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"}}},{"cell_type":"markdown","source":"* References\n1. k-NN method: https://www.kaggle.com/konstantinmasich/titanic-0-82-0-83\n2. RF and file handling: https://www.kaggle.com/alexisbcook/titanic-tutorial","metadata":{}},{"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport os\n# for dirname, _, filenames in os.walk('/kaggle/input'):\n#     for filename in filenames:\n#         print(os.path.join(dirname, filename))\n\n# Scalers\nfrom sklearn.preprocessing import MinMaxScaler\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.utils import shuffle\n\n# Models\nfrom sklearn.linear_model import LogisticRegression #logistic regression\nfrom sklearn.linear_model import Perceptron\nfrom sklearn import svm #support vector Machine\nfrom sklearn.ensemble import RandomForestClassifier #Random Forest\nfrom sklearn.neighbors import KNeighborsClassifier #KNN\nfrom sklearn.naive_bayes import GaussianNB #Naive bayes\nfrom sklearn.tree import DecisionTreeClassifier #Decision Tree\nfrom sklearn.model_selection import train_test_split #training and testing data split\nfrom sklearn import metrics #accuracy measure\nfrom sklearn.metrics import confusion_matrix #for confusion matrix\nfrom sklearn.ensemble import VotingClassifier\nfrom sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.neural_network import MLPClassifier\n\n# Cross-validation\nfrom sklearn.model_selection import KFold #for K-fold cross validation\nfrom sklearn.model_selection import cross_val_score #score evaluation\nfrom sklearn.model_selection import cross_val_predict #prediction\nfrom sklearn.model_selection import cross_validate\n\n# GridSearchCV\nfrom sklearn.model_selection import GridSearchCV\n\n#Common Model Algorithms\nfrom sklearn import svm, tree, linear_model, neighbors, naive_bayes, ensemble, discriminant_analysis, gaussian_process\n\n#Common Model Helpers\nfrom sklearn.preprocessing import OneHotEncoder, LabelEncoder\nfrom sklearn import feature_selection\nfrom sklearn import model_selection\nfrom sklearn import metrics\n","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","papermill":{"duration":0.051662,"end_time":"2021-08-12T07:18:14.679246","exception":false,"start_time":"2021-08-12T07:18:14.627584","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:14:15.911634Z","iopub.execute_input":"2021-08-12T16:14:15.912134Z","iopub.status.idle":"2021-08-12T16:14:17.356229Z","shell.execute_reply.started":"2021-08-12T16:14:15.912019Z","shell.execute_reply":"2021-08-12T16:14:17.355325Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import pydicom\nimport random\nimport matplotlib.pyplot as plt\nimport glob\n","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.297545,"end_time":"2021-08-12T07:18:15.013562","exception":false,"start_time":"2021-08-12T07:18:14.716017","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:14:18.21646Z","iopub.execute_input":"2021-08-12T16:14:18.217115Z","iopub.status.idle":"2021-08-12T16:14:18.502614Z","shell.execute_reply.started":"2021-08-12T16:14:18.21706Z","shell.execute_reply":"2021-08-12T16:14:18.501567Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# directory setting\nINPUT = '../input/rsna-miccai-brain-tumor-radiogenomic-classification'","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.043836,"end_time":"2021-08-12T07:18:15.094469","exception":false,"start_time":"2021-08-12T07:18:15.050633","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:14:40.763485Z","iopub.execute_input":"2021-08-12T16:14:40.764205Z","iopub.status.idle":"2021-08-12T16:14:40.768796Z","shell.execute_reply.started":"2021-08-12T16:14:40.764138Z","shell.execute_reply":"2021-08-12T16:14:40.767657Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_lab = pd.read_csv(INPUT + '/' + 'train_labels.csv')\nsample_sub = pd.read_csv(INPUT + '/' + 'sample_submission.csv')\n","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.066846,"end_time":"2021-08-12T07:18:15.199963","exception":false,"start_time":"2021-08-12T07:18:15.133117","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:14:42.131317Z","iopub.execute_input":"2021-08-12T16:14:42.131978Z","iopub.status.idle":"2021-08-12T16:14:42.20675Z","shell.execute_reply.started":"2021-08-12T16:14:42.131911Z","shell.execute_reply":"2021-08-12T16:14:42.205767Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print('Train labels')\ntrain_lab","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.06834,"end_time":"2021-08-12T07:18:15.306879","exception":false,"start_time":"2021-08-12T07:18:15.238539","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:14:55.028142Z","iopub.execute_input":"2021-08-12T16:14:55.028618Z","iopub.status.idle":"2021-08-12T16:14:55.060247Z","shell.execute_reply.started":"2021-08-12T16:14:55.028579Z","shell.execute_reply":"2021-08-12T16:14:55.059143Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"temp = train_lab['BraTS21ID'] + 100000\nitem_id = []\nfor i in range(len(train_lab)):\n    item_id = item_id + [str(temp[i])[-5:]]\nprint('Number of samples in training data')\nlen(item_id)   # 585","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.072956,"end_time":"2021-08-12T07:18:15.419671","exception":false,"start_time":"2021-08-12T07:18:15.346715","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:14:56.671532Z","iopub.execute_input":"2021-08-12T16:14:56.671963Z","iopub.status.idle":"2021-08-12T16:14:56.706806Z","shell.execute_reply.started":"2021-08-12T16:14:56.671924Z","shell.execute_reply":"2021-08-12T16:14:56.705602Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def GenerateD(df, fol, Itype): # fol: 'train'; Itype: 'FLAIR'\n    print('number, number of images, image_count, intensity, volume, average, Gmin, Gmax, Gmax-average, CmaxName')\n    for i in range(len(item_id[:])):\n        item_fol = os.listdir(INPUT + '/' + fol + '/' + item_id[i] + '/' + Itype)\n        item_fol2 = []\n        for j in item_fol:\n            k = 1000 + int(j[6:len(j)-4])\n            item_fol2 = item_fol2 + [k]\n        item_fols = sorted(item_fol2)\n        volume = 0\n        intensity = 0\n        image_count = 0\n        vac = 0\n        Gmax = 0\n        Gmin = 0\n        Amax = 0\n        Imax = 0\n        area_prev = 0\n        sumN_prev = 0\n        changeMax = 0\n        maxName ='none'\n        AmaxName ='none'\n        ImaxName ='none'\n        CmaxName ='00000'\n        for j in item_fols:\n            l = str(j-1000)\n            path = INPUT + '/' + fol + '/' + item_id[i] + '/' + Itype + '/Image-' + l + '.dcm'\n            dicom = pydicom.read_file(path)\n            data = dicom.pixel_array\n            sumN = np.sum(data)\n            sumN_plus = sumN - sumN_prev\n            sumN_prev = sumN\n            if sumN > Imax:\n                Imax = sumN\n                ImaxName = j\n            maxN = np.max(data)\n            if maxN > Gmax:\n                Gmax = maxN\n                maxName = j\n            minN = np.min(data)\n            if minN < Gmin:\n                Gmin = minN\n            zerocount = np.count_nonzero(data == 0)\n            area = np.count_nonzero(data != 0)\n            if area >0:\n                image_count = image_count +1\n            area_plus = area - area_prev\n            area_prev = area\n            if area > Amax:\n                Amax = area\n                AmaxName = j\n            change = -(sumN_plus/(area_plus+1))\n            if change > changeMax:\n                changeMax = change\n                CmaxName = j\n            intensity = intensity + sumN\n            volume = volume + area\n            vac = vac + zerocount\n        average = intensity/(volume+1)\n        df.loc[i,'c0'] = len(item_fol)\n        df.loc[i,'c1'] = image_count\n        df.loc[i,'c2'] = int(intensity)\n        df.loc[i,'c3'] = volume\n        df.loc[i,'c4'] = vac\n        df.loc[i,'c5'] = volume+vac\n        df.loc[i,'c6'] = average\n        df.loc[i,'c7'] = Gmin\n        df.loc[i,'c8'] = Gmax\n        df.loc[i,'c9'] = Gmax-average\n        df.loc[i,'c10'] = 'Image-' + str(int(CmaxName) -1000) + '.dcm'\n        print(i, len(item_fol), image_count, intensity, volume, average, Gmin, Gmax, Gmax-average, 'Image-' + str(int(CmaxName) -1000) + '.dcm')\n    return df\n\ntrain_lab = GenerateD(train_lab, 'train', 'FLAIR') # fol: 'train'; Itype: 'FLAIR'\n\ntrain_lab.head(10)","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":830.027219,"end_time":"2021-08-12T07:32:05.485624","exception":false,"start_time":"2021-08-12T07:18:15.458405","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:15:03.58657Z","iopub.execute_input":"2021-08-12T16:15:03.587032Z","iopub.status.idle":"2021-08-12T16:15:17.859473Z","shell.execute_reply.started":"2021-08-12T16:15:03.58699Z","shell.execute_reply":"2021-08-12T16:15:17.857401Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fol_num = '00000'\nfil_num = 70\npathA = '../input/rsna-miccai-brain-tumor-radiogenomic-classification/train/'+fol_num+'/FLAIR/Image-'+str(fil_num)+'.dcm'\ndicom = pydicom.read_file(pathA)\ndata = dicom.pixel_array\n# print(i+1, np.min(data), np.average(data), np.max(data), np.sum(data), np.max(data)/np.average(data))\nprint('An example image')\nplt.figure(figsize=(16, 5))\nplt.imshow(data, cmap=\"gray\")\nplt.show()\n\n# for i in range(129):\n#     fil_num = i+1\n#     pathA = '../input/rsna-miccai-brain-tumor-radiogenomic-classification/train/'+fol_num+'/FLAIR/Image-'+str(fil_num)+'.dcm'\n#     dicom = pydicom.read_file(pathA)\n#     data = dicom.pixel_array\n#     print(i+1, np.min(data), np.average(data), np.max(data), np.sum(data), np.max(data)/np.average(data))\n#     plt.figure(figsize=(16, 5))\n#     plt.imshow(data, cmap=\"gray\")\n#     plt.show()\n","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.477109,"end_time":"2021-08-12T07:32:06.179474","exception":false,"start_time":"2021-08-12T07:32:05.702365","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:15:20.046918Z","iopub.execute_input":"2021-08-12T16:15:20.04739Z","iopub.status.idle":"2021-08-12T16:15:20.269787Z","shell.execute_reply.started":"2021-08-12T16:15:20.047348Z","shell.execute_reply":"2021-08-12T16:15:20.26857Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(i, 'number of images', 'intensity', 'volume', 'average', 'Gmin', 'Gmax', 'Gmax-average', 'CmaxName')# for i in range(len(item_id[:10])):\n# for i in range(len(item_id[:1])):\nfor i in range(len(item_id[:])):\n    item_fol = os.listdir(INPUT + '/train/' + item_id[i] + '/FLAIR')\n    item_fol2 = []\n    for j in item_fol:\n#         k = 'A' + j[6:len(j)-4]\n        k = 1000 + int(j[6:len(j)-4])\n        item_fol2 = item_fol2 + [k]\n    item_fols = sorted(item_fol2)\n#     volume = 0\n#     intensity = 0\n#     vac = 0\n#     Gmax = 0\n#     Gmin = 0\n#     Amax = 0\n#     Imax = 0\n#     area_prev = 0\n#     sumN_prev = 0\n#     changeMax = 0\n#     maxName ='none'\n#     AmaxName ='none'\n#     ImaxName ='none'\n#     CmaxName ='00000'\n    P50 = 0\n    P60 = 0\n    P70 = 0\n    P80 = 0\n    P90 = 0\n    P95 = 0\n    F2 = 0\n    F3 = 0\n    F4 = 0\n    F5 = 0\n    F6 = 0\n    val50 = train_lab['c9'][i] * 0.5 + train_lab['c6'][i]\n    val60 = train_lab['c9'][i] * 0.6 + train_lab['c6'][i]\n    val70 = train_lab['c9'][i] * 0.7 + train_lab['c6'][i]\n    val80 = train_lab['c9'][i] * 0.8 + train_lab['c6'][i]\n    val90 = train_lab['c9'][i] * 0.9 + train_lab['c6'][i]\n    val95 = train_lab['c9'][i] * 0.95 + train_lab['c6'][i]\n    F2val = train_lab['c6'][i] * 2\n    F3val = train_lab['c6'][i] * 3\n    F4val = train_lab['c6'][i] * 4\n    F5val = train_lab['c6'][i] * 5\n    F6val = train_lab['c6'][i] * 6\n    for j in item_fols:\n        l = str(j-1000)\n        path = INPUT + '/train/' + item_id[i] + '/FLAIR/Image-' + l + '.dcm'\n        dicom = pydicom.read_file(path)\n        data = dicom.pixel_array\n#         sumN = np.sum(data)\n#         sumN_plus = sumN - sumN_prev\n#         sumN_prev = sumN\n#         if sumN > Imax:\n#             Imax = sumN\n#             ImaxName = j\n#         maxN = np.max(data)\n#         if maxN > Gmax:\n#             Gmax = maxN\n#             maxName = j\n#         minN = np.min(data)\n#         if minN < Gmin:\n#             Gmin = minN\n        count50 = np.count_nonzero(data > val50)\n        count60 = np.count_nonzero(data > val60)\n        count70 = np.count_nonzero(data > val70)\n        count80 = np.count_nonzero(data > val80)\n        count90 = np.count_nonzero(data > val90)\n        count95 = np.count_nonzero(data > val95)\n        countF2 = np.count_nonzero(data > F2val)\n        countF3 = np.count_nonzero(data > F3val)\n        countF4 = np.count_nonzero(data > F4val)\n        countF5 = np.count_nonzero(data > F5val)\n        countF6 = np.count_nonzero(data > F6val)\n#         area = np.count_nonzero(data != 0)\n#         area_plus = area - area_prev\n#         area_prev = area\n#         if area > Amax:\n#             Amax = area\n#             AmaxName = j\n#         change = -(sumN_plus/area_plus)\n#         if change > changeMax:\n#             changeMax = change\n#             CmaxName = j\n#         intensity = intensity + sumN\n#         volume = volume + area\n        P50 = P50 + count50\n        P60 = P60 + count60\n        P70 = P70 + count70\n        P80 = P80 + count80\n        P90 = P90 + count90\n        P95 = P95 + count95\n        F2 = F2 + countF2\n        F3 = F3 + countF3\n        F4 = F4 + countF4\n        F5 = F5 + countF5\n        F6 = F6 + countF6\n#         print(i, j, sumN, maxN, minN, zerocount, area, area_plus, sumN_plus, change)\n#     average = intensity/volume\n#     train_lab.loc[i,'c1'] = len(item_fol)\n#     train_lab.loc[i,'c2'] = int(intensity)\n#     train_lab.loc[i,'c3'] = volume\n#     train_lab.loc[i,'c4'] = vac\n#     train_lab.loc[i,'c5'] = volume+vac\n#     train_lab.loc[i,'c6'] = int(average)\n#     train_lab.loc[i,'c7'] = Gmin\n#     train_lab.loc[i,'c8'] = Gmax\n#     train_lab.loc[i,'c9'] = int(Gmax-average)\n#     train_lab.loc[i,'c10'] = 'Image-' + str(int(CmaxName) -1000) + '.dcm'\n    c3val = train_lab['c3'][i]\n    train_lab.loc[i,'c11'] = P50 * 1e7 / c3val\n    train_lab.loc[i,'c12'] = P60 * 1e7 / c3val\n    train_lab.loc[i,'c13'] = P70 * 1e7 / c3val\n    train_lab.loc[i,'c14'] = P80 * 1e7 / c3val\n    train_lab.loc[i,'c15'] = P90 * 1e7 / c3val\n    train_lab.loc[i,'c16'] = P95 * 1e7 / c3val\n    train_lab.loc[i,'c17'] = F2 *  1e7 / c3val\n    train_lab.loc[i,'c18'] = F3 *  1e7 / c3val\n    train_lab.loc[i,'c19'] = F4 * 1e7 / c3val\n    train_lab.loc[i,'c20'] = F5 * 1e7 / c3val\n    train_lab.loc[i,'c21'] = F6 * 1e7 / c3val\n#     train_lab.loc[i,['c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8', 'c9']] = (len(item_fol), intensity, volume, vac, volume+vac, average, Gmin, Gmax, int(Gmax-average))\n#     train_lab.loc[i,['c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8', 'c9']] = (len(item_fol), intensity, volume, vac, volume+vac, average, Gmin, Gmax, int(Gmax-average))\n#     print(i, (P50, P60, P70, P80, P90, P95, \n#     print(i, (F2, F3, F4, F5, F6)*1e7/train_lab['c3'][i])\n\n#     