{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Exercise 9.2\n", "Large arrays of radio antennas can be used to measure cosmic rays by recording the electromagnetic radiation generated in the atmosphere.\n", "These radio signals are strongly contaminated by galactic noise as well as signals from human origin. Since these signals appear to be similar to the background, the discovery of cosmic-ray events can be challenging.\n", "## Identification of signals\n", "In this exercise, we design an RNN to classify if the recorded radio signals contain a cosmic-ray event or only noise.\n", "\n", "The signal-to-noise ratio (SNR) of a measured trace $S(t)$ is defined as follows:\n", "\n", "$$\\mathrm{SNR}=\\frac{S^{\\mathrm{signal}}(t)_\\mathrm{max}}{\\mathrm{RMS}[S(t)]},$$ \n", "where $S^{\\mathrm{signal}}(t)_\\mathrm{max}$ denotes the maximum amplitude of the (true) signal.\n", "\n", "Typical cosmic-ray observatories enable a precise reconstruction at an SNR of roughly 3.\n", "\n", "We choose a challenging setup in this task and try to identify cosmic-ray events in signal traces with an SNR of 2. \n", "Training RNNs can be computationally demanding, thus, we recommend to use a GPU for this task." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "keras version 2.4.0\n" ] } ], "source": [ "import tensorflow as tf\n", "from tensorflow import keras\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "layers = keras.layers\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Load and prepare dataset\n", "In this task, we use a simulation of cosmic-ray-induced air showers that are measured by radion antennas. \n", "For more information, see https://arxiv.org/abs/1901.04079. \n", "The task is to design an RNN which is able to identify if the measured signal traces (shortened to 500 time steps) contains a signal or not." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import os\n", "import gdown\n", "url = \"https://drive.google.com/u/0/uc?export=download&confirm=HgGH&id=1R-qfxO1jVh88TC9Gnm9JGMomSRg0Zpkx\"\n", "output = 'radio_data.npz'\n", "\n", "if os.path.exists(output) == False:\n", " gdown.download(url, output, quiet=True)\n", "\n", "f = np.load(output)\n", "n_train = 40000\n", "\n", "x_train, x_test = f[\"traces\"][:n_train], f[\"traces\"][n_train:] # measured traces (signal + colored noise)\n", "signals = f[\"signals\"] # signal part (only available for cosmic-ray events)\n", "\n", "labels = (signals.std(axis=-1) != 0).astype(float) # define training label (1=cosmic event, 0=noise)\n", "y_train, y_test = labels[:n_train], labels[n_train:]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot example signal traces\n", "Left: signal trace containing a cosmic-ray event. The underlying cosmic-ray signal is shown in red, the backgrounds + signal is shown in blue.\n", "Right: background noise." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from matplotlib import pyplot as plt\n", "fs = 180e6 # Sampling frequency of antenna setup 180 MHz\n", "t = np.arange(500) / fs * 1e6\n", "idx = np.random.randint(0, labels.sum()-1)\n", "idx2 = np.random.randint(0, n_train - labels.sum())\n", "\n", "plt.figure(1, (12, 4))\n", "plt.subplot(1, 2, 1)\n", "plt.plot(t, np.real(f[\"traces\"][labels.astype(bool)][idx]), linewidth = 1, color=\"b\", label=\"Measured trace\")\n", "plt.plot(t, np.real(signals[labels.astype(bool)][idx]), linewidth = 1, color=\"r\", label=\"CR signal\")\n", "plt.ylabel('Amplitude / mV')\n", "plt.xlabel('Time / $\\mu \\mathrm{s}$')\n", "plt.legend()\n", "plt.title(\"Cosmic-ray event\")\n", "plt.subplot(1, 2, 2)\n", "\n", "plt.plot(t, np.real(x_train[~y_train.astype(bool)][idx2]), linewidth = 1, color=\"b\", label=\"Measured trace\")\n", "plt.ylabel('Amplitude / mV')\n", "plt.xlabel('Time / $\\mu \\mathrm{s}$')\n", "plt.legend()\n", "plt.title(\"Noise event\")\n", "\n", "plt.grid(True)\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define RNN model\n", "In the following, design a cosmic-ray model to identify cosmic-ray events using an RNN-based classifier." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model = keras.models.Sequential()\n", "model.add(...)\n", "\n", "model.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Pre-processing of data and RNN training" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "sigma = x_train.std()\n", "x_train /= sigma\n", "x_test /= sigma" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model.compile(...)\n", "\n", "\n", "results = model.fit(x_train[...,np.newaxis], y_train, ...)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model.evaluate(x_test[...,np.newaxis], y_test)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot loss and accuracy" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plt.figure(1, (12, 4))\n", "plt.subplot(1, 2, 1)\n", "plt.plot(results.history['loss'])\n", "plt.plot(results.history['val_loss'])\n", "plt.ylabel('loss')\n", "plt.xlabel('epoch')\n", "plt.legend(['train', 'val'], loc='upper right')\n", "\n", "plt.subplot(1, 2, 2)\n", "plt.plot(results.history['accuracy'])\n", "plt.plot(results.history['val_accuracy'])\n", "plt.ylabel('accuracy')\n", "plt.xlabel('epoch')\n", "plt.legend(['train', 'val'], loc='upper left')\n", "plt.tight_layout()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 4 }