data_play_fitz.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "import os\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_file = 'fitzpatrick17k.csv'#'fitzpatrick17k.csv'\n",
    "df = pd.read_csv(csv_file)\n",
    "fig_folder = 'Figures/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop unknown skin type\n",
    "df_known = df.loc[df['fitzpatrick'] != -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 1, 2, 6, 4, 5])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_known['fitzpatrick'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# encode disease names to numbers\n",
    "df[\"low\"] = df['label'].astype('category').cat.codes\n",
    "df[\"mid\"] = df['nine_partition_label'].astype('category').cat.codes\n",
    "df[\"high\"] = df['three_partition_label'].astype('category').cat.codes\n",
    "df[\"hasher\"] = df[\"md5hash\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_path = 'fitapatrick17k_known_code.csv'\n",
    "df_known.to_csv(new_path, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "code_df = pd.read_csv('fitapatrick17k_known_code.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16012\n",
      "1    2947\n",
      "2    4808\n",
      "3    3308\n",
      "4    2781\n",
      "5    1533\n",
      "6     635\n",
      "Name: fitzpatrick, dtype: int64\n",
      "2947\n",
      "0     2160\n",
      "1     2160\n",
      "2    11692\n",
      "Name: high, dtype: int64\n",
      "[[0.         0.         0.        ]\n",
      " [0.89537577 0.87758684 1.0497104 ]\n",
      " [0.96660738 0.8741153  1.03411278]\n",
      " [0.93946382 0.97860815 1.01620083]\n",
      " [1.02221699 1.24635759 0.9610472 ]\n",
      " [1.3006283  1.40680204 0.9123066 ]\n",
      " [1.94683533 1.40427466 0.87486508]]\n",
      "[[   0.    0.    0.]\n",
      " [ 444.  453. 2050.]\n",
      " [ 671.  742. 3395.]\n",
      " [ 475.  456. 2377.]\n",
      " [ 367.  301. 2113.]\n",
      " [ 159.  147. 1227.]\n",
      " [  44.   61.  530.]]\n",
      "16012\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "calculate weights for each skin type and condition\n",
    "method 1 reweighting\n",
    "'''\n",
    "level = 'high'\n",
    "total = code_df['fitzpatrick'].count()  # total samples\n",
    "type_count = code_df['fitzpatrick'].value_counts().sort_index()\n",
    "condition_count = code_df[level].value_counts().sort_index()\n",
    "print(total)\n",
    "print(type_count)\n",
    "print(type_count[1])\n",
    "print(condition_count)\n",
    "weight_record = np.zeros((7, 3))\n",
    "num_record = np.zeros((7, 3))\n",
    "for i in range(1, 7): # skin type\n",
    "    for j in range(len(condition_count)): # skin condition\n",
    "        x = code_df.loc[(code_df['fitzpatrick']==i) & (code_df[level]==j)]\n",
    "        num_record[i, j] = len(x)\n",
    "        # print('joint num', len(x))\n",
    "        weight = type_count[i]*condition_count[j]/(len(x)*total)\n",
    "        # print('weight', weight)\n",
    "        weight_record[i, j] = weight\n",
    "print(weight_record)\n",
    "print(num_record)\n",
    "# add weights to the csv file\n",
    "weight_list = []  # weight for each sample in the code_df\n",
    "for k in range(total):\n",
    "    row_data = code_df.iloc[k]\n",
    "    # print(row_data)\n",
    "    weight_list.append(weight_record[int(row_data['fitzpatrick']), int(row_data[level])])\n",
    "    # print(weight_list)\n",
    "print(len(weight_list))\n",
    "code_df['REWT_weights'] = weight_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "code_df.to_csv('fitzpatrick17k_known_code.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.         0.         0.        ]\n",
      " [0.00225225 0.00220751 0.0004878 ]\n",
      " [0.00149031 0.00134771 0.00029455]\n",
      " [0.00210526 0.00219298 0.0004207 ]\n",
