diff --git "a/physLSTM/lstm_vav_rtu4.ipynb" "b/physLSTM/lstm_vav_rtu4.ipynb" new file mode 100644--- /dev/null +++ "b/physLSTM/lstm_vav_rtu4.ipynb" @@ -0,0 +1,812 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "from datetime import datetime \n", + "from datetime import date\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "from keras.models import Sequential\n", + "from keras.layers import LSTM, Dense\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import MinMaxScaler,StandardScaler\n", + "from keras.callbacks import ModelCheckpoint\n", + "import tensorflow as tf\n", + "import joblib\n", + "from datetime import datetime" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "merged = pd.read_csv(r'../data/long_merge.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "zones = [16, 17, 21,23,24, 46,47, 51,52,53,54]\n", + "rtu = 4\n", + "cols = []\n", + "\n", + "for zone in zones:\n", + " for column in merged.columns:\n", + " if (\n", + " f\"zone_0{zone}\" in column\n", + " and \"co2\" not in column\n", + " and \"hw_valve\" not in column\n", + " and \"cooling_sp\" not in column\n", + " and \"heating_sp\" not in column\n", + " ):\n", + " cols.append(column)\n", + "\n", + "for zone in zones:\n", + " for column in merged.columns:\n", + " if f\"zone_0{zone}\" in column:\n", + " if \"cooling_sp\" in column or \"heating_sp\" in column:\n", + " cols.append(column)\n", + "# for rtu in rtus:\n", + "# for column in merged.columns:\n", + "# if f\"rtu_00{rtu}_fltrd_sa\" in column:\n", + "# cols.append(column)\n", + "cols = (\n", + " [\"date\"]\n", + " + cols\n", + " + [\n", + " f\"rtu_00{rtu}_fltrd_sa_flow_tn\",\n", + " f\"rtu_00{rtu}_sa_temp\",\n", + " \"air_temp_set_1\",\n", + " \"air_temp_set_2\",\n", + " \"dew_point_temperature_set_1d\",\n", + " \"relative_humidity_set_1\",\n", + " \"solar_radiation_set_1\",\n", + " ]\n", + ")\n", + "input_dataset = merged[cols]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "50" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(cols)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\arbal\\AppData\\Local\\Temp\\ipykernel_151912\\1855433847.py:1: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " input_dataset['date'] = pd.to_datetime(input_dataset['date'], format = \"%Y-%m-%d %H:%M:%S\")\n" + ] + } + ], + "source": [ + "input_dataset['date'] = pd.to_datetime(input_dataset['date'], format = \"%Y-%m-%d %H:%M:%S\")\n", + "df_filtered = input_dataset[ (input_dataset.date.dt.date >date(2019, 3, 1)) & (input_dataset.date.dt.date< date(2021, 1, 1))]\n", + "\n", + "if df_filtered.isna().any().any():\n", + " print(\"There are NA values in the DataFrame columns.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "testdataset_df = df_filtered[(df_filtered.date.dt.date >date(2020, 3, 1)) & (df_filtered.date.dt.date date(2019, 3, 1)) & (df_filtered.date.dt.date date(2020, 7, 1)) & (df_filtered.date.dt.date 11\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalidation_data\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mX_test\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_test\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m128\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mcheckpoint_callback\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\keras\\src\\utils\\traceback_utils.py:117\u001b[0m, in \u001b[0;36mfilter_traceback..error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 115\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 116\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 117\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 118\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m 119\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\keras\\src\\backend\\tensorflow\\trainer.py:314\u001b[0m, in \u001b[0;36mTensorFlowTrainer.fit\u001b[1;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq)\u001b[0m\n\u001b[0;32m 312\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step, iterator \u001b[38;5;129;01min\u001b[39;00m epoch_iterator\u001b[38;5;241m.\u001b[39menumerate_epoch():\n\u001b[0;32m 313\u001b[0m callbacks\u001b[38;5;241m.\u001b[39mon_train_batch_begin(step)\n\u001b[1;32m--> 314\u001b[0m logs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 315\u001b[0m logs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pythonify_logs(logs)\n\u001b[0;32m 316\u001b[0m callbacks\u001b[38;5;241m.