{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "0", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:04.619105Z", "iopub.status.busy": "2026-06-30T22:35:04.618887Z", "iopub.status.idle": "2026-06-30T22:35:04.623282Z", "shell.execute_reply": "2026-06-30T22:35:04.622349Z" }, "tags": [ "hide-in-docs" ] }, "outputs": [], "source": [ "# Check whether easydiffraction is installed; install it if needed.\n", "# Required for remote environments such as Google Colab.\n", "import importlib.util\n", "\n", "if importlib.util.find_spec('easydiffraction') is None:\n", " %pip install easydiffraction==0.19.1" ] }, { "cell_type": "markdown", "id": "1", "metadata": {}, "source": [ "# Taurine - single-crystal neutron TOF - basic\n", "\n", "Verifies calculated F2 values for a no-extinction neutron\n", "single-crystal time-of-flight baseline with isotropic ADPs.\n", "\n", "**Refinement:** the overall scale only; all other parameters are\n", "taken from the FullProf reference. Extinction is set to zero in the\n", "FullProf model so the comparison focuses on the structure-factor\n", "physics shared by cryspy and FullProf." ] }, { "cell_type": "code", "execution_count": 2, "id": "2", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:04.625143Z", "iopub.status.busy": "2026-06-30T22:35:04.624848Z", "iopub.status.idle": "2026-06-30T22:35:07.439387Z", "shell.execute_reply": "2026-06-30T22:35:07.438527Z" } }, "outputs": [], "source": [ "import easydiffraction as edi\n", "from easydiffraction import ExperimentFactory\n", "from easydiffraction import StructureFactory\n", "from easydiffraction.analysis import verification as verify" ] }, { "cell_type": "markdown", "id": "3", "metadata": {}, "source": [ "## Build the project" ] }, { "cell_type": "code", "execution_count": 3, "id": "4", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:07.441151Z", "iopub.status.busy": "2026-06-30T22:35:07.440843Z", "iopub.status.idle": "2026-06-30T22:35:07.652288Z", "shell.execute_reply": "2026-06-30T22:35:07.651383Z" } }, "outputs": [], "source": [ "project = edi.Project()" ] }, { "cell_type": "markdown", "id": "5", "metadata": {}, "source": [ "## Define the structure" ] }, { "cell_type": "code", "execution_count": 4, "id": "6", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:07.653929Z", "iopub.status.busy": "2026-06-30T22:35:07.653769Z", "iopub.status.idle": "2026-06-30T22:35:07.668230Z", "shell.execute_reply": "2026-06-30T22:35:07.667489Z" } }, "outputs": [], "source": [ "structure = StructureFactory.from_scratch(name='taurine')\n", "\n", "structure.space_group.name_h_m = 'P 21/c' # FullProf Space group symbol\n", "\n", "structure.cell.length_a = 5.272901 # FullProf a\n", "structure.cell.length_b = 11.656488 # FullProf b\n", "structure.cell.length_c = 7.838297 # FullProf c\n", "structure.cell.angle_beta = 94.010994 # FullProf beta\n", "\n", "# fmt: off\n", "_ATOMS = [\n", " ('S1', 'S', 0.19448, 0.35173, 0.34730, 1.37018),\n", " ('O1', 'O', 0.31207, 0.23951, 0.35143, 2.68011),\n", " ('O2', 'O', -0.05909, 0.33563, 0.29636, 3.50515),\n", " ('O3', 'O', 0.22105, 0.41215, 0.50573, 1.83513),\n", " ('N1', 'N', 0.26340, 0.62808, 0.33048, 2.07364),\n", " ('H1', 'H', 0.12861, 0.58669, 0.41769, 3.31527),\n", " ('H2', 'H', 0.18953, 0.71385, 0.31124, 4.46988),\n", " ('H3', 'H', 0.43970, 0.62023, 0.34592, 4.34151),\n", " ('C1', 'C', 0.34384, 0.44116, 0.20155, 1.73667),\n", " ('H11', 'H', 0.55246, 0.43345, 0.24304, 3.32279),\n", " ('H12', 'H', 0.32537, 0.38970, 0.08264, 3.05746),\n", " ('C2', 'C', 0.20029, 0.55716, 0.18272, 1.66017),\n", " ('H21', 'H', 0.27650, 