{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "0", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:27:19.217656Z", "iopub.status.busy": "2026-06-30T22:27:19.217459Z", "iopub.status.idle": "2026-06-30T22:27:19.221686Z", "shell.execute_reply": "2026-06-30T22:27:19.220922Z" }, "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": [ "# Pr₂NiO₄ — single-crystal neutron CW — basic\n", "\n", "Verifies calculated F² values for a constant-wavelength neutron\n", "single-crystal reference with anisotropic ADPs.\n", "\n", "**Refinement:** the overall scale only; all other parameters are\n", "taken from the FullProf reference." ] }, { "cell_type": "code", "execution_count": 2, "id": "2", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:27:19.223945Z", "iopub.status.busy": "2026-06-30T22:27:19.223729Z", "iopub.status.idle": "2026-06-30T22:27:22.150402Z", "shell.execute_reply": "2026-06-30T22:27:22.149524Z" } }, "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": "2026-06-30T22:27:22.152666Z", "iopub.status.busy": "2026-06-30T22:27:22.152372Z", "iopub.status.idle": "2026-06-30T22:27:22.365805Z", "shell.execute_reply": "2026-06-30T22:27:22.364785Z" } }, "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": "2026-06-30T22:27:22.367622Z", "iopub.status.busy": "2026-06-30T22:27:22.367452Z", "iopub.status.idle": "2026-06-30T22:27:22.381669Z", "shell.execute_reply": "2026-06-30T22:27:22.380742Z" } }, "outputs": [], "source": [ "structure = StructureFactory.from_scratch(name='pr2nio4')\n", "\n", "structure.space_group.name_h_m = 'F m m m' # FullProf Space group symbol\n", "\n", "structure.cell.length_a = 5.417799 # FullProf a\n", "structure.cell.length_b = 5.414600 # FullProf b\n", "structure.cell.length_c = 12.483399 # FullProf c\n", "\n", "# Anisotropic sites carry the FullProf β tensor directly: ``adp_type`` is\n", "# set to ``'beta'`` and the dimensionless β components are assigned\n", "# verbatim. F m m m is orthorhombic, so β11, β22, β33 are independent —\n", "# each is set explicitly rather than left to a symmetry constraint.\n", "# FullProf occupancy folds in the site multiplicity; the chemical\n", "# occupancy here is the FullProf Occ scaled by the multiplicity (1.0 for\n", "# a full site).\n", "structure.atom_sites.create(\n", " id='Pr', # FullProf Atom\n", " type_symbol='Pr', # FullProf Typ\n", " fract_x=0.5, # FullProf X\n", " fract_y=0.5, # FullProf Y\n", " fract_z=0.35973, # FullProf Z\n", " adp_type='beta', # FullProf beta tensor\n", ")\n", "aniso = structure.atom_site_aniso['Pr']\n", "aniso.adp_11 = 0.00710 # FullProf beta11\n", "aniso.adp_22 = 0.00710 # FullProf beta22\n", "aniso.adp_33 = 0.00084 # FullProf beta33\n", "\n", "structure.atom_sites.create(\n", " id='Ni', # FullProf Atom\n", " type_symbol='Ni', # FullProf Typ\n", " fract_x=0, # FullProf X\n", " fract_y=0, # FullProf Y\n", " fract_z=0, # FullProf Z\n", " adp_type='beta', # FullProf beta tensor\n", ")\n", "aniso = structure.atom_site_aniso['Ni']\n", "aniso.adp_11 = 0.00280 # FullProf beta11\n", "aniso.adp_22 = 0.00280 # FullProf beta22\n", "aniso.adp_33 = 0.00151 # FullProf beta33\n", "\n", "structure.atom_sites.create(\n", " id='O1', # FullProf Atom\n", " type_symbol='O', # FullProf Typ\n", " fract_x=0.25, # FullProf