notebooks/pygplates-Flowlines.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Flowlines\n",
    "This example details dynamic construction and plotting within a python script of synthetic flowlines generated from a plate model. For a general introduction to flowlines, see the GPlates user manual:\n",
    "\n",
    "http://www.gplates.org/user-manual/Flowlines.html\n",
    "\n",
    "The example goes through the case of creating flowline/motion path features within a script (assuming that we know enough to assign parameters like position of the seed points, plateid/conjugate plateid, and the time range and time sampling that we want for the feature). Then we can calculate motion paths for one (or several) rotation models, for different frames of reference.   \n",
    "\n",
    "The flowline example uses the Tasman Sea, which in the GPlates default reconstruction model opened from ~90 Ma to ~52 (Ma), with rotation parameters from the study of Gaina et al (1998), which are used in the Seton et al (2012) global compilation. The parameters we need to set to make a reasonable synthetic flowlines are as follows:\n",
    "\n",
    "   - The seed points - typically, points on a present day mid-ocean ridge or (in this case) an extinct ridge axis\n",
    "   - Plate IDs for the two plates that were spreading apart - in this case Australia (801) and the Lord Howe Rise (833)\n",
    "   - The time range for the spreading (or at least, the section of the spreading you want to visualise the flowline for)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pygplates\n",
    "\n",
    "import os\n",
    "data_root = \"Data\"\n",
    "if not os.path.isdir(data_root):\n",
    "    print(f'\"{data_root}\" is not a folder. Try to use \"../data\" instead.')\n",
    "    data_root = \"../data\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rotation file to be used to generate synthetic flowlines-only needs to be loaded in once\n",
    "rotation_filename = f'{data_root}/Seton_etal_ESR2012_2012.1.rot'\n",
    "\n",
    "# Parameters required to define a flowline (as in GPlates)\n",
    "SeedPoints = zip([-40,-43],[157,157.5])\n",
    "left_plate = 801\n",
    "right_plate = 833\n",
    "times = np.arange(0,90,1.)     # using numpy to get a list of times in 1 Myr increments\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a flowline feature\n",
    "The next section of codes generates a flowline feature within the script (analogous to the process in GPlates GUI of digitizing a new point and applying parameters to make it a flowline feature) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CREATE FLOWLINE\n",
    "# POINTS ON THE FLOWLINE\n",
    "multi_point = pygplates.MultiPointOnSphere(SeedPoints)\n",
    "\n",
    "# Create the flowline feature\n",
    "flowline_feature = pygplates.Feature.create_flowline(\n",
    "    multi_point,\n",
    "    times,\n",
    "    valid_time=(np.max(times), np.min(times)),\n",
    "    left_plate=left_plate,\n",
    "    right_plate=right_plate)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make the flowline for a chosen reconstruction model\n",
    "The flowline feature does not have any set flowline path, it is agnositic of rotation models. To make a synthetic flowline,  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load a rotation model (required to generate a synthetic flowline)\n",
    "rotation_model=pygplates.RotationModel(rotation_filename)\n",
    "\n",
    "# Reconstruct the flowline - we want it in present day coordinates\n",
    "reconstruction_time=0\n",
    "\n",
    "# Create an empty feature in which the reconstructed flowline geometries will be placed\n",
    "reconstructed_flowlines = []\n",
    "\n",
    "# Call pygplates to generate the flowline feature\n",
    "pygplates.reconstruct(flowline_feature, rotation_model, reconstructed_flowlines, reconstruction_time,\n",
    "                  anchor_plate_id=1, reconstruct_type=pygplates.ReconstructType.flowline)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualise the results\n",
    "A useful way of assessing synthetic flowlines against observations is to plot them overlain on maps showing seafloor fabric, ideally gravity anomaly maps of the oceans derived from satellite altimetry. The code below plots the flowlines over the (low resolution) etopo raster image distributed with Basemap.\n",
    "\n",
    "The flowline features are split into 'right' and 'left' sides, so plotting them takes a few lines of code that iterate over each half of each flowline.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 3600x3600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.io.shapereader as shpreader\n",
    "%matplotlib inline\n",
    "\n",
    "# Create figure\n",
    "fig = plt.figure(figsize=(12,12),dpi=300)\n",
    "pmap = fig.add_subplot(111, projection=ccrs.Mercator())\n",
    "pmap.set_extent([145, 170, -50, -30])\n",
    "\n",
    "# Create land and ocean features in greyscale\n",
    "pmap.coastlines(resolution='10m', color='white', linewidth=0.25)\n",
    "pmap.add_feature(cfeature.LAND, color = 'grey', edgecolor='grey')\n",
    "pmap.add_feature(cfeature.OCEAN, color='white')\n",
    "pmap.add_feature(cfeature.LAKES, color='white', edgecolor='white')\n",
    "\n",
    "# Iterate over the left and right sides that the flowline is split into.\n",
    "for reconstructed_flowline in reconstructed_flowlines:\n",
    "    \n",
    "    # Iterate over the left flowline points\n",
    "    # Create an empty array to hold left flowline points which we append over.\n",
    "    flowlinearray_left = np.empty([0,0])\n",
    "    # Access each left flowline from an array holding the flowline spread along the *left* plate from the \n",
    "    # reconstructed seed point.\n",
    "    for left_point in reconstructed_flowline.get_left_flowline():\n",
    "        # Append the initially empty flowlinearray_left array with the left points obtained from reconstructed_flowline\n",
    "        # which have been turned into values of a lat-lon array.\n",
    "        flowlinearray_left = np.append(flowlinearray_left, left_point.to_lat_lon_array())\n",
    "    \n",
    "    # Repeat this iteration for the right flowline points.\n",
    "    flowlinearray_right = np.empty([0,0])\n",
    "    for right_point in reconstructed_flowline.get_right_flowline():\n",
    "        flowlinearray_right = np.append(flowlinearray_right, right_point.to_lat_lon_array())\n",
    "\n",
    "    x,y = flowlinearray_left[1::2],flowlinearray_left[::2]\n",
    "\n",
    "    l1=pmap.plot(x, y, 'r', transform=ccrs.PlateCarree(), zorder=2)\n",
    "    l3=pmap.scatter(x, y, 30, c=times, transform=ccrs.PlateCarree(),\n",
    "                          cmap=plt.cm.gnuplot_r, edgecolor='none', zorder=1,vmin=50,vmax=90)\n",
    "\n",
    "    x,y = flowlinearray_right[1::2],flowlinearray_right[::2]\n",
    "    l1=pmap.plot(x, y, 'r', transform=ccrs.PlateCarree(), zorder=2)\n",
    "    l3=pmap.scatter(x, y, 30, c=times, transform=ccrs.PlateCarree(),\n",
    "                          cmap=plt.cm.gnuplot_r, edgecolor='none',zorder=1,vmin=50,vmax=90)\n",
    "\n",
    "\n",
    "# Set a colorbar to help visualise the passage of every millionth year.\n",
    "fig.colorbar(l3, ax=pmap).set_label('Age (Ma)',fontsize=12)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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