0.60004, 0.07688, 2.15403),\n", " ('H22', 'H', -0.00383, 0.54767, 0.15762, 4.71303),\n", "]\n", "# fmt: on\n", "\n", "for _id, _type, _x, _y, _z, _biso in _ATOMS:\n", " structure.atom_sites.create(\n", " id=_id, # FullProf Atom\n", " type_symbol=_type, # FullProf Typ\n", " fract_x=_x, # FullProf X\n", " fract_y=_y, # FullProf Y\n", " fract_z=_z, # FullProf Z\n", " adp_type='Biso', # FullProf Biso\n", " adp_iso=_biso, # FullProf Biso\n", " )\n", "\n", "project.structures.add(structure)" ] }, { "cell_type": "code", "execution_count": 5, "id": "7", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:07.670194Z", "iopub.status.busy": "2026-06-30T22:35:07.670029Z", "iopub.status.idle": "2026-06-30T22:35:07.764028Z", "shell.execute_reply": "2026-06-30T22:35:07.763198Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mStructure ๐Ÿงฉ \u001b[0m\u001b[32m'taurine'\u001b[0m\u001b[1;36m as text\u001b[0m\n" ] }, { "data": { "text/html": [ "
Edi
1data_taurine
2
3_cell.length_a 5.272901
4_cell.length_b 11.656488
5_cell.length_c 7.838297
6_cell.angle_alpha 90.
7_cell.angle_beta 94.010994
8_cell.angle_gamma 90.
9
10_space_group.name_h_m "P 21/c"
11_space_group.coord_system_code b1
12
13_geom.min_bond_distance_cutoff 0.
14_geom.bond_distance_inc 0.25
15
16loop_
17_atom_site.id
18_atom_site.type_symbol
19_atom_site.fract_x
20_atom_site.fract_y
21_atom_site.fract_z
22_atom_site.wyckoff_letter
23_atom_site.multiplicity
24_atom_site.occupancy
25_atom_site.adp_iso
26_atom_site.adp_type
27S1 S 0.19448 0.35173 0.3473 e 4 1. 1.37018 Biso
28O1 O 0.31207 0.23951 0.35143 e 4 1. 2.68011 Biso
29O2 O -0.05909 0.33563 0.29636 e 4 1. 3.50515 Biso
30O3 O 0.22105 0.41215 0.50573 e 4 1. 1.83513 Biso
31N1 N 0.2634 0.62808 0.33048 e 4 1. 2.07364 Biso
32H1 H 0.12861 0.58669 0.41769 e 4 1. 3.31527 Biso
33H2 H 0.18953 0.71385 0.31124 e 4 1. 4.46988 Biso
34H3 H 0.4397 0.62023 0.34592 e 4 1. 4.34151 Biso
35C1 C 0.34384 0.44116 0.20155 e 4 1. 1.73667 Biso
36H11 H 0.55246 0.43345 0.24304 e 4 1. 3.32279 Biso
37H12 H 0.32537 0.3897 0.08264 e 4 1. 3.05746 Biso
38C2 C 0.20029 0.55716 0.18272 e 4 1. 1.66017 Biso
39H21 H 0.2765 0.60004 0.07688 e 4 1. 2.15403 Biso
40H22 H -0.00383 0.54767 0.15762 e 4 1. 4.71303 Biso
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "structure.show_as_text()" ] }, { "cell_type": "markdown", "id": "8", "metadata": {}, "source": [ "## Load the FullProf reference" ] }, { "cell_type": "code", "execution_count": 6, "id": "9", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:07.765918Z", "iopub.status.busy": "2026-06-30T22:35:07.765765Z", "iopub.status.idle": "2026-06-30T22:35:07.769910Z", "shell.execute_reply": "2026-06-30T22:35:07.769137Z" } }, "outputs": [], "source": [ "FULLPROF_PROJECT_DIR = 'sc-neut-tof_taurine_basic'\n", "FULLPROF_OUT_FILE = 'taurine.out'\n", "FULLPROF_SCALE = 2.711 # FullProf Scale\n", "\n", "f2calc = verify.load_fullprof_sc_f2calc(FULLPROF_PROJECT_DIR, FULLPROF_OUT_FILE)\n", "FULLPROF_LABEL = verify.fullprof_label(FULLPROF_PROJECT_DIR, FULLPROF_OUT_FILE)" ] }, { "cell_type": "markdown", "id": "10", "metadata": {}, "source": [ "## Create the experiment" ] }, { "cell_type": "code", "execution_count": 7, "id": "11", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:07.771541Z", "iopub.status.busy": "2026-06-30T22:35:07.771334Z", "iopub.status.idle": "2026-06-30T22:35:07.865666Z", "shell.execute_reply": "2026-06-30T22:35:07.865126Z" } }, "outputs": [], "source": [ "experiment = ExperimentFactory.from_scratch(\n", " name='taurine',\n", " sample_form='single