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Merge pull request #124 from scipp/inelastic-sample
Add inelastic sample component that changes neutron wavelengths
2 parents f953256 + ce486d0 commit 99684b8

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‎docs/api-reference/index.md‎

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Chopper
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ChopperReading
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Component
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ComponentReading
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Dashboard
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Detector
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DetectorReading
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InelasticSample
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Model
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ReadingField
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Result
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Source
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SourceParameters
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SourceReading
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```
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## Top-level functions
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:template: module-template.rst
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:recursive:
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facilities
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utils
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```

‎docs/components.ipynb‎

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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import scipp as sc\n",
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"import plopp as pp\n",
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"import tof\n",
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"\n",
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"meter = sc.Unit('m')\n",
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"id": "33",
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"metadata": {},
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"source": [
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"## Loading from a JSON file\n",
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"## Inelastic sample\n",
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"\n",
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"Placing an `InelasticSample` in the instrument will change the energy of the incoming neutrons by a $\\Delta E$ defined in a function.\n",
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"That function takes in the incident energy and returns the final energy after the energy transfer took place.\n",
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"\n",
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"To give an equal chance for a random $\\Delta E$ between -0.2 and 0.2 meV, we can use Numpy's uniform random sampling:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "34",
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"metadata": {},
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"outputs": [],
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"source": [
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"rng = np.random.default_rng(seed=83)\n",
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"\n",
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"\n",
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"def uniform_deltae(e_i):\n",
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" # Uniform sampling between -0.2 and 0.2 meV\n",
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" de = sc.array(\n",
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" dims=e_i.dims, values=rng.uniform(-0.2, 0.2, size=e_i.shape), unit='meV'\n",
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" )\n",
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" return e_i.to(unit='meV', copy=False) - de\n",
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"\n",
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"\n",
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"sample = tof.InelasticSample(distance=28.0 * meter, name=\"sample\", func=uniform_deltae)\n",
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"sample"
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]
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},
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{
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"cell_type": "markdown",
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"id": "35",
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"metadata": {},
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"source": [
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"We then make a single fast-rotating chopper with one small opening,\n",
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"to select a narrow wavelength range at every rotation.\n",
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"\n",
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"We also add a monitor before the sample, and a detector after the sample so we can follow the changes in energies/wavelengths."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "36",
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"metadata": {},
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"outputs": [],
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"source": [
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"choppers = [\n",
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" tof.Chopper(\n",
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" frequency=70.0 * Hz,\n",
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" open=sc.array(dims=['cutout'], values=[0.0], unit='deg'),\n",
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" close=sc.array(dims=['cutout'], values=[1.0], unit='deg'),\n",
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" phase=0.0 * deg,\n",
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" distance=20.0 * meter,\n",
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" name=\"fastchopper\",\n",
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" ),\n",
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"]\n",
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"\n",
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"detectors = [\n",
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" tof.Detector(distance=26.0 * meter, name='monitor'),\n",
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" tof.Detector(distance=32.0 * meter, name='detector'),\n",
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"]\n",
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"\n",
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"source = tof.Source(facility='ess', neutrons=5_000_000)\n",
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"\n",
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"model = tof.Model(source=source, components=choppers + detectors + [sample])\n",
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"res = model.run()\n",
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"\n",
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"\n",
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"fig, ax = plt.subplots(1, 2, figsize=(12, 4.5))\n",
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"\n",
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"dw = sc.scalar(0.1, unit='angstrom')\n",
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"pp.plot(\n",
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" {\n",
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" 'monitor': res['monitor'].data.hist(wavelength=dw),\n",
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" 'detector': res['detector'].data.hist(wavelength=dw),\n",
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" },\n",
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" title=\"With inelastic sample\",\n",
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" xmin=4,\n",
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" xmax=20,\n",
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" ymin=-20,\n",
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" ymax=400,\n",
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" ax=ax[1],\n",
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")\n",
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"\n",
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"res.plot(visible_rays=10000, ax=ax[0])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "37",
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"metadata": {},
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"source": [
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"### Non-uniform energy-transfer distributions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "38",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Sample 1: double-peak at min and max\n",
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"def double_peak(e_i):\n",
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" # Either -0.2 or 0.2 meV\n",
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" de = sc.array(\n",
