{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "0", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:23.195294Z", "iopub.status.busy": "2026-06-30T22:32:23.195083Z", "iopub.status.idle": "2026-06-30T22:32:23.199853Z", "shell.execute_reply": "2026-06-30T22:32:23.198962Z" }, "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": [ "# Pair Distribution Function: NaCl, XRD\n", "\n", "This example demonstrates a pair distribution function (PDF) analysis\n", "of NaCl, based on data collected from an X-ray powder diffraction\n", "experiment.\n", "\n", "The dataset is taken from:\n", "https://github.com/diffpy/add2019-diffpy-cmi/tree/master" ] }, { "cell_type": "markdown", "id": "2", "metadata": {}, "source": [ "## πŸ› οΈ Import Library" ] }, { "cell_type": "code", "execution_count": 2, "id": "3", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:23.201644Z", "iopub.status.busy": "2026-06-30T22:32:23.201429Z", "iopub.status.idle": "2026-06-30T22:32:26.138469Z", "shell.execute_reply": "2026-06-30T22:32:26.137118Z" } }, "outputs": [], "source": [ "import easydiffraction as edi" ] }, { "cell_type": "markdown", "id": "4", "metadata": {}, "source": [ "## πŸ“¦ Define Project" ] }, { "cell_type": "markdown", "id": "5", "metadata": {}, "source": [ "### Create Project" ] }, { "cell_type": "code", "execution_count": 3, "id": "6", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:26.140328Z", "iopub.status.busy": "2026-06-30T22:32:26.140001Z", "iopub.status.idle": "2026-06-30T22:32:26.358336Z", "shell.execute_reply": "2026-06-30T22:32:26.357487Z" } }, "outputs": [], "source": [ "project = edi.Project(name='nacl_xray_pdf')" ] }, { "cell_type": "markdown", "id": "7", "metadata": {}, "source": [ "### Set Plotting Engine" ] }, { "cell_type": "code", "execution_count": 4, "id": "8", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:26.360426Z", "iopub.status.busy": "2026-06-30T22:32:26.360247Z", "iopub.status.idle": "2026-06-30T22:32:26.363036Z", "shell.execute_reply": "2026-06-30T22:32:26.362173Z" } }, "outputs": [], "source": [ "# Keep the auto-selected engine. Alternatively, you can uncomment the\n", "# line below to explicitly set the engine to the required one.\n", "# project.rendering_plot.type = 'plotly'" ] }, { "cell_type": "code", "execution_count": 5, "id": "9", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:26.364753Z", "iopub.status.busy": "2026-06-30T22:32:26.364593Z", "iopub.status.idle": "2026-06-30T22:32:26.367413Z", "shell.execute_reply": "2026-06-30T22:32:26.366667Z" } }, "outputs": [], "source": [ "# Set global plot range for plots\n", "project.rendering_plot.plotter.x_min = 2.0\n", "project.rendering_plot.plotter.x_max = 30.0" ] }, { "cell_type": "markdown", "id": "10", "metadata": {}, "source": [ "### Add Structure" ] }, { "cell_type": "code", "execution_count": 6, "id": "11", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:26.369339Z", "iopub.status.busy": "2026-06-30T22:32:26.369080Z", "iopub.status.idle": "2026-06-30T22:32:26.373439Z", "shell.execute_reply": "2026-06-30T22:32:26.372664Z" } }, "outputs": [], "source": [ "project.structures.create(name='nacl')" ] }, { "cell_type": "code", "execution_count": 7, "id": "12", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:26.375337Z", "iopub.status.busy": "2026-06-30T22:32:26.375130Z", "iopub.status.idle": "2026-06-30T22:32:26.382586Z", "shell.execute_reply": "2026-06-30T22:32:26.381403Z" } }, "outputs": [], "source": [ "project.structures['nacl'].space_group.name_h_m = 'F m -3 m'\n", "project.structures['nacl'].space_group.coord_system_code = '1'\n", "project.structures['nacl'].cell.length_a = 5.62\n", "project.structures['nacl'].atom_sites.create(\n", " id='Na',\n", " type_symbol='Na',\n", " fract_x=0,\n", " fract_y=0,\n", " fract_z=0,\n", " adp_iso=1.0,\n", ")\n", "project.structures['nacl'].atom_sites.create(\n", " id='Cl',\n", " type_symbol='Cl',\n", " fract_x=0.5,\n", " fract_y=0.5,\n", " fract_z=0.5,\n", " adp_iso=1.0,\n", ")" ] }, { "cell_type": "markdown", "id": "13", "metadata": {}, "source": [ "### Display Structure" ] }, { "cell_type": "code", "execution_count": 8, "id": "14", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:26.384167Z", "iopub.status.busy": "2026-06-30T22:32:26.383965Z", "iopub.status.idle": "2026-06-30T22:32:27.073077Z", "shell.execute_reply": "2026-06-30T22:32:27.072343Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mStructure 🧩 \u001b[0m\u001b[32m'nacl'\u001b[0m\u001b[1;36m \u001b[0m\u001b[1;36m(\u001b[0m\u001b[1;36mAtom view type: \u001b[0m\u001b[32m'covalent'\u001b[0m\u001b[1;36m)\u001b[0m\n" ] }, { "data": { "text/html": [ "
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\n", "\n", "\n", "\n", "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.display.structure(struct_name='nacl')" ] }, { "cell_type": "markdown", "id": "15", "metadata": {}, "source": [ "### Add Experiment" ] }, { "cell_type": "code", "execution_count": 9, "id": "16", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.074592Z", "iopub.status.busy": "2026-06-30T22:32:27.074432Z", "iopub.status.idle": "2026-06-30T22:32:27.365233Z", "shell.execute_reply": "2026-06-30T22:32:27.363536Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mGetting data\u001b[0m\u001b[1;36m...\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Data \u001b[32m'meas-nacl-pdf'\u001b[0m: NaCl, PDF\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "βœ… Data \u001b[32m'meas-nacl-pdf'\u001b[0m downloaded to \u001b[32m'../../../data/meas-nacl-pdf.gr'\u001b[0m\n" ] } ], "source": [ "data_path = edi.download_data('meas-nacl-pdf', destination='data')" ] }, { "cell_type": "code", "execution_count": 10, "id": "17", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.367605Z", "iopub.status.busy": "2026-06-30T22:32:27.367352Z", "iopub.status.idle": "2026-06-30T22:32:27.939333Z", "shell.execute_reply": "2026-06-30T22:32:27.938230Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "⚠️ No uncertainty (sy) column provided. Defaulting to 0.03. \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mData loaded successfully\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Experiment πŸ”¬ \u001b[32m'xray_pdf'\u001b[0m. Number of data points: \u001b[1;36m5000\u001b[0m.\n" ] } ], "source": [ "project.experiments.add_from_data_path(\n", " name='xray_pdf',\n", " data_path=data_path,\n", " sample_form='powder',\n", " beam_mode='constant wavelength',\n", " radiation_probe='xray',\n", " scattering_type='total',\n", ")" ] }, { "cell_type": "code", "execution_count": 11, "id": "18", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.940969Z", "iopub.status.busy": "2026-06-30T22:32:27.940786Z", "iopub.status.idle": "2026-06-30T22:32:27.949061Z", "shell.execute_reply": "2026-06-30T22:32:27.948242Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mPeak types\u001b[0m\n" ] }, { "data": { "text/html": [ "
TypeDescription
1*gaussian-damped-sincTotal-scattering Gaussian-damped sinc profile for PDF analysis.