crystal',\n", " beam_mode='time-of-flight',\n", " radiation_probe='neutron',\n", " scattering_type='bragg',\n", ")\n", "\n", "experiment.linked_structure.structure_id = 'taurine'\n", "experiment.linked_structure.scale = FULLPROF_SCALE\n", "\n", "verify.set_reference_reflections(experiment, f2calc)\n", "\n", "project.experiments.add(experiment)" ] }, { "cell_type": "markdown", "id": "12", "metadata": {}, "source": [ "## edi-cryspy VS FullProf" ] }, { "cell_type": "code", "execution_count": 8, "id": "13", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:07.868201Z", "iopub.status.busy": "2026-06-30T22:35:07.868013Z", "iopub.status.idle": "2026-06-30T22:35:08.141979Z", "shell.execute_reply": "2026-06-30T22:35:08.141327Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mCalculator for experiment \u001b[0m\u001b[32m'taurine'\u001b[0m\u001b[1;36m already set to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cryspy\n" ] }, { "data": { "text/html": [ "
Loading plotโ€ฆ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "calc_ed_cryspy = verify.calculate_reflections(project, experiment, 'cryspy')\n", "LABEL_ED_CRYSPY = verify.engine_label('cryspy')\n", "reference, candidate = verify.align_reflections(f2calc, calc_ed_cryspy)\n", "\n", "project.display.reflection_comparison(\n", " 'taurine',\n", " reference=reference,\n", " candidate=candidate,\n", " reference_label=FULLPROF_LABEL,\n", " candidate_label=LABEL_ED_CRYSPY,\n", ")" ] }, { "cell_type": "markdown", "id": "14", "metadata": {}, "source": [ "## Fit edi-cryspy to FullProf" ] }, { "cell_type": "code", "execution_count": 9, "id": "15", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:08.143659Z", "iopub.status.busy": "2026-06-30T22:35:08.143494Z", "iopub.status.idle": "2026-06-30T22:35:08.557479Z", "shell.execute_reply": "2026-06-30T22:35:08.556649Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mCalculator for experiment \u001b[0m\u001b[32m'taurine'\u001b[0m\u001b[1;36m already set to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cryspy\n" ] }, { "data": { "text/html": [], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "(function() {\n", " const button = document.getElementById('ed-fit-stop-015174c9a36a457c8ecd66a9ecc45d41-button');\n", " const status = document.getElementById('ed-fit-stop-015174c9a36a457c8ecd66a9ecc45d41-status');\n", " const kernelId = '';\n", " if (!button) {\n", " return;\n", " }\n", "\n", " function setStatus(text) {\n", " if (status) {\n", " status.textContent = text;\n", " }\n", " }\n", "\n", " function pageConfig() {\n", " const element = document.getElementById('jupyter-config-data');\n", " if (!element || !element.textContent) {\n", " return {};\n", " }\n", " try {\n", " return JSON.parse(element.textContent);\n", " } catch (error) {\n", " return {};\n", " }\n", " }\n", "\n", " function baseUrl(config) {\n", " const configured = config.baseUrl || config.base_url ||\n", " (window.Jupyter && Jupyter.notebook && Jupyter.notebook.base_url);\n", " if (configured) {\n", " return configured.endsWith('/') ? configured : configured + '/';\n", " }\n", " const markers = ['/lab/', '/notebooks/', '/tree/'];\n", " for (const marker of markers) {\n", " const index = window.location.pathname.indexOf(marker);\n", " if (index >= 0) {\n", " return window.location.pathname.slice(0, index + 1);\n", " }\n", " }\n", " return '/';\n", " }\n", "\n", " function token(config) {\n", " return config.token || new URLSearchParams(window.location.search).get('token') || '';\n", " }\n", "\n", " function cookie(name) {\n", " const prefix = name + '=';\n", " for (const part of document.cookie.split(';')) {\n", " const