID: a1b2c3d4e5f6 +Revises: fc9af856df20 +Create Date: 2026-05-18 00:00:00.000000 + +""" + +from collections.abc import Sequence + +import sqlalchemy as sa +from alembic import op + +# revision identifiers, used by Alembic. +revision: str = "a1b2c3d4e5f6" +down_revision: str | None = "fc9af856df20" +branch_labels: str | Sequence[str] | None = None +depends_on: str | Sequence[str] | None = None + + +def upgrade() -> None: + op.create_table( + "ttl_mask_states", + sa.Column("id", sa.Integer(), autoincrement=True, nullable=False), + sa.Column("high_mask", sa.Integer(), nullable=False), + sa.Column("low_mask", sa.Integer(), nullable=False), + sa.Column("updated_at", sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint("id"), + ) + + +def downgrade() -> None: + op.drop_table("ttl_mask_states") diff --git a/src/icon/server/data_access/models/sqlite/__init__.py b/src/icon/server/data_access/models/sqlite/__init__.py index 34f2b976..0b54d1a5 100644 --- a/src/icon/server/data_access/models/sqlite/__init__.py +++ b/src/icon/server/data_access/models/sqlite/__init__.py @@ -12,6 +12,7 @@ from icon.server.data_access.models.sqlite.job import Job from icon.server.data_access.models.sqlite.job_run import JobRun from icon.server.data_access.models.sqlite.scan_parameter import ScanParameter +from icon.server.data_access.models.sqlite.ttl_mask_state import TTLMaskState __all__ = [ "Base", @@ -20,4 +21,5 @@ "Job", "JobRun", "ScanParameter", + "TTLMaskState", ] diff --git a/src/icon/server/data_access/models/sqlite/ttl_mask_state.py b/src/icon/server/data_access/models/sqlite/ttl_mask_state.py new file mode 100644 index 00000000..2c5967d7 --- /dev/null +++ b/src/icon/server/data_access/models/sqlite/ttl_mask_state.py @@ -0,0 +1,42 @@ +import datetime + +import pytz +import sqlalchemy +import sqlalchemy.orm + +from icon.config.config import get_config +from icon.server.data_access.models.sqlite.base import Base + +timezone = pytz.timezone(get_config().date.timezone) + + +class TTLMaskState(Base): + """SQLAlchemy model for persisting TTL override masks. + + A single row (id=1) stores the current high_mask and low_mask written to the + Zedboard FPGA. This allows the server to restore channel states after a hardware + power cycle. + """ + + __tablename__ = "ttl_mask_states" + + id: sqlalchemy.orm.Mapped[int] = sqlalchemy.orm.mapped_column( + primary_key=True, autoincrement=True + ) + high_mask: sqlalchemy.orm.Mapped[int] = sqlalchemy.orm.mapped_column( + nullable=False, default=0 + ) + low_mask: sqlalchemy.orm.Mapped[int] = sqlalchemy.orm.mapped_column( + nullable=False, default=0 + ) + updated_at: sqlalchemy.orm.Mapped[datetime.datetime] = sqlalchemy.orm.mapped_column( + nullable=False, + default=lambda: datetime.datetime.now(timezone), + onupdate=lambda: datetime.datetime.now(timezone), + ) + + def __repr__(self) -> str: + return ( + f"" + ) diff --git a/src/icon/server/data_access/repositories/ttl_repository.py b/src/icon/server/data_access/repositories/ttl_repository.py new file mode 100644 index 00000000..0bb18f08 --- /dev/null +++ b/src/icon/server/data_access/repositories/ttl_repository.py @@ -0,0 +1,41 @@ +import logging + +import sqlalchemy.orm + +from icon.server.data_access.db_context.sqlite import engine +from icon.server.data_access.models.sqlite.ttl_mask_state import TTLMaskState + +logger = logging.getLogger(__name__) + +_SINGLETON_ID = 1 + + +class TTLRepository: + """Data access object for the TTL mask state table. + + The table always contains at most one row (id=1), representing the last + mask pair written to the Zedboard FPGA. + """ + + def get_masks(self) -> tuple[int, int]: + """Return (high_mask, low_mask); returns (0, 0) if no row exists yet.""" + with sqlalchemy.orm.Session(engine) as session: + row = session.get(TTLMaskState, _SINGLETON_ID) + if row is None: + return 0, 0 + return row.high_mask, row.low_mask + + def save_masks(self, high_mask: int, low_mask: int) -> None: + """Upsert the single TTL state row with new mask values.""" + with sqlalchemy.orm.Session(engine) as session: + row = session.get(TTLMaskState, _SINGLETON_ID) + if row is None: + row = TTLMaskState(id=_SINGLETON_ID, high_mask=high_mask, low_mask=low_mask) + session.add(row) + else: + row.high_mask = high_mask + row.low_mask = low_mask + session.commit() + logger.debug( + "Saved TTL masks: high=0x%08x low=0x%08x", high_mask, low_mask + ) diff --git a/src/icon/server/hardware_processing/hardware_controller.py b/src/icon/server/hardware_processing/hardware_controller.py index e866b62b..b83d9d6f 100644 --- a/src/icon/server/hardware_processing/hardware_controller.py +++ b/src/icon/server/hardware_processing/hardware_controller.py @@ -67,3 +67,29 @@ def run(self, *, sequence: str, number_of_shots: int) -> ResultDict: else {}, "shot_channels": results.shot_channels, } + + def get_ttl_masks(self) -> tuple[int, int]: + """Return (high_mask, low_mask) from the hardware via the ttlMasks RPC call.""" + if not self.connected: + self.connect() + if not self.connected: + if HAS_TIQI_ZEDBOARD: + raise RuntimeError("Could not connect to the Zedboard") + raise RuntimeError( + "Tiqi zedboard package is not available. " + "Please use 'uv sync --all-extras' to install all dependencies" + ) + return self._zedboard._invoke("ttlMasks") # type: ignore[union-attr] + + def set_ttl_masks(self, high_mask: int, low_mask: int) -> None: + """Write (high_mask, low_mask) to the hardware via the setTTLMasks RPC call.""" + if not self.connected: + self.connect() + if not self.connected: + if HAS_TIQI_ZEDBOARD: + raise RuntimeError("Could not connect to the Zedboard") + raise RuntimeError( + "Tiqi zedboard package is not available. " + "Please use 'uv sync --all-extras' to install all dependencies" + ) + self._zedboard._invoke("setTTLMasks", high_mask, low_mask) # type: ignore[union-attr] diff --git a/tests/server/__init__.py b/tests/server/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/server/api/test_ttl_controller.py b/tests/server/api/test_ttl_controller.py new file mode 100644 index 00000000..7d0d64c0 --- /dev/null +++ b/tests/server/api/test_ttl_controller.py @@ -0,0 +1,125 @@ +"""Tests for TTLController mask encoding/decoding and state management.""" + +from unittest.mock import MagicMock, patch + +import pytest + +from icon.server.api.ttl_controller import ( + TTLController, + _decode_state, + _encode_state, +) + + +class TestDecodeState: + def test_off_when_low_bit_set(self) -> None: + assert _decode_state(0, high_mask=0b00, low_mask=0b01) == 0 + + def test_on_when_high_bit_set(self) -> None: + assert _decode_state(0, high_mask=0b01, low_mask=0b00) == 1 + + def test_control_when_both_bits_clear(self) -> None: + assert _decode_state(0, high_mask=0b00, low_mask=0b00) == 2 + + def test_channel_31_off(self) -> None: + low_mask = 1 << 31 + assert _decode_state(31, high_mask=0, low_mask=low_mask) == 0 + + def test_channel_31_on(self) -> None: + high_mask = 1 << 31 + assert _decode_state(31, high_mask=high_mask, low_mask=0) == 1 + + def test_channel_31_control(self) -> None: + assert _decode_state(31, high_mask=0, low_mask=0) == 2 + + def test_independent_of_other_channels(self) -> None: + # Channel 0 is ON; channel 1 is in CONTROL — decoding ch1 should give 2 + high_mask = 0b01 # ch0 ON + low_mask = 0b00 + assert _decode_state(1, high_mask, low_mask) == 2 + + +class TestEncodeState: + def test_set_off(self) -> None: + high, low = _encode_state(0, state=0, high_mask=0b01, low_mask=0b00) + assert not (high & 1) # high bit cleared + assert low & 1 # low bit set + + def test_set_on(self) -> None: + high, low = _encode_state(0, state=1, high_mask=0b00, low_mask=0b01) + assert high & 1 # high bit set + assert not (low & 1) # low bit cleared + + def test_set_control(self) -> None: + high, low = _encode_state(0, state=2, high_mask=0b01, low_mask=0b01) + assert not (high & 1) # high bit cleared + assert not (low & 1) # low bit cleared + + def test_does_not_affect_other_channels(self) -> None: + # Channel 1 is ON (bit 1 set in high_mask) + high, low = _encode_state(0, state=0, high_mask=0b10, low_mask=0b00) + assert high & 0b10 # channel 1 still ON + + def test_invalid_state_raises(self) -> None: + with pytest.raises(ValueError, match="Invalid TTL state"): + _encode_state(0, state=3, high_mask=0, low_mask=0) + + def test_channel_31(self) -> None: + high, low = _encode_state(31, state=1, high_mask=0, low_mask=0) + assert high == (1 << 31) + assert low == 0 + + +class TestTTLController: + def _make_controller(self, hw_masks=(0, 0)): + with ( + patch("icon.server.api.ttl_controller.HardwareController") as MockHW, + patch("icon.server.api.ttl_controller.TTLRepository") as MockRepo, + patch("icon.server.api.ttl_controller.get_config") as MockConfig, + ): + MockConfig.return_value.hardware.n_ttl_channels = 32 + hw = MockHW.return_value + hw.get_ttl_masks.return_value = hw_masks + repo = MockRepo.return_value + repo.get_masks.return_value = hw_masks + ctrl = TTLController() + ctrl._hw = hw + ctrl._repo = repo + ctrl._n_channels = 32 + return ctrl, hw, repo + + def test_get_states_all_control_when_masks_zero(self) -> None: + ctrl, hw, _ = self._make_controller((0, 0)) + states = ctrl.get_states() + assert all(s == 2 for s in states) + assert len(states) == 32 + + def test_get_states_channel_0_on(self) -> None: + ctrl, hw, _ = self._make_controller((0b01, 0b00)) + states = ctrl.get_states() + assert states[0] == 1 + assert states[1] == 2 + + def test_get_states_falls_back_to_db_on_error(self) -> None: + ctrl, hw, repo = self._make_controller() + hw.get_ttl_masks.side_effect = RuntimeError("no hardware") + repo.get_masks.return_value = (0b01, 0b00) + states = ctrl.get_states() + assert states[0] == 1 + + def test_set_state_writes_to_hw_and_persists(self) -> None: + ctrl, hw, repo = self._make_controller((0, 0)) + with patch("icon.server.api.ttl_controller.emit_queue"): + ctrl.set_state(0, 1) + hw.set_ttl_masks.assert_called_once_with(0b01, 0b00) + repo.save_masks.assert_called_once_with(0b01, 0b00) + + def test_set_state_invalid_channel_raises(self) -> None: + ctrl, _, _ = self._make_controller() + with pytest.raises(ValueError, match="out of range"): + ctrl.set_state(32, 1) + + def test_get_masks_returns_dict(self) -> None: + ctrl, hw, _ = self._make_controller((0xAB, 0xCD)) + result = ctrl.get_masks() + assert result == {"high_mask": 0xAB, "low_mask": 0xCD} From 6f6263be14615f8c6cbb04300480cbf61b4f8cf0 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Mon, 18 May 2026 14:53:56 +0200 Subject: [PATCH 30/46] feat(frontend): add TTL channel control page with ionizer-style two-button UX Adds a dedicated /ttl page with 32-channel grid. Each channel mirrors ionizer's ControlButton (blue=FPGA, grey=manual) + StateButton (green=ON, red=OFF) layout. StateButton retains its value when in CONTROL mode and applies it on switch-back, matching ionizer behaviour exactly. Also adds server-side label persistence (TTLController.get_labels/set_label, labels column on ttl_mask_states via migration b2c3d4e5f6a1). Labels are editable inline via double-click and persisted to SQLite. Co-Authored-By: Claude Sonnet 4.6 --- frontend/src/App.tsx | 6 + frontend/src/components/ttl/TTLChannel.tsx | 148 ++++++++++++++++++ .../src/components/ttl/TTLControlPanel.tsx | 53 +++++++ frontend/src/hooks/useTTLState.tsx | 104 ++++++++++++ frontend/src/main.tsx | 5 + frontend/src/pages/ttl.tsx | 7 + src/icon/server/api/ttl_controller.py | 29 ++++ ...3d4e5f6a1_add_labels_to_ttl_mask_states.py | 28 ++++ .../models/sqlite/ttl_mask_state.py | 4 + .../repositories/ttl_repository.py | 35 ++++- 10 files changed, 418 insertions(+), 1 deletion(-) create mode 100644 frontend/src/components/ttl/TTLChannel.tsx create mode 100644 frontend/src/components/ttl/TTLControlPanel.tsx create mode 100644 frontend/src/hooks/useTTLState.tsx create mode 100644 frontend/src/pages/ttl.tsx create mode 100644 src/icon/server/data_access/db_context/sqlite/alembic/versions/b2c3d4e5f6a1_add_labels_to_ttl_mask_states.py diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index eb3645af..bd811740 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -1,6 +1,7 @@ import DashboardIcon from "@mui/icons-material/Dashboard"; import ScienceIcon from "@mui/icons-material/Science"; import TimelineIcon from "@mui/icons-material/Timeline"; +import ToggleOnIcon from "@mui/icons-material/ToggleOn"; import { Outlet } from "react-router"; import { ReactRouterAppProvider } from "@toolpad/core/react-router"; import type { Navigation } from "@toolpad/core/AppProvider"; @@ -57,6 +58,11 @@ const NAVIGATION: Navigation = [ ), }, + { + segment: "ttl", + title: "TTL", + icon: , + }, { kind: "divider", }, diff --git a/frontend/src/components/ttl/TTLChannel.tsx b/frontend/src/components/ttl/TTLChannel.tsx new file mode 100644 index 00000000..c02cb859 --- /dev/null +++ b/frontend/src/components/ttl/TTLChannel.tsx @@ -0,0 +1,148 @@ +import { useState, KeyboardEvent } from "react"; +import Box from "@mui/material/Box"; +import IconButton from "@mui/material/IconButton"; +import TextField from "@mui/material/TextField"; +import Typography from "@mui/material/Typography"; +import Tooltip from "@mui/material/Tooltip"; +import FiberManualRecordIcon from "@mui/icons-material/FiberManualRecord"; +import MemoryIcon from "@mui/icons-material/Memory"; + +interface Props { + channel: number; + /** Hardware state: 0=OFF, 1=ON, 2=CONTROL */ + state: number; + /** Remembered manual ON(1)/OFF(0), persisted independently of CONTROL mode */ + localManualState: 0 | 1; + label: string; + onSetState: (state: number) => void; + onSetLocalManual: (manual: 0 | 1) => void; + onSetLabel: (label: string) => void; +} + +export function TTLChannel({ + channel, + state, + localManualState, + label, + onSetState, + onSetLocalManual, + onSetLabel, +}: Props) { + const [editingLabel, setEditingLabel] = useState(false); + const [labelDraft, setLabelDraft] = useState(label); + + const inControl = state === 2; + + function handleControlClick() { + if (inControl) { + // CONTROL → manual: apply the remembered manual state + onSetState(localManualState); + } else { + // manual → CONTROL + onSetState(2); + } + } + + function handleStateClick() { + const newManual: 0 | 1 = localManualState === 1 ? 0 : 1; + onSetLocalManual(newManual); + if (!inControl) { + onSetState(newManual); + } + } + + function handleLabelCommit() { + setEditingLabel(false); + const trimmed = labelDraft.trim() || label; + setLabelDraft(trimmed); + if (trimmed !== label) { + onSetLabel(trimmed); + } + } + + function handleLabelKeyDown(e: KeyboardEvent) { + if (e.key === "Enter") handleLabelCommit(); + if (e.key === "Escape") { + setLabelDraft(label); + setEditingLabel(false); + } + } + + return ( + + {/* ControlButton: blue = CONTROL (FPGA owns channel), grey = manual */} + + + + + + + {/* StateButton: green = ON, red = OFF; faded when in CONTROL */} + + + + + + + {/* Editable label */} + {editingLabel ? ( + setLabelDraft(e.target.value)} + onBlur={handleLabelCommit} + onKeyDown={handleLabelKeyDown} + autoFocus + slotProps={{ input: { style: { fontSize: 12, padding: "2px 6px" } } }} + sx={{ width: 90 }} + /> + ) : ( + + { + setLabelDraft(label); + setEditingLabel(true); + }} + sx={{ + cursor: "text", + userSelect: "none", + overflow: "hidden", + textOverflow: "ellipsis", + whiteSpace: "nowrap", + minWidth: 0, + }} + > + {label} + + + )} + + ); +} diff --git a/frontend/src/components/ttl/TTLControlPanel.tsx b/frontend/src/components/ttl/TTLControlPanel.tsx new file mode 100644 index 00000000..7ca68587 --- /dev/null +++ b/frontend/src/components/ttl/TTLControlPanel.tsx @@ -0,0 +1,53 @@ +import Box from "@mui/material/Box"; +import Typography from "@mui/material/Typography"; +import { TTLChannel } from "./TTLChannel"; +import { TTLState } from "../../hooks/useTTLState"; + +interface Props { + ttl: TTLState; +} + +export function TTLControlPanel({ ttl }: Props) { + const { states, labels, localManualState, setState, setLocalManual, setLabel } = ttl; + + return ( + + + TTL Channels + + + + {" "}FPGA control   + + {" "}ON   + + {" "}OFF  — double-click a label to rename + + + {states.map((state, channel) => ( + setState(channel, s)} + onSetLocalManual={(m) => setLocalManual(channel, m)} + onSetLabel={(l) => setLabel(channel, l)} + /> + ))} + + + ); +} diff --git a/frontend/src/hooks/useTTLState.tsx b/frontend/src/hooks/useTTLState.tsx new file mode 100644 index 00000000..edaab972 --- /dev/null +++ b/frontend/src/hooks/useTTLState.tsx @@ -0,0 +1,104 @@ +import { useCallback, useEffect, useState } from "react"; +import { runMethod, socket } from "../socket"; +import { deserialize } from "../utils/deserializer"; +import { SerializedObject } from "../types/SerializedObject"; + +const N_CHANNELS = 32; + +function defaultLabels(): string[] { + return Array.from({ length: N_CHANNELS }, (_, i) => `TTL ${i.toString().padStart(2, "0")}`); +} + +interface TTLUpdateEvent { + channel: number; + state: number; +} + +interface TTLLabelUpdateEvent { + channel: number; + label: string; +} + +export interface TTLState { + /** Hardware state per channel: 0=OFF, 1=ON, 2=CONTROL. */ + states: number[]; + /** Per-channel labels (editable). */ + labels: string[]; + /** + * Remembered manual ON/OFF value per channel, independent of whether the + * channel is currently in CONTROL mode. Matches ionizer's StateButton state. + */ + localManualState: number[]; + setState: (channel: number, state: number) => void; + setLocalManual: (channel: number, manual: 0 | 1) => void; + setLabel: (channel: number, label: string) => void; +} + +export function useTTLState(): TTLState { + const [states, setStates] = useState(Array(N_CHANNELS).fill(2)); + const [labels, setLabels] = useState(defaultLabels()); + const [localManualState, setLocalManualState] = useState( + Array(N_CHANNELS).fill(0), + ); + + useEffect(() => { + runMethod("ttl.get_states", [], {}, (ack) => { + const fetched = deserialize(ack as SerializedObject) as number[]; + setStates(fetched); + setLocalManualState(fetched.map((s) => (s === 2 ? 0 : s))); + }); + + runMethod("ttl.get_labels", [], {}, (ack) => { + setLabels(deserialize(ack as SerializedObject) as string[]); + }); + + function onTTLUpdate(data: TTLUpdateEvent) { + setStates((prev) => { + const next = [...prev]; + next[data.channel] = data.state; + return next; + }); + if (data.state !== 2) { + setLocalManualState((prev) => { + const next = [...prev]; + next[data.channel] = data.state; + return next; + }); + } + } + + function onLabelUpdate(data: TTLLabelUpdateEvent) { + setLabels((prev) => { + const next = [...prev]; + next[data.channel] = data.label; + return next; + }); + } + + socket.on("ttl.update", onTTLUpdate); + socket.on("ttl.label_update", onLabelUpdate); + + return () => { + socket.off("ttl.update", onTTLUpdate); + socket.off("ttl.label_update", onLabelUpdate); + }; + }, []); + + const setState = useCallback((channel: number, state: number) => { + runMethod("ttl.set_state", [channel, state]); + }, []); + + const setLocalManual = useCallback((channel: number, manual: 0 | 1) => { + setLocalManualState((prev) => { + const next = [...prev]; + next[channel] = manual; + return next; + }); + }, []); + + const setLabel = useCallback((channel: number, label: string) => { + runMethod("ttl.set_label", [channel, label]); + }, []); + + return { states, labels, localManualState, setState, setLocalManual, setLabel }; +} diff --git a/frontend/src/main.tsx b/frontend/src/main.tsx index 4462a68e..d98f5af0 100644 --- a/frontend/src/main.tsx +++ b/frontend/src/main.tsx @@ -9,6 +9,7 @@ import ParameterPage from "./pages/parameters"; import { DataPage } from "./pages/data"; import DevicesPage from "./pages/devices"; import { SettingsPage } from "./pages/settings"; +import TTLPage from "./pages/ttl"; import JobViewerLayout from "./layouts/job-viewer"; import { JobViewerPage } from "./pages/job-viewer"; @@ -40,6 +41,10 @@ const router = createBrowserRouter([ path: "devices", Component: DevicesPage, }, + { + path: "ttl", + Component: TTLPage, + }, { path: "settings", Component: SettingsPage, diff --git a/frontend/src/pages/ttl.tsx b/frontend/src/pages/ttl.tsx new file mode 100644 index 00000000..dba92865 --- /dev/null +++ b/frontend/src/pages/ttl.tsx @@ -0,0 +1,7 @@ +import { TTLControlPanel } from "../components/ttl/TTLControlPanel"; +import { useTTLState } from "../hooks/useTTLState"; + +export default function TTLPage() { + const ttl = useTTLState(); + return ; +} diff --git a/src/icon/server/api/ttl_controller.py b/src/icon/server/api/ttl_controller.py index bf3f6c96..d1f88e90 100644 --- a/src/icon/server/api/ttl_controller.py +++ b/src/icon/server/api/ttl_controller.py @@ -128,6 +128,35 @@ def get_masks(self) -> dict[str, int]: high_mask, low_mask = self._repo.get_masks() return {"high_mask": high_mask, "low_mask": low_mask} + def get_labels(self) -> list[str]: + """Return per-channel labels; missing entries default to 'TTL XX'.""" + return self._repo.get_labels(self._n_channels) + + def set_label(self, channel: int, label: str) -> None: + """Persist a custom label for one channel and emit a ``ttl.label_update`` event. + + Args: + channel: Channel index (0 to n_ttl_channels - 1). + label: New label string. + + Raises: + ValueError: If channel is out of range. + """ + if not (0 <= channel < self._n_channels): + raise ValueError( + f"Channel {channel} out of range [0, {self._n_channels - 1}]" + ) + labels = self._repo.get_labels(self._n_channels) + labels[channel] = label + self._repo.save_labels(labels) + emit_queue.put( + { + "event": "ttl.label_update", + "data": {"channel": channel, "label": label}, + } + ) + logger.info("TTL channel %d label set to %r", channel, label) + async def restore_masks(self) -> None: """Write the last persisted masks back to the hardware. diff --git a/src/icon/server/data_access/db_context/sqlite/alembic/versions/b2c3d4e5f6a1_add_labels_to_ttl_mask_states.py b/src/icon/server/data_access/db_context/sqlite/alembic/versions/b2c3d4e5f6a1_add_labels_to_ttl_mask_states.py new file mode 100644 index 00000000..0d113658 --- /dev/null +++ b/src/icon/server/data_access/db_context/sqlite/alembic/versions/b2c3d4e5f6a1_add_labels_to_ttl_mask_states.py @@ -0,0 +1,28 @@ +"""Add labels column to ttl_mask_states table. + +Revision ID: b2c3d4e5f6a1 +Revises: a1b2c3d4e5f6 +Create Date: 2026-05-18 00:01:00.000000 + +""" + +from collections.abc import Sequence + +import sqlalchemy as sa +from alembic import op + +# revision identifiers, used by Alembic. +revision: str = "b2c3d4e5f6a1" +down_revision: str | None = "a1b2c3d4e5f6" +branch_labels: str | Sequence[str] | None = None +depends_on: str | Sequence[str] | None = None + + +def upgrade() -> None: + with op.batch_alter_table("ttl_mask_states", schema=None) as batch_op: + batch_op.add_column(sa.Column("labels", sa.Text(), nullable=True)) + + +def downgrade() -> None: + with op.batch_alter_table("ttl_mask_states", schema=None) as batch_op: + batch_op.drop_column("labels") diff --git a/src/icon/server/data_access/models/sqlite/ttl_mask_state.py b/src/icon/server/data_access/models/sqlite/ttl_mask_state.py index 2c5967d7..c23cd59e 100644 --- a/src/icon/server/data_access/models/sqlite/ttl_mask_state.py +++ b/src/icon/server/data_access/models/sqlite/ttl_mask_state.py @@ -34,6 +34,10 @@ class TTLMaskState(Base): default=lambda: datetime.datetime.now(timezone), onupdate=lambda: datetime.datetime.now(timezone), ) + labels: sqlalchemy.orm.Mapped[str | None] = sqlalchemy.orm.mapped_column( + nullable=True, default=None + ) + """JSON-encoded list of per-channel label strings, e.g. '["TTL 00", "397 0th", ...]'.""" def __repr__(self) -> str: return ( diff --git a/src/icon/server/data_access/repositories/ttl_repository.py b/src/icon/server/data_access/repositories/ttl_repository.py index 0bb18f08..c839fd30 100644 --- a/src/icon/server/data_access/repositories/ttl_repository.py +++ b/src/icon/server/data_access/repositories/ttl_repository.py @@ -1,3 +1,4 @@ +import json import logging import sqlalchemy.orm @@ -10,11 +11,15 @@ _SINGLETON_ID = 1 +def _default_labels(n: int) -> list[str]: + return [f"TTL {i:02d}" for i in range(n)] + + class TTLRepository: """Data access object for the TTL mask state table. The table always contains at most one row (id=1), representing the last - mask pair written to the Zedboard FPGA. + mask pair and channel labels written to the Zedboard FPGA. """ def get_masks(self) -> tuple[int, int]: @@ -39,3 +44,31 @@ def save_masks(self, high_mask: int, low_mask: int) -> None: logger.debug( "Saved TTL masks: high=0x%08x low=0x%08x", high_mask, low_mask ) + + def get_labels(self, n_channels: int) -> list[str]: + """Return stored per-channel labels; missing entries filled with 'TTL XX' defaults.""" + with sqlalchemy.orm.Session(engine) as session: + row = session.get(TTLMaskState, _SINGLETON_ID) + if row is None or row.labels is None: + return _default_labels(n_channels) + stored: list[str] = json.loads(row.labels) + defaults = _default_labels(n_channels) + # Merge: use stored value where present, default otherwise + result = defaults[:] + for i, label in enumerate(stored): + if i < n_channels: + result[i] = label + return result + + def save_labels(self, labels: list[str]) -> None: + """Persist the full labels list as a JSON string.""" + with sqlalchemy.orm.Session(engine) as session: + row = session.get(TTLMaskState, _SINGLETON_ID) + if row is None: + row = TTLMaskState(id=_SINGLETON_ID, high_mask=0, low_mask=0, + labels=json.dumps(labels)) + session.add(row) + else: + row.labels = json.dumps(labels) + session.commit() + logger.debug("Saved TTL labels") From 2deca6149c09bbd59f09d17e7f27aaef302d9398 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Mon, 18 May 2026 15:00:01 +0200 Subject: [PATCH 31/46] fix(migrations): rebase TTL migration onto f60d837b7263 Points down_revision to the actual HEAD of main's migration chain instead of the branching point fc9af856df20. Co-Authored-By: Claude Sonnet 4.6 --- .../alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py b/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py index d6836995..bc6ab3e5 100644 --- a/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py +++ b/src/icon/server/data_access/db_context/sqlite/alembic/versions/a1b2c3d4e5f6_add_ttl_mask_state_table.py @@ -13,7 +13,7 @@ # revision identifiers, used by Alembic. revision: str = "a1b2c3d4e5f6" -down_revision: str | None = "fc9af856df20" +down_revision: str | None = "f60d837b7263" branch_labels: str | Sequence[str] | None = None depends_on: str | Sequence[str] | None = None From 3c49b29ebd10c194d4f9d9b69f91889c0d13038d Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 19 May 2026 13:12:57 +0200 Subject: [PATCH 32/46] add back imports and removing duplicated lines added by mistake when merging --- pyproject.toml | 1 + .../data_access/repositories/experiment_data_repository.py | 7 +++---- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index f55f6b6f..cf59cc44 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,6 +19,7 @@ server = [ "scipy>=1.14.0", "sqlalchemy>=2.0.36", "tables>=3.10.1", + "filelock>=3.16.1", "h5py>=3.12.1", "psutil>=7.0.0", ] diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index c3aecb09..3ac42b73 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -10,6 +10,7 @@ from typing import TYPE_CHECKING, Any, Literal, TypedDict, cast import h5py # type: ignore +from filelock import FileLock import numpy as np import numpy.typing as npt @@ -346,6 +347,8 @@ class ExperimentDataRepository: hdf5-level locking to support concurrent writers. """ + LOCK_EXTENSION = ".lock" + @staticmethod def update_metadata_by_job_id( # noqa: PLR0913 *, @@ -722,8 +725,6 @@ def get_experiment_data_by_job_id( for key, value in cast( "Sequence[tuple[str, h5py.Dataset]]", shot_channels_group.items(), - "Sequence[tuple[str, h5py.Dataset]]", - shot_channels_group.items(), ) } @@ -744,8 +745,6 @@ def get_experiment_data_by_job_id( for channel_name, vector_group in cast( "Sequence[tuple[str, h5py.Group]]", vector_channels_group.items(), - "Sequence[tuple[str, h5py.Group]]", - vector_channels_group.items(), ) } From 1ea91d562c892b75aa605474725f860e3fc452a2 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 19 May 2026 13:14:29 +0200 Subject: [PATCH 33/46] npm run build, warning this has the TTL tab + the fitting changes! --- .../server/frontend/assets/index-BPLIYou4.js | 45 +++++++++++++++++++ .../server/frontend/assets/index-CwRx0pcN.js | 45 ------------------- .../server/frontend/assets/index-Dur0C053.js | 45 ------------------- src/icon/server/frontend/index.html | 2 +- 4 files changed, 46 insertions(+), 91 deletions(-) create mode 100644 src/icon/server/frontend/assets/index-BPLIYou4.js delete mode 100644 src/icon/server/frontend/assets/index-CwRx0pcN.js delete mode 100644 src/icon/server/frontend/assets/index-Dur0C053.js diff --git a/src/icon/server/frontend/assets/index-BPLIYou4.js b/src/icon/server/frontend/assets/index-BPLIYou4.js new file mode 100644 index 00000000..3ce4e641 --- /dev/null +++ b/src/icon/server/frontend/assets/index-BPLIYou4.js @@ -0,0 +1,45 @@ +import{r as hb,a as mb,b as y,c as Je,j as d,u as Or,S as pb,d as vb,B as yb,A as Vf,e as gb,f as Rt,I as mt,g as bb,h as ef,T as jv,i as xb,C as Tv,k as Dv,l as fl,m as Sb,n as e0,o as St,s as kf,p as pe,q as Gt,t as Rv,v as Nt,P as Eb,D as Nr,w as Sf,x as Cb,L as _b,y as wb,z as _r,G as jb,E as qf,F as Tb,H as wr,J as jr,K as Tr,M as tf,N as Eo,O as Yf,Q as hl,R as en,U as Co,V as lt,W as Ba,X as Ha,Y as aa,Z as Db,_ as Av,$ as Rb,a0 as ta,a1 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gt=!1,h1(e,t,n);gt=(e.flags&131072)!==0}else gt=!1,He&&(t.flags&1048576)!==0&&uh(t,fs,t.index);switch(t.lanes=0,t.tag){case 16:e:{e=t.pendingProps;var i=t.elementType,o=i._init;if(i=o(i._payload),t.type=i,typeof i=="function")bu(i)?(e=sl(i,e),t.tag=1,t=Dm(null,t,i,e,n)):(t.tag=0,t=ac(null,t,i,e,n));else{if(i!=null){if(o=i.$$typeof,o===P){t.tag=11,t=Em(null,t,i,e,n);break e}else if(o===K){t.tag=14,t=Cm(null,t,i,e,n);break e}}throw t=I(i)||i,Error(s(306,t,""))}}return t;case 0:return ac(e,t,t.type,t.pendingProps,n);case 1:return i=t.type,o=sl(i,t.pendingProps),Dm(e,t,i,o,n);case 3:e:{if(gl(t,t.stateNode.containerInfo),e===null)throw Error(s(387));i=t.pendingProps;var c=t.memoizedState;o=c.element,Nu(e,t),ki(t,i,null,n);var v=t.memoizedState;if(i=v.cache,ca(t,pt,i),i!==c.cache&&Tu(t,[pt],n,!0),Vi(),i=v.element,c.isDehydrated)if(c={element:i,isDehydrated:!1,cache:v.cache},t.updateQueue.baseState=c,t.memoizedState=c,t.flags&256){t=Rm(e,t,i,n);break e}else 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e===null&&He&&((o=i=nt)&&(i=q1(i,t.type,t.pendingProps,jn),i!==null?(t.stateNode=i,Mt=t,nt=xn(i.firstChild),jn=!1,o=!0):o=!1),o||nl(t)),ut(t),o=t.type,c=t.pendingProps,v=e!==null?e.memoizedProps:null,i=c.children,kc(o,c)?i=null:v!==null&&kc(o,v)&&(t.flags|=32),t.memoizedState!==null&&(o=Vu(e,t,i1,null,null,n),or._currentValue=o),Ms(e,t),_t(e,t,i,n),t.child;case 6:return e===null&&He&&((e=n=nt)&&(n=Y1(n,t.pendingProps,jn),n!==null?(t.stateNode=n,Mt=t,nt=null,e=!0):e=!1),e||nl(t)),null;case 13:return Am(e,t,n);case 4:return gl(t,t.stateNode.containerInfo),i=t.pendingProps,e===null?t.child=Gl(t,null,i,n):_t(e,t,i,n),t.child;case 11:return Em(e,t,t.type,t.pendingProps,n);case 7:return _t(e,t,t.pendingProps,n),t.child;case 8:return _t(e,t,t.pendingProps.children,n),t.child;case 12:return _t(e,t,t.pendingProps.children,n),t.child;case 10:return i=t.pendingProps,ca(t,t.type,i.value),_t(e,t,i.children,n),t.child;case 9:return o=t.type._context,i=t.pendingProps.children,ll(t),o=Dt(o),i=i(o),t.flags|=1,_t(e,t,i,n),t.child;case 14:return Cm(e,t,t.type,t.pendingProps,n);case 15:return _m(e,t,t.type,t.pendingProps,n);case 19:return Om(e,t,n);case 31:return i=t.pendingProps,n=t.mode,i={mode:i.mode,children:i.children},e===null?(n=Os(i,n),n.ref=t.ref,t.child=n,n.return=t,t=n):(n=Yn(e.child,i),n.ref=t.ref,t.child=n,n.return=t,t=n),t;case 22:return wm(e,t,n);case 24:return ll(t),i=Dt(pt),e===null?(o=Au(),o===null&&(o=Ke,c=Du(),o.pooledCache=c,c.refCount++,c!==null&&(o.pooledCacheLanes|=n),o=c),t.memoizedState={parent:i,cache:o},Ou(t),ca(t,pt,o)):((e.lanes&n)!