{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d660e1d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy.fftpack\n",
    "import netCDF4 as netcdf\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import display,clear_output\n",
    "import xarray as xr\n",
    "import os\n",
    "\n",
    "g = 9.80665 # gravitation constant"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22f09a7c",
   "metadata": {},
   "source": [
    "## Set model configuration parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "483bb3fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remember for python, so array index goes from 0 to nx-1 in x-direction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60644533",
   "metadata": {},
   "source": [
    "## Specify the grid:\n",
    "Select a grid size that allows the Poisson solver to be fast.\n",
    "\n",
    "2<sup>n</sup> +1 for `nx` and `nz` is ideal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c6bab9ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grid spacings in x and z directions:  40.0 40.0\n",
      "Courant number =      1.000\n"
     ]
    }
   ],
   "source": [
    "nx = 65 # number of grid points in horizontal\n",
    "nz = 65 # number of grid points in vertical\n",
    "\n",
    "lenx = 2560 # grid length in meters\n",
    "lenz = 2560 # grid height in meters\n",
    "\n",
    "# Calculate grid spacing dx, dz; Note: subtract number of points by 1 to account for endpoints.\n",
    "\n",
    "dx = lenx/(nx - 1.)\n",
    "dz = lenz/(nz - 1.)\n",
    "\n",
    "print( 'Grid spacings in x and z directions: ', dx, dz)\n",
    "\n",
    "tstop = 1000.0 # seconds\n",
    "\n",
    "dt = 4.0 # time step size in seconds\n",
    "\n",
    "Courant =  dt/dx * 10.0 # Courant number assiming max wind speed of 10 m/s. Should not exceed 1.\n",
    "\n",
    "print( \"Courant number = {0:10.3f}\".format(Courant) )\n",
    "\n",
    "numt = int( tstop/dt ) + 1 # number of times to advance time t\n",
    "\n",
    "theta0 = 300.\n",
    "\n",
    "thermradx = 0.2*lenx # Initial thermal bubble horizontal radius in m\n",
    "thermradz = 0.2*lenz # Initial thermal bubble vertical radius in m\n",
    "\n",
    "# Remember: python indicies start at 0\n",
    "thermx = 0.5*lenx # Initial horizontal position of thermal bubble \n",
    "thermz = 0.5*lenz # Initial vertical position of thermal bubble\n",
    "\n",
    "delpt = 5. # Thermal bubble perturbation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37fd3231",
   "metadata": {},
   "source": [
    "## Calculate 2-d advection of general variable b\n",
    "## m1 and p1 refer to minus and plus one respectively"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "188a7623",
   "metadata": {},
   "source": [
    "## Also explicitly calculate x, z, and t arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4d7555a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1D Courant number in x =      1.000\n"
     ]
    }
   ],
   "source": [
    "x_grid = np.arange(0,nx,1)*dx\n",
    "z_grid = np.arange(0,nz,1)*dz\n",
    "t_grid = np.arange(0,numt,1)*dt\n",
    "\n",
    "# Initalize state variable arrays to zero\n",
    "u = np.zeros((numt,nz,nx))\n",
    "w = np.zeros((numt,nz,nx))\n",
    "theta = np.zeros((numt,nz,nx)) # Note theta here is perturbations per governing equations\n",
    "\n",
    "u[:,:,:] = -10.0\n",
    "w[:,:,:] = 0.0\n",
    "\n",
    "umax = np.max( np.abs(u[0,:,:]) )\n",
    "Courant = dt/dx * umax # Courant number assiming max wind speed of 10 m/s. Should not exceed 1.\n",
    "print( \"1D Courant number in x = {0:10.3f}\".format(Courant) )\n",
    "\n",
    "# Initial thermal perturbation \n",
    "for i in np.arange(1,nx-1):\n",
    "    for k in np.arange(1,nz-1):\n",
    "        radnd = np.sqrt(((i*dx-thermx)/thermradx)**2.+((k*dx-thermz)/thermradz)**2.)\n",
    "        if(radnd < 1.):\n",
    "            theta[0,k,i] = theta[0,k,i] + delpt*(np.cos(radnd*np.pi/2.)**2.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1ba28780",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cal_advect_2d(u,w,bim1,bip1,bkm1,bkp1,b,dx,dz):\n",
    "\n",
    "    adv = -0.5*( ((u+np.absolute(u))*(b-bim1)+(u-np.absolute(u))*(bip1-b))/dx \\\n",
    "                +((w+np.absolute(w))*(b-bkm1)+(w-np.absolute(w))*(bkp1-b))/dz )\n",
    "    \n",
    "    return adv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e3966c9b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ptmin,ptmax at time      4 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time      8 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     12 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     16 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     20 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     24 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     28 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     32 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     36 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     40 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     44 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     48 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     52 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     56 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     60 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     64 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     68 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     72 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     76 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     80 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     84 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     88 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     92 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time     96 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    100 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    104 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    108 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    112 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    116 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    120 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    124 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    128 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    132 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    136 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    140 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    144 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    148 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    152 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    156 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    160 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    164 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    168 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    172 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    176 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    180 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    184 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    188 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    192 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    196 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    200 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    204 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    208 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    212 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    216 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    220 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    224 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    228 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    232 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    236 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    240 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    244 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    248 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    252 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    256 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    260 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    264 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    268 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    272 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    276 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    280 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    284 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    288 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    292 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    296 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    300 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    304 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    308 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    312 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    316 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    320 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    324 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    328 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    332 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    336 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    340 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    344 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    348 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    352 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    356 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    360 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    364 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    368 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    372 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    376 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    380 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    384 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    388 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    392 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    396 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    400 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    404 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    408 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    412 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    416 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    420 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    424 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    428 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    432 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    436 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    440 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    444 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    448 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    452 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    456 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    460 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    464 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    468 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    472 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    476 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    480 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    484 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    488 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    492 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    496 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    500 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    504 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    508 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    512 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    516 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    520 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    524 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    528 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    532 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    536 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    540 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    544 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    548 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    552 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    556 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    560 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    564 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    568 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    572 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    576 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    580 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    584 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    588 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    592 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    596 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    600 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    604 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    608 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    612 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    616 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    620 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    624 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    628 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    632 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    636 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    640 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    644 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    648 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    652 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    656 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    660 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    664 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    668 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    672 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    676 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    680 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    684 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    688 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    692 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    696 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    700 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    704 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    708 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    712 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    716 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    720 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    724 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    728 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    732 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    736 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    740 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    744 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    748 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    752 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    756 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    760 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    764 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    768 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    772 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    776 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    780 