3197 lines
1.2 MiB
3197 lines
1.2 MiB
{
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||
"cells": [
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||
{
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"cell_type": "markdown",
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||
"metadata": {},
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"source": [
|
||
"# Bayesian Optimisation of starting Gaussian Process hyperparameters"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 2,
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||
"metadata": {
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||
"id": "Aovwtky_5Cao"
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||
},
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||
"outputs": [],
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||
"source": [
|
||
"from pathlib import Path\n",
|
||
"from shutil import copyfile\n",
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||
"import pickle"
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||
]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {
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||
"id": "a517af1c-4204-45c9-aae4-865a2cb259e9"
|
||
},
|
||
"source": [
|
||
"Data manipulation"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 1,
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||
"metadata": {
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||
"id": "62628e60-28c6-4a9a-8a81-22e5bfd74722"
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||
},
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||
"outputs": [],
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||
"source": [
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||
"import numpy as np\n",
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||
"import pandas as pd"
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]
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},
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{
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||
"cell_type": "markdown",
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||
"metadata": {
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||
"id": "acb33a41-06b9-4a1d-9ea7-6a2d87b1f4fb"
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||
},
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||
"source": [
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||
"Plotting / Visualisation"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 3,
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||
"metadata": {
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||
"id": "bVyvgbND5642"
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||
},
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||
"outputs": [],
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||
"source": [
|
||
"import matplotlib.pyplot as plt"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 4,
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||
"metadata": {
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||
"id": "E9mmvHyH57RO"
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||
},
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||
"outputs": [],
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||
"source": [
|
||
"%matplotlib inline\n",
|
||
"plt.rcParams[\"figure.figsize\"] = (15, 6)"
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||
]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {
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||
"id": "90fdac33-eed4-4ab4-b2b1-de0f1f27727b"
|
||
},
|
||
"source": [
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||
"Gaussian Process Regression"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 5,
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||
"metadata": {
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||
"id": "3Z6cHHaD6EkP"
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||
},
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||
"outputs": [],
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||
"source": [
|
||
"import gpflow\n",
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||
"import tensorflow as tf"
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]
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},
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{
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||
"cell_type": "code",
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||
"execution_count": 6,
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||
"metadata": {},
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||
"outputs": [
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||
{
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||
"data": {
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||
"text/plain": [
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||
"[name: \"/device:CPU:0\"\n",
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||
" device_type: \"CPU\"\n",
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||
" memory_limit: 268435456\n",
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||
" locality {\n",
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||
" }\n",
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||
" incarnation: 6682909200786859820]"
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||
]
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||
},
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||
"execution_count": 6,
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||
"metadata": {},
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||
"output_type": "execute_result"
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||
}
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||
],
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||
"source": [
|
||
"from tensorflow.python.client import device_lib\n",
|
||
"device_lib.list_local_devices()"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
|
||
"execution_count": 7,
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||
"metadata": {
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||
"id": "-fqvYTly6E9D"
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||
},
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||
"outputs": [],
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||
"source": [
|
||
"from gpflow.utilities import print_summary"
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]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 8,
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||
"metadata": {
|
||
"id": "VpKUUEvC6F7i"
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||
},
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||
"outputs": [],
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||
"source": [
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||
"gpflow.config.set_default_summary_fmt(\"notebook\")"
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]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
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||
"Input scaler:"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 9,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
|
||
"from sklearn.preprocessing import MinMaxScaler, RobustScaler\n",
|
||
"from sklearn.exceptions import NotFittedError"
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||
]
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},
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{
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||
"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
|
||
"Bayesian optimisation based on gaussian processes:"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 10,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
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||
"import trieste"
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||
]
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||
},
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||
{
|
||
"cell_type": "markdown",
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||
"metadata": {
|
||
"id": "0aba0df5-b0e3-4738-bb61-1dad869d1ea3"
|
||
},
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||
"source": [
|
||
"## Load previously exported data"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 11,
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||
"metadata": {
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||
"id": "wuz33V9a6W-a"
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||
},
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||
"outputs": [],
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||
"source": [
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||
"#dict_cols = pickle.load(open(Path(\"dict_cols.pkl\"), 'rb'))\n",
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"dfs_train = pickle.load(open(Path(\"dfs_train.pkl\"), 'rb'))\n",
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||
"dfs_test = pickle.load(open(Path(\"dfs_test.pkl\"), 'rb'))"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 45,
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||
"metadata": {},
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||
"outputs": [],
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"source": [
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||
"df = pd.read_csv(\"../Simulink/Exp1_table.csv\")\n",
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"df.rename(columns = {'Power': 'SimulatedHeat'}, inplace = True)"
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]
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},
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{
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||
"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"train_exps = ['Exp1', 'Exp3', 'Exp5', 'Exp6']\n",
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"test_exps = ['Exp2', 'Exp4', 'Exp7']"
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]
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},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 15,
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||
"metadata": {},
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||
"outputs": [],
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"source": [
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"t_cols = ['time_h', 'time_m']\n",
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"t_cols = []\n",
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"w_cols = ['SolRad', 'OutsideTemp']\n",
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"u_cols = ['SimulatedHeat']\n",
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"y_cols = ['SimulatedTemp']"
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]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 16,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
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||
"t_lags = 1\n",
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"w_lags = 0\n",
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"u_lags = 2\n",
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"y_lags = 3"
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]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 17,
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"metadata": {},
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||
"outputs": [],
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||
"source": [
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"dict_cols = {\n",
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" 't': (t_lags, t_cols),\n",
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" 'w': (w_lags, w_cols),\n",
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" 'u': (u_lags, u_cols),\n",
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||
" 'y': (y_lags, y_cols)\n",
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||
"}"
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||
]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
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||
"Create the scaler and set up input data scaling:"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 18,
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||
"metadata": {
|
||
"colab": {
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||
"base_uri": "https://localhost:8080/"
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||
},
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||
"id": "7uZWtjPo6XhD",
|
||
"outputId": "e0c4a8be-881e-4adc-a344-0b7e4ee9bc75"
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||
},
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||
"outputs": [],
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||
"source": [
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||
"scaler = MinMaxScaler(feature_range = (-1, 1))"
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]
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},
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{
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||
"cell_type": "code",
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||
"execution_count": 19,
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||
"metadata": {},
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||
"outputs": [],
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"source": [
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||
"def get_scaled_df(df, dict_cols, scaler):\n",
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" \n",
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" t_list = dict_cols['t'][1]\n",
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" w_list = dict_cols['w'][1]\n",
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" u_list = dict_cols['u'][1]\n",
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" y_list = dict_cols['y'][1]\n",
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" \n",
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" df_local = df[t_list + w_list + u_list + y_list]\n",
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" df_scaled = df_local.to_numpy()\n",
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" \n",
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" try:\n",
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" df_scaled = scaler.transform(df_scaled)\n",
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||
" except NotFittedError:\n",
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" df_scaled = scaler.fit_transform(df_scaled)\n",
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||
" \n",