train_lab.c1[i] = len(item_fol)\n\n# print(item_id[:1], maxName, AmaxName, ImaxName)\ntrain_lab.head(10)","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.221153,"end_time":"2021-08-12T07:32:06.614529","exception":false,"start_time":"2021-08-12T07:32:06.393376","status":"completed"},"tags":[],"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-08-12T16:15:34.136493Z","iopub.execute_input":"2021-08-12T16:15:34.136882Z","iopub.status.idle":"2021-08-12T16:16:00.635766Z","shell.execute_reply.started":"2021-08-12T16:15:34.136851Z","shell.execute_reply":"2021-08-12T16:16:00.633408Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_lab","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-08-12T16:18:45.856647Z","iopub.execute_input":"2021-08-12T16:18:45.857077Z","iopub.status.idle":"2021-08-12T16:18:45.909981Z","shell.execute_reply.started":"2021-08-12T16:18:45.857042Z","shell.execute_reply":"2021-08-12T16:18:45.908955Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_lab.to_csv('Table_trainA.csv')\ntrain_lab2 = train_lab[train_lab['c2'] != 0]\ntrain_data = train_lab2.reset_index()\ntrain_data","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.291693,"end_time":"2021-08-12T07:46:28.976956","exception":false,"start_time":"2021-08-12T07:46:28.685263","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:20:59.901835Z","iopub.execute_input":"2021-08-12T16:20:59.902354Z","iopub.status.idle":"2021-08-12T16:20:59.965613Z","shell.execute_reply.started":"2021-08-12T16:20:59.902311Z","shell.execute_reply":"2021-08-12T16:20:59.964465Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def AddDif1(df):\n    df2 = df\n    df2['d1'] = df['c11'] - df['c12']\n    df2['d2'] = df['c12'] - df['c13']\n    df2['d3'] = df['c13'] - df['c14']\n    df2['d4'] = df['c14'] - df['c15']\n    df2['d5'] = df['c15'] - df['c16']\n    return df2\n    \ntrain_data = AddDif1(train_data)\ntrain_data","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.253352,"end_time":"2021-08-12T07:32:07.08195","exception":false,"start_time":"2021-08-12T07:32:06.828598","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:21:43.907664Z","iopub.execute_input":"2021-08-12T16:21:43.908101Z","iopub.status.idle":"2021-08-12T16:21:43.959434Z","shell.execute_reply.started":"2021-08-12T16:21:43.908061Z","shell.execute_reply":"2021-08-12T16:21:43.958551Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample_sub","metadata":{"_kg_hide-input":false,"papermill":{"duration":0.237028,"end_time":"2021-08-12T07:46:29.43955","exception":false,"start_time":"2021-08-12T07:46:29.202522","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:24:50.927369Z","iopub.execute_input":"2021-08-12T16:24:50.92784Z","iopub.status.idle":"2021-08-12T16:24:50.943096Z","shell.execute_reply.started":"2021-08-12T16:24:50.927803Z","shell.execute_reply":"2021-08-12T16:24:50.942366Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"temp = sample_sub['BraTS21ID'] + 100000\nitem_id = []\nfor i in range(len(sample_sub)):\n    item_id = item_id + [str(temp[i])[-5:]]\nprint('Number of samples in test data')\nlen(item_id)   # 87","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.233628,"end_time":"2021-08-12T07:46:29.894817","exception":false,"start_time":"2021-08-12T07:46:29.661189","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:24:52.522214Z","iopub.execute_input":"2021-08-12T16:24:52.522621Z","iopub.status.idle":"2021-08-12T16:24:52.532331Z","shell.execute_reply.started":"2021-08-12T16:24:52.522585Z","shell.execute_reply":"2021-08-12T16:24:52.531399Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_lab = sample_sub\n\n# Note: change 'train' path to 'test'","metadata":{"_kg_hide-input":true,"_kg_hide-output":false,"papermill":{"duration":0.233518,"end_time":"2021-08-12T07:46:30.355483","exception":false,"start_time":"2021-08-12T07:46:30.121965","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:24:56.376262Z","iopub.execute_input":"2021-08-12T16:24:56.376693Z","iopub.status.idle":"2021-08-12T16:24:56.381128Z","shell.execute_reply.started":"2021-08-12T16:24:56.376655Z","shell.execute_reply":"2021-08-12T16:24:56.380285Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_lab = GenerateD(train_lab, 'test', 'FLAIR') # fol: 'train'; Itype: 'FLAIR'\n\ntrain_lab.head(10)","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":123.648317,"end_time":"2021-08-12T07:48:34.229018","exception":false,"start_time":"2021-08-12T07:46:30.580701","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:25:08.831487Z","iopub.execute_input":"2021-08-12T16:25:08.832121Z","iopub.status.idle":"2021-08-12T16:25:22.57051Z","shell.execute_reply.started":"2021-08-12T16:25:08.832085Z","shell.execute_reply":"2021-08-12T16:25:22.569081Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(i, 'number of images', 'intensity', 'volume', 'average', 'Gmin', 'Gmax', 'Gmax-average', 'CmaxName')# for i in range(len(item_id[:10])):\n# for i in range(len(item_id[:1])):\nfor i in range(len(item_id[:])):\n    item_fol = os.listdir(INPUT + '/test/' + item_id[i] + '/FLAIR')\n    item_fol2 = []\n    for j in item_fol:\n#         k = 'A' + j[6:len(j)-4]\n        k = 1000 + int(j[6:len(j)-4])\n        item_fol2 = item_fol2 + [k]\n    item_fols = sorted(item_fol2)\n#     volume = 0\n#     intensity = 0\n#     vac = 0\n#     Gmax = 0\n#     Gmin = 0\n#     Amax = 0\n#     Imax = 0\n#     area_prev = 0\n#     sumN_prev = 0\n#     changeMax = 0\n#     maxName ='none'\n#     AmaxName ='none'\n#     ImaxName ='none'\n#     CmaxName ='00000'\n    P50 = 0\n    P60 = 0\n    P70 = 0\n    P80 = 0\n    P90 = 0\n    P95 = 0\n    F2 = 0\n    F3 = 0\n    F4 = 0\n    F5 = 0\n    F6 = 0\n    val50 = train_lab['c9'][i] * 0.5 + train_lab['c6'][i]\n    val60 = train_lab['c9'][i] * 0.6 + train_lab['c6'][i]\n    val70 = train_lab['c9'][i] * 0.7 + train_lab['c6'][i]\n    val80 = train_lab['c9'][i] * 0.8 + train_lab['c6'][i]\n    val90 = train_lab['c9'][i] * 0.9 + train_lab['c6'][i]\n    val95 = train_lab['c9'][i] * 0.95 + train_lab['c6'][i]\n    F2val = train_lab['c6'][i] * 2\n    F3val = train_lab['c6'][i] * 3\n    F4val = train_lab['c6'][i] * 4\n    F5val = train_lab['c6'][i] * 5\n    F6val = train_lab['c6'][i] * 6\n    for j in item_fols:\n        l = str(j-1000)\n        path = INPUT + '/test/' + item_id[i] + '/FLAIR/Image-' + l + '.dcm'\n        dicom = pydicom.read_file(path)\n        data = dicom.pixel_array\n#         sumN = np.sum(data)\n#         sumN_plus = sumN - sumN_prev\n#         sumN_prev = sumN\n#         if sumN > Imax:\n#             Imax = sumN\n#             ImaxName = j\n#         maxN = np.max(data)\n#         if maxN > Gmax:\n#             Gmax = maxN\n#             maxName = j\n#         minN = np.min(data)\n#         if minN < Gmin:\n#             Gmin = minN\n        count50 = np.count_nonzero(data > val50)\n        count60 = np.count_nonzero(data > val60)\n        count70 = np.count_nonzero(data > val70)\n        count80 = np.count_nonzero(data > val80)\n        count90 = np.count_nonzero(data > val90)\n        count95 = np.count_nonzero(data > val95)\n        countF2 = np.count_nonzero(data > F2val)\n        countF3 = np.count_nonzero(data > F3val)\n        countF4 = np.count_nonzero(data > F4val)\n        countF5 = np.count_nonzero(data > F5val)\n        countF6 = np.count_nonzero(data > F6val)\n#         area = np.count_nonzero(data != 0)\n#         area_plus = area - area_prev\n#         area_prev = area\n#         if area > Amax:\n#             Amax = area\n#             AmaxName = j\n#         change = -(sumN_plus/area_plus)\n#         if change > changeMax:\n#             changeMax = change\n#             CmaxName = j\n#         intensity = intensity + sumN\n#         volume = volume + area\n        P50 = P50 + count50\n        P60 = P60 + count60\n        P70 = P70 + count70\n        P80 = P80 + count80\n        P90 = P90 + count90\n        P95 = P95 + count95\n        F2 = F2 + countF2\n        F3 = F3 + countF3\n        F4 = F4 + countF4\n        F5 = F5 + countF5\n        F6 = F6 + countF6\n#         print(i, j, sumN, maxN, minN, zerocount, area, area_plus, sumN_plus, change)\n#     average = intensity/volume\n#     train_lab.loc[i,'c1'] = len(item_fol)\n#     train_lab.loc[i,'c2'] = int(intensity)\n#     train_lab.loc[i,'c3'] = volume\n#     train_lab.loc[i,'c4'] = vac\n#     train_lab.loc[i,'c5'] = volume+vac\n#     train_lab.loc[i,'c6'] = int(average)\n#     train_lab.loc[i,'c7'] = Gmin\n#     train_lab.loc[i,'c8'] = Gmax\n#     train_lab.loc[i,'c9'] = int(Gmax-average)\n#     train_lab.loc[i,'c10'] = 'Image-' + str(int(CmaxName) -1000) + '.dcm'\n    c3val = train_lab['c3'][i]\n    train_lab.loc[i,'c11'] = P50 * 1e7 / c3val\n    train_lab.loc[i,'c12'] = P60 * 1e7 / c3val\n    train_lab.loc[i,'c13'] = P70 * 1e7 / c3val\n    train_lab.loc[i,'c14'] = P80 * 1e7 / c3val\n    train_lab.loc[i,'c15'] = P90 * 1e7 / c3val\n    train_lab.loc[i,'c16'] = P95 * 1e7 / c3val\n    train_lab.loc[i,'c17'] = F2 *  1e7 / c3val\n    train_lab.loc[i,'c18'] = F3 *  1e7 / c3val\n    train_lab.loc[i,'c19'] = F4 * 1e7 / c3val\n    train_lab.loc[i,'c20'] = F5 * 1e7 / c3val\n    train_lab.loc[i,'c21'] = F6 * 1e7 / c3val\n#     train_lab.loc[i,['c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8', 'c9']] = (len(item_fol), intensity, volume, vac, volume+vac, average, Gmin, Gmax, int(Gmax-average))\n#     train_lab.loc[i,['c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8', 'c9']] = (len(item_fol), intensity, volume, vac, volume+vac, average, Gmin, Gmax, int(Gmax-average))\n#     print(i, (P50, P60, P70, P80, P90, P95, \n#     print(i, (F2, F3, F4, F5, F6)*1e7/train_lab['c3'][i])\n\n#     train_lab.c1[i] = len(item_fol)\n\n# print(item_id[:1], maxName, AmaxName, ImaxName)\ntrain_lab.head(10)","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-08-12T16:25:27.823846Z","iopub.execute_input":"2021-08-12T16:25:27.824501Z","iopub.status.idle":"2021-08-12T16:25:57.163741Z","shell.execute_reply.started":"2021-08-12T16:25:27.824462Z","shell.execute_reply":"2021-08-12T16:25:57.162266Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample_sub = train_lab     # <=== Caution!","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.268689,"end_time":"2021-08-12T07:49:24.670952","exception":false,"start_time":"2021-08-12T07:49:24.402263","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:28:45.614423Z","iopub.execute_input":"2021-08-12T16:28:45.614866Z","iopub.status.idle":"2021-08-12T16:28:45.620583Z","shell.execute_reply.started":"2021-08-12T16:28:45.614834Z","shell.execute_reply":"2021-08-12T16:28:45.619224Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample_sub.to_csv('Table_testA.csv')\ntest_data = sample_sub\ntest_data","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.31684,"end_time":"2021-08-12T07:49:25.24861","exception":false,"start_time":"2021-08-12T07:49:24.93177","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:28:46.268646Z","iopub.execute_input":"2021-08-12T16:28:46.269084Z","iopub.status.idle":"2021-08-12T16:28:46.31881Z","shell.execute_reply.started":"2021-08-12T16:28:46.269045Z","shell.execute_reply":"2021-08-12T16:28:46.317636Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_data = AddDif1(test_data)\ntest_data","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-08-12T16:29:25.693854Z","iopub.execute_input":"2021-08-12T16:29:25.694264Z","iopub.status.idle":"2021-08-12T16:29:25.745528Z","shell.execute_reply.started":"2021-08-12T16:29:25.694232Z","shell.execute_reply":"2021-08-12T16:29:25.744725Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"output = pd.read_csv('../input/rsna-miccai-brain-tumor-radiogenomic-classification/sample_submission.csv')\noutput","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.284216,"end_time":"2021-08-12T07:49:25.793245","exception":false,"start_time":"2021-08-12T07:49:25.509029","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:33:24.42409Z","iopub.execute_input":"2021-08-12T16:33:24.424525Z","iopub.status.idle":"2021-08-12T16:33:24.443522Z","shell.execute_reply.started":"2021-08-12T16:33:24.424488Z","shell.execute_reply":"2021-08-12T16:33:24.44263Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# k-Nearest neighbor or Random forest","metadata":{}},{"cell_type":"code","source":"features = [\"c2\", \"c3\", \"c4\", \"c5\", \"c6\", \"c8\", \"c9\", \n#             \"c11\", \"c12\", \"c13\", \"c14\", \"c15\", \"c16\",\n            \"d1\", \"d2\", \"d3\", \"d4\", \"d5\"]\ny = train_data[\"MGMT_value\"]\nX = pd.get_dummies(train_data[features])\nX_test = pd.get_dummies(test_data[features])","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.253352,"end_time":"2021-08-12T07:32:07.08195","exception":false,"start_time":"2021-08-12T07:32:06.828598","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:38:49.879213Z","iopub.execute_input":"2021-08-12T16:38:49.879636Z","iopub.status.idle":"2021-08-12T16:38:49.894865Z","shell.execute_reply.started":"2021-08-12T16:38:49.879604Z","shell.execute_reply":"2021-08-12T16:38:49.893807Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"std_scaler = StandardScaler()\nX = std_scaler.fit_transform(X)\nX_test = std_scaler.transform(X_test)","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.253352,"end_time":"2021-08-12T07:32:07.08195","exception":false,"start_time":"2021-08-12T07:32:06.828598","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:38:51.483473Z","iopub.execute_input":"2021-08-12T16:38:51.483975Z","iopub.status.idle":"2021-08-12T16:38:51.496321Z","shell.execute_reply.started":"2021-08-12T16:38:51.483929Z","shell.execute_reply":"2021-08-12T16:38:51.49514Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# # KNN\n# n_neighbors = [6,7,8,9,10,11,12,14,16,18,20,22,24,26]\n# algorithm = ['auto']\n# weights = ['uniform', 'distance']\n# leaf_size = list(range(1,50,5))\n# hyperparams = {'algorithm': algorithm, 'weights': weights, 'leaf_size': leaf_size, \n#                'n_neighbors': n_neighbors}\n# gd=GridSearchCV(estimator = KNeighborsClassifier(), param_grid = hyperparams, verbose=True, \n#                 cv=9, scoring = \"roc_auc\")\n# gd.fit(X, y)\n# print(gd.best_score_)\n# print(gd.best_estimator_)\n\n# gd.best_estimator_.fit(X, y)\n# y_pred = gd.best_estimator_.predict_proba(X_test)[:,1]\n# y_pred\n\n# y_score1 = gd.best_estimator_.predict_proba(X)[:,1]\n# predictions = gd.best_estimator_.predict_proba(X_test)[:,1]\n","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.253352,"end_time":"2021-08-12T07:32:07.08195","exception":false,"start_time":"2021-08-12T07:32:06.828598","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:38:57.628632Z","iopub.execute_input":"2021-08-12T16:38:57.629041Z","iopub.status.idle":"2021-08-12T16:39:01.276819Z","shell.execute_reply.started":"2021-08-12T16:38:57.629009Z","shell.execute_reply":"2021-08-12T16:39:01.274905Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.ensemble import RandomForestClassifier\n\ny = train_data[\"MGMT_value\"]\n\nfeatures = [\"c2\", \"c3\", \"c4\", \"c5\", \"c6\", \"c8\", \"c9\", \n#             \"c11\", \"c12\", \"c13\", \"c14\", \"c15\", \"c16\",\n            \"d1\", \"d2\", \"d3\", \"d4\", \"d5\"]\n#             \"c17\", \"c18\", \"c19\", \"c20\", \"c21\"]\nX = pd.get_dummies(train_data[features])\nX_test = pd.get_dummies(test_data[features])\n\nmodel = RandomForestClassifier(n_estimators=100, max_depth=7, random_state=1)\nmodel.fit(X, y)\n\ny_score1 = model.predict_proba(X)[:,1]\npredictions = model.predict_proba(X_test)[:,1]\n","metadata":{"_kg_hide-input":true,"execution":{"iopub.execute_input":"2021-08-12T07:49:26.306346Z","iopub.status.busy":"2021-08-12T07:49:26.305565Z","iopub.status.idle":"2021-08-12T07:49:28.004137Z","shell.execute_reply":"2021-08-12T07:49:28.003596Z","shell.execute_reply.started":"2021-08-11T14:18:55.878193Z"},"papermill":{"duration":1.961317,"end_time":"2021-08-12T07:49:28.004306","exception":false,"start_time":"2021-08-12T07:49:26.042989","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.metrics import roc_auc_score\nfrom sklearn.metrics import roc_curve\nimport matplotlib.pyplot as plt\ny_true1 = y\n# # y_score1 = model.predict_proba(X)[:,1]\n# y_score1 = gd.best_estimator_.predict_proba(X)[:,1]\n\nroc1 = roc_curve(y_true1, y_score1)\n\nfpr1, tpr1, thresholds1 = roc_curve(y_true1, y_score1)\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.metrics import precision_score\nfrom sklearn.metrics import recall_score\nfrom sklearn.metrics import f1_score\ny_pred = np.round(y_score1, decimals = 0)\ntn1, fp1, fn1, tp1 = confusion_matrix(y_true1, y_pred).ravel()\nac1 = accuracy_score(y_true1, y_pred)\npr1 = precision_score(y_true1, y_pred)\nrc1 = recall_score(y_true1, y_pred)\nsp1 = tn1/(fp1+tn1)\nf11 = f1_score(y_true1, y_pred)\nphi1 = (tp1*tn1-fp1*fn1)/np.sqrt((tp1+fn1)*(tp1+fp1)*(tn1+fn1)*(tn1+fp1))\n\n# y_true2 = y_vali\n# y_score2 = p_vali\n\n# roc2 = roc_curve(y_true2, y_score2)\n\n# fpr2, tpr2, thresholds2 = roc_curve(y_true2, y_score2)\n# y_pred = np.round(p_vali, decimals = 0)\n# tn2, fp2, fn2, tp2 = confusion_matrix(y_true2, y_pred).ravel()\n# ac2 = accuracy_score(y_true2, y_pred)\n# pr2 = precision_score(y_true2, y_pred)\n# rc2 = recall_score(y_true2, y_pred)\n# sp2 = tn2/(fp2+tn2)\n# f12 = f1_score(y_true2, y_pred)\n# phi2 = (tp2*tn2-fp2*fn2)/np.sqrt((tp2+fn2)*(tp2+fp2)*(tn2+fn2)*(tn2+fp2))\n\n# y_true3 = y_test\n# y_score3 = p_test\n\n# roc3 = roc_curve(y_true3, y_score3)\n\n# fpr3, tpr3, thresholds3 = roc_curve(y_true3, y_score3)\n# y_pred = np.round(p_test, decimals = 0)\n# tn3, fp3, fn3, tp3 = confusion_matrix(y_true3, y_pred).ravel()\n# ac3 = accuracy_score(y_true3, y_pred)\n# pr3 = precision_score(y_true3, y_pred)\n# rc3 = recall_score(y_true3, y_pred)\n# sp3 = tn3/(fp3+tn3)\n# f13 = f1_score(y_true3, y_pred)\n# phi3 = (tp3*tn3-fp3*fn3)/np.sqrt((tp3+fn3)*(tp3+fp3)*(tn3+fn3)*(tn3+fp3))\n\nplt.figure(figsize=(6,6))\nplt.plot((0,1), (0,1), color=\"black\", linestyle=\"--\")\nplt.plot(fpr1, tpr1, linewidth=3)#, marker='o')\n# plt.plot(fpr2, tpr2, linewidth=3)#, marker='o')\n# plt.plot(fpr3, tpr3, linewidth=3)#, marker='o')\nplt.tick_params(direction='in')\nplt.xlabel('FPR: False positive rate')\nplt.ylabel('TPR: True positive rate')\n# plt.legend(['train', 'valid', 'test'], loc='lower right')\nplt.grid()\nROC1=roc_auc_score(y_true1, y_score1)\n# ROC2=roc_auc_score(y_true2, y_score2)\n# ROC3=roc_auc_score(y_true3, y_score3)\nprint(ROC1)#,ROC2,ROC3)","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.4848,"end_time":"2021-08-12T07:49:28.745441","exception":false,"start_time":"2021-08-12T07:49:28.260641","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:42:01.440892Z","iopub.execute_input":"2021-08-12T16:42:01.441274Z","iopub.status.idle":"2021-08-12T16:42:01.476493Z","shell.execute_reply.started":"2021-08-12T16:42:01.441234Z","shell.execute_reply":"2021-08-12T16:42:01.474768Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# for i in range(len(X)):\n#     print(i, y[i], model.predict_proba(X)[:,1][i])","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2021-08-12T07:49:29.260411Z","iopub.status.busy":"2021-08-12T07:49:29.259351Z","iopub.status.idle":"2021-08-12T07:49:40.573146Z","shell.execute_reply":"2021-08-12T07:49:40.573877Z","shell.execute_reply.started":"2021-08-11T14:19:06.133063Z"},"papermill":{"duration":11.57559,"end_time":"2021-08-12T07:49:40.574323","exception":false,"start_time":"2021-08-12T07:49:28.998733","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# predictions = model.predict_proba(X_test)[:,1]\n# predictions = gd.best_estimator_.predict_proba(X_test)[:,1]\noutput['MGMT_value'] = predictions\noutput","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"papermill":{"duration":0.301687,"end_time":"2021-08-12T07:49:41.145036","exception":false,"start_time":"2021-08-12T07:49:40.843349","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2021-08-12T16:43:19.794458Z","iopub.execute_input":"2021-08-12T16:43:19.794862Z","iopub.status.idle":"2021-08-12T16:43:19.825673Z","shell.execute_reply.started":"2021-08-12T16:43:19.794831Z","shell.execute_reply":"2021-08-12T16:43:19.823322Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"temp = output['BraTS21ID'] + 100000\nitem_id = []\nfor i in range(len(temp)):\n    item_id = item_id + [str(temp[i])[-5:]]\noutput['BraTS21ID'] = item_id\n\noutput.to_csv('submission.csv', index=False)\nprint(\"Your submission was successfully saved!\")","metadata":{"_kg_hide-input":true,"execution":{"iopub.execute_input":"2021-08-12T07:49:41.701419Z","iopub.status.busy":"2021-08-12T07:49:41.699919Z","iopub.status.idle":"2021-08-12T07:49:41.705563Z","shell.execute_reply":"2021-08-12T07:49:41.704874Z","shell.execute_reply.started":"2021-08-11T14:19:09.313057Z"},"papermill":{"duration":0.284729,"end_time":"2021-08-12T07:49:41.705724","exception":false,"start_time":"2021-08-12T07:49:41.420995","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"output","metadata":{"execution":{"iopub.execute_input":"2021-08-12T07:49:42.250412Z","iopub.status.busy":"2021-08-12T07:49:42.249408Z","iopub.status.idle":"2021-08-12T07:49:42.263024Z","shell.execute_reply":"2021-08-12T07:49:42.263589Z","shell.execute_reply.started":"2021-08-11T14:19:14.788578Z"},"papermill":{"duration":0.287783,"end_time":"2021-08-12T07:49:42.263769","exception":false,"start_time":"2021-08-12T07:49:41.975986","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"feature_importance = model.feature_importances_\nprint('Feature importances')\nfor i in range(len(features)):\n    print(features[i], feature_importance[i])","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2021-08-12T07:49:42.816343Z","iopub.status.busy":"2021-08-12T07:49:42.815624Z","iopub.status.idle":"2021-08-12T07:49:42.824771Z","shell.execute_reply":"2021-08-12T07:49:42.824074Z","shell.execute_reply.started":"2021-08-11T14:19:17.588252Z"},"papermill":{"duration":0.294731,"end_time":"2021-08-12T07:49:42.824928","exception":false,"start_time":"2021-08-12T07:49:42.530197","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nindices = np.argsort(feature_importance)[::1]\nplt.figure(figsize = (6, 6))\nplt.barh(np.array(features)[indices], feature_importance[indices], height = 0.5)\nplt.yticks(fontsize = 20)\nplt.xlabel(\"Feature importances\", fontsize = 25)\nplt.show()","metadata":{"execution":{"iopub.execute_input":"2021-08-12T07:49:44.077814Z","iopub.status.busy":"2021-08-12T07:49:44.076983Z","iopub.status.idle":"2021-08-12T07:49:44.189781Z","shell.execute_reply":"2021-08-12T07:49:44.188368Z"},"papermill":{"duration":0.392293,"end_time":"2021-08-12T07:49:44.190205","exception":true,"start_time":"2021-08-12T07:49:43.797912","status":"failed"},"tags":[],"_kg_hide-input":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# import numpy as np # linear algebra\n# import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n# Resulting_train = pd.read_csv('../input/rf-brain-tumor-flair/Table_trainA.csv')\n# # len(Resulting_train)\n\n# def AddDif1(df):\n#     df2 = df\n#     