{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "0e2fd5c7", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:19.141718Z", "iopub.status.busy": "2026-01-06T13:54:19.141527Z", "iopub.status.idle": "2026-01-06T13:54:19.148602Z", "shell.execute_reply": "2026-01-06T13:54:19.146332Z" }, "tags": [ "hide-in-docs" ] }, "outputs": [], "source": [ "# Check if the easydiffraction library is installed.\n", "# If not, install it with the 'visualization' extras.\n", "# Needed when running remotely (e.g. Colab) where the lib is absent.\n", "import builtins\n", "import importlib.util\n", "\n", "if (hasattr(builtins, '__IPYTHON__') and\n", " importlib.util.find_spec('easydiffraction') is None):\n", " !pip install 'easydiffraction[visualization]==0.10.1'" ] }, { "cell_type": "markdown", "id": "0", "metadata": {}, "source": [ "# Structure Refinement: HS, HRPT\n", "\n", "This example demonstrates a Rietveld refinement of HS crystal\n", "structure using constant wavelength neutron powder diffraction data\n", "from HRPT at PSI." ] }, { "cell_type": "markdown", "id": "1", "metadata": {}, "source": [ "## Import Library" ] }, { "cell_type": "code", "execution_count": 2, "id": "2", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:19.150502Z", "iopub.status.busy": "2026-01-06T13:54:19.150379Z", "iopub.status.idle": "2026-01-06T13:54:21.987492Z", "shell.execute_reply": "2026-01-06T13:54:21.986356Z" } }, "outputs": [], "source": [ "from easydiffraction import ExperimentFactory\n", "from easydiffraction import Project\n", "from easydiffraction import SampleModelFactory\n", "from easydiffraction import download_data" ] }, { "cell_type": "markdown", "id": "3", "metadata": {}, "source": [ "## Define Sample Model\n", "\n", "This section shows how to add sample models and modify their\n", "parameters.\n", "\n", "#### Create Sample Model" ] }, { "cell_type": "code", "execution_count": 3, "id": "4", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:21.991076Z", "iopub.status.busy": "2026-01-06T13:54:21.990707Z", "iopub.status.idle": "2026-01-06T13:54:22.000617Z", "shell.execute_reply": "2026-01-06T13:54:21.999772Z" } }, "outputs": [], "source": [ "model = SampleModelFactory.create(name='hs')" ] }, { "cell_type": "markdown", "id": "5", "metadata": {}, "source": [ "#### Set Space Group" ] }, { "cell_type": "code", "execution_count": 4, "id": "6", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.003563Z", "iopub.status.busy": "2026-01-06T13:54:22.003416Z", "iopub.status.idle": "2026-01-06T13:54:22.005652Z", "shell.execute_reply": "2026-01-06T13:54:22.005163Z" } }, "outputs": [], "source": [ "model.space_group.name_h_m = 'R -3 m'\n", "model.space_group.it_coordinate_system_code = 'h'" ] }, { "cell_type": "markdown", "id": "7", "metadata": { "lines_to_next_cell": 2 }, "source": [ "#### Set Unit Cell" ] }, { "cell_type": "code", "execution_count": 5, "id": "8", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.007734Z", "iopub.status.busy": "2026-01-06T13:54:22.007278Z", "iopub.status.idle": "2026-01-06T13:54:22.010172Z", "shell.execute_reply": "2026-01-06T13:54:22.009677Z" } }, "outputs": [], "source": [ "model.cell.length_a = 6.9\n", "model.cell.length_c = 14.1" ] }, { "cell_type": "markdown", "id": "9", "metadata": {}, "source": [ "#### Set Atom Sites" ] }, { "cell_type": "code", "execution_count": 6, "id": "10", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.011834Z", "iopub.status.busy": "2026-01-06T13:54:22.011714Z", "iopub.status.idle": "2026-01-06T13:54:22.020953Z", "shell.execute_reply": "2026-01-06T13:54:22.020438Z" } }, "outputs": [], "source": [ "model.atom_sites.add(\n", " label='Zn',\n", " type_symbol='Zn',\n", " fract_x=0,\n", " fract_y=0,\n", " fract_z=0.5,\n", " wyckoff_letter='b',\n", " b_iso=0.5,\n", ")\n", "model.atom_sites.add(\n", " label='Cu',\n", " type_symbol='Cu',\n", " fract_x=0.5,\n", " fract_y=0,\n", " fract_z=0,\n", " wyckoff_letter='e',\n", " b_iso=0.5,\n", ")\n", "model.atom_sites.add(\n", " label='O',\n", " type_symbol='O',\n", " fract_x=0.21,\n", " fract_y=-0.21,\n", " fract_z=0.06,\n", " wyckoff_letter='h',\n", " b_iso=0.5,\n", ")\n", "model.atom_sites.add(\n", " label='Cl',\n", " type_symbol='Cl',\n", " fract_x=0,\n", " fract_y=0,\n", " fract_z=0.197,\n", " wyckoff_letter='c',\n", " b_iso=0.5,\n", ")\n", "model.atom_sites.add(\n", " label='H',\n", " type_symbol='2H',\n", " fract_x=0.13,\n", " fract_y=-0.13,\n", " fract_z=0.08,\n", " wyckoff_letter='h',\n", " b_iso=0.5,\n", ")" ] }, { "cell_type": "markdown", "id": "11", "metadata": {}, "source": [ "## Define Experiment\n", "\n", "This section shows how to add experiments, configure their parameters,\n", "and link the sample models defined in the previous step.\n", "\n", "#### Download Measured Data" ] }, { "cell_type": "code", "execution_count": 7, "id": "12", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.022958Z", "iopub.status.busy": "2026-01-06T13:54:22.022856Z", "iopub.status.idle": "2026-01-06T13:54:22.124404Z", "shell.execute_reply": "2026-01-06T13:54:22.124044Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mGetting data\u001b[0m\u001b[1;34m...