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.experiments['xray_pdf'].peak.show_supported()" ] }, { "cell_type": "code", "execution_count": 12, "id": "19", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.950691Z", "iopub.status.busy": "2026-06-30T22:32:27.950515Z", "iopub.status.idle": "2026-06-30T22:32:27.956249Z", "shell.execute_reply": "2026-06-30T22:32:27.955292Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mPeak profile type for experiment \u001b[0m\u001b[32m'xray_pdf'\u001b[0m\u001b[1;36m changed to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "gaussian-damped-sinc\n" ] } ], "source": [ "project.experiments['xray_pdf'].peak.type = 'gaussian-damped-sinc'" ] }, { "cell_type": "code", "execution_count": 13, "id": "20", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.957924Z", "iopub.status.busy": "2026-06-30T22:32:27.957696Z", "iopub.status.idle": "2026-06-30T22:32:27.962517Z", "shell.execute_reply": "2026-06-30T22:32:27.961702Z" } }, "outputs": [], "source": [ "project.experiments['xray_pdf'].peak.damp_q = 0.03\n", "project.experiments['xray_pdf'].peak.broad_q = 0\n", "project.experiments['xray_pdf'].peak.cutoff_q = 21\n", "project.experiments['xray_pdf'].peak.sharp_delta_1 = 0\n", "project.experiments['xray_pdf'].peak.sharp_delta_2 = 5\n", "project.experiments['xray_pdf'].peak.damp_particle_diameter = 0" ] }, { "cell_type": "code", "execution_count": 14, "id": "21", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.964320Z", "iopub.status.busy": "2026-06-30T22:32:27.964086Z", "iopub.status.idle": "2026-06-30T22:32:27.968079Z", "shell.execute_reply": "2026-06-30T22:32:27.967310Z" } }, "outputs": [], "source": [ "project.experiments['xray_pdf'].linked_structures.create(structure_id='nacl', scale=0.5)" ] }, { "cell_type": "markdown", "id": "22", "metadata": {}, "source": [ "## πŸš€ Perform Analysis" ] }, { "cell_type": "markdown", "id": "23", "metadata": {}, "source": [ "### Set Free Parameters" ] }, { "cell_type": "code", "execution_count": 15, "id": "24", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.969720Z", "iopub.status.busy": "2026-06-30T22:32:27.969568Z", "iopub.status.idle": "2026-06-30T22:32:27.972662Z", "shell.execute_reply": "2026-06-30T22:32:27.971863Z" } }, "outputs": [], "source": [ "project.structures['nacl'].cell.length_a.free = True\n", "project.structures['nacl'].atom_sites['Na'].adp_iso.free = True\n", "project.structures['nacl'].atom_sites['Cl'].adp_iso.free = True" ] }, { "cell_type": "code", "execution_count": 16, "id": "25", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.974074Z", "iopub.status.busy": "2026-06-30T22:32:27.973918Z", "iopub.status.idle": "2026-06-30T22:32:27.977515Z", "shell.execute_reply": "2026-06-30T22:32:27.976687Z" } }, "outputs": [], "source": [ "project.experiments['xray_pdf'].linked_structures['nacl'].scale.free = True\n", "project.experiments['xray_pdf'].peak.damp_q.free = True\n", "project.experiments['xray_pdf'].peak.sharp_delta_2.free = True" ] }, { "cell_type": "markdown", "id": "26", "metadata": {}, "source": [ "### Run Fitting" ] }, { "cell_type": "code", "execution_count": 17, "id": "27", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:27.978969Z", "iopub.status.busy": "2026-06-30T22:32:27.978827Z", "iopub.status.idle": "2026-06-30T22:32:40.242116Z", "shell.execute_reply": "2026-06-30T22:32:40.241304Z" } }, "outputs": [ { "data": { "text/html": [], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "(function() {\n", " const button = document.getElementById('ed-fit-stop-0dd15fa8936f48ac93dd7efb46e2dd4b-button');\n", " const status = document.getElementById('ed-fit-stop-0dd15fa8936f48ac93dd7efb46e2dd4b-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": [ "πŸ“‹ Using experiment πŸ”¬ \u001b[32m'xray_pdf'\u001b[0m for \u001b[32m'single'\u001b[0m fitting\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "πŸš€ 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": [ "πŸ“ˆ Goodness-of-fit progress:\n" ] }, { "data": { "text/html": [ "
iterationtime (s)χ²change / status
110.261023.73
2102.3329.9497.1% ↓
3174.014.5384.9% ↓
4245.591.5266.4% ↓
5317.101.483.2% ↓
65311.911.48
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "πŸ† Best goodness-of-fit \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m is \u001b[1;36m1.48\u001b[0m at iteration \u001b[1;36m52\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "βœ… Fitting complete.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "βš™οΈ Settings used:\n" ] }, { "data": { "text/html": [ "
NameValueDescription
1max_iterations1000Maximum solver iterations.