==0&&(Nu(e,t),ki(t,null,null,n),Vi()),o=e.memoizedState,c=t.memoizedState,o.parent!==i?(o={parent:i,cache:i},t.memoizedState=o,t.lanes===0&&(t.memoizedState=t.updateQueue.baseState=o),ca(t,pt,i)):(i=c.cache,ca(t,pt,i),i!==o.cache&&Tu(t,[pt],n,!0))),_t(e,t,t.pendingProps.children,n),t.child;case 29:throw t.pendingProps}throw Error(s(156,t.tag))}function $n(e){e.flags|=4}function zm(e,t){if(t.type!=="stylesheet"||(t.state.loading&4)!==0)e.flags&=-16777217;else if(e.flags|=16777216,!Yp(t)){if(t=un.current,t!==null&&((ze&4194048)===ze?Tn!==null:(ze&62914560)!==ze&&(ze&536870912)===0||t!==Tn))throw Bi=Mu,yh;e.flags|=8192}}function Ns(e,t){t!==null&&(e.flags|=4),e.flags&16384&&(t=e.tag!==22?Kr():536870912,e.lanes|=t,Kl|=t)}function Ki(e,t){if(!He)switch(e.tailMode){case"hidden":t=e.tail;for(var n=null;t!==null;)t.alternate!==null&&(n=t),t=t.sibling;n===null?e.tail=null:n.sibling=null;break;case"collapsed":n=e.tail;for(var i=null;n!==null;)n.alternate!==null&&(i=n),n=n.sibling;i===null?t||e.tail===null?e.tail=null:e.tail.sibling=null:i.sibling=null}}function et(e){var t=e.alternate!==null&&e.alternate.child===e.child,n=0,i=0;if(t)for(var o=e.child;o!==null;)n|=o.lanes|o.childLanes,i|=o.subtreeFlags&65011712,i|=o.flags&65011712,o.return=e,o=o.sibling;else for(o=e.child;o!==null;)n|=o.lanes|o.childLanes,i|=o.subtreeFlags,i|=o.flags,o.return=e,o=o.sibling;return e.subtreeFlags|=i,e.childLanes=n,t}function m1(e,t,n){var i=t.pendingProps;switch(Cu(t),t.tag){case 31:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return et(t),null;case 1:return et(t),null;case 3:return n=t.stateNode,i=null,e!==null&&(i=e.memoizedState.cache),t.memoizedState.cache!==i&&(t.flags|=2048),Qn(pt),ia(),n.pendingContext&&(n.context=n.pendingContext,n.pendingContext=null),(e===null||e.child===null)&&(Ai(t)?$n(t):e===null||e.memoizedState.isDehydrated&&(t.flags&256)===0||(t.flags|=1024,dh())),et(t),null;case 26:return n=t.memoizedState,e===null?($n(t),n!==null?(et(t),zm(t,n)):(et(t),t.flags&=-16777217)):n?n!==e.memoizedState?($n(t),et(t),zm(t,n)):(et(t),t.flags&=-16777217):(e.memoizedProps!==i&&$n(t),et(t),t.flags&=-16777217),null;case 27:pn(t),n=zt.current;var o=t.type;if(e!==null&&t.stateNode!=null)e.memoizedProps!==i&&$n(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return et(t),null}e=Ue.current,Ai(t)?ch(t):(e=zp(o,i,n),t.stateNode=e,$n(t))}return et(t),null;case 5:if(pn(t),n=t.type,e!==null&&t.stateNode!=null)e.memoizedProps!==i&&$n(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return et(t),null}if(e=Ue.current,Ai(t))ch(t);else{switch(o=Qs(zt.current),e){case 1:e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case 2:e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;default:switch(n){case"svg":e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case"math":e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;case"script":e=o.createElement("div"),e.innerHTML=" + From d989ca9d02e3040e1bf38bccbc67ceb9ee28c285 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Fri, 15 May 2026 11:49:05 +0000 Subject: [PATCH 34/46] Regenerate scan values when pattern dropdown changes --- frontend/src/components/scanInterface/ParameterCard.tsx | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/frontend/src/components/scanInterface/ParameterCard.tsx b/frontend/src/components/scanInterface/ParameterCard.tsx index 8c77c63f..c4c1d472 100644 --- a/frontend/src/components/scanInterface/ParameterCard.tsx +++ b/frontend/src/components/scanInterface/ParameterCard.tsx @@ -414,14 +414,21 @@ export const ParameterCard = ({ label="Scan pattern" value={pattern} onChange={(e) => { + const nextPattern = e.target.value as ScanPattern; dispatchScanInfoStateUpdate({ type: "UPDATE_PARAMETER", index: index!, payload: { generation: { ...param.generation, - pattern: e.target.value as ScanPattern, + pattern: nextPattern, }, + values: generateScanValues( + param.generation.start, + param.generation.stop, + param.generation.points, + nextPattern, + ), }, }); }} From 226e62259e3d6aaefcb75845af7f6cda9ef54d79 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 19 May 2026 14:20:38 +0200 Subject: [PATCH 35/46] npm run build. Warning this contains TTL tab + fitting branch --- .../{index-BPLIYou4.js => index-hJ7hriKR.js} | 20 +++++++++---------- src/icon/server/frontend/index.html | 2 +- 2 files changed, 11 insertions(+), 11 deletions(-) rename src/icon/server/frontend/assets/{index-BPLIYou4.js => index-hJ7hriKR.js} (79%) diff --git a/src/icon/server/frontend/assets/index-BPLIYou4.js b/src/icon/server/frontend/assets/index-hJ7hriKR.js similarity index 79% rename from src/icon/server/frontend/assets/index-BPLIYou4.js rename to src/icon/server/frontend/assets/index-hJ7hriKR.js index 3ce4e641..2c56ccfe 100644 --- a/src/icon/server/frontend/assets/index-BPLIYou4.js +++ b/src/icon/server/frontend/assets/index-hJ7hriKR.js @@ -1,4 +1,4 @@ -import{r as hb,a as mb,b as y,c as Je,j as d,u as Or,S as pb,d as vb,B as yb,A as Vf,e as gb,f as Rt,I as mt,g as bb,h as ef,T as jv,i as xb,C as Tv,k as Dv,l as fl,m as Sb,n as e0,o as St,s as kf,p as pe,q as Gt,t as Rv,v as Nt,P as Eb,D as Nr,w as Sf,x as Cb,L as _b,y as wb,z 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u.integrity&&(f.integrity=u.integrity),u.referrerPolicy&&(f.referrerPolicy=u.referrerPolicy),u.crossOrigin==="use-credentials"?f.credentials="include":u.crossOrigin==="anonymous"?f.credentials="omit":f.credentials="same-origin",f}function s(u){if(u.ep)return;u.ep=!0;const f=r(u);fetch(u.href,f)}})();var nf={exports:{}},hr={},af={exports:{}},lf={};/** +import{r as hb,a as mb,b as y,c as Je,j as d,u as Or,S as pb,d as vb,B as yb,A as Vf,e as gb,f as Rt,I as mt,g as bb,h as tf,T as jv,i as xb,C as Tv,k as Dv,l as fl,m as Sb,n as e0,o as St,s as kf,p as pe,q as Gt,t as Rv,v as Nt,P as Eb,D as Nr,w as Sf,x as Cb,L as _b,y as wb,z as _r,G as jb,E as qf,F as Tb,H as wr,J as jr,K as Tr,M as nf,N as Co,O as Yf,Q as hl,R as en,U as _o,V as lt,W as Ba,X as Ha,Y as aa,Z as Db,_ as Av,$ as Rb,a0 as ta,a1 as na,a2 as Yt,a3 as Va,a4 as Ze,a5 as Ab,a6 as Mb,a7 as wo,a8 as jo,a9 as To,aa as Ob,ab as Mv,ac as Nb,ad as zb,ae as Lb,af as Ub,ag as Bb,ah as Ma}from"./mui-bAivgoRt.js";import{u as Hb,i as 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changed, 11 insertions(+) diff --git a/uv.lock b/uv.lock index 3bffa061..cee40edf 100644 --- a/uv.lock +++ b/uv.lock @@ -678,6 +678,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl", hash = "sha256:1c797122d0a86c5cace2e54bf4e819c36223b552017172f32c5c024a6b77e463", size = 24024, upload-time = "2025-08-14T18:49:34.776Z" }, ] +[[package]] +name = "filelock" +version = "3.29.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/b5/fe/997687a931ab51049acce6fa1f23e8f01216374ea81374ddee763c493db5/filelock-3.29.0.tar.gz", hash = "sha256:69974355e960702e789734cb4871f884ea6fe50bd8404051a3530bc07809cf90", size = 57571, upload-time = "2026-04-19T15:39:10.068Z" } +wheels = [ + { url = 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00:00:00 2001 From: Florence Berterottiere Date: Wed, 20 May 2026 19:56:39 +0200 Subject: [PATCH 37/46] npm run build --- .../server/frontend/assets/index-Ciiw6jzV.js | 45 ------------------- src/icon/server/frontend/index.html | 2 +- 2 files changed, 1 insertion(+), 46 deletions(-) delete mode 100644 src/icon/server/frontend/assets/index-Ciiw6jzV.js diff --git a/src/icon/server/frontend/assets/index-Ciiw6jzV.js b/src/icon/server/frontend/assets/index-Ciiw6jzV.js deleted file mode 100644 index f1b5e5a7..00000000 --- a/src/icon/server/frontend/assets/index-Ciiw6jzV.js +++ /dev/null @@ -1,45 +0,0 @@ -import{r as db,a as hb,b as y,c as rt,j as d,u as Mr,S as mb,d as pb,B as vb,A as Sv,e as yb,f as $t,I as xt,g as gb,h as Jc,T as Ev,i as bb,C as wv,k as Cv,l as il,m as xb,n as $p,o as bt,s as Uf,p as be,q as gn,t as _v,v as Wn,P as Sb,D as Or,w as vf,x as Eb,L as wb,y as Cb,z as wr,G as _b,E as Bf,F as Tb,H as Cr,J as _r,K as Tr,M as Fc,N as Tv,O as jv,Q as So,R as rl,U as Dv,V as Rn,W as 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o=t.type;if(e!==null&&t.stateNode!=null)e.memoizedProps!==i&&Kn(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return Ie(t),null}e=Ue.current,ji(t)?ih(t):(e=Rp(o,i,n),t.stateNode=e,Kn(t))}return Ie(t),null;case 5:if(cn(t),n=t.type,e!==null&&t.stateNode!=null)e.memoizedProps!==i&&Kn(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return Ie(t),null}if(e=Ue.current,ji(t))ih(t);else{switch(o=Xs(Mt.current),e){case 1:e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case 2:e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;default:switch(n){case"svg":e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case"math":e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;case"script":e=o.createElement("div"),e.innerHTML=" + From f066f3b48c416587f28ce7de82d23b1e45a7aafb Mon Sep 17 00:00:00 2001 From: Flo Date: Wed, 20 May 2026 20:06:21 +0200 Subject: [PATCH 38/46] make storing of nb of shots more flexible to accept some shots being retaken by recrystallizations --- .../repositories/experiment_data_repository.py | 10 ++++++++-- src/icon/server/pre_processing/worker.py | 9 ++++++++- 2 files changed, 16 insertions(+), 3 deletions(-) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index f5c7b527..bd3e6743 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -298,7 +298,7 @@ def write_shot_channels_to_datasets( shot_dataset = shot_group.require_dataset( key, shape=(number_of_data_points, number_of_shots), - maxshape=(None, number_of_shots), + maxshape=(None, None), chunks=True, dtype=np.float64, compression="gzip", @@ -307,7 +307,13 @@ def write_shot_channels_to_datasets( if data_point_index >= number_of_data_points: resize_dataset(shot_dataset, next_index=data_point_index, axis=0) - shot_dataset[data_point_index] = value + + actual_shots = len(value) + if actual_shots > shot_dataset.shape[1]: + resize_dataset(shot_dataset, next_index=actual_shots - 1, axis=1) + padded = np.full(shot_dataset.shape[1], np.nan) + padded[:actual_shots] = value + shot_dataset[data_point_index] = padded def write_vector_channels_to_datasets( diff --git a/src/icon/server/pre_processing/worker.py b/src/icon/server/pre_processing/worker.py index 74a38934..dd7d63c0 100644 --- a/src/icon/server/pre_processing/worker.py +++ b/src/icon/server/pre_processing/worker.py @@ -417,7 +417,7 @@ def _handle_regular_scan( for combination in enumerate(scan_parameter_value_combinations): self._data_points_to_process.put(combination) - while self._processed_data_points.qsize() != len( + while self._processed_data_points.qsize() < len( scan_parameter_value_combinations ): self._handle_parameter_updates(pre_processing_task, namespace) @@ -427,9 +427,16 @@ def _handle_regular_scan( try: index, data_point = self._data_points_to_process.get(block=False) except queue.Empty: + # Waiting phase: all tasks have been submitted but some may still + # be processing. Any task that the hw worker marked as "outdated" + # (task.created < parameter_update_timestamp) ends up in + # _outdated_tasks instead of _processed_data_points. We must + # regenerate those here; otherwise processed_data_points.qsize() + # never reaches N and this loop never exits. time.sleep(1.0) if job_run_cancelled_or_failed(job_id=pre_processing_task.job.id): break + self._regenerate_outdated_jobs(client, namespace) continue finally: should_exit = job_run_cancelled_or_failed( From 6346ba269c3fe2d43321f84c2a91477b7ba329bb Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Wed, 20 May 2026 20:41:04 +0200 Subject: [PATCH 39/46] fix filelock error from merging --- .../experiment_data_repository.py | 34 ++++--------------- 1 file changed, 7 insertions(+), 27 deletions(-) diff --git a/src/icon/server/data_access/repositories/experiment_data_repository.py b/src/icon/server/data_access/repositories/experiment_data_repository.py index bd3e6743..0bd66349 100644 --- a/src/icon/server/data_access/repositories/experiment_data_repository.py +++ b/src/icon/server/data_access/repositories/experiment_data_repository.py @@ -3,17 +3,12 @@ import time from collections.abc import Iterator from contextlib import contextmanager -import os -import time -from collections.abc import Iterator -from contextlib import contextmanager from dataclasses import asdict, dataclass from datetime import datetime from pathlib import Path from typing import TYPE_CHECKING, Any, Literal, TypedDict, cast import h5py # type: ignore -from filelock import FileLock import numpy as np import numpy.typing as npt @@ -862,13 +857,8 @@ def write_fit_result_by_job_id( job_id: Job identifier. fit_result: The fit result to persist. """ - filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) - with FileLock(lock_path), h5py.File(file, "a") as h5file: + h5_path = Path(get_config().data.results_dir) / get_filename_by_job_id(job_id) + with h5_open(h5_path, "a") as h5file: fits_group = h5file.require_group("fits") channel = fit_result.result_channel if channel in fits_group: @@ -886,16 +876,11 @@ def get_fit_results_by_job_id(*, job_id: int) -> dict[str, dict[str, object]]: Returns: Dict mapping result channel names to their fit result dicts. """ - filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" - if not os.path.exists(file): + h5_path = Path(get_config().data.results_dir) / get_filename_by_job_id(job_id) + if not h5_path.exists(): return {} - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) - with FileLock(lock_path), h5py.File(file, "r") as h5file: + with h5_open(h5_path, "r") as h5file: return _read_fits_from_hdf5(h5file) @@ -906,12 +891,7 @@ def delete_fit_result_by_job_id(*, job_id: int, result_channel: str) -> None: job_id: Job identifier. result_channel: Name of the result channel whose fit to delete. """ - filename = get_filename_by_job_id(job_id) - file = f"{get_config().data.results_dir}/{filename}" - lock_path = ( - f"{get_config().data.results_dir}/.{filename}" - f"{ExperimentDataRepository.LOCK_EXTENSION}" - ) - with FileLock(lock_path), h5py.File(file, "a") as h5file: + h5_path = Path(get_config().data.results_dir) / get_filename_by_job_id(job_id) + with h5_open(h5_path, "a") as h5file: if "fits" in h5file and result_channel in h5file["fits"]: del h5file["fits"][result_channel] From ed182efb6a1ed5ef49a66e14c34870407fcb7f1f Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Wed, 20 May 2026 20:57:25 +0200 Subject: [PATCH 40/46] fix: histogram memo never cached; remove stale LOCK_EXTENSION reference useMemo in HistogramPlot depended on categories/seriesData computed outside it, so new object references on every render meant the memo never skipped. Move all computation inside the memo and filter NaN values from shot arrays (padding added when recrystallized shot count exceeds the HDF5 dataset width). Also remove three references to ExperimentDataRepository.LOCK_EXTENSION in standalone fit functions that were missed when the attribute was deleted in the h5_open refactor. Co-Authored-By: Claude Sonnet 4.6 --- .../src/components/jobView/HistogramPlot.tsx | 53 ++++++++----------- 1 file changed, 22 insertions(+), 31 deletions(-) diff --git a/frontend/src/components/jobView/HistogramPlot.tsx b/frontend/src/components/jobView/HistogramPlot.tsx index a24b3332..43068929 100644 --- a/frontend/src/components/jobView/HistogramPlot.tsx +++ b/frontend/src/components/jobView/HistogramPlot.tsx @@ -24,42 +24,33 @@ export const HistogramPlot = ({ const [chart, setChart] = useState(null); const notifications = useNotifications(); - const latestPerChannel: Record = {}; - const sc = experimentData?.shot_channels ?? {}; - - for (const [channelName, groups] of Object.entries(sc)) { - if (!groups || !channelNames.includes(channelName)) continue; - - // Get the latest key by calculating the max of the available keys - const keys = Object.keys(groups).map(Number); - const latestKey = String(Math.max(...keys)); - - latestPerChannel[channelName] = groups[latestKey]; - } - - // Build the categories and frequency data - let categories: string[] = []; - const seriesData: { name: string; data: number[] }[] = []; + const option = useMemo(() => { + const sc = experimentData?.shot_channels ?? {}; + const latestPerChannel: Record = {}; + + for (const [channelName, groups] of Object.entries(sc)) { + if (!groups || !channelNames.includes(channelName)) continue; + const keys = Object.keys(groups).map(Number); + const latestKey = String(Math.max(...keys)); + latestPerChannel[channelName] = groups[latestKey]; + } - const allArrays = Object.values(latestPerChannel); - if (allArrays.length > 0) { - const globalMax = Math.max(...allArrays.map((a) => Math.max(...a))); - const rangeMax = Math.max(80, globalMax); // ensure at least 0..80 + const allArrays = Object.values(latestPerChannel); + if (allArrays.length === 0) return undefined; - // categories are the integer values from 0..rangeMax - categories = Array.from({ length: rangeMax + 1 }, (_, i) => String(i)); + const globalMax = Math.max( + ...allArrays.map((a) => Math.max(...a.filter((v) => !Number.isNaN(v)))) + ); + const rangeMax = Math.max(80, globalMax); + const categories = Array.from({ length: rangeMax + 1 }, (_, i) => String(i)); - for (const [name, arr] of Object.entries(latestPerChannel)) { + const seriesData = Object.entries(latestPerChannel).map(([name, arr]) => { const counts = new Array(rangeMax + 1).fill(0); for (const v of arr) { - counts[v]++; + if (!Number.isNaN(v)) counts[v]++; } - seriesData.push({ name, data: counts }); - } - } - - const option = useMemo(() => { - if (categories.length === 0 || seriesData.length === 0) return undefined; + return { name, data: counts }; + }); return { title: { @@ -129,7 +120,7 @@ export const HistogramPlot = ({ large: true, })), }; - }, [title, categories, seriesData]); + }, [title, subtitle, experimentData.shot_channels, channelNames]); const empty = !option; From 78cf343b908978a6ea24053731f1ffeff772aa59 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Wed, 20 May 2026 21:06:05 +0200 Subject: [PATCH 41/46] =?UTF-8?q?perf:=20eliminate=20O(N=C2=B2)=20accumula?= =?UTF-8?q?tion=20as=20live=20data=20grows?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Two separate O(N * data_points) operations ran on every incoming data point, causing the browser to freeze progressively: 1. HistogramPlot searched for the latest shot array by iterating all accumulated data-point keys on every update. Track latestShotData (Record) in useExperimentData instead and pass it directly to HistogramPlot, making the histogram O(N_shots) regardless of how many points have been collected. 2. autoYBounds in JobView iterated every result-channel value on every update (unbounded scan). Track resultBounds incrementally in the hook so the windowSize=null case is O(1) per update; the windowed case scans only the last windowSize points (bounded). Also replace O(N) Object.values(firstChannel).length with total_data_points for the dataLength lookup. Co-Authored-By: Claude Sonnet 4.6 --- frontend/src/components/JobView.tsx | 24 ++++------- .../src/components/jobView/HistogramPlot.tsx | 16 +++---- frontend/src/hooks/useExperimentData.tsx | 42 ++++++++++++++++++- 3 files changed, 56 insertions(+), 26 deletions(-) diff --git a/frontend/src/components/JobView.tsx b/frontend/src/components/JobView.tsx index 3b3eb7e1..6d084e11 100644 --- a/frontend/src/components/JobView.tsx +++ b/frontend/src/components/JobView.tsx @@ -49,7 +49,7 @@ export const JobView = ({ const jobInfo = useJobInfo(jobId); const jobRunInfo = useJobRunInfo(jobId); - const { experimentData, experimentDataError, loading } = useExperimentData(jobId); + const { experimentData, experimentDataError, loading, latestShotData, resultBounds } = useExperimentData(jobId); const is1D = jobInfo?.scan_parameters.length === 1; const is2D = (jobInfo?.scan_parameters.length ?? 0) >= 2; @@ -58,16 +58,15 @@ export const JobView = ({ const [yMax, setYMax] = useState(null); const autoYBounds = useMemo(() => { + if (windowSize === null) { + if (!Number.isFinite(resultBounds.min)) return { min: 0, max: 0 }; + return resultBounds; + } if (!experimentData?.result_channels) return { min: 0, max: 0 }; - let min = Infinity; let max = -Infinity; - for (const channelData of Object.values(experimentData.result_channels)) { - let values = Object.values(channelData) as number[]; - if (windowSize != null && values.length > windowSize) { - values = values.slice(-windowSize); - } + const values = (Object.values(channelData) as number[]).slice(-windowSize); for (const v of values) { if (Number.isFinite(v)) { if (v < min) min = v; @@ -75,16 +74,11 @@ export const JobView = ({ } } } - if (!Number.isFinite(min)) return { min: 0, max: 0 }; return { min, max }; - }, [experimentData, windowSize]); + }, [experimentData.result_channels, windowSize, resultBounds]); - const dataLength = useMemo(() => { - if (!experimentData?.result_channels) return 0; - const firstChannel = Object.values(experimentData.result_channels)[0]; - return firstChannel ? Object.values(firstChannel).length : 0; - }, [experimentData]); + const dataLength = experimentData.total_data_points; const loadedDataPoints = Object.keys( Object.values(experimentData.result_channels)[0] ?? {}, @@ -399,7 +393,7 @@ export const JobView = ({
