Convolution

examples/component_example.ipynb → examples/components.ipynb

@@ -74,18 +74,16 @@
    "source": [
     "delta = DeltaFunction(name='Delta', center=0.0, area=1.0)\n",
     "x1=np.linspace(-2, 2, 100)\n",
-    "y=delta.evaluate(x1)\n",
+    "y1=delta.evaluate(x1)\n",
     "x2=np.linspace(-2,2,51)\n",
     "y2=delta.evaluate(x2)\n",
     "plt.figure()\n",
-    "plt.plot(x1, y, label='Delta Function')\n",
+    "plt.plot(x1, y1, label='Delta Function')\n",
     "plt.plot(x2, y2, label='Delta Function (coarser)')\n",
     "plt.legend()\n",
     "plt.show()\n",
     "# The area under the Delta function is indeed equal to the area parameter.\n",
-    "xx=np.linspace(-2, 2, 10000)\n",
-    "yy=delta.evaluate(xx)\n",
-    "area= np.trapezoid(y, x1)\n",
+    "area= np.trapezoid(y1, x1)\n",
     "print(area)\n"
    ]
   },
@@ -114,7 +112,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "newdynamics",
+   "display_name": "easydynamics_newbase",
    "language": "python",
    "name": "python3"
   },
@@ -128,7 +126,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.13"
+   "version": "3.12.12"
   }
  },
  "nbformat": 4,

examples/convolution.ipynb

@@ -0,0 +1,154 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f42e34d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "from easydynamics.sample_model import DeltaFunction, Gaussian, Lorentzian, SampleModel, DampedHarmonicOscillator\n",
+    "from easydynamics.convolution import Convolution \n",
+    "from easydynamics.utils import _detailed_balance_factor as detailed_balance_factor\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib widget\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "600c0850",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Standard example of convolution of a sample model with a resolution model\n",
+    "sample_model=SampleModel(name='sample_model')\n",
+    "gaussian=Gaussian(name='Gaussian',width=0.5,area=1)\n",
+    "dho = DampedHarmonicOscillator(name='DHO',center=1.0,width=0.3,area=2.0)\n",
+    "lorentzian = Lorentzian(name='Lorentzian',center=-1.0,width=0.2,area=1.0)\n",
+    "delta = DeltaFunction(name='Delta',center=0.4,area=0.5)\n",
+    "sample_model.add_component(gaussian)\n",
+    "# sample_model.add_component(dho)\n",
+    "sample_model.add_component(lorentzian)\n",
+    "sample_model.add_component(delta)\n",
+    "\n",
+    "resolution_model = SampleModel(name='resolution_model')\n",
+    "resolution_gaussian=Gaussian(name='Resolution Gaussian',width=0.015,area=0.8)\n",
+    "resolution_lorentzian = Lorentzian(name='Resolution Lorentzian',width=0.025,area=0.2)\n",
+    "resolution_model.add_component(resolution_gaussian)\n",
+    "resolution_model.add_component(resolution_lorentzian)\n",
+    "\n",
+    "energy=np.linspace(-2, 2, 100)\n",
+    "\n",
+    "convolver = Convolution(sample_model=sample_model, resolution_model=resolution_model, energy=energy)\n",
+    "y = convolver.convolution()\n",
+    "plt.figure()\n",
+    "plt.plot(energy, y, label='Convoluted Model')\n",
+    "plt.xlabel('Energy (meV)')\n",
+    "plt.ylabel('Intensity (arb. units)')\n",
+    "plt.title('Convolution of Sample Model with Resolution Model')\n",
+    "\n",
+    "plt.plot(energy, sample_model.evaluate(energy), label='Sample Model', linestyle='--')\n",
+    "plt.plot(energy, resolution_model.evaluate(energy), label='Resolution Model', linestyle=':')\n",
+    "\n",
+    "\n",
+    "plt.legend()\n",
+    "# set the limit on the y axis\n",
+    "plt.ylim(0,6)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d49acae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "convolver.upsample_factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fede1a58",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# Use some of the extra settings for the numerical convolution\n",
+    "sample_model=SampleModel(name='sample_model')\n",
+    "gaussian=Gaussian(name='Gaussian',width=0.3,area=1)\n",
+    "dho = DampedHarmonicOscillator(name='DHO',center=1.0,width=0.3,area=2.0)\n",
+    "lorentzian = Lorentzian(name='Lorentzian',center=-1.0,width=0.2,area=1.0)\n",
+    "delta = DeltaFunction(name='Delta',center=0.4,area=0.5)\n",
+    "sample_model.add_component(gaussian)\n",
+    "sample_model.add_component(dho)\n",
+    "sample_model.add_component(lorentzian)\n",
+    "\n",
+    "resolution_model = SampleModel(name='resolution_model')\n",
+    "resolution_gaussian=Gaussian(name='Resolution Gaussian',width=0.15,area=0.8)\n",
+    "resolution_lorentzian = Lorentzian(name='Resolution Lorentzian',width=0.25,area=0.2)\n",
+    "resolution_model.add_component(resolution_gaussian)\n",
+    "resolution_model.add_component(resolution_lorentzian)\n",
+    "\n",
+    "energy=np.linspace(-2, 2, 100)\n",
+    "\n",
+    "\n",
+    "temperature = 10.0  # Temperature in Kelvin\n",
+    "offset = 0.5\n",
+    "upsample_factor = 5\n",
+    "extension_factor = 0.5\n",
+    "plt.figure()\n",
+    "plt.xlabel('Energy (meV)')\n",
+    "plt.ylabel('Intensity (arb. units)')\n",
+    "\n",
+    "convolver = Convolution(\n",
+    "    sample_model=sample_model, \n",
+    "    resolution_model=resolution_model, \n",
+    "    energy=energy-offset,  \n",
+    "    upsample_factor=upsample_factor,\n",
+    "    extension_factor=extension_factor,\n",
+    "    temperature=temperature,\n",
+    "    normalize_detailed_balance=True,)\n",
+    "y = convolver.convolution()\n",
+    "\n",
+    "\n",
+    "plt.plot(energy, y, label='Convoluted Model')\n",
+    "\n",
+    "plt.plot(energy, sample_model.evaluate(energy-offset)*detailed_balance_factor(energy-offset, temperature), label='Sample Model with DB', linestyle='--')\n",
+    "\n",
+    "plt.plot(energy, resolution_model.evaluate(energy   ), label='Resolution Model', linestyle=':')\n",
+    "plt.title('Convolution of Sample Model with Resolution Model with detailed balancing')\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.ylim(0,2.5)\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "newdynamics",
+   "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": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/sample_model.ipynb

