From 0cfaa6433cebd0af63091ddbb48d539b06f01cd1 Mon Sep 17 00:00:00 2001 From: Christopher Mayes <31023527+ChristopherMayes@users.noreply.github.com> Date: Tue, 7 Nov 2023 14:53:22 -0800 Subject: [PATCH] Example docs --- docs/examples/bunching.ipynb | 344 +++++++++++++++++++++++++++++++++++ mkdocs.yml | 1 + 2 files changed, 345 insertions(+) create mode 100644 docs/examples/bunching.ipynb diff --git a/docs/examples/bunching.ipynb b/docs/examples/bunching.ipynb new file mode 100644 index 0000000..dab1a06 --- /dev/null +++ b/docs/examples/bunching.ipynb @@ -0,0 +1,344 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d6490636-6e3c-4d4b-9122-394a314e10d3", + "metadata": {}, + "source": [ + "# Bunching\n", + "\n", + "Bunching at some wavelength $\\lambda$ for a list of particles $z$ is given by the weighted sum of complex phasors:\n", + "\n", + "$$B(z, \\lambda) = \\frac{\\left|\\sum_j w_j e^{i k z_j}\\right|}{\\sum w_j}$$\n", + "\n", + "where $k = 2\\pi/\\lambda$ and $w_j$ are the weights of the particles.\n", + "\n", + "See for example [D. Ratner's disseratation](https://www.osti.gov/servlets/purl/1443197). " + ] + }, + { + "cell_type": "markdown", + "id": "c72d25c9-ec8d-4a3a-88ef-e6aba001d113", + "metadata": {}, + "source": [ + "## Add bunching to particles\n", + "\n", + "This uses a simple method to add perfect bunching at 0.1 µm" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "89d98045-89b5-4d05-a1b3-33f956ba329c", + "metadata": {}, + "outputs": [], + "source": [ + "from pmd_beamphysics import ParticleGroup\n", + "%config InlineBackend.figure_format = 'retina'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "2808d05b-41dc-44eb-ac98-ae00ec7ba97b", + "metadata": {}, + "outputs": [], + "source": [ + "P = ParticleGroup( 'data/bmad_particles2.h5')\n", + "P.drift_to_t()\n", + "\n", + "wavelength = 0.1e-6\n", + "dz = (P.z/wavelength % 1) * wavelength\n", + "P.z -= dz" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f92a71d1-2804-4fba-a38b-3089351a910d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 438, + "width": 562 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "P.plot('z')" + ] + }, + { + "cell_type": "markdown", + "id": "ecc456e2-226a-426f-82f3-6f20ce9a4441", + "metadata": {}, + "source": [ + "## Calculate bunching\n", + "\n", + "All of these methods will calculate the bunching." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "95d51518-4dad-478d-a67f-4416e5e5a989", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P.bunching(wavelength)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "9a0ba850-3e57-4b70-b0d1-31376166da55", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P['bunching_0.1e-6']" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "1627bba1-710e-47b6-b923-9c64a6d32903", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P['bunching_0.1_um']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "8e93a423-a3bc-4eac-9832-46888bd23f24", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "P['bunching_0.1_µm']" + ] + }, + { + "cell_type": "markdown", + "id": "0d8186ef-a9ab-4db8-8963-b7bc1bdb9365", + "metadata": {}, + "source": [ + "# Simple plot" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "d24b9496-e828-45f1-a055-4e27e7aeba31", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "c6b5c501-bfdd-492d-891e-ba10e6b546ef", + "metadata": {}, + "outputs": [], + "source": [ + "wavelengths = wavelength * np.linspace(0.9, 1.1, 200)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "50cda5af-4a97-4aa0-bf9c-c3984140d39c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'bunching')" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 432, + "width": 569 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(wavelengths*1e6, list(map(P.bunching, wavelengths)))\n", + "plt.xlabel('wavelength (µm)')\n", + "plt.ylabel('bunching')" + ] + }, + { + "cell_type": "markdown", + "id": "8a0a3ee9-3fbe-4299-ba9f-7055cf2869ab", + "metadata": {}, + "source": [ + "## Bunching function\n", + "\n", + "This is the function that is used." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "ac7ee4c6-1b02-40a1-96a3-3be6629da002", + "metadata": {}, + "outputs": [], + "source": [ + "from pmd_beamphysics.statistics import bunching" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "af2982d8-a19d-481f-b9ec-940d5d02e290", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\u001b[0;31mSignature:\u001b[0m \u001b[0mbunching\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwavelength\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mDocstring:\u001b[0m\n", + "Calculate the normalized bunching parameter, which is the magnitude of the \n", + "complex sum of weighted exponentials at a given point.\n", + "\n", + "The formula for bunching is given by:\n", + "\n", + "$$\n", + "B(z, \\lambda) = \f", + "rac{\\left|\\sum w_i e^{i k z_i}\r", + "ight|}{\\sum w_i}\n", + "$$\n", + "\n", + "where:\n", + "- \\( z \\) is the position array,\n", + "- \\( \\lambda \\) is the wavelength,\n", + "- \\( k = \f", + "rac{2\\pi}{\\lambda} \\) is the wave number,\n", + "- \\( w_i \\) are the weights.\n", + "\n", + "Parameters\n", + "----------\n", + "z : np.ndarray\n", + " Array of positions where the bunching parameter is calculated.\n", + "wavelength : float\n", + " Wavelength of the wave.\n", + "weight : np.ndarray, optional\n", + " Weights for each exponential term. Default is 1 for all terms.\n", + "\n", + "Returns\n", + "-------\n", + "float\n", + " The normalized bunching parameter.\n", + "\n", + "Raises\n", + "------\n", + "ValueError\n", + " If `wavelength` is not a positive number.\n", + "\u001b[0;31mFile:\u001b[0m ~/Code/GitHub/openPMD-beamphysics/pmd_beamphysics/statistics.py\n", + "\u001b[0;31mType:\u001b[0m function\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "?bunching" + ] + } + ], + "metadata": { + "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": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/mkdocs.yml b/mkdocs.yml index e09ca80..f1c1265 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -12,6 +12,7 @@ nav: - examples/read_examples.ipynb - examples/write_examples.ipynb - examples/plot_examples.ipynb + - examples/bunching.ipynb - Fields: - examples/fields/field_examples.ipynb - examples/fields/field_expansion.ipynb