ssim.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9e1dedfb76a02ac1",
   "metadata": {},
   "source": [
    "# Structural Similarity of Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4c6a1672108c3ccc",
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "/home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/zmq/backend/cython/../../../../.././libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/pypocketfft.cpython-311-x86_64-linux-gnu.so)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 7\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mnn\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mparallel\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m DataParallel \u001b[38;5;28;01mas\u001b[39;00m DP\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnetwork\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpatch_visualizer\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m PatchVisualizer\n\u001b[1;32m      8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnetwork\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m MaskedGAN\n\u001b[1;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnetwork\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgenerators\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m PatchUNet\n",
      "File \u001b[0;32m~/Documents/DEV/NoStripesNet/network/patch_visualizer.py:6\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata_io\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m loadTiff\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtomography\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m reconstruct\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m toTensor, toNumpy, rescale\n\u001b[1;32m      8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvisualizers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseGANVisualizer\n",
      "File \u001b[0;32m~/Documents/DEV/NoStripesNet/utils/tomography.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mtp\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmpi4py\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m MPI\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mh5py\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m File\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/tomopy/__init__.py:68\u001b[0m\n\u001b[1;32m     65\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m     67\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_fft_loader\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fft_impl\n\u001b[0;32m---> 68\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcorr\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m     69\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmorph\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m     70\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mphantom\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/tomopy/misc/corr.py:64\u001b[0m\n\u001b[1;32m     62\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumexpr\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mne\u001b[39;00m\n\u001b[1;32m     63\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mconcurrent\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfutures\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mcf\u001b[39;00m\n\u001b[0;32m---> 64\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msignal\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m medfilt2d\n\u001b[1;32m     66\u001b[0m logger \u001b[38;5;241m=\u001b[39m logging\u001b[38;5;241m.\u001b[39mgetLogger(\u001b[38;5;18m__name__\u001b[39m)\n\u001b[1;32m     68\u001b[0m __author__ \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDoga Gursoy, William Judge\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/signal/__init__.py:311\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;124;03m=======================================\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;124;03mSignal processing (:mod:`scipy.signal`)\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    307\u001b[0m \n\u001b[1;32m    308\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    309\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m\n\u001b[0;32m--> 311\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _sigtools, windows\n\u001b[1;32m    312\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_waveforms\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m    313\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_max_len_seq\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m max_len_seq\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/signal/windows/__init__.py:42\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;124;03mWindow functions (:mod:`scipy.signal.windows`)\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;124;03m==============================================\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     39\u001b[0m \n\u001b[1;32m     40\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m---> 42\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_windows\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m     44\u001b[0m \u001b[38;5;66;03m# Deprecated namespaces, to be removed in v2.0.0\u001b[39;00m\n\u001b[1;32m     45\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m windows\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/signal/windows/_windows.py:7\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m linalg, special, fft \u001b[38;5;28;01mas\u001b[39;00m sp_fft\n\u001b[1;32m      9\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mboxcar\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtriang\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mparzen\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbohman\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mblackman\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnuttall\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     10\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mblackmanharris\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mflattop\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbartlett\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbarthann\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     11\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhamming\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mkaiser\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mkaiser_bessel_derived\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgaussian\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     12\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgeneral_cosine\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgeneral_gaussian\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgeneral_hamming\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     13\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mchebwin\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcosine\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhann\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mexponential\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtukey\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtaylor\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     14\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdpss\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mget_window\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlanczos\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m     17\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_len_guards\u001b[39m(M):\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/__init__.py:189\u001b[0m, in \u001b[0;36m__getattr__\u001b[0;34m(name)\u001b[0m\n\u001b[1;32m    187\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getattr__\u001b[39m(name):\n\u001b[1;32m    188\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m submodules:\n\u001b[0;32m--> 189\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_importlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimport_module\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mscipy.