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" dims=e_i.dims, values=rng.choice([-0.2, 0.2], size=e_i.shape), unit='meV'\n",
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" )\n",
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" return e_i.to(unit='meV', copy=False) - de\n",
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"\n",
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"\n",
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"sample1 = tof.InelasticSample(\n",
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" distance=28.0 * meter,\n",
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" name=\"sample\",\n",
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" func=double_peak,\n",
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")\n",
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"\n",
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"\n",
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"# Sample 2: normal distribution\n",
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"def normal_deltae(e_i):\n",
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" de = sc.array(\n",
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" dims=e_i.dims, values=rng.normal(scale=0.05, size=e_i.shape), unit='meV'\n",
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" )\n",
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" return e_i.to(unit='meV', copy=False) - de\n",
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"\n",
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"\n",
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"sample2 = tof.InelasticSample(\n",
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" distance=28.0 * meter,\n",
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" name=\"sample\",\n",
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" func=normal_deltae,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "39",
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"metadata": {},
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"outputs": [],
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"source": [
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"model1 = tof.Model(source=source, components=choppers + detectors + [sample1])\n",
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"model2 = tof.Model(source=source, components=choppers + detectors + [sample2])\n",
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"\n",
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"res1 = model1.run()\n",
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"res2 = model2.run()\n",
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"\n",
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"fig, ax = plt.subplots(2, 2, figsize=(12, 9))\n",
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"\n",
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"res1.plot(visible_rays=10000, ax=ax[0, 0], title=\"Sample 1\")\n",
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"pp.plot(\n",
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" {\n",
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" 'monitor': res1['monitor'].data.hist(wavelength=dw),\n",
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" 'detector': res1['detector'].data.hist(wavelength=dw),\n",
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" },\n",
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" title=\"Sample 1\",\n",
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" xmin=4,\n",
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" xmax=20,\n",
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" ymin=-20,\n",
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" ymax=400,\n",
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" ax=ax[0, 1],\n",
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")\n",
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"\n",
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"res2.plot(visible_rays=10000, ax=ax[1, 0], title=\"Sample 2\")\n",
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"_ = pp.plot(\n",
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" {\n",
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" 'monitor': res2['monitor'].data.hist(wavelength=dw),\n",
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" 'detector': res2['detector'].data.hist(wavelength=dw),\n",
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" },\n",
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" title=\"Sample 2\",\n",
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" xmin=4,\n",
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" xmax=20,\n",
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" ymin=-20,\n",
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" ymax=400,\n",
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" ax=ax[1, 1],\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "40",
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"metadata": {},
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"source": [
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"## Loading components from a JSON file\n",
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"\n",
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"It is also possible to load components from a JSON file,\n",
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"which can be very useful to quickly load a pre-configured instrument.\n",
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{
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"cell_type": "code",
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"id": "41",
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"\n",
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"params = {\n",
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" \"source\": {\n",
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" \"type\": \"source\",\n",
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" \"facility\": \"ess\",\n",
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" \"neutrons\": 1e6,\n",
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" \"pulses\": 1\n",
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" },\n",
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" \"source\": {\"type\": \"source\", \"facility\": \"ess\", \"neutrons\": 1e6, \"pulses\": 1},\n",
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" \"chopper1\": {\n",
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" \"type\": \"chopper\",\n",
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" \"frequency\": {\"value\": 56.0, \"unit\": \"Hz\"},\n",
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{
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"cell_type": "code",
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},
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"metadata": {},
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"source": [
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"We now use the `tof.Model.from_json()` method to load our instrument:"
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{
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"cell_type": "code",
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"execution_count": null,
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},
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"cell_type": "markdown",
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"We can see that all components have been read in correctly.\n",
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{
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"cell_type": "code",
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"### Modifying the source\n",
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"cell_type": "markdown",
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"metadata": {},
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"## Saving to JSON\n",
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{
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"source": [

‎src/tof/__init__.py‎

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submodules=['facilities'],
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submod_attrs={
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'chopper': ['AntiClockwise', 'Chopper', 'ChopperReading', 'Clockwise'],
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'component': ['Component', 'ComponentReading', 'ReadingField'],
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'dashboard': ['Dashboard'],
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'detector': ['Detector', 'DetectorReading'],
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'inelastic': ['InelasticSample', 'InelasticSampleReading'],
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'model': ['Model'],
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'reading': ['ComponentReading', 'ReadingField'],
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'result': ['Result'],
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'source': ['Source', 'SourceParameters'],
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'source': ['Source', 'SourceReading'],
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},
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)
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