\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Data #\u001b[1;36m11\u001b[0m: HS, HRPT \u001b[1m(\u001b[0mPSI\u001b[1m)\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Data #\u001b[1;36m11\u001b[0m downloaded to \u001b[32m'data/ed-11.xye'\u001b[0m\n" ] } ], "source": [ "data_path = download_data(id=11, destination='data')" ] }, { "cell_type": "markdown", "id": "13", "metadata": {}, "source": [ "#### Create Experiment" ] }, { "cell_type": "code", "execution_count": 8, "id": "14", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.126323Z", "iopub.status.busy": "2026-01-06T13:54:22.126190Z", "iopub.status.idle": "2026-01-06T13:54:22.699459Z", "shell.execute_reply": "2026-01-06T13:54:22.698406Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mData loaded successfully\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Experiment 🔬 \u001b[32m'hrpt'\u001b[0m. Number of data points: \u001b[1;36m3220\u001b[0m\n" ] } ], "source": [ "expt = ExperimentFactory.create(name='hrpt', data_path=data_path)" ] }, { "cell_type": "markdown", "id": "15", "metadata": {}, "source": [ "#### Set Instrument" ] }, { "cell_type": "code", "execution_count": 9, "id": "16", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.703729Z", "iopub.status.busy": "2026-01-06T13:54:22.703545Z", "iopub.status.idle": "2026-01-06T13:54:22.707329Z", "shell.execute_reply": "2026-01-06T13:54:22.706200Z" } }, "outputs": [], "source": [ "expt.instrument.setup_wavelength = 1.89\n", "expt.instrument.calib_twotheta_offset = 0.0" ] }, { "cell_type": "markdown", "id": "17", "metadata": {}, "source": [ "#### Set Peak Profile" ] }, { "cell_type": "code", "execution_count": 10, "id": "18", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.711036Z", "iopub.status.busy": "2026-01-06T13:54:22.710837Z", "iopub.status.idle": "2026-01-06T13:54:22.718192Z", "shell.execute_reply": "2026-01-06T13:54:22.717514Z" } }, "outputs": [], "source": [ "expt.peak.broad_gauss_u = 0.1\n", "expt.peak.broad_gauss_v = -0.2\n", "expt.peak.broad_gauss_w = 0.2\n", "expt.peak.broad_lorentz_x = 0.0\n", "expt.peak.broad_lorentz_y = 0" ] }, { "cell_type": "markdown", "id": "19", "metadata": {}, "source": [ "#### Set Background" ] }, { "cell_type": "code", "execution_count": 11, "id": "20", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.722348Z", "iopub.status.busy": "2026-01-06T13:54:22.721855Z", "iopub.status.idle": "2026-01-06T13:54:22.728760Z", "shell.execute_reply": "2026-01-06T13:54:22.728179Z" } }, "outputs": [], "source": [ "expt.background.add(id='1', x=4.4196, y=500)\n", "expt.background.add(id='2', x=6.6207, y=500)\n", "expt.background.add(id='3', x=10.4918, y=500)\n", "expt.background.add(id='4', x=15.4634, y=500)\n", "expt.background.add(id='5', x=45.6041, y=500)\n", "expt.background.add(id='6', x=74.6844, y=500)\n", "expt.background.add(id='7', x=103.4187, y=500)\n", "expt.background.add(id='8', x=121.6311, y=500)\n", "expt.background.add(id='9', x=159.4116, y=500)" ] }, { "cell_type": "markdown", "id": "21", "metadata": {}, "source": [ "#### Set Linked Phases" ] }, { "cell_type": "code", "execution_count": 12, "id": "22", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.730804Z", "iopub.status.busy": "2026-01-06T13:54:22.730614Z", "iopub.status.idle": "2026-01-06T13:54:22.733332Z", "shell.execute_reply": "2026-01-06T13:54:22.732836Z" } }, "outputs": [], "source": [ "expt.linked_phases.add(id='hs', scale=0.5)" ] }, { "cell_type": "markdown", "id": "23", "metadata": {}, "source": [ "## Define Project\n", "\n", "The project object is used to manage the sample model, experiment, and\n", "analysis.\n", "\n", "#### Create Project" ] }, { "cell_type": "code", "execution_count": 13, "id": "24", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.735577Z", "iopub.status.busy": "2026-01-06T13:54:22.735439Z", "iopub.status.idle": "2026-01-06T13:54:22.879688Z", "shell.execute_reply": "2026-01-06T13:54:22.879138Z" } }, "outputs": [], "source": [ "project = Project()" ] }, { "cell_type": "markdown", "id": "25", "metadata": {}, "source": [ "#### Set Plotting Engine" ] }, { "cell_type": "code", "execution_count": 14, "id": "26", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.889083Z", "iopub.status.busy": "2026-01-06T13:54:22.888579Z", "iopub.status.idle": "2026-01-06T13:54:22.895455Z", "shell.execute_reply": "2026-01-06T13:54:22.894626Z" } }, "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.plotter.engine = 'plotly'" ] }, { "cell_type": "markdown", "id": "27", "metadata": {}, "source": [ "#### Add Sample Model" ] }, { "cell_type": "code", "execution_count": 15, "id": "28", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.897807Z", "iopub.status.busy": "2026-01-06T13:54:22.897654Z", "iopub.status.idle": "2026-01-06T13:54:22.900840Z", "shell.execute_reply": "2026-01-06T13:54:22.899751Z" } }, "outputs": [], "source": [ "project.sample_models.add(sample_model=model)" ] }, { "cell_type": "markdown", "id": "29", "metadata": {}, "source": [ "#### Add Experiment" ] }, { "cell_type": "code", "execution_count": 16, "id": "30", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.904010Z", "iopub.status.busy": "2026-01-06T13:54:22.903828Z", "iopub.status.idle": "2026-01-06T13:54:22.906527Z", "shell.execute_reply": "2026-01-06T13:54:22.905744Z" } }, "outputs": [], "source": [ "project.experiments.add(experiment=expt)" ] }, { "cell_type": "markdown", "id": "31", "metadata": {}, "source": [ "## Perform Analysis\n", "\n", "This section shows the analysis process, including how to set up\n", "calculation and fitting engines.