X\n", " fract_y=0.25, # FullProf Y\n", " fract_z=0, # FullProf Z\n", " adp_type='beta', # FullProf beta tensor\n", ")\n", "aniso = structure.atom_site_aniso['O1']\n", "aniso.adp_11 = 0.00500 # FullProf beta11\n", "aniso.adp_22 = 0.00500 # FullProf beta22\n", "aniso.adp_33 = 0.00413 # FullProf beta33\n", "aniso.adp_12 = -0.00140 # FullProf beta12\n", "\n", "structure.atom_sites.create(\n", " id='O2', # FullProf Atom\n", " type_symbol='O', # FullProf Typ\n", " fract_x=0, # FullProf X\n", " fract_y=0, # FullProf Y\n", " fract_z=0.17385, # FullProf Z\n", " occupancy=0.722965, # FullProf Occ 1.44593 / multiplicity\n", " adp_type='beta', # FullProf beta tensor\n", ")\n", "aniso = structure.atom_site_aniso['O2']\n", "aniso.adp_11 = 0.01716 # FullProf beta11\n", "aniso.adp_22 = 0.01716 # FullProf beta22\n", "aniso.adp_33 = 0.00045 # FullProf beta33\n", "\n", "structure.atom_sites.create(\n", " id='Oi', # FullProf Atom\n", " type_symbol='O', # FullProf Typ\n", " fract_x=0.25, # FullProf X\n", " fract_y=0.25, # FullProf Y\n", " fract_z=0.25, # FullProf Z\n", " occupancy=0.074655, # FullProf Occ 0.14931 / multiplicity\n", " adp_type='beta', # FullProf beta tensor\n", ")\n", "aniso = structure.atom_site_aniso['Oi']\n", "aniso.adp_11 = 0.01033 # FullProf beta11\n", "aniso.adp_22 = 0.01176 # FullProf beta22\n", "aniso.adp_33 = 0.00100 # FullProf beta33\n", "\n", "# The split interstitial oxygen Od is refined with an isotropic B.\n", "structure.atom_sites.create(\n", " id='Od', # FullProf Atom\n", " type_symbol='O', # FullProf Typ\n", " fract_x=0.07347, # FullProf X\n", " fract_y=0.07347, # FullProf Y\n", " fract_z=0.17349, # FullProf Z\n", " occupancy=0.074654, # FullProf Occ 0.59723 / multiplicity\n", " adp_type='Biso', # FullProf Biso\n", " adp_iso=2.31435, # FullProf Biso\n", ")\n", "\n", "project.structures.add(structure)" ] }, { "cell_type": "code", "execution_count": 5, "id": "7", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:27:22.383273Z", "iopub.status.busy": "2026-06-30T22:27:22.383081Z", "iopub.status.idle": "2026-06-30T22:27:23.037950Z", "shell.execute_reply": "2026-06-30T22:27:23.037138Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mStructure 🧩 \u001b[0m\u001b[32m'pr2nio4'\u001b[0m\u001b[1;36m as text\u001b[0m\n" ] }, { "data": { "text/html": [ "
Edi
1data_pr2nio4
2
3_cell.length_a 5.417799
4_cell.length_b 5.4146
5_cell.length_c 12.483399
6_cell.angle_alpha 90.
7_cell.angle_beta 90.
8_cell.angle_gamma 90.
9
10_space_group.name_h_m "F m m m"
11_space_group.coord_system_code abc
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
27Pr Pr 0.5 0.5 0.35973 i 8 1. 0.00924491 beta
28Ni Ni 0. 0. 0. a 4 1. 0.0067478 beta
29O1 O 0.25 0.25 0. e 8 1. 0.01582218 beta
30O2 O 0. 0. 0.17385 i 8 0.722965 0.01818564 beta
31Oi O 0.25 0.25 0.25 f 8 0.074655 0.01357409 beta
32Od O 0.07347 0.07347 0.17349 p 32 0.074654 2.31435 Biso
33
34loop_
35_atom_site_aniso.id
36_atom_site_aniso.adp_11
37_atom_site_aniso.adp_22
38_atom_site_aniso.adp_33
39_atom_site_aniso.adp_12
40_atom_site_aniso.adp_13
41_atom_site_aniso.adp_23
42Pr 0.0071 0.0071 0.00084 0. 0. 0.
43Ni 0.0028 0.0028 0.00151 0. 0. 0.
44O1 0.005 0.005 0.00413 -0.0014 0. 0.
45O2 0.01716 0.01716 0.00045 0. 0. 0.
46Oi 0.01033 0.01176 0.001 0. 0. 0.