{expandedShotChannels[win.name] !== false && ( ; channelNames: string[]; title: string; subtitle: string; @@ -15,7 +14,7 @@ interface HistogramPlotProps { } export const HistogramPlot = ({ - experimentData, + latestShotData, title, subtitle, loading, @@ -25,14 +24,11 @@ export const HistogramPlot = ({ const notifications = useNotifications(); const option = useMemo(() => { - const sc = experimentData?.shot_channels ?? {}; const latestPerChannel: Record = {}; - for (const [channelName, groups] of Object.entries(sc)) { - if (!groups || !channelNames.includes(channelName)) continue; - const keys = Object.keys(groups).map(Number); - const latestKey = String(Math.max(...keys)); - latestPerChannel[channelName] = groups[latestKey]; + for (const [channelName, arr] of Object.entries(latestShotData)) { + if (!arr || !channelNames.includes(channelName)) continue; + latestPerChannel[channelName] = arr; } const allArrays = Object.values(latestPerChannel); @@ -120,7 +116,7 @@ export const HistogramPlot = ({ large: true, })), }; - }, [title, subtitle, experimentData.shot_channels, channelNames]); + }, [title, subtitle, latestShotData, channelNames]); const empty = !option; diff --git a/frontend/src/hooks/useExperimentData.tsx b/frontend/src/hooks/useExperimentData.tsx index c7354a01..7547dc7b 100644 --- a/frontend/src/hooks/useExperimentData.tsx +++ b/frontend/src/hooks/useExperimentData.tsx @@ -41,11 +41,15 @@ export function useExperimentData(jobId: string | undefined) { useState(emptyExperimentData); const [experimentDataError, setError] = useState(null); const [loading, setLoading] = useState(true); + const [latestShotData, setLatestShotData] = useState>({}); + const [resultBounds, setResultBounds] = useState({ min: Infinity, max: -Infinity }); useEffect(() => { setLoading(true); setError(null); setExperimentData(emptyExperimentData); + setLatestShotData({}); + setResultBounds({ min: Infinity, max: -Infinity }); if (!jobId) return; const dataPointEvent = `experiment_${jobId}`; @@ -90,6 +94,19 @@ export function useExperimentData(jobId: string | undefined) { total_data_points: prev.total_data_points + 1, }; }); + if (Object.keys(data.shot_channels).length > 0) { + setLatestShotData((prev) => ({ ...prev, ...data.shot_channels })); + } + setResultBounds((prev) => { + let { min, max } = prev; + for (const value of Object.values(data.result_channels)) { + if (Number.isFinite(value)) { + if (value < min) min = value as number; + if (value > max) max = value as number; + } + } + return min === prev.min && max === prev.max ? prev : { min, max }; + }); }; const metadataEvent = `experiment_${jobId}_metadata`; @@ -140,6 +157,29 @@ export function useExperimentData(jobId: string | undefined) { console.info("Failed to fetch job run:", deserialized); setError(deserialized); } else { + const latestShots: Record = {}; + for (const [channel, groups] of Object.entries(deserialized.shot_channels)) { + let latestIdx = -1; + let latestArr: number[] | undefined; + for (const [k, v] of Object.entries(groups)) { + const n = parseInt(k, 10); + if (n > latestIdx) { latestIdx = n; latestArr = v as number[]; } + } + if (latestArr !== undefined) latestShots[channel] = latestArr; + } + setLatestShotData(latestShots); + + let min = Infinity, max = -Infinity; + for (const channelData of Object.values(deserialized.result_channels)) { + for (const v of Object.values(channelData) as number[]) { + if (Number.isFinite(v)) { + if (v < min) min = v; + if (v > max) max = v; + } + } + } + setResultBounds({ min: Number.isFinite(min) ? min : 0, max: Number.isFinite(max) ? max : 0 }); + setExperimentData(deserialized); } setLoading(false); @@ -153,5 +193,5 @@ export function useExperimentData(jobId: string | undefined) { }; }, [jobId]); - return { experimentData, experimentDataError, loading }; + return { experimentData, experimentDataError, loading, latestShotData, resultBounds }; } From 177d55a199f0c5f5a21ddd3a1d013a59c4d5b92e Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 26 May 2026 12:00:47 +0200 Subject: [PATCH 42/46] Sort 1D scan data by parameter value for live display Points in a centred scan arrive in centre-out order. ECharts draws lines connecting data points in array order, causing zigzag artefacts. Sort fullDataSet (and per-repetition repData) by x-value after building them in buildResultChannelChartSeries, and apply the same sort in the windowed live-display path in ResultChannelPlot. As a side-effect this also makes the lttb downsampling algorithm work correctly, since it assumes x-ordered data. Co-Authored-By: Claude Sonnet 4.6 --- frontend/src/components/ResultChannelPlot.tsx | 7 ++- .../utils/buildResultChannelChartSeries.ts | 48 ++++++++++--------- 2 files changed, 29 insertions(+), 26 deletions(-) diff --git a/frontend/src/components/ResultChannelPlot.tsx b/frontend/src/components/ResultChannelPlot.tsx index 7b2e783c..74010a86 100644 --- a/frontend/src/components/ResultChannelPlot.tsx +++ b/frontend/src/components/ResultChannelPlot.tsx @@ -222,10 +222,9 @@ const ResultChannelPlot = ({ xAxisData = observedX; - const fullDataSet = observedX.map((xVal, index) => [ - xVal, - ...channels.map((ch) => ch.data[index]), - ]); + const fullDataSet = observedX + .map((xVal, index) => [xVal, ...channels.map((ch) => ch.data[index])]) + .sort((a, b) => (a[0] as number) - (b[0] as number)); chartSeries = channels.map((channel, index) => ({ name: channel.name, diff --git a/frontend/src/utils/buildResultChannelChartSeries.ts b/frontend/src/utils/buildResultChannelChartSeries.ts index de2eaea0..bfcf2ab5 100644 --- a/frontend/src/utils/buildResultChannelChartSeries.ts +++ b/frontend/src/utils/buildResultChannelChartSeries.ts @@ -31,22 +31,24 @@ export function buildResultChannelChartSeries( const getVal = (ch: Channel, rep: number, i: number): number => Number.isFinite(ch.data[rep * xLen + i]) ? ch.data[rep * xLen + i] : Number.NaN; - // merged data - const fullDataSet: number[][] = xAxisData.map((x, i) => { - const ys = resultChannels.map((ch) => { - let sum = 0, - cnt = 0; - for (let r = 0; r < repetitions; r++) { - const v = getVal(ch, r, i); - if (Number.isFinite(v)) { - sum += v; - cnt++; + // merged data — sorted by x so lines connect points in scan-parameter order + const fullDataSet: number[][] = xAxisData + .map((x, i) => { + const ys = resultChannels.map((ch) => { + let sum = 0, + cnt = 0; + for (let r = 0; r < repetitions; r++) { + const v = getVal(ch, r, i); + if (Number.isFinite(v)) { + sum += v; + cnt++; + } } - } - return cnt ? sum / cnt : Number.NaN; - }); - return [x, ...ys]; - }); + return cnt ? sum / cnt : Number.NaN; + }); + return [x, ...ys]; + }) + .sort((a, b) => a[0] - b[0]); // merged series const chartSeries: EChartsOption["series"] = resultChannels.map((ch, chIdx) => ({ @@ -62,13 +64,15 @@ export function buildResultChannelChartSeries( if (showRepetitions && repetitions > 1) { for (let r = 0; r < repetitions; r++) { - const repData: number[][] = xAxisData.map((x, i) => { - const ys = resultChannels.map((ch) => { - const v = getVal(ch, r, i); - return Number.isFinite(v) ? v : Number.NaN; - }); - return [x, ...ys]; - }); + const repData: number[][] = xAxisData + .map((x, i) => { + const ys = resultChannels.map((ch) => { + const v = getVal(ch, r, i); + return Number.isFinite(v) ? v : Number.NaN; + }); + return [x, ...ys]; + }) + .sort((a, b) => a[0] - b[0]); for (let chIdx = 0; chIdx < resultChannels.length; chIdx++) { chartSeries.push({ From f331deeb12573b7880b2c7ea9a7b64b221d60e88 Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 26 May 2026 15:11:49 +0200 Subject: [PATCH 43/46] add color bar properly displayed, and with bounds updated in real time so as to have always the max contrast for 2D scans --- frontend/src/components/ResultChannelPlot.tsx | 71 ++++++++++++++++--- 1 file changed, 62 insertions(+), 9 deletions(-) diff --git a/frontend/src/components/ResultChannelPlot.tsx b/frontend/src/components/ResultChannelPlot.tsx index 74010a86..86aef9f7 100644 --- a/frontend/src/components/ResultChannelPlot.tsx +++ b/frontend/src/components/ResultChannelPlot.tsx @@ -297,6 +297,23 @@ const ResultChannelPlot = ({ }); } + // Determine which channel is currently displayed and compute its data range so + // the color bar always reflects the actual values without a post-render fixup. + const activeChannelName = selectedChannel ?? resultChannels[0]?.name; + const activeChannel = + resultChannels.find((rc) => rc.name === activeChannelName) ?? resultChannels[0]; + const finiteValues = (activeChannel?.data ?? []).filter((v) => Number.isFinite(v)); + const vmMin = finiteValues.length ? Math.min(...finiteValues) : 0; + const vmMax = + finiteValues.length && Math.max(...finiteValues) !== vmMin + ? Math.max(...finiteValues) + : vmMin + 1; // guard against a flat / empty dataset + + // Preserve the legend selection across setOption({ notMerge: true }) calls. + const legendSelected = Object.fromEntries( + resultChannels.map((rc) => [rc.name, rc.name === activeChannelName]), + ); + const categoryAxisProps = { axisLabel: { formatter: formatAxisLabel }, }; @@ -305,12 +322,13 @@ const ResultChannelPlot = ({ title, legend: { selectedMode: "single", - left: "right", top: 40, + left: "center", + selected: legendSelected, }, grid: { left: 30, - right: 40, + right: 160, bottom: 20, top: 70, containLabel: true, @@ -335,11 +353,19 @@ const ResultChannelPlot = ({ : categoryAxisProps), }, series, - visualMap: { - left: "right", - bottom: 30, - inRange: { color: ["#313695", "#1483d5", "#73bf7f", "#fcbe3d", "#ffff00"] }, - }, + visualMap: [ + { + type: "continuous", + show: true, + calculable: true, + orient: "vertical", + right: 10, + top: "center", + min: vmMin, + max: vmMax, + inRange: { color: ["#313695", "#1483d5", "#73bf7f", "#fcbe3d", "#ffff00"] }, + }, + ], }; } @@ -365,6 +391,28 @@ const ResultChannelPlot = ({ } } + // Add fit curve overlays for 1D scans + if (scanParameters.length === 1 && fits) { + for (const [channelName, fitResult] of Object.entries(fits)) { + if (!fitResult.success || !fitResult.fit_curve) continue; + if (!channelNames.includes(channelName)) continue; + + const fitData = fitResult.fit_curve.x.map((x, i) => [ + x, + fitResult.fit_curve!.y[i], + ]); + + (chartSeries as unknown[]).push({ + name: `${channelName} fit`, + type: "line", + data: fitData, + showSymbol: false, + lineStyle: { type: "dashed", width: 2 }, + tooltip: { show: false }, + }); + } + } + return { title, textStyle: { fontFamily: "sans-serif", fontSize: 12 }, @@ -408,6 +456,7 @@ const ResultChannelPlot = ({ yRange, fits, channelNames, + selectedChannel, ]); const updateChart = useCallback( @@ -435,12 +484,16 @@ const ResultChannelPlot = ({ }; }, [chart, onChartClick]); - useEffect(() => { + useEffect(() => { if (!is2D || !chart) return; updateVisualMap(chart, selectedChannel); }, [option, chart]); + + // When the user picks a different channel in the legend, update selectedChannel so + // the useMemo recomputes the option (including the correct