\n", "\n", "#### Set Calculator" ] }, { "cell_type": "code", "execution_count": 17, "id": "32", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.908949Z", "iopub.status.busy": "2026-01-06T13:54:22.908518Z", "iopub.status.idle": "2026-01-06T13:54:22.914697Z", "shell.execute_reply": "2026-01-06T13:54:22.913646Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mCurrent calculator changed to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cryspy\n" ] } ], "source": [ "project.analysis.current_calculator = 'cryspy'" ] }, { "cell_type": "markdown", "id": "33", "metadata": {}, "source": [ "#### Set Minimizer" ] }, { "cell_type": "code", "execution_count": 18, "id": "34", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.917797Z", "iopub.status.busy": "2026-01-06T13:54:22.917614Z", "iopub.status.idle": "2026-01-06T13:54:22.922679Z", "shell.execute_reply": "2026-01-06T13:54:22.922208Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mCurrent minimizer changed to\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "lmfit \u001b[1m(\u001b[0mleastsq\u001b[1m)\u001b[0m\n" ] } ], "source": [ "project.analysis.current_minimizer = 'lmfit (leastsq)'" ] }, { "cell_type": "markdown", "id": "35", "metadata": {}, "source": [ "#### Plot Measured vs Calculated" ] }, { "cell_type": "code", "execution_count": 19, "id": "36", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:22.925015Z", "iopub.status.busy": "2026-01-06T13:54:22.924854Z", "iopub.status.idle": "2026-01-06T13:54:23.391913Z", "shell.execute_reply": "2026-01-06T13:54:23.391325Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', show_residual=True)" ] }, { "cell_type": "code", "execution_count": 20, "id": "37", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:23.393869Z", "iopub.status.busy": "2026-01-06T13:54:23.393764Z", "iopub.status.idle": "2026-01-06T13:54:24.086368Z", "shell.execute_reply": "2026-01-06T13:54:24.082990Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', x_min=48, x_max=51, show_residual=True)" ] }, { "cell_type": "markdown", "id": "38", "metadata": {}, "source": [ "### Perform Fit 1/5\n", "\n", "Set parameters to be refined." ] }, { "cell_type": "code", "execution_count": 21, "id": "39", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:24.089363Z", "iopub.status.busy": "2026-01-06T13:54:24.088014Z", "iopub.status.idle": "2026-01-06T13:54:24.095280Z", "shell.execute_reply": "2026-01-06T13:54:24.094507Z" } }, "outputs": [], "source": [ "model.cell.length_a.free = True\n", "model.cell.length_c.free = True\n", "\n", "expt.linked_phases['hs'].scale.free = True\n", "expt.instrument.calib_twotheta_offset.free = True" ] }, { "cell_type": "markdown", "id": "40", "metadata": {}, "source": [ "Show free parameters after selection." ] }, { "cell_type": "code", "execution_count": 22, "id": "41", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:24.111703Z", "iopub.status.busy": "2026-01-06T13:54:24.109954Z", "iopub.status.idle": "2026-01-06T13:54:24.602887Z", "shell.execute_reply": "2026-01-06T13:54:24.601585Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFree parameters for both sample models \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🧩 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\u001b[1;34m and experiments \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🔬 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 datablockcategoryentryparametervalueuncertaintyminmaxunits
1hscelllength_a6.90000-infinfÅ
2hscelllength_c14.10000-infinfÅ
3hrptlinked_phaseshsscale0.50000-infinf
4hrptinstrumenttwotheta_offset0.00000-infinfdeg
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 iterationχ²improvement [%]
11576.50
28122.0278.8% ↓
313115.195.6% ↓
418109.864.6% ↓
523106.682.9% ↓
628104.602.0% ↓
733102.871.7% ↓
838101.131.7% ↓
94399.201.9% ↓
104896.862.4% ↓
115393.933.0% ↓
125890.343.8% ↓
136386.204.6% ↓
146881.665.3% ↓
157376.786.0% ↓
167871.716.6% ↓
178366.826.8% ↓
188862.486.5% ↓
199358.995.6% ↓
209856.414.4% ↓
2110354.643.1% ↓
2210853.492.1% ↓
2311352.761.4% ↓
2412352.021.4% ↓
2530451.57
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"metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { 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themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " 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notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "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;36m51.57\u001b[0m at iteration \u001b[1;36m303\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Fitting complete.\n" ] } ], "source": [ "project.analysis.fit()" ] }, { "cell_type": "code", "execution_count": 24, "id": "44", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:52.578511Z", "iopub.status.busy": "2026-01-06T13:54:52.577918Z", "iopub.status.idle": "2026-01-06T13:54:53.705999Z", "shell.execute_reply": "2026-01-06T13:54:53.703281Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFit results\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Success: \u001b[3;92mTrue\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "⏱️ Fitting time: \u001b[1;36m27.20\u001b[0m seconds\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Goodness-of-fit \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m: \u001b[1;36m51.57\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor \u001b[1m(\u001b[0mRf\u001b[1m)\u001b[0m: \u001b[1;36m19.70\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor squared \u001b[1m(\u001b[0mRf²\u001b[1m)\u001b[0m: \u001b[1;36m30.20\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Weighted R-factor \u001b[1m(\u001b[0mwR\u001b[1m)\u001b[0m: \u001b[1;36m30.35\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📈 Fitted parameters:\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if 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 datablockcategoryentryparameterstartfitteduncertaintyunitschange