trimmed = part.trim();\n", " if (trimmed.startsWith(prefix)) {\n", " return decodeURIComponent(trimmed.slice(prefix.length));\n", " }\n", " }\n", " return '';\n", " }\n", "\n", " function notebookPath() {\n", " const decoded = decodeURIComponent(window.location.pathname);\n", " const markers = ['/lab/tree/', '/notebooks/', '/tree/'];\n", " for (const marker of markers) {\n", " const index = decoded.indexOf(marker);\n", " if (index >= 0) {\n", " return decoded.slice(index + marker.length);\n", " }\n", " }\n", " return '';\n", " }\n", "\n", " async function kernelFromSessions(config) {\n", " const url = new URL(baseUrl(config) + 'api/sessions', window.location.origin);\n", " const authToken = token(config);\n", " if (authToken) {\n", " url.searchParams.set('token', authToken);\n", " }\n", " const response = await fetch(url, {credentials: 'same-origin'});\n", " if (!response.ok) {\n", " return '';\n", " }\n", " const sessions = await response.json();\n", " const path = notebookPath();\n", " const session = sessions.find((item) => item.path === path) || sessions[0];\n", " return session && session.kernel ? session.kernel.id : '';\n", " }\n", "\n", " async function interruptKernel(config, resolvedKernelId) {\n", " const url = new URL(\n", " baseUrl(config) + 'api/kernels/' + resolvedKernelId + '/interrupt',\n", " window.location.origin\n", " );\n", " const authToken = token(config);\n", " if (authToken) {\n", " url.searchParams.set('token', authToken);\n", " }\n", " const xsrfToken = cookie('_xsrf');\n", " const headers = {};\n", " if (xsrfToken) {\n", " headers['X-XSRFToken'] = xsrfToken;\n", " }\n", " const response = await fetch(url, {\n", " method: 'POST',\n", " credentials: 'same-origin',\n", " headers: headers\n", " });\n", " return response.ok;\n", " }\n", "\n", " button.addEventListener('click', async function() {\n", " button.disabled = true;\n", " setStatus('Stopping...');\n", " const config = pageConfig();\n", " try {\n", " const resolvedKernelId = kernelId || await kernelFromSessions(config);\n", " if (!resolvedKernelId) {\n", " throw new Error('Could not resolve the current kernel id.');\n", " }\n", " const interrupted = await interruptKernel(config, resolvedKernelId);\n", " if (!interrupted) {\n", " throw new Error('Jupyter Server rejected the interrupt request.');\n", " }\n", " setStatus('Interrupt sent...');\n", " } catch (error) {\n", " button.disabled = false;\n", " setStatus('Use Kernel > Interrupt to stop this fit.');\n", " }\n", " });\n", "})();\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mStandard fitting\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "๐Ÿ“‹ Using experiment ๐Ÿ”ฌ \u001b[32m'taurine'\u001b[0m for \u001b[32m'single'\u001b[0m fitting\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "๐Ÿš€ Starting fit process with \u001b[32m'lmfit \u001b[0m\u001b[32m(\u001b[0m\u001b[32mleastsq\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m\u001b[33m...\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "๐Ÿ“ˆ Goodness-of-fit progress:\n" ] }, { "data": { "text/html": [ "
iterationtime (s)ฯ‡ยฒchange / status
110.01764.53
250.040.00100.0% โ†“
380.070.00
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "๐Ÿ† Best goodness-of-fit \u001b[1m(\u001b[0mreduced ฯ‡ยฒ\u001b[1m)\u001b[0m is \u001b[1;36m0.00\u001b[0m at iteration \u001b[1;36m5\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "โœ… Fitting complete.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "โš™๏ธ Settings used:\n" ] }, { "data": { "text/html": [ "
NameValueDescription
1max_iterations1000Maximum solver iterations.