df2['d1'] = df['c11'] - df['c12']\n#     df2['d2'] = df['c12'] - df['c13']\n#     df2['d3'] = df['c13'] - df['c14']\n#     df2['d4'] = df['c14'] - df['c15']\n#     df2['d5'] = df['c15'] - df['c16']\n#     return df2\n    \n# Resulting_train = AddDif1(Resulting_train)\nResulting_train = train_data\nResulting_train.head(2)","metadata":{"execution":{"iopub.status.busy":"2021-08-14T10:43:05.216866Z","iopub.execute_input":"2021-08-14T10:43:05.217269Z","iopub.status.idle":"2021-08-14T10:43:05.262472Z","shell.execute_reply.started":"2021-08-14T10:43:05.217238Z","shell.execute_reply":"2021-08-14T10:43:05.261515Z"},"_kg_hide-input":true,"_kg_hide-output":true,"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"Positive_train = Resulting_train[Resulting_train.MGMT_value == 1]\nNegative_train = Resulting_train[Resulting_train.MGMT_value == 0]\n(len(Positive_train), len(Negative_train), len(Positive_train) + len(Negative_train))","metadata":{"execution":{"iopub.status.busy":"2021-08-14T10:44:31.882543Z","iopub.execute_input":"2021-08-14T10:44:31.882907Z","iopub.status.idle":"2021-08-14T10:44:31.89375Z","shell.execute_reply.started":"2021-08-14T10:44:31.882877Z","shell.execute_reply":"2021-08-14T10:44:31.892786Z"},"_kg_hide-input":true,"_kg_hide-output":true,"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\n%matplotlib inline\nimport seaborn as sns\n\nfig, ax = plt.subplots(4, 3, figsize=(12, 9))\nsns.set_palette(sns.color_palette(\"icefire\"))\n\nsns.kdeplot(data=Positive_train['c2'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[0][0])\nsns.kdeplot(data=Negative_train['c2'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[0][0])\nax[0][0].set_title('c2', fontsize=15, fontweight='bold')\nax[0][0].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['c3'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[0][1])\nsns.kdeplot(data=Negative_train['c3'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[0][1])\nax[0][1].set_title('c3', fontsize=15, fontweight='bold')\nax[0][1].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['c4'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[0][2])\nsns.kdeplot(data=Negative_train['c4'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[0][2])\nax[0][2].set_title('c4', fontsize=15, fontweight='bold')\nax[0][2].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['c6'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[1][0])\nsns.kdeplot(data=Negative_train['c6'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[1][0])\nax[1][0].set_title('c6', fontsize=15, fontweight='bold')\nax[1][0].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['c8'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[1][1])\nsns.kdeplot(data=Negative_train['c8'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[1][1])\nax[1][1].set_title('c8', fontsize=15, fontweight='bold')\nax[1][1].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['c9'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[1][2])\nsns.kdeplot(data=Negative_train['c9'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[1][2])\nax[1][2].set_title('c9', fontsize=15, fontweight='bold')\nax[1][2].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['d1'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[2][0])\nsns.kdeplot(data=Negative_train['d1'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[2][0])\nax[2][0].set_title('d1', fontsize=15, fontweight='bold')\nax[2][0].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['d2'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[2][1])\nsns.kdeplot(data=Negative_train['d2'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[2][1])\nax[2][1].set_title('d2', fontsize=15, fontweight='bold')\nax[2][1].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['d3'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[2][2])\nsns.kdeplot(data=Negative_train['d3'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[2][2])\nax[2][2].set_title('d3', fontsize=15, fontweight='bold')\nax[2][2].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['d4'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[3][0])\nsns.kdeplot(data=Negative_train['d4'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[3][0])\nax[3][0].set_title('d4', fontsize=15, fontweight='bold')\nax[3][0].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['d5'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[3][1])\nsns.kdeplot(data=Negative_train['d5'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[3][1])\nax[3][1].set_title('d4', fontsize=15, fontweight='bold')\nax[3][1].tick_params(direction='in')\n\nsns.kdeplot(data=Positive_train['c1'], label=\"positive\", color=\"#9999ff\", shade=True, ax=ax[3][2])\nsns.kdeplot(data=Negative_train['c1'], label=\"negative\", color=\"#ffaaaa\", shade=True, ax=ax[3][2])\nax[3][2].set_title('c1', fontsize=15, fontweight='bold')\nax[3][2].tick_params(direction='in')\n\n\nfig.suptitle('Distribution: positive (blue) and nagative (red)', fontsize=20, fontweight='bold')\n\nfig.tight_layout(rect=[0, 0.03, 1, 0.90]);","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2021-08-14T11:02:29.617206Z","iopub.execute_input":"2021-08-14T11:02:29.617633Z","iopub.status.idle":"2021-08-14T11:02:32.127964Z","shell.execute_reply.started":"2021-08-14T11:02:29.617593Z","shell.execute_reply":"2021-08-14T11:02:32.126851Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"Debug_mode = False","metadata":{"_kg_hide-input":true,"_kg_hide-output":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# directory setting\nINPUT = '../input/rsna-miccai-brain-tumor-radiogenomic-classification'\ntrain_lab = pd.read_csv(INPUT + '/' + 'train_labels.csv')\nsample_sub = pd.read_csv(INPUT + '/' + 'sample_submission.csv')\n\nif Debug_mode == True:\n    train_lab = train_lab.iloc[:5,:] ###########################################\n    \ntemp = train_lab['BraTS21ID'] + 100000\nitem_id = []\nfor i in range(len(train_lab)):\n    item_id = item_id + [str(temp[i])[-5:]]\n","metadata":{"_kg_hide-input":true,"_kg_hide-output":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"'''\n各画像の平均値と標準偏差を取得し、まとめる\n'''\ndef GenerateH(df, fol, Itype): # fol: 'train'; Itype: 'FLAIR'\n    Types = ['FLAIR', 'T1w', 'T1wCE', 'T2w']\n#     print('Start 1')\n    for i in range(len(item_id[:])):\n        item_fol = os.listdir(INPUT + '/' + fol + '/' + item_id[i] + '/' + Types[Itype])\n        item_fol2 = []\n        for j in item_fol:\n            k = 1000 + int(j[6:len(j)-4])\n            item_fol2 = item_fol2 + [k]\n        item_fols = sorted(item_fol2)\n\n        heikin = []\n        hensa = []\n        saidai = []\n        for j in item_fols:\n            l = str(j-1000)\n            path = INPUT + '/' + fol + '/' + item_id[i] + '/' + Types[Itype] + '/Image-' + l + '.dcm'\n            dicom = pydicom.read_file(path)\n            data = dicom.pixel_array\n            dataF = data.flatten()\n            dataB = np.setdiff1d(dataF, [0])\n            if len(dataB) > 0:\n                heikin = heikin + [np.nanmean(dataB)]\n                hensa = hensa + [np.nanstd(dataB, ddof=1)]\n                saidai = saidai + [np.nanmax(dataB)]\n#         print(i, np.mean(heikin), np.std(heikin, ddof=1), np.mean(hensa), np.std(hensa, ddof=1))           \n#         print(i, np.mean(saidai), np.std(saidai, ddof=1))           \n            \n        df.loc[i, str(Itype)+'h1'] = np.nanmean(heikin)\n        df.loc[i, str(Itype)+'h2'] = np.nanstd(heikin, ddof=1)\n        df.loc[i, str(Itype)+'h3'] = np.nanmean(hensa)\n        df.loc[i, str(Itype)+'h4'] = np.nanstd(hensa, ddof=1)\n        df.loc[i, str(Itype)+'h5'] = np.nanmean(saidai)\n        