1hscelllength_a6.90006.86230.0003Å0.55 % ↓
2hscelllength_c14.100014.13650.0008Å0.26 % ↑
3hrptlinked_phaseshsscale0.50000.25480.003049.04 % ↓
4hrptinstrumenttwotheta_offset0.00000.12710.0051degN/A
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_fit_results()" ] }, { "cell_type": "markdown", "id": "45", "metadata": {}, "source": [ "#### Plot Measured vs Calculated" ] }, { "cell_type": "code", "execution_count": 25, "id": "46", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:53.711504Z", "iopub.status.busy": "2026-01-06T13:54:53.709841Z", "iopub.status.idle": "2026-01-06T13:54:54.444063Z", "shell.execute_reply": "2026-01-06T13:54:54.443493Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', show_residual=True)" ] }, { "cell_type": "code", "execution_count": 26, "id": "47", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:54.448308Z", "iopub.status.busy": "2026-01-06T13:54:54.447923Z", "iopub.status.idle": "2026-01-06T13:54:55.103586Z", "shell.execute_reply": "2026-01-06T13:54:55.097519Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', x_min=48, x_max=51, show_residual=True)" ] }, { "cell_type": "markdown", "id": "48", "metadata": {}, "source": [ "### Perform Fit 2/5\n", "\n", "Set more parameters to be refined." ] }, { "cell_type": "code", "execution_count": 27, "id": "49", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:55.128165Z", "iopub.status.busy": "2026-01-06T13:54:55.127909Z", "iopub.status.idle": "2026-01-06T13:54:55.145928Z", "shell.execute_reply": "2026-01-06T13:54:55.139173Z" } }, "outputs": [], "source": [ "expt.peak.broad_gauss_u.free = True\n", "expt.peak.broad_gauss_v.free = True\n", "expt.peak.broad_gauss_w.free = True\n", "expt.peak.broad_lorentz_x.free = True\n", "\n", "for point in expt.background:\n", " point.y.free = True" ] }, { "cell_type": "markdown", "id": "50", "metadata": {}, "source": [ "Show free parameters after selection." ] }, { "cell_type": "code", "execution_count": 28, "id": "51", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:55.156334Z", "iopub.status.busy": "2026-01-06T13:54:55.156059Z", "iopub.status.idle": "2026-01-06T13:54:55.518179Z", "shell.execute_reply": "2026-01-06T13:54:55.516616Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFree parameters for both sample models \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🧩 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\u001b[1;34m and experiments \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🔬 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { 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 datablockcategoryentryparametervalueuncertaintyminmaxunits
1hscelllength_a6.862290.00029-infinfÅ
2hscelllength_c14.136510.00084-infinfÅ
3hrptlinked_phaseshsscale0.254800.00305-infinf
4hrptpeakbroad_gauss_u0.10000-infinfdeg²
5hrptpeakbroad_gauss_v-0.20000-infinfdeg²
6hrptpeakbroad_gauss_w0.20000-infinfdeg²
7hrptpeakbroad_lorentz_x0.00000-infinfdeg
8hrptinstrumenttwotheta_offset0.127120.00515-infinfdeg
9hrptbackground1y500.00000-infinf
10hrptbackground2y500.00000-infinf
11hrptbackground3y500.00000-infinf
12hrptbackground4y500.00000-infinf
13hrptbackground5y500.00000-infinf
14hrptbackground6y500.00000-infinf
15hrptbackground7y500.00000-infinf
16hrptbackground8y500.00000-infinf
17hrptbackground9y500.00000-infinf
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_free_params()" ] }, { "cell_type": "markdown", "id": "52", "metadata": {}, "source": [ "#### Run Fitting" ] }, { "cell_type": "code", "execution_count": 29, "id": "53", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:54:55.521517Z", "iopub.status.busy": "2026-01-06T13:54:55.521060Z", "iopub.status.idle": "2026-01-06T13:55:24.923034Z", "shell.execute_reply": "2026-01-06T13:55:24.921406Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mUsing experiment 🔬 \u001b[0m\u001b[32m'hrpt'\u001b[0m\u001b[1;34m for \u001b[0m\u001b[32m'single'\u001b[0m\u001b[1;34m fitting\u001b[0m\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 \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m change:\n" ] }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 iterationχ²improvement [%]
1151.78
22113.0774.8% ↓
34012.663.2% ↓
45812.491.3% ↓
534012.41
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document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "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;36m12.41\u001b[0m at iteration \u001b[1;36m339\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Fitting complete.\n" ] } ], "source": [ "project.analysis.fit()" ] }, { "cell_type": "code", "execution_count": 30, "id": "54", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:24.928128Z", "iopub.status.busy": "2026-01-06T13:55:24.926799Z", "iopub.status.idle": "2026-01-06T13:55:26.030628Z", "shell.execute_reply": "2026-01-06T13:55:26.027786Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFit results\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Success: \u001b[3;92mTrue\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "⏱️ Fitting time: \u001b[1;36m28.52\u001b[0m seconds\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Goodness-of-fit \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m: \u001b[1;36m12.41\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor \u001b[1m(\u001b[0mRf\u001b[1m)\u001b[0m: \u001b[1;36m9.62\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor squared \u001b[1m(\u001b[0mRf²\u001b[1m)\u001b[0m: \u001b[1;36m12.83\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Weighted R-factor \u001b[1m(\u001b[0mwR\u001b[1m)\u001b[0m: \u001b[1;36m12.21\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📈 Fitted parameters:\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", " \n", " 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 datablockcategoryentryparameterstartfitteduncertaintyunitschange