visualMap range) for the + // newly active channel. useEffect(() => { if (!is2D || !chart) return; @@ -453,7 +506,7 @@ const ResultChannelPlot = ({ return () => { chart.off("legendselectchanged"); }; - }, [chart]); + }, [chart, is2D]); return ( <> From f6ddf5bb884da97207bc869669e10cba702c4b61 Mon Sep 17 00:00:00 2001 From: Antti Luomi Date: Mon, 1 Jun 2026 12:20:50 +0000 Subject: [PATCH 44/46] Prevent histogram from freezing the browser on large/long shot channels --- .../src/components/jobView/HistogramPlot.tsx | 22 ++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) diff --git a/frontend/src/components/jobView/HistogramPlot.tsx b/frontend/src/components/jobView/HistogramPlot.tsx index 3313210a..58f0048e 100644 --- a/frontend/src/components/jobView/HistogramPlot.tsx +++ b/frontend/src/components/jobView/HistogramPlot.tsx @@ -34,16 +34,28 @@ export const HistogramPlot = ({ const allArrays = Object.values(latestPerChannel); if (allArrays.length === 0) return undefined; - const globalMax = Math.max( - ...allArrays.map((a) => Math.max(...a.filter((v) => !Number.isNaN(v)))) - ); - const rangeMax = Math.max(80, globalMax); + // Hard cap on histogram bins + const MAX_BINS = 4096; + + // Largest finite value across displayed channels + let observedMax = 0; + for (const arr of allArrays) { + for (const v of arr) { + if (Number.isFinite(v) && v > observedMax) observedMax = v; + } + } + + const rangeMax = Math.min(Math.max(80, Math.ceil(observedMax)), MAX_BINS); const categories = Array.from({ length: rangeMax + 1 }, (_, i) => String(i)); const seriesData = Object.entries(latestPerChannel).map(([name, arr]) => { const counts = new Array(rangeMax + 1).fill(0); for (const v of arr) { - if (!Number.isNaN(v)) counts[v]++; + if (!Number.isFinite(v)) continue; + // Clamp into [0, rangeMax] so an out-of-range shot still gets counted + // (in the edge bin) instead of indexing past the array. + const bin = Math.min(Math.max(Math.floor(v), 0), rangeMax); + counts[bin]++; } return { name, data: counts }; }); From 8e90d0ed08fbe524cf2f51fee1f81334ce97d9ee Mon Sep 17 00:00:00 2001 From: Florence Berterottiere Date: Tue, 26 May 2026 16:07:18 +0200 Subject: [PATCH 45/46] added the option to scan either in start/stop mode, or with center/span mode, where the center value is the previously calibrated value and the span is provided by the user --- .../scanInterface/ParameterCard.tsx | 307 ++++++++++++++---- frontend/src/types/ScanParameterInfo.ts | 5 + 2 files changed, 241 insertions(+), 71 deletions(-) diff --git a/frontend/src/components/scanInterface/ParameterCard.tsx b/frontend/src/components/scanInterface/ParameterCard.tsx index c4c1d472..ade80242 100644 --- a/frontend/src/components/scanInterface/ParameterCard.tsx +++ b/frontend/src/components/scanInterface/ParameterCard.tsx @@ -6,8 +6,12 @@ import { MenuItem, Select, TextField, + ToggleButton, + ToggleButtonGroup, } from "@mui/material"; import { useContext, useMemo } from "react"; +import { useParameter } from "../../hooks/useParameter"; +import { ParameterStoreContext } from "../../contexts/ParameterStoreContext"; import { DeviceInfoContext } from "../../contexts/DeviceInfoContext"; import { ExperimentsContext } from "../../contexts/ExperimentsContext"; import { ParameterDisplayGroupsContext } from "../../contexts/ParameterDisplayGroupsContext"; @@ -17,6 +21,7 @@ import { experimentIdToNamespace, } from "../../utils/experimentUtils"; import { + ScanInputMode, ScanParameterInfo, ScanPattern, scanPatterns, @@ -89,6 +94,7 @@ export const ParameterCard = ({ ); const deviceInfo = useContext(DeviceInfoContext); const experiments = useContext(ExperimentsContext); + const parameterStore = useContext(ParameterStoreContext); // Create a mapping from namespace to experiment display name const namespaceToDisplayName: Record = Object.fromEntries( @@ -166,6 +172,51 @@ export const ParameterCard = ({ }, [param, parameterDisplayGroups, deviceInfo]); const pattern = param.generation.pattern ?? "linear"; + const inputMode: ScanInputMode = param.generation.inputMode ?? "startStop"; + + // Live value of the currently selected parameter — used to seed "Center" when + // switching to span/center mode. + const [currentParamValue] = useParameter(param.id); + const currentNumericValue = + typeof currentParamValue === "number" ? currentParamValue : null; + + // Derived quantities for span/center mode. + const center = (param.generation.start + param.generation.stop) / 2; + const span = param.generation.stop - param.generation.start; + + const handleInputModeChange = (_: React.MouseEvent, newMode: ScanInputMode | null) => { + if (!newMode || newMode === inputMode) return; + + if (newMode === "spanCenter") { + // Seed center from the live parameter value when available, otherwise keep the + // midpoint of the existing range. + const newCenter = + currentNumericValue !== null ? currentNumericValue : center; + const newSpan = Math.abs(span) || 1; // keep existing span (>0 guard) + const newStart = newCenter - newSpan / 2; + const newStop = newCenter + newSpan / 2; + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { + generation: { + ...param.generation, + inputMode: "spanCenter", + start: newStart, + stop: newStop, + }, + values: generateScanValues(newStart, newStop, param.generation.points, pattern), + }, + }); + } else { + // Switching back to start/stop: just flip the mode flag; start/stop are already correct. + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { generation: { ...param.generation, inputMode: "startStop" } }, + }); + } + }; return (
@@ -272,11 +323,37 @@ export const ParameterCard = ({ value={param.id} title={param.id} onChange={(e) => { - dispatchScanInfoStateUpdate({ - type: "UPDATE_PARAMETER", - index, - payload: { id: e.target.value }, - }); + const newParamId = e.target.value; + + if (inputMode === "spanCenter") { + // Re-centre on the new parameter's live value (if numeric); keep the span. + const rawValue = parameterStore?.get(newParamId); + const newCenter = + typeof rawValue === "number" ? rawValue : center; + const currentSpan = Math.abs(span) || 1; + const newStart = newCenter - currentSpan / 2; + const newStop = newCenter + currentSpan / 2; + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { + id: newParamId, + generation: { ...param.generation, start: newStart, stop: newStop }, + values: generateScanValues( + newStart, + newStop, + param.generation.points, + pattern, + ), + }, + }); + } else { + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { id: newParamId }, + }); + } }} renderValue={(value) => { if (Object.keys(parameterOptions).length === 0) { @@ -302,76 +379,164 @@ export const ParameterCard = ({
- - dispatchScanInfoStateUpdate({ - type: "UPDATE_PARAMETER", - index, - payload: { - generation: { - ...param.generation, - start: Number(e.target.value), + onChange={handleInputModeChange} + > + + Start / Stop + + + Center / Span + + + + {inputMode === "spanCenter" ? ( + <> + { + const newCenter = Number(e.target.value); + const newStart = newCenter - span / 2; + const newStop = newCenter + span / 2; + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { + generation: { ...param.generation, start: newStart, stop: newStop }, + values: generateScanValues( + newStart, + newStop, + param.generation.points, + pattern, + ), + }, + }); + }} + variant="outlined" + slotProps={{ + input: { + inputProps: { + min: parameterOptions[param.id]?.min, + max: parameterOptions[param.id]?.max, + }, }, - values: generateScanValues( - Number(e.target.value), - param.generation.stop, - param.generation.points, - pattern, - ), - }, - }) - } - variant="outlined" - slotProps={{ - input: { - inputProps: { - min: parameterOptions[param.id]?.min, - max: parameterOptions[param.id]?.max, - }, - }, - }} - /> - - dispatchScanInfoStateUpdate({ - type: "UPDATE_PARAMETER", - index, - payload: { - generation: { - ...param.generation, - stop: Number(e.target.value), + }} + /> + { + const newSpan = Math.abs(Number(e.target.value)); + const newStart = center - newSpan / 2; + const newStop = center + newSpan / 2; + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { + generation: { ...param.generation, start: newStart, stop: newStop }, + values: generateScanValues( + newStart, + newStop, + param.generation.points, + pattern, + ), + }, + }); + }} + variant="outlined" + slotProps={{ + input: { inputProps: { min: 0 } }, + }} + /> + + ) : ( + <> + + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { + generation: { + ...param.generation, + start: Number(e.target.value), + }, + values: generateScanValues( + Number(e.target.value), + param.generation.stop, + param.generation.points, + pattern, + ), + }, + }) + } + variant="outlined" + slotProps={{ + input: { + inputProps: { + min: parameterOptions[param.id]?.min, + max: parameterOptions[param.id]?.max, + }, }, - values: generateScanValues( - param.generation.start, - Number(e.target.value), - param.generation.points, - pattern, - ), - }, - }) - } - variant="outlined" - slotProps={{ - input: { - inputProps: { - min: parameterOptions[param.id]?.min, - max: parameterOptions[param.id]?.max, - }, - }, - }} - /> + }} + /> + + dispatchScanInfoStateUpdate({ + type: "UPDATE_PARAMETER", + index, + payload: { + generation: { + ...param.generation, + stop: Number(e.target.value), + }, + values: generateScanValues( + param.generation.start, + Number(e.target.value), + param.generation.points, + pattern, + ), + }, + }) + } + variant="outlined" + slotProps={{ + input: { + inputProps: { + min: parameterOptions[param.id]?.min, + max: parameterOptions[param.id]?.max, + }, + }, + }} + /> + + )} + Date: Sun, 7 Jun 2026 09:00:47 +0200 Subject: [PATCH 46/46] feat: add configurable hardware connection timeout Adds a `timeout` field to `HardwareConfig` (default 5 s) and threads it through to the hardware controller connection, preventing indefinite hangs when the instrument is unreachable. Also silences the pycrystal library logger to ERROR to reduce noise. Co-Authored-By: Claude Sonnet 4.6 --- src/icon/config/v1.py | 1 + .../pycrystal_experiment_library_client.py | 2 +- .../server/frontend/assets/index-C2XDlQRV.js | 45 + .../server/frontend/assets/index-hJ7hriKR.js | 45 - .../server/frontend/assets/mui-Ku81UjCE.js | 178 + .../server/frontend/assets/mui-bAivgoRt.js | 178 - src/icon/server/frontend/index.html | 4 +- .../hardware_controller.py | 4 +- uv.lock | 3325 ++++++++++------- 9 files changed, 2121 insertions(+), 1661 deletions(-) create mode 100644 src/icon/server/frontend/assets/index-C2XDlQRV.js delete mode 100644 src/icon/server/frontend/assets/index-hJ7hriKR.js create mode 100644 src/icon/server/frontend/assets/mui-Ku81UjCE.js delete mode 100644 src/icon/server/frontend/assets/mui-bAivgoRt.js diff --git a/src/icon/config/v1.py b/src/icon/config/v1.py index 603e7061..d240b655 100644 --- a/src/icon/config/v1.py +++ b/src/icon/config/v1.py @@ -59,6 +59,7 @@ class HardwareConfig(BaseModel): host: str = "localhost" port: int = 6007 n_ttl_channels: int = 32 + timeout: int = 5 class ServiceConfigV1(BaseConfig): # type: ignore[misc] diff --git a/src/icon/server/data_access/pycrystal_experiment_library_client.py b/src/icon/server/data_access/pycrystal_experiment_library_client.py index a4709616..237b82b2 100644 --- a/src/icon/server/data_access/pycrystal_experiment_library_client.py +++ b/src/icon/server/data_access/pycrystal_experiment_library_client.py @@ -36,7 +36,7 @@ logger = logging.getLogger("experiment_library") logging.getLogger("pycrystal").setLevel(logging.ERROR) logging.getLogger("ionpulse_sequence_generator").setLevel(logging.ERROR) -LOG_LEVEL = logging.INFO +LOG_LEVEL = logging.ERROR class AsyncPyCrystalClient(VEnvExperimentLibraryClient): diff --git a/src/icon/server/frontend/assets/index-C2XDlQRV.js b/src/icon/server/frontend/assets/index-C2XDlQRV.js new file mode 100644 index 00000000..c95e10cc --- /dev/null +++ b/src/icon/server/frontend/assets/index-C2XDlQRV.js @@ -0,0 +1,45 @@ +import{r as mb,a as 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Pl(t,e.child,null,n),e=oc(t,t.pendingProps.children),e.flags|=2,t.memoizedState=null,e}function Om(e,t,n){e.lanes|=t;var i=e.alternate;i!