\u001b[39mon_train_batch_end(step, logs)\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\util\\traceback_utils.py:150\u001b[0m, in \u001b[0;36mfilter_traceback..error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 148\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 149\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 150\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m 152\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\polymorphic_function\\polymorphic_function.py:833\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 830\u001b[0m compiler \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mxla\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnonXla\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 832\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m OptionalXlaContext(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile):\n\u001b[1;32m--> 833\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 835\u001b[0m new_tracing_count \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexperimental_get_tracing_count()\n\u001b[0;32m 836\u001b[0m without_tracing \u001b[38;5;241m=\u001b[39m (tracing_count \u001b[38;5;241m==\u001b[39m new_tracing_count)\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\polymorphic_function\\polymorphic_function.py:878\u001b[0m, in \u001b[0;36mFunction._call\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 875\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock\u001b[38;5;241m.\u001b[39mrelease()\n\u001b[0;32m 876\u001b[0m \u001b[38;5;66;03m# In this case we have not created variables on the first call. So we can\u001b[39;00m\n\u001b[0;32m 877\u001b[0m \u001b[38;5;66;03m# run the first trace but we should fail if variables are created.\u001b[39;00m\n\u001b[1;32m--> 878\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mtracing_compilation\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_function\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 879\u001b[0m \u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_variable_creation_config\u001b[49m\n\u001b[0;32m 880\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 881\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_created_variables:\n\u001b[0;32m 882\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreating variables on a non-first call to a function\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 883\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m decorated with tf.function.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\polymorphic_function\\tracing_compilation.py:139\u001b[0m, in \u001b[0;36mcall_function\u001b[1;34m(args, kwargs, tracing_options)\u001b[0m\n\u001b[0;32m 137\u001b[0m bound_args \u001b[38;5;241m=\u001b[39m function\u001b[38;5;241m.\u001b[39mfunction_type\u001b[38;5;241m.\u001b[39mbind(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 138\u001b[0m flat_inputs \u001b[38;5;241m=\u001b[39m function\u001b[38;5;241m.\u001b[39mfunction_type\u001b[38;5;241m.\u001b[39munpack_inputs(bound_args)\n\u001b[1;32m--> 139\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunction\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_flat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# pylint: disable=protected-access\u001b[39;49;00m\n\u001b[0;32m 140\u001b[0m \u001b[43m \u001b[49m\u001b[43mflat_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcaptured_inputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfunction\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcaptured_inputs\u001b[49m\n\u001b[0;32m 141\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\polymorphic_function\\concrete_function.py:1322\u001b[0m, in \u001b[0;36mConcreteFunction._call_flat\u001b[1;34m(self, tensor_inputs, captured_inputs)\u001b[0m\n\u001b[0;32m 1318\u001b[0m possible_gradient_type \u001b[38;5;241m=\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPossibleTapeGradientTypes(args)\n\u001b[0;32m 1319\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (possible_gradient_type \u001b[38;5;241m==\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPOSSIBLE_GRADIENT_TYPES_NONE\n\u001b[0;32m 1320\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m executing_eagerly):\n\u001b[0;32m 1321\u001b[0m \u001b[38;5;66;03m# No tape is watching; skip to running the function.\u001b[39;00m\n\u001b[1;32m-> 1322\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_inference_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_preflattened\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1323\u001b[0m forward_backward \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_select_forward_and_backward_functions(\n\u001b[0;32m 1324\u001b[0m args,\n\u001b[0;32m 1325\u001b[0m possible_gradient_type,\n\u001b[0;32m 1326\u001b[0m executing_eagerly)\n\u001b[0;32m 1327\u001b[0m forward_function, args_with_tangents \u001b[38;5;241m=\u001b[39m forward_backward\u001b[38;5;241m.\u001b[39mforward()\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\polymorphic_function\\atomic_function.py:216\u001b[0m, in \u001b[0;36mAtomicFunction.call_preflattened\u001b[1;34m(self, args)\u001b[0m\n\u001b[0;32m 214\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcall_preflattened\u001b[39m(\u001b[38;5;28mself\u001b[39m, args: Sequence[core\u001b[38;5;241m.\u001b[39mTensor]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Any:\n\u001b[0;32m 215\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Calls with flattened tensor inputs and returns the structured output.\"\"\"\u001b[39;00m\n\u001b[1;32m--> 216\u001b[0m flat_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_flat\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 217\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfunction_type\u001b[38;5;241m.\u001b[39mpack_output(flat_outputs)\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\polymorphic_function\\atomic_function.py:251\u001b[0m, in \u001b[0;36mAtomicFunction.call_flat\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m 249\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m record\u001b[38;5;241m.\u001b[39mstop_recording():\n\u001b[0;32m 250\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_bound_context\u001b[38;5;241m.\u001b[39mexecuting_eagerly():\n\u001b[1;32m--> 251\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_bound_context\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_function\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 252\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 253\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 254\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunction_type\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflat_outputs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 255\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 256\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 257\u001b[0m outputs \u001b[38;5;241m=\u001b[39m make_call_op_in_graph(\n\u001b[0;32m 258\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 259\u001b[0m \u001b[38;5;28mlist\u001b[39m(args),\n\u001b[0;32m 260\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_bound_context\u001b[38;5;241m.\u001b[39mfunction_call_options\u001b[38;5;241m.\u001b[39mas_attrs(),\n\u001b[0;32m 261\u001b[0m )\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\context.py:1500\u001b[0m, in \u001b[0;36mContext.call_function\u001b[1;34m(self, name, tensor_inputs, num_outputs)\u001b[0m\n\u001b[0;32m 1498\u001b[0m cancellation_context \u001b[38;5;241m=\u001b[39m cancellation\u001b[38;5;241m.\u001b[39mcontext()\n\u001b[0;32m 1499\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cancellation_context \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 1500\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mexecute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1501\u001b[0m \u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mutf-8\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1502\u001b[0m \u001b[43m \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_outputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1503\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtensor_inputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1504\u001b[0m \u001b[43m \u001b[49m\u001b[43mattrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1505\u001b[0m \u001b[43m \u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1506\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1507\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 1508\u001b[0m outputs \u001b[38;5;241m=\u001b[39m execute\u001b[38;5;241m.\u001b[39mexecute_with_cancellation(\n\u001b[0;32m 1509\u001b[0m name\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m 1510\u001b[0m num_outputs\u001b[38;5;241m=\u001b[39mnum_outputs,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1514\u001b[0m cancellation_manager\u001b[38;5;241m=\u001b[39mcancellation_context,\n\u001b[0;32m 1515\u001b[0m )\n", + "File \u001b[1;32md:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\tensorflow\\python\\eager\\execute.py:53\u001b[0m, in \u001b[0;36mquick_execute\u001b[1;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[0;32m 51\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m 52\u001b[0m ctx\u001b[38;5;241m.\u001b[39mensure_initialized()\n\u001b[1;32m---> 53\u001b[0m tensors \u001b[38;5;241m=\u001b[39m \u001b[43mpywrap_tfe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTFE_Py_Execute\u001b[49m\u001b[43m(\u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_handle\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mop_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 54\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 55\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m core\u001b[38;5;241m.\u001b[39m_NotOkStatusException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m 56\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "\u001b[1;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "\n", + "model = Sequential()\n", + "model.add(LSTM(units=50, return_sequences=True, input_shape=(X_train.shape[1], X_train.shape[2])))\n", + "model.add(LSTM(units=50, return_sequences=True))\n", + "model.add(LSTM(units=30))\n", + "model.add(Dense(units=y_train.shape[1]))\n", + "\n", + "model.compile(optimizer='adam', loss='mean_squared_error')\n", + "\n", + "checkpoint_path = \"lstm_vav_04.keras\"\n", + "checkpoint_callback = ModelCheckpoint(filepath=checkpoint_path, monitor='val_loss', verbose=1, save_best_only=True, mode='min')\n", + "model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=1, batch_size=128, verbose=1, callbacks=[checkpoint_callback])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model.load_weights(checkpoint_path)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m12244/12244\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m114s\u001b[0m 9ms/step\n" + ] + } + ], + "source": [ + "test_predict1 = model.predict(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{0: 'zone_061_fan_spd',\n", + " 1: 'zone_056_temp',\n", + " 2: 'zone_056_fan_spd',\n", + " 3: 'zone_055_temp',\n", + " 4: 'zone_055_fan_spd',\n", + " 5: 'zone_048_temp',\n", + " 6: 'zone_048_fan_spd',\n", + " 7: 'zone_045_temp',\n", + " 8: 'zone_045_fan_spd',\n", + " 9: 'zone_026_temp',\n", + " 10: 'zone_026_fan_spd',\n", + " 11: 'zone_025_temp',\n", + " 12: 'zone_025_fan_spd',\n", + " 13: 'zone_018_temp',\n", + " 14: 'zone_018_fan_spd',\n", + " 15: 'zone_061_cooling_sp',\n", + " 16: 'zone_061_heating_sp',\n", + " 17: 'zone_056_cooling_sp',\n", + " 18: 'zone_056_heating_sp',\n", + " 19: 'zone_055_cooling_sp',\n", + " 20: 'zone_055_heating_sp',\n", + " 21: 'zone_048_cooling_sp',\n", + " 22: 'zone_048_heating_sp',\n", + " 23: 'zone_026_cooling_sp',\n", + " 24: 'zone_026_heating_sp',\n", + " 25: 'zone_025_cooling_sp',\n", + " 26: 'zone_025_heating_sp',\n", + " 27: 'zone_018_cooling_sp',\n", + " 28: 'zone_018_heating_sp',\n", + " 29: 'rtu_003_fltrd_sa_flow_tn',\n", + " 30: 'rtu_003_sa_temp',\n", + " 31: 'air_temp_set_1',\n", + " 32: 'air_temp_set_2',\n", + " 33: 'dew_point_temperature_set_1d',\n", + " 34: 'relative_humidity_set_1',\n", + " 35: 'solar_radiation_set_1'}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "idx_2_col = {}\n", + "for i, col in enumerate(traindataset_df.columns[1:]):\n", + " idx_2_col[i] = col\n", + "\n", + "idx_2_col" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(391787, 16)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_predict1.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "test_predict1_unscaled = test_predict1*scaler.scale_[0:22] + scaler.mean_[0:22]\n", + "y_test_unscaled = y_test*scaler.scale_[0:22] + scaler.mean_[0:22]" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "d:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:7588: FutureWarning: Dtype inference on a pandas object (Series, Index, ExtensionArray) is deprecated. The Index constructor will keep the original dtype in the future. Call `infer_objects` on the result to get the old behavior.\n", + " return Index(sequences[0], name=names)\n", + "d:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:7588: FutureWarning: Dtype inference on a pandas object (Series, Index, ExtensionArray) is deprecated. The Index constructor will keep the original dtype in the future. Call `infer_objects` on the result to get the old behavior.\n", + " return Index(sequences[0], name=names)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "var = 0\n", + "\n", + "df = pd.DataFrame([testdataset_df.index[31:],test_predict1_unscaled[:,var], y_test_unscaled[:,var]] ).T\n", + "fig, ax = plt.subplots(figsize=(10,8))\n", + "df.plot(x = 0, y=1, ax = ax, label = 'Predicted')\n", + "df.plot(x = 0, y=2, ax = ax, label = 'Actual')\n", + "\n", + "anomalies = df.where(df[1]-df[2]>0.38)[0]\n", + "df['anomalies'] = anomalies\n", + "\n", + "df_new = df.dropna()\n", + "\n", + "df_new.plot.scatter(x='anomalies', y=1, c='r', ax = ax, label = 'Anomalies')\n", + "\n", + "# ax.scatter(anomalies,test_predict1[anomalies,var], color='black',marker =\"o\",s=100 )\n", + "\n", + "\n", + "ax.set_title('Testing Data - Predicted vs Actual [Zone 72 Temperature]', fontsize=20)\n", + "ax.set_xlabel('Time', fontsize=15)\n", + "ax.set_ylabel('Value', fontsize = 15)\n", + "ax.legend(fontsize = 15)\n", + "fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "d:\\anaconda3\\envs\\smartbuilding\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:7588: FutureWarning: Dtype inference on a pandas object (Series, Index, ExtensionArray) is deprecated. The Index constructor will keep the original dtype in the future. Call `infer_objects` on the result to get the old behavior.\n", + " return Index(sequences[0], name=names)\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'MSE')" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10,8))\n", + "df['residual'] = df[1] - df[2]\n", + "df['mse'] = (df[1] - df[2])**2\n", + "df.plot(x = 0, y='mse', figsize=(10,8), title = 'Mean Squared Error', ax = ax)\n", + "ax.set_xlabel('Time', fontsize=15)\n", + "ax.set_ylabel('MSE', fontsize = 15)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['pca_vav_3.pkl']" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.cluster import KMeans\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.decomposition import PCA\n", + "\n", + "# Generating random data for demonstration\n", + "np.random.seed(0)\n", + "X = (test_predict1 - y_test)\n", + "\n", + "k = 2\n", + "\n", + "pca = PCA(n_components=2)\n", + "X = pca.fit_transform(X)\n", + "\n", + "kmeans = KMeans(n_clusters=k)\n", + "\n", + "kmeans.fit(X)\n", + "\n", + "\n", + "\n", + "# Getting the cluster centers and labels\n", + "centroids = kmeans.cluster_centers_\n", + "# centroids = pca.transform(centroids)\n", + "labels = kmeans.labels_\n", + "\n", + "# Plotting the data points and cluster centers\n", + "plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='viridis', alpha=0.5)\n", + "plt.scatter(centroids[:, 0], centroids[:, 1], marker='x', c='red', s=200, linewidths=2)\n", + "plt.text(centroids[0,0]+0.2, centroids[0,1]+0.5, 'Normal', fontsize=12, color='red')\n", + "plt.text(centroids[1,0]+0.5, centroids[1,1]+0.2, 'Anomaly', fontsize=12, color='red')\n", + "plt.title('KMeans Clustering')\n", + "plt.xlabel('Feature 1')\n", + "plt.ylabel('Feature 2')\n", + "plt.tight_layout()\n", + "\n", + "joblib.dump(kmeans, 'kmeans_vav_4.pkl')\n", + "joblib.dump(pca, 'pca_vav_4.pkl')" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(391787, 16)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(test_predict1 - y_test).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "k = 60\n", + "X= test_predict1 - y_test\n", + "processed_data = []\n", + "feat_df = pd.DataFrame(columns=[\"mean\",\"std\",])\n", + "for i in range(0,len(X), 60):\n", + " mean = X[i:i+k].mean(axis = 0)\n", + " std = X[i:i+k].std(axis = 0)\n", + " max = X[i:i+k].max(axis = 0)\n", + " min = X[i:i+k].min(axis = 0)\n", + " iqr = np.percentile(X[i:i+k], 75, axis=0) - np.percentile(X[i:i+k], 25,axis=0)\n", + " data = np.concatenate([mean, std, max, min, iqr])\n", + " processed_data.append([data])\n", + "processed_data = np.concatenate(processed_data,axis=0) " + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "X = processed_data\n", + "\n", + "kmeans = KMeans(n_clusters=2, algorithm='elkan', max_iter=1000, n_init = 5)\n", + "\n", + "kmeans.fit(X)\n", + "\n", + "pca = PCA(n_components=2)\n", + "X = pca.fit_transform(X)\n", + "\n", + "\n", + "# Getting the cluster centers and labels\n", + "centroids = kmeans.cluster_centers_\n", + "centroids = pca.transform(centroids)\n", + "labels = kmeans.labels_\n", + "\n", + "# Plotting the data points and cluster centers\n", + "plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='viridis', alpha=0.5)\n", + "plt.scatter(centroids[:, 0], centroids[:, 1], marker='x', c='red', s=200, linewidths=2)\n", + "plt.title('KMeans Clustering')\n", + "plt.xlabel('Feature 1')\n", + "plt.ylabel('Feature 2')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.mixture import GaussianMixture\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.decomposition import PCA\n", + "\n", + "# Generating random data for demonstration\n", + "np.random.seed(0)\n", + "X = processed_data\n", + "\n", + "# Creating the GMM instance with desired number of clusters\n", + "gmm = GaussianMixture(n_components=2, init_params='k-means++')\n", + "\n", + "# Fitting the model to the data\n", + "gmm.fit(X)\n", + "labels = gmm.predict(X)\n", + "\n", + "\n", + "pca = PCA(n_components=2)\n", + "X = pca.fit_transform(X)\n", + "\n", + "\n", + "# Getting the cluster labels\n", + "\n", + "# Plotting the data points with colors representing different clusters\n", + "plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='viridis', alpha=0.5)\n", + "plt.title('GMM Clustering')\n", + "plt.xlabel('Feature 1')\n", + "plt.ylabel('Feature 2')\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.cluster import KMeans\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "# Generating random data for demonstration\n", + "np.random.seed(0)\n", + "X = test_predict1 - y_test \n", + "\n", + "kmeans = KMeans(n_clusters=2)\n", + "\n", + "kmeans.fit(X)\n", + "\n", + "\n", + "pca = PCA(n_components=2)\n", + "X = pca.fit_transform(X)\n", + "\n", + "\n", + "\n", + "# Getting the cluster centers and labels\n", + "centroids = kmeans.cluster_centers_\n", + "centroids = pca.transform(centroids)\n", + "labels = kmeans.labels_\n", + "\n", + "# Plotting the data points and cluster centers\n", + "plt.figure()\n", + "plt.scatter(X[:, 0], X[:, 1], c=labels, cmap='viridis', alpha=0.5)\n", + "plt.scatter(centroids[:, 0], centroids[:, 1], marker='x', c='red', s=200, linewidths=2)\n", + "plt.text(centroids[0,0], centroids[0,1], 'Normal', fontsize=12, color='red')\n", + "plt.text(centroids[1,0], centroids[1,1], 'Anomaly', fontsize=12, color='red')\n", + "plt.title('KMeans Clustering')\n", + "plt.xlabel('Feature 1')\n", + "plt.ylabel('Feature 2')\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "tensorflow", + "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": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}