Diffusion model

examples/diffusion_model.ipynb

@@ -0,0 +1,128 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64deaa41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "from easydynamics.sample_model import BrownianTranslationalDiffusion\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "%matplotlib widget"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "784d9e82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create Brownian Translational Diffusion model and plot the model for different Q values.\n",
+    "# Q is in Angstrom^-1 and energy in meV.\n",
+    "\n",
+    "Q=np.linspace(0.5,2,7)\n",
+    "# energy=np.linspace(-2, 2, 501)\n",
+    "energy=sc.linspace(start=-2,stop=2,num=501,unit=\"meV\",dim='energy')\n",
+    "scale=1.0\n",
+    "diffusion_coefficient = 2.4e-9  # m^2/s\n",
+    "diffusion_unit= \"m**2/s\"\n",
+    "\n",
+    "diffusion_model=BrownianTranslationalDiffusion(display_name=\"DiffusionModel\", scale=scale, diffusion_coefficient= diffusion_coefficient, diffusion_unit=diffusion_unit)\n",
+    "\n",
+    "component_collections=diffusion_model.create_component_collections(Q)\n",
+    "\n",
+    "\n",
+    "cmap = plt.cm.jet\n",
+    "nQ = len(component_collections)\n",
+    "plt.figure()\n",
+    "for Q_index in range(len(component_collections)):\n",
+    "    color = cmap(Q_index / (nQ - 1))\n",
+    "    y=component_collections[Q_index].evaluate(energy)\n",
+    "    plt.plot(energy, y, label=f'Q={Q[Q_index]} Å^-1',color=color)\n",
+    "    \n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "plt.xlabel('Energy (meV)')\n",
+    "plt.ylabel('Intensity (arb. units)')\n",
+    "plt.title('Brownian Translational Diffusion Model')    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dce619d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "energy=np.linspace(-2, 2, 501)\n",
+    "energy=sc.linspace(start=-2,stop=2,num=501,unit=\"meV\",dim='energy')\n",
+    "energy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "555cb19a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_collections[0].get_all_parameters()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7247d79d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "component_collections[0].get_all_parameters()[2].dependency_expression"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04e99b93",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "diffusion_model.diffusion_coefficient=5.0e-9"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "486cb003",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "easydynamics_newbase",
+   "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": "3.12.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

src/easydynamics/sample_model/__init__.py

@@ -7,6 +7,9 @@
     Polynomial,
     Voigt,
 )
+from .diffusion_model.brownian_translational_diffusion import (
+    BrownianTranslationalDiffusion,
+)
 
 __all__ = [
     "ComponentCollection",
@@ -16,4 +19,5 @@
     "DeltaFunction",
     "DampedHarmonicOscillator",
     "Polynomial",
+    "BrownianTranslationalDiffusion",
 ]

src/easydynamics/sample_model/diffusion_model/__init__.py

@@ -0,0 +1,7 @@
+from .brownian_translational_diffusion import BrownianTranslationalDiffusion
+from .diffusion_model_base import DiffusionModelBase
+
+__all__ = [
+    "DiffusionModelBase",
+    "BrownianTranslationalDiffusion",
+]