\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    190\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    191\u001b[0m         \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/importlib/__init__.py:126\u001b[0m, in \u001b[0;36mimport_module\u001b[0;34m(name, package)\u001b[0m\n\u001b[1;32m    124\u001b[0m             \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[1;32m    125\u001b[0m         level \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m--> 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_bootstrap\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_gcd_import\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m[\u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpackage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/__init__.py:92\u001b[0m\n\u001b[1;32m     90\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_fftlog\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fhtoffset\n\u001b[1;32m     91\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_fftlog_multimethods\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fht, ifht\n\u001b[0;32m---> 92\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_helper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m next_fast_len\n\u001b[1;32m     93\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_backend\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (set_backend, skip_backend, set_global_backend,\n\u001b[1;32m     94\u001b[0m                        register_backend)\n\u001b[1;32m     95\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfft\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fftfreq, rfftfreq, fftshift, ifftshift\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_helper.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfunctools\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m update_wrapper, lru_cache\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_pocketfft\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m helper \u001b[38;5;28;01mas\u001b[39;00m _helper\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnext_fast_len\u001b[39m(target, real\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m      7\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Find the next fast size of input data to ``fft``, for zero-padding, etc.\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \n\u001b[1;32m      9\u001b[0m \u001b[38;5;124;03m    SciPy's FFT algorithms gain their speed by a recursive divide and conquer\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     60\u001b[0m \n\u001b[1;32m     61\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\" FFT backend using pypocketfft \"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbasic\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mrealtransforms\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhelper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/basic.py:6\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mfunctools\u001b[39;00m\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m pypocketfft \u001b[38;5;28;01mas\u001b[39;00m pfft\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhelper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (_asfarray, _init_nd_shape_and_axes, _datacopied,\n\u001b[1;32m      8\u001b[0m                      _fix_shape, _fix_shape_1d, _normalization,\n\u001b[1;32m      9\u001b[0m                      _workers)\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mc2c\u001b[39m(forward, x, n\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, norm\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, overwrite_x\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m     12\u001b[0m         workers\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m, plan\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n",
      "\u001b[0;31mImportError\u001b[0m: /home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/zmq/backend/cython/../../../../.././libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/pypocketfft.cpython-311-x86_64-linux-gnu.so)"
     ]
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "import numpy as np\n",
    "\n",
    "import torch\n",
    "from torch.nn.parallel import DataParallel as DP\n",
    "\n",
    "from network.patch_visualizer import PatchVisualizer\n",
    "from network.models import MaskedGAN\n",
    "from network.models.generators import PatchUNet\n",
    "from network.models.discriminators import PatchDiscriminator\n",
    "from utils.metrics import structural_similarity\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3fb332f4b39c5a9",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f8702d5eb2c57da",
   "metadata": {},
   "source": [
    "### Helper Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1fc7535e4dfafd1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_model(path, device=None):\n",
    "    # Load model state dict from disk\n",
    "    checkpoint = torch.load(path, map_location=device)\n",
    "    # Initialize Generator and Discriminator\n",
    "    gen = DP(PatchUNet())\n",
    "    gen.load_state_dict(checkpoint['gen_state_dict'])\n",
    "    disc = DP(PatchDiscriminator())\n",
    "    disc.load_state_dict(checkpoint['disc_state_dict'])\n",
    "    # Initialize Model\n",
    "    model = MaskedGAN(gen, disc, mode='test', device=device)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7566bf7995623138",
   "metadata": {},
   "source": [
    "### Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f487f5401b5d7543",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample No.: 0\n"
     ]
    }
   ],
   "source": [
    "i12 = Path('/media/algol/HD-LXU3/No_stripes_net_data')\n",
    "data_dir = i12/'data'/'wider_stripes'\n",
    "model_file = i12/'pretrained_models'/'five_sample'/'4x4'/'val'/'five_sample_4x4_100.tar'\n",
    "mask_file = i12/'stripe_masks.npz'\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    d = torch.device('cuda')\n",
    "else:\n",
    "    d = torch.device('cpu')\n",
    "\n",
    "rng = np.random.default_rng()\n",
    "cor = 1253\n",
    "sample_no = 0\n",
    "print(f\"Sample No.: {sample_no}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13318509f480143b",
   "metadata": {},
   "source": [
    "## Load Model & Visualizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9d49f8f0",
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "/home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/zmq/backend/cython/../../../../.././libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/pypocketfft.cpython-311-x86_64-linux-gnu.so)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnetwork\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpatch_visualizer\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m PatchVisualizer\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnetwork\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m MaskedGAN\n",