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "πŸ“‹ Least-squares fit results:\n" ] }, { "data": { "text/html": [ "
MetricValue
1πŸ§ͺ Minimizerlmfit (leastsq)
2βœ… Overall statussuccess
3⏱️ Fitting time (seconds)11.91
4πŸ” Iterations50
5πŸ“ Goodness-of-fit (reduced χ²)1.48
6πŸ“ R-factor (Rf, %)11.03
7πŸ“ R-factor squared (RfΒ², %)11.38
8πŸ“ Weighted R-factor (wR, %)11.38
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "πŸ“ˆ Refined parameters:\n" ] }, { "data": { "text/html": [ "
datablockcategoryentryparameterunitsstartvalues.u.change
1naclcelllength_aΓ…5.62005.60180.00010.32 % ↓
2naclatom_siteNaadp_isoΓ…Β²1.00001.10530.007710.53 % ↑
3naclatom_siteCladp_isoΓ…Β²1.00000.57070.003242.93 % ↓
4xray_pdflinked_structurenaclscale0.50000.18090.000563.81 % ↓
5xray_pdfpeakdamp_qÅ⁻¹0.03000.06060.0001102.13 % ↑
6xray_pdfpeaksharp_delta_2Γ…Β²5.00003.50410.066729.92 % ↓
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
β€’ start = parameter value before refinement
β€’ value = refined value from least-squares minimization
β€’ s.u. = standard uncertainty (one sigma), from the covariance matrix
β€’ change = relative change from start, in %; ↑ = increase, ↓ = decrease
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.fit()\n", "project.display.fit.results()\n", "project.display.fit.correlations()" ] }, { "cell_type": "markdown", "id": "28", "metadata": {}, "source": [ "### Display Pattern" ] }, { "cell_type": "code", "execution_count": 18, "id": "29", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:40.243735Z", "iopub.status.busy": "2026-06-30T22:32:40.243575Z", "iopub.status.idle": "2026-06-30T22:32:40.285715Z", "shell.execute_reply": "2026-06-30T22:32:40.284920Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.display.pattern(expt_name='xray_pdf')" ] }, { "cell_type": "markdown", "id": "30", "metadata": {}, "source": [ "## πŸ’Ύ Save Project" ] }, { "cell_type": "code", "execution_count": 19, "id": "31", "metadata": { "execution": { "iopub.execute_input": "2026-06-30T22:32:40.288021Z", "iopub.status.busy": "2026-06-30T22:32:40.287783Z", "iopub.status.idle": "2026-06-30T22:32:40.674841Z", "shell.execute_reply": "2026-06-30T22:32:40.674013Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36mSaving project πŸ“¦ \u001b[0m\u001b[32m'nacl_xray_pdf'\u001b[0m\u001b[1;36m to \u001b[0m\u001b[32m'../../../projects/pdf-nacl-xrd'\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”œβ”€β”€ πŸ“„ project.edi\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”œβ”€β”€ πŸ“ structures/\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”‚ └── πŸ“„ nacl.edi\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”œβ”€β”€ πŸ“ experiments/\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”‚ └── πŸ“„ xray_pdf.edi\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”œβ”€β”€ πŸ“ analysis/\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "β”‚ └── πŸ“„ analysis.edi\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "└── πŸ“ reports/\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " └── πŸ“„ nacl_xray_pdf.html\n" ] } ], "source": [ "project.save_as(dir_path='projects/pdf-nacl-xrd')" ] } ], "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 }