heatmap_generation.ipynb

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    "import pandas as pd \n",
    "import datashader.transfer_functions as tf\n",
    "import datashader as ds\n",
    "from collections import OrderedDict as odict\n",
    "from sqlalchemy import create_engine\n",
    "from shapely import wkt\n",
    "\n",
    "import gdal"
   ]
  },
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   "source": [
    "# /scratch/krodriguez/kaguyageoms.csv was generated with the query:\n",
    "# \\copy (Select st_x(geom) as x, st_y(geom) as y From kaguyasp.points) To '/scratch/krodriguez/kaguyageoms.csv' With CSV header\n",
    "\n",
    "df = pd.read_csv(\"/scratch/krodriguez/kaguyageoms.csv\")"
   ]
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   "execution_count": 3,
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   "source": [
    "# change the size here to control granularity,\n",
    "# we aren't so much making a heatmap so much as a 2-D histogram, but works well for our purposes.\n",
    "# Probably look much better when all points a loaded. \n",
    "\n",
    "hist = ds.Canvas(plot_width=400, plot_height=200).points(df,'x','y')\n",
    "\n",
    "# colorblind safe cmap from: https://colorbrewer2.org/#type=diverging&scheme=RdBu&n=11\n",
    "colors = ['#67001f','#b2182b','#d6604d','#f4a582','#fddbc7','#d1e5f0','#92c5de','#4393c3','#2166ac','#053061'][::-1]\n",
    "hist = tf.shade(hist, cmap=colors, how='linear', alpha=255, min_alpha=40)\n",
    "\n",
    "# comment out this line to print image in jupyter, just careful if you are making a very large image\n",
    "hist"
   ]
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   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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   "source": [
    "# Save to disk\n",
    "from PIL import ImageFilter\n",
    "\n",
    "itiff = '/home/krodriguez/heatmap.tif'\n",
    "img = hist.to_pil()\n",
    "\n",
    "# img = img.filter(ImageFilter.GaussianBlur(1))\n",
    "img.save(open(itiff, 'bw'))"
   ]
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  {
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   "execution_count": 9,
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   "source": [
    "temp = '/tmp/tmp.tif'\n",
    "otiff = '/home/krodriguez/heatmap_spatial.tif'\n",
    "\n",
    "# Add spatial data to the image\n",
    "# sometimes this is flakey and you have to run the command's equivilent opn the command line \n",
    "_ = gdal.Translate(otiff, itiff, outputBounds= (0, 90, 360, -90), outputSRS='EPSG:4326')"
   ]
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