==null&&(i.lanes|=t),Tu(e.return,t,n)}function cc(e,t,n,i,o){var c=e.memoizedState;c===null?e.memoizedState={isBackwards:t,rendering:null,renderingStartTime:0,last:i,tail:n,tailMode:o}:(c.isBackwards=t,c.rendering=null,c.renderingStartTime=0,c.last=i,c.tail=n,c.tailMode=o)}function Nm(e,t,n){var i=t.pendingProps,o=i.revealOrder,c=i.tail;if(jt(e,t,i.children,n),i=bt.current,(i&2)!==0)i=i&1|2,t.flags|=128;else{if(e!==null&&(e.flags&128)!==0)e:for(e=t.child;e!==null;){if(e.tag===13)e.memoizedState!==null&&Om(e,n,t);else if(e.tag===19)Om(e,n,t);else if(e.child!==null){e.child.return=e,e=e.child;continue}if(e===t)break e;for(;e.sibling===null;){if(e.return===null||e.return===t)break 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fc(e,t){return(e.lanes&t)!==0?!0:(e=e.dependencies,!!(e!==null&&ms(e)))}function m1(e,t,n){switch(t.tag){case 3:We(t,t.stateNode.containerInfo),da(t,gt,e.memoizedState.cache),Oi();break;case 27:case 5:dt(t);break;case 4:We(t,t.stateNode.containerInfo);break;case 10:da(t,t.type,t.memoizedProps.value);break;case 13:var i=t.memoizedState;if(i!==null)return i.dehydrated!==null?(ya(t),t.flags|=128,null):(n&t.child.childLanes)!==0?Mm(e,t,n):(ya(t),e=Jn(e,t,n),e!==null?e.sibling:null);ya(t);break;case 19:var o=(e.flags&128)!==0;if(i=(n&t.childLanes)!==0,i||(zi(e,t,n,!1),i=(n&t.childLanes)!==0),o){if(i)return Nm(e,t,n);t.flags|=128}if(o=t.memoizedState,o!==null&&(o.rendering=null,o.tail=null,o.lastEffect=null),oe(bt,bt.current),i)break;return null;case 22:case 23:return t.lanes=0,jm(e,t,n);case 24:da(t,gt,e.memoizedState.cache)}return Jn(e,t,n)}function zm(e,t,n){if(e!==null)if(e.memoizedProps!==t.pendingProps)xt=!0;else{if(!fc(e,n)&&(t.flags&128)===0)return xt=!1,m1(e,t,n);xt=(e.flags&131072)!==0}else xt=!1,He&&(t.flags&1048576)!==0&&ch(t,hs,t.index);switch(t.lanes=0,t.tag){case 16:e:{e=t.pendingProps;var i=t.elementType,o=i._init;if(i=o(i._payload),t.type=i,typeof i=="function")xu(i)?(e=cl(i,e),t.tag=1,t=Rm(null,t,i,e,n)):(t.tag=0,t=lc(null,t,i,e,n));else{if(i!=null){if(o=i.$$typeof,o===Y){t.tag=11,t=Cm(null,t,i,e,n);break e}else if(o===M){t.tag=14,t=_m(null,t,i,e,n);break e}}throw t=W(i)||i,Error(s(306,t,""))}}return t;case 0:return lc(e,t,t.type,t.pendingProps,n);case 1:return i=t.type,o=cl(i,t.pendingProps),Rm(e,t,i,o,n);case 3:e:{if(We(t,t.stateNode.containerInfo),e===null)throw Error(s(387));i=t.pendingProps;var c=t.memoizedState;o=c.element,zu(e,t),qi(t,i,null,n);var v=t.memoizedState;if(i=v.cache,da(t,gt,i),i!==c.cache&&Du(t,[gt],n,!0),ki(),i=v.element,c.isDehydrated)if(c={element:i,isDehydrated:!1,cache:v.cache},t.updateQueue.baseState=c,t.memoizedState=c,t.flags&256){t=Am(e,t,i,n);break e}else 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e===null&&He&&((o=i=lt)&&(i=Y1(i,t.type,t.pendingProps,Rn),i!==null?(t.stateNode=i,Nt=t,lt=Cn(i.firstChild),Rn=!1,o=!0):o=!1),o||il(t)),dt(t),o=t.type,c=t.pendingProps,v=e!==null?e.memoizedProps:null,i=c.children,qc(o,c)?i=null:v!==null&&qc(o,v)&&(t.flags|=32),t.memoizedState!==null&&(o=ku(e,t,r1,null,null,n),ur._currentValue=o),Ns(e,t),jt(e,t,i,n),t.child;case 6:return e===null&&He&&((e=n=lt)&&(n=G1(n,t.pendingProps,Rn),n!==null?(t.stateNode=n,Nt=t,lt=null,e=!0):e=!1),e||il(t)),null;case 13:return Mm(e,t,n);case 4:return We(t,t.stateNode.containerInfo),i=t.pendingProps,e===null?t.child=Pl(t,null,i,n):jt(e,t,i,n),t.child;case 11:return Cm(e,t,t.type,t.pendingProps,n);case 7:return jt(e,t,t.pendingProps,n),t.child;case 8:return jt(e,t,t.pendingProps.children,n),t.child;case 12:return jt(e,t,t.pendingProps.children,n),t.child;case 10:return i=t.pendingProps,da(t,t.type,i.value),jt(e,t,i.children,n),t.child;case 9:return o=t.type._context,i=t.pendingProps.children,sl(t),o=At(o),i=i(o),t.flags|=1,jt(e,t,i,n),t.child;case 14:return _m(e,t,t.type,t.pendingProps,n);case 15:return wm(e,t,t.type,t.pendingProps,n);case 19:return Nm(e,t,n);case 31:return i=t.pendingProps,n=t.mode,i={mode:i.mode,children:i.children},e===null?(n=zs(i,n),n.ref=t.ref,t.child=n,n.return=t,t=n):(n=Xn(e.child,i),n.ref=t.ref,t.child=n,n.return=t,t=n),t;case 22:return jm(e,t,n);case 24:return sl(t),i=At(gt),e===null?(o=Mu(),o===null&&(o=Fe,c=Ru(),o.pooledCache=c,c.refCount++,c!==null&&(o.pooledCacheLanes|=n),o=c),t.memoizedState={parent:i,cache:o},Nu(t),da(t,gt,o)):((e.lanes&n)!==0&&(zu(e,t),qi(t,null,null,n),ki()),o=e.memoizedState,c=t.memoizedState,o.parent!==i?(o={parent:i,cache:i},t.memoizedState=o,t.lanes===0&&(t.memoizedState=t.updateQueue.baseState=o),da(t,gt,i)):(i=c.cache,da(t,gt,i),i!==o.cache&&Du(t,[gt],n,!0))),jt(e,t,t.pendingProps.children,n),t.child;case 29:throw t.pendingProps}throw Error(s(156,t.tag))}function Wn(e){e.flags|=4}function Lm(e,t){if(t.type!=="stylesheet"||(t.state.loading&4)!==0)e.flags&=-16777217;else if(e.flags|=16777216,!Gp(t)){if(t=fn.current,t!==null&&((ze&4194048)===ze?An!==null:(ze&62914560)!==ze&&(ze&536870912)===0||t!==An))throw Hi=Ou,gh;e.flags|=8192}}function Ls(e,t){t!==null&&(e.flags|=4),e.flags&16384&&(t=e.tag!==22?Fr():536870912,e.lanes|=t,Kl|=t)}function Ki(e,t){if(!He)switch(e.tailMode){case"hidden":t=e.tail;for(var n=null;t!==null;)t.alternate!==null&&(n=t),t=t.sibling;n===null?e.tail=null:n.sibling=null;break;case"collapsed":n=e.tail;for(var i=null;n!==null;)n.alternate!==null&&(i=n),n=n.sibling;i===null?t||e.tail===null?e.tail=null:e.tail.sibling=null:i.sibling=null}}function nt(e){var t=e.alternate!==null&&e.alternate.child===e.child,n=0,i=0;if(t)for(var o=e.child;o!==null;)n|=o.lanes|o.childLanes,i|=o.subtreeFlags&65011712,i|=o.flags&65011712,o.return=e,o=o.sibling;else for(o=e.child;o!==null;)n|=o.lanes|o.childLanes,i|=o.subtreeFlags,i|=o.flags,o.return=e,o=o.sibling;return e.subtreeFlags|=i,e.childLanes=n,t}function p1(e,t,n){var i=t.pendingProps;switch(_u(t),t.tag){case 31:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return nt(t),null;case 1:return nt(t),null;case 3:return n=t.stateNode,i=null,e!==null&&(i=e.memoizedState.cache),t.memoizedState.cache!==i&&(t.flags|=2048),Fn(gt),Xt(),n.pendingContext&&(n.context=n.pendingContext,n.pendingContext=null),(e===null||e.child===null)&&(Mi(t)?Wn(t):e===null||e.memoizedState.isDehydrated&&(t.flags&256)===0||(t.flags|=1024,hh())),nt(t),null;case 26:return n=t.memoizedState,e===null?(Wn(t),n!==null?(nt(t),Lm(t,n)):(nt(t),t.flags&=-16777217)):n?n!==e.memoizedState?(Wn(t),nt(t),Lm(t,n)):(nt(t),t.flags&=-16777217):(e.memoizedProps!==i&&Wn(t),nt(t),t.flags&=-16777217),null;case 27:gn(t),n=Ke.current;var o=t.type;if(e!==null&&t.stateNode!=null)e.memoizedProps!==i&&Wn(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return nt(t),null}e=Le.current,Mi(t)?fh(t):(e=Lp(o,i,n),t.stateNode=e,Wn(t))}return nt(t),null;case 5:if(gn(t),n=t.type,e!==null&&t.stateNode!=null)e.memoizedProps!==i&&Wn(t);else{if(!i){if(t.stateNode===null)throw Error(s(166));return nt(t),null}if(e=Le.current,Mi(t))fh(t);else{switch(o=Ks(Ke.current),e){case 1:e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case 2:e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;default:switch(n){case"svg":e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case"math":e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;case"script":e=o.createElement("div"),e.innerHTML=" - + + diff --git a/src/icon/server/hardware_processing/hardware_controller.py b/src/icon/server/hardware_processing/hardware_controller.py index 1dd27739..e2a2b1de 100644 --- a/src/icon/server/hardware_processing/hardware_controller.py +++ b/src/icon/server/hardware_processing/hardware_controller.py @@ -28,7 +28,9 @@ def connect(self) -> None: self._port = get_config().hardware.port if HAS_TIQI_ZEDBOARD: self._zedboard = tiqi_zedboard.zedboard.Zedboard( - hostname=self._host, port=self._port + hostname=self._host, + port=self._port, + timeout=get_config().hardware.timeout, ) if not self.connected: logger.warning("Failed to connect to the Zedboard") diff --git a/uv.lock b/uv.lock index 47fefc8e..3e8558fb 100644 --- a/uv.lock +++ b/uv.lock @@ -2,8 +2,15 @@ version = 1 revision = 3 requires-python = ">=3.12" resolution-markers = [ - "python_full_version >= '3.14'", - "python_full_version < '3.14'", + "python_full_version >= '3.15' and sys_platform == 'win32'", + "python_full_version == '3.14.*' and sys_platform == 'win32'", + "python_full_version >= '3.15' and sys_platform == 'emscripten'", + "python_full_version == '3.14.*' and sys_platform == 'emscripten'", + "python_full_version >= '3.15' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version == '3.14.*' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version < '3.14' and sys_platform == 'win32'", + "python_full_version < '3.14' and sys_platform == 'emscripten'", + "python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'", ] [[package]] @@ -17,7 +24,7 @@ wheels = [ [[package]] name = "aiohttp" -version = "3.12.15" +version = "3.13.5" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "aiohappyeyeballs" }, @@ -28,42 +35,76 @@ dependencies = [ { name = "propcache" }, { name = "yarl" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/9b/e7/d92a237d8802ca88483906c388f7c201bbe96cd80a165ffd0ac2f6a8d59f/aiohttp-3.12.15.tar.gz", hash = "sha256:4fc61385e9c98d72fcdf47e6dd81833f47b2f77c114c29cd64a361be57a763a2", size = 7823716, upload-time = "2025-07-29T05:52:32.215Z" 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