{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":87230,"databundleVersionId":9911932,"sourceType":"competition"}],"dockerImageVersionId":30786,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import numpy as np\nimport matplotlib.pyplot as plt\nimport random\nimport glob\n\nfig, axes = plt.subplots(10, 1, figsize=(5, 10 * 5))\nfiles = glob.glob('/kaggle/input/gpr-max-deep-learning-challenge-1-gdlc-1/Training_Bscan/Training_Bscan/*.npy')\n\nfor ax in axes:\n    file1, file2 = random.choice(files), random.choice(files)\n    file1_index = file1.split('/')[-1].split('.')[0]\n    file2_index = file2.split('/')[-1].split('.')[0]\n    data1 = np.load(file1)\n    data2 = np.load(file2)\n    im = ax.imshow(data1 == data2)\n    fig.colorbar(im, ax=ax, shrink=0.8)\n    ax.set_title(file1_index + '==' + file2_index)\n    \nplt.tight_layout()\nplt.show()","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-11-07T16:03:17.550901Z","iopub.execute_input":"2024-11-07T16:03:17.551369Z","iopub.status.idle":"2024-11-07T16:03:21.371108Z","shell.execute_reply.started":"2024-11-07T16:03:17.551324Z","shell.execute_reply":"2024-11-07T16:03:21.369744Z"},"collapsed":true,"jupyter":{"outputs_hidden":true},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}