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||
" df_scaled = pd.DataFrame(df_scaled, index = df_local.index, columns = df_local.columns)\n",
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||
" \n",
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||
" return df_scaled"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 20,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
|
||
"df_train = pd.concat(dfs_train)"
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||
]
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||
},
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||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Condition number of the raw input data:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"279119.2189692174"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.linalg.cond(df_train.to_numpy())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Fit the scaler and scale the data:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"df_train_sc = get_scaled_df(df_train, dict_cols, scaler)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
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||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"pickle.dump(scaler, open(Path(\"scaler.pkl\"), 'wb'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Check the condition number of the input data:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"4.482732755981847"
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.linalg.cond(df_train_sc.to_numpy())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"NOTE: Condition number of scaled data is much smaller. This makes sense."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Scale the data for each experiment individually. Used for validation graphs:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
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||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"dfs_train_sc = []\n",
|
||
"dfs_test_sc = []\n",
|
||
"for df in dfs_train:\n",
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||
" df_sc = get_scaled_df(df, dict_cols, scaler)\n",
|
||
" dfs_train_sc.append(df_sc)\n",
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||
" \n",
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||
"for df in dfs_test:\n",
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" df_sc = get_scaled_df(df, dict_cols, scaler)\n",
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||
" dfs_test_sc.append(df_sc)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([[<AxesSubplot:title={'center':'SolRad'}>,\n",
|
||
" <AxesSubplot:title={'center':'OutsideTemp'}>],\n",
|
||
" [<AxesSubplot:title={'center':'SimulatedHeat'}>,\n",
|
||
" <AxesSubplot:title={'center':'SimulatedTemp'}>]], dtype=object)"
|
||
]
|
||
},
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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tc26S5wNXA9uq6ouLTZRkK7AVYG5ujk6nM9CLbtu0f6D5h2FhYWHgdgxqWOth7oi1L2vS6wBg12e+fM/juSPgD998ydgzbNs0/GWu9u/Shr/FUnkH2cZWa9TroQ3v/WEZpC0WZ5IktcufAK8Eqrm/AHjhYhNW1Q5gB8DmzZtrfn5+oBde62Xfh+nCU45k0HYMaljrYdum/Vywa23/au05a34oGQbRux4GaUvbrLYtbftb9Brn32XU66HT6Uz8vT8sg7TFbo2SJLVIVd1WVXdX1deB1wOPn3QmSdJ4WJxJktQiSTb0PH0GcP1S00qS1pf1cXxakqQplOQtwDxwXJJbgFcA80keQ7db4x7gZyeVT5I0XhZnkiRNSFU9d5HBbxh7EElSK1icSZIkSVrWxhFfMGjbpv0rXoxnz/mnjzRDG3jOmSRJkiS1gMWZJEmSJLWAxZkkSZIktYDFmSRJkiS1gBcEkSRJaplRX3xBUjt55EySJEmSWqDv4izJIUn+JcllzfNjk1ye5Mbm/pjRxZQkSZKk9W01R85eAuzueb4duKKqTgKuaJ5LkiRJktagr+IsyUOA04E/6xl8BrCzebwTOHOoySRJkiRphvR75Oy1wK8BX+8ZNldVewGa++OHG02SJEmSZseKV2tM8nRgX1Vdk2R+tS+QZCuwFWBubo5Op7PaRQCwsLDAtk13r2neYeunDQsLC2tu6yRMU95pygrTlXeassJ05Z2mrJKkb/DKme3Rhr/FnvNPH+ny+7mU/pOAn0xyGnAf4P5J/hK4LcmGqtqbZAOwb7GZq2oHsANg8+bNNT8/v6agnU6HCz5w15rmHbY9Z82vOE2n02GtbZ2Eaco7TVlhuvJOU1aYrrzTlFWSJE3Git0aq+plVfWQqtoIPAd4b1U9D7gU2NJMtgW4ZGQpJUmSJGmdG+R3zs4HnprkRuCpzXNJkiRJ0hr0063xHlXVATrN488DJw8/kiRJkiTNnkGOnEmSJEmShsTiTJIkSZJawOJMkiRJklrA4kySpAlJ8sYk+5Jc3zPs2CSXJ7mxuT9mkhklSeNjcSZJ0uRcCJxy0LDtwBVVdRJwRfNckjQDLM4kSZqQqroS+MJBg88AdjaPdwJnjjOTJGlyVnUpfUmSNHJzVbUXoKr2Jjl+qQmTbAW2AszNzdHpdAZ64W2b9g80/zAsLCwM3I5BDWs9zB3RjnU6DLalnWzL+PXz+TTI55jFmSRJU6qqdgA7ADZv3lzz8/MDLe+c7e8cQqrBXHjKkQzajkENaz1s27SfC3atj3+1bEs72Zbx23PW/IrTdDqdNX+O2a1RkqR2uS3JBoDmft+E80iSxsTiTJKkdrkU2NI83gJcMsEskqQxsjiTJGlCkrwF+CDwiCS3JHkRcD7w1CQ3Ak9tnkuSZkD7O3ZKkrROVdVzlxh18liDSJJawSNnkiRJktQCFmeSJEmS1AIWZ5IkSZLUAhZnkiRJktQCFmeSJEmS1AJerVGSJLXGrs98mXO2v3PSMSRpIjxyJkmSJEktYHEmSZIkSS1gcSZJkiRJLWBxJkmSJEktYHEmSZIkSS1gcSZJkiRJLWBxJkmSJEktsGJxluTEJO9LsjvJDUle0gw/NsnlSW5s7o8ZfVxJkiRJWp/6OXK2H9hWVY8Engj8YpJHAduBK6rqJOCK5rkkSZIkaQ1WLM6qam9VXds8vhPYDZwAnAHsbCbbCZw5ooySJEmStO6t6pyzJBuBxwJXAXNVtRe6BRxw/NDTSZIkSdKMOLTfCZMcBbwdeGlV3ZGk3/m2AlsB5ubm6HQ6a4gJCwsLbNt095rmHbZ+2rCwsLDmtk7CNOWdpqwwXXmnKStMV95pyipJkiajr+IsyWF0C7M3V9XFzeDbkmyoqr1JNgD7Fpu3qnYAOwA2b95c8/Pzawra6XS44AN3rWneYdtz1vyK03Q6Hdba1kmYprzTlBWmK+80ZYXpyjtNWSVJ0mT0c7XGAG8AdlfVq3tGXQpsaR5vAS4ZfjxJkmZTkj1JdiW5LsnVk84jSRq9fo6cPQk4G9iV5Lpm2MuB84GLkrwIuBl41kgSSpI0u55SVbdPOoQkaTxWLM6q6gPAUieYnTzcOJIkSZI0m/q+IIgkSRqrAt6TpID/2ZzD/U2GddGtA7Zt2j/Q/MMwd0Q7cgyDbWkn29JO09KWUV8Y0OJMkqR2elJV3ZrkeODyJB+tqit7JxjWRbcOOGf7Oweafxi2bdrPBbvWx78ntqWdbEs7TUtbRn1hwFX9zpkkSRqPqrq1ud8HvAN4/GQTSZJGzeJMkqSWSXJkkvsdeAw8Dbh+sqkkSaPW/mOHkiTNnjngHd1fs+FQ4K+q6m8nG0mSNGoWZ5I0RBuXOGdn26b9YzufZ8/5p4/ldTQ6VXUT8OhJ55AkjZfdGiVJkiSpBSzOJEmSJKkF7Na4Bkt1W+o16i5MdluSJEmS1hePnEmSJElSC1icSZIkSVILWJxJkiRJUgtYnEmSJElSC3hBEEnrRj8X65EkSWorj5xJkiRJUgt45ExaB4Z1xGjUPwExbNOWV5IkaTkeOZMkSZKkFvDI2ZQa9rk1azkC4Q9hd630t/DojiRJkvrhkTNJkiRJagGLM0mSJElqAYszSZIkSWoBizNJkiRJagEvCKKp5o8OS5Ikab2wONOaTaow8uqHkiRJWo/s1ihJkiRJLTBQcZbklCQfS/KJJNuHFUqSpFnnPlaSZs+ai7MkhwB/BJwKPAp4bpJHDSuYJEmzyn2sJM2mQY6cPR74RFXdVFX/AbwVOGM4sSRJmmnuYyVpBqWq1jZj8kzglKr6meb52cATqurcg6bbCmxtnj4C+Ngasx4H3L7GeSfBvKMzTVlhuvJOU1aYrrzTlBXgYVX1wEmHmFUT2Me2ybS9V5ZjW9rJtrTTLLVlyX3sIFdrzCLD7lXpVdUOYMcAr9N9seTqqto86HLGxbyjM01ZYbryTlNWmK6805RVrTDWfWybrKf3im1pJ9vSTrala5BujbcAJ/Y8fwhw6wDLkyRJXe5jJWkGDVKc/TNwUpKHJzkceA5w6XBiSZI009zHStIMWnO3xqran+Rc4O+AQ4A3VtUNQ0t2b9PWbcO8ozNNWWG68k5TVpiuvNOUVRM2gX1sm6yn94ptaSfb0k62hQEuCCJJkiRJGp6BfoRakiRJkjQcFmeSJEmS1AKtKs6SPCvJDUm+nmTJy08mOSXJx5J8Isn2nuHHJrk8yY3N/TEjzrvi6yV5RJLrem53JHlpM+68JJ/pGXfaJLM20+1JsqvJc/Vq5x9n3iQnJnlfkt3NdvOSnnEjX7dLbYc945PkD5rxH0nyuH7nHYU+8p7V5PxIkn9M8uiecYtuFxPMOp/kyz1/39/sd94J5f3VnqzXJ7k7ybHNuLGuW6ltVrN/SXJIkn9Jctk4M/Zr0H1XGwyyb2ubQfZ7bdPvvi3JDzT7mGeOM99q9NOWZj9/XfMeef+4M/arj23s6CT/O8mHm7a8YMWFVlVrbsAj6f6IZgfYvMQ0hwCfBL4dOBz4MPCoZtzvAdubx9uB3x1x3lW9XpP9s3R/eA7gPOBXxrRu+8oK7AGOG7St48gLbAAe1zy+H/Dxnm1hpOt2ue2wZ5rTgHfT/b2iJwJX9TvvhPL+EHBM8/jUA3mX2y4mmHUeuGwt804i70HT/wTw3kmsW2/e2nhbzf4F+C/AXy32/m/DbdB916Rvg+zb2nYbdL/Xplu/+5lmuvcC7wKeOencA/xdHgD8K/DQ5vnxk849QFtefuBzAHgg8AXg8OWW26ojZ1W1u6o+tsJkjwc+UVU3VdV/AG8FzmjGnQHsbB7vBM4cSdBvWO3rnQx8sqo+NcpQSxh03bRu3VbV3qq6tnl8J7AbOGHEuQ5Ybjs84Azgz6vrQ8ADkmzoc96x562qf6yqLzZPP0T3d5UmYZD108p1e5DnAm8ZcSZpmvS1f0nyEOB04M/GE2tN2r7vWskg+7a2mab93kr63c+8GHg7sG+c4Vapn7b8NHBxVd0MUFVtbU8/bSngfkkCHEW3ONu/3EJbVZz16QTg0z3Pb+EbH2pzVbUXuh9+wPEjzrLa13sO9/6n7NzmcPobl+vKMQT9Zi3gPUmuSbJ1DfMPy6peL8lG4LHAVT2DR7lul9sOV5qmn3mHbbWv+SK634wesNR2MQr9Zv3BppvAu5N8zyrnHaa+XzPJfYFT6O48DxjnupXaqN/P+9cCvwZ8fUy51mIY+65JGmTf1jaD7vfaZMW2JDkBeAbwp2PMtRb9/F2+CzgmSafZNz5/bOlWp5+2vI5uz8BbgV3AS6pq2c+wNf/O2Vol+XvgQYuM+q9VdUk/i1hk2Mh+D2C5vKtczuHATwIv6xn8J8Ar6eZ/JXAB8MK1JR1a1idV1a1JjgcuT/LRqrpyrZmWM8R1exTdf3ZfWlV3NIOHum4Xe9lFhh28HS41zVi34RWy3HvC5Cl0d1JP7hk8tu2C/rJeS7d78EK65xP+DXBSn/MO22pe8yeAf6iqL/QMG+e6lSZi0M/7JE8H9lXVNUnmhxht1Ua875q0QfZtbTPofq9N+mnLa4Ffr6q7uwdpWqufthwKfD/dHmdHAB9M8qGq+viow61SP235ceA64EeB76C7n/8/y73nx16cVdWPDbiIW4ATe54/hG41CnBbkg1Vtbc5xD7wYdDl8iZZzeudClxbVbf1LPuex0leDwx0gvMwslbVrc39viTvoHvI9kpaum6THEZ35/bmqrq4Z9lDXbeLWG47XGmaw/uYd9j6yUuS76PbZejUqvr8geHLbBcTydr7oVZV70ryx0mO62feEVjNa97r6PmY1600EUP4vH8S8JPNlzH3Ae6f5C+r6nkjirykUe67WmCQfVvbDLTfa5l+2rIZeGtTmB0HnJZkf1X9zVgS9q/fbez2qroLuCvJlcCj6Z6f2Sb9tOUFwPnVPensE0n+Dfhu4J+WWug0dmv8Z+CkJA9vjkY9B7i0GXcpsKV5vAXo50jcIFbzevc6z+SgPtrPAK4farpvtmLWJEcmud+Bx8DTejK1bt02/XffAOyuqlcfNG7U63a57fCAS4Hnp+uJwJebbi79zDtsK75mkocCFwNn9347tcJ2MamsD2r+/iR5PN3Pss/3M+8k8jY5jwZ+hJ5teQLrVmqjFT/vq+plVfWQqtpI9z323kkUZn0YaN/VAoPs29pmzfu9FlqxLVX18Kra2LxH3gb8QgsLM+hvG7sE+OEkh6Z7OsAT6J6b2Tb9tOVmukcASTJH98KHNy271GrB1U4O3Oj+E30L8FXgNuDvmuEPBt7VM91pdKvnT9LtDnlg+LcBVwA3NvfHjjjvoq+3SN770v3H8eiD5v8Luv1PP9L8MTdMMivdq818uLnd0PZ1S7f7QTXr77rmdtq41u1i2yHwc8DPNY8D/FEzfhc9VyBdahse8TpdKe+fAV/sWZdXr7RdTDDruU2WD9M9ifuH2rxum+fnAG89aL6xr1tv3tp26+fz/qDp52nv1RoH2ne14TbIvq1tt7Xu99p462c/0zPthbT0ao39tgX4VbpXbLyebtffiede4zb2YOA9zXvleuB5Ky0zzYySJEmSpAmaxm6NkiRJkrTuWJxJkiRJUgtYnEmSJElSC1icSZIkSVILWJxJkiRJUgtYnEmSJElSC1icSZIkSVILWJxJkiRJUgtYnEmSJElSC1icSZIkSVILWJxJkiRJUgtYnGmqJDkryXtGtOwLk/z2KJa9yGudk+QD43gtSZKW475Vag+LM7VSkicn+cckX07yhST/kOQHqurNVfW0FuTrJPmZIS6vknznQcPOS/KXQ1j2xmb5hw66LEnS9JqVfWuShyZZ6LlVkrt6nv/wMPJKo+A/a2qdJPcHLgN+HrgIOBz4YeCrk8wlSdK0mqV9a1XdDBx14HmSAh5dVZ+YXCqpPx45Uxt9F0BVvaWq7q6qr1TVe6rqIwd3WWi+DfuFJDcmuTPJK5N8R5IPJrkjyUVJDm+mvVd3h8WOWDXDj0lyWZLPJfli8/ghzbjfobtDe13zDdzrmuHfneTy5tvIjyV5ds/yvi3JpU2mfwK+Y7UrZYXln57kX5rlfzrJeT2zXtncf6nJ+4OrfW1J0tRz39qd51uTvCrJzUluS/KnSY5oxs0nuSXJryXZl2RvkjOTnJbk402Gl/cs67wkb0vy1816ujbJo1f1V5EOYnGmNvo4cHeSnUlOTXLMCtOfAnw/8ETg14AdwFnAicD3As9dQ4ZvAd4EPAx4KPAV4HUAVfVfgf8DnFtVR1XVuUmOBC4H/go4vnnNP07yPc3y/gj4d2AD8MLm1rc+ln8X8HzgAcDpwM8nObMZ95+a+wc0eT+4mteWJK0L7lu7fpduofoY4DuBE4Df7Bn/IOA+PcNfDzyP7rr4YeA3k3x7z/RnAP8LOLbJ+TdJDutvdUj3ZnGm1qmqO4AnA0X3Q/FzzTdjc0vM8rtVdUdV3QBcD7ynqm6qqi8D7wYeu4YMn6+qt1fV/62qO4HfAX5kmVmeDuypqjdV1f6quhZ4O/DMJIcA/w/wm1V1V1VdD+xcZBnXJvnSgRuwvZ/lN3k7VbWrqr5eVR8B3rJCXknSDJnhfes9kgT4z8AvV9UXmgz/HXhOz2RfA36nqr4GvBU4Dvj9qrqzWRc3AN/XM/01VfW2ZvpX0y3sntjvOpEO5jlnaqWq2g2cA90uDcBfAq8F/m6RyW/refyVRZ4/aLWvn+S+wGvofnN44NvF+yU5pKruXmSWhwFPaIqqAw4F/gJ4YPP40z3jPrXIMh7X2x++6Zp4oFvIcssnyROA8+l+m3k48K10v8mTJAmY2X1rrwcC9wWu6dZp3VjAIT3TfL4ny1ea+4PbflTP83tev6q+nuQW4MEr5JCW5JEztV5VfRS4kG7hMYi76H4oA5BkuR3LNuARwBOq6v58o2vggU/zOmj6TwPvr6oH9NyOqqqfBz4H7KfbFeSAh64y+3LLh25XikuBE6vqaOBPl8kqSZpxM7pvvZ1ucfU9Pcs7uqqOWmG+5dzz+km+BXgIcOsAy9OMszhT6zQn/27rOUn4RLr9zD804KI/DHxPksckuQ9w3jLT3o/uB/iXkhwLvOKg8bcBvX3OLwO+K8nZSQ5rbj+Q5JHNN3AXA+cluW+SRwFbVpl9yeX35P1CVf17kscDP90z7+eArx+UV5I0Q9y3do9s0e3S+ZokxwMkOSHJj/ff3Hv5/iQ/le7P1byU7tUvB12nmmEWZ2qjO4EnAFcluYvuh9z1dL9xW7Oq+jjw34C/B24ElvuhytcCR9D9lu1DwN8eNP736fZ5/2KSP2j6rT+Nbr/1W4HP0j3p+Fub6c+l2w3is3S/qXzTKrOvtPxfAP5bkjvpnsB8Uc+8/5duv/5/aM5nsy+8JM0e961dvw58AvhQkjua3I/oY76lXAL8v8AXgbOBn2rOP5PWJFX2eJIkSZJW48C54VX1vEln0frhkTNJkiRJagGLM0mSJElqAbs1SpIkSVILeORMkiRJklpgrD9Cfdxxx9XGjRvveX7XXXdx5JFHjjPCmpl1NKYl67TkBLOOyqxlveaaa26vqgcOKZLG4OB97LBM07Y/iFlpJ9jW9WhW2gnro63L7WPHWpxt3LiRq6+++p7nnU6H+fn5cUZYM7OOxrRknZacYNZRmbWsST41nDQal4P3scMyTdv+IGalnWBb16NZaSesj7Yut4+1W6MkSZIktYDFmSRJkiS1gMWZJEmSJLWAxZkkSZIktYDFmSRJkiS1wFiv1ihp/dq4/Z2rnmfbpv2cs4b5lrLn/NOHtixJmqS1fKb2q9/PXj9TpfFb8chZkhOTvC/J7iQ3JHlJM/y8JJ9Jcl1zO230cSVJkiRpfernyNl+YFtVXZvkfsA1SS5vxr2mql41uniSJEmSNBtWLM6qai+wt3l8Z5LdwAmjDiZJkiRJs2RVFwRJshF4LHBVM+jcJB9J8sYkxww7nCRJkiTNir4vCJLkKODtwEur6o4kfwK8Eqjm/gLghYvMtxXYCjA3N0en07ln3MLCwjc9b7PerLs+8+XJhgE2nXD0kuOmdb222bTkhMll3bZp/6rnmTtibfMtZZTtdhuQJEmj1ldxluQwuoXZm6vqYoCquq1n/OuByxabt6p2ADsANm/eXPPz8/eM63Q69D5vs96sw7y63FrtOWt+yXHTul7bbFpywuSyruV9sW3Tfi7YNbyLxi73vhiU24AkSRq1fq7WGOANwO6qenXP8A09kz0DuH748SRJkiRpNvTzlfWTgLOBXUmua4a9HHhuksfQ7da4B/jZEeSTJEmSpJnQz9UaPwBkkVHvGn4cSZIkSZpNq7paoyRJkiRpNCzOJEmSJKkFLM4kSZqQJPdJ8k9JPpzkhiS/1Qw/NsnlSW5s7v0tUUmaARZnkiRNzleBH62qRwOPAU5J8kRgO3BFVZ0EXNE8lyStcxZnkiRNSHUtNE8Pa24FnAHsbIbvBM4cfzpJ0rhZnEmSNEFJDml+qmYfcHlVXQXMVdVegOb++AlGlCSNST+/cyZJkkakqu4GHpPkAcA7knxvv/Mm2QpsBZibm6PT6Qw938LCwkiW2zZta+e2TftHtuy5I/pbfpvWx1q17e86KrPSTlj/bbU4kySpBarqS0k6wCnAbUk2VNXeJBvoHlVbbJ4dwA6AzZs31/z8/NBzdTodRrHctmlbO8/Z/s6RLXvbpv1csGvlfwH3nDU/sgzj0ra/66jMSjth/bfVbo2SJE1Ikgc2R8xIcgTwY8BHgUuBLc1kW4BLJhJQkjRWHjmTJGlyNgA7kxxC9wvTi6rqsiQfBC5K8iLgZuBZkwwpSRoPizNJkiakqj4CPHaR4Z8HTh5/IknSJNmtUZIkSZJawOJMkiRJklrA4kySJEmSWsDiTJIkSZJawOJMkiRJklrA4kySJEmSWmDF4izJiUnel2R3khuSvKQZfmySy5Pc2NwfM/q4kiRJkrQ+9XPkbD+wraoeCTwR+MUkjwK2A1dU1UnAFc1zSZIkSdIarFicVdXeqrq2eXwnsBs4ATgD2NlMthM4c0QZJUmSJGndW9U5Z0k2Ao8FrgLmqmovdAs44Pihp5MkSZKkGXFovxMmOQp4O/DSqrojSb/zbQW2AszNzdHpdO4Zt7Cw8E3P26w367ZN+ycbBpZdb9O6XttsWnLC5LKu5X0xd8Rw309/+OZLhrasg80d0d/yN51w9Mgy9GuatldJkvQNfRVnSQ6jW5i9uaoubgbflmRDVe1NsgHYt9i8VbUD2AGwefPmmp+fv2dcp9Oh93mb9WY9Z/s7JxsG2HPW/JLjpnW9ttm05ITJZV3L+2Lbpv1csKvv74gmqt+sy703x2WatldJWs7GAf/n2rZp/8D/t+05//SB5pdWo5+rNQZ4A7C7ql7dM+pSYEvzeAswuq+sJUmSJGmd6+cr6ycBZwO7klzXDHs5cD5wUZIXATcDzxpJQkmSJEmaASsWZ1X1AWCpE8xOHm4cSZIkSZpNq7paoyRJkiRpNCzOJEmSJKkFLM4kSZIkqQUsziRJkiSpBSzOJEmSJKkFLM4kSZIkqQUsziRJkiSpBSzOJEmSJKkFLM4kSZIkqQUsziRJkiSpBQ6ddACtzcbt71xy3LZN+zlnmfHDsuf800f+GtK0We69OS4XnnLkpCNIkqQ18MiZJEmSJLWAxZkkSZIktYDFmSRJkiS1gMWZJEmSJLWAxZkkSZIktcBUXa1xkldBG9cVECVJsyPJicCfAw8Cvg7sqKrfT3Is8NfARmAP8Oyq+uKkckqSxmPFI2dJ3phkX5Lre4adl+QzSa5rbqeNNqYkSevSfmBbVT0SeCLwi0keBWwHrqiqk4ArmueSpHWun26NFwKnLDL8NVX1mOb2ruHGkiRp/auqvVV1bfP4TmA3cAJwBrCzmWwncOZEAkqSxmrFbo1VdWWSjWPIIknSzGr2tY8FrgLmqmovdAu4JMcvMc9WYCvA3NwcnU5n6LkWFhZGsty2aVs7t23aP7Jlzx3R3/LbsD4GXQ/9tnU5bVgPK2nb9jtK672tg5xzdm6S5wNX0+2SYV94SZLWIMlRwNuBl1bVHUn6mq+qdgA7ADZv3lzz8/NDz9bpdBjFctumbe0c5Xnu2zbt54JdK/8LuOes+ZFl6Neg66Hfti6nDethJW3bfkdpvbd1rVvrnwCvBKq5vwB44WITLvet3mor31F+i7SSYXzzMi7jyjqMby2m5duPackJk8u6lm3O99VoTNP2KkhyGN3C7M1VdXEz+LYkG5qjZhuAfZNLKEkalzUVZ1V124HHSV4PXLbMtEt+q7fayneSV0scxjcv4zKurMP4Jmlavv2YlpwwuaxreX/6vhqNC085cmq211mX7iGyNwC7q+rVPaMuBbYA5zf3l0wgniRpzNb0n8aBb/Oap88Arl9uekmStKgnAWcDu5Jc1wx7Od2i7KIkLwJuBp41mXiSJvlTTgfsOf/0SUfQmKxYnCV5CzAPHJfkFuAVwHySx9Dt1rgH+NnRRZQkaX2qqg8AS51gdvI4s0iSJq+fqzU+d5HBbxhBFkmSJEmaWdNxAoWkZfV2udi2af9Ez8+UJEnS2vTzI9SSJEmSpBGzOJMkSZKkFrA4kyRJkqQWsDiTJEmSpBawOJMkSZKkFrA4kyRJkqQWsDiTJEmSpBawOJMkSZKkFrA4kyRJkqQWsDiTJEmSpBawOJMkSZKkFrA4kyRJkqQWOHTSASRJktQ+G7e/c9IRpJnjkTNJkiRJagGLM0mSJElqAYszSZIkSWqBFc85S/JG4OnAvqr63mbYscBfAxuBPcCzq+qLo4spSZI0Hp5rpbZZaZvctmk/54x4u91z/ukjXb66+jlydiFwykHDtgNXVNVJwBXNc0mSJEnSGq1YnFXVlcAXDhp8BrCzebwTOHO4sSRJkiRptqz1nLO5qtoL0NwfP7xIkiRJkjR7Rv47Z0m2AlsB5ubm6HQ694xbWFj4pucr2bZp/5DT9W/uiMm+/mqMK+tq/nZLWe02MCltz9n793ZbHY1pytr27VWSJC1urcXZbUk2VNXeJBuAfUtNWFU7gB0Amzdvrvn5+XvGdTodep+vZNQnOi5n26b9XLBrOn6ze1xZ95w1P/AyVrsNTErbc/a+N9xWR2Oasl54ypGt3l4lSdLi1tqt8VJgS/N4C3DJcOJIkiRJ0mxasThL8hbgg8AjktyS5EXA+cBTk9wIPLV5LkmSJElaoxX76FTVc5cYdfKQs0iSJEnSzFprt0ZJkiRJ0hBZnEmSJElSC1icSZIkSVILWJxJkiRJUgtYnEmSNCFJ3phkX5Lre4Ydm+TyJDc298dMMqMkaXym4xdV1Uobh/Cj4Ns27R/ox8X3nH/6wBkkaYIuBF4H/HnPsO3AFVV1fpLtzfNfn0A2SdKYeeRMkqQJqaorgS8cNPgMYGfzeCdw5jgzSZImxyNnkiS1y1xV7QWoqr1Jjl9qwiRbga0Ac3NzdDqdoYdZWFgYyXLbpred2zbtn2yYEZs7Yv238YBZaes42tmWz4H1/plkcSZJ0pSqqh3ADoDNmzfX/Pz80F+j0+kwiuW2TW87B+luPw22bdrPBbtm41/AWWnrONq556z5kS6/X+v9M8lujZIktcttSTYANPf7JpxHkjQmFmeSJLXLpcCW5vEW4JIJZpEkjdH6P84rSVJLJXkLMA8cl+QW4BXA+cBFSV4E3Aw8a3IJx28YVwJei0GvHixp9DZuf+fE36ujvlK4xZkkSRNSVc9dYtTJYw0iSWoFuzVKkiRJUgtYnEmSJElSC9itUZIkAYuf7zXp8zskaZZYnGmqjevE8eX+ORn1iaGSJEmaDQMVZ0n2AHcCdwP7q2rzMEJJkiRJ0qwZxpGzp1TV7UNYjiRJkiTNLC8IIkmSJEktMGhxVsB7klyTZOswAkmSJEnSLBq0W+OTqurWJMcDlyf