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  {
   "cell_type": "markdown",
   "id": "194dad49",
   "metadata": {},
   "source": [
    "From the outputs of `make_connectivity_matrices.ipynb`, generates gifs of connectivity matrices for a particular variation scheme."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0621ea42",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import imageio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "be8cc712",
   "metadata": {},
   "outputs": [],
   "source": [
    "# specify directory/directories with images to turn into gifs\n",
    "plot_dirs = ['connectivity_matrices_2021_10_27/']\n",
    "files = np.concatenate([[os.path.join(d, x) for x in os.listdir(d)] for d in plot_dirs])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "388dbb7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# group together matrices of a particular variation scheme\n",
    "# (ORN bootstrapping, LN bootstrapping, PN synapse density, etc.)\n",
    "ORN_conmats = [f for f in files if 'resample_ORN_conmat' in f and '.png' in f]\n",
    "LN_conmats = [f for f in files if 'resample_LN_conmat' in f and '.png' in f]\n",
    "PN_conmats = [f for f in files if 'resample_PN_conmat' in f and '.png' in f]\n",
    "PN_density_conmats = [f for f in files if 'resample_PN_densityconmat' in f and '.png' in f]\n",
    "ORN_LN_PN_conmats = [f for f in files if 'resample_ORN_LN_PN_conmat' in f and '.png' in f]\n",
    "ORN_LN_PN_PN_density_conmats = [f for f in files if 'resample_ORN_LN_PN_PN_densityconmat' in f and '.png' in f]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8b55019f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make names for output gifs\n",
    "all_conmat_sets = [ORN_conmats, LN_conmats, PN_conmats, PN_density_conmats, ORN_LN_PN_conmats, ORN_LN_PN_PN_density_conmats]\n",
    "conmat_set_names = ['ORN_bootstrapping', \n",
    "                    'LN_bootstrapping',\n",
    "                    'PN_bootstrapping',\n",
    "                    'PN_synapse_density',\n",
    "                    'ORN_LN_PN_bootstrapping',\n",
    "                    'ORN_LN_PN_bootstrapping_PN_synapse_density']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d6ccfc7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10, 10, 10, 10, 10, 10]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check how many will go into each gif\n",
    "[len(x) for x in all_conmat_sets]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3d35502b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# specify save directory\n",
    "save_dir = '../figures/supmovies_connectivity_matrices/'\n",
    "# make the directory if it doesn't exist already\n",
    "if not os.path.exists(save_dir):\n",
    "    os.makedirs(save_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6186b9a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "saved ORN_bootstrapping\n",
      "saved LN_bootstrapping\n",
      "saved PN_bootstrapping\n",
      "saved PN_synapse_density\n",
      "saved ORN_LN_PN_bootstrapping\n",
      "saved ORN_LN_PN_bootstrapping_PN_synapse_density\n"
     ]
    }
   ],
   "source": [
    "frame_duration = 0.5 # seconds\n",
    "\n",
    "n_sets = len(all_conmat_sets)\n",
    "for i in range(n_sets):\n",
    "    # get the set of connectivity matrices\n",
    "    conmat_set = all_conmat_sets[i]\n",
    "    conmat_set_name = conmat_set_names[i]\n",
    "    \n",
    "    # convert filenames to image arrays\n",
    "    filenames = conmat_set\n",
    "    images = list(map(lambda filename: imageio.imread(filename), filenames))\n",
    "    \n",
    "    # save gif\n",
    "    imageio.mimsave(os.path.join(save_dir, \n",
    "                                 'movie_{}.gif'.format(conmat_set_name)), \n",
    "                    images, duration = frame_duration)\n",
    "    \n",
    "    print('saved {}'.format(conmat_set_name))"
   ]
  }
 ],
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