      "File \u001b[0;32m~/Documents/DEV/NoStripesNet/network/patch_visualizer.py:6\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata_io\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m loadTiff\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtomography\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m reconstruct\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m toTensor, toNumpy, rescale\n\u001b[1;32m      8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvisualizers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseGANVisualizer\n",
      "File \u001b[0;32m~/Documents/DEV/NoStripesNet/utils/tomography.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mtp\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmpi4py\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m MPI\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mh5py\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m File\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/tomopy/__init__.py:68\u001b[0m\n\u001b[1;32m     65\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m     67\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_fft_loader\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fft_impl\n\u001b[0;32m---> 68\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcorr\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m     69\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmorph\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m     70\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtomopy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmisc\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mphantom\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/tomopy/misc/corr.py:64\u001b[0m\n\u001b[1;32m     62\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumexpr\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mne\u001b[39;00m\n\u001b[1;32m     63\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mconcurrent\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfutures\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mcf\u001b[39;00m\n\u001b[0;32m---> 64\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01msignal\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m medfilt2d\n\u001b[1;32m     66\u001b[0m logger \u001b[38;5;241m=\u001b[39m logging\u001b[38;5;241m.\u001b[39mgetLogger(\u001b[38;5;18m__name__\u001b[39m)\n\u001b[1;32m     68\u001b[0m __author__ \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDoga Gursoy, William Judge\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/signal/__init__.py:311\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;124;03m=======================================\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;124;03mSignal processing (:mod:`scipy.signal`)\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    307\u001b[0m \n\u001b[1;32m    308\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    309\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m\n\u001b[0;32m--> 311\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m _sigtools, windows\n\u001b[1;32m    312\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_waveforms\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m    313\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_max_len_seq\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m max_len_seq\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/signal/windows/__init__.py:42\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;124;03mWindow functions (:mod:`scipy.signal.windows`)\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;124;03m==============================================\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     39\u001b[0m \n\u001b[1;32m     40\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m---> 42\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_windows\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m     44\u001b[0m \u001b[38;5;66;03m# Deprecated namespaces, to be removed in v2.0.0\u001b[39;00m\n\u001b[1;32m     45\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m windows\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/signal/windows/_windows.py:7\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mwarnings\u001b[39;00m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m linalg, special, fft \u001b[38;5;28;01mas\u001b[39;00m sp_fft\n\u001b[1;32m      9\u001b[0m __all__ \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mboxcar\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtriang\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mparzen\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbohman\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mblackman\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnuttall\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     10\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mblackmanharris\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mflattop\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbartlett\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbarthann\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     11\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhamming\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mkaiser\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mkaiser_bessel_derived\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgaussian\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     12\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgeneral_cosine\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgeneral_gaussian\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgeneral_hamming\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     13\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mchebwin\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcosine\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhann\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mexponential\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtukey\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtaylor\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m     14\u001b[0m            \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdpss\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mget_window\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlanczos\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m     17\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_len_guards\u001b[39m(M):\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/__init__.py:189\u001b[0m, in \u001b[0;36m__getattr__\u001b[0;34m(name)\u001b[0m\n\u001b[1;32m    187\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getattr__\u001b[39m(name):\n\u001b[1;32m    188\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m submodules:\n\u001b[0;32m--> 189\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_importlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimport_module\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mscipy.