1hscelllength_a6.86236.86280.0003Å0.01 % ↑
2hscelllength_c14.136514.13890.0009Å0.02 % ↑
3hrptlinked_phaseshsscale0.25480.45700.003279.37 % ↑
4hrptpeakbroad_gauss_u0.10000.10420.0451deg²4.18 % ↑
5hrptpeakbroad_gauss_v-0.2000-0.49770.0619deg²148.83 % ↑
6hrptpeakbroad_gauss_w0.20000.35920.0227deg²79.60 % ↑
7hrptpeakbroad_lorentz_x0.00000.50420.0075degN/A
8hrptinstrumenttwotheta_offset0.12710.12890.0038deg1.39 % ↑
9hrptbackground1y500.0000645.483023.767429.10 % ↑
10hrptbackground2y500.0000520.859513.60884.17 % ↑
11hrptbackground3y500.0000455.003610.42209.00 % ↓
12hrptbackground4y500.0000428.86395.401914.23 % ↓
13hrptbackground5y500.0000453.50085.21359.30 % ↓
14hrptbackground6y500.0000446.75925.468610.65 % ↓
15hrptbackground7y500.0000411.56205.449017.69 % ↓
16hrptbackground8y500.0000364.38285.663427.12 % ↓
17hrptbackground9y500.0000469.28375.49876.14 % ↓
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_fit_results()" ] }, { "cell_type": "markdown", "id": "55", "metadata": {}, "source": [ "#### Plot Measured vs Calculated" ] }, { "cell_type": "code", "execution_count": 31, "id": "56", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:26.033182Z", "iopub.status.busy": "2026-01-06T13:55:26.033031Z", "iopub.status.idle": "2026-01-06T13:55:26.630618Z", "shell.execute_reply": "2026-01-06T13:55:26.630058Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', show_residual=True)" ] }, { "cell_type": "code", "execution_count": 32, "id": "57", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:26.634898Z", "iopub.status.busy": "2026-01-06T13:55:26.634716Z", "iopub.status.idle": "2026-01-06T13:55:27.026575Z", "shell.execute_reply": "2026-01-06T13:55:27.025746Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', x_min=48, x_max=51, show_residual=True)" ] }, { "cell_type": "markdown", "id": "58", "metadata": {}, "source": [ "### Perform Fit 3/5\n", "\n", "Set more parameters to be refined." ] }, { "cell_type": "code", "execution_count": 33, "id": "59", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:27.029588Z", "iopub.status.busy": "2026-01-06T13:55:27.029426Z", "iopub.status.idle": "2026-01-06T13:55:27.032669Z", "shell.execute_reply": "2026-01-06T13:55:27.032110Z" } }, "outputs": [], "source": [ "model.atom_sites['O'].fract_x.free = True\n", "model.atom_sites['O'].fract_z.free = True\n", "model.atom_sites['Cl'].fract_z.free = True\n", "model.atom_sites['H'].fract_x.free = True\n", "model.atom_sites['H'].fract_z.free = True" ] }, { "cell_type": "markdown", "id": "60", "metadata": {}, "source": [ "Show free parameters after selection." ] }, { "cell_type": "code", "execution_count": 34, "id": "61", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:27.034618Z", "iopub.status.busy": "2026-01-06T13:55:27.034519Z", "iopub.status.idle": "2026-01-06T13:55:27.394880Z", "shell.execute_reply": "2026-01-06T13:55:27.393722Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFree parameters for both sample models \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🧩 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\u001b[1;34m and experiments \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🔬 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { 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 datablockcategoryentryparametervalueuncertaintyminmaxunits
1hscelllength_a6.862760.00033-infinfÅ
2hscelllength_c14.138890.00088-infinfÅ
3hsatom_siteOfract_x0.21000-infinf
4hsatom_siteOfract_z0.06000-infinf
5hsatom_siteClfract_z0.19700-infinf
6hsatom_siteHfract_x0.13000-infinf
7hsatom_siteHfract_z0.08000-infinf
8hrptlinked_phaseshsscale0.457040.00318-infinf
9hrptpeakbroad_gauss_u0.104180.04510-infinfdeg²
10hrptpeakbroad_gauss_v-0.497660.06188-infinfdeg²
11hrptpeakbroad_gauss_w0.359190.02266-infinfdeg²
12hrptpeakbroad_lorentz_x0.504190.00753-infinfdeg
13hrptinstrumenttwotheta_offset0.128890.00379-infinfdeg
14hrptbackground1y645.4830323.76745-infinf
15hrptbackground2y520.8595213.60879-infinf
16hrptbackground3y455.0035510.42197-infinf
17hrptbackground4y428.863905.40186-infinf
18hrptbackground5y453.500845.21353-infinf
19hrptbackground6y446.759165.46856-infinf
20hrptbackground7y411.562025.44902-infinf
21hrptbackground8y364.382795.66340-infinf
22hrptbackground9y469.283745.49874-infinf
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_free_params()" ] }, { "cell_type": "markdown", "id": "62", "metadata": {}, "source": [ "#### Run Fitting" ] }, { "cell_type": "code", "execution_count": 35, "id": "63", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:27.397856Z", "iopub.status.busy": "2026-01-06T13:55:27.397524Z", "iopub.status.idle": "2026-01-06T13:55:43.100394Z", "shell.execute_reply": "2026-01-06T13:55:43.099503Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mUsing experiment 🔬 \u001b[0m\u001b[32m'hrpt'\u001b[0m\u001b[1;34m for \u001b[0m\u001b[32m'single'\u001b[0m\u001b[1;34m fitting\u001b[0m\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 \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m change:\n" ] }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 iterationχ²improvement [%]