5aFVd2TtBU7RtBZibm6PT6dwzbmFh4Zuer2Tbpv0Dxl27uSMm+/qrYdbhWy7narbhUenNNi3rFMw6Kqv9bJUkSe0wUHFWVbc29/uSvAN4PHDlQdPsAHYAbN68uebn5+8Z1+l06H2+kkleynfbpv1csGs6Lm5p1uFbLuees+bHG2YRve+NaVmnYNZRufCUI1f12SpJktphzd0akxyZ5H4HHgNPA64fVjBJkiRJmiWDfA08B7wjyYHl/FVV/e1QUkmSJEnSjFlzcVZVNwGPHmIWSZIkSZpZXkpfkiRJklrA4kySJEmSWsDiTJIkSZJawOJMkiRJklrA4kySJEmSWmA6flFVarGNE/xxdEmSpHHw/53x8MiZJEmSJLWAxZkkSZIktYDFmSRJkiS1gMWZJEmSJLWAxZkkSZIktYDFmSRJkiS1gMWZJEmSJLWAxZkkSZIktYDFmSRJkiS1gMWZJEmSJLWAxZkkSZIktcBAxVmSU5J8LMknkmwfVihJkmad+1hJmj1rLs6SHAL8EXAq8CjguUkeNaxgkiTNKvexkjSbBjly9njgE1V1U1X9B/BW4IzhxJIkaaa5j5WkGTRIcXYC8Ome57c0wyRJ0mDcx0rSDEpVrW3G5FnAj1fVzzTPzwYeX1UvPmi6rcDW5ukjgI/1jD4OuH1NAcbPrKMxLVmnJSeYdVRmLevDquqBwwij1RvSPnZYpmnbH8SstBNs63o0K+2E9dHWJfexhw6w0FuAE3uePwS49eCJqmoHsGOxBSS5uqo2D5BhbMw6GtOSdVpygllHxawas4H3scMyK9vTrLQTbOt6NCvthPXf1kG6Nf4zcFKShyc5HHgOcOlwYkmSNNPcx0rSDFrzkbOq2p/kXODvgEOAN1bVDUNLJknSjHIfK0mzaZBujVTVu4B3DbCIkXbFGDKzjsa0ZJ2WnGDWUTGrxmoI+9hhmZXtaVbaCbZ1PZqVdsI6b+uaLwgiSZIkSRqeQc45kyRJkiQNyciLsyTPSnJDkq8nWfLKKklOSfKxJJ9Isr1n+LFJLk9yY3N/zAizrvhaSR6R5Lqe2x1JXtqMOy/JZ3rGnTbJrM10e5LsavJcvdr5x5EzyYlJ3pdkd7OtvKRn3MjX6VLbXs/4JPmDZvxHkjyu33knkPWsJuNHkvxjkkf3jFt0W5hQzvkkX+75u/5mv/NOIOuv9uS8PsndSY5txo1tnTav98Yk+5Jcv8T41myrml6Dfm633SCf+dNmkH3GNOn38y3JDzSf4c8cZ75h6qetzT72uua9+f5xZxyWPrbfo5P87yQfbtr6gknkHLqqGukNeCTd317pAJuXmOYQ4JPAtwOHAx8GHtWM+z1ge/N4O/C7I8y6qtdqcn+W7m8VAJwH/Mqo1+lqsgJ7gOMGbesocwIbgMc1j+8HfLzn7z/SdbrcttczzWnAu4EATwSu6nfeCWT9IeCY5vGpB7Iuty1MKOc8cNla5h131oOm/wngveNepz2v95+AxwHXLzG+Fduqt+m+Dfq53ebbIJ/503YbdJ8xLbd+P9+a6d5L9zzOZ0469wj/pg8A/hV4aPP8+EnnHmFbX37g8wl4IPAF4PBJZx/0NvIjZ1W1u6pW+lHMxwOfqKqbquo/gLcCZzTjzgB2No93AmeOJOjaXutk4JNV9akRZlrKoOtlXOt1xdepqr1VdW3z+E5gN3DCiPIcbLlt74AzgD+vrg8BD0iyoc95x5q1qv6xqr7YPP0Q3d9GGrdB1kvr1ulBngu8ZYR5llVVV9Ld+SylLduqplvbP7cHMchn/rSZln3GoPr9fHsx8HZg3zjDDVk/bf1p4OKquhmgqqa1vf20tYD7JQlwFN394/7xxhy+tpxzdgLw6Z7nt/CND/m5qtoL3Z0BcPwIc6z2tZ7Dvf9RO7fpHvDGxbqCDFG/WQt4T5Jrkmxdw/zjyglAko3AY4GregaPcp0ut+2tNE0/8w7Tal/vRXS//T1gqW1h2PrN+YNNV4R3J/meVc47LH2/XpL7AqfQ3bkfMK512q+2bKuabsP43G6rQT7zp82g+4xpsWI7k5wAPAP40zHmGoV+/qbfBRyTpNPsm54/tnTD1U9bX0e3h96twC7gJVX19fHEG52BLqV/QJK/Bx60yKj/WlWX9LOIRYaN5DKSy2Vd5XIOB34SeFnP4D8BXkk3+yuBC4AXri3p0LI+qapuTXI8cHmSjzbfvg/NENfpUXT/8X1pVd3RDB7qOl3sZRcZdvC2t9Q0Y9tuV8hx7wmTp9Dd0T65Z/DIt4VV5LyWbnfghXTPI/wb4KQ+5x2m1bzeTwD/UFW9R67GtU771ZZtVS034s/tNhvkM3/aDLrPmBb9tPO1wK9X1d3dgyxTq5+2Hgp8P93eXUcAH0zyoar6+KjDDVk/bf1x4DrgR4HvoLsf/j9T8lm0pKEUZ1X1YwMu4hbgxJ7nD6FbBQPclmRDVe1tuhUMdHh2uaxJVvNapwLXVtVtPcu+53GS1wOXTTprVd3a3O9L8g66h4mvZIjrdRg5kxxGdwf/5qq6uGfZQ12ni1hu21tpmsP7mHeY+slKku8D/gw4tao+f2D4MtvC2HP2fnBW1buS/HGS4/qZd9xZe9zrSPkY12m/2rKtquVG+bndcoN85k+bgfYZU6Sfdm4G3toUZscBpyXZX1V/M5aEw9Pv9nt7Vd0F3JXkSuDRdM8LnSb9tPUFwPlVVcAnkvwb8N3AP40n4mi0pVvjPwMnJXl4c0TqOcClzbhLgS3N4y1AP0fi1mo1r3Wvc08O6pP+DGDRK6oNyYpZkxyZ5H4HHgNP68k0rvXaT84AbwB2V9WrDxo36nW63LZ3wKXA89P1RODLTVeffuYda9YkDwUuBs7u/ZZshW1hEjkf1PzdSfJ4up9Fn+9n3nFnbTIeDfwIPdvvmNdpv9qyrWq6DfS53XKDfOZPmzXvM6bMiu2sqodX1caq2gi8DfiFKSzMoL/t9xLgh5Mcmm53/CfQPSd02vTT1pvpHiEkyRzdCxDeNNaUo1Cjv9rKM+hWv18FbgP+rhn+YOBdPdOdRreq/yTd7pAHhn8bcAVwY3N/7AizLvpai2S9L91/JI8+aP6/oNvn9SN0N6ANk8xK9wo3H25uN0xivfaZ88l0D1V/hO7h6euA08a1Thfb9oCfA36ueRzgj5rxu+i56uhS2+0I/+4rZf0z4Is96/HqlbaFCeU8t8nxYbonof9QW9dp8/wc4K0HzTfWddq85luAvcDX6H6uvqit26q36b0N+rnd9tsgn/nTdlvrPmPabv18jvdMeyFTerXGftsK/CrdKzZeT7fL8cRzj6KtzWfSe5r36fXA8yadeRi3NI2TJEmSJE1QW7o1SpIkSdJMsziTJEmSpBawOJMkSZKkFrA4kyRJkqQWsDiTJEmSpBawOJMkSZKkFrA4kyRJkqQWsDiTJEmSpBb4/wFhAcE8nHawqwAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<Figure size 1080x432 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"dfs_test_sc[0].hist()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Set up the function which generated the GPR input matrix from the experimental data (including all autoregressive inputs, etc.):"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def data_to_gpr(df, dict_cols):\n",
|
||
" \n",
|
||
" t_list = dict_cols['t'][1]\n",
|
||
" w_list = dict_cols['w'][1]\n",
|
||
" u_list = dict_cols['u'][1]\n",
|
||
" y_list = dict_cols['y'][1]\n",
|
||
" \n",
|
||
" df_gpr = df[t_list + w_list + u_list + y_list].copy()\n",
|
||
" \n",
|
||
" for lags, names in dict_cols.values():\n",
|
||
" for name in names:\n",
|
||
" col_idx = df_gpr.columns.get_loc(name)\n",
|
||
" for lag in range(1, lags + 1):\n",
|
||
" df_gpr.insert(col_idx + lag, f\"{name}_{lag}\", df_gpr.loc[:, name].shift(lag))\n",
|
||
"\n",
|
||
" df_gpr.dropna(inplace = True)\n",
|
||
" \n",
|
||
" return df_gpr"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
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"<div>\n",
|
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"<style scoped>\n",
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|
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|
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|
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|
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|
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|
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|
||
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|
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|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>SolRad</th>\n",
|
||
" <th>OutsideTemp</th>\n",
|
||
" <th>SimulatedHeat</th>\n",
|
||
" <th>SimulatedHeat_1</th>\n",
|
||
" <th>SimulatedHeat_2</th>\n",
|
||
" <th>SimulatedTemp</th>\n",
|
||
" <th>SimulatedTemp_1</th>\n",
|
||
" <th>SimulatedTemp_2</th>\n",
|
||
" <th>SimulatedTemp_3</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>timestamp</th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
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|
||
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|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 20:45:00+02:00</th>\n",
|
||
" <td>-0.970807</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" <td>0.214339</td>\n",
|
||
" <td>0.153839</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:00:00+02:00</th>\n",
|
||
" <td>-0.980063</td>\n",
|
||
" <td>0.019608</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" <td>0.214339</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:15:00+02:00</th>\n",
|
||
" <td>-0.989906</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:30:00+02:00</th>\n",
|
||
" <td>-0.991909</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.091034</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:45:00+02:00</th>\n",
|
||
" <td>-0.992483</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>0.577419</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.203306</td>\n",
|
||
" <td>0.091034</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" SolRad OutsideTemp SimulatedHeat \\\n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 -0.970807 0.058824 0.438090 \n",
|
||
"2017-06-01 21:00:00+02:00 -0.980063 0.019608 0.438090 \n",
|
||
"2017-06-01 21:15:00+02:00 -0.989906 -0.058824 -0.470064 \n",
|
||
"2017-06-01 21:30:00+02:00 -0.991909 -0.058824 -0.470064 \n",
|
||
"2017-06-01 21:45:00+02:00 -0.992483 -0.058824 0.577419 \n",
|
||
"\n",
|
||
" SimulatedHeat_1 SimulatedHeat_2 SimulatedTemp \\\n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 0.438090 0.438090 0.248081 \n",
|
||
"2017-06-01 21:00:00+02:00 0.438090 0.438090 0.216876 \n",
|
||
"2017-06-01 21:15:00+02:00 0.438090 0.438090 0.062767 \n",
|
||
"2017-06-01 21:30:00+02:00 -0.470064 0.438090 0.091034 \n",
|
||
"2017-06-01 21:45:00+02:00 -0.470064 -0.470064 0.203306 \n",
|
||
"\n",
|
||
" SimulatedTemp_1 SimulatedTemp_2 SimulatedTemp_3 \n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 0.233535 0.214339 0.153839 \n",
|
||
"2017-06-01 21:00:00+02:00 0.248081 0.233535 0.214339 \n",
|
||
"2017-06-01 21:15:00+02:00 0.216876 0.248081 0.233535 \n",
|
||
"2017-06-01 21:30:00+02:00 0.062767 0.216876 0.248081 \n",
|
||
"2017-06-01 21:45:00+02:00 0.091034 0.062767 0.216876 "
|
||
]
|
||
},
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"dfs_gpr_train = []\n",
|
||
"for df_sc in dfs_train_sc:\n",
|
||
" dfs_gpr_train.append(data_to_gpr(df_sc, dict_cols))\n",
|
||
"df_gpr_train = pd.concat(dfs_gpr_train)\n",
|
||
"df_gpr_train.head()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"dfs_gpr_test = []\n",
|
||
"for df_sc in dfs_test_sc:\n",
|
||
" dfs_gpr_test.append(data_to_gpr(df_sc, dict_cols))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#df_gpr_train = df_gpr_train.sample(n = 500)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {
|
||
"id": "eZAetwUd6YuE"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"df_input_train = df_gpr_train.drop(columns = dict_cols['u'][1] + dict_cols['y'][1])\n",
|
||
"df_output_train = df_gpr_train[dict_cols['y'][1]]\n",
|
||
"\n",
|
||
"np_input_train = df_input_train.to_numpy()\n",
|
||
"np_output_train = df_output_train.to_numpy().reshape(-1, 1)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"data_train = (np_input_train, np_output_train)\n",
|
||
"pickle.dump(data_train, open(Path(\"data_train.pkl\"), 'wb'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>SolRad</th>\n",
|
||
" <th>OutsideTemp</th>\n",
|
||
" <th>SimulatedHeat_1</th>\n",
|
||
" <th>SimulatedHeat_2</th>\n",
|
||
" <th>SimulatedTemp_1</th>\n",
|
||
" <th>SimulatedTemp_2</th>\n",
|
||
" <th>SimulatedTemp_3</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>timestamp</th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 20:45:00+02:00</th>\n",
|
||
" <td>-0.970807</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" <td>0.214339</td>\n",
|
||
" <td>0.153839</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:00:00+02:00</th>\n",
|
||
" <td>-0.980063</td>\n",
|
||
" <td>0.019608</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" <td>0.214339</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:15:00+02:00</th>\n",
|
||
" <td>-0.989906</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:30:00+02:00</th>\n",
|
||
" <td>-0.991909</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:45:00+02:00</th>\n",
|
||
" <td>-0.992483</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.091034</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" SolRad OutsideTemp SimulatedHeat_1 \\\n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 -0.970807 0.058824 0.438090 \n",
|
||
"2017-06-01 21:00:00+02:00 -0.980063 0.019608 0.438090 \n",
|
||
"2017-06-01 21:15:00+02:00 -0.989906 -0.058824 0.438090 \n",
|
||
"2017-06-01 21:30:00+02:00 -0.991909 -0.058824 -0.470064 \n",
|
||
"2017-06-01 21:45:00+02:00 -0.992483 -0.058824 -0.470064 \n",
|
||
"\n",
|
||
" SimulatedHeat_2 SimulatedTemp_1 SimulatedTemp_2 \\\n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 0.438090 0.233535 0.214339 \n",
|
||
"2017-06-01 21:00:00+02:00 0.438090 0.248081 0.233535 \n",
|
||
"2017-06-01 21:15:00+02:00 0.438090 0.216876 0.248081 \n",
|
||
"2017-06-01 21:30:00+02:00 0.438090 0.062767 0.216876 \n",
|
||
"2017-06-01 21:45:00+02:00 -0.470064 0.091034 0.062767 \n",
|
||
"\n",
|
||
" SimulatedTemp_3 \n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 0.153839 \n",
|
||
"2017-06-01 21:00:00+02:00 0.214339 \n",
|
||
"2017-06-01 21:15:00+02:00 0.233535 \n",
|
||
"2017-06-01 21:30:00+02:00 0.248081 \n",
|
||
"2017-06-01 21:45:00+02:00 0.216876 "
|
||
]
|
||
},
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df_input_train.head()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import scipy.io"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 42,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"scipy.io.savemat(\n",
|
||
" f\"dfs_datasets.mat\",\n",
|
||
" {'train0': dfs_train_sc[0][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'train1': dfs_train_sc[1][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'train2': dfs_train_sc[2][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'train3': dfs_train_sc[3][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'test0': dfs_test_sc[0][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'test1': dfs_test_sc[1][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'test2': dfs_test_sc[2][t_cols + w_cols + u_cols + y_cols].to_numpy(),\n",
|
||
" 'cols': t_cols + w_cols + u_cols + y_cols, \n",
|
||
" })"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"np_export_train = df_gpr_train.to_numpy()\n",
|
||
"np_export_test = dfs_gpr_test[0].to_numpy()\n",
|
||
"scipy.io.savemat(f\"gpr_export.mat\", {'train': np_export_train, 'cols': df_gpr_train.columns.to_list(), 'test': np_export_test})"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {
|
||
"id": "l_VzOWL66aD3"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"## Define Kernel"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {
|
||
"id": "oBHgoYNf6b6t"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"nb_dims = np_input_train.shape[1]\n",
|
||
"rational_dims = np.arange(0, (dict_cols['t'][0] + 1) * len(dict_cols['t'][1]), 1)\n",
|
||
"nb_rational_dims = len(rational_dims)\n",
|
||
"squared_dims = np.arange(nb_rational_dims, nb_dims, 1)\n",
|
||
"nb_squared_dims = len(squared_dims)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "_WagEJum8uUG",
|
||
"outputId": "c65ec503-b964-49f6-fe3a-51c57a175f9b"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"rational: 0\n",
|
||
"squared: 7\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(f\"rational: {nb_rational_dims}\")\n",
|
||
"print(f\"squared: {nb_squared_dims}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {
|
||
"id": "kTIQlLIP6dJz"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"squared_l = np.linspace(10, 10, nb_squared_dims)\n",
|
||
"rational_l = np.linspace(10, 10, nb_rational_dims)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"metadata": {
|
||
"id": "MEGkQJvY_izQ"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"#variance = tf.math.reduce_variance(np_input_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 37,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"variance = 1"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"metadata": {
|
||
"id": "WZfssVHG6edn"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"k0 = gpflow.kernels.SquaredExponential(lengthscales = squared_l, active_dims = squared_dims, variance = variance)\n",
|
||
"k1 = gpflow.kernels.Constant(variance = variance)\n",
|
||
"k2 = gpflow.kernels.RationalQuadratic(lengthscales = rational_l, active_dims = rational_dims, variance = variance)\n",
|
||
"k3 = gpflow.kernels.Periodic(k2)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 40,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"k4 = gpflow.kernels.Linear(variance = [1]*nb_dims)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 41,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 169
|
||
},
|
||
"id": "vo8rcdBm6fuc",
|
||
