[ESSREFLECTOMETRY] feat: freia choppers and more scaffolding #747
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "0", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# FREIA detector data\n", | ||
| "\n", | ||
| "Visualize detector images, arrival-time distributions, and wavelength spectra. Wavelengths are reconstructed using the WFM chopper settings." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "1", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%matplotlib widget\n", | ||
| "import plopp as pp\n", | ||
| "import scipp as sc\n", | ||
| "\n", | ||
| "from ess import freia\n", | ||
| "from ess.freia import data\n", | ||
| "from ess.reduce.nexus.types import DiskChoppers, Filename, RawDetector\n", | ||
| "from ess.reduce.unwrap import (\n", | ||
| " ChopperFrameSequence,\n", | ||
| " DistanceResolution,\n", | ||
| " PulsePeriod,\n", | ||
| " TimeResolution,\n", | ||
| " WavelengthDetector,\n", | ||
| ")\n", | ||
| "from ess.reduce.unwrap.types import KeepEventTimeOffset\n", | ||
| "from ess.reflectometry.types import SampleRun" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "2", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Select a run\n", | ||
| "\n", | ||
| "Download the example sample run and set the resolution used to reconstruct wavelengths. The file is cached locally by `pooch` (`pip install pooch`). To use your own data, replace the download function with a file path." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "3", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "freia_mcstas = freia.FreiaMcStasWorkflow(wavelength_from='analytical')\n", | ||
| "freia_mcstas[Filename[SampleRun]] = data.freia_mcstas_reference_run()\n", | ||
| "freia_mcstas[KeepEventTimeOffset] = True\n", | ||
| "freia_mcstas[TimeResolution] = sc.scalar(20.0, unit='us')\n", | ||
| "freia_mcstas[DistanceResolution] = sc.scalar(0.1, unit='m')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "4", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Inspect the WFM chopper cascade\n", | ||
| "\n", | ||
| "Inspect the chopper timing used to reconstruct wavelengths. For a non-WFM run, call `freia_mcstas.insert(freia.mcstas.non_wfm_choppers)` before computing wavelengths. Other configurations can be assigned to `freia_mcstas[DiskChoppers[SampleRun]]`." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "5", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "choppers = freia_mcstas.compute(DiskChoppers[SampleRun])\n", | ||
| "sc.DataGroup(choppers)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "6", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "frames = freia_mcstas.compute(ChopperFrameSequence[SampleRun])\n", | ||
| "frames.draw()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "7", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Load and unwrap the detector events\n", | ||
| "\n", | ||
| "Compute wavelengths from the event arrival times and chopper transmission bands." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "8", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "results = freia_mcstas.compute((RawDetector[SampleRun], WavelengthDetector[SampleRun]))\n", | ||
| "raw = results[RawDetector[SampleRun]]\n", | ||
| "unwrapped = results[WavelengthDetector[SampleRun]]\n", | ||
| "raw" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "9", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Detector image and arrival times\n", | ||
| "\n", | ||
| "The image uses `longitude` and `height` in the detector's local frame. Intensities are sums of event weights." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "10", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "detector_image = raw.hist(longitude=120, height=64, dim=raw.dims)\n", | ||
| "pp.plot(detector_image, norm='log', title='FREIA detector', vmin=1e-1)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "11", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "pulse_period = freia_mcstas.compute(PulsePeriod).to(unit='s').value\n", | ||
| "arrival_times = raw.hist(\n", | ||
| " event_time_offset=sc.linspace(\n", | ||
| " 'event_time_offset', 0.0, pulse_period, 501, unit='s'\n", | ||
| " ),\n", | ||
| " dim=raw.dims,\n", | ||
| ")\n", | ||
| "arrival_times.coords['event_time_offset'] = arrival_times.coords[\n", | ||
| " 'event_time_offset'\n", | ||
| "].to(unit='ms')\n", | ||
| "pp.plot(arrival_times, title='Arrival time within the source period')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "12", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Wavelengths from analytical frame unwrapping\n", | ||
| "\n", | ||
| "The chopper cascade and arrival times determine the wavelengths. Events outside the modeled transmission bands or above the workflow's relative wavelength uncertainty threshold have NaN wavelengths and do not contribute to the wavelength histograms. Inspect the assigned-event count when assessing the result." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "13", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "event_wavelengths = unwrapped.bins.constituents['data'].coords['wavelength']\n", | ||
|
Member
There was a problem hiding this comment. Can we do this differently than having to go via Can we instead do something like Histogramming into 1 bin should discard all the NaNs. |
||
| "valid = sc.isfinite(event_wavelengths)\n", | ||
| "print(f'{sc.sum(valid).value:,} / {valid.size:,} events have an assigned wavelength')\n", | ||
| "\n", | ||
| "wavelength_bins = sc.linspace('wavelength', 1.0, 12.0, 441, unit='angstrom')\n", | ||
| "spectrum = unwrapped.hist(wavelength=wavelength_bins, dim=unwrapped.dims)\n", | ||
| "pp.plot(spectrum, title='FREIA wavelength spectrum')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "14", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "wavelength_image = unwrapped.hist(\n", | ||
| " wavelength=wavelength_bins, longitude=120, dim=unwrapped.dims\n", | ||
| ")\n", | ||
| "pp.plot(wavelength_image, norm='log', title='Wavelength across the detector', vmin=1e0)" | ||
| ] | ||
| } | ||
| ], | ||
|
Member
There was a problem hiding this comment. Is it worth adding at the end of the notebook an inspector plot, where we histogram in |
||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3 (ipykernel)", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.12.13" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } | ||
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I'll upload these files to the pooch repo