{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "
\n", " \n", "Disclaimer: \n", " \n", "The main objective of the Jupyter notebooks is to show how to use the models of the QENS library by\n", " \n", "- building a fitting model: composition of models, convolution with a resolution function \n", "- setting and running the fit \n", "- extracting and displaying information about the results \n", "\n", "These steps have a minimizer-dependent syntax. That is one of the reasons why different minimizers have been used in the notebooks provided as examples. \n", "But, the initial guessed parameters might not be optimal, resulting in a poor fit of the reference data.\n", "\n", "
\n", "\n", "# Lorentzian with lmfit \n", "\n", "## Introduction\n", "\n", "
\n", " \n", "The objective of this notebook is to show how to use one of the models of \n", "the QENSlibrary, lorentzian, to perform some fits. \n", "\n", "scipy.optimize.curve_fit is used for fitting.\n", "
\n", "\n", "### Physical units\n", "\n", "For information about unit conversion, please refer to the jupyter notebook called `Convert_units.ipynb` in the `tools` folder.\n", "\n", "The dictionary of units defined in the cell below specify the units of the refined parameters adapted to the convention used in the experimental datafile." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Units of parameters for selected QENS model and experimental data\n", "dict_physical_units = {\"omega\": \"1/ps\", \n", " 'scale': \"unit_of_signal.ps\", \n", " 'center': \"1/ps\", \n", " 'hwhm': \"1/ps\"}" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Import libraries" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [], "source": [ "import numpy as np\n", "import ipywidgets\n", "import matplotlib.pyplot as plt\n", "from scipy.optimize import curve_fit\n", "import ipywidgets\n", "import QENSmodels" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Plot fitting model\n", "\n", "The widget below shows the lorentzian peak shape function imported from QENSmodels where the function's parameters *Scale*, *Center* and *FWHM* can be varied." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8c49c164cd4b4f1386cdf151347e9341", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(VBox(children=(FloatSlider(value=5.0, continuous_update=False, description='scale', max=10.0, m…" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "569f5802ffc047b5ab6fe6a84ddd7b70", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "92f109c64953453d922a0f2025e24475", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Button(description='Reset', style=ButtonStyle())" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Dictionary of initial values\n", "ini_parameters = {'scale': 5., 'center': 5., 'hwhm': 3.}\n", "\n", "def interactive_fct(scale, center, hwhm):\n", " \"\"\"\n", " Plot to be updated when ipywidgets sliders are modified\n", " \"\"\"\n", " xs = np.linspace(-10, 10, 100)\n", " \n", " fig0, ax0 = plt.subplots()\n", " ax0.plot(xs, QENSmodels.lorentzian(xs, scale, center, hwhm))\n", " ax0.set_xlabel('x')\n", " ax0.grid()\n", "\n", "# Define sliders for modifiable parameters and their range of variations\n", "scale_slider = ipywidgets.FloatSlider(value=ini_parameters['scale'],\n", " min=0.1, max=10, step=0.1,\n", " description='scale',\n", " continuous_update=False) \n", "\n", "center_slider = ipywidgets.IntSlider(value=ini_parameters['center'],\n", " min=-10, max=10, step=1,\n", " description='center', \n", " continuous_update=False) \n", "\n", "hwhm_slider = ipywidgets.FloatSlider(value=ini_parameters['hwhm'],\n", " min=0.1, max=10, step=0.1,\n", " description='hwhm', \n", " continuous_update=False)\n", "\n", "grid_sliders = ipywidgets.HBox([ipywidgets.VBox([scale_slider, center_slider]), \n", " ipywidgets.VBox([hwhm_slider])])\n", " \n", "# Define function to reset all parameters' values to the initial ones\n", "def reset_values(b):\n", " \"\"\"\n", " Reset the interactive plots to inital values.\n", " \"\"\"\n", " scale_slider.value = ini_parameters['scale'] \n", " center_slider.value = ini_parameters['center'] \n", " hwhm_slider.value = ini_parameters['hwhm']\n", "\n", "# Define reset button and occurring action when clicking on it\n", "reset_button = ipywidgets.Button(description = \"Reset\")\n", "reset_button.on_click(reset_values)\n", "\n", "# Display the interactive plot\n", "interactive_plot = ipywidgets.interactive_output(\n", " interactive_fct,\n", " {'scale': scale_slider,\n", " 'center': center_slider,\n", " 'hwhm': hwhm_slider}\n", ") \n", " \n", "display(grid_sliders, interactive_plot, reset_button)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Creating reference data\n", "\n", "**Input:** the reference data for this simple example correspond to a Lorentzian with added noise.\n", "\n", "The fit is performed using `scipy.optimize.curve_fit`.
The example is based on implementations from https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Creation of reference data\n", "nb_points = 100\n", "xx = np.linspace(-10, 10, nb_points)\n", "added_noise = np.random.normal(0, 1, nb_points)\n", "lorentzian_noisy = QENSmodels.lorentzian(\n", " xx,\n", " scale=0.89,\n", " center=-0.025,\n", " hwhm=0.45\n", ") * (1. + 0.1 * added_noise) + 0.01 * added_noise\n", "\n", "fig1, ax1 = plt.subplots()\n", "ax1.plot(xx, lorentzian_noisy, label='reference data')\n", "ax1.set_xlabel('x')\n", "ax1.grid()\n", "ax1.legend();" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Setting and fitting\n", "From https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "initial_parameters_values = [1, 0.2, 0.5]\n", "\n", "fig2, ax2 = plt.subplots()\n", "ax2.plot(xx, lorentzian_noisy, 'b-', label='reference data')\n", "ax2.plot(\n", " xx, \n", " QENSmodels.lorentzian(xx, *initial_parameters_values), \n", " 'r-', \n", " label='model with initial guesses'\n", ")\n", "ax2.set_xlabel('x')\n", "ax2.legend(bbox_to_anchor=(0., 1.15), loc='upper left', borderaxespad=0.)\n", "ax2.grid();" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "popt, pcov = curve_fit(QENSmodels.lorentzian, xx, lorentzian_noisy, p0=initial_parameters_values)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Plotting the results" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": true, "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Values of refined parameters:\n", "scale: 0.8401433663930493 +/- 0.015271146793198383 unit_of_signal.ps\n", "center: -0.018478686118974085 +/- 0.007422705328117259 1/ps\n", "HWHM: 0.4094755075815917 +/- 0.010543965084163493 1/ps\n" ] } ], "source": [ "# Calculation of the errors on the refined parameters:\n", "perr = np.sqrt(np.diag(pcov))\n", "\n", "print(f\"Values of refined parameters:\\nscale: {popt[0]} +/- {perr[0]} {dict_physical_units['scale']}\\n\"\n", " f\"center: {popt[1]} +/- {perr[1]} {dict_physical_units['center']}\\n\"\n", " f\"HWHM: {popt[2]} +/- {perr[2]} {dict_physical_units['hwhm']}\")" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ " # Comparison of reference data with fitting result\n", "fig3, ax3 = plt.subplots()\n", "ax3.plot(xx, lorentzian_noisy, 'b-', label='reference data')\n", "ax3.plot(\n", " xx, \n", " QENSmodels.lorentzian(xx, *popt), \n", " 'g--', \n", " label='fit: %5.3f, %5.3f, %5.3f' % tuple(popt))\n", "ax3.legend()\n", "ax3.set_xlabel('x')\n", "ax3.grid();" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.9" }, "livereveal": { "scroll": true }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": true, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }