2022-07-25_caustique.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pip in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 4)) (22.2.1)\n",
      "Requirement already satisfied: matplotlib in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 5)) (3.5.2)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 6)) (1.23.1)\n",
      "Requirement already satisfied: MotionClouds in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 7)) (20200212)\n",
      "Requirement already satisfied: imageio in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 8)) (2.20.0)\n",
      "Requirement already satisfied: pygifsicle in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 9)) (1.0.5)\n",
      "Requirement already satisfied: lambda2color in /usr/local/lib/python3.9/site-packages (from -r requirements.txt (line 10)) (1.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (2.8.2)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (4.30.0)\n",
      "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (20.9)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (2.4.7)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (9.0.1)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (1.3.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/site-packages (from matplotlib->-r requirements.txt (line 5)) (0.10.0)\n",
      "Requirement already satisfied: six in /usr/local/lib/python3.9/site-packages (from cycler>=0.10->matplotlib->-r requirements.txt (line 5)) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install --upgrade -r requirements.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# caustique d'onde"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from IPython.display import display\n",
    "import numpy as np\n",
    "import MotionClouds as mc\n",
    "from caustique import init, Caustique\n",
    "figpath = '2022-07-25_caustique'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving our simulations in=2022-07-25_caustique\n"
     ]
    }
   ],
   "source": [
    "print(f'Saving our simulations in={figpath}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "opt = init()\n",
    "opt.figpath = figpath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Namespace(tag='caustique', figpath='2022-07-25_caustique', vext='mp4', nx=256, ny=256, nframe=160, bin_dens=2, bin_spectrum=6, seed=42, H=6.0, variation=0.4, sf_0=0.006, B_sf=0.002, V_Y=0.3, V_X=0.3, B_V=4.0, theta=2.399988291783386, B_theta=1.0471975511965976, min_lum=0.2, gamma=2.4, fps=18, multispectral=True, cache=False, verbose=False)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "%rm -fr {figpath}"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "%rm -fr {figpath}/*.{opt.vext}"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "%rm -fr /tmp/{figpath} "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# une simple caustique"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## a wave pattern"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "c = Caustique(opt)\n",
    "wave_videoname = f'{opt.figpath}/{opt.tag}_wave'\n",
    "if not os.path.isfile(f'{wave_videoname}{c.mc.vext}'):\n",
    "    print(f'Doing {wave_videoname}{c.mc.vext}')\n",
    "    z = c.wave()\n",
    "    c.mc.anim_save(z.swapaxes(0, 1), wave_videoname)\n",
    "c.show(f'{wave_videoname}{c.mc.vext}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## generating caustics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(256, 256, 160)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = Caustique(opt)\n",
    "z = c.wave()\n",
    "z.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(81, 13)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "N_wavelengths = len(c.cs_srgb.cmf[:, 0])\n",
    "N_wavelengths, N_wavelengths//c.opt.bin_spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 0\n",
      "1 6\n",
      "2 12\n",
      "3 18\n",
      "4 24\n",
      "5 30\n",
      "6 36\n",
      "7 42\n",
      "8 48\n",
      "9 54\n",
      "10 60\n",
      "11 66\n",
      "12 72\n",
      "13 78\n"
     ]
    }
   ],
   "source": [
    "for ii, i in enumerate(range(0, N_wavelengths, c.opt.bin_spectrum)): print(ii, i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "videoname = f'{opt.figpath}/{opt.tag}.{opt.vext}'\n",
    "if not os.path.isfile(videoname):\n",
    "    c = Caustique(opt)\n",
    "    z = c.wave()\n",
    "    videoname = c.plot(z, videoname=videoname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique.mp4\" type=\"video/mp4\" width=1024\\>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c.show(videoname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(256, 256, 160)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## exploring parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_scan = 9\n",
    "base = 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 5.000\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_5.000.mp4\n"
     ]
    },
    {
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      ]
     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 5.946\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_5.946.mp4\n"
     ]
    },
    {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 7.071\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_7.071.mp4\n"
     ]
    },
    {
     "data": {
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 8.409\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_8.409.mp4\n"
     ]
    },
    {
     "data": {
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       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_H_8.409.mp4\" type=\"video/mp4\" width=1024\\>"
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       "<IPython.core.display.HTML object>"
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 10.000\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_10.000.mp4\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_H_10.000.mp4\" type=\"video/mp4\" width=1024\\>"
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     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 11.892\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_11.892.mp4\n"
     ]
    },
    {
     "data": {
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       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_H_11.892.mp4\" type=\"video/mp4\" width=1024\\>"
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       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 14.142\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_14.142.mp4\n"
     ]
    },
    {
     "data": {
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 16.818\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_16.818.mp4\n"
     ]
    },
    {
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     },
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H = 20.000\n",
      "2022-07-25_caustique 2022-07-25_caustique/caustique_H_20.000.mp4\n"
     ]
    },
    {
     "data": {
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       "<IPython.core.display.HTML object>"
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     "metadata": {},
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   ],
   "source": [
    "opt = init()\n",
    "opt.figpath = figpath\n",
    "opt.H = 10.\n",
    "opt.variation = .09\n",
    "\n",
    "c = Caustique(opt)\n",
    "# compute just once\n",
    "z = c.wave()\n",
    "\n",
    "for H_ in c.opt.H*np.logspace(-1, 1, N_scan, base=base):\n",
    "    opt = init()\n",
    "    opt.figpath = figpath\n",
    "    c = Caustique(opt)\n",
    "\n",
    "    print(f'H = {H_:.3f}')\n",
    "    c.opt.H = H_\n",
    "    c.opt.tag = f'{opt.tag}_H_{H_:.3f}'\n",
    "    videoname = f'{opt.figpath}/{c.opt.tag}.{opt.vext}'\n",
    "    print(c.opt.figpath, videoname)\n",
    "    if not os.path.isfile(videoname):\n",
    "        url=c.plot(z, videoname=videoname)\n",
    "    c.show(videoname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "variation = 0.009\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_variation_0.009.mp4\" type=\"video/mp4\" width=1024\\>"
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      ]
     },
     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "variation = 0.016\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_variation_0.016.mp4\" type=\"video/mp4\" width=1024\\>"
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "variation = 0.028\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_variation_0.028.mp4\" type=\"video/mp4\" width=1024\\>"
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     "metadata": {},
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     "output_type": "stream",
     "text": [
      "variation = 0.051\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_variation_0.051.mp4\" type=\"video/mp4\" width=1024\\>"
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     "text": [
      "variation = 0.090\n"
     ]
    },
    {
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      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_variation_0.090.mp4\" type=\"video/mp4\" width=1024\\>"
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     "text": [
      "variation = 0.160\n"
     ]
    },
    {
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     "name": "stdout",
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     "text": [
      "variation = 0.285\n"
     ]
    },
    {
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    {
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     "text": [
      "variation = 0.506\n"
     ]
    },
    {
     "data": {
      "text/html": [
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "variation = 0.900\n"
     ]
    },
    {
     "data": {
      "text/html": [
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   ],
   "source": [
    "opt = init()\n",
    "opt.figpath = figpath\n",
    "opt.H = 10.\n",
    "opt.variation = .09\n",
    "\n",
    "c = Caustique(opt)\n",
    "# compute just once\n",
    "z = c.wave()\n",
    "\n",
    "for variation_ in opt.variation*np.logspace(-1, 1, N_scan, base=10, endpoint=True):\n",
    "    opt = init()\n",
    "    opt.figpath = figpath\n",
    "    c = Caustique(opt)\n",
    "\n",
    "    print(f'variation = {variation_:.3f}')\n",
    "    c.opt.variation = variation_\n",
    "    c.opt.tag = f'{opt.tag}_variation_{variation_:.3f}'\n",
    "    videoname = f'{opt.figpath}/{c.opt.tag}.{opt.vext}'\n",
    "    if not os.path.isfile(videoname):\n",
    "        url=c.plot(z, videoname=videoname)\n",
    "    c.show(videoname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======sf_0======\n",
      "sf_0=sf_0(default)*0.500=3.000E-03\n"
     ]
    },
    {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*0.595=3.568E-03\n"
     ]
    },
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*0.707=4.243E-03\n"
     ]
    },
    {
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     "text": [
      "sf_0=sf_0(default)*0.841=5.045E-03\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*1.000=6.000E-03\n"
     ]
    },
    {
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       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_sf_0_modul_1.000.mp4\" type=\"video/mp4\" width=1024\\>"
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     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*1.189=7.135E-03\n"
     ]
    },
    {
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       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_sf_0_modul_1.189.mp4\" type=\"video/mp4\" width=1024\\>"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*1.414=8.485E-03\n"
     ]
    },
    {
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      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_sf_0_modul_1.414.mp4\" type=\"video/mp4\" width=1024\\>"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*1.682=1.009E-02\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_sf_0_modul_1.682.mp4\" type=\"video/mp4\" width=1024\\>"
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       "<IPython.core.display.HTML object>"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sf_0=sf_0(default)*2.000=1.200E-02\n"
     ]
    },
    {
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      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_sf_0_modul_2.000.mp4\" type=\"video/mp4\" width=1024\\>"
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======B_sf======\n",
      "B_sf=B_sf(default)*0.500=1.000E-03\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_B_sf_modul_0.500.mp4\" type=\"video/mp4\" width=1024\\>"
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     "output_type": "stream",
     "text": [
      "B_sf=B_sf(default)*0.595=1.189E-03\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_B_sf_modul_0.595.mp4\" type=\"video/mp4\" width=1024\\>"
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B_sf=B_sf(default)*0.707=1.414E-03\n"
     ]
    },
    {
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      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_B_sf_modul_0.707.mp4\" type=\"video/mp4\" width=1024\\>"
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B_sf=B_sf(default)*0.841=1.682E-03\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_B_sf_modul_0.841.mp4\" type=\"video/mp4\" width=1024\\>"
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    {
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     "output_type": "stream",
     "text": [
      "B_sf=B_sf(default)*1.000=2.000E-03\n"
     ]
    },
    {
     "data": {
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       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_B_sf_modul_1.000.mp4\" type=\"video/mp4\" width=1024\\>"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B_sf=B_sf(default)*1.189=2.378E-03\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<video  loop=\"1\" autoplay=\"1\" controls  src=\"2022-07-25_caustique/caustique_B_sf_modul_1.189.mp4\" type=\"video/mp4\" width=1024\\>"
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B_sf=B_sf(default)*1.414=2.828E-03\n",
      "B_sf=B_sf(default)*1.682=3.364E-03\n",
      "B_sf=B_sf(default)*2.000=4.000E-03\n"
     ]
    }
   ],
   "source": [
    "for variable in ['sf_0', 'B_sf']: #, 'theta', 'B_theta', 'V_X', 'V_Y', 'B_V']:\n",
    "    print(f'======{variable}======')\n",
    "    for modul in np.logspace(-1, 1, N_scan, base=base):\n",
    "        opt = init()\n",
    "        opt.figpath = figpath\n",
    "\n",
    "        c = Caustique(opt)\n",
    "        c.d[variable] *= modul\n",
    "        c.opt.tag = f'{opt.tag}_{variable}_modul_{modul:.3f}'\n",
    "        videoname = f'{opt.figpath}/{c.opt.tag}.{opt.vext}'\n",
    "\n",
    "        print(f'{variable}={variable}(default)*{modul:.3f}={c.d[variable]:.3E}')\n",
    "        if os.path.isfile(videoname): c.show(videoname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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