\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    190\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    191\u001b[0m         \u001b[38;5;28;01mtry\u001b[39;00m:\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/importlib/__init__.py:126\u001b[0m, in \u001b[0;36mimport_module\u001b[0;34m(name, package)\u001b[0m\n\u001b[1;32m    124\u001b[0m             \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[1;32m    125\u001b[0m         level \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m--> 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_bootstrap\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_gcd_import\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m[\u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpackage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/__init__.py:92\u001b[0m\n\u001b[1;32m     90\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_fftlog\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fhtoffset\n\u001b[1;32m     91\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_fftlog_multimethods\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fht, ifht\n\u001b[0;32m---> 92\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_helper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m next_fast_len\n\u001b[1;32m     93\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_backend\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (set_backend, skip_backend, set_global_backend,\n\u001b[1;32m     94\u001b[0m                        register_backend)\n\u001b[1;32m     95\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfft\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m fftfreq, rfftfreq, fftshift, ifftshift\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_helper.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfunctools\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m update_wrapper, lru_cache\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_pocketfft\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m helper \u001b[38;5;28;01mas\u001b[39;00m _helper\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnext_fast_len\u001b[39m(target, real\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m      7\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Find the next fast size of input data to ``fft``, for zero-padding, etc.\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \n\u001b[1;32m      9\u001b[0m \u001b[38;5;124;03m    SciPy's FFT algorithms gain their speed by a recursive divide and conquer\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     60\u001b[0m \n\u001b[1;32m     61\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\" FFT backend using pypocketfft \"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbasic\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mrealtransforms\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhelper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/basic.py:6\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mfunctools\u001b[39;00m\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m pypocketfft \u001b[38;5;28;01mas\u001b[39;00m pfft\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mhelper\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (_asfarray, _init_nd_shape_and_axes, _datacopied,\n\u001b[1;32m      8\u001b[0m                      _fix_shape, _fix_shape_1d, _normalization,\n\u001b[1;32m      9\u001b[0m                      _workers)\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mc2c\u001b[39m(forward, x, n\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, norm\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, overwrite_x\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m     12\u001b[0m         workers\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m, plan\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n",
      "\u001b[0;31mImportError\u001b[0m: /home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/zmq/backend/cython/../../../../.././libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by /home/algol/miniconda3/envs/pytorch/lib/python3.11/site-packages/scipy/fft/_pocketfft/pypocketfft.cpython-311-x86_64-linux-gnu.so)"
     ]
    }
   ],
   "source": [
    "from network.patch_visualizer import PatchVisualizer\n",
    "from network.models import MaskedGAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "05a549e5",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'v' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mlen\u001b[39m(\u001b[43mv\u001b[49m\u001b[38;5;241m.\u001b[39mclean_idxs)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'v' is not defined"
     ]
    }
   ],
   "source": [
    "len(v.clean_idxs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f82fed955d457cc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = load_model(model_file, device=d)\n",
    "v = PatchVisualizer(data_dir, model, sample_no=sample_no, mask_file=mask_file,\n",
    "                    full_sino_size=(1801, 2560), patch_size=(1801, 256))\n",
    "\n",
    "# `v.clean_idxs` contains naturally clean sinograms\n",
    "# `v.stripe_idxs` contains naturally stripey sinograms\n",
    "# Can only do SSIM for artificial stripes, as no ground truth for natural stripes\n",
    "\n",
    "# 'sro' means stripe regions only\n",
    "clean_sinos = []\n",
    "clean_sro = []\n",
    "stripe_sinos = []\n",
    "stripe_sro = []\n",
    "model_sinos = []\n",
    "model_sro = []\n",
    "for i in v.clean_idxs:\n",
    "    clean_sino = v.get_sinogram(i, 'clean')\n",
    "    stripe_sino = v.get_sinogram(i, 'stripe')\n",
    "    model_sino = v.get_model_sinogram(i)\n",
    "    mask = v.mask[:, i, :].asype(np.bool_)\n",
    "    \n",
    "    clean_sinos.append(clean_sino)\n",
    "    stripe_sinos.append(stripe_sino)\n",
    "    model_sinos.append(model_sino)\n",
    "    clean_sro.append(clean_sino[mask])\n",
    "    stripe_sro.append(stripe_sino[mask])\n",
    "    model_sro.append(model_sino[mask])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71a127132a14a277",
   "metadata": {},
   "source": [
    "## Calculate Structural Similarity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c6ddca35c2bd877",
   "metadata": {},
   "source": [
    "### SSIM from Clean to Model Outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c5373190e905be8",
   "metadata": {},
   "source": [
    "#### Whole Sinograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ce90ef8af00d5f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_sino_ssim = structural_similarity(clean_sinos, model_sinos)\n",
    "print(f\"SSIM from Clean to Model Outputs, Whole Sinograms: {model_sino_ssim}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f959ed716fd3343",
   "metadata": {},
   "source": [
    "#### Stripe Regions Only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42577064ce941258",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_sro_ssim = structural_similarity(clean_sro, model_sro)\n",
    "print(f\"SSIM from Clean to Model Outputs, Stripe Regions Only: {model_sro_ssim}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7baf5daef91de1",
   "metadata": {},
   "source": [
    "### SSIM from Clean to Stripe Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc20520c92aa7423",
   "metadata": {},
   "source": [
    "#### Whole Sinograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d74b646e87a6c5b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "control_sino_ssim = structural_similarity(clean_sinos, stripe_sinos)\n",
    "print(f\"SSIM from Clean to Stripe Data, Whole Sinograms: {control_sino_ssim}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0ae3011dea923ce",
   "metadata": {},
   "source": [
    "#### Stripe Regions Only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "164e0315c1d25f94",
   "metadata": {},
   "outputs": [],
   "source": [
    "control_sro_ssim = structural_similarity(clean_sro, model_sro)\n",
    "print(f\"SSIM from Clean to Stripe Data, Stripe Regions Only: {control_sro_ssim}\")"
   ]
  }
 ],
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