" ], "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": "2026-06-30T22:27:23.039769Z", "iopub.status.busy": "2026-06-30T22:27:23.039584Z", "iopub.status.idle": "2026-06-30T22:27:23.043691Z", "shell.execute_reply": "2026-06-30T22:27:23.042881Z" } }, "outputs": [], "source": [ "FULLPROF_PROJECT_DIR = 'sc-neut-cwl_pr2nio4_basic'\n", "FULLPROF_OUT_FILE = 'prnio.out'\n", "FULLPROF_SCALE = 0.06298 # FullProf Scale\n", "FULLPROF_WAVELENGTH = 0.8302 # FullProf Lambda\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": "2026-06-30T22:27:23.045288Z", "iopub.status.busy": "2026-06-30T22:27:23.045124Z", "iopub.status.idle": "2026-06-30T22:27:23.112962Z", "shell.execute_reply": "2026-06-30T22:27:23.112355Z" } }, "outputs": [], "source": [ "experiment = ExperimentFactory.from_scratch(\n", " name='pr2nio4',\n", " sample_form='single crystal',\n", " beam_mode='constant wavelength',\n", " radiation_probe='neutron',\n", " scattering_type='bragg',\n", ")\n", "\n", "experiment.linked_structure.structure_id = 'pr2nio4'\n", "experiment.linked_structure.scale = FULLPROF_SCALE\n", "experiment.instrument.setup_wavelength = FULLPROF_WAVELENGTH\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": "2026-06-30T22:27:23.118599Z", "iopub.status.busy": "2026-06-30T22:27:23.118378Z", "iopub.status.idle": "2026-06-30T22:27:23.391172Z", "shell.execute_reply": "2026-06-30T22:27:23.389866Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mCalculator for experiment \u001b[0m\u001b[32m'pr2nio4'\u001b[0m\u001b[1;36m already set to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cryspy\n" ] }, { "data": { "text/html": [ "
Loading plot…
" ], "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", " 'pr2nio4',\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": "2026-06-30T22:27:23.393307Z", "iopub.status.busy": "2026-06-30T22:27:23.392928Z", "iopub.status.idle": "2026-06-30T22:27:23.911519Z", "shell.execute_reply": "2026-06-30T22:27:23.910773Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mCalculator for experiment \u001b[0m\u001b[32m'pr2nio4'\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-3b25e9a4448c42989afdd9db763b3fed-button');\n", " const status = document.getElementById('ed-fit-stop-3b25e9a4448c42989afdd9db763b3fed-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": [ "📋 Using experiment 🔬 \u001b[32m'pr2nio4'\u001b[0m for \u001b[32m'single'\u001b[0m fitting\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "🚀 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": [ "📈 Goodness-of-fit progress:\n" ] }, { "data": { "text/html": [ "
iterationtime (s)χ²change / status
110.0234301.03
250.080.01100.0% ↓
380.130.01
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "🏆 Best goodness-of-fit \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m is \u001b[1;36m0.01\u001b[0m at iteration \u001b[1;36m5\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Fitting complete.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "⚙️ Settings used:\n" ] }, { "data": { "text/html": [ "
NameValueDescription
1max_iterations1000Maximum solver iterations.
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "📋 Least-squares fit results:\n" ] }, { "data": { "text/html": [ "
MetricValue
1🧪 Minimizerlmfit (leastsq)
2✅ Overall statussuccess
3⏱️ Fitting time (seconds)0.13
4🔁 Iterations5
5📏 Goodness-of-fit (reduced χ²)0.01
6📏 R-factor (Rf, %)0.06
7📏 R-factor squared (Rf², %)0.05
8📏 Weighted R-factor (wR, %)0.05
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "📈 Refined parameters:\n" ] }, { "data": { "text/html": [ "
datablockcategoryentryparameterunitsstartvalues.u.change
1pr2nio4linked_structurescale0.06302.01760.00013103.50 % ↑
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
• start = parameter value before refinement
• value = refined value from least-squares minimization
• s.u. = standard uncertainty (one sigma), from the covariance matrix
• change = relative change from start, in %; ↑ = increase, ↓ = decrease
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mCalculator for experiment \u001b[0m\u001b[32m'pr2nio4'\u001b[0m\u001b[1;36m already set to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cryspy\n" ] }, { "data": { "text/html": [ "
Loading plot…
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
MetricBeforeAfter
1Profile diff (%)96.880.05
2Max deviation (%)96.880.08
3Area ratio0.03121.0004
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", " 'pr2nio4',\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": "2026-06-30T22:27:23.913072Z", "iopub.status.busy": "2026-06-30T22:27:23.912920Z", "iopub.status.idle": "2026-06-30T22:27:23.920221Z", "shell.execute_reply": "2026-06-30T22:27:23.919228Z" } }, "outputs": [ { "data": { "text/html": [ "
ComparisonMetricExpectedActualOK
1edi 0.19.1 (cryspy 0.12.1, scale only) vs FullProf 8.40Profile diff (%)< 2.50.05✅
2Max deviation (%)< 60.08✅
3Area ratio0.99 to 1.011.0004✅
4Shape correlation> 0.9991.0000✅
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