"outputId": "75485dcd-961c-40d9-cf1f-d10516e2b80f"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>name </th><th>class </th><th>transform </th><th>prior </th><th>trainable </th><th>shape </th><th>dtype </th><th>value </th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>Linear.variance</td><td>Parameter</td><td>Softplus </td><td> </td><td>True </td><td>(7,) </td><td>float64</td><td>[1., 1., 1....</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"k = (k0 + k1) * k2\n",
|
||
"k = k4\n",
|
||
"print_summary(k)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "4af25a43-15c9-4543-af73-3c313b5fc7af"
|
||
},
|
||
"source": [
|
||
"## Compile Model"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 44,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 190
|
||
},
|
||
"id": "PC4cbp926j29",
|
||
"outputId": "72c9441d-2657-4e0f-de70-11a197d07ad3"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>name </th><th>class </th><th>transform </th><th>prior </th><th>trainable </th><th>shape </th><th>dtype </th><th>value </th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>GPR.kernel.variance </td><td>Parameter</td><td>Softplus </td><td> </td><td>True </td><td>(7,) </td><td>float64</td><td>[1., 1., 1....</td></tr>\n",
|
||
"<tr><td>GPR.likelihood.variance</td><td>Parameter</td><td>Softplus + Shift</td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"m = gpflow.models.GPR(\n",
|
||
" data = data_train, \n",
|
||
" kernel = k, \n",
|
||
" mean_function = None,\n",
|
||
" )\n",
|
||
"print_summary(m)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 45,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#m.likelihood.variance.assign(0.5)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#gpflow.set_trainable(m.likelihood.variance, False)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "08f41235-12df-4e9c-bf63-e7a4390cf21a"
|
||
},
|
||
"source": [
|
||
"## Train Model"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 47,
|
||
"metadata": {
|
||
"id": "Pn5TwPPT6ogs"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"opt = gpflow.optimizers.Scipy()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 48,
|
||
"metadata": {
|
||
"id": "slQg9Ohv6oxR"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from datetime import datetime"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 49,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 212
|
||
},
|
||
"id": "GhsxZhc56p43",
|
||
"outputId": "778ec150-cfc3-44b7-9e21-e52bf69d494a",
|
||
"scrolled": true,
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Finished fitting in 0:00:04.616717\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>name </th><th>class </th><th>transform </th><th>prior </th><th>trainable </th><th>shape </th><th>dtype </th><th>value </th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>GPR.kernel.variance </td><td>Parameter</td><td>Softplus </td><td> </td><td>True </td><td>(7,) </td><td>float64</td><td>[1.88404972e-05, 2.35199453e-04, 4.70785497e-02...</td></tr>\n",
|
||
"<tr><td>GPR.likelihood.variance</td><td>Parameter</td><td>Softplus + Shift</td><td> </td><td>True </td><td>() </td><td>float64</td><td>0.0011367938506279384 </td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"start_time = datetime.now()\n",
|
||
"opt.minimize(m.training_loss, m.trainable_variables)\n",
|
||
"print(f\"Finished fitting in {datetime.now() - start_time}\")\n",
|
||
"print_summary(m)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Export model parameters:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 51,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"m_params = gpflow.utilities.parameter_dict(m)\n",
|
||
"pickle.dump(m_params, open(Path(Path.cwd(), 'gp_params.pkl'), 'wb'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 52,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"pickle.dump(m, open(Path(Path.cwd(), 'gp_model.pkl'), 'wb'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 69,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"m = pickle.load(open(Path(\"gp_model.pkl\"), 'rb'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "7dd49280-bb3f-4903-a339-b7225a56ae16"
|
||
},
|
||
"source": [
|
||
"## Evaluate performance on training data"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 70,
|
||
"metadata": {
|
||
"id": "I62Aw_Cs6tv6"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"nb_plts = len(dfs_gpr_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 71,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 1000
|
||
},
|
||
"id": "wp3fsnyb6uE6",
|
||
"outputId": "2bc7a0c3-0160-4857-d205-9b00dda6bf0e"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1440x1440 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize = (20, 20))\n",
|
||
"\n",
|
||
"for idx, df_iter in enumerate(dfs_gpr_train):\n",
|
||
" plt.subplot(nb_plts, 1, idx + 1)\n",
|
||
" df_input_iter = df_iter.drop(columns = dict_cols['y'][1] + dict_cols['u'][1])\n",
|
||
" df_output_iter = df_iter[dict_cols['y'][1]]\n",
|
||
" np_input_iter = df_input_iter.to_numpy()\n",
|
||
" np_output_iter = df_output_iter.to_numpy().reshape(-1, 1)\n",
|
||
" \n",
|
||
" mean, var = m.predict_f(np_input_iter)\n",
|
||
" \n",
|
||
" plt.plot(df_iter.index, np_output_iter[:, :], label = 'Measured data')\n",
|
||
" plt.plot(df_iter.index, mean[:, :], label = 'Gaussian Process Prediction')\n",
|
||
" plt.fill_between(\n",
|
||
" df_iter.index, \n",
|
||
" mean[:, 0] - 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" mean[:, 0] + 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" alpha = 0.2\n",
|
||
" )\n",
|
||
" plt.title(f\"Model Performance on training data: {train_exps[idx]}\")\n",
|
||
" plt.legend()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 72,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 855
|
||
},
|
||
"id": "OPB0DbY_6wyj",
|
||
"outputId": "e29accbe-4029-45b5-cbe1-0e216325d2b0"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1440x1440 with 3 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize = (20, 20))\n",
|
||
"\n",
|
||
"for idx, df_iter in enumerate(dfs_gpr_test):\n",
|
||
" plt.subplot(nb_plts, 1, idx + 1)\n",
|
||
" df_input_iter = df_iter.drop(columns = dict_cols['y'][1] + dict_cols['u'][1])\n",
|
||
" df_output_iter = df_iter[dict_cols['y'][1]]\n",
|
||
" np_input_iter = df_input_iter.to_numpy()\n",
|
||
" np_output_iter = df_output_iter.to_numpy().reshape(-1, 1)\n",
|
||
" \n",
|
||
" mean, var = m.predict_f(np_input_iter)\n",
|
||
" \n",
|
||
" plt.plot(df_iter.index, np_output_iter[:, :], label = 'Measured data')\n",
|
||
" plt.plot(df_iter.index, mean[:, :], label = 'Gaussian Process Prediction')\n",
|
||
" plt.fill_between(\n",
|
||
" df_iter.index, \n",
|
||
" mean[:, 0] - 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" mean[:, 0] + 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" alpha = 0.2\n",
|
||
" )\n",
|
||
" plt.title(f\"Model Performance on test data: {test_exps[idx]}\")\n",
|
||
" plt.legend()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 73,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "MG8l9PhX6yhz",
|
||
"outputId": "db07cfa0-0e64-4725-8697-1a2b70beafec"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"64.26510397973743"
|
||
]
|
||
},
|
||
"execution_count": 73,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.linalg.cond(np_input_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 74,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "0xkmBo0X9uCr",
|
||
"outputId": "13b9f9b6-01c4-45d6-ce49-995f4c8be04a"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"1.2399082841705338e+22"
|
||
]
|
||
},
|
||
"execution_count": 74,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.linalg.cond(k(np_input_train))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 64,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"ylag1_idx = df_iter.columns.to_list().index(f\"{dict_cols['y'][1][0]}_1\")\n",
|
||
"ylags = dict_cols['y'][0]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 65,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#@tf.function\n",
|
||
"def multistep_prediction(m, tf_input):\n",
|
||
" N_pred = tf_input.shape[0]\n",
|
||
" for idxx in range(N_pred - 1):\n",
|
||
" mean,_ = m.predict_f(tf.reshape(tf_input[idxx, :], (1, -1)))\n",
|
||
" tf_input[idxx+1, ylag1_idx].assign(mean[0,0])\n",
|
||
" tf_input[idxx + 1, ylag1_idx + 1 : ylag1_idx + ylags].assign(tf_input[idxx, ylag1_idx : ylag1_idx + ylags - 1])\n",
|
||
" mean, _ = m.predict_f(tf_input)\n",
|
||
" return mean"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 66,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#@tf.function\n",
|
||
"def multistep_error(m, data):\n",
|
||
" tf_input = data[0]\n",
|
||
" tf_targets = data[1]\n",
|
||
" tf_outputs = multistep_prediction(m, tf_input)\n",
|
||
" err = tf.sqrt(tf.reduce_mean((tf_targets - tf_outputs)**2))\n",
|
||
" return err"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 67,
|
||
"metadata": {
|
||
"id": "uBB14WZQz0r7"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def m_obj_value(m):\n",
|
||
"\n",
|
||
" tf_errs = 0\n",
|
||
" tf_vars = 0\n",
|
||
" tf_multi_err = 0\n",
|
||
" for idx, df_iter in enumerate(dfs_gpr_test):\n",
|
||
" df_input_iter = df_iter.drop(columns = dict_cols['y'][1] + dict_cols['u'][1])\n",
|
||
" df_output_iter = df_iter[dict_cols['y'][1]]\n",
|
||
" np_input_iter = df_input_iter.to_numpy()\n",
|
||
" np_output_iter = df_output_iter.to_numpy().reshape(-1, 1)\n",
|
||
" \n",
|
||
" mean, var = m.predict_f(np_input_iter)\n",
|
||
"\n",
|
||
" err_iter = tf.reshape(mean - np_output_iter, (-1,))\n",
|
||
" tf_errs += tf.tensordot(err_iter, err_iter, 1)\n",
|
||
"\n",
|
||
" var_iter = tf.reshape(var,(-1,))\n",
|
||
" tf_vars += tf.tensordot(var_iter, var_iter, 1)\n",
|
||
" \n",
|
||
" # Get n random points at which to compute multistep error\n",
|
||
" n_multi = 10\n",
|
||
" idx_multi = np.random.choice(len(df_iter), n_multi)\n",
|
||
" for idxx in idx_multi:\n",
|
||
" tf_input_multi = tf.Variable(df_input_iter.iloc[idx:(idx + N_pred)])\n",
|
||
" tf_output_multi = tf.Variable(df_output_iter.iloc[idx:(idx + N_pred)])\n",
|
||
" tf_data_multi = (tf_input_multi, tf_output_multi)\n",
|
||
" tf_multi_err += multistep_error(m, tf_data_multi)\n",
|
||
" \n",
|
||
"\n",
|
||
"\n",
|
||
" obj = 5 * tf_errs + 0 * tf_vars + 1 * tf_multi_err\n",
|
||
"\n",
|
||
"\n",
|
||
" return obj"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 68,
|
||
"metadata": {
|
||
"id": "xVrIALdM2Hrr"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def get_gp_from_hyperparams(tf_params):\n",
|
||
"\n",
|
||
" print(\"Training a GP\")\n",
|
||
" squared_l = tf_params[0]\n",
|
||
" variance = tf_params[1]\n",
|
||
"\n",
|
||
" k0 = gpflow.kernels.SquaredExponential(lengthscales = [squared_l]*np_input_train.shape[1], variance = variance)\n",
|
||
"\n",
|
||
" k = k0\n",
|
||
"\n",
|
||
" m = gpflow.models.GPR(\n",
|
||
" data = (np_input_train, np_output_train), \n",
|
||
" kernel = k, \n",
|
||
" mean_function = None\n",
|
||
" )\n",
|
||
"\n",
|
||
" opt = gpflow.optimizers.Scipy()\n",
|
||
"\n",
|
||
" opt.minimize(m.training_loss, m.trainable_variables)\n",
|
||
"\n",
|
||
" return m"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 69,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"7"
|
||
]
|
||
},
|
||
"execution_count": 69,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np_input_train.shape[1]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 70,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Training a GP\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"m_test = get_gp_from_hyperparams([0.1, 1])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 50,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'.kernel.kernels[0].kernels[0].variance': <Parameter: dtype=float64, shape=[], fn=\"softplus\", numpy=17.68127119263729>,\n",
|
||
" '.kernel.kernels[0].kernels[0].lengthscales': <Parameter: dtype=float64, shape=[7], fn=\"softplus\", numpy=\n",
|
||
" array([5682.89228974, 2927.70798971, 123.90443445, 170.87216202,\n",
|
||
" 12.24082499, 18.2855289 , 1652.39401848])>,\n",
|
||
" '.kernel.kernels[0].kernels[1].variance': <Parameter: dtype=float64, shape=[], fn=\"softplus\", numpy=4.089199799344012e-08>,\n",
|
||
" '.kernel.kernels[1].variance': <Parameter: dtype=float64, shape=[], fn=\"softplus\", numpy=17.560183988120716>,\n",
|
||
" '.kernel.kernels[1].lengthscales': <Parameter: dtype=float64, shape=[2], fn=\"softplus\", numpy=array([6013.93882777, 5912.03412562])>,\n",
|
||
" '.kernel.kernels[1].alpha': <Parameter: dtype=float64, shape=[], fn=\"softplus\", numpy=1.7367603383166306>,\n",
|
||
" '.likelihood.variance': <Parameter: dtype=float64, shape=[], fn=\"chain_of_shift_of_softplus\", numpy=0.05000000000000001>}"
|
||
]
|
||
},
|
||
"execution_count": 50,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"gpflow.utilities.parameter_dict(m)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 762,
|
||
"metadata": {
|
||
"id": "aJSky20pFHdI"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def gp_cost(tf_params):\n",
|
||
"\n",
|
||
" try:\n",
|
||
" m = get_gp_from_hyperparams(tf_params)\n",
|
||
" obj = m_obj_value(m)\n",
|
||
" except tf.errors.InvalidArgumentError:\n",
|
||
" obj = np.nan\n",
|
||
" \n",
|
||
" if obj == np.inf or obj > 1000:\n",
|
||
" obj = np.nan\n",
|
||
"\n",
|
||
" return obj"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 763,
|
||
"metadata": {
|
||
"id": "BNL_0TyS8GYW"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def gp_cost_map(tf_params):\n",
|
||
" obj = tf.map_fn(gp_cost, tf_params)\n",
|
||
" obj = tf.reshape(obj, (-1, 1))\n",
|
||
" return obj"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 53,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"bl = [100] * nb_rational_dims + [1.0] * nb_squared_dims\n",
|
||
"bu = [250] * nb_rational_dims + [2.5] * nb_squared_dims"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 839,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"bl = [0.1, 0.1]\n",
|
||
"bu = [10, 10]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 840,
|
||
"metadata": {
|
||
"id": "ycO8i7gYICgS"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"search_space = trieste.space.Box(bl, bu)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 842,
|
||
"metadata": {
|
||
"id": "QEhgf703Nbbl"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"init_X = search_space.sample(25)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "0te5Vr_0wkTr"
|
||
},
|
||
"source": [
|
||
"### Optimization with failure regions"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 843,
|
||
"metadata": {
|
||
"id": "UDqwUp2OQ-Ar"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"OBJECTIVE = \"OBJECTIVE\"\n",
|
||
"FAILURE = \"FAILURE\"\n",
|
||
"\n",