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    784 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    788 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    792 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    796 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    800 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    804 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    808 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    812 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    816 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    820 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    824 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    828 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    832 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    836 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    840 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    844 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    848 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    852 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    856 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    860 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    864 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    868 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    872 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    876 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    880 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    884 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    888 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    892 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    896 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    900 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    904 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    908 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    912 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    916 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    920 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    924 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    928 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    932 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    936 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    940 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    944 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    948 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    952 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    956 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    960 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    964 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    968 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    972 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    976 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    980 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    984 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    988 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    992 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time    996 (s) are:   0.00   5.00 \n",
      "ptmin,ptmax at time   1000 (s) are:   0.00   5.00 \n"
     ]
    }
   ],
   "source": [
    "# main time loop, horizontal loop, vertical loop\n",
    "# note that boundary points remain zero to satisfy boundary conditions\n",
    "for t in np.arange(0, numt-1, 1):\n",
    "\n",
    "    for i in np.arange(1, nx-1, 1):\n",
    "        for k in np.arange(1, nz-1, 1):\n",
    "             theta[t+1,k,i] = theta[t,k,i] - dt/dx * u[t, k,i ]*( theta[ t,k,i+1] - theta[t,k,i]   )# complete this line\n",
    "#\n",
    "# write alternative form of code that uses np.absolute(u) without if condition  \n",
    "#\n",
    "#           theta[t+1,k,i] = theta[t,k,i] - ...   # complete this line\n",
    "#\n",
    "#\n",
    "    time = (t+1) *  dt\n",
    "    \n",
    "# set periodic boundary condition for theta in x direction\n",
    "\n",
    "    theta[t+1,:,0] = theta[t+1,:,nx-2]\n",
    "    theta[t+1,:,nx-1] = theta[t+1,:,1]\n",
    "    \n",
    "    ptmax = np.max( theta[t+1,:,:] )\n",
    "    ptmin = np.min( theta[t+1,:,:] )\n",
    "\n",
    "    print(\"ptmin,ptmax at time {0:6.0f} (s) are: {1:6.2f} {2:6.2f} \".format(time,ptmin,ptmax) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a9d338b7-423a-4e47-8e72-0feb4aa1e732",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make plots\n",
    "# First construct figure and axes of plot\n",
    "fig_ex = plt.figure( figsize=(15, 17) )\n",
    "ax_ex = fig_ex.add_subplot(111)\n",
    "\n",
    "outdir='Cloud_pngs' \n",
    "if outdir and not os.path.exists(outdir): os.mkdir(outdir)\n",
    "\n",
    "# Time loop to display plots sequentially\n",
    "for t in np.arange(0,numt,5):\n",
    "    \n",
    "    # Clear prior axis data so plots don't stack on top of each other\n",
    "    ax_ex.clear()\n",
    "    \n",
    "    # Note arrays are (row,column...) in python indices. Since i is column and k is\n",
    "    # row in our model, we need to simply transverse 2-D arrays to align with the \n",
    "    # expected plots\n",
    "    \n",
    "    # Plot theta\n",
    "    \n",
    "#    sfmax = np.max( streamf[t,:,:] )\n",
    "#    sfmin = np.min( streamf[t,:,:] )\n",
    "    \n",
    "    #print(\"sfmin= {0:6.2f}, sfmax= {1:6.2f} at time {2:6.0f} (s)\".format(sfmin, sfmax,t*dt) )\n",
    "    \n",
    "    levels = [0.0,0.125,0.25,0.5,0.75,1.0,1.25,1.5,1.75,2.0,2.5,3.0,3.5,4.0,4.5,5.0]\n",
    "#    levels = np.arange(0,3.5,0.5)\n",
    "    \n",
    "    theta_plot = ax_ex.contourf(x_grid,z_grid,theta[t,:,:], levels=levels, extend='both')\n",
    "#    theta_plot = ax_ex.contourf(x_grid,z_grid,theta[t,:,:], extend='both')\n",
    "    \n",
    "    # Plot streamfunction (levels are contours, 'w' refers to white contours)\n",
    "    #streamf_plot = ax_ex.contour(x_grid,z_grid,streamf[t,:,:],\\\n",
    "    #        evels=np.array([-500,-400,-300,-250,-200,-150,-125,-100,-75,-50,-25,\\\n",
    "    #                        25,50,75,100,125,250,200,300,400,500]),colors='red')\n",
    "    \n",
    "#    streamf_plot = ax_ex.contour(x_grid,z_grid,streamf[t,:,:],\\\n",
    "#                                 levels=np.arange(-500,550,50),colors='red')\n",
    "    \n",
    "    # Plot wind vectors at windintv intervals (python slices arrays as [start:stop:interval])\n",
    "    windintv = 3 # Plot interval for wind vectors\n",
    "    vector_plot = ax_ex.quiver(x_grid[::windintv],z_grid[::windintv],\\\n",
    "                               u[t,::windintv,::windintv],w[t,::windintv,::windintv], color='white')\n",
    "    time = t*dt\n",
    "    plt.title('Simulated theta at time {0:6.1f} (s)'.format(time),fontsize=20 )\n",
    "    \n",
    "    if t == 0:\n",
    "        cb1 = fig_ex.colorbar(theta_plot, ax=ax_ex, location='bottom', shrink=1.0, fraction=0.05, pad=0.05)\n",
    "        cb1.set_label('(K)', size='x-large')\n",
    "\n",
    "    # Display plots\n",
    "    clear_output(wait=True)\n",
    "    display(fig_ex)\n",
    "    \n",
    "    if outdir: \n",
    "        timestamp = round(time,2)\n",
    "        pngname = outdir+'/cloud%06d.png' % round(timestamp) \n",
    "#        print( pngname )\n",
    "        plt.savefig(pngname, dpi=72, facecolor='w', edgecolor='w', orientation='portrait',bbox_inches = 'tight')\n",
    "    \n",
    "clear_output()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5044fce0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from janim import makeanim\n",
    "import glob\n",
    "\n",
    "pngs = glob.glob(outdir+'/*.png') # the * matches anything\n",
    "pngs.sort()\n",
    "makeanim(pngs,outfile=\"1DAdvection.html\",sortOrder=True,\n",
    "         ctlOnSide=True,titlestring=\"Animation of 1D Advection\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ad58b8ca-d479-44c0-90de-a0c34b504b04",
   "metadata": {},
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