{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring Code for Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata = pd.read_csv(\"../data/focus/metadata.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>image_path</th>\n",
       "      <th>original_filename</th>\n",
       "      <th>study_id</th>\n",
       "      <th>scan_uuid</th>\n",
       "      <th>focus_value</th>\n",
       "      <th>stack_id</th>\n",
       "      <th>obj_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01631...</td>\n",
       "      <td>I01631_X013_Y012_Z5107.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>fba56d57-656e-4b6f-ba63-e4ba3ad083f5</td>\n",
       "      <td>-2.82953</td>\n",
       "      <td>1658220</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01632...</td>\n",
       "      <td>I01632_X013_Y012_Z5175.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>fba56d57-656e-4b6f-ba63-e4ba3ad083f5</td>\n",
       "      <td>-2.70408</td>\n",
       "      <td>1658220</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01633...</td>\n",
       "      <td>I01633_X013_Y012_Z5722.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>fba56d57-656e-4b6f-ba63-e4ba3ad083f5</td>\n",
       "      <td>-2.69918</td>\n",
       "      <td>1658220</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01634...</td>\n",
       "      <td>I01634_X013_Y012_Z5244.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>fba56d57-656e-4b6f-ba63-e4ba3ad083f5</td>\n",
       "      <td>-2.50266</td>\n",
       "      <td>1658220</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01635...</td>\n",
       "      <td>I01635_X013_Y012_Z5654.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>fba56d57-656e-4b6f-ba63-e4ba3ad083f5</td>\n",
       "      <td>-2.36450</td>\n",
       "      <td>1658220</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>565</td>\n",
       "      <td>31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01406...</td>\n",
       "      <td>I01406_X016_Y009_Z5361.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>4c7e9e66-61a1-47ca-aa4e-340b0eef8db1</td>\n",
       "      <td>-3.41147</td>\n",
       "      <td>1674918</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>566</td>\n",
       "      <td>31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01407...</td>\n",
       "      <td>I01407_X016_Y009_Z5087.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>4c7e9e66-61a1-47ca-aa4e-340b0eef8db1</td>\n",
       "      <td>-3.05424</td>\n",
       "      <td>1674918</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>567</td>\n",
       "      <td>31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01408...</td>\n",
       "      <td>I01408_X016_Y009_Z5292.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>4c7e9e66-61a1-47ca-aa4e-340b0eef8db1</td>\n",
       "      <td>-1.48608</td>\n",
       "      <td>1674918</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>568</td>\n",
       "      <td>31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01409...</td>\n",
       "      <td>I01409_X016_Y009_Z5156.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>4c7e9e66-61a1-47ca-aa4e-340b0eef8db1</td>\n",
       "      <td>-0.52804</td>\n",
       "      <td>1674918</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>569</td>\n",
       "      <td>31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01410...</td>\n",
       "      <td>I01410_X016_Y009_Z5224.jpg</td>\n",
       "      <td>31</td>\n",
       "      <td>4c7e9e66-61a1-47ca-aa4e-340b0eef8db1</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1674918</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>570 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0                                         image_path  \\\n",
       "0             0  31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01631...   \n",
       "1             1  31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01632...   \n",
       "2             2  31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01633...   \n",
       "3             3  31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01634...   \n",
       "4             4  31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01635...   \n",
       "..          ...                                                ...   \n",
       "565         565  31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01406...   \n",
       "566         566  31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01407...   \n",
       "567         567  31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01408...   \n",
       "568         568  31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01409...   \n",
       "569         569  31/4c7e9e66-61a1-47ca-aa4e-340b0eef8db1/I01410...   \n",
       "\n",
       "              original_filename  study_id  \\\n",
       "0    I01631_X013_Y012_Z5107.jpg        31   \n",
       "1    I01632_X013_Y012_Z5175.jpg        31   \n",
       "2    I01633_X013_Y012_Z5722.jpg        31   \n",
       "3    I01634_X013_Y012_Z5244.jpg        31   \n",
       "4    I01635_X013_Y012_Z5654.jpg        31   \n",
       "..                          ...       ...   \n",
       "565  I01406_X016_Y009_Z5361.jpg        31   \n",
       "566  I01407_X016_Y009_Z5087.jpg        31   \n",
       "567  I01408_X016_Y009_Z5292.jpg        31   \n",
       "568  I01409_X016_Y009_Z5156.jpg        31   \n",
       "569  I01410_X016_Y009_Z5224.jpg        31   \n",
       "\n",
       "                                scan_uuid  focus_value  stack_id  obj_name  \n",
       "0    fba56d57-656e-4b6f-ba63-e4ba3ad083f5     -2.82953   1658220       133  \n",
       "1    fba56d57-656e-4b6f-ba63-e4ba3ad083f5     -2.70408   1658220       133  \n",
       "2    fba56d57-656e-4b6f-ba63-e4ba3ad083f5     -2.69918   1658220       133  \n",
