{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":56537,"databundleVersionId":8877088,"sourceType":"competition"},{"sourceId":8957256,"sourceType":"datasetVersion","datasetId":5390890},{"sourceId":8957344,"sourceType":"datasetVersion","datasetId":5390958}],"dockerImageVersionId":30746,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport polars as pl\nimport pickle\nimport os","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-07-15T09:07:50.178984Z","iopub.execute_input":"2024-07-15T09:07:50.179504Z","iopub.status.idle":"2024-07-15T09:07:51.88391Z","shell.execute_reply.started":"2024-07-15T09:07:50.179457Z","shell.execute_reply":"2024-07-15T09:07:51.882659Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"preds_hr_files = os.listdir('/kaggle/input/leap-model-preds-hr')\npreds_hr = np.zeros((625000, 368))\nfor x in preds_hr_files:\n    preds_temp = pickle.load(open(f'/kaggle/input/leap-model-preds-hr/{x}', 'br'))\n    preds_hr = preds_hr+preds_temp\npreds_hr = preds_hr/len(preds_hr_files)","metadata":{"execution":{"iopub.status.busy":"2024-07-15T09:10:54.904532Z","iopub.execute_input":"2024-07-15T09:10:54.904954Z","iopub.status.idle":"2024-07-15T09:12:58.915814Z","shell.execute_reply.started":"2024-07-15T09:10:54.90492Z","shell.execute_reply":"2024-07-15T09:12:58.913603Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"preds_lr_files = os.listdir('/kaggle/input/leap-model-preds-lr')\npreds_lr = np.zeros((625000, 368))\nfor x in preds_lr_files:\n    preds_temp = pickle.load(open(f'/kaggle/input/leap-model-preds-lr/{x}', 'br'))\n    preds_lr = preds_lr+preds_temp\npreds_lr = preds_lr/len(preds_lr_files)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"preds = preds_hr*0.65+preds_lr*0.35\npickle.dump(preds, open('preds.p', 'bw'))","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sub = pd.read_csv(\"/kaggle/input/leap-atmospheric-physics-ai-climsim/sample_submission.csv\")\nsub.iloc[:len(preds),1:] = preds\ntest_polars = pl.from_pandas(sub)\ntest_polars.write_parquet(\"submission.parquet\")","metadata":{},"execution_count":null,"outputs":[]}]}