Experimental PH-TESS notebook

A modification of the 1D sonification notebook. It replaces the generated 1D data with a couple of simulated TESS light curves from Planet Hunters TESS.
james-trayford · Dec 19, 2023 · ec235ea · ec235ea
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diff --git a/examples/SonifyingDataTESS.ipynb b/examples/SonifyingDataTESS.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "03b73a45",
+   "metadata": {},
+   "source": [
+    "## <u> Demonstrate some generic techniques for sonifying 1D data:</u>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "37f21355",
+   "metadata": {},
+   "source": [
+    "**First, import relevant modules:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f64e736a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%reload_ext autoreload \n",
+    "%autoreload 2\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "from strauss.sonification import Sonification\n",
+    "from strauss.sources import Objects\n",
+    "from strauss import channels\n",
+    "from strauss.score import Score\n",
+    "from strauss.generator import Synthesizer\n",
+    "import IPython.display as ipd\n",
+    "import os\n",
+    "from scipy.interpolate import interp1d\n",
+    "import numpy as np\n",
+    "import requests\n",
+    "import json"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c4a3e9c2-e9e3-48ca-a21c-0ae64bb549f6",
+   "metadata": {},
+   "source": [
+    "**Now, we load some test data!**\n",
+    "\n",
+    "We use a simulated subject from the PH-TESS dataset (subject 94880899 or subject 94880882):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fbf7b1b5-79b7-4a2a-a8e9-15f196a15ca6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "s94880899 = 'https://panoptes-uploads.zooniverse.org/subject_location/03caefe6-7d48-4225-9cc0-e5a60f337af8.txt'\n",
+    "s94880882 = 'https://panoptes-uploads.zooniverse.org/subject_location/7578bd5d-b8da-4c42-8da7-5f897ded018e.txt'\n",
+    "response = json.loads(requests.get(s94880882).text)\n",
+    "days = np.array(response['x'])\n",
+    "normalised_days = lambda d: d / days.max()\n",
+    "x = np.array(list(map(normalised_days, days)))\n",
+    "normalised_flux = map(lambda f: f + 0.5,response['y'])\n",
+    "y = np.array(list(normalised_flux))\n",
+    "\n",
+    "\n",
+    "plt.plot(x,y)\n",
+    "plt.ylabel('Normalised flux')\n",
+    "plt.xlabel('Days')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d0f6edf6-59bf-4bdc-a9e7-c7f097cd08d3",
+   "metadata": {},
+   "source": [
+    "**Set up some universal sonification parameters and classes for the examples below**\n",
+    "\n",
+    "For all examples we use the `Synthesizer` generator to create a 30 second, mono sonification."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "009d6c9a-fb4c-4cd9-a87d-ccae4f280d89",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# specify audio system (e.g. mono, stereo, 5.1, ...)\n",
+    "system = \"stereo\"\n",
+    "\n",
+    "# length of the sonification in s\n",
+    "length = 15.\n",
+    "\n",
+    "# set up synth and turn on LP filter\n",
+    "generator = Synthesizer()\n",
+    "generator.load_preset('pitch_mapper')\n",
+    "generator.preset_details('pitch_mapper')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7a7b7ed-6da8-4694-8aef-df00a7277d42",
+   "metadata": {},
+   "source": [
+    "### <u>Example 1</u> &nbsp; **Pitch Mapping**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c92480b-345a-4212-883c-b9eded4060d5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "notes = [[\"A2\"]]\n",
+    "score =  Score(notes, length)\n",
+    "\n",
+    "data = {'pitch':1.,\n",
+    "        'time_evo':x,\n",
+    "        'azimuth':(x*0.5+0.25) % 1,\n",
+    "        'polar':0.5,\n",
+    "        'pitch_shift':y**0.7}\n",
+    "\n",
+    "# set up source\n",
+    "sources = Objects(data.keys())\n",
+    "sources.fromdict(data)\n",
+    "sources.apply_mapping_functions()\n",
+    "\n",
+    "soni = Sonification(score, sources, generator, system)\n",
+    "soni.render()\n",
+    "soni.notebook_display()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "285b12a8-ef64-49f9-a851-b011bde05e29",
+   "metadata": {},
+   "source": [
+    "### <u>Example 2</u> &nbsp; **Volume Mapping**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7bed74fc-a506-47d7-aff1-0ea6e200bd8a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "notes = [[\"A2\"]]\n",
+    "score =  Score(notes, length)\n",
+    "\n",
+    "data = {'pitch':1.,\n",
+    "        'time_evo':x,\n",
+    "        'azimuth':(x*0.5+0.25) % 1,\n",
+    "        'polar':0.5,\n",
+    "        'volume':y**0.7}\n",
+    "\n",
+    "# set up source\n",
+    "sources = Objects(data.keys())\n",
+    "sources.fromdict(data)\n",
+    "sources.apply_mapping_functions()\n",
+    "\n",
+    "soni = Sonification(score, sources, generator, system)\n",
+    "soni.render()\n",
+    "soni.notebook_display()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25f17dd1-fe8c-4b61-8a15-4a3cedb646b4",
+   "metadata": {},
+   "source": [
+    "### <u>Example 3</u> &nbsp; **Filter Cutoff Mapping**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a1efde9b-c4c9-4c0f-b4c5-9d32a2098fb1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generator = Synthesizer()\n",
+    "generator.modify_preset({'filter':'on'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a583f3bd-b57b-4448-8cf2-d30de234a3bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "notes = [[\"C2\",\"G2\",\"C3\",\"G3\"]]\n",
+    "score =  Score(notes, length)\n",
+    "\n",
+    "data = {'pitch':[0,1,2,3],\n",
+    "        'time_evo':[x]*4,\n",
+    "        'azimuth':[(x*0.5+0.25) % 1]*4,\n",
+    "        'polar':[0.5]*4,\n",
+    "        'cutoff':[y**0.8]*4}\n",
+    "\n",
+    "# set up source\n",
+    "sources = Objects(data.keys())\n",
+    "sources.fromdict(data)\n",
+    "sources.apply_mapping_functions()\n",
+    "\n",
+    "soni = Sonification(score, sources, generator, system)\n",
+    "soni.render()\n",
+    "soni.notebook_display()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17785113-03f2-4f3a-824c-9c3d93ed1530",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generator = Synthesizer()\n",
+    "generator.load_preset('windy')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d001083d-e5d8-4308-bcc2-f775d963395a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = {'pitch':[0,1,2,3],\n",
+    "        'time_evo':[x],\n",
+    "        'azimuth':[(x*0.5+0.25) % 1],\n",
+    "        'polar':[0.5],\n",
+    "        'cutoff':[y**0.8]}\n",
+    "sources = Objects(data.keys())\n",
+    "sources.fromdict(data)\n",
+    "sources.apply_mapping_functions()\n",
+    "\n",
+    "soni = Sonification(score, sources, generator, system)\n",
+    "soni.render()\n",
+    "soni.notebook_display()"
+   ]
+  }
+ ],
+ "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": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}