       "3    fba56d57-656e-4b6f-ba63-e4ba3ad083f5     -2.50266   1658220       133  \n",
       "4    fba56d57-656e-4b6f-ba63-e4ba3ad083f5     -2.36450   1658220       133  \n",
       "..                                    ...          ...       ...       ...  \n",
       "565  4c7e9e66-61a1-47ca-aa4e-340b0eef8db1     -3.41147   1674918       217  \n",
       "566  4c7e9e66-61a1-47ca-aa4e-340b0eef8db1     -3.05424   1674918       217  \n",
       "567  4c7e9e66-61a1-47ca-aa4e-340b0eef8db1     -1.48608   1674918       217  \n",
       "568  4c7e9e66-61a1-47ca-aa4e-340b0eef8db1     -0.52804   1674918       217  \n",
       "569  4c7e9e66-61a1-47ca-aa4e-340b0eef8db1      0.00000   1674918       217  \n",
       "\n",
       "[570 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'31/fba56d57-656e-4b6f-ba63-e4ba3ad083f5/I01631_X013_Y012_Z5107_600_375.jpg'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idx = 0\n",
    "# File Path\n",
    "metadata.iloc[idx, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2.82953"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Focus Value\n",
    "metadata.iloc[idx, 5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing FocusDataSet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "570\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'image': array([[[172, 173, 159],\n",
       "         [166, 167, 153],\n",
       "         [171, 173, 160],\n",
       "         ...,\n",
       "         [199, 202, 173],\n",
       "         [199, 202, 173],\n",
       "         [200, 201, 170]],\n",
       " \n",
       "        [[167, 169, 155],\n",
       "         [164, 166, 152],\n",
       "         [171, 175, 160],\n",
       "         ...,\n",
       "         [194, 197, 168],\n",
       "         [195, 198, 169],\n",
       "         [199, 200, 169]],\n",
       " \n",
       "        [[146, 153, 135],\n",
       "         [149, 156, 138],\n",
       "         [163, 172, 153],\n",
       "         ...,\n",
       "         [189, 192, 163],\n",
       "         [191, 194, 165],\n",
       "         [197, 198, 167]],\n",
       " \n",
       "        ...,\n",
       " \n",
       "        [[ 57,  62,  68],\n",
       "         [ 41,  46,  52],\n",
       "         [ 24,  31,  39],\n",
       "         ...,\n",
       "         [198, 189, 180],\n",
       "         [188, 179, 170],\n",
       "         [180, 171, 164]],\n",
       " \n",
       "        [[ 46,  51,  57],\n",
       "         [ 34,  39,  45],\n",
       "         [ 21,  28,  36],\n",
       "         ...,\n",
       "         [208, 200, 189],\n",
       "         [197, 190, 180],\n",
       "         [188, 181, 173]],\n",
       " \n",
       "        [[ 31,  39,  42],\n",
       "         [ 23,  31,  34],\n",
       "         [ 18,  25,  31],\n",
       "         ...,\n",
       "         [215, 209, 197],\n",
       "         [205, 199, 187],\n",
       "         [197, 190, 180]]], dtype=uint8),\n",
       " 'focus_value': 0.0}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from importlib.machinery import SourceFileLoader\n",
    "\n",
    "focus_datamodule = SourceFileLoader(\"focus_datamodule\", \"../src/datamodules/focus_datamodule.py\").load_module()\n",
    "from focus_datamodule import FocusDataSet\n",
    "\n",
    "ds = FocusDataSet(\"../data/focus/metadata.csv\", \"../data/focus/\")\n",
    "\n",
    "counter = 0\n",
    "for d in ds:\n",
    "    counter += 1\n",
    "\n",
    "print(counter)\n",
    "\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from focus_datamodule import FocusDataModule\n",
    "\n",
    "datamodule = FocusDataModule(data_dir=\"../data/focus\", csv_file=\"../data/focus/metadata.csv\")\n",
    "datamodule.setup()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for data in datamodule.test_dataloader():\n",
    "    break\n",
    "\n",
    "len(data[\"focus_value\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hku/.local/lib/python3.8/site-packages/torch/nn/modules/loss.py:96: UserWarning: Using a target size (torch.Size([64])) that is different to the input size (torch.Size([64, 1])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.\n",
      "  return F.l1_loss(input, target, reduction=self.reduction)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(tensor(2.5787, grad_fn=<L1LossBackward0>),\n",
       " tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "         0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "         0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " tensor([-1.2805, -0.0943, -2.3645,  0.8542, -0.8047, -6.0020,  0.0000, -4.3352,\n",
       "         -1.8066, -2.7189, -6.4697, -3.2557, -4.2778, -5.0264, -3.4891,  0.0000,\n",
       "         -1.7181, -2.7314,  0.3324, -0.0943, -0.8991,  0.0000, -4.4178,  1.9723,\n",
       "         -3.0026, -5.5685,  3.8374,  3.8625, -0.4125, -4.1936, -1.5781, -1.6393,\n",
       "         -2.9583, -5.4933, -1.7807, -3.3135, -5.3423, -0.7978, -5.3971, -4.9412,\n",
       "          0.0000, -4.4128, -5.7744, -5.2755, -1.0996, -5.7482,  0.0000, -0.1737,\n",
       "         -3.5851, -6.1429, -6.3642, -3.9653, -0.2081, -0.9539, -0.4159, -0.5388,\n",
       "         -1.3643, -4.4441, -1.5161,  0.6395, -5.4710, -2.6482,  0.0000, -2.6257],\n",
       "        dtype=torch.float64))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import types\n",
    "import importlib.machinery\n",
    "focus_module = SourceFileLoader('focus_module', '../src/models/focus_module.py').load_module()\n",
    "from focus_module import FocusLitModule\n",
    "\n",
    "model = FocusLitModule()\n",
    "\n",
    "model.step(data)"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac"
  },
  "kernelspec": {
   "display_name": "Python 3.9.7 64-bit",
   "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": "3.8.10"
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