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "๐Ÿ“‹ Least-squares fit results:\n" ] }, { "data": { "text/html": [ "
MetricValue
1๐Ÿงช Minimizerlmfit (leastsq)
2โœ… Overall statussuccess
3โฑ๏ธ Fitting time (seconds)0.07
4๐Ÿ” Iterations5
5๐Ÿ“ Goodness-of-fit (reduced ฯ‡ยฒ)0.00
6๐Ÿ“ R-factor (Rf, %)0.00
7๐Ÿ“ R-factor squared (Rfยฒ, %)0.00
8๐Ÿ“ Weighted R-factor (wR, %)0.00
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "๐Ÿ“ˆ Refined parameters:\n" ] }, { "data": { "text/html": [ "
datablockcategoryentryparameterunitsstartvalues.u.change
1taurinelinked_structurescale2.71101.35550.000050.00 % โ†“
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
โ€ข start = parameter value before refinement
โ€ข value = refined value from least-squares minimization
โ€ข s.u. = standard uncertainty (one sigma), from the covariance matrix
โ€ข change = relative change from start, in %; โ†‘ = increase, โ†“ = decrease
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mCalculator for experiment \u001b[0m\u001b[32m'taurine'\u001b[0m\u001b[1;36m already set to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cryspy\n" ] }, { "data": { "text/html": [ "
Loading plotโ€ฆ
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
MetricBeforeAfter
1Profile diff (%)100.000.00
2Max deviation (%)100.000.00
3Area ratio2.00001.0000
4Shape correlation1.00001.0000
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "experiment.calculator.type = 'cryspy'\n", "\n", "experiment.linked_structure.scale.free = True\n", "\n", "project.analysis.fit()\n", "project.display.fit.results()\n", "\n", "calc_ed_cryspy_refined = verify.calculate_reflections(project, experiment, 'cryspy')\n", "LABEL_ED_CRYSPY_REFINED = verify.engine_label('cryspy', note='scale only')\n", "reference_refined, candidate_refined = verify.align_reflections(f2calc, calc_ed_cryspy_refined)\n", "\n", "project.display.reflection_comparison(\n", " 'taurine',\n", " reference=reference_refined,\n", " candidate=candidate_refined,\n", " reference_label=FULLPROF_LABEL,\n", " candidate_label=LABEL_ED_CRYSPY_REFINED,\n", ")\n", "\n", "verify.report_refinement_closeness(\n", " reference,\n", " candidate,\n", " candidate_refined,\n", ")" ] }, { "cell_type": "markdown", "id": "16", "metadata": {}, "source": [ "## Agreement check" ] }, { "cell_type": "code", "execution_count": 10, "id": "17", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:35:08.559002Z", "iopub.status.busy": "2026-06-30T22:35:08.558841Z", "iopub.status.idle": "2026-06-30T22:35:08.566234Z", "shell.execute_reply": "2026-06-30T22:35:08.565394Z" } }, "outputs": [ { "data": { "text/html": [ "
ComparisonMetricExpectedActualOK
1edi 0.19.1 (cryspy 0.12.1, scale only) vs FullProf 8.40Profile diff (%)< 2.50.00โœ…
2Max deviation (%)< 60.00โœ…
3Area ratio0.99 to 1.011.0000โœ…
4Shape correlation> 0.9991.0000โœ…
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "True" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "verify.assert_patterns_agree([\n", " (f'{LABEL_ED_CRYSPY_REFINED} vs {FULLPROF_LABEL}', reference_refined, candidate_refined),\n", "])" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "python", "notebook_metadata_filter": "-all" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.14.5" } }, "nbformat": 4, "nbformat_minor": 5 }