      " [0.0027248  0.00332226 0.00047326]\n",
      " [0.00628931 0.00680272 0.000815  ]\n",
      " [0.02272727 0.01639344 0.00188679]]\n",
      "16012\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "calculate weights for each skin type and condition\n",
    "method 2 resampling   weight=1/num\n",
    "'''\n",
    "level = 'high'\n",
    "total = code_df['fitzpatrick'].count()  # total samples\n",
    "type_count = code_df['fitzpatrick'].value_counts().sort_index()\n",
    "condition_count = code_df[level].value_counts().sort_index()\n",
    "weight_record = np.zeros((7, 3))\n",
    "num_record = np.zeros((7, 3))\n",
    "for i in range(1, 7): # skin type\n",
    "    for j in range(len(condition_count)): # skin condition\n",
    "        x = code_df.loc[(code_df['fitzpatrick']==i) & (code_df[level]==j)]\n",
    "        num_record[i, j] = len(x)\n",
    "        # print('joint num', len(x))\n",
    "        weight = 1/len(x)\n",
    "        # print('weight', weight)\n",
    "        weight_record[i, j] = weight\n",
    "# print(num_record)\n",
    "print(weight_record)\n",
    "# add weights to the csv file\n",
    "weight_list = []  # weight for each sample in the code_df\n",
    "for k in range(total):\n",
    "    row_data = code_df.iloc[k]\n",
    "    # print(row_data)\n",
    "    weight_list.append(weight_record[int(row_data['fitzpatrick']), int(row_data[level])])\n",
    "    # print(weight_list)\n",
    "print(len(weight_list))\n",
    "code_df['RESM_weights'] = weight_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "code_df.to_csv('fitzpatrick17k_known_code.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'low': ['acanthosis nigricans', 'acne', 'acne vulgaris', 'acquired autoimmune bullous diseaseherpes gestationis', 'acrodermatitis enteropathica', 'actinic keratosis', 'allergic contact dermatitis', 'aplasia cutis', 'basal cell carcinoma', 'basal cell carcinoma morpheiform', 'becker nevus', 'behcets disease', 'calcinosis cutis', 'cheilitis', 'congenital nevus', 'dariers disease', 'dermatofibroma', 'dermatomyositis', 'disseminated actinic porokeratosis', 'drug eruption', 'drug induced pigmentary changes', 'dyshidrotic eczema', 'eczema', 'ehlers danlos syndrome', 'epidermal nevus', 'epidermolysis bullosa', 'erythema annulare centrifigum', 'erythema elevatum diutinum', 'erythema multiforme', 'erythema nodosum', 'factitial dermatitis', 'fixed eruptions', 'folliculitis', 'fordyce spots', 'granuloma annulare', 'granuloma pyogenic', 'hailey hailey disease', 'halo nevus', 'hidradenitis', 'ichthyosis vulgaris', 'incontinentia pigmenti', 'juvenile xanthogranuloma', 'kaposi sarcoma', 'keloid', 'keratosis pilaris', 'langerhans cell histiocytosis', 'lentigo maligna', 'lichen amyloidosis', 'lichen planus', 'lichen simplex', 'livedo reticularis', 'lupus erythematosus', 'lupus subacute', 'lyme disease', 'lymphangioma', 'malignant melanoma', 'melanoma', 'milia', 'mucinosis', 'mucous cyst', 'mycosis fungoides', 'myiasis', 'naevus comedonicus', 'necrobiosis lipoidica', 'nematode infection', 'neurodermatitis', 'neurofibromatosis', 'neurotic excoriations', 'neutrophilic dermatoses', 'nevocytic nevus', 'nevus sebaceous of jadassohn', 'papilomatosis confluentes and reticulate', 'paronychia', 'pediculosis lids', 'perioral dermatitis', 'photodermatoses', 'pilar cyst', 'pilomatricoma', 'pityriasis lichenoides chronica', 'pityriasis rosea', 'pityriasis rubra pilaris', 'porokeratosis actinic', 'porokeratosis of mibelli', 'porphyria', 'port wine stain', 'prurigo nodularis', 'psoriasis', 'pustular psoriasis', 'pyogenic granuloma', 'rhinophyma', 'rosacea', 'sarcoidosis', 'scabies', 'scleroderma', 'scleromyxedema', 'seborrheic dermatitis', 'seborrheic keratosis', 'solid cystic basal cell carcinoma', 'squamous cell carcinoma', 'stasis edema', 'stevens johnson syndrome', 'striae', 'sun damaged skin', 'superficial spreading melanoma ssm', 'syringoma', 'telangiectases', 'tick bite', 'tuberous sclerosis', 'tungiasis', 'urticaria', 'urticaria pigmentosa', 'vitiligo', 'xanthomas', 'xeroderma pigmentosum'], 'mid': ['benign dermal', 'benign epidermal', 'benign melanocyte', 'genodermatoses', 'inflammatory', 'malignant cutaneous lymphoma', 'malignant dermal', 'malignant epidermal', 'malignant melanoma'], 'high': ['benign', 'malignant', 'non-neoplastic']}\n"
     ]
    }
   ],
   "source": [
    "# connect class number and class name\n",
    "connection = {}\n",
    "name_list = {'low':'label', 'mid':'nine_partition_label', 'high':'three_partition_label'}\n",
    "connection['low'] = [0]*114\n",
    "connection['mid'] = [0]*9\n",
    "connection['high'] = [0]*3\n",
    "for label in ['low', 'mid', 'high']:\n",
    "    for i in range(len(connection[label])):\n",
    "        capture = code_df.loc[code_df[label]==i].iloc[0][name_list[label]]\n",
    "        connection[label][i] = capture\n",
    "print(connection)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    unique_values  counts\n",
      "0               8     253\n",
      "1              48     225\n",
      "2              98     196\n",
      "3              80     172\n",
      "4              92     126\n",
      "..            ...     ...\n",
      "87             74       2\n",
      "88             77       2\n",
      "89             72       2\n",
      "90             24       2\n",
      "91             53       1\n",
      "\n",
      "[92 rows x 2 columns]\n",
      "91\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "Look into Derm/Atla\n",
    "'''\n",
    "derm = code_df.loc[code_df.url.str.contains(\"dermaamin\")==False]\n",
    "value_counts = derm['low'].value_counts()\n",
    "value_counts = value_counts.rename_axis('unique_values').reset_index(name='counts')\n",
    "print(value_counts)\n",
    "final_set = set((value_counts.loc[value_counts['counts']>1])['unique_values'])\n",
    "print(len(final_set))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2    3300\n",
      "1    2217\n",
      "3    1833\n",
      "4    1343\n",
      "5     731\n",
      "6     343\n",
      "Name: fitzpatrick, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "'''\n",
    "Visualize data distribution\n",
    "'''\n",
    "plt.figure(figsize=(10,5))\n",
    "type = code_df['fitzpatrick']\n",
    "# for derm\n",
    "derm = code_df.loc[code_df.url.str.contains(\"dermaamin\")==True]\n",
    "type = derm['fitzpatrick']\n",
    "print(type.value_counts())\n",
    "type.value_counts().sort_index().plot.bar()\n",
    "plt.xlabel('skin type')\n",
    "plt.ylabel('samples')\n",
    "plt.title('number of samples per skin type in atla')\n",
    "# plt.savefig(fig_folder+'skin_type_statistics.jpg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "'''\n",
    "Visualize Skin type distribution\n",
    "'''\n",
    "# count number of samples for each skin condition\n",
    "# plt.figure(figsize=(25, 5), dpi=200)\n",
    "plt.figure()\n",
    "phase = 'high'\n",
    "label = code_df[phase]\n",
    "label.value_counts().plot.bar(width=1)\n",
    "# plt.hist(count_condition.values, bins=200)\n",
    "# plt.title('Histogram age_approx counts in train')\n",
    "plt.xlabel('classes')\n",
    "plt.ylabel('samples')\n",
    "# plt.xticks([])\n",
    "plt.title('number of samples per {} class'.format(phase))\n",
    "plt.savefig(fig_folder+'{}_class_statistics.jpg'.format(phase))\n",
    "plt.show()\n",
    "# print(count_condition)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Visualize some images of one class\n",
    "'''\n",
    "img_folder = 'fitzpatrick17k/data/finalfitz17k/'\n",
    "group_condition = list(code_df.groupby('label'))\n",
