geosphere_webplots.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e5360d0f-59e1-4f31-bc85-964706d0d021",
   "metadata": {
    "tags": []
   },
   "source": [
    "### GeoSphere website plots\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "geomagnetic storm statistics\n",
    "\n",
    "solar storm statistics\n",
    "\n",
    "aurora in Austria\n",
    "\n",
    "science examples\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec85c42d-c843-4476-9334-afe8adcac082",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "system is mac\n",
      "/Users/chris/python/data/insitu_python/\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import numpy as np\n",
    "import datetime\n",
    "from datetime import timedelta\n",
    "import seaborn as sns\n",
    "import urllib\n",
    "import pandas as pd\n",
    "import os\n",
    "import sys\n",
    "from numba import njit\n",
    "import importlib\n",
    "import copy\n",
    "import locale\n",
    "\n",
    "#Plotly imports\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.graph_objects as go\n",
    "import plotly.io as pio\n",
    "from plotly.offline import iplot, init_notebook_mode\n",
    "import plotly.express as px\n",
    "\n",
    "\n",
    "#import geosphere colors\n",
    "import colors as c\n",
    "\n",
    "\n",
    "#import heliocats files\n",
    "from heliocats import data as hd\n",
    "importlib.reload(hd) #reload again while debugging\n",
    "\n",
    "from heliocats import plot as hp\n",
    "importlib.reload(hp) #reload again while debugging\n",
    "\n",
    "###\n",
    "\n",
    "outputdir='results/geosphere_web/'\n",
    "\n",
    "##### check for system type\n",
    "#server\n",
    "if sys.platform == 'linux': \n",
    "    print('system is linux')\n",
    "    from config_server import data_path\n",
    "    matplotlib.use('Agg') \n",
    "   \n",
    "        \n",
    "#mac\n",
    "if sys.platform =='darwin':  \n",
    "    print('system is mac')\n",
    "    from config_local import data_path    \n",
    "    #matplotlib.use('Agg') \n",
    "    %matplotlib inline     \n",
    "\n",
    "print(data_path)\n",
    "\n",
    "\n",
    "os.system('jupyter nbconvert --to script geosphere_webplots.ipynb')    \n",
    "\n",
    "\n",
    "def add_logo(location):\n",
    "    logo = plt.imread('logo/GSA_Basislogo_Positiv_RGB_XXS.png')\n",
    "    newax = fig.add_axes(location, anchor='NE', zorder=1)\n",
    "    newax.imshow(logo)\n",
    "    newax.axis('off')\n",
    "\n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "99b56c55-593f-44b3-a3d3-6eb546e5a5df",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x1300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context('talk')\n",
    "sns.set_style('whitegrid')\n",
    "fig, ax1=plt.subplots(1,figsize=(20,13),dpi=100)\n",
    "\n",
    "\n",
    "ax1.plot(np.arange(10),np.arange(10),markersize=5,color=c.geo_green,lw=5)\n",
    "ax1.plot(np.arange(10)*2,np.arange(10),markersize=5,color=c.geo_lime,lw=5)\n",
    "ax1.plot(np.arange(10)*5,np.arange(10),markersize=5,color=c.geo_ocher,lw=5)\n",
    "\n",
    "\n",
    "add_logo([0.9,0.9,0.1,0.1])\n",
    "\n",
    "#plt.tight_layout()\n",
    "\n",
    "plt.savefig(outputdir+'test.png')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeda8eed-480b-44c6-a971-f6cfd7648cf4",
   "metadata": {},
   "source": [
    "Tabellenüberschrift\n",
    "Source Sans Pro Bold, 30 Px, Farbe: #052E37, RGB (5/46/55)\n",
    "2 Achsenbeschriftung\n",
    "Source Sans Pro Bold, 16 Px, Farbe: #052E37, RGB (5/46/55)\n",
    "3 Copyrightvermerk\n",
    "Source Sans Pro Bold, 16 Px, Farbe: #9AACAF, RGB (154/172/175)\n",
    "wenn möglich rechts unten (kein Logo!)\n",
    "4 Rahmen\n",
    "Breite: 1 Px, Farbe: #9AACAF, RGB (154/172/175)\n",
    "Wenn Grafiken im Content eingesetzt werden und sie auf weiß auslaufen, sollte man einen entsprechenden Rahmen zur opti- schen Begrenzung anlegen. Wenn sie in einem Slider zum Ein- satz kommen, kann dieser Rahmen auch weggelassen werden, da der Slider bereits selbst durch einen Rahmen begrenzt ist.\n",
    "5 Achsen\n",
    "Breite: 1 Px, Farbe: #052E37, RGB (5/46/55)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40b085c9-6bf1-41c5-b649-7b2bd8944088",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5be10e8-c855-44e0-85af-4590b0ed355a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.10.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}