initial upload

test/old_tests/inversion_2/check_src_rec_file.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.append(\"../../utils/\")\n",
+    "\n",
+    "from src_rec_file_helper import read_src_rec_file\n",
+    "\n",
+    "events_true = read_src_rec_file(\"./src_rec_test_out.dat\")\n",
+    "events_calc = read_src_rec_file(\"./src_rec_test_out_out.dat\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# check objective function value\n",
+    "v_obj = 0.0\n",
+    "for i_ev in range(len(events_true)):\n",
+    "    for i_rec in range(len(events_true[i_ev].rec_list)):\n",
+    "        v_obj += abs(events_true[i_ev].rec_list[i_rec].arr_time - events_calc[i_ev].rec_list[i_rec].arr_time)**2/2.0\n",
+    "\n",
+    "print(\"v_obj: \", v_obj)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate summation of difference of arrival times at each receiver\n",
+    "list_diff_v_obj = []\n",
+    "for i_ev in range(len(events_true)):\n",
+    "    for i_rec in range(len(events_true[i_ev].rec_list)):\n",
+    "        #tmp_v_obj = abs(events_true[i_ev].rec_list[i_rec].arr_time - events_calc[i_ev].rec_list[i_rec].arr_time)**2/2.0\n",
+    "        tmp_v_obj = events_true[i_ev].rec_list[i_rec].arr_time - events_calc[i_ev].rec_list[i_rec].arr_time\n",
+    "\n",
+    "        if (i_ev == 0):\n",
+    "            list_diff_v_obj.append(tmp_v_obj)\n",
+    "        else:\n",
+    "            list_diff_v_obj[i_rec] += tmp_v_obj\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plot list_diff_v_obj on map\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "# colormap by list_diff_v_obj\n",
+    "cmap = plt.get_cmap('viridis')\n",
+    "norm = plt.Normalize(vmin=min(list_diff_v_obj), vmax=max(list_diff_v_obj))\n",
+    "\n",
+    "print(\"min: \", min(list_diff_v_obj))\n",
+    "print(\"max: \", max(list_diff_v_obj))\n",
+    "\n",
+    "list_lon = []\n",
+    "list_lat = []\n",
+    "\n",
+    "for i_rec in range(len(events_true[0].rec_list)):\n",
+    "    list_lon.append(events_true[0].rec_list[i_rec].lon)\n",
+    "    list_lat.append(events_true[0].rec_list[i_rec].lat)\n",
+    "\n",
+    "plt.scatter(list_lon, list_lat, c=list_diff_v_obj, cmap=cmap, norm=norm)\n",
+    "\n",
+    "# color bar\n",
+    "plt.colorbar()\n",
+    "\n",
+    "# tight \n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.1 64-bit ('3.9.1')",
+   "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": "3.9.1"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}