helper file for previewing mat

utilities/mat_preview.ipynb

@@ -0,0 +1,315 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5c8aa3fd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.io import loadmat as scipy_loadmat\n",
+    "from mat73 import loadmat as mat73_loadmat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "4a419040",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f = \"../results/fold_slice/Niter10.mat\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "405b77b4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['__header__', '__version__', '__globals__', 'outputs', 'probe', 'object', 'p', '__function_workspace__'])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contents = scipy_loadmat(f)\n",
+    "contents.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "8a7b58b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(403, 403, 20)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contents['object'].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "9846eb96",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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 truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAGFCAYAAAASI+9IAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjYsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvq6yFwwAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs/cmWPMmS5of9RNUGn2L4TzncseYCGo1uEBtiQS75Qjx8DB6+AV+CK3LJLQEQRAPoruqq6lt3yuE/xeSjmakKFyKq5pG3bneDrEbfIF3PyZOZER7u5maqMnzyySeiqsplXdZlXdZlXRYQ/mNfwGVd1mVd1mX94ayLU7isy7qsy7qsui5O4bIu67Iu67LqujiFy7qsy7qsy6rr4hQu67Iu67Iuq66LU7isy7qsy7qsui5O4bIu67Iu67LqujiFy7qsy7qsy6qr+fd94Z/+H/9P/yGv47Iu67Iu67L+A6+/+z/87/+dr7lkCpd1WZd1WZdV18UpXNZlXdZlXVZdF6dwWZd1WZd1WXVdnMJlXdZlXdZl1XVxCpd1WZd1WZdV18UpXNZlXdZlXVZdF6dwWZd1WZd1WXVdnMJlXdZlXdZl1XVxCpd1WZd1WZdV18UpXNZlXdZlXVZdF6dwWZd1WZd1WXVdnMJlXdZlXdZl1XVxCpd1WZd1WZdV18UpXNZlXdZlXVZdF6dwWZd1WZd1WXVdnMJlXdZlXdZl1XVxCpd1WZd1WZdV18UpXNZlXdZlXVZdF6dwWZd1WZd1WXVdnMJlXdZlXdZl1XVxCpd1WZd1WZdV18UpXNZlXdZlXVZdF6dwWZd1WZd1WXVdnMJlXdZlXdZl1XVxCpd1WZd1WZdV18UpXNZlXdZlXVZdzX/sC7isy/qPsvTsv+U/2lVc1mX9wa2LU7is/++X8u9vWPUH//+/hEH+4Wf+u35/cRKX9f/H6wIfvdT17zJ0/0t+vvyen5//TP89f/dve+3/J9f4P/d9/rEcwr/v5+rv+e/Luqz/SOv/dzOF3xO9qviP1f67LPnB4dQw/1xlfoFksf8PClmQdPZ3Yn9X3p/zf//w2gACqCgIiIpd8rkhE/tvyeUann9W+Y4q9pp6DTJftyiQf/B35/dHfvee1HuRf8+f+f3RH9xfyb97rZLnz/h3ZhTl9/759VrO78cPX6/z9WqY/1/DD17/Dzmx8789uxf1us/eS8Pze3z++b83tNIfvPbsb589s9/3t2fP6H9WNvZvW7/vXl7WZfl6mU7hf066//uMQfazFubXFIMmAOnMuEfQM2tV/0vspIqCJNA4f041aGdGgKD+2TI7pWJQJpAzI1iMbrlkyZBbhQCS5Nnn1K+nfl1BUb8uFfvYcn3V+EW16yhfAyCDBJDJfpYbv77M7CDK/VL7nPIeWr6szo7g3KjKuWGT+Ts+e1TBLiaM8szgawQt90793kV3pkns3p05guoUz5/5mbOp1/jDfeH3jiz195KYP09lfl5nzlr9Psj0g/cs391fm+P8LMv7SP7BfTjbM9Uhlu9UrqXh2f1B5udTnaH/TH5wn38YtJTvqWfPpd6P4tDDWXBUL4yzZ/97HNy5w/yhU/t9meZl/UdfL88p/L4U+98WkfODTe2/K9GrZDM8udyNfPaa4AYJ5jdww16MjuJGr/xN1OpsVCAkeW5szqJRRSiJiCQ3HAHC6E7mPJIX/5naG0s99Go/d2chSarBEM4ObDGGCtpBbhRJs6FF7Gcx2Xcr0XG19+5MtAEZBRmFMPrf9TI7kPLd/HuGqfztDwzImUGdjZTUvw3JbV9r97N8r/IsNCjq1yvuVO3+gIzm4HJbDDqEcX7vci+rQU9+7X6zw2TfvzhGyUKY5r2SOvt5Dbwn+xtUzHmf7avzAECDgth9e5bNlHuRfI941iX1mnTen+cZlc6vK7+XdHZtxTCfOXLNYvf2/Pq1ODjm4MUfYBj9Y9v5d+DXe74Py9fRM8f8g4CL80BIn/+7OrByRv4BJ1Uc6nlmd+48y6pn/TwQO3PGz9CAH57JM0f47DrPAzzOfu+/O7+XL3m9PKfww3T8/OdnD+8ZDAJQYJ6zaLkc2hpJlT+Qs0j+bHOeR/HFyNcoSs8MQDGmWdBGbb9Wg+0GJ7oDEEXVDmkYBV3q/DU8itSGZ46qXHs1Bq0bIlHCyaO3AqXU17ihndw4Jsgd1QBpBG3MKNWMgucRoB1aM8YSmKEzhXi071MiUQ3lu0p1cNNKzVE9O5BCGOx1GtXuiRsyhWqQK5xz7nTKtYbZwEo6i37PHLpMUh2DBmVa2nWEQWo0HNwxaDCnR6sQzeBLPnNKQc0B+HMIY/C9pO6ofM8MZ9+1OMiSBZ05WyJkd3o1W/Vr0ghhgJLyKfactGRJAeTkv1d9DoeVdWaky3fI7fxCUT8f/t2q0ff9YDfQ92r0gKBs0lw/Yv4Pnff4+R6qR/QHwdocfM2/+x3Y0QOcEijVz8k/+K7MTtGuz89gLOHX7372s/v1A4NfbcUPgspn8OwPnEa9Fec2SH/393+o6+U5hX/o5p4dvBI5Q9lQ8wauxsKj8Wo0hLMDz1lURY3eyM8/VyapcAcqc4SazcCBG0WPwqsDaimBvr3dJPMGFjdAzJ91Hs2ICpqYjZ8bQAHi5MatYY7GS+R8HnF5tE+YoyIpBnEUtLGIs2x2OTv0on6pbmC1OJoEKdq/ZZzvbe7sL1WEaZ0hQDxKhUHqMxFIndbvlFtqtsREvdZnsAZAa5937pxqFHkGy8gkNEepe0KjG8jp7PVnjrY8z9xAHHxvCORYLprZkba+R86i2+pQxb+DBwzq0Bxi90bDnJEgnjGV98DuZ24h9epZZflsIRSnUvZNgngScuOZXJqfv0b1a5LZEYndl5LFSbZr0yg1QLCoXSFIdYqWWZ59RzCHUj6rONgSNHhGcm4c6/Py19YMqvw4nWXhJRspn1G+3+SvOzPiOfgHBKk/4yxb+eEeKYHG+T6staOz7OXfZsyrAy8v+6HDq//z+9/jD229PKcAzz1zMV5aNuSZkS/rDK4oD65i1EnOMFeZd1DdNFINSG79V88M5pkzwQ5Gbt3A/QCzLxGZuvEm45CEoKKkTmskn/0wF1ipHKRiiMW/Y4VzJnvNM0xZ53+fZ0Xn2UcYzYkVPDyhtQaR2/lei3g0n+zehUlIal4iN5A7tex8MENTlzshyULcz1mDJMgOiZT7H4sDcviFLBbZR4O1gt+DXBxdzZb8wSYlt2eOtRiyApm58cn++XGQGZ5idhg1Ik7zPa5wnDvf3LihzpB7h2RG/8wSlSsVYsu9kro5ICkQVTy6MxevAbkBD1OxNPqDgKdke36v/JpzVOJJELHIuEb/LTCKJQDFqPo1yGTfpziAMNn1173hTqBkLOfGvOz3HLxmle3zfidyPt+LOp+FEryUzKTCg8Gi+jB6IIY8c7iSBfUzWuo85fmag5uDLD1/Ztg1a+PPspzNsk/Psplzx25vxPPXUgIBeQZBn39n9Rv+LKN4IetlOYUfPqiymeom1GosSiQnP4ioKmumPs3ZgAR8U5X38LcsWUI5lNkP3Xm2INk2QI5aoSXgecR2llmUKF89usmdORMdHCv3SEumEu3xPHo5y4jqRmzsoBRIBP+a6oYSPXs/sXTaIkD7+2k1G79z41WiOw12nRpBk86Ra3EivZKDokNwOGx2zs3BYJBqYDwypcHuF5B65gJsErSF5EZMg8IgxEGQMNdsSvRYoKpENqN2Dsf4folHu+Bxo4aPq0fj7iQtsymf79+p0xoBxxNegNcaNMggNRq3iFas8P0DuMuyD60BhuDOvzUDGE/FuPteK8a4wCp1/2qFLavxOnPMZc+U18vkNS0155fKPvLry63WbDKVLFMt65Dke7rV5wXx4mD8b7XAWPns3BRnWgx0cWxnz8MclzuetlyTBUg1Wg/zv8szD4N9n9wpkv36eV7bKOdkJl9Qa33nhJJcoF7O9hP8zvd9Vlc7Pxd+xmpNsaxzhOIFOQR4YU6hGLLzyN9+7hsgixtKjxZEQeTZwy3/If4kNdohK5uibgaBXIxunKMKFccnxzkLUGZqqhkieeawqv8p/+07rBQmtVEzNOXqHIsNk32f3HqE4+/PmSEHL0q7UwjT8xS/GiwvLhYnVw8tZ9d69h3y0q+pRDt+f84Lp9VxZWASmrE8kGL05VnxMPXmOGTEHJIKYVRSYdPAcxZPPYjm6IrRCaOQRUn9HClqB81eabeBtFCm60zcORTmDpszR5L7TBoDcRTLVgr+Xb6j74O00GrYc2MPMrfUzEuYI1170fxcShCSOzWH50Z6vi9KWpxbFnc6AtNSHcpTd3DumI5CPJozsffUuu8LAaA92T0psNNsvZihGIeb1CGx8zpMjfbLc5b5Z7mdv6v4XguFFRWwzESxiP/MUKob5TBJdUgCFQbKohWKq+91ZkxLAJEd+gsTRqw4e01uytlihpbcaWq5sWcW+lnB2IvQtdYyzXu5Ot+z12s++3JuZ86h7fNAtMLRP3Qcf6DrRTkF8Ht7duh+yBAo+G9NEX+YuiYsxfa/r28SLMLj/OGXB+8RmhlGZ6HoWSbwDxTISkSez5gztpllpheW108FM7WTks8KfM8KeufRVihw1kwLrc4iYKlzFsKk5CDPU9iS9SgO36gbTy+E+vcKOju7Ah+EEzPu6vc7t1qLtHP9Rs7qC4rGmbpbPyNjzKGSTXkWUVg08ViMkczF+X420mAOMQ7CuMnkTmif7H2CR7rFYeaI7XZRyzZSqMZghnCUtKTCagXGUVFCsoI4oThaZkaN4+K5gZi0PpviyIsRDQ5X5XWeoS01qJB+Noa5V4cWxWpSZ/uqOUjdW/FIrQGgfn0wO3vMEZcMJQz+twWCmjxL8j1VitUzFKoVrtQK1T3fk+WZ1fNUAiuH/Oo6D+DKs6Ykifo7r9czwgABSDNklgsRopACzlKDQtcttOoCaxFno21kiLMA8+zn5XkV01DLine truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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 truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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 truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "for layer in np.permute_dims(contents['object'], axes=(-1, 0, 1)):\n",
+    "    plt.imshow(np.abs(layer))\n",
+    "    plt.axis('off')\n",
+    "    plt.show()\n",
+    "    plt.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8870f98",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "lemon",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}