{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Particle Cloud\n",
    "\n",
    "\n",
    "Using the same setup as `detailed_look.jl` or `example2()`, here we simulate\n",
    "a point cloud getting advected by the flow field.\n",
    "For additional documentation e.g. see :\n",
    "[1](https://JuliaClimate.github.io/IndividualDisplacements.jl/dev/),\n",
    "[2](https://JuliaClimate.github.io/MeshArrays.jl/dev/),\n",
    "[3](https://docs.juliadiffeq.org/latest/solvers/ode_solve.html),\n",
    "[4](https://en.wikipedia.org/wiki/Displacement_(vector))"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 1. Import Software"
   ],
   "metadata": {}
  },
  {
   "outputs": [],
   "cell_type": "code",
   "source": [
    "using IndividualDisplacements, Statistics\n",
    "\n",
    "import IndividualDisplacements.OrdinaryDiffEq: solve, Tsit5\n",
    "import IndividualDisplacements.DataFrames: DataFrame\n",
    "\n",
    "p=dirname(pathof(IndividualDisplacements))\n",
    "include(joinpath(p,\"../examples/more/example123.jl\"));"
   ],
   "metadata": {},
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 2. Setup Problem"
   ],
   "metadata": {}
  },
  {
   "outputs": [],
   "cell_type": "code",
   "source": [
    "𝑃,Γ=example2_setup()\n",
    "\n",
    "ii1=5:5:40; ii2=5:5:25\n",
    "x=vec([x-0.5 for x in ii1, y in ii2])\n",
    "y=vec([y-0.5 for x in ii1, y in ii2])\n",
    "xy = permutedims([[x[i];y[i];1.0] for i in eachindex(x)])\n",
    "\n",
    "solv(prob) = IndividualDisplacements.ensemble_solver(prob,solver=Tsit5(),reltol=1e-6,abstol=1e-6)\n",
    "tr = DataFrame(ID=Int[], x=Float64[], y=Float64[], t=Float64[])\n",
    "\n",
    "#𝐼 = Individuals{Float64,2}(📌=xy[:,:], 🔴=tr, 🆔=collect(1:size(xy,2)),"
   ],
   "metadata": {},
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "source": [
    "                        🚄 = dxdt!, ∫ = solv, 🔧 = postprocess_xy, 𝑃=𝑃);"
   ],
   "metadata": {}
  },
  {
   "outputs": [],
   "cell_type": "code",
   "source": [
    "I=(position=xy,record=deepcopy(tr),velocity=dxdt!,\n",
    "   integration=solv,postprocessing=postprocess_xy,parameters=𝑃)\n",
    "𝐼=Individuals(I)"
   ],
   "metadata": {},
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 3. Compute Trajectories"
   ],
   "metadata": {}
  },
  {
   "outputs": [],
   "cell_type": "code",
   "source": [
    "𝑇 = (0.0,2998*3600.0)\n",
    "∫!(𝐼,𝑇)"
   ],
   "metadata": {},
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 4. Display results"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Compare with trajectory output from `MITgcm`"
   ],
   "metadata": {}
  },
  {
   "outputs": [],
   "cell_type": "code",
   "source": [
    "#IndividualDisplacements.flt_example_download()\n",
    "#df=read_flt(IndividualDisplacements.flt_example_path,Float32)\n",
    "#ref=plot_paths(df,size(xy,2),100000.0)"
   ],
   "metadata": {},
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "source": [
    "---\n",
    "\n",
    "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*"
   ],
   "metadata": {}
  }
 ],
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