|
||
"def gp_observer(x):\n",
|
||
" try:\n",
|
||
" y = gp_cost_map(x)\n",
|
||
" except:\n",
|
||
" y = np.nan\n",
|
||
" print(y)\n",
|
||
" mask = np.isfinite(y).reshape(-1)\n",
|
||
" return {\n",
|
||
" OBJECTIVE: trieste.data.Dataset(x[mask], y[mask]),\n",
|
||
" FAILURE: trieste.data.Dataset(x, tf.cast(np.isfinite(y), tf.float64))\n",
|
||
" }"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 844,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "_WHmvaLbRwRd",
|
||
"outputId": "a92663ab-e4d7-4c50-9b5b-d7cf316e9578",
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor(\n",
|
||
"[[49.68307447]\n",
|
||
" [48.17950289]\n",
|
||
" [52.46541048]\n",
|
||
" [52.67746495]\n",
|
||
" [48.04459403]\n",
|
||
" [ nan]\n",
|
||
" [52.87997034]\n",
|
||
" [48.88740409]\n",
|
||
" [52.81439254]\n",
|
||
" [ nan]\n",
|
||
" [52.30934785]\n",
|
||
" [39.64154545]\n",
|
||
" [ nan]\n",
|
||
" [48.25223144]\n",
|
||
" [52.57604174]\n",
|
||
" [ nan]\n",
|
||
" [47.52992461]\n",
|
||
" [49.17097817]\n",
|
||
" [52.07901221]\n",
|
||
" [49.65099421]\n",
|
||
" [ nan]\n",
|
||
" [ nan]\n",
|
||
" [30.41374006]\n",
|
||
" [ nan]\n",
|
||
" [51.19509676]], shape=(25, 1), dtype=float64)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"initial_data = gp_observer(init_X)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 845,
|
||
"metadata": {
|
||
"id": "pj2PYA-gZD_Z"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def create_regression_model(data):\n",
|
||
" variance = tf.math.reduce_variance(data.observations)\n",
|
||
" kernel = gpflow.kernels.Matern52(variance=variance, lengthscales=[0.2]*2)\n",
|
||
" gpr = gpflow.models.GPR(data.astuple(), kernel, noise_variance=1e-5)\n",
|
||
" gpflow.set_trainable(gpr.likelihood, False)\n",
|
||
" return gpr\n",
|
||
"\n",
|
||
"\n",
|
||
"def create_classification_model(data):\n",
|
||
" kernel = gpflow.kernels.SquaredExponential(\n",
|
||
" variance=100.0, lengthscales=[0.2]*2\n",
|
||
" )\n",
|
||
" likelihood = gpflow.likelihoods.Bernoulli()\n",
|
||
" vgp = gpflow.models.VGP(data.astuple(), kernel, likelihood)\n",
|
||
" gpflow.set_trainable(vgp.kernel.variance, False)\n",
|
||
" return vgp\n",
|
||
"\n",
|
||
"\n",
|
||
"regression_model = create_regression_model(initial_data[OBJECTIVE])\n",
|
||
"classification_model = create_classification_model(initial_data[FAILURE])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 846,
|
||
"metadata": {
|
||
"id": "LFPOK1Yrbgmr"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"class NatGradTrainedVGP(trieste.models.VariationalGaussianProcess):\n",
|
||
" def optimize(self, dataset):\n",
|
||
" gpflow.set_trainable(self.model.q_mu, False)\n",
|
||
" gpflow.set_trainable(self.model.q_sqrt, False)\n",
|
||
" variational_params = [(self.model.q_mu, self.model.q_sqrt)]\n",
|
||
" adam_opt = tf.optimizers.Adam(1e-3)\n",
|
||
" natgrad_opt = gpflow.optimizers.NaturalGradient(gamma=0.1)\n",
|
||
"\n",
|
||
" for step in range(50):\n",
|
||
" loss = self.model.training_loss\n",
|
||
" natgrad_opt.minimize(loss, variational_params)\n",
|
||
" adam_opt.minimize(loss, self.model.trainable_variables)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 847,
|
||
"metadata": {
|
||
"id": "slD_7rh0b4T9"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from typing import Dict\n",
|
||
"\n",
|
||
"models: Dict[str, trieste.models.ModelSpec] = {\n",
|
||
" OBJECTIVE: {\n",
|
||
" \"model\": regression_model,\n",
|
||
" \"optimizer\": gpflow.optimizers.Scipy(),\n",
|
||
" \"optimizer_args\": {\n",
|
||
" \"minimize_args\": {\"options\": dict(maxiter=100)},\n",
|
||
" },\n",
|
||
" },\n",
|
||
" FAILURE: NatGradTrainedVGP(classification_model),\n",
|
||
"}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 848,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"class ProbabilityOfValidity(trieste.acquisition.SingleModelAcquisitionBuilder):\n",
|
||
" def prepare_acquisition_function(self, dataset, model):\n",
|
||
" return lambda at: trieste.acquisition.lower_confidence_bound(model, 0.0, at)\n",
|
||
"\n",
|
||
"ei = trieste.acquisition.ExpectedImprovement()\n",
|
||
"pov = ProbabilityOfValidity()\n",
|
||
"acq_fn = trieste.acquisition.Product(ei.using(OBJECTIVE), pov.using(FAILURE))\n",
|
||
"rule = trieste.acquisition.rule.EfficientGlobalOptimization(acq_fn)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 849,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"nb_optimization_steps = 50"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 850,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"bo = trieste.bayesian_optimizer.BayesianOptimizer(gp_observer, search_space)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 851,
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[48.49316661]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.73941858]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.53105]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.81369458]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.80402914]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[48.96366872]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[48.93070182]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.74872954]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[49.99420801]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.95142066]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.95569493]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[49.98487867]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.88252083]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.80064534]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.91044925]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.89272017]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.75757517]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[48.0571689]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[44.40234229]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[47.85692281]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[nan]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[50.32359746]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[52.74704816]], shape=(1, 1), dtype=float64)\n",
|
||
"Training a GP\n",
|
||
"tf.Tensor([[48.76249199]], shape=(1, 1), dtype=float64)\n",
|
||
"Optimization completed without errors\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"result = bo.optimize(nb_optimization_steps, initial_data, models, rule)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 852,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"query point: [5.40174621 5.07058858]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"result = result.final_result.unwrap()\n",
|
||
"\n",
|
||
"arg_min_idx = tf.squeeze(tf.argmin(result.datasets[OBJECTIVE].observations, axis=0))\n",
|
||
"print(f\"query point: {result.datasets[OBJECTIVE].query_points[arg_min_idx, :]}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 853,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"best_params = result.datasets[OBJECTIVE].query_points[arg_min_idx, :]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 854,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Training a GP\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"m_best = get_gp_from_hyperparams(best_params)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 855,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#m_best = m"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 83,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'.kernel.variance': <Parameter: dtype=float64, shape=[7], fn=\"softplus\", numpy=\n",
|
||
" array([1.88404972e-05, 2.35199453e-04, 4.70785497e-02, 2.67713883e-02,\n",
|
||
" 7.46741281e+00, 3.53745465e+00, 2.97911475e-02])>,\n",
|
||
" '.likelihood.variance': <Parameter: dtype=float64, shape=[], fn=\"chain_of_shift_of_softplus\", numpy=0.0011367938506279384>}"
|
||
]
|
||
},
|
||
"execution_count": 83,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"gpflow.utilities.parameter_dict(m_best)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 81,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1440x1440 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"nb_plts = len(dfs_train)\n",
|
||
"\n",
|
||
"plt.figure(figsize = (20, 20))\n",
|
||
"\n",
|
||
"for idx, df_iter in enumerate(dfs_gpr_train):\n",
|
||
" plt.subplot(nb_plts, 1, idx + 1)\n",
|
||
" df_input_iter = df_iter.drop(columns = dict_cols['y'][1] + dict_cols['u'][1])\n",
|
||
" df_output_iter = df_iter[dict_cols['y'][1]]\n",
|
||
" np_input_iter = df_input_iter.to_numpy()\n",
|
||
" np_output_iter = df_output_iter.to_numpy().reshape(-1, 1)\n",
|
||
" \n",
|
||
" mean, var = m_best.predict_f(np_input_iter)\n",
|
||
" \n",
|
||
" plt.plot(df_iter.index, np_output_iter[:, :], label = 'Measured data')\n",
|
||
" plt.plot(df_iter.index, mean[:, :], label = 'Gaussian Process Prediction')\n",
|
||
" plt.fill_between(\n",
|
||
" df_iter.index, \n",
|
||
" mean[:, 0] - 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" mean[:, 0] + 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" alpha = 0.2\n",
|
||
" )\n",
|
||
" plt.title(f\"Model Performance on training data: {train_exps[idx]}\")\n",
|
||
" plt.legend()\n",
|
||
"plt.savefig(f\"Performance_train_exps.png\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 82,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1440x1440 with 3 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"nb_plts = len(dfs_test)\n",
|
||
"\n",
|
||
"plt.figure(figsize = (20, 20))\n",
|
||
"\n",
|
||
"for idx, df_iter in enumerate(dfs_gpr_test):\n",
|
||
" plt.subplot(nb_plts, 1, idx + 1)\n",
|
||
" df_input_iter = df_iter.drop(columns = dict_cols['y'][1] + dict_cols['u'][1])\n",
|
||
" df_output_iter = df_iter[dict_cols['y'][1]]\n",
|
||
" np_input_iter = df_input_iter.to_numpy()\n",
|
||
" np_output_iter = df_output_iter.to_numpy().reshape(-1, 1)\n",
|
||
" \n",
|
||
" mean, var = m_best.predict_f(np_input_iter)\n",
|
||
" \n",
|
||
" plt.plot(df_iter.index, np_output_iter[:, :], label = 'Measured data')\n",
|
||
" plt.plot(df_iter.index, mean[:, :], label = 'Gaussian Process Prediction')\n",
|
||
" plt.fill_between(\n",
|
||
" df_iter.index, \n",
|
||
" mean[:, 0] - 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" mean[:, 0] + 1.96 * np.sqrt(var[:, 0]),\n",
|
||
" alpha = 0.2\n",
|
||
" )\n",
|
||
" plt.title(f\"Model Performance on test data: {test_exps[idx]}\")\n",
|
||
" plt.legend()\n",
|
||
"plt.savefig(f\"Performance_test_exps.png\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 825,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"21.182911210003116"
|
||
]
|
||
},
|
||
"execution_count": 825,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.log10(np.linalg.cond(m_best.kernel(np_input_train)))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 826,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<tf.Tensor: shape=(), dtype=float64, numpy=15.182775154614564>"
|
||
]
|
||
},
|
||
"execution_count": 826,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"m_obj_value(m_best)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 827,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
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"<style scoped>\n",
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||
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|
||
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|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>SolRad</th>\n",
|
||
" <th>OutsideTemp</th>\n",
|
||
" <th>SimulatedHeat_1</th>\n",
|
||
" <th>SimulatedHeat_2</th>\n",
|
||
" <th>SimulatedTemp_1</th>\n",
|
||
" <th>SimulatedTemp_2</th>\n",
|
||
" <th>SimulatedTemp_3</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>timestamp</th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 20:45:00+02:00</th>\n",
|
||
" <td>-0.970807</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
" <td>0.214339</td>\n",
|
||
" <td>0.153839</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:00:00+02:00</th>\n",
|
||
" <td>-0.980063</td>\n",
|
||
" <td>0.019608</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
|
||
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|
||
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|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:15:00+02:00</th>\n",
|
||
" <td>-0.989906</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>0.438090</td>\n",
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||
" <td>0.438090</td>\n",
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||
" <td>0.216876</td>\n",
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||
" <td>0.248081</td>\n",
|
||
" <td>0.233535</td>\n",
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||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:30:00+02:00</th>\n",
|
||
" <td>-0.991909</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.438090</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" <td>0.248081</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-06-01 21:45:00+02:00</th>\n",
|
||
" <td>-0.992483</td>\n",
|
||
" <td>-0.058824</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>-0.470064</td>\n",
|
||
" <td>0.091034</td>\n",
|
||
" <td>0.062767</td>\n",
|
||
" <td>0.216876</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-07-10 04:45:00+02:00</th>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>-0.411765</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.090031</td>\n",
|
||
" <td>0.077547</td>\n",
|
||
" <td>0.067484</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-07-10 05:00:00+02:00</th>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>-0.411765</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.098815</td>\n",
|
||
" <td>0.090031</td>\n",
|
||
" <td>0.077547</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-07-10 05:15:00+02:00</th>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>-0.411765</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.103469</td>\n",
|
||
" <td>0.098815</td>\n",
|
||
" <td>0.090031</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-07-10 05:30:00+02:00</th>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>-0.411765</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.107503</td>\n",
|
||
" <td>0.103469</td>\n",
|
||
" <td>0.098815</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-07-10 05:45:00+02:00</th>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>-0.411765</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.423283</td>\n",
|
||
" <td>0.107503</td>\n",
|
||
" <td>0.107503</td>\n",
|
||
" <td>0.103469</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>864 rows × 7 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" SolRad OutsideTemp SimulatedHeat_1 \\\n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 -0.970807 0.058824 0.438090 \n",
|
||
"2017-06-01 21:00:00+02:00 -0.980063 0.019608 0.438090 \n",
|
||
"2017-06-01 21:15:00+02:00 -0.989906 -0.058824 0.438090 \n",
|
||
"2017-06-01 21:30:00+02:00 -0.991909 -0.058824 -0.470064 \n",
|
||
"2017-06-01 21:45:00+02:00 -0.992483 -0.058824 -0.470064 \n",
|
||
"... ... ... ... \n",
|
||
"2017-07-10 04:45:00+02:00 -1.000000 -0.411765 0.423283 \n",
|
||
"2017-07-10 05:00:00+02:00 -1.000000 -0.411765 0.423283 \n",
|
||
"2017-07-10 05:15:00+02:00 -1.000000 -0.411765 0.423283 \n",
|
||
"2017-07-10 05:30:00+02:00 -1.000000 -0.411765 0.423283 \n",
|
||
"2017-07-10 05:45:00+02:00 -1.000000 -0.411765 0.423283 \n",
|
||
"\n",
|
||
" SimulatedHeat_2 SimulatedTemp_1 SimulatedTemp_2 \\\n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 0.438090 0.233535 0.214339 \n",
|
||
"2017-06-01 21:00:00+02:00 0.438090 0.248081 0.233535 \n",
|
||
"2017-06-01 21:15:00+02:00 0.438090 0.216876 0.248081 \n",
|
||
"2017-06-01 21:30:00+02:00 0.438090 0.062767 0.216876 \n",
|
||
"2017-06-01 21:45:00+02:00 -0.470064 0.091034 0.062767 \n",
|
||
"... ... ... ... \n",
|
||
"2017-07-10 04:45:00+02:00 0.423283 0.090031 0.077547 \n",
|
||
"2017-07-10 05:00:00+02:00 0.423283 0.098815 0.090031 \n",
|
||
"2017-07-10 05:15:00+02:00 0.423283 0.103469 0.098815 \n",
|
||
"2017-07-10 05:30:00+02:00 0.423283 0.107503 0.103469 \n",
|
||
"2017-07-10 05:45:00+02:00 0.423283 0.107503 0.107503 \n",
|
||
"\n",
|
||
" SimulatedTemp_3 \n",
|
||
"timestamp \n",
|
||
"2017-06-01 20:45:00+02:00 0.153839 \n",
|
||
"2017-06-01 21:00:00+02:00 0.214339 \n",
|
||
"2017-06-01 21:15:00+02:00 0.233535 \n",
|
||
"2017-06-01 21:30:00+02:00 0.248081 \n",
|
||
"2017-06-01 21:45:00+02:00 0.216876 \n",
|
||
"... ... \n",
|
||
"2017-07-10 04:45:00+02:00 0.067484 \n",
|
||
"2017-07-10 05:00:00+02:00 0.077547 \n",
|
||
"2017-07-10 05:15:00+02:00 0.090031 \n",
|
||
"2017-07-10 05:30:00+02:00 0.098815 \n",
|
||
"2017-07-10 05:45:00+02:00 0.103469 \n",
|
||
"\n",
|
||
"[864 rows x 7 columns]"
|
||
]
|
||
},
|
||
"execution_count": 827,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df_input_train"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Multistep prediction"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 72,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"df_input = dfs_gpr_train[0].drop(columns = dict_cols['u'][1] + dict_cols['y'][1])\n",
|
||
"df_output = dfs_gpr_train[0][dict_cols['y'][1]]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 73,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"start_idx = 25\n",
|
||
"nb_predictions = 10\n",
|
||
"N_pred = 8"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 74,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"[<matplotlib.lines.Line2D at 0x7ff53e879a90>]"
|
||
]
|
||
},
|
||
"execution_count": 74,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1080x432 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure()\n",
|
||
"plt.plot(df_output.iloc[start_idx:start_idx + nb_predictions + N_pred], 'o-', label = 'measured', color = 'darkblue')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 75,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
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|
||
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|
||
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|
||
" <th></th>\n",
|
||
" <th>SolRad</th>\n",
|
||
" <th>OutsideTemp</th>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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||
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||
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||
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||
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|
||
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|
||
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||
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||
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||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
" <tr>\n",
|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
" <th>2017-07-20 05:30:00+02:00</th>\n",
|
||
" <td>-0.993300</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.969031</td>\n",
|
||
" <td>0.969031</td>\n",
|
||
" <td>0.969031</td>\n",
|
||
" <td>0.709030</td>\n",
|
||
" <td>0.743645</td>\n",
|
||
" <td>0.729486</td>\n",
|
||
" <td>0.716151</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2017-07-20 05:45:00+02:00</th>\n",
|
||
" <td>-0.993092</td>\n",
|
||
" <td>0.058824</td>\n",
|
||
" <td>0.351363</td>\n",
|
||
" <td>0.969031</td>\n",
|
||
" <td>0.969031</td>\n",
|
||
" <td>0.574791</td>\n",
|
||
" <td>0.709030</td>\n",
|
||
" <td>0.743645</td>\n",
|
||
" <td>0.729486</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>613 rows × 9 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" SolRad OutsideTemp SimulatedHeat \\\n",
|
||
"timestamp \n",
|
||
"2017-07-13 20:45:00+02:00 -0.906144 0.294118 -0.906566 \n",
|
||
"2017-07-13 21:00:00+02:00 -0.971051 0.254902 -0.906566 \n",
|
||
"2017-07-13 21:15:00+02:00 -0.986502 0.176471 -0.906566 \n",
|
||
"2017-07-13 21:30:00+02:00 -0.990599 0.176471 -0.906566 \n",
|
||
"2017-07-13 21:45:00+02:00 -0.991623 0.176471 -0.906566 \n",
|
||
"... ... ... ... \n",
|
||
"2017-07-20 04:45:00+02:00 -0.993065 0.058824 0.969031 \n",
|
||
"2017-07-20 05:00:00+02:00 -0.993245 0.058824 0.969031 \n",
|
||
"2017-07-20 05:15:00+02:00 -0.993307 0.058824 0.969031 \n",
|
||
"2017-07-20 05:30:00+02:00 -0.993300 0.058824 0.969031 \n",
|
||
"2017-07-20 05:45:00+02:00 -0.993092 0.058824 0.351363 \n",
|
||
"\n",
|
||
" SimulatedHeat_1 SimulatedHeat_2 SimulatedTemp \\\n",
|
||
"timestamp \n",
|
||
"2017-07-13 20:45:00+02:00 -0.906566 -0.906566 -0.152825 \n",
|
||
"2017-07-13 21:00:00+02:00 -0.906566 -0.906566 -0.187286 \n",
|
||
"2017-07-13 21:15:00+02:00 -0.906566 -0.906566 -0.232325 \n",
|
||
"2017-07-13 21:30:00+02:00 -0.906566 -0.906566 -0.270313 \n",
|
||
"2017-07-13 21:45:00+02:00 -0.906566 -0.906566 -0.307765 \n",
|
||
"... ... ... ... \n",
|
||
"2017-07-20 04:45:00+02:00 0.969031 0.969031 0.716151 \n",
|
||
"2017-07-20 05:00:00+02:00 0.969031 0.969031 0.729486 \n",
|
||
"2017-07-20 05:15:00+02:00 0.969031 0.969031 0.743645 \n",
|
||
"2017-07-20 05:30:00+02:00 0.969031 0.969031 0.709030 \n",
|
||
"2017-07-20 05:45:00+02:00 0.969031 0.969031 0.574791 \n",
|
||
"\n",
|
||
" SimulatedTemp_1 SimulatedTemp_2 SimulatedTemp_3 \n",
|
||
"timestamp \n",
|
||
"2017-07-13 20:45:00+02:00 -0.120327 -0.078555 0.065348 \n",
|
||
"2017-07-13 21:00:00+02:00 -0.152825 -0.120327 -0.078555 \n",
|
||
"2017-07-13 21:15:00+02:00 -0.187286 -0.152825 -0.120327 \n",
|
||
"2017-07-13 21:30:00+02:00 -0.232325 -0.187286 -0.152825 \n",
|
||
"2017-07-13 21:45:00+02:00 -0.270313 -0.232325 -0.187286 \n",
|
||
"... ... ... ... \n",
|
||
"2017-07-20 04:45:00+02:00 0.716151 0.705869 0.685924 \n",
|
||
"2017-07-20 05:00:00+02:00 0.716151 0.716151 0.705869 \n",
|
||
"2017-07-20 05:15:00+02:00 0.729486 0.716151 0.716151 \n",
|
||
"2017-07-20 05:30:00+02:00 0.743645 0.729486 0.716151 \n",
|
||
"2017-07-20 05:45:00+02:00 0.709030 0.743645 0.729486 \n",
|
||
"\n",
|
||
"[613 rows x 9 columns]"
|
||
]
|
||
},
|
||
"execution_count": 75,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df_iter"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 76,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"m_best = m"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 77,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1080x432 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure()\n",
|
||
"\n",
|
||
"y_name = dict_cols['y'][1][0]\n",
|
||
"for idx in range(start_idx, start_idx + nb_predictions):\n",
|
||
" df_iter = df_input.iloc[idx:(idx + N_pred)].copy()\n",
|
||
" for idxx in range(N_pred - 1):\n",
|
||
" idx_old = df_iter.index[idxx]\n",
|
||
" idx_new = df_iter.index[idxx+1]\n",
|
||
" mean, var = m_best.predict_f(df_iter.loc[idx_old, :].to_numpy().reshape(1, -1))\n",
|
||
" df_iter.loc[idx_new, f'{y_name}_1'] = mean.numpy().flatten()\n",
|
||
" for lag in range(2, dict_cols['y'][0] + 1):\n",
|
||
" df_iter.loc[idx_new, f\"{y_name}_{lag}\"] = df_iter.loc[idx_old, f\"{y_name}_{lag-1}\"]\n",
|
||
" \n",
|
||
" mean_iter, var_iter = m_best.predict_f(df_iter.to_numpy())\n",
|
||
" plt.plot(df_iter.index, mean_iter.numpy(), '.-', label = 'predicted', color = 'orange')\n",
|
||
"plt.plot(df_output.iloc[start_idx:start_idx + nb_predictions + N_pred], 'o-', label = 'measured', color = 'darkblue')\n",
|
||
"plt.title(f\"Prediction over {N_pred} steps\")\n",
|
||
"plt.savefig(f\"prediction_{N_pred}_steps.png\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 147,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<bound method InternalDataTrainingLossMixin.training_loss of <gpflow.models.gpr.GPR object at 0x7fe4481501c0>>"
|
||
]
|
||
},
|
||
"execution_count": 147,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"m.training_loss"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 152,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"tf_test = tf.Variable(np.ones((3, 3)))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 296,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2.79 s ± 76.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%%timeit\n",
|
||
"df_iter = df_input.iloc[idx:(idx + N_pred)].copy()\n",
|
||
"for idxx in range(N_pred - 1):\n",
|
||
" idx_old = df_iter.index[idxx]\n",
|
||
" idx_new = df_iter.index[idxx+1]\n",
|
||
" mean, var = m_best.predict_f(df_iter.loc[idx_old, :].to_numpy().reshape(1, -1))\n",
|
||
" df_iter.loc[idx_new, f'{y_name}_1'] = mean.numpy().flatten()\n",
|
||
" for lag in range(2, dict_cols['y'][0] + 1):\n",
|
||
" df_iter.loc[idx_new, f\"{y_name}_{lag}\"] = df_iter.loc[idx_old, f\"{y_name}_{lag-1}\"]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 407,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"N_pred = 15"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"data_in = df_input.iloc[idx:(idx + N_pred)].copy()\n",
|
||
"data_out = df_output.iloc[idx:(idx + N_pred)].copy()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 416,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"ylag1_idx = df_iter.columns.to_list().index(f\"{dict_cols['y'][1][0]}_1\")\n",
|
||
"ylags = dict_cols['y'][0]\n",
|
||
"tf_input = tf.Variable(data_in)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 417,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"@tf.function\n",
|
||
"def multistep_prediction(tf_input):\n",
|
||
" N_pred = tf_input.shape[0]\n",
|
||
" for idxx in range(N_pred - 1):\n",
|
||
" mean,_ = m.predict_f(tf.reshape(tf_input[idxx, :], (1, -1)))\n",
|
||
" tf_input[idxx+1, ylag1_idx].assign(mean[0,0])\n",
|
||
" tf_input[idxx + 1, ylag1_idx + 1 : ylag1_idx + ylags].assign(tf_input[idxx, ylag1_idx : ylag1_idx + ylags - 1])\n",
|
||
" mean, _ = m.predict_f(tf_input)\n",
|
||
" return mean"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 418,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"WARNING:tensorflow:AutoGraph could not transform <function multistep_prediction at 0x7fe3f6ae6b80> and will run it as-is.\n",
|
||
"Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n",
|
||
"Cause: invalid syntax (tmpusoeex0r.py, line 20)\n",
|
||
"To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n",
|
||
"WARNING: AutoGraph could not transform <function multistep_prediction at 0x7fe3f6ae6b80> and will run it as-is.\n",
|
||
"Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n",
|
||
"Cause: invalid syntax (tmpusoeex0r.py, line 20)\n",
|
||
"To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"model_out = multistep_prediction(tf.Variable(data_in))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 419,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"#@tf.function\n",
|
||
"def multistep_error(data):\n",
|
||
" tf_input = data[0]\n",
|
||
" tf_targets = data[1]\n",
|
||
" tf_outputs = multistep_prediction(tf_input)\n",
|
||
" err = tf.sqrt(tf.reduce_mean((tf_targets - tf_outputs)**2))\n",
|
||
" return err"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"data = (tf.Variable(data_in), tf.Variable(data_out))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 428,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"26.4 s ± 3.3 s per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%%timeit\n",
|
||
"for idx in range(50):\n",
|
||
" multistep_error(data)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 423,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.legend.Legend at 0x7fe3f5008460>"
|
||
]
|
||
},
|
||
"execution_count": 423,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
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\n",
|
||
"text/plain": [
|
||
"<Figure size 1080x432 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure()\n",
|
||
"plt.plot(data_out.to_numpy(), label = 'measured')\n",
|
||
"plt.plot(model_out, label = 'gp_prediction')\n",
|
||
"plt.legend()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 440,
|
||
"metadata": {
|
||
"scrolled": true,
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"ename": "InvalidArgumentError",
|
||
"evalue": " Input matrix is not invertible.\n\t [[node gradient_tape/triangular_solve/MatrixTriangularSolve (defined at /usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py:173) ]] [Op:__inference__tf_eval_1886136]\n\nErrors may have originated from an input operation.\nInput Source operations connected to node gradient_tape/triangular_solve/MatrixTriangularSolve:\n Cholesky (defined at /usr/lib/python3.9/site-packages/gpflow/models/gpr.py:87)\n\nFunction call stack:\n_tf_eval\n",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mInvalidArgumentError\u001b[0m Traceback (most recent call last)",
|
||
"\u001b[0;32m<ipython-input-440-4a0499d0427b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0mopt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgpflow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimizers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mScipy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m \u001b[0mopt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mminimize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrainable_variables\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py\u001b[0m in \u001b[0;36mminimize\u001b[0;34m(self, closure, variables, method, step_callback, compile, **scipy_kwargs)\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0mscipy_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallback\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 90\u001b[0;31m return scipy.optimize.minimize(\n\u001b[0m\u001b[1;32m 91\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minitial_params\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mjac\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mscipy_kwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 92\u001b[0m )\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_minimize.py\u001b[0m in \u001b[0;36mminimize\u001b[0;34m(fun, x0, args, method, jac, hess, hessp, bounds, constraints, tol, callback, options)\u001b[0m\n\u001b[1;32m 617\u001b[0m **options)\n\u001b[1;32m 618\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mmeth\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'l-bfgs-b'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 619\u001b[0;31m return _minimize_lbfgsb(fun, x0, args, jac, bounds,\n\u001b[0m\u001b[1;32m 620\u001b[0m callback=callback, **options)\n\u001b[1;32m 621\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mmeth\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'tnc'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/lbfgsb.py\u001b[0m in \u001b[0;36m_minimize_lbfgsb\u001b[0;34m(fun, x0, args, jac, bounds, disp, maxcor, ftol, gtol, eps, maxfun, maxiter, iprint, callback, maxls, finite_diff_rel_step, **unknown_options)\u001b[0m\n\u001b[1;32m 358\u001b[0m \u001b[0;31m# until the completion of the current minimization iteration.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 359\u001b[0m \u001b[0;31m# Overwrite f and g:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 360\u001b[0;31m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc_and_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 361\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mtask_str\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstartswith\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mb'NEW_X'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 362\u001b[0m \u001b[0;31m# new iteration\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36mfun_and_grad\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 258\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray_equal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 259\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_x_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 260\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 261\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 262\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36m_update_fun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 224\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_update_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 225\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_updated\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 226\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 227\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_updated\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 228\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36mupdate_fun\u001b[0;34m()\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mupdate_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfun_wrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun_impl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mupdate_fun\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36mfun_wrapped\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfun_wrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnfev\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 130\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mupdate_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/optimize.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, x, *args)\u001b[0m\n\u001b[1;32m 72\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 73\u001b[0m \u001b[0;34m\"\"\" returns the the function value \"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 74\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compute_if_needed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 75\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_value\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/optimize.py\u001b[0m in \u001b[0;36m_compute_if_needed\u001b[0;34m(self, x, *args)\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_value\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjac\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 67\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 68\u001b[0;31m \u001b[0mfg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 69\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjac\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfg\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfg\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py\u001b[0m in \u001b[0;36m_eval\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 112\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_eval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mTuple\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 113\u001b[0;31m \u001b[0mloss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrad\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_tf_eval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_to_tensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 114\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloat64\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrad\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloat64\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m 826\u001b[0m \u001b[0mtracing_count\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperimental_get_tracing_count\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 827\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtrace\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTrace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_name\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mtm\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 828\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 829\u001b[0m \u001b[0mcompiler\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"xla\"\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_experimental_compile\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;34m\"nonXla\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 830\u001b[0m \u001b[0mnew_tracing_count\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperimental_get_tracing_count\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py\u001b[0m in \u001b[0;36m_call\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m 860\u001b[0m \u001b[0;31m# In this case we have not created variables on the first call. So we can\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 861\u001b[0m \u001b[0;31m# run the first trace but we should fail if variables are created.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 862\u001b[0;31m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_stateful_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 863\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_created_variables\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 864\u001b[0m raise ValueError(\"Creating variables on a non-first call to a function\"\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 2940\u001b[0m (graph_function,\n\u001b[1;32m 2941\u001b[0m filtered_flat_args) = self._maybe_define_function(args, kwargs)\n\u001b[0;32m-> 2942\u001b[0;31m return graph_function._call_flat(\n\u001b[0m\u001b[1;32m 2943\u001b[0m filtered_flat_args, captured_inputs=graph_function.captured_inputs) # pylint: disable=protected-access\n\u001b[1;32m 2944\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36m_call_flat\u001b[0;34m(self, args, captured_inputs, cancellation_manager)\u001b[0m\n\u001b[1;32m 1916\u001b[0m and executing_eagerly):\n\u001b[1;32m 1917\u001b[0m \u001b[0;31m# No tape is watching; skip to running the function.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1918\u001b[0;31m return self._build_call_outputs(self._inference_function.call(\n\u001b[0m\u001b[1;32m 1919\u001b[0m ctx, args, cancellation_manager=cancellation_manager))\n\u001b[1;32m 1920\u001b[0m forward_backward = self._select_forward_and_backward_functions(\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36mcall\u001b[0;34m(self, ctx, args, cancellation_manager)\u001b[0m\n\u001b[1;32m 553\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0m_InterpolateFunctionError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 554\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcancellation_manager\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 555\u001b[0;31m outputs = execute.execute(\n\u001b[0m\u001b[1;32m 556\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msignature\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 557\u001b[0m \u001b[0mnum_outputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_outputs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/execute.py\u001b[0m in \u001b[0;36mquick_execute\u001b[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[1;32m 57\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[0mctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mensure_initialized\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 59\u001b[0;31m tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,\n\u001b[0m\u001b[1;32m 60\u001b[0m inputs, attrs, num_outputs)\n\u001b[1;32m 61\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_NotOkStatusException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;31mInvalidArgumentError\u001b[0m: Input matrix is not invertible.\n\t [[node gradient_tape/triangular_solve/MatrixTriangularSolve (defined at /usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py:173) ]] [Op:__inference__tf_eval_1886136]\n\nErrors may have originated from an input operation.\nInput Source operations connected to node gradient_tape/triangular_solve/MatrixTriangularSolve:\n Cholesky (defined at /usr/lib/python3.9/site-packages/gpflow/models/gpr.py:87)\n\nFunction call stack:\n_tf_eval\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"rational_l = 1\n",
|
||
"squared_l = 1\n",
|
||
"\n",
|
||
"variance = 1\n",
|
||
"\n",
|
||
"k0 = gpflow.kernels.SquaredExponential(lengthscales = squared_l, active_dims = squared_dims, variance = variance)\n",
|
||
"k1 = gpflow.kernels.Constant(variance = variance)\n",
|
||
"k2 = gpflow.kernels.RationalQuadratic(lengthscales = rational_l, active_dims = rational_dims, variance = variance)\n",
|
||
"\n",
|
||
"k = (k0 + k1) * k2\n",
|
||
"\n",
|
||
"m = gpflow.models.GPR(\n",
|
||
"data = (np_input_train, np_output_train), \n",
|
||
"kernel = k, \n",
|
||
"mean_function = None\n",
|
||
")\n",
|
||
"\n",
|
||
"opt = gpflow.optimizers.Scipy()\n",
|
||
"\n",
|
||
"opt.minimize(m.training_loss, m.trainable_variables)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 567,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"class MultistepGP(gpflow.models.GPR):\n",
|
||
" \n",
|
||
" def __init__(self, data):\n",
|
||
" \n",
|
||
" rational_l = 1\n",
|
||
" squared_l = 1\n",
|
||
"\n",
|
||
" variance = 1\n",
|
||
"\n",
|
||
" k0 = gpflow.kernels.SquaredExponential(lengthscales = squared_l, active_dims = squared_dims, variance = variance)\n",
|
||
" k1 = gpflow.kernels.Constant(variance = variance)\n",
|
||
" k2 = gpflow.kernels.RationalQuadratic(lengthscales = rational_l, active_dims = rational_dims, variance = variance)\n",
|
||
"\n",
|
||
" k = (k0 + k1) * k2\n",
|
||
" \n",
|
||
" self.train_data = tf.Variable(data[0][:10]), tf.Variable(data[1][:10])\n",
|
||
"\n",
|
||
" \n",
|
||
" super().__init__(data = data, kernel = k, mean_function = None)\n",
|
||
"\n",
|
||
"\"\"\"\n",
|
||
" @tf.function\n",
|
||
" @tf.autograph.experimental.do_not_convert\n",
|
||
" def multistep_prediction(self, tf_input):\n",
|
||
" N_pred = tf_input.shape[0]\n",
|
||
" for idxx in range(N_pred - 1):\n",
|
||
" mean,_ = self.predict_f(tf.reshape(tf_input[idxx, :], (1, -1)))\n",
|
||
" tf_input[idxx+1, ylag1_idx].assign(mean[0,0])\n",
|
||
" tf_input[idxx + 1, ylag1_idx + 1 : ylag1_idx + ylags].assign(tf_input[idxx, ylag1_idx : ylag1_idx + ylags - 1])\n",
|
||
" mean, _ = self.predict_f(tf_input)\n",
|
||
" return mean\n",
|
||
" \n",
|
||
" @tf.function\n",
|
||
" @tf.autograph.experimental.do_not_convert\n",
|
||
" def multistep_error(self,data):\n",
|
||
" tf_inputs, tf_targets = data\n",
|
||
" tf_outputs = self.multistep_prediction(tf_inputs)\n",
|
||
" err = tf.sqrt(tf.reduce_mean((tf_targets - tf_outputs)**2))\n",
|
||
" return err\n",
|
||
" \n",
|
||
" def multistep_training_loss(self):\n",
|
||
" return self.multistep_error(self.train_data)\n",
|
||
"\"\"\"\n",
|
||
" "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 568,
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||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
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"text/html": [
|
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"<__main__.MultistepGP object at 0x7fe3e7e50400>\n",
|
||
"<table>\n",
|
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"<thead>\n",
|
||
"<tr><th>name </th><th>class </th><th>transform </th><th>prior </th><th>trainable </th><th>shape </th><th>dtype </th><th>value </th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>MultistepGP.train_data[0] </td><td>ResourceVariable</td><td> </td><td> </td><td>True </td><td>(10, 9)</td><td>float64</td><td>[[2.22613378e-03, -1.87413538e+00, -9.95142923e-01...</td></tr>\n",
|
||
"<tr><td>MultistepGP.train_data[1] </td><td>ResourceVariable</td><td> </td><td> </td><td>True </td><td>(10, 1)</td><td>float64</td><td>[[-4.72829156e-17... </td></tr>\n",
|
||
"<tr><td>MultistepGP.kernel.kernels[0].kernels[0].variance </td><td>Parameter </td><td>Softplus </td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.kernel.kernels[0].kernels[0].lengthscales</td><td>Parameter </td><td>Softplus </td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.kernel.kernels[0].kernels[1].variance </td><td>Parameter </td><td>Softplus </td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.kernel.kernels[1].variance </td><td>Parameter </td><td>Softplus </td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.kernel.kernels[1].lengthscales </td><td>Parameter </td><td>Softplus </td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.kernel.kernels[1].alpha </td><td>Parameter </td><td>Softplus </td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.likelihood.variance </td><td>Parameter </td><td>Softplus + Shift</td><td> </td><td>True </td><td>() </td><td>float64</td><td>1.0 </td></tr>\n",
|
||
"<tr><td>MultistepGP.data[0] </td><td>ResourceVariable</td><td> </td><td> </td><td>True </td><td>(15, 9)</td><td>float64</td><td>[[2.22613378e-03, -1.87413538e+00, -9.95142923e-01...</td></tr>\n",
|
||
"<tr><td>MultistepGP.data[1] </td><td>ResourceVariable</td><td> </td><td> </td><td>True </td><td>(15, 1)</td><td>float64</td><td>[[-4.72829156e-17... </td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table>"
|
||
],
|
||
"text/plain": [
|
||
"<__main__.MultistepGP object at 0x7fe3e7e50400>\n",
|
||
"name class transform prior trainable shape dtype value\n",
|
||
"----------------------------------------------------- ---------------- ---------------- ------- ----------- ------- ------- -----------------------------------------------------\n",
|
||
"MultistepGP.train_data[0] ResourceVariable True (10, 9) float64 [[2.22613378e-03, -1.87413538e+00, -9.95142923e-01...\n",
|
||
"MultistepGP.train_data[1] ResourceVariable True (10, 1) float64 [[-4.72829156e-17...\n",
|
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"MultistepGP.kernel.kernels[0].kernels[0].variance Parameter Softplus True () float64 1.0\n",
|
||
"MultistepGP.kernel.kernels[0].kernels[0].lengthscales Parameter Softplus True () float64 1.0\n",
|
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"MultistepGP.kernel.kernels[0].kernels[1].variance Parameter Softplus True () float64 1.0\n",
|
||
"MultistepGP.kernel.kernels[1].variance Parameter Softplus True () float64 1.0\n",
|
||
"MultistepGP.kernel.kernels[1].lengthscales Parameter Softplus True () float64 1.0\n",
|
||
"MultistepGP.kernel.kernels[1].alpha Parameter Softplus True () float64 1.0\n",
|
||
"MultistepGP.likelihood.variance Parameter Softplus + Shift True () float64 1.0\n",
|
||
"MultistepGP.data[0] ResourceVariable True (15, 9) float64 [[2.22613378e-03, -1.87413538e+00, -9.95142923e-01...\n",
|
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"MultistepGP.data[1] ResourceVariable True (15, 1) float64 [[-4.72829156e-17..."
|
||
]
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},
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||
"execution_count": 568,
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||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"test_gp = MultistepGP(data)\n",
|
||
"test_gp"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 571,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<bound method InternalDataTrainingLossMixin.training_loss of <__main__.MultistepGP object at 0x7fe3e7e50400>>"
|
||
]
|
||
},
|
||
"execution_count": 571,
|
||
"metadata": {},
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||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"test_gp.training_loss"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 572,
|
||
"metadata": {
|
||
"scrolled": true,
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"ename": "ValueError",
|
||
"evalue": "in user code:\n\n /usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py:107 _tf_eval *\n return loss, cls.pack_tensors(grads)\n /usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py:139 pack_tensors *\n flats = [tf.reshape(tensor, (-1,)) for tensor in tensors]\n /usr/lib/python3.9/site-packages/tensorflow/python/util/dispatch.py:201 wrapper **\n return target(*args, **kwargs)\n /usr/lib/python3.9/site-packages/tensorflow/python/ops/array_ops.py:195 reshape\n result = gen_array_ops.reshape(tensor, shape, name)\n /usr/lib/python3.9/site-packages/tensorflow/python/ops/gen_array_ops.py:8377 reshape\n _, _, _op, _outputs = _op_def_library._apply_op_helper(\n /usr/lib/python3.9/site-packages/tensorflow/python/framework/op_def_library.py:538 _apply_op_helper\n raise ValueError(\n\n ValueError: Tried to convert 'tensor' to a tensor and failed. Error: None values not supported.\n",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
||
"\u001b[0;32m<ipython-input-572-d93f3b788bd5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mopt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgpflow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimizers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mScipy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mopt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mminimize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_gp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtest_gp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrainable_variables\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py\u001b[0m in \u001b[0;36mminimize\u001b[0;34m(self, closure, variables, method, step_callback, compile, **scipy_kwargs)\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0mscipy_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallback\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 90\u001b[0;31m return scipy.optimize.minimize(\n\u001b[0m\u001b[1;32m 91\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minitial_params\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mjac\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mscipy_kwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 92\u001b[0m )\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_minimize.py\u001b[0m in \u001b[0;36mminimize\u001b[0;34m(fun, x0, args, method, jac, hess, hessp, bounds, constraints, tol, callback, options)\u001b[0m\n\u001b[1;32m 617\u001b[0m **options)\n\u001b[1;32m 618\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mmeth\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'l-bfgs-b'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 619\u001b[0;31m return _minimize_lbfgsb(fun, x0, args, jac, bounds,\n\u001b[0m\u001b[1;32m 620\u001b[0m callback=callback, **options)\n\u001b[1;32m 621\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mmeth\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'tnc'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/lbfgsb.py\u001b[0m in \u001b[0;36m_minimize_lbfgsb\u001b[0;34m(fun, x0, args, jac, bounds, disp, maxcor, ftol, gtol, eps, maxfun, maxiter, iprint, callback, maxls, finite_diff_rel_step, **unknown_options)\u001b[0m\n\u001b[1;32m 304\u001b[0m \u001b[0miprint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdisp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 305\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 306\u001b[0;31m sf = _prepare_scalar_function(fun, x0, jac=jac, args=args, epsilon=eps,\n\u001b[0m\u001b[1;32m 307\u001b[0m \u001b[0mbounds\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnew_bounds\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 308\u001b[0m finite_diff_rel_step=finite_diff_rel_step)\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/optimize.py\u001b[0m in \u001b[0;36m_prepare_scalar_function\u001b[0;34m(fun, x0, jac, args, bounds, epsilon, finite_diff_rel_step, hess)\u001b[0m\n\u001b[1;32m 259\u001b[0m \u001b[0;31m# ScalarFunction caches. Reuse of fun(x) during grad\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 260\u001b[0m \u001b[0;31m# calculation reduces overall function evaluations.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 261\u001b[0;31m sf = ScalarFunction(fun, x0, args, grad, hess,\n\u001b[0m\u001b[1;32m 262\u001b[0m finite_diff_rel_step, bounds, epsilon=epsilon)\n\u001b[1;32m 263\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, fun, x0, args, grad, hess, finite_diff_rel_step, finite_diff_bounds, epsilon)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun_impl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mupdate_fun\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 136\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 138\u001b[0m \u001b[0;31m# Gradient evaluation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36m_update_fun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 224\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_update_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 225\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_updated\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 226\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 227\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_updated\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 228\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/scipy/optimize/_differentiable_functions.py\u001b[0m in \u001b[0;36mupdate_fun\u001b[0;34m()\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mupdate_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfun_wrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_fun_impl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mupdate_fun\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
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|
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"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py\u001b[0m in \u001b[0;36m_call\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m 869\u001b[0m \u001b[0;31m# This is the first call of __call__, so we have to initialize.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 870\u001b[0m \u001b[0minitializers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 871\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_initialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0madd_initializers_to\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minitializers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 872\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 873\u001b[0m \u001b[0;31m# At this point we know that the initialization is complete (or less\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
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|
||
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|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36m_maybe_define_function\u001b[0;34m(self, args, kwargs)\u001b[0m\n\u001b[1;32m 3359\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3360\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_function_cache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmissed\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcall_context_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3361\u001b[0;31m \u001b[0mgraph_function\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_graph_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3362\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_function_cache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprimary\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcache_key\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3363\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36m_create_graph_function\u001b[0;34m(self, args, kwargs, override_flat_arg_shapes)\u001b[0m\n\u001b[1;32m 3194\u001b[0m \u001b[0marg_names\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbase_arg_names\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mmissing_arg_names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3195\u001b[0m graph_function = ConcreteFunction(\n\u001b[0;32m-> 3196\u001b[0;31m func_graph_module.func_graph_from_py_func(\n\u001b[0m\u001b[1;32m 3197\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3198\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_python_function\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/framework/func_graph.py\u001b[0m in \u001b[0;36mfunc_graph_from_py_func\u001b[0;34m(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)\u001b[0m\n\u001b[1;32m 988\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moriginal_func\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf_decorator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munwrap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpython_func\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 989\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 990\u001b[0;31m \u001b[0mfunc_outputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpython_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mfunc_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mfunc_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 991\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 992\u001b[0m \u001b[0;31m# invariant: `func_outputs` contains only Tensors, CompositeTensors,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py\u001b[0m in \u001b[0;36mwrapped_fn\u001b[0;34m(*args, **kwds)\u001b[0m\n\u001b[1;32m 632\u001b[0m \u001b[0mxla_context\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mExit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 633\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 634\u001b[0;31m \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mweak_wrapped_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__wrapped__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 635\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 636\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/lib/python3.9/site-packages/tensorflow/python/framework/func_graph.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 975\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# pylint:disable=broad-except\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 976\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"ag_error_metadata\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 977\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mag_error_metadata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 978\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 979\u001b[0m \u001b[0;32mraise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;31mValueError\u001b[0m: in user code:\n\n /usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py:107 _tf_eval *\n return loss, cls.pack_tensors(grads)\n /usr/lib/python3.9/site-packages/gpflow/optimizers/scipy.py:139 pack_tensors *\n flats = [tf.reshape(tensor, (-1,)) for tensor in tensors]\n /usr/lib/python3.9/site-packages/tensorflow/python/util/dispatch.py:201 wrapper **\n return target(*args, **kwargs)\n /usr/lib/python3.9/site-packages/tensorflow/python/ops/array_ops.py:195 reshape\n result = gen_array_ops.reshape(tensor, shape, name)\n /usr/lib/python3.9/site-packages/tensorflow/python/ops/gen_array_ops.py:8377 reshape\n _, _, _op, _outputs = _op_def_library._apply_op_helper(\n /usr/lib/python3.9/site-packages/tensorflow/python/framework/op_def_library.py:538 _apply_op_helper\n raise ValueError(\n\n ValueError: Tried to convert 'tensor' to a tensor and failed. Error: None values not supported.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"opt = gpflow.optimizers.Scipy()\n",
|
||
"\n",
|
||
"opt.minimize(test_gp.training_loss, test_gp.trainable_variables)"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"accelerator": "GPU",
|
||
"colab": {
|
||
"name": "Untitled3.ipynb",
|
||
"provenance": []
|
||
},
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"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": "3.9.4"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 4
|
||
}
|