@@ -0,0 +1,94 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64deaa41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "from easydynamics.sample_model import Gaussian\n",
+    "from easydynamics.sample_model import Lorentzian\n",
+    "from easydynamics.sample_model import DampedHarmonicOscillator\n",
+    "from easydynamics.sample_model import Polynomial\n",
+    "\n",
+    "from easydynamics.sample_model import SampleModel\n",
+    "\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "%matplotlib widget"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "784d9e82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sample_model=SampleModel(name='sample_model')\n",
+    "\n",
+    "# Creating components\n",
+    "gaussian=Gaussian(name='Gaussian',width=0.5,area=1)\n",
+    "dho = DampedHarmonicOscillator(name='DHO',center=1.0,width=0.3,area=2.0)\n",
+    "lorentzian = Lorentzian(name='Lorentzian',center=-1.0,width=0.2,area=1.0)\n",
+    "polynomial = Polynomial(name='Polynomial',coefficients=[0.1, 0, 0.5])  # y=0.1+0.5*x^2\n",
+    "\n",
+    "sample_model.add_component(gaussian)\n",
+    "sample_model.add_component(dho)\n",
+    "sample_model.add_component(lorentzian)\n",
+    "sample_model.add_component(polynomial)\n",
+    "\n",
+    "\n",
+    "x=np.linspace(-2, 2, 100)\n",
+    "\n",
+    "plt.figure()\n",
+    "y=sample_model.evaluate(x)\n",
+    "plt.plot(x, y, label='Sample Model')\n",
+    "\n",
+    "for component in list(sample_model):\n",
+    "    y = component.evaluate(x)\n",
+    "    plt.plot(x, y, label=component.name)\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d35179d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# sample_model=SampleModel(name='sample_model')\n",
+    "sample_model.components"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "newdynamics",
+   "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": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

src/easydynamics/convolution/__init__.py

@@ -0,0 +1,3 @@
+from .convolution import Convolution
+
+__all__ = ["Convolution"]