1112.43
2265.1158.9% ↓
3494.4013.9% ↓
4724.351.3% ↓
51884.34
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + 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// Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "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;36m4.34\u001b[0m at iteration \u001b[1;36m187\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Fitting complete.\n" ] } ], "source": [ "project.analysis.fit()" ] }, { "cell_type": "code", "execution_count": 36, "id": "64", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:43.103608Z", "iopub.status.busy": "2026-01-06T13:55:43.103393Z", "iopub.status.idle": "2026-01-06T13:55:44.031577Z", "shell.execute_reply": "2026-01-06T13:55:44.030444Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFit results\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Success: \u001b[3;92mTrue\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "⏱️ Fitting time: \u001b[1;36m15.02\u001b[0m seconds\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Goodness-of-fit \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m: \u001b[1;36m4.34\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor \u001b[1m(\u001b[0mRf\u001b[1m)\u001b[0m: \u001b[1;36m6.01\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor squared \u001b[1m(\u001b[0mRf²\u001b[1m)\u001b[0m: \u001b[1;36m7.75\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Weighted R-factor \u001b[1m(\u001b[0mwR\u001b[1m)\u001b[0m: \u001b[1;36m7.54\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📈 Fitted parameters:\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) 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 datablockcategoryentryparameterstartfitteduncertaintyunitschange
1hscelllength_a6.86286.86210.0002Å0.01 % ↓
2hscelllength_c14.138914.13560.0005Å0.02 % ↓
3hsatom_siteOfract_x0.21000.20590.00021.96 % ↓
4hsatom_siteOfract_z0.06000.06250.00024.14 % ↑
5hsatom_siteClfract_z0.19700.19770.00020.36 % ↑
6hsatom_siteHfract_x0.13000.13300.00022.33 % ↑
7hsatom_siteHfract_z0.08000.08770.00019.59 % ↑
8hrptlinked_phaseshsscale0.45700.41760.00218.63 % ↓
9hrptpeakbroad_gauss_u0.10420.17890.0119deg²71.71 % ↑
10hrptpeakbroad_gauss_v-0.4977-0.39640.0222deg²20.35 % ↓
11hrptpeakbroad_gauss_w0.35920.32720.0100deg²8.92 % ↓
12hrptpeakbroad_lorentz_x0.50420.36010.0089deg28.57 % ↓
13hrptinstrumenttwotheta_offset0.12890.11670.0021deg9.43 % ↓
14hrptbackground1y645.4830647.402414.06100.30 % ↑
15hrptbackground2y520.8595523.47258.05100.50 % ↑
16hrptbackground3y455.0036453.75456.16780.27 % ↓
17hrptbackground4y428.8639437.94793.22212.12 % ↑
18hrptbackground5y453.5008477.48633.22615.29 % ↑
19hrptbackground6y446.7592485.01773.40078.56 % ↑
20hrptbackground7y411.5620452.43383.28949.93 % ↑
21hrptbackground8y364.3828435.37323.500719.48 % ↑
22hrptbackground9y469.2837427.38833.62748.93 % ↓
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_fit_results()" ] }, { "cell_type": "markdown", "id": "65", "metadata": {}, "source": [ "#### Plot Measured vs Calculated" ] }, { "cell_type": "code", "execution_count": 37, "id": "66", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:44.035019Z", "iopub.status.busy": "2026-01-06T13:55:44.034804Z", "iopub.status.idle": "2026-01-06T13:55:44.484862Z", "shell.execute_reply": "2026-01-06T13:55:44.484090Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', show_residual=True)" ] }, { "cell_type": "code", "execution_count": 38, "id": "67", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:44.488739Z", "iopub.status.busy": "2026-01-06T13:55:44.488202Z", "iopub.status.idle": "2026-01-06T13:55:45.179146Z", "shell.execute_reply": "2026-01-06T13:55:45.178527Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', x_min=48, x_max=51, show_residual=True)" ] }, { "cell_type": "markdown", "id": "68", "metadata": {}, "source": [ "### Perform Fit 4/5\n", "\n", "Set more parameters to be refined." ] }, { "cell_type": "code", "execution_count": 39, "id": "69", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:45.181113Z", "iopub.status.busy": "2026-01-06T13:55:45.180905Z", "iopub.status.idle": "2026-01-06T13:55:45.184135Z", "shell.execute_reply": "2026-01-06T13:55:45.183591Z" } }, "outputs": [], "source": [ "model.atom_sites['Zn'].b_iso.free = True\n", "model.atom_sites['Cu'].b_iso.free = True\n", "model.atom_sites['O'].b_iso.free = True\n", "model.atom_sites['Cl'].b_iso.free = True\n", "model.atom_sites['H'].b_iso.free = True" ] }, { "cell_type": "markdown", "id": "70", "metadata": {}, "source": [ "Show free parameters after selection." ] }, { "cell_type": "code", "execution_count": 40, "id": "71", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:45.186274Z", "iopub.status.busy": "2026-01-06T13:55:45.186117Z", "iopub.status.idle": "2026-01-06T13:55:45.573076Z", "shell.execute_reply": "2026-01-06T13:55:45.571740Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFree parameters for both sample models \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🧩 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\u001b[1;34m and experiments \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34m🔬 data blocks\u001b[0m\u001b[1;34m)\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { 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 datablockcategoryentryparametervalueuncertaintyminmaxunits
1hscelllength_a6.862050.00020-infinfÅ
2hscelllength_c14.135600.00049-infinfÅ
3hsatom_siteZnb_iso0.50000-infinfŲ
4hsatom_siteCub_iso0.50000-infinfŲ
5hsatom_siteOfract_x0.205890.00022-infinf
6hsatom_siteOfract_z0.062480.00016-infinf
7hsatom_siteOb_iso0.50000-infinfŲ
8hsatom_siteClfract_z0.197710.00016-infinf
9hsatom_siteClb_iso0.50000-infinfŲ
10hsatom_siteHfract_x0.133030.00017-infinf
11hsatom_siteHfract_z0.087670.00012-infinf
12hsatom_siteHb_iso0.50000-infinfŲ
13hrptlinked_phaseshsscale0.417580.00208-infinf
14hrptpeakbroad_gauss_u0.178880.01187-infinfdeg²
15hrptpeakbroad_gauss_v-0.396380.02219-infinfdeg²
16hrptpeakbroad_gauss_w0.327150.00999-infinfdeg²
17hrptpeakbroad_lorentz_x0.360120.00888-infinfdeg
18hrptinstrumenttwotheta_offset0.116740.00215-infinfdeg
19hrptbackground1y647.4024214.06098-infinf
20hrptbackground2y523.472548.05103-infinf
21hrptbackground3y453.754496.16778-infinf
22hrptbackground4y437.947873.22213-infinf
23hrptbackground5y477.486273.22612-infinf
24hrptbackground6y485.017663.40075-infinf
25hrptbackground7y452.433793.28943-infinf
26hrptbackground8y435.373213.50066-infinf
27hrptbackground9y427.388253.62743-infinf
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_free_params()" ] }, { "cell_type": "markdown", "id": "72", "metadata": {}, "source": [ "#### Run Fitting" ] }, { "cell_type": "code", "execution_count": 41, "id": "73", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:45.575154Z", "iopub.status.busy": "2026-01-06T13:55:45.575019Z", "iopub.status.idle": "2026-01-06T13:55:57.417421Z", "shell.execute_reply": "2026-01-06T13:55:57.416360Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mUsing experiment 🔬 \u001b[0m\u001b[32m'hrpt'\u001b[0m\u001b[1;34m for \u001b[0m\u001b[32m'single'\u001b[0m\u001b[1;34m fitting\u001b[0m\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 \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m change:\n" ] }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 iterationχ²improvement [%]
114.35
2312.3047.1% ↓
3592.118.3% ↓
41442.11
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "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;36m2.11\u001b[0m at iteration \u001b[1;36m118\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Fitting complete.\n" ] } ], "source": [ "project.analysis.fit()" ] }, { "cell_type": "code", "execution_count": 42, "id": "74", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:57.420186Z", "iopub.status.busy": "2026-01-06T13:55:57.419992Z", "iopub.status.idle": "2026-01-06T13:55:58.161585Z", "shell.execute_reply": "2026-01-06T13:55:58.161022Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mFit results\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "✅ Success: \u001b[3;92mTrue\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "⏱️ Fitting time: \u001b[1;36m11.22\u001b[0m seconds\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Goodness-of-fit \u001b[1m(\u001b[0mreduced χ²\u001b[1m)\u001b[0m: \u001b[1;36m2.11\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor \u001b[1m(\u001b[0mRf\u001b[1m)\u001b[0m: \u001b[1;36m4.17\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 R-factor squared \u001b[1m(\u001b[0mRf²\u001b[1m)\u001b[0m: \u001b[1;36m5.05\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📏 Weighted R-factor \u001b[1m(\u001b[0mwR\u001b[1m)\u001b[0m: \u001b[1;36m4.72\u001b[0m%\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "📈 Fitted parameters:\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = 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 datablockcategoryentryparameterstartfitteduncertaintyunitschange
1hscelllength_a6.86216.86150.0001Å0.01 % ↓
2hscelllength_c14.135614.13600.0004Å0.00 % ↑
3hsatom_siteZnb_iso0.50000.08550.0630Ų82.91 % ↓
4hsatom_siteCub_iso0.50001.19370.0399Ų138.74 % ↑
5hsatom_siteOfract_x0.20590.20600.00020.06 % ↑
6hsatom_siteOfract_z0.06250.06090.00012.53 % ↓
7hsatom_siteOb_iso0.50000.70010.0360Ų40.02 % ↑
8hsatom_siteClfract_z0.19770.19680.00010.49 % ↓
9hsatom_siteClb_iso0.50001.11290.0385Ų122.58 % ↑
10hsatom_siteHfract_x0.13300.13220.00020.62 % ↓
11hsatom_siteHfract_z0.08770.09000.00012.63 % ↑
12hsatom_siteHb_iso0.50002.34040.0401Ų368.08 % ↑
13hrptlinked_phaseshsscale0.41760.49180.002217.76 % ↑
14hrptpeakbroad_gauss_u0.17890.15790.0076deg²11.70 % ↓
15hrptpeakbroad_gauss_v-0.3964-0.35710.0147deg²9.91 % ↓
16hrptpeakbroad_gauss_w0.32720.34980.0067deg²6.92 % ↑
17hrptpeakbroad_lorentz_x0.36010.29270.0065deg18.73 % ↓
18hrptinstrumenttwotheta_offset0.11670.11370.0015deg2.62 % ↓
19hrptbackground1y647.4024648.41259.79680.16 % ↑
20hrptbackground2y523.4725523.78805.60950.06 % ↑
21hrptbackground3y453.7545454.93754.29760.26 % ↑
22hrptbackground4y437.9479435.91312.25120.46 % ↓
23hrptbackground5y477.4863472.97182.27590.95 % ↓
24hrptbackground6y485.0177486.60642.43560.33 % ↑
25hrptbackground7y452.4338472.40952.34834.42 % ↑
26hrptbackground8y435.3732496.73382.621114.09 % ↑
27hrptbackground9y427.3883473.14572.936110.71 % ↑