df.loc[i, str(Itype)+'h6'] = np.nanstd(saidai, ddof=1)\n    return df\n\ndef GenerateD(df, fol, Itype): # fol: 'train'; Itype: 'FLAIR'\n    Types = ['FLAIR', 'T1w', 'T1wCE', 'T2w']\n#     print('Start 1')\n    for i in range(len(item_id[:])):\n        item_fol = os.listdir(INPUT + '/' + fol + '/' + item_id[i] + '/' + Types[Itype])\n        item_fol2 = []\n        for j in item_fol:\n            k = 1000 + int(j[6:len(j)-4])\n            item_fol2 = item_fol2 + [k]\n        item_fols = sorted(item_fol2)\n        volume = 0\n        intensity = 0\n        image_count = 0\n        vac = 0\n        Gmax = 0\n        Gmin = 0\n#         Amax = 0\n#         Imax = 0\n#         area_prev = 0\n#         sumN_prev = 0\n#         changeMax = 0\n#         maxName ='none'\n#         AmaxName ='none'\n#         ImaxName ='none'\n#         CmaxName ='00000'\n        for j in item_fols:\n            l = str(j-1000)\n            path = INPUT + '/' + fol + '/' + item_id[i] + '/' + Types[Itype] + '/Image-' + l + '.dcm'\n            dicom = pydicom.read_file(path)\n            data = dicom.pixel_array\n            sumN = np.sum(data)\n#             sumN_plus = sumN - sumN_prev\n#             sumN_prev = sumN\n#             if sumN > Imax:\n#                 Imax = sumN\n#                 ImaxName = j\n            maxN = np.max(data)\n            if maxN > Gmax:\n                Gmax = maxN\n#                 maxName = j\n            minN = np.min(data)\n            if minN < Gmin:\n                Gmin = minN\n            zerocount = np.count_nonzero(data == 0)\n            area = np.count_nonzero(data != 0)\n            if area >0:\n                image_count = image_count +1\n#             area_plus = area - area_prev\n#             area_prev = area\n#             if area > Amax:\n#                 Amax = area\n#                 AmaxName = j\n#             change = -(sumN_plus/(area_plus+1))\n#             if change > changeMax:\n#                 changeMax = change\n#                 CmaxName = j\n            intensity = intensity + sumN\n            volume = volume + area\n            vac = vac + zerocount\n        average = intensity/(volume+1)\n        df.loc[i, str(Itype)+'c0'] = len(item_fol)\n        df.loc[i, str(Itype)+'c1'] = image_count\n        df.loc[i, str(Itype)+'c2'] = intensity\n        df.loc[i, str(Itype)+'c3'] = volume\n        df.loc[i, str(Itype)+'c4'] = vac\n        df.loc[i, str(Itype)+'c5'] = volume+vac\n        df.loc[i, str(Itype)+'c6'] = average\n        df.loc[i, str(Itype)+'c7'] = Gmin\n        df.loc[i, str(Itype)+'c8'] = Gmax\n        df.loc[i, str(Itype)+'c9'] = Gmax-average\n#         df.loc[i,'c10'] = 'Image-' + str(int(CmaxName) -1000) + '.dcm'\n#         print(i, len(item_fol), image_count, intensity, volume, average, Gmin, Gmax, Gmax-average)#, 'Image-' + str(int(CmaxName) -1000) + '.dcm')\n    return df\n\ndef GenerateD2(df, fol, Itype): # fol: 'train'; Itype: 'FLAIR'\n    Types = ['FLAIR', 'T1w', 'T1wCE', 'T2w']\n    for i in range(len(item_id[:])):\n        item_fol = os.listdir(INPUT + '/' + fol + '/' + item_id[i] + '/' + Types[Itype])\n        item_fol2 = []\n        for j in item_fol:\n            k = 1000 + int(j[6:len(j)-4])\n            item_fol2 = item_fol2 + [k]\n        item_fols = sorted(item_fol2)\n        Gmean = df[str(Itype)+'c6'][i] # Gmean\n        B10 = Gmean * 0.2\n        B20 = Gmean * 0.4\n        B30 = Gmean * 0.6\n        B40 = Gmean * 0.8\n        B50 = Gmean\n        B60 = Gmean * 1.2\n        B70 = Gmean * 1.4\n        B80 = Gmean * 1.6\n        B90 = Gmean * 1.8\n        B100 = Gmean * 2\n        B110 = Gmean * 2.2\n        B120 = Gmean * 2.4\n        B130 = Gmean * 2.6\n        B140 = Gmean * 2.8\n        B150 = Gmean * 3\n        B160 = Gmean * 3.2\n        B170 = Gmean * 3.4\n        B180 = Gmean * 3.6\n        B190 = Gmean * 3.8\n        B200 = Gmean * 4\n        B210 = Gmean * 4.2\n        B220 = Gmean * 4.4\n        B230 = Gmean * 4.6\n        B240 = Gmean * 4.8\n        B250 = Gmean * 5\n        B260 = Gmean * 5.2\n        B270 = Gmean * 5.4\n        B280 = Gmean * 5.6\n        B290 = Gmean * 5.8\n        B300 = Gmean * 6\n        \n        count10 = 0\n        count20 = 0\n        count30 = 0\n        count40 = 0\n        count50 = 0\n        count60 = 0\n        count70 = 0\n        count80 = 0\n        count90 = 0\n        count100 = 0\n        count110 = 0\n        count120 = 0\n        count130 = 0\n        count140 = 0\n        count150 = 0\n        count160 = 0\n        count170 = 0\n        count180 = 0\n        count190 = 0\n        count200 = 0\n        count210 = 0\n        count220 = 0\n        count230 = 0\n        count240 = 0\n        count250 = 0\n        count260 = 0\n        count270 = 0\n        count280 = 0\n        count290 = 0\n        count300 = 0\n        \n        for j in item_fols:\n            l = str(j-1000)\n            path = INPUT + '/' + fol + '/' + item_id[i] + '/' + Types[Itype] + '/Image-' + l + '.dcm'\n            dicom = pydicom.read_file(path)\n            data = dicom.pixel_array\n            cou10 = np.count_nonzero(data < B10)\n            cou20 = np.count_nonzero(data < B20)\n            cou30 = np.count_nonzero(data < B30)\n            cou40 = np.count_nonzero(data < B40)\n            cou50 = np.count_nonzero(data < B50)\n            cou60 = np.count_nonzero(data < B60)\n            cou70 = np.count_nonzero(data < B70)\n            cou80 = np.count_nonzero(data < B80)\n            cou90 = np.count_nonzero(data < B90)\n            cou100 = np.count_nonzero(data < B100)\n            cou110 = np.count_nonzero(data < B110)\n            cou120 = np.count_nonzero(data < B120)\n            cou130 = np.count_nonzero(data < B130)\n            cou140 = np.count_nonzero(data < B140)\n            cou150 = np.count_nonzero(data < B150)\n            cou160 = np.count_nonzero(data < B160)\n            cou170 = np.count_nonzero(data < B170)\n            cou180 = np.count_nonzero(data < B180)\n            cou190 = np.count_nonzero(data < B190)\n            cou200 = np.count_nonzero(data < B200)\n            cou210 = np.count_nonzero(data < B210)\n            cou220 = np.count_nonzero(data < B220)\n            cou230 = np.count_nonzero(data < B230)\n            cou240 = np.count_nonzero(data < B240)\n            cou250 = np.count_nonzero(data < B250)\n            cou260 = np.count_nonzero(data < B260)\n            cou270 = np.count_nonzero(data < B270)\n            cou280 = np.count_nonzero(data < B280)\n            cou290 = np.count_nonzero(data < B290)\n            cou300 = np.count_nonzero(data < B300)\n\n            count10 = count10 + cou10\n            count20 = count20 + cou20\n            count30 = count30 + cou30\n            count40 = count40 + cou40\n            count50 = count50 + cou50\n            count60 = count60 + cou60\n            count70 = count70 + cou70\n            count80 = count80 + cou80\n            count90 = count90 + cou90\n            count100 = count100 + cou100\n            count110 = count110 + cou110\n            count120 = count120 + cou120\n            count130 = count130 + cou130\n            count140 = count140 + cou140\n            count150 = count150 + cou150\n            count160 = count160 + cou160\n            count170 = count170 + cou170\n            count180 = count180 + cou180\n            count190 = count190 + cou190\n            count200 = count200 + cou200\n            count210 = count210 + cou210\n            count220 = count220 + cou220\n            count230 = count230 + cou230\n            count240 = count240 + cou240\n            count250 = count250 + cou250\n            count260 = count260 + cou260\n            count270 = count270 + cou270\n            count280 = count280 + cou280\n            count290 = count290 + cou290\n            count300 = count300 + cou300\n\n        Volume1 = (df[str(Itype)+'c3'][i] + 1) / 100\n        vac = df[str(Itype)+'c4'][i]\n\n        df.loc[i, str(Itype)+'B1'] = (count10 - vac) / Volume1\n        df.loc[i, str(Itype)+'B2'] = (count20 - vac) / Volume1\n        df.loc[i, str(Itype)+'B3'] = (count30 - vac) / Volume1\n        df.loc[i, str(Itype)+'B4'] = (count40 - vac) / Volume1\n        df.loc[i, str(Itype)+'B5'] = (count50 - vac) / Volume1\n        df.loc[i, str(Itype)+'B6'] = (count60 - vac) / Volume1\n        df.loc[i, str(Itype)+'B7'] = (count70 - vac) / Volume1\n        df.loc[i, str(Itype)+'B8'] = (count80 - vac) / Volume1\n        df.loc[i, str(Itype)+'B9'] = (count90 - vac) / Volume1\n        df.loc[i, str(Itype)+'B10'] = (count100 - vac) / Volume1\n        df.loc[i, str(Itype)+'B11'] = (count110 - vac) / Volume1\n        df.loc[i, str(Itype)+'B12'] = (count120 - vac) / Volume1\n        df.loc[i, str(Itype)+'B13'] = (count130 - vac) / Volume1\n        df.loc[i, str(Itype)+'B14'] = (count140 - vac) / Volume1\n        df.loc[i, str(Itype)+'B15'] = (count150 - vac) / Volume1\n        df.loc[i, str(Itype)+'B16'] = (count160 - vac) / Volume1\n        df.loc[i, str(Itype)+'B17'] = (count170 - vac) / Volume1\n        df.loc[i, str(Itype)+'B18'] = (count180 - vac) / Volume1\n        df.loc[i, str(Itype)+'B19'] = (count190 - vac) / Volume1\n        df.loc[i, str(Itype)+'B20'] = (count200 - vac) / Volume1\n        df.loc[i, str(Itype)+'B21'] = (count210 - vac) / Volume1\n        df.loc[i, str(Itype)+'B22'] = (count220 - vac) / Volume1\n        df.loc[i, str(Itype)+'B23'] = (count230 - vac) / Volume1\n        df.loc[i, str(Itype)+'B24'] = (count240 - vac) / Volume1\n        df.loc[i, str(Itype)+'B25'] = (count250 - vac) / Volume1\n        df.loc[i, str(Itype)+'B26'] = (count260 - vac) / Volume1\n        df.loc[i, str(Itype)+'B27'] = (count270 - vac) / Volume1\n        df.loc[i, str(Itype)+'B28'] = (count280 - vac) / Volume1\n        df.loc[i, str(Itype)+'B29'] = (count290 - vac) / Volume1\n        df.loc[i, str(Itype)+'B30'] = (count300 - vac) / Volume1\n\n        \n        \n#         df.loc[i,'c12'] = P60 * 1e7 / c3val\n#         df.loc[i,'c13'] = P70 * 1e7 / c3val\n#         df.loc[i,'c14'] = P80 * 1e7 / c3val\n#         df.loc[i,'c15'] = P90 * 1e7 / c3val\n#         df.loc[i,'c16'] = P95 * 1e7 / c3val\n#         df.loc[i,'b1'] = (B10 - c4val) * 1e7 / c3val\n#         df.loc[i,'b2'] = (B20 - c4val) * 1e7 / c3val\n#         df.loc[i,'b3'] = (B30 - c4val) * 1e7 / c3val\n#         df.loc[i,'b4'] = (B40 - c4val) * 1e7 / c3val\n#         df.loc[i,'b5'] = (B50 - c4val) * 1e7 / c3val\n#         df.loc[i,'c17'] = F2 *  1e7 / c3val\n#         df.loc[i,'c18'] = F3 *  1e7 / c3val\n#         df.loc[i,'c19'] = F4 * 1e7 / c3val\n#         df.loc[i,'c20'] = F5 * 1e7 / c3val\n#         df.loc[i,'c21'] = F6 * 1e7 / c3val\n    return df\n\ndef AddDif1(df):\n    df2 = df\n    for i in range(4):\n        df2[str(i)+'d1'] = df[str(i)+'B1']\n        df2[str(i)+'d2'] = df[str(i)+'B2'] - df[str(i)+'B1']\n        df2[str(i)+'d3'] = df[str(i)+'B3'] - df[str(i)+'B2']\n        df2[str(i)+'d4'] = df[str(i)+'B4'] - df[str(i)+'B3']\n        df2[str(i)+'d5'] = df[str(i)+'B5'] - df[str(i)+'B4']\n        df2[str(i)+'d6'] = df[str(i)+'B6'] - df[str(i)+'B5']\n        df2[str(i)+'d7'] = df[str(i)+'B7'] - df[str(i)+'B6']\n        df2[str(i)+'d8'] = df[str(i)+'B8'] - df[str(i)+'B7']\n        df2[str(i)+'d9'] = df[str(i)+'B9'] - df[str(i)+'B8']\n        df2[str(i)+'d10'] = df[str(i)+'B10'] - df[str(i)+'B9']\n        df2[str(i)+'d11'] = df[str(i)+'B11'] - df[str(i)+'B10']\n        df2[str(i)+'d12'] = df[str(i)+'B12'] - df[str(i)+'B11']\n        df2[str(i)+'d13'] = df[str(i)+'B13'] - df[str(i)+'B12']\n        df2[str(i)+'d14'] = df[str(i)+'B14'] - df[str(i)+'B13']\n        df2[str(i)+'d15'] = df[str(i)+'B15'] - df[str(i)+'B14']\n        df2[str(i)+'d16'] = df[str(i)+'B16'] - df[str(i)+'B15']\n        df2[str(i)+'d17'] = df[str(i)+'B17'] - df[str(i)+'B16']\n        df2[str(i)+'d18'] = df[str(i)+'B18'] - df[str(i)+'B17']\n        df2[str(i)+'d19'] = df[str(i)+'B19'] - df[str(i)+'B18']\n        df2[str(i)+'d20'] = df[str(i)+'B20'] - df[str(i)+'B19']\n        df2[str(i)+'d21'] = df[str(i)+'B21'] - df[str(i)+'B20']\n        df2[str(i)+'d22'] = df[str(i)+'B22'] - df[str(i)+'B21']\n        df2[str(i)+'d23'] = df[str(i)+'B23'] - df[str(i)+'B22']\n        df2[str(i)+'d24'] = df[str(i)+'B24'] - df[str(i)+'B23']\n        df2[str(i)+'d25'] = df[str(i)+'B25'] - df[str(i)+'B24']\n        df2[str(i)+'d26'] = df[str(i)+'B26'] - df[str(i)+'B25']\n        df2[str(i)+'d27'] = df[str(i)+'B27'] - df[str(i)+'B26']\n        df2[str(i)+'d28'] = df[str(i)+'B28'] - df[str(i)+'B27']\n        df2[str(i)+'d29'] = df[str(i)+'B29'] - df[str(i)+'B28']\n        df2[str(i)+'d30'] = df[str(i)+'B30'] - df[str(i)+'B29']\n        df2[str(i)+'d31'] = df[str(i)+'c3']/((df[str(i)+'c3']+1)/100) - df[str(i)+'B30']\n        df2[str(i)+'d32'] = df[str(i)+'d1'] + df[str(i)+'d2'] + df[str(i)+'d3'] + df[str(i)+'d4'] + df[str(i)+'d5'] + df[str(i)+'d6'] + df[str(i)+'d7'] + df[str(i)+'d8'] + df[str(i)+'d9'] + df[str(i)+'d10'] + df[str(i)+'d11'] + df[str(i)+'d12'] + df[str(i)+'d13'] + df[str(i)+'d14'] + df[str(i)+'d15'] + df[str(i)+'d16'] + df[str(i)+'d17'] + df[str(i)+'d18'] + df[str(i)+'d19'] + df[str(i)+'d20'] + df[str(i)+'d21'] + df[str(i)+'d22'] + df[str(i)+'d23'] + df[str(i)+'d24'] + df[str(i)+'d25'] + df[str(i)+'d26'] + df[str(i)+'d27'] + df[str(i)+'d28'] + df[str(i)+'d29'] + df[str(i)+'d30'] + df[str(i)+'d31']\n\n    return df2\n","metadata":{"_kg_hide-input":true,"_kg_hide-output":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for i in range(4):\n    train_lab = GenerateH(train_lab, 'train', i) # fol: 'train'; Itype: 'FLAIR', 'T1w', 'T2w', 'T2w'\n\nfor i in range(4):\n    train_lab = GenerateD(train_lab, 'train', i) # fol: 'train'; Itype: 'FLAIR', 'T1w', 'T2w', 'T2w'\n\nfor i in range(4):\n    train_lab = GenerateD2(train_lab, 'train', i) # fol: 'train'; Itype: 'FLAIR'\n\ntrain_lab.to_csv('Table_trainAx.csv', index=False)\ntrain_lab2 = train_lab[train_lab['0c2'] != 0]\ntrain_lab2 = train_lab2[train_lab['1c2'] != 0]\ntrain_lab2 = train_lab2[train_lab['2c2'] != 0]\ntrain_lab2 = train_lab2[train_lab['3c2'] != 0]\ntrain_lab2 = train_lab2.reset_index()\ntrain_data = train_lab2.drop('index', axis=1)\n\ntrain_data = AddDif1(train_data)\n\ntrain_data.to_csv('Table_trainBx.csv', index=False)\n\ntrain_data.head(5)","metadata":{"_kg_hide-input":true,"_kg_hide-output":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"if Debug_mode == True:\n    sample_sub = sample_sub.iloc[:5,:] ###########################################\n\ntemp = sample_sub['BraTS21ID'] + 100000\nitem_id = []\nfor i in range(len(sample_sub)):\n    item_id = item_id + [str(temp[i])[-5:]]\n# print('Number of samples in test data')\nlen(item_id)   # 87\n\nfor i in range(4):\n    sample_sub = GenerateH(sample_sub, 'test', i) # fol: 'train'; Itype: 'FLAIR'\n\nfor i in range(4):\n    sample_sub = GenerateD(sample_sub, 'test', i) # fol: 'train'; Itype: 'FLAIR'\n\nfor i in range(4):\n    sample_sub = GenerateD2(sample_sub, 'test', i) # fol: 'train'; Itype: 'FLAIR'\n\nsample_sub.to_csv('Table_testAx.csv', index=False)\ntest_data = sample_sub\n\ntest_data = AddDif1(test_data)\ntest_data.to_csv('Table_testBx.csv', index=False)\ntest_data.head(5)","metadata":{"_kg_hide-input":true,"_kg_hide-output":true},"execution_count":null,"outputs":[]}]}