    "fig = plt.figure(figsize=(25,25))\n",
    "want_label = 4\n",
    "get_index = -1\n",
    "for i in range(len(group_condition)):\n",
    "    if group_condition[i][1].iloc[0]['low'] == want_label:\n",
    "        get_index = i\n",
    "data = group_condition[get_index][1]\n",
    "print(group_condition[get_index][0])\n",
    "print('number of samples', data.shape[0])\n",
    "for i in range(1, 61):\n",
    "    fig.add_subplot(6, 10, i)\n",
    "    img_name = img_folder+data.iloc[i]['md5hash']+'.jpg'\n",
    "    img = Image.open(img_name)\n",
    "    plt.imshow(img)\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "    plt.title('ID'+str(i-1))\n",
    "\n",
    "plt.pause(0.001)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[   0.    0.    0.]\n",
      " [ 444.  453. 2050.]\n",
      " [ 671.  742. 3395.]\n",
      " [ 475.  456. 2377.]\n",
      " [ 367.  301. 2113.]\n",
      " [ 159.  147. 1227.]\n",
      " [  44.   61.  530.]\n",
      " [   0.    0.    0.]]\n",
      "[ 2160.  2160. 11692.]\n",
      "[   0. 2947. 4808. 3308. 2781. 1533.  635.    0.]\n",
      "16012.0\n"
     ]
    }
   ],
   "source": [
    "'''get number of samples per skin type per class  with unknown type\n",
    "'''\n",
    "np.set_printoptions(suppress=True)\n",
    "label = 'high'\n",
    "# fig_folder = 'figures/'\n",
    "df = pd.read_csv('fitzpatrick17k_known_code.csv')\n",
    "whole = np.zeros((8, len(df[label].unique())))  # whole samples\n",
    "\n",
    "for i in range(df.shape[0]):\n",
    "    row = df.iloc[i]\n",
    "    type = int(row['fitzpatrick']) if row['fitzpatrick'] > 0 else 0  # set type -1 as 0\n",
    "    whole[type, row[label]] += 1\n",
    "\n",
    "print(whole)\n",
    "print(np.sum(whole, axis=0))\n",
    "print(np.sum(whole, axis=1))\n",
    "print(np.sum(whole))\n",
    "# calculate row 7. sum row 0-6        \n",
    "# whole[7, :] = np.sum(whole[0:7, :], axis=0)\n",
    "\n",
    "# plot\n",
    "# plt.figure(figsize=(100,8), dpi=200)\n",
    "# sns.heatmap(record_array[0:7, :], annot=True, fmt=\".2g\", linewidths=.5)\n",
    "sns.heatmap(whole[0:7, :], annot=True, fmt=\".2g\", linewidths=.5)\n",
    "plt.xlabel('label')\n",
    "plt.ylabel('skin type')\n",
    "name = 'train__class_statistic_{}'.format(label)\n",
    "plt.title(name)\n",
    "# plt.savefig(fig_folder+name+'.jpg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 20000x1600 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "'''get number of samples per skin type per class  out  unknown type\n",
    "'''\n",
    "np.set_printoptions(suppress=True)\n",
    "label = 'low'\n",
    "# fig_folder = 'figures/'\n",
    "df = pd.read_csv('temp_test.csv')\n",
    "whole = np.zeros((8, len(df[label].unique())))  # whole samples\n",
    "\n",
    "for i in range(df.shape[0]):\n",
    "    row = df.iloc[i]\n",
    "    type = int(row['fitzpatrick']) \n",
    "    whole[type, row[label]] += 1\n",
    "\n",
    "# calculate row 7. sum row 0-6        \n",
    "whole[7, :] = np.sum(whole[0:7, :], axis=0)\n",
    "\n",
    "# plot\n",
    "plt.figure(figsize=(100,8), dpi=200)\n",
    "# sns.heatmap(record_array[0:7, :], annot=True, fmt=\".2g\", linewidths=.5)\n",
    "sns.heatmap(whole[1:7, :], annot=True, fmt=\".2g\", linewidths=.5)\n",
    "plt.xlabel('label')\n",
    "plt.ylabel('skin type')\n",
    "name = 'train__class_statistic_{}'.format(label)\n",
    "plt.title(name)\n",
    "# plt.savefig(fig_folder+name+'.jpg')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "d7d995bc54c9aaecfe64e6668cd10ce18771211a7298b34b6f0fab6698bea7d7"
  },
  "kernelspec": {
   "display_name": "Python 3.8.12 ('skinlesion')",
   "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": "3.8.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
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