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.analysis.show_fit_results()" ] }, { "cell_type": "markdown", "id": "75", "metadata": {}, "source": [ "#### Plot Measured vs Calculated" ] }, { "cell_type": "code", "execution_count": 43, "id": "76", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:58.163511Z", "iopub.status.busy": "2026-01-06T13:55:58.163367Z", "iopub.status.idle": "2026-01-06T13:55:58.615077Z", "shell.execute_reply": "2026-01-06T13:55:58.610019Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', show_residual=True)" ] }, { "cell_type": "code", "execution_count": 44, "id": "77", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:58.618089Z", "iopub.status.busy": "2026-01-06T13:55:58.617861Z", "iopub.status.idle": "2026-01-06T13:55:59.032736Z", "shell.execute_reply": "2026-01-06T13:55:59.032241Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "project.plot_meas_vs_calc(expt_name='hrpt', x_min=48, x_max=51, show_residual=True)" ] }, { "cell_type": "markdown", "id": "78", "metadata": {}, "source": [ "## Summary\n", "\n", "This final section shows how to review the results of the analysis." ] }, { "cell_type": "markdown", "id": "79", "metadata": {}, "source": [ "#### Show Project Summary" ] }, { "cell_type": "code", "execution_count": 45, "id": "80", "metadata": { "execution": { "iopub.execute_input": "2026-01-06T13:55:59.035468Z", "iopub.status.busy": "2026-01-06T13:55:59.035275Z", "iopub.status.idle": "2026-01-06T13:56:00.592408Z", "shell.execute_reply": "2026-01-06T13:56:00.591916Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;32m————————————\u001b[0m\n", "\u001b[1;32mPROJECT INFO\u001b[0m\n", "\u001b[1;32m————————————\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mTitle\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Untitled Project\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;32m—————————————————————\u001b[0m\n", "\u001b[1;32mCRYSTALLOGRAPHIC DATA\u001b[0m\n", "\u001b[1;32m—————————————————————\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mPhase datablock\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "🧩 hs\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mSpace group\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "R \u001b[1;36m-3\u001b[0m m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mCell parameters\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 ParameterValue
1a6.86149
2b6.86149
3c14.13604
4alpha90.00000
5beta90.00000
6gamma120.00000
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mAtom sites\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 labeltypexyzoccBiso
1ZnZn0.000000.000000.500001.000000.08546
2CuCu0.500000.000000.000001.000001.19372
3OO0.20601-0.206010.060901.000000.70009
4ClCl0.000000.000000.196751.000001.11288
5H2H0.13220-0.132200.089981.000002.34039
\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;32m———————————\u001b[0m\n", "\u001b[1;32mEXPERIMENTS\u001b[0m\n", "\u001b[1;32m———————————\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mExperiment datablock\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "🔬 hrpt\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mExperiment type\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "powder, neutron, constant wavelength\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mWavelength\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36m1.89000\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34m2θ offset\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;36m0.11368\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mProfile type\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "PeakProfileTypeEnum.PSEUDO_VOIGT\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1;34mPeak broadening \u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34mGaussian\u001b[0m\u001b[1;34m)\u001b[0m\n" ] }, { "data": { "application/javascript": [ "\n", " (function() {\n", " var isDark = false;\n", "\n", " // Check JupyterLab theme\n", " if (document.body.classList.contains('jp-mod-dark') || \n", " document.body.classList.contains('theme-dark') ||\n", " document.body.classList.contains('vscode-dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check theme attribute\n", " var themeAttr = document.body.getAttribute('data-jp-theme-name');\n", " if (themeAttr && themeAttr.includes('dark')) {\n", " isDark = true;\n", " }\n", "\n", " // Check computed background color\n", " var notebookEl = document.querySelector('.jp-Notebook') || \n", " document.querySelector('.notebook_app') ||\n", " document.body;\n", " if (notebookEl) {\n", " var bgColor = window.getComputedStyle(notebookEl).backgroundColor;\n", " var rgb = bgColor.match(/\\d+/g);\n", " if (rgb && rgb.length >= 3) {\n", " var brightness = (parseInt(rgb[0]) + parseInt(rgb[1]) + parseInt(rgb[2])) / 3;\n", " if (brightness < 128) {\n", " isDark = true;\n", " }\n", " }\n", " }\n", "\n", " // Store result\n", " if (typeof IPython !== 'undefined' && IPython.notebook && IPython.notebook.kernel) {\n", " IPython.notebook.kernel.execute('_jupyter_dark_detect_result = ' + isDark);\n", " }\n", " })();\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", " if (typeof IPython !== 'undefined' && IPython.notebook) {\n", " IPython.notebook.kernel.execute(\"_jupyter_dark_detect_result = \" + \n", " (document.body.classList.contains('theme-dark') || \n", " document.body.classList.contains('jp-mod-dark') ||\n", " (document.body.getAttribute('data-jp-theme-name') && \n", " document.body.getAttribute('data-jp-theme-name').includes('dark'))));\n", " }\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 ParameterValue
1U0.15795
2V-0.35708
3W0.34978
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 ParameterValue
1X0.29266
2Y0.00000
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 metricvalue